diff --git a/.github/DISCUSSION_TEMPLATE/q-a.yml b/.github/DISCUSSION_TEMPLATE/q-a.yml index d0229b2d7bd10..af6688cde1705 100644 --- a/.github/DISCUSSION_TEMPLATE/q-a.yml +++ b/.github/DISCUSSION_TEMPLATE/q-a.yml @@ -22,7 +22,7 @@ body: if there's another way to solve your problem: [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction), - [API Reference](https://api.python.langchain.com/en/stable/), + [API Reference](https://python.langchain.com/api_reference/), [GitHub search](https://github.com/langchain-ai/langchain), [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions), [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue), diff --git a/.github/ISSUE_TEMPLATE/bug-report.yml b/.github/ISSUE_TEMPLATE/bug-report.yml index 4fe94a53c8fd7..f1276df4de6c7 100644 --- a/.github/ISSUE_TEMPLATE/bug-report.yml +++ b/.github/ISSUE_TEMPLATE/bug-report.yml @@ -16,7 +16,7 @@ body: if there's another way to solve your problem: [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction), - [API Reference](https://api.python.langchain.com/en/stable/), + [API Reference](https://python.langchain.com/api_reference/), [GitHub search](https://github.com/langchain-ai/langchain), [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions), [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue), diff --git a/.github/ISSUE_TEMPLATE/documentation.yml b/.github/ISSUE_TEMPLATE/documentation.yml index 0b4bd4bd7d288..a931cef1d2952 100644 --- a/.github/ISSUE_TEMPLATE/documentation.yml +++ b/.github/ISSUE_TEMPLATE/documentation.yml @@ -21,7 +21,7 @@ body: place to ask your question: [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction), - [API Reference](https://api.python.langchain.com/en/stable/), + [API Reference](https://python.langchain.com/api_reference/), [GitHub search](https://github.com/langchain-ai/langchain), [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions), [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue), diff --git a/.github/scripts/check_diff.py b/.github/scripts/check_diff.py index bc5670e499322..a85f05dc613f8 100644 --- a/.github/scripts/check_diff.py +++ b/.github/scripts/check_diff.py @@ -32,18 +32,8 @@ "huggingface", ] -# Cap python version at 3.12 for some packages with dependencies that are not yet -# compatible with python 3.13 (mostly hf tokenizers). PY_312_MAX_PACKAGES = [ - f"libs/partners/{integration}" - for integration in [ - "chroma", - "couchbase", - "huggingface", - "mistralai", - "nomic", - "qdrant", - ] + "libs/partners/huggingface", # https://github.com/pytorch/pytorch/issues/130249 ] @@ -134,10 +124,11 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]: elif dir_ in PY_312_MAX_PACKAGES: py_versions = ["3.9", "3.12"] - elif dir_ in ["libs/community", "libs/langchain"] and job == "extended-tests": - # community extended test resolution in 3.12 is slow - # even in uv - py_versions = ["3.9", "3.11"] + elif dir_ == "libs/langchain" and job == "extended-tests": + py_versions = ["3.9", "3.13"] + + elif dir_ == "libs/community" and job == "extended-tests": + py_versions = ["3.9", "3.12"] elif dir_ == "libs/community" and job == "compile-integration-tests": # community integration deps are slow in 3.12 @@ -281,6 +272,9 @@ def _get_configs_for_multi_dirs( # TODO: update to include all packages that rely on standard-tests (all partner packages) # note: won't run on external repo partners dirs_to_run["lint"].add("libs/standard-tests") + dirs_to_run["test"].add("libs/standard-tests") + dirs_to_run["lint"].add("libs/cli") + dirs_to_run["test"].add("libs/cli") dirs_to_run["test"].add("libs/partners/mistralai") dirs_to_run["test"].add("libs/partners/openai") dirs_to_run["test"].add("libs/partners/anthropic") @@ -288,8 +282,9 @@ def _get_configs_for_multi_dirs( dirs_to_run["test"].add("libs/partners/groq") elif file.startswith("libs/cli"): - # todo: add cli makefile - pass + dirs_to_run["lint"].add("libs/cli") + dirs_to_run["test"].add("libs/cli") + elif file.startswith("libs/partners"): partner_dir = file.split("/")[2] if os.path.isdir(f"libs/partners/{partner_dir}") and [ diff --git a/.github/workflows/_compile_integration_test.yml b/.github/workflows/_compile_integration_test.yml index 4d2d772c8565b..ea4d4625930b9 100644 --- a/.github/workflows/_compile_integration_test.yml +++ b/.github/workflows/_compile_integration_test.yml @@ -13,7 +13,7 @@ on: description: "Python version to use" env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: @@ -21,6 +21,7 @@ jobs: run: working-directory: ${{ inputs.working-directory }} runs-on: ubuntu-latest + timeout-minutes: 20 name: "poetry run pytest -m compile tests/integration_tests #${{ inputs.python-version }}" steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/_integration_test.yml b/.github/workflows/_integration_test.yml index 7f9ea8ddf57c6..798ea62b44ee0 100644 --- a/.github/workflows/_integration_test.yml +++ b/.github/workflows/_integration_test.yml @@ -12,7 +12,7 @@ on: description: "Python version to use" env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: diff --git a/.github/workflows/_lint.yml b/.github/workflows/_lint.yml index 057959d5fccaa..993fd41821132 100644 --- a/.github/workflows/_lint.yml +++ b/.github/workflows/_lint.yml @@ -13,7 +13,7 @@ on: description: "Python version to use" env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }} # This env var allows us to get inline annotations when ruff has complaints. @@ -23,6 +23,7 @@ jobs: build: name: "make lint #${{ inputs.python-version }}" runs-on: ubuntu-latest + timeout-minutes: 20 steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/_release.yml b/.github/workflows/_release.yml index bf0c1e0454f20..e54bcb360f403 100644 --- a/.github/workflows/_release.yml +++ b/.github/workflows/_release.yml @@ -21,7 +21,7 @@ on: env: PYTHON_VERSION: "3.11" - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: @@ -167,6 +167,7 @@ jobs: - release-notes - test-pypi-publish runs-on: ubuntu-latest + timeout-minutes: 20 steps: - uses: actions/checkout@v4 @@ -191,7 +192,12 @@ jobs: poetry-version: ${{ env.POETRY_VERSION }} working-directory: ${{ inputs.working-directory }} - - name: Import published package + - uses: actions/download-artifact@v4 + with: + name: dist + path: ${{ inputs.working-directory }}/dist/ + + - name: Import dist package shell: bash working-directory: ${{ inputs.working-directory }} env: @@ -207,15 +213,7 @@ jobs: # - attempt install again after 5 seconds if it fails because there is # sometimes a delay in availability on test pypi run: | - poetry run pip install \ - --extra-index-url https://test.pypi.org/simple/ \ - "$PKG_NAME==$VERSION" || \ - ( \ - sleep 15 && \ - poetry run pip install \ - --extra-index-url https://test.pypi.org/simple/ \ - "$PKG_NAME==$VERSION" \ - ) + poetry run pip install dist/*.whl # Replace all dashes in the package name with underscores, # since that's how Python imports packages with dashes in the name. @@ -224,10 +222,10 @@ jobs: poetry run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))" - name: Import test dependencies - run: poetry install --with test + run: poetry install --with test --no-root working-directory: ${{ inputs.working-directory }} - # Overwrite the local version of the package with the test PyPI version. + # Overwrite the local version of the package with the built version - name: Import published package (again) working-directory: ${{ inputs.working-directory }} shell: bash @@ -235,9 +233,7 @@ jobs: PKG_NAME: ${{ needs.build.outputs.pkg-name }} VERSION: ${{ needs.build.outputs.version }} run: | - poetry run pip install \ - --extra-index-url https://test.pypi.org/simple/ \ - "$PKG_NAME==$VERSION" + poetry run pip install dist/*.whl - name: Run unit tests run: make tests diff --git a/.github/workflows/_test.yml b/.github/workflows/_test.yml index 0e03bbb16aece..4316fc407e520 100644 --- a/.github/workflows/_test.yml +++ b/.github/workflows/_test.yml @@ -13,7 +13,7 @@ on: description: "Python version to use" env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: @@ -21,6 +21,7 @@ jobs: run: working-directory: ${{ inputs.working-directory }} runs-on: ubuntu-latest + timeout-minutes: 20 name: "make test #${{ inputs.python-version }}" steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/_test_doc_imports.yml b/.github/workflows/_test_doc_imports.yml index 1b1db0d84c251..1c7c5d13d9617 100644 --- a/.github/workflows/_test_doc_imports.yml +++ b/.github/workflows/_test_doc_imports.yml @@ -9,11 +9,12 @@ on: description: "Python version to use" env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: runs-on: ubuntu-latest + timeout-minutes: 20 name: "check doc imports #${{ inputs.python-version }}" steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/_test_pydantic.yml b/.github/workflows/_test_pydantic.yml index ee48f46500b96..50831fd8f1274 100644 --- a/.github/workflows/_test_pydantic.yml +++ b/.github/workflows/_test_pydantic.yml @@ -18,7 +18,7 @@ on: description: "Pydantic version to test." env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: @@ -26,6 +26,7 @@ jobs: run: working-directory: ${{ inputs.working-directory }} runs-on: ubuntu-latest + timeout-minutes: 20 name: "make test # pydantic: ~=${{ inputs.pydantic-version }}, python: ${{ inputs.python-version }}, " steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/_test_release.yml b/.github/workflows/_test_release.yml index c7ba3c0f40eee..5d70d3974e22d 100644 --- a/.github/workflows/_test_release.yml +++ b/.github/workflows/_test_release.yml @@ -14,7 +14,7 @@ on: description: "Release from a non-master branch (danger!)" env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" PYTHON_VERSION: "3.10" jobs: diff --git a/.github/workflows/api_doc_build.yml b/.github/workflows/api_doc_build.yml index 959f35a94bd37..28ad2d742367a 100644 --- a/.github/workflows/api_doc_build.yml +++ b/.github/workflows/api_doc_build.yml @@ -5,7 +5,7 @@ on: schedule: - cron: '0 13 * * *' env: - POETRY_VERSION: "1.8.1" + POETRY_VERSION: "1.8.4" PYTHON_VERSION: "3.11" jobs: @@ -73,7 +73,7 @@ jobs: working-directory: langchain run: | python -m uv pip install $(ls ./libs/partners | xargs -I {} echo "./libs/partners/{}") - python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental + python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental libs/standard-tests python -m uv pip install -r docs/api_reference/requirements.txt - name: Set Git config diff --git a/.github/workflows/check_diffs.yml b/.github/workflows/check_diffs.yml index 5caa9c9348b12..61c921c03b9e4 100644 --- a/.github/workflows/check_diffs.yml +++ b/.github/workflows/check_diffs.yml @@ -17,7 +17,7 @@ concurrency: cancel-in-progress: true env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: @@ -119,6 +119,7 @@ jobs: job-configs: ${{ fromJson(needs.build.outputs.extended-tests) }} fail-fast: false runs-on: ubuntu-latest + timeout-minutes: 20 defaults: run: working-directory: ${{ matrix.job-configs.working-directory }} diff --git a/.github/workflows/run_notebooks.yml b/.github/workflows/run_notebooks.yml index 5d80c0917fef0..4f4fc703b3854 100644 --- a/.github/workflows/run_notebooks.yml +++ b/.github/workflows/run_notebooks.yml @@ -15,7 +15,7 @@ on: - cron: '0 13 * * *' env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" jobs: build: diff --git a/.github/workflows/scheduled_test.yml b/.github/workflows/scheduled_test.yml index 6a4767988bf2a..bcf489e52b107 100644 --- a/.github/workflows/scheduled_test.yml +++ b/.github/workflows/scheduled_test.yml @@ -2,32 +2,60 @@ name: Scheduled tests on: workflow_dispatch: # Allows to trigger the workflow manually in GitHub UI + inputs: + working-directory-force: + type: string + description: "From which folder this pipeline executes - defaults to all in matrix - example value: libs/partners/anthropic" + python-version-force: + type: string + description: "Python version to use - defaults to 3.9 and 3.11 in matrix - example value: 3.9" schedule: - cron: '0 13 * * *' env: - POETRY_VERSION: "1.7.1" + POETRY_VERSION: "1.8.4" + DEFAULT_LIBS: '["libs/partners/openai", "libs/partners/anthropic", "libs/partners/fireworks", "libs/partners/groq", "libs/partners/mistralai", "libs/partners/google-vertexai", "libs/partners/google-genai", "libs/partners/aws"]' jobs: + compute-matrix: + if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule' + runs-on: ubuntu-latest + name: Compute matrix + outputs: + matrix: ${{ steps.set-matrix.outputs.matrix }} + steps: + - name: Set matrix + id: set-matrix + env: + DEFAULT_LIBS: ${{ env.DEFAULT_LIBS }} + WORKING_DIRECTORY_FORCE: ${{ github.event.inputs.working-directory-force || '' }} + PYTHON_VERSION_FORCE: ${{ github.event.inputs.python-version-force || '' }} + run: | + # echo "matrix=..." where matrix is a json formatted str with keys python-version and working-directory + # python-version should default to 3.9 and 3.11, but is overridden to [PYTHON_VERSION_FORCE] if set + # working-directory should default to DEFAULT_LIBS, but is overridden to [WORKING_DIRECTORY_FORCE] if set + python_version='["3.9", "3.11"]' + working_directory="$DEFAULT_LIBS" + if [ -n "$PYTHON_VERSION_FORCE" ]; then + python_version="[\"$PYTHON_VERSION_FORCE\"]" + fi + if [ -n "$WORKING_DIRECTORY_FORCE" ]; then + working_directory="[\"$WORKING_DIRECTORY_FORCE\"]" + fi + matrix="{\"python-version\": $python_version, \"working-directory\": $working_directory}" + echo $matrix + echo "matrix=$matrix" >> $GITHUB_OUTPUT build: if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule' name: Python ${{ matrix.python-version }} - ${{ matrix.working-directory }} runs-on: ubuntu-latest + needs: [compute-matrix] + timeout-minutes: 20 strategy: fail-fast: false matrix: - python-version: - - "3.9" - - "3.11" - working-directory: - - "libs/partners/openai" - - "libs/partners/anthropic" - - "libs/partners/fireworks" - - "libs/partners/groq" - - "libs/partners/mistralai" - - "libs/partners/google-vertexai" - - "libs/partners/google-genai" - - "libs/partners/aws" + python-version: ${{ fromJSON(needs.compute-matrix.outputs.matrix).python-version }} + working-directory: ${{ fromJSON(needs.compute-matrix.outputs.matrix).working-directory }} steps: - uses: actions/checkout@v4 diff --git a/Makefile b/Makefile index 5b684c94ac9a7..05fd5b5cfea66 100644 --- a/Makefile +++ b/Makefile @@ -69,7 +69,11 @@ lint lint_package lint_tests: poetry run ruff check docs cookbook poetry run ruff format docs cookbook cookbook --diff poetry run ruff check --select I docs cookbook - git grep 'from langchain import' docs/docs cookbook | grep -vE 'from langchain import (hub)' && exit 1 || exit 0 + git --no-pager grep 'from langchain import' docs cookbook | grep -vE 'from langchain import (hub)' && echo "Error: no importing langchain from root in docs, except for hub" && exit 1 || exit 0 + + git --no-pager grep 'api.python.langchain.com' -- docs/docs ':!docs/docs/additional_resources/arxiv_references.mdx' ':!docs/docs/integrations/document_loaders/sitemap.ipynb' || exit 0 && \ + echo "Error: you should link python.langchain.com/api_reference, not api.python.langchain.com in the docs" && \ + exit 1 ## format: Format the project files. format format_diff: diff --git a/README.md b/README.md index f3e64b60cdb7f..dd8643d4b0a40 100644 --- a/README.md +++ b/README.md @@ -38,18 +38,21 @@ conda install langchain -c conda-forge For these applications, LangChain simplifies the entire application lifecycle: -- **Open-source libraries**: Build your applications using LangChain's open-source [building blocks](https://python.langchain.com/docs/concepts/#langchain-expression-language-lcel), [components](https://python.langchain.com/docs/concepts/), and [third-party integrations](https://python.langchain.com/docs/integrations/providers/). + +- **Open-source libraries**: Build your applications using LangChain's open-source +[components](https://python.langchain.com/docs/concepts/) and +[third-party integrations](https://python.langchain.com/docs/integrations/providers/). Use [LangGraph](https://langchain-ai.github.io/langgraph/) to build stateful agents with first-class streaming and human-in-the-loop support. - **Productionization**: Inspect, monitor, and evaluate your apps with [LangSmith](https://docs.smith.langchain.com/) so that you can constantly optimize and deploy with confidence. -- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/). +- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/). ### Open-source libraries -- **`langchain-core`**: Base abstractions and LangChain Expression Language. -- **`langchain-community`**: Third party integrations. - - Some integrations have been further split into **partner packages** that only rely on **`langchain-core`**. Examples include **`langchain_openai`** and **`langchain_anthropic`**. +- **`langchain-core`**: Base abstractions. +- **Integration packages** (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers. - **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. -- **[`LangGraph`](https://langchain-ai.github.io/langgraph/)**: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph). +- **`langchain-community`**: Third-party integrations that are community maintained. +- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph). ### Productionization: @@ -57,7 +60,7 @@ For these applications, LangChain simplifies the entire application lifecycle: ### Deployment: -- **[LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/)**: Turn your LangGraph applications into production-ready APIs and Assistants. +- **[LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/)**: Turn your LangGraph applications into production-ready APIs and Assistants. ![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](docs/static/svg/langchain_stack_112024.svg#gh-light-mode-only "LangChain Architecture Overview") ![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](docs/static/svg/langchain_stack_112024_dark.svg#gh-dark-mode-only "LangChain Architecture Overview") @@ -85,19 +88,12 @@ And much more! Head to the [Tutorials](https://python.langchain.com/docs/tutoria The main value props of the LangChain libraries are: -1. **Components**: composable building blocks, tools and integrations for working with language models. Components are modular and easy-to-use, whether you are using the rest of the LangChain framework or not -2. **Off-the-shelf chains**: built-in assemblages of components for accomplishing higher-level tasks - -Off-the-shelf chains make it easy to get started. Components make it easy to customize existing chains and build new ones. - -## LangChain Expression Language (LCEL) - -LCEL is a key part of LangChain, allowing you to build and organize chains of processes in a straightforward, declarative manner. It was designed to support taking prototypes directly into production without needing to alter any code. This means you can use LCEL to set up everything from basic "prompt + LLM" setups to intricate, multi-step workflows. - -- **[Overview](https://python.langchain.com/docs/concepts/#langchain-expression-language-lcel)**: LCEL and its benefits -- **[Interface](https://python.langchain.com/docs/concepts/#runnable-interface)**: The standard Runnable interface for LCEL objects -- **[Primitives](https://python.langchain.com/docs/how_to/#langchain-expression-language-lcel)**: More on the primitives LCEL includes -- **[Cheatsheet](https://python.langchain.com/docs/how_to/lcel_cheatsheet/)**: Quick overview of the most common usage patterns +1. **Components**: composable building blocks, tools and integrations for working with language models. Components are modular and easy-to-use, whether you are using the rest of the LangChain framework or not. +2. **Easy orchestration with LangGraph**: [LangGraph](https://langchain-ai.github.io/langgraph/), +built on top of `langchain-core`, has built-in support for [messages](https://python.langchain.com/docs/concepts/messages/), [tools](https://python.langchain.com/docs/concepts/tools/), +and other LangChain abstractions. This makes it easy to combine components into +production-ready applications with persistence, streaming, and other key features. +Check out the LangChain [tutorials page](https://python.langchain.com/docs/tutorials/#orchestration) for examples. ## Components @@ -105,15 +101,19 @@ Components fall into the following **modules**: **📃 Model I/O** -This includes [prompt management](https://python.langchain.com/docs/concepts/#prompt-templates), [prompt optimization](https://python.langchain.com/docs/concepts/#example-selectors), a generic interface for [chat models](https://python.langchain.com/docs/concepts/#chat-models) and [LLMs](https://python.langchain.com/docs/concepts/#llms), and common utilities for working with [model outputs](https://python.langchain.com/docs/concepts/#output-parsers). +This includes [prompt management](https://python.langchain.com/docs/concepts/prompt_templates/) +and a generic interface for [chat models](https://python.langchain.com/docs/concepts/chat_models/), including a consistent interface for [tool-calling](https://python.langchain.com/docs/concepts/tool_calling/) and [structured output](https://python.langchain.com/docs/concepts/structured_outputs/) across model providers. **📚 Retrieval** -Retrieval Augmented Generation involves [loading data](https://python.langchain.com/docs/concepts/#document-loaders) from a variety of sources, [preparing it](https://python.langchain.com/docs/concepts/#text-splitters), then [searching over (a.k.a. retrieving from)](https://python.langchain.com/docs/concepts/#retrievers) it for use in the generation step. +Retrieval Augmented Generation involves [loading data](https://python.langchain.com/docs/concepts/document_loaders/) from a variety of sources, [preparing it](https://python.langchain.com/docs/concepts/text_splitters/), then [searching over (a.k.a. retrieving from)](https://python.langchain.com/docs/concepts/retrievers/) it for use in the generation step. **🤖 Agents** -Agents allow an LLM autonomy over how a task is accomplished. Agents make decisions about which Actions to take, then take that Action, observe the result, and repeat until the task is complete. LangChain provides a [standard interface for agents](https://python.langchain.com/docs/concepts/#agents), along with [LangGraph](https://github.com/langchain-ai/langgraph) for building custom agents. +Agents allow an LLM autonomy over how a task is accomplished. Agents make decisions about which Actions to take, then take that Action, observe the result, and repeat until the task is complete. [LangGraph](https://langchain-ai.github.io/langgraph/) makes it easy to use +LangChain components to build both [custom](https://langchain-ai.github.io/langgraph/tutorials/) +and [built-in](https://langchain-ai.github.io/langgraph/how-tos/create-react-agent/) +LLM agents. ## 📖 Documentation @@ -123,7 +123,7 @@ Please see [here](https://python.langchain.com) for full documentation, which in - [Tutorials](https://python.langchain.com/docs/tutorials/): If you're looking to build something specific or are more of a hands-on learner, check out our tutorials. This is the best place to get started. - [How-to guides](https://python.langchain.com/docs/how_to/): Answers to “How do I….?” type questions. These guides are goal-oriented and concrete; they're meant to help you complete a specific task. - [Conceptual guide](https://python.langchain.com/docs/concepts/): Conceptual explanations of the key parts of the framework. -- [API Reference](https://api.python.langchain.com): Thorough documentation of every class and method. +- [API Reference](https://python.langchain.com/api_reference/): Thorough documentation of every class and method. ## 🌐 Ecosystem diff --git a/SECURITY.md b/SECURITY.md index 50e0632582c68..15e44be0b4314 100644 --- a/SECURITY.md +++ b/SECURITY.md @@ -1,5 +1,30 @@ # Security Policy +LangChain has a large ecosystem of integrations with various external resources like local and remote file systems, APIs and databases. These integrations allow developers to create versatile applications that combine the power of LLMs with the ability to access, interact with and manipulate external resources. + +## Best practices + +When building such applications developers should remember to follow good security practices: + +* [**Limit Permissions**](https://en.wikipedia.org/wiki/Principle_of_least_privilege): Scope permissions specifically to the application's need. Granting broad or excessive permissions can introduce significant security vulnerabilities. To avoid such vulnerabilities, consider using read-only credentials, disallowing access to sensitive resources, using sandboxing techniques (such as running inside a container), specifying proxy configurations to control external requests, etc. as appropriate for your application. +* **Anticipate Potential Misuse**: Just as humans can err, so can Large Language Models (LLMs). Always assume that any system access or credentials may be used in any way allowed by the permissions they are assigned. For example, if a pair of database credentials allows deleting data, it’s safest to assume that any LLM able to use those credentials may in fact delete data. +* [**Defense in Depth**](https://en.wikipedia.org/wiki/Defense_in_depth_(computing)): No security technique is perfect. Fine-tuning and good chain design can reduce, but not eliminate, the odds that a Large Language Model (LLM) may make a mistake. It’s best to combine multiple layered security approaches rather than relying on any single layer of defense to ensure security. For example: use both read-only permissions and sandboxing to ensure that LLMs are only able to access data that is explicitly meant for them to use. + +Risks of not doing so include, but are not limited to: +* Data corruption or loss. +* Unauthorized access to confidential information. +* Compromised performance or availability of critical resources. + +Example scenarios with mitigation strategies: + +* A user may ask an agent with access to the file system to delete files that should not be deleted or read the content of files that contain sensitive information. To mitigate, limit the agent to only use a specific directory and only allow it to read or write files that are safe to read or write. Consider further sandboxing the agent by running it in a container. +* A user may ask an agent with write access to an external API to write malicious data to the API, or delete data from that API. To mitigate, give the agent read-only API keys, or limit it to only use endpoints that are already resistant to such misuse. +* A user may ask an agent with access to a database to drop a table or mutate the schema. To mitigate, scope the credentials to only the tables that the agent needs to access and consider issuing READ-ONLY credentials. + +If you're building applications that access external resources like file systems, APIs +or databases, consider speaking with your company's security team to determine how to best +design and secure your applications. + ## Reporting OSS Vulnerabilities LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide @@ -14,7 +39,7 @@ Before reporting a vulnerability, please review: 1) In-Scope Targets and Out-of-Scope Targets below. 2) The [langchain-ai/langchain](https://python.langchain.com/docs/contributing/repo_structure) monorepo structure. -3) LangChain [security guidelines](https://python.langchain.com/docs/security) to +3) The [Best practicies](#best-practices) above to understand what we consider to be a security vulnerability vs. developer responsibility. @@ -33,13 +58,13 @@ The following packages and repositories are eligible for bug bounties: All out of scope targets defined by huntr as well as: - **langchain-experimental**: This repository is for experimental code and is not - eligible for bug bounties, bug reports to it will be marked as interesting or waste of + eligible for bug bounties (see [package warning](https://pypi.org/project/langchain-experimental/)), bug reports to it will be marked as interesting or waste of time and published with no bounty attached. - **tools**: Tools in either langchain or langchain-community are not eligible for bug bounties. This includes the following directories - - langchain/tools - - langchain-community/tools - - Please review our [security guidelines](https://python.langchain.com/docs/security) + - libs/langchain/langchain/tools + - libs/community/langchain_community/tools + - Please review the [best practices](#best-practices) for more details, but generally tools interact with the real world. Developers are expected to understand the security implications of their code and are responsible for the security of their tools. @@ -47,7 +72,7 @@ All out of scope targets defined by huntr as well as: case basis, but likely will not be eligible for a bounty as the code is already documented with guidelines for developers that should be followed for making their application secure. -- Any LangSmith related repositories or APIs see below. +- Any LangSmith related repositories or APIs (see [Reporting LangSmith Vulnerabilities](#reporting-langsmith-vulnerabilities)). ## Reporting LangSmith Vulnerabilities diff --git a/cookbook/README.md b/cookbook/README.md index a5e33d9eb624c..cfb9ea8e73473 100644 --- a/cookbook/README.md +++ b/cookbook/README.md @@ -63,4 +63,5 @@ Notebook | Description [oracleai_demo.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/oracleai_demo.ipynb) | This guide outlines how to utilize Oracle AI Vector Search alongside Langchain for an end-to-end RAG pipeline, providing step-by-step examples. The process includes loading documents from various sources using OracleDocLoader, summarizing them either within or outside the database with OracleSummary, and generating embeddings similarly through OracleEmbeddings. It also covers chunking documents according to specific requirements using Advanced Oracle Capabilities from OracleTextSplitter, and finally, storing and indexing these documents in a Vector Store for querying with OracleVS. [rag-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/rag-locally-on-intel-cpu.ipynb) | Perform Retrieval-Augmented-Generation (RAG) on locally downloaded open-source models using langchain and open source tools and execute it on Intel Xeon CPU. We showed an example of how to apply RAG on Llama 2 model and enable it to answer the queries related to Intel Q1 2024 earnings release. [visual_RAG_vdms.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/visual_RAG_vdms.ipynb) | Performs Visual Retrieval-Augmented-Generation (RAG) using videos and scene descriptions generated by open source models. -[contextual_rag.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/contextual_rag.ipynb) | Performs contextual retrieval-augmented generation (RAG) prepending chunk-specific explanatory context to each chunk before embedding. \ No newline at end of file +[contextual_rag.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/contextual_rag.ipynb) | Performs contextual retrieval-augmented generation (RAG) prepending chunk-specific explanatory context to each chunk before embedding. +[rag-agents-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/local_rag_agents_intel_cpu.ipynb) | Build a RAG agent locally with open source models that routes questions through one of two paths to find answers. The agent generates answers based on documents retrieved from either the vector database or retrieved from web search. If the vector database lacks relevant information, the agent opts for web search. Open-source models for LLM and embeddings are used locally on an Intel Xeon CPU to execute this pipeline. \ No newline at end of file diff --git a/cookbook/local_rag_agents_intel_cpu.ipynb b/cookbook/local_rag_agents_intel_cpu.ipynb new file mode 100644 index 0000000000000..58bdeb2f633f5 --- /dev/null +++ b/cookbook/local_rag_agents_intel_cpu.ipynb @@ -0,0 +1,655 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "9e7a7c86", + "metadata": {}, + "source": [ + "### Custom RAG Agent Workflow with Open Source LLMs Running Locally on Intel CPU" + ] + }, + { + "cell_type": "markdown", + "id": "f309f56d-1db4-4e03-870e-a2a6f5ee4dc5", + "metadata": {}, + "source": [ + "Author - Pratool Bharti (pratool.bharti@intel.com)" + ] + }, + { + "cell_type": "markdown", + "id": "0af01c3c-c42a-4ba5-95fa-4b83fd77fe9d", + "metadata": {}, + "source": [ + "This notebook demonstrates a Retrieval-Augmented Generation (RAG) agent that routes questions through two paths to find answers. The agent generates answers based on documents retrieved from either the vector database or web search. If the vector database lacks relevant information, the agent opts for web search. Open-source models for LLM and embeddings are used locally on an Intel Xeon CPU to execute this pipeline." + ] + }, + { + "cell_type": "markdown", + "id": "8b50e68f", + "metadata": {}, + "source": [ + "
\n", + "
Flow chart for the Custom RAG Agent Workflow
\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "24f76969", + "metadata": {}, + "source": [ + "Install required libraries in a conda or venv environment" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "746ae008", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" + ] + } + ], + "source": [ + "!pip install --upgrade --quiet tiktoken scikit-learn gpt4all langchain langchain-community langchain-core langchain_nomic langchain_ollama langgraph " + ] + }, + { + "cell_type": "markdown", + "id": "399f7e2e", + "metadata": {}, + "source": [ + "In Linux systems, use following commands to install Ollama and download Llama 3.1 model locally.\n", + "```\n", + "curl -fsSL https://ollama.com/install.sh | sh\n", + "ollama run llama3.1\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c7ea62fe-7ea0-4e98-95e5-df79599b1545", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "This cell asks you to set up environment variables for a local RAG (Retrieval-Augmented Generation) agent.\n", + "\n", + "Environment Variables:\n", + "- USER_AGENT: Specifies the user agent string to be used.\n", + "- LANGCHAIN_TRACING_V2: Enables or disables tracing for LangChain.\n", + "- LANGCHAIN_API_KEY: API key for accessing LangChain services.\n", + "- TAVILY_API_KEY: API key for accessing Tavily services.\n", + "\"\"\"\n", + "import os\n", + "\n", + "os.environ[\"USER_AGENT\"] = \"myagent\"\n", + "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", + "os.environ[\"LANGCHAIN_API_KEY\"] = \"xxxx\"\n", + "os.environ[\"TAVILY_API_KEY\"] = \"tvly-xxxx\"" + ] + }, + { + "cell_type": "markdown", + "id": "f4fe714b", + "metadata": {}, + "source": [ + "Use local embedding model to store documents in vector database" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "8d1b3be3-b150-4e39-aecf-f4a51a5eb358", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Failed to load libllamamodel-mainline-cuda-avxonly.so: dlopen: libcudart.so.11.0: cannot open shared object file: No such file or directory\n", + "Failed to load libllamamodel-mainline-cuda.so: dlopen: libcudart.so.11.0: cannot open shared object file: No such file or directory\n" + ] + } + ], + "source": [ + "\"\"\"\n", + "This cell performs the following tasks:\n", + "\n", + "1. Imports necessary modules and classes from langchain and related libraries.\n", + "2. Defines a list of URLs from IRS to load tax related documents from.\n", + "3. Loads documents from the specified URLs using the WebBaseLoader.\n", + "4. Flattens the list of loaded documents.\n", + "5. Initializes a RecursiveCharacterTextSplitter with a specified chunk size and overlap.\n", + "6. Splits the loaded documents into chunks using the text splitter.\n", + "7. Initializes an SKLearnVectorStore with the document chunks embedded using local embeddings model \"nomic-embed-text-v1.5\" from NomicEmbeddings.\n", + "8. Converts the vector store into a retriever with a specified number of nearest neighbors (k=4).\n", + "\n", + "Modules and Classes:\n", + "- RecursiveCharacterTextSplitter: Splits text into chunks based on character count.\n", + "- WebBaseLoader: Loads documents from web URLs.\n", + "- SKLearnVectorStore: Stores document vectors for retrieval.\n", + "- NomicEmbeddings: Generates embeddings for documents.\n", + "- tool: Utility for defining tools.\n", + "\n", + "Variables:\n", + "- urls: List of URLs to load documents from.\n", + "- docs: List of loaded documents from the URLs.\n", + "- docs_list: Flattened list of loaded documents.\n", + "- text_splitter: Instance of RecursiveCharacterTextSplitter.\n", + "- doc_splits: List of document chunks.\n", + "- vectorstore: Instance of SKLearnVectorStore.\n", + "- retriever: Retriever instance for querying the vector store.\n", + "\"\"\"\n", + "\n", + "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", + "from langchain_community.document_loaders import WebBaseLoader\n", + "from langchain_community.vectorstores import SKLearnVectorStore\n", + "from langchain_core.tools import tool\n", + "from langchain_nomic.embeddings import NomicEmbeddings\n", + "\n", + "# List of URLs to load documents from\n", + "urls = [\n", + " \"https://www.irs.gov/newsroom/irs-releases-tax-inflation-adjustments-for-tax-year-2025\",\n", + " \"https://www.irs.gov/newsroom/401k-limit-increases-to-23500-for-2025-ira-limit-remains-7000\",\n", + " \"https://www.irs.gov/newsroom/tax-basics-understanding-the-difference-between-standard-and-itemized-deductions\",\n", + "]\n", + "\n", + "# Load documents from the URLs\n", + "docs = [WebBaseLoader(url).load() for url in urls]\n", + "docs_list = [item for sublist in docs for item in sublist]\n", + "\n", + "# Initialize a text splitter with specified chunk size and overlap\n", + "text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(\n", + " chunk_size=250, chunk_overlap=0\n", + ")\n", + "\n", + "# Split the documents into chunks\n", + "doc_splits = text_splitter.split_documents(docs_list)\n", + "\n", + "# Add the document chunks to the \"vector store\" using NomicEmbeddings\n", + "vectorstore = SKLearnVectorStore.from_documents(\n", + " documents=doc_splits,\n", + " embedding=NomicEmbeddings(\n", + " model=\"nomic-embed-text-v1.5\", inference_mode=\"local\", device=\"cpu\"\n", + " ),\n", + " # embedding=OpenAIEmbeddings(),\n", + ")\n", + "retriever = vectorstore.as_retriever(k=4)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "f8d54464-37b9-4b48-877e-38fc7620c1ff", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "This cell imports the necessary modules and initializes the web search tool for the LLM.\n", + "\n", + "Modules:\n", + "- `Document` from `langchain.schema`: Represents a document schema.\n", + "- `TavilySearchResults` from `langchain_community.tools.tavily_search`: Provides functionality to perform web search by LLM if required.\n", + "\n", + "Initialization:\n", + "- `web_search_tool`: An instance of `TavilySearchResults` used to perform web searches.\n", + "\"\"\"\n", + "from langchain.schema import Document\n", + "from langchain_community.tools.tavily_search import TavilySearchResults\n", + "\n", + "web_search_tool = TavilySearchResults()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "36dad7e6-3752-4939-be70-f87d23d90d6f", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "This cell sets up a question-answering assistant using the LangChain library. \n", + "1. It imports necessary modules: `ChatOllama` for the language model, `PromptTemplate` for creating prompts, and `StrOutputParser` for parsing the output.\n", + "2. It defines a prompt template that instructs the assistant to answer questions concisely using provided documents.\n", + "3. It initializes the `ChatOllama` language model with specific parameters.\n", + "4. It creates a chain (`rag_chain`) that combines the prompt template, language model, and output parser to process and generate answers.\n", + "This setup is essential for enabling the assistant to handle question-answering tasks effectively.\n", + "\"\"\"\n", + "from langchain.prompts import PromptTemplate\n", + "from langchain_core.output_parsers import StrOutputParser\n", + "from langchain_ollama import ChatOllama\n", + "\n", + "prompt = PromptTemplate(\n", + " template=\"\"\"You are an assistant for question-answering tasks. \n", + " \n", + " Use the following documents to answer the question. \n", + " \n", + " If you don't know the answer, just say that you don't know. \n", + " \n", + " Use three sentences maximum and keep the answer concise:\n", + " Question: {question} \n", + " Documents: {documents} \n", + " Answer: \n", + " \"\"\",\n", + " input_variables=[\"question\", \"documents\"],\n", + ")\n", + "\n", + "llm = ChatOllama(\n", + " model=\"llama3.1\",\n", + " temperature=0,\n", + ")\n", + "\n", + "rag_chain = prompt | llm | StrOutputParser()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0affbee8-30c4-4dd0-a95a-d8ab571b55c6", + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"\n", + "This cell sets up a prompt template and a retrieval grader for assessing the relevance of a retrieved document to a user question.\n", + "\n", + "Functionality:\n", + "- Imports the necessary JsonOutputParser from langchain_core.output_parsers.\n", + "- Defines a PromptTemplate that instructs a grader to assess the relevance of a document to a user question.\n", + "- The grader uses a simple binary scoring system ('yes' or 'no') to indicate relevance.\n", + "- The result is provided as a JSON object with a single key 'score'.\n", + "- Combines the prompt template with a language model (llm) and the JsonOutputParser to create the retrieval_grader.\n", + "\n", + "The retrieval_grader can be used in the workflow to filter out erroneous document retrievals based on their relevance to user questions.\n", + "\"\"\"\n", + "from langchain_core.output_parsers import JsonOutputParser\n", + "\n", + "prompt = PromptTemplate(\n", + " template=\"\"\"You are a grader assessing relevance of a retrieved document to a user question. \\n \n", + " Here is the retrieved document: \\n\\n {document} \\n\\n\n", + " Here is the user question: {question} \\n\n", + " If the document contains keywords related to the user question, grade it as relevant. \\n\n", + " It does not need to be a stringent test. The goal is to filter out erroneous retrievals. \\n\n", + " Give a binary score 'yes' or 'no' score to indicate whether the document is relevant to the question. \\n\n", + " Provide the binary score as a JSON with a single key 'score' and no premable or explanation.\"\"\",\n", + " input_variables=[\"question\", \"document\"],\n", + ")\n", + "\n", + "retrieval_grader = prompt | llm | JsonOutputParser()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "d672ffdf", + "metadata": {}, + "outputs": [], + "source": [ + "# This cell defines the state of the graph and imports necessary modules for graph visualization.\n", + "# It includes a TypedDict class `GraphState` that represents the state of the graph with attributes\n", + "# such as question, generation, search, documents, and steps. This state will be used to manage\n", + "# the workflow of the RAG agent.\n", + "\n", + "from IPython.display import Image, display\n", + "from langgraph.graph import END, START, StateGraph\n", + "from typing_extensions import List, TypedDict\n", + "\n", + "\n", + "class GraphState(TypedDict):\n", + " \"\"\"\n", + " Represents the state of our graph.\n", + "\n", + " Attributes:\n", + " question: question\n", + " generation: LLM generation\n", + " search: whether to add search\n", + " documents: list of documents\n", + " \"\"\"\n", + "\n", + " question: str\n", + " generation: str\n", + " search: str\n", + " documents: List[str]\n", + " steps: List[str]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "2f26efee", + "metadata": {}, + "outputs": [], + "source": [ + "# This cell contains the core functions for the document retrieval and answer generation pipeline.\n", + "# The functions are designed to work with a state dictionary that maintains the current state of the process.\n", + "\n", + "\n", + "def retrieve(state):\n", + " \"\"\"\n", + " Retrieve documents\n", + "\n", + " Args:\n", + " state (dict): The current graph state\n", + "\n", + " Returns:\n", + " state (dict): New key added to state, documents, that contains retrieved documents\n", + " \"\"\"\n", + " question = state[\"question\"]\n", + " documents = retriever.invoke(question)\n", + " steps = state[\"steps\"]\n", + " steps.append(\"retrieve_documents\")\n", + " return {\"documents\": documents, \"question\": question, \"steps\": steps}\n", + "\n", + "\n", + "def generate(state):\n", + " \"\"\"\n", + " Generate answer\n", + "\n", + " Args:\n", + " state (dict): The current graph state\n", + "\n", + " Returns:\n", + " state (dict): New key added to state, generation, that contains LLM generation\n", + " \"\"\"\n", + "\n", + " question = state[\"question\"]\n", + " documents = state[\"documents\"]\n", + " generation = rag_chain.invoke({\"documents\": documents, \"question\": question})\n", + " steps = state[\"steps\"]\n", + " steps.append(\"generate_answer\")\n", + " return {\n", + " \"documents\": documents,\n", + " \"question\": question,\n", + " \"generation\": generation,\n", + " \"steps\": steps,\n", + " }\n", + "\n", + "\n", + "def grade_documents(state):\n", + " \"\"\"\n", + " Determines whether the retrieved documents are relevant to the question.\n", + "\n", + " Args:\n", + " state (dict): The current graph state\n", + "\n", + " Returns:\n", + " state (dict): Updates documents key with only filtered relevant documents\n", + " \"\"\"\n", + "\n", + " question = state[\"question\"]\n", + " documents = state[\"documents\"]\n", + " steps = state[\"steps\"]\n", + " steps.append(\"grade_document_retrieval\")\n", + " filtered_docs = []\n", + " search = \"No\"\n", + " for d in documents:\n", + " score = retrieval_grader.invoke(\n", + " {\"question\": question, \"document\": d.page_content}\n", + " )\n", + " grade = score[\"score\"]\n", + " if grade == \"yes\":\n", + " filtered_docs.append(d)\n", + " else:\n", + " search = \"Yes\"\n", + " continue\n", + " return {\n", + " \"documents\": filtered_docs,\n", + " \"question\": question,\n", + " \"search\": search,\n", + " \"steps\": steps,\n", + " }\n", + "\n", + "\n", + "def web_search(state):\n", + " \"\"\"\n", + " Web search based on the re-phrased question.\n", + "\n", + " Args:\n", + " state (dict): The current graph state\n", + "\n", + " Returns:\n", + " state (dict): Updates documents key with appended web results\n", + " \"\"\"\n", + "\n", + " question = state[\"question\"]\n", + " documents = state.get(\"documents\", [])\n", + " steps = state[\"steps\"]\n", + " steps.append(\"web_search\")\n", + " web_results = web_search_tool.invoke({\"query\": question})\n", + " documents.extend(\n", + " [\n", + " Document(page_content=d[\"content\"], metadata={\"url\": d[\"url\"]})\n", + " for d in web_results\n", + " ]\n", + " )\n", + " return {\"documents\": documents, \"question\": question, \"steps\": steps}\n", + "\n", + "\n", + "def decide_to_generate(state):\n", + " \"\"\"\n", + " Determines whether to generate an answer, or re-generate a question.\n", + "\n", + " Args:\n", + " state (dict): The current graph state\n", + "\n", + " Returns:\n", + " str: Binary decision for next node to call\n", + " \"\"\"\n", + " search = state[\"search\"]\n", + " if search == \"Yes\":\n", + " return \"search\"\n", + " else:\n", + " return \"generate\"" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e056c4c8-fb62-4524-bb38-11b8c2a20326", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Graph\n", + "\"\"\"\n", + "This cell defines and builds a state graph workflow for the agent pipeline described earlier.\n", + "\n", + "The workflow consists of the following nodes:\n", + "- \"retrieve\": Retrieves documents from the vector database.\n", + "- \"grade_documents\": Grades the retrieved documents.\n", + "- \"generate\": Generates output based on the graded documents.\n", + "- \"web_search\": Performs a web search if needed.\n", + "\n", + "The workflow is constructed as follows:\n", + "1. The entry point is set to the \"retrieve\" node. so the first step is to retrieve similar documents from the vector database.\n", + "2. An edge is added from \"retrieve\" to \"grade_documents\".\n", + "3. Conditional edges are added from \"grade_documents\" to either \"web_search\" or \"generate\" based on the decision function `decide_to_generate`.\n", + "4. An edge is added from \"web_search\" to \"generate\".\n", + "5. An edge is added from \"generate\" to the end of the workflow.\n", + "\n", + "Finally, the workflow is compiled into a custom graph and displayed as a Mermaid diagram.\n", + "\"\"\"\n", + "workflow = StateGraph(GraphState)\n", + "\n", + "# Define the nodes\n", + "workflow.add_node(\"retrieve\", retrieve) # retrieve\n", + "workflow.add_node(\"grade_documents\", grade_documents) # grade documents\n", + "workflow.add_node(\"generate\", generate) # generate\n", + "workflow.add_node(\"web_search\", web_search) # web search\n", + "\n", + "# Build graph\n", + "workflow.set_entry_point(\"retrieve\")\n", + "workflow.add_edge(\"retrieve\", \"grade_documents\")\n", + "workflow.add_conditional_edges(\n", + " \"grade_documents\",\n", + " decide_to_generate,\n", + " {\"search\": \"web_search\", \"generate\": \"generate\"},\n", + ")\n", + "workflow.add_edge(\"web_search\", \"generate\")\n", + "workflow.add_edge(\"generate\", END)\n", + "\n", + "custom_graph = workflow.compile()\n", + "\n", + "display(Image(custom_graph.get_graph(xray=True).draw_mermaid_png()))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "f26919fb-85ac-4afc-aaf7-cbb222dcd737", + "metadata": {}, + "outputs": [], + "source": [ + "import uuid\n", + "\n", + "\n", + "def predict_custom_agent_answer(example: dict):\n", + " # This cell defines a function to predict the answer from a custom agent based on the provided example input.\n", + " \"\"\"\n", + " Predicts the answer from a custom agent based on the provided example input.\n", + "\n", + " Args:\n", + " example (dict): A dictionary containing the input question under the key \"input\".\n", + "\n", + " Returns:\n", + " dict: A dictionary containing the response generated by the custom agent under the key \"response\",\n", + " and the steps taken during the generation process under the key \"steps\".\n", + "\n", + " The `config` dictionary is used to pass configuration settings to the custom graph.\n", + " In this case, it includes a unique `thread_id` generated using `uuid.uuid4()`.\n", + " The `thread_id` ensures that each invocation of the function is uniquely identifiable,\n", + " which can be useful for tracing and debugging purposes.\n", + " \"\"\"\n", + "\n", + " config = {\"configurable\": {\"thread_id\": str(uuid.uuid4())}}\n", + "\n", + " state_dict = custom_graph.invoke(\n", + " {\"question\": example[\"input\"], \"steps\": []}, config\n", + " )\n", + "\n", + " return {\"response\": state_dict[\"generation\"], \"steps\": state_dict[\"steps\"]}" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "5261f17e-3b6a-43df-ad5d-17ad9639e8dd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'response': 'The standard deduction is a fixed amount that most taxpayers can claim, while itemized deductions are specific expenses like mortgage interest, charitable donations, and medical expenses that can be deducted from taxable income. Taxpayers choose the option that gives them the lowest overall tax.',\n", + " 'steps': ['retrieve_documents',\n", + " 'grade_document_retrieval',\n", + " 'generate_answer']}" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "# Here we define an example input question about the difference between standard deduction and itemized deduction,\n", + "# and then uses the `predict_custom_agent_answer` function to generate a response based on the input and show it.\n", + "# Since, this question is related to tax deductions, the agent should provide an answer based on the loaded tax documents.\n", + "\"\"\"\n", + "example = {\n", + " \"input\": \"What is the difference between standard deduction and itemized deduction?\"\n", + "}\n", + "response = predict_custom_agent_answer(example)\n", + "response" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "627e38d9-3e0a-4094-b1fd-917fb89cc5bb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'response': 'India won the 2024 cricket world cup and Virat Kohli was named Player of the Match for. The final match was played between India and South Africa on June 29, 2024. India defeated South Africa by 7 runs to win their second T20 World Cup title.',\n", + " 'steps': ['retrieve_documents',\n", + " 'grade_document_retrieval',\n", + " 'web_search',\n", + " 'generate_answer']}" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "# Here we define another example input question about the sports event,\n", + "# and then uses the `predict_custom_agent_answer` function to generate a response based on the input and show it.\n", + "# Since, this question is NOT related to tax deductions, the agent should provide an answer based on the documents returned from web search.\n", + "\"\"\"\n", + "example = {\"input\": \"Who won the 2024 cricket world cup and who was the MVP in final?\"}\n", + "response = predict_custom_agent_answer(example)\n", + "response" + ] + }, + { + "cell_type": "markdown", + "id": "2caa78d6-f2aa-41eb-9298-f16ba6e467ba", + "metadata": {}, + "source": [ + "As demonstrated in the previous examples, the RAG agent routes the control flow through web search to generate answers for non-TAX related questions. For TAX related queries, it uses documents retrieved from the vector database." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87a59300-c8ab-4281-9a31-25d37a5149f3", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "test-env-langchain", + "language": "python", + "name": "test-env-langchain" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/Makefile b/docs/Makefile index a3c41260e3dd0..107bb1feb4d3d 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -47,6 +47,7 @@ generate-files: $(PYTHON) scripts/partner_pkg_table.py $(INTERMEDIATE_DIR) curl https://raw.githubusercontent.com/langchain-ai/langserve/main/README.md | sed 's/<=/\<=/g' > $(INTERMEDIATE_DIR)/langserve.md + cp ../SECURITY.md $(INTERMEDIATE_DIR)/security.md $(PYTHON) scripts/resolve_local_links.py $(INTERMEDIATE_DIR)/langserve.md https://github.com/langchain-ai/langserve/tree/main/ copy-infra: @@ -59,6 +60,7 @@ copy-infra: cp package.json $(OUTPUT_NEW_DIR) cp sidebars.js $(OUTPUT_NEW_DIR) cp -r static $(OUTPUT_NEW_DIR) + cp -r ../libs/cli/langchain_cli/integration_template $(OUTPUT_NEW_DIR)/src/theme cp yarn.lock $(OUTPUT_NEW_DIR) render: @@ -80,6 +82,7 @@ build: install-py-deps generate-files copy-infra render md-sync append-related vercel-build: install-vercel-deps build generate-references rm -rf docs mv $(OUTPUT_NEW_DOCS_DIR) docs + cp -r ../libs/cli/langchain_cli/integration_template src/theme rm -rf build mkdir static/api_reference git clone --depth=1 https://github.com/langchain-ai/langchain-api-docs-html.git diff --git a/docs/api_reference/_static/css/custom.css b/docs/api_reference/_static/css/custom.css index 87195de8f72ef..f98ef26197313 100644 --- a/docs/api_reference/_static/css/custom.css +++ b/docs/api_reference/_static/css/custom.css @@ -80,6 +80,8 @@ html { --pst-font-family-base: 'Inter'; --pst-font-family-heading: 'Inter Tight', sans-serif; + + --pst-icon-versionmodified-deprecated: var(--pst-icon-exclamation-triangle); } /******************************************************************************* @@ -92,50 +94,7 @@ html { * https://sass-lang.com/documentation/interpolation */ /* Defaults to light mode if data-theme is not set */ -html:not([data-theme]) { - --pst-color-primary: #287977; - --pst-color-primary-bg: #80D6D3; - --pst-color-secondary: #6F3AED; - --pst-color-secondary-bg: #DAD6FE; - --pst-color-accent: #c132af; - --pst-color-accent-bg: #f8dff5; - --pst-color-info: #276be9; - --pst-color-info-bg: #dce7fc; - --pst-color-warning: #f66a0a; - --pst-color-warning-bg: #f8e3d0; - --pst-color-success: #00843f; - --pst-color-success-bg: #d6ece1; - --pst-color-attention: var(--pst-color-warning); - --pst-color-attention-bg: var(--pst-color-warning-bg); - --pst-color-danger: #d72d47; - --pst-color-danger-bg: #f9e1e4; - --pst-color-text-base: #222832; - --pst-color-text-muted: #48566b; - --pst-color-heading-color: #ffffff; - --pst-color-shadow: rgba(0, 0, 0, 0.1); - --pst-color-border: #d1d5da; - --pst-color-border-muted: rgba(23, 23, 26, 0.2); - --pst-color-inline-code: #912583; - --pst-color-inline-code-links: #246161; - --pst-color-target: #f3cf95; - --pst-color-background: #ffffff; - --pst-color-on-background: #F4F9F8; - --pst-color-surface: #F4F9F8; - --pst-color-on-surface: #222832; -} -html:not([data-theme]) { - --pst-color-link: var(--pst-color-primary); - --pst-color-link-hover: var(--pst-color-secondary); -} -html:not([data-theme]) .only-dark, -html:not([data-theme]) .only-dark ~ figcaption { - display: none !important; -} - -/* NOTE: @each {...} is like a for-loop - * https://sass-lang.com/documentation/at-rules/control/each - */ -html[data-theme=light] { +html:not([data-theme]), html[data-theme=light] { --pst-color-primary: #287977; --pst-color-primary-bg: #80D6D3; --pst-color-secondary: #6F3AED; @@ -165,15 +124,8 @@ html[data-theme=light] { --pst-color-on-background: #F4F9F8; --pst-color-surface: #F4F9F8; --pst-color-on-surface: #222832; - color-scheme: light; -} -html[data-theme=light] { - --pst-color-link: var(--pst-color-primary); - --pst-color-link-hover: var(--pst-color-secondary); -} -html[data-theme=light] .only-dark, -html[data-theme=light] .only-dark ~ figcaption { - display: none !important; + --pst-color-deprecated: #f47d2e; + --pst-color-deprecated-bg: #fff3e8; } html[data-theme=dark] { @@ -206,6 +158,8 @@ html[data-theme=dark] { --pst-color-on-background: #222832; --pst-color-surface: #29313d; --pst-color-on-surface: #f3f4f5; + --pst-color-deprecated: #b46f3e; + --pst-color-deprecated-bg: #341906; /* Adjust images in dark mode (unless they have class .only-dark or * .dark-light, in which case assume they're already optimized for dark * mode). @@ -216,6 +170,30 @@ html[data-theme=dark] { */ color-scheme: dark; } + +html:not([data-theme]) { + --pst-color-link: var(--pst-color-primary); + --pst-color-link-hover: var(--pst-color-secondary); +} +html:not([data-theme]) .only-dark, +html:not([data-theme]) .only-dark ~ figcaption { + display: none !important; +} + +/* NOTE: @each {...} is like a for-loop + * https://sass-lang.com/documentation/at-rules/control/each + */ +html[data-theme=light] { + color-scheme: light; +} +html[data-theme=light] { + --pst-color-link: var(--pst-color-primary); + --pst-color-link-hover: var(--pst-color-secondary); +} +html[data-theme=light] .only-dark, +html[data-theme=light] .only-dark ~ figcaption { + display: none !important; +} html[data-theme=dark] { --pst-color-link: var(--pst-color-primary); --pst-color-link-hover: var(--pst-color-secondary); @@ -389,6 +367,13 @@ html[data-theme=dark] .MathJax_SVG * { div.deprecated { margin-top: 0.5em; margin-bottom: 2em; + + background-color: var(--pst-color-deprecated-bg); + border-color: var(--pst-color-deprecated); +} + +span.versionmodified.deprecated:before { + color: var(--pst-color-deprecated); } .admonition-beta.admonition, div.admonition-beta.admonition { @@ -408,4 +393,4 @@ dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(. p { font-size: 0.9rem; margin-bottom: 0.5rem; -} \ No newline at end of file +} diff --git a/docs/api_reference/conf.py b/docs/api_reference/conf.py index 3f742b051571a..acc77ab2aa6d9 100644 --- a/docs/api_reference/conf.py +++ b/docs/api_reference/conf.py @@ -87,6 +87,18 @@ def run(self): def setup(app): app.add_directive("example_links", ExampleLinksDirective) app.add_directive("beta", Beta) + app.connect("autodoc-skip-member", skip_private_members) + + +def skip_private_members(app, what, name, obj, skip, options): + if skip: + return True + if hasattr(obj, "__doc__") and obj.__doc__ and ":private:" in obj.__doc__: + return True + if name == "__init__" and obj.__objclass__ is object: + # dont document default init + return True + return None # -- Project information ----------------------------------------------------- diff --git a/docs/api_reference/create_api_rst.py b/docs/api_reference/create_api_rst.py index b3cff2b3f28b1..1d4a35b9f0dd1 100644 --- a/docs/api_reference/create_api_rst.py +++ b/docs/api_reference/create_api_rst.py @@ -72,14 +72,21 @@ def _load_module_members(module_path: str, namespace: str) -> ModuleMembers: Returns: list: A list of loaded module objects. """ + classes_: List[ClassInfo] = [] functions: List[FunctionInfo] = [] module = importlib.import_module(module_path) + + if ":private:" in (module.__doc__ or ""): + return ModuleMembers(classes_=[], functions=[]) + for name, type_ in inspect.getmembers(module): if not hasattr(type_, "__module__"): continue if type_.__module__ != module_path: continue + if ":private:" in (type_.__doc__ or ""): + continue if inspect.isclass(type_): # The type of the class is used to select a template @@ -479,11 +486,11 @@ def _package_namespace(package_name: str) -> str: Returns: modified package_name: Can be either "langchain" or "langchain_{package_name}" """ - return ( - package_name - if package_name == "langchain" - else f"langchain_{package_name.replace('-', '_')}" - ) + if package_name == "langchain": + return "langchain" + if package_name == "standard-tests": + return "langchain_tests" + return f"langchain_{package_name.replace('-', '_')}" def _package_dir(package_name: str = "langchain") -> Path: diff --git a/docs/cassettes/extraction_0bb138d7-116e-4542-aa5f-bebf0c301ec6.msgpack.zlib b/docs/cassettes/extraction_0bb138d7-116e-4542-aa5f-bebf0c301ec6.msgpack.zlib new file mode 100644 index 0000000000000..2888367a54e6f --- /dev/null +++ b/docs/cassettes/extraction_0bb138d7-116e-4542-aa5f-bebf0c301ec6.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/extraction_13165ac8-a1dc-44ce-a6ed-f52b577473e4.msgpack.zlib b/docs/cassettes/extraction_13165ac8-a1dc-44ce-a6ed-f52b577473e4.msgpack.zlib deleted file mode 100644 index 9de117e001ca1..0000000000000 --- a/docs/cassettes/extraction_13165ac8-a1dc-44ce-a6ed-f52b577473e4.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -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 \ No newline at end of file diff --git a/docs/cassettes/extraction_6b73d4e2-d18d-4d47-89ec-99b5eb6b234f.msgpack.zlib b/docs/cassettes/extraction_6b73d4e2-d18d-4d47-89ec-99b5eb6b234f.msgpack.zlib new file mode 100644 index 0000000000000..2677bb12b0402 --- /dev/null +++ b/docs/cassettes/extraction_6b73d4e2-d18d-4d47-89ec-99b5eb6b234f.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/extraction_855d0878-b1d9-4843-ace3-179b3f26ce7f.msgpack.zlib b/docs/cassettes/extraction_855d0878-b1d9-4843-ace3-179b3f26ce7f.msgpack.zlib new file mode 100644 index 0000000000000..177d28fb324ec --- /dev/null +++ b/docs/cassettes/extraction_855d0878-b1d9-4843-ace3-179b3f26ce7f.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/extraction_cf7062cc-1d1d-4a37-9122-509d1b87f0a6.msgpack.zlib b/docs/cassettes/extraction_cf7062cc-1d1d-4a37-9122-509d1b87f0a6.msgpack.zlib index 5ea02b181de84..e92fa85f6841f 100644 --- a/docs/cassettes/extraction_cf7062cc-1d1d-4a37-9122-509d1b87f0a6.msgpack.zlib +++ b/docs/cassettes/extraction_cf7062cc-1d1d-4a37-9122-509d1b87f0a6.msgpack.zlib @@ -1 +1 @@ -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 \ No newline at end of file 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 \ No newline at end of file diff --git a/docs/cassettes/extraction_dd42a935-022f-4860-b9e0-84268f55b22a.msgpack.zlib b/docs/cassettes/extraction_dd42a935-022f-4860-b9e0-84268f55b22a.msgpack.zlib new file mode 100644 index 0000000000000..4c7015ed7e9ee --- /dev/null +++ b/docs/cassettes/extraction_dd42a935-022f-4860-b9e0-84268f55b22a.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/llm_chain_0abb0863-bee7-448d-b013-79d8db01e330.msgpack.zlib b/docs/cassettes/llm_chain_0abb0863-bee7-448d-b013-79d8db01e330.msgpack.zlib new file mode 100644 index 0000000000000..c23a2b7e5ea7f --- /dev/null +++ b/docs/cassettes/llm_chain_0abb0863-bee7-448d-b013-79d8db01e330.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/llm_chain_1b2481f0.msgpack.zlib b/docs/cassettes/llm_chain_1b2481f0.msgpack.zlib index 854400a94ec8a..4da8498db3a9a 100644 --- a/docs/cassettes/llm_chain_1b2481f0.msgpack.zlib +++ b/docs/cassettes/llm_chain_1b2481f0.msgpack.zlib @@ -1 +1 @@ -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 \ No newline at end of file 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 \ No newline at end of file diff --git a/docs/cassettes/llm_chain_3e45595a.msgpack.zlib b/docs/cassettes/llm_chain_3e45595a.msgpack.zlib index 481dc32e51e9c..76d3c73c95837 100644 --- a/docs/cassettes/llm_chain_3e45595a.msgpack.zlib +++ b/docs/cassettes/llm_chain_3e45595a.msgpack.zlib @@ -1 +1 @@ -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 \ No newline at end of file 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_0005810b-1b95-4666-a795-08d80e478b83.msgpack.zlib b/docs/cassettes/qa_chat_history_0005810b-1b95-4666-a795-08d80e478b83.msgpack.zlib deleted file mode 100644 index 17c8ad10a55ba..0000000000000 --- a/docs/cassettes/qa_chat_history_0005810b-1b95-4666-a795-08d80e478b83.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_0907cef3-05cb-45c7-ab46-382c58c52eb1.msgpack.zlib b/docs/cassettes/qa_chat_history_0907cef3-05cb-45c7-ab46-382c58c52eb1.msgpack.zlib new file mode 100644 index 0000000000000..651390403731f --- /dev/null +++ b/docs/cassettes/qa_chat_history_0907cef3-05cb-45c7-ab46-382c58c52eb1.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_0e89c75f-7ad7-4331-a2fe-57579eb8f840.msgpack.zlib b/docs/cassettes/qa_chat_history_0e89c75f-7ad7-4331-a2fe-57579eb8f840.msgpack.zlib deleted file mode 100644 index b529e74f4abd1..0000000000000 --- a/docs/cassettes/qa_chat_history_0e89c75f-7ad7-4331-a2fe-57579eb8f840.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_1046c92f-21b3-4214-907d-92878d8cba23.msgpack.zlib b/docs/cassettes/qa_chat_history_1046c92f-21b3-4214-907d-92878d8cba23.msgpack.zlib deleted file mode 100644 index f09787d2f0f74..0000000000000 --- a/docs/cassettes/qa_chat_history_1046c92f-21b3-4214-907d-92878d8cba23.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_17021822-896a-4513-a17d-1d20b1c5381c.msgpack.zlib b/docs/cassettes/qa_chat_history_17021822-896a-4513-a17d-1d20b1c5381c.msgpack.zlib deleted file mode 100644 index 49912ef3ee9b7..0000000000000 --- a/docs/cassettes/qa_chat_history_17021822-896a-4513-a17d-1d20b1c5381c.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_170403a2-c914-41db-85d8-a2c381da112d.msgpack.zlib b/docs/cassettes/qa_chat_history_170403a2-c914-41db-85d8-a2c381da112d.msgpack.zlib deleted file mode 100644 index 3000ae003a486..0000000000000 --- a/docs/cassettes/qa_chat_history_170403a2-c914-41db-85d8-a2c381da112d.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_1c8df9d7-6a74-471c-aaef-6c4819ee0cd0.msgpack.zlib b/docs/cassettes/qa_chat_history_1c8df9d7-6a74-471c-aaef-6c4819ee0cd0.msgpack.zlib deleted file mode 100644 index fb6d8d5b1c38c..0000000000000 --- a/docs/cassettes/qa_chat_history_1c8df9d7-6a74-471c-aaef-6c4819ee0cd0.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_4fbca953-970d-4271-be30-6c7799893dd1.msgpack.zlib b/docs/cassettes/qa_chat_history_4fbca953-970d-4271-be30-6c7799893dd1.msgpack.zlib new file mode 100644 index 0000000000000..479e283de5bda --- /dev/null +++ b/docs/cassettes/qa_chat_history_4fbca953-970d-4271-be30-6c7799893dd1.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_570d8c68-136e-4ba5-969a-03ba195f6118.msgpack.zlib b/docs/cassettes/qa_chat_history_570d8c68-136e-4ba5-969a-03ba195f6118.msgpack.zlib deleted file mode 100644 index a52774e63218c..0000000000000 --- a/docs/cassettes/qa_chat_history_570d8c68-136e-4ba5-969a-03ba195f6118.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_5c7e1717-d262-4947-a64d-6b116e53856a.msgpack.zlib b/docs/cassettes/qa_chat_history_5c7e1717-d262-4947-a64d-6b116e53856a.msgpack.zlib new file mode 100644 index 0000000000000..4379824c7d30a --- /dev/null +++ b/docs/cassettes/qa_chat_history_5c7e1717-d262-4947-a64d-6b116e53856a.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_6d0a7a73-d151-47d9-9e99-b4f3291c0322.msgpack.zlib b/docs/cassettes/qa_chat_history_6d0a7a73-d151-47d9-9e99-b4f3291c0322.msgpack.zlib deleted file mode 100644 index 62e443907b73e..0000000000000 --- a/docs/cassettes/qa_chat_history_6d0a7a73-d151-47d9-9e99-b4f3291c0322.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_71c32048-1a41-465f-a9e2-c4affc332fd9.msgpack.zlib b/docs/cassettes/qa_chat_history_71c32048-1a41-465f-a9e2-c4affc332fd9.msgpack.zlib deleted file mode 100644 index b69f9c15ad386..0000000000000 --- a/docs/cassettes/qa_chat_history_71c32048-1a41-465f-a9e2-c4affc332fd9.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib b/docs/cassettes/qa_chat_history_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib deleted file mode 100644 index 207999417ad2c..0000000000000 --- a/docs/cassettes/qa_chat_history_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_8ef6aefc-fe0e-457f-b552-303a45f47342.msgpack.zlib b/docs/cassettes/qa_chat_history_8ef6aefc-fe0e-457f-b552-303a45f47342.msgpack.zlib deleted file mode 100644 index bf42d4896f326..0000000000000 --- a/docs/cassettes/qa_chat_history_8ef6aefc-fe0e-457f-b552-303a45f47342.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_931c4fe3-c603-4efb-9b37-5f7cbbb1cbbd.msgpack.zlib b/docs/cassettes/qa_chat_history_931c4fe3-c603-4efb-9b37-5f7cbbb1cbbd.msgpack.zlib deleted file mode 100644 index 0497b803e875a..0000000000000 --- a/docs/cassettes/qa_chat_history_931c4fe3-c603-4efb-9b37-5f7cbbb1cbbd.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_9ab78984-d7fa-40e1-a440-c041a6456c1f.msgpack.zlib b/docs/cassettes/qa_chat_history_9ab78984-d7fa-40e1-a440-c041a6456c1f.msgpack.zlib new file mode 100644 index 0000000000000..f16662747ec4b --- /dev/null +++ b/docs/cassettes/qa_chat_history_9ab78984-d7fa-40e1-a440-c041a6456c1f.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_a2f48f92-bd91-4033-a01b-7bd0667e3d87.msgpack.zlib b/docs/cassettes/qa_chat_history_a2f48f92-bd91-4033-a01b-7bd0667e3d87.msgpack.zlib new file mode 100644 index 0000000000000..f08bfd4dbae8e --- /dev/null +++ b/docs/cassettes/qa_chat_history_a2f48f92-bd91-4033-a01b-7bd0667e3d87.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_b1d2b4d4-e604-497d-873d-d345b808578e.msgpack.zlib b/docs/cassettes/qa_chat_history_b1d2b4d4-e604-497d-873d-d345b808578e.msgpack.zlib deleted file mode 100644 index 32bd4102f46cf..0000000000000 --- a/docs/cassettes/qa_chat_history_b1d2b4d4-e604-497d-873d-d345b808578e.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_b4369949-39f1-4cdc-b652-179e0b891b51.msgpack.zlib b/docs/cassettes/qa_chat_history_b4369949-39f1-4cdc-b652-179e0b891b51.msgpack.zlib new file mode 100644 index 0000000000000..30cddb0c75967 --- /dev/null +++ b/docs/cassettes/qa_chat_history_b4369949-39f1-4cdc-b652-179e0b891b51.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_bf55faaf-0d17-4b74-925d-c478b555f7b2.msgpack.zlib b/docs/cassettes/qa_chat_history_bf55faaf-0d17-4b74-925d-c478b555f7b2.msgpack.zlib deleted file mode 100644 index eeeae4c1c1c44..0000000000000 --- a/docs/cassettes/qa_chat_history_bf55faaf-0d17-4b74-925d-c478b555f7b2.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_c6d16477-52f5-4755-83d1-60eebddfaaa0.msgpack.zlib b/docs/cassettes/qa_chat_history_c6d16477-52f5-4755-83d1-60eebddfaaa0.msgpack.zlib new file mode 100644 index 0000000000000..f7d0edea80305 --- /dev/null +++ b/docs/cassettes/qa_chat_history_c6d16477-52f5-4755-83d1-60eebddfaaa0.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_c9d6f0ee-b5a9-4141-9f6f-ad86a04e083f.msgpack.zlib b/docs/cassettes/qa_chat_history_c9d6f0ee-b5a9-4141-9f6f-ad86a04e083f.msgpack.zlib new file mode 100644 index 0000000000000..5fcd60f7bcdee --- /dev/null +++ b/docs/cassettes/qa_chat_history_c9d6f0ee-b5a9-4141-9f6f-ad86a04e083f.msgpack.zlib @@ -0,0 +1 @@ +eNrte3dYU8u6N4pdFEFBsbEEpEkghRCKgHRp0nvbKSsQSMEUQkdFsYOoiKKI9CYgRenYUCkCIk1QQEG6gDQRFP1WAu7tLvec7z7nnO+593u2f2DWzDvvvG1+81vJzLFUH5DOINGoy26TqEyQjsUzoQfGpWOpdPAwC2Qwj6dQQKYHjZBkbmZlnciik9plPZhMb4aqggLWmyRP8wapWJI8nkZR8EEo4D2wTAXoszcZ5KpJwtEIfh3rdgSIUUAGA+sOMsRUAacAMTwNmovKhB7E7KAhAIkBWGMZXoAuyBlMY5A4ozXF5AAxOo0McsRYDJAuFiQH/DyWyiKTfxLBMhgkBhMLdUGNTBqN7IbHkslLMzL9vLlCRBaV6yFHhkTgtHCE3Ay8Gf4IPwdLhOnhg77mWKo9A4X2B03cOWK/DlGFZqdiKVw9dJBJJ4E+IEcAS3dnUSCTOFOJBTiLQXGj+zlDD85if/bKWSxILCjI5Q+uiFnRWHQ8CM0gxeB+klIFpH7EmUwik7BUNkh1l3cnMT1YOHkSTQHSx2QoIOFIFAyuBIP+QtGlMhWkgpypOotqVQF9krs8gJAHzKAc+5BANkAjAljAxMQU5k1jg3SQAGBZTBqVRqGxGAB3PMDwYzBBijxHCWQyldNkRoXsMidjqVQS1V3cmaoFcDNMwmOZkAYmx0MWgwVF0Q8gUX1oZB+QAVCwVD8A0uTNkAe0qEu6qSBIYABMGuBFpbEBNifxTA/QD8DSQQBLJQDe0BwA1gPEEqD5/xw5aGodDyyJyvECqkiWuwcTkNahWasBdiAJAJkAliwPQAFBygAeWAaA44yFFAOcmiBg6ZB+OqSMCTkBMEG8B5UE5Qkg0ugASPXAUvGcdgqNAJIBb5AONUMu4EGARl30FvTlegq5Y+0BLslBVUuiMph0Fp4bCBrgzELCEXimB4nqxXUewC0GgdvOlWAxoVz6cxRAPjOh5QVjkiAjOVOwmFiOlxwpwpLbIOQIfTHEnKmgHgYFijNI54aLQeLYRf8RZigSAJOOpTI4tkPuk9x/HkhhkZkkSJyTGSgbWBz0cbGbq8oDcoBMgiK6JA4lggsH3lCdL5rFDfqS51x/VKBUcjzlxA2KLB5a4FDanKn/kUq2poMgxwTrxbwzAGkHLO2nnKNkANAXEoXqixMHKO6grzeZRucm9YfrdBDLoFG59tIgrMBBxjBJULFCdQhi8R7cQMoDhkyASKIzmL9lgcH1HPIRChrlD+H8UYjcJHBjCRkPwSiTswj+IMTgVBZXUg7AQ8ZwSxELJQ3ybbGMWHRwscAYIJYOWbQUVwAP5QMHAtr6VoA0DhpJYHrAFo1cFJQBoDLW5fQSQO8/9bGhUP/wEDIMAH2wZBZ38UJxwgJ4Mgc5iSTINmkfEhZqWVwoXKUUrCcURaYf4ENjgj+WJeHnZfnDOAKEFoA0QoajFIKYxVkXa/SnlUcmeYEQLlpxw8VZfPYOjvLOzlSEvDMEpc6L2wEHEDghZ7Bw7jQseVEQsh8CXI4OaIgmR1oayZ2MxeAuacgwGMMbxEOe4H9dl5xNSA0A5SEchHRDjiwCAo3uB9BYTDKJCvkkxlXPhjoX80Gl+YDQvgK1SaOWgufBonBXBLRIGfI/b0ucbeZ3243b/82m8kfw/zPWcbBlqei4BQCVPifv3MVGoLGpnLT9EYR/Bgi5RYT5abEvoQRU3b+C9K8oyFhMy6/oav0TusrIQUgNLiXkV9xbTOgi6v0Z7+R+gtR/BqaQMqw3pI5TnpDpNPZitnEgE4IfgEUlQPSEA+Dc3EDLC/QF8axfEYmLYNCsvwIftxQ8fizTHxCJ/7GZ/T57vzGGP2ZEB0q3H40FkGk0aHfzBhi0RZSmQPOysX7chBBonMlIzL/gKS5QCzdWnCZ3byZMkQaDTCNxJDk8AgH9DxUoiKVAD0SowkFODYEUbw5yQCAAtcLlMUt19Q8YzD+lJgSQgaeTvJdkxCyXuqDocJPCjSMdJGOXUokFuNyFGyRvLB1SCCWBwdUOpQiyjoOX3EeuHPfTD7sgf6B4QNyGEw2IO5IgfsGxfEmUE5IfojScJ4iHgs7hQamc/R6apItnU5IHtBNEZv+eVuZg8XgI02AgFU/jFEFklrs/CaowAkjkmJ0BJY0KcoMQmeEFgt4wLJnkA6Ysjoq8A9UWd5FA/QqeEPrfXkoyjGPLn7szOPlb3IAiC8wgI7QMFcz9IPymQjwKjZRH3vGFQRVDopKhVQmD+Ip7ZIo3t7/05w5vLN4LUgJb4taRKYuDs3+WoTEik02xeDOr36nkIHZkMpZOUVLM/7mdzqJymEJkqo75n6db6vxtOpQ8AiGPyf2dYoYfFR+ZzC22wt8NhmrCD4anQToi4+EpeKjiSWBk+6SbG57ohqOoUx2YSE8bbVOEgY2ZEs4eq0Nhex2yNoArabGNfSzpujY2WghLf7rbQX04DIFBIVFwRaQKBoaQh8sj5BEwX3N9AtwIhbb3Z2uTEUZWnm5aBz3ZurTDvsr6jvJaFl76JCtLooqtHcZAHsM85OdhzaQydf3pNgxvb0M2xV+JjmEhlRD6hvLu+iZkGzyN6OvHZKsBkHUsHxJBnYWFWxuZ2Bwy1gGtLW2MdfyRlo5UkheO7KlFQpjjTXGmVuZW/ubmBB3aT+ZhMGgYfMlCJbiiMpzzL/tHbZAhgsL0iExCopUxaXSQAWEHAwxN4eyeLMaxJKgQwedVqUuvNAlmxr/VsHCSLlSUkeX6dJIcgEQCh2g+HHqiCCBUVFHKqlCLgan17SVaA7P+yxrMteaCGVSHej9qPhXvwaJ6gYQMnb+s9nJOtUOp5NgPAREM4j4QbYEtWRV52x5mufgyBzPUzV9cWjAa3R1LJflzp40s55Y929+XTcCzCAQPHzYFruKviCLhQBaeWLA0ZGkzggyCURiRiWhFxeylnh+FlwH5ClUBHAZHlPjCOCyITKKQoIBy/y69UTIik9BQtIv+LMCkeYFURmSqIjcd8IqfJeggBapYzty/qVFUUVEp+2uhH6pQkAgagSr5vRQD/NkaBJLCKPqzwJKKRAyFcdv3hziMRIhsl4Ae3BAEFBFEqCARODiIQuFVMEgEkoBTxsERWCQSpYIt5gAiHlLDyaY3jc6EMaCdi8OlItvlKFhfDsqooxBolBLkqhqEyHgyiwBasXC6NI4TEG2ByDeZhiXk6OjDdKDtEYRZcQswMlXX4ZCWqaHOPXvYz5UEM+PiPNRPpTGoJCIxxQp67QPpkRl4Mo1FgOCSDqZAuiy1HCILlEElnBICCScSFAkonBIRpg0B0Q9tv9ZdEgdrU7FkyHYffGS+B0pdTFVRESWmBjELdWUlKE/cN/yjKYvg/2TZN9Gza3i4/3jPWdVSX8M3lY3sO6XudOKrR9TgFcnB+JPTR4UPWW5drpdNkAxMkwDb4F/Hl4FOF3dtTdu4PDcfVapmTBXXPuBdtebO3hmTFmTFte8X6gp8WyOm0PddG6gDa79PTo1l+ntUbIWv47PaLz5l0KpGtIY1rk+checfVF/Vclg11uRSu+K1giPIneAtm7sR7pK22md9L5oQD1982pvJG0BaobNaZE5IQLvq3sJJDfSz+xciCcxz0sxw2zUO0bpr7MV1VqQxHvllqJ/zvyAyanGylSXex/PxadUNC5kvj77Q1JRniRYyU6k9wXcbK4ooHyeaOh83FTaIjtuNnN/V/NqYNnwvPq/xNop0hD3x4fa2PbfSPYuFy4WKHqHk9xygtEg3a0xveL3yK+kFVfgC7IhI8jnJdQsvvQ2M8KdTx054861HHTqesP7Vw9Pv5UuY39Tv1ODalWX5d+/uKaXKvLS+iz6hNrXNKP6EU79wupf7LsfduzLvsm6ptMs2t6Z1DHSV3dqYlz/92FVo/npbYu80j39v+s472amJ6/1VDMz0Sj+NpSBqrlQFeIb0ejw+IcLT+Munwk7nl10NCswZzUn1B9tad/u5Or0/FnvoTaoDH/+UGym2lvL4rVJ9Yo1x/L6Cu0Kj+Ufy6i8p+rldtpMxBjr0cqBEf//Oy/PIZlBbYgUPzz/41kjiv/7WCKTgQAKn3ha/L2r3ChDjUm0Oe3BCo5UhtoRGI5XlAJSSCvRHUQktBygpIZWUXH7Hs5jQGyDsV10wLAELg8ORHCrzgzu4LZIejjAOywCVFMX+ph//0+mHg7yNiR8ZS9Ih6mh7+Chp22rh0PagNd7Ok+lvKm/NZGnbOsIRNJSFt9dv+zviV/qh7Ya18/Yn0VUMmCxTDM4GKW+BtWXYwHFsYxLdEeeLZVJVzPXNbJkgzsYXRyf5E1GKxj5MbQTDDvREO/rjfI0RBoe0ta394Yb6+j4kRzsfazuL3+iHjjlC390Hp2RGxlK07U3JJrYUmvFhfU802ZiiTTVXtNEBDXyoRDuKrelP5imqKP1z+pGIgP832ce2f8I+UP8R9lH6B/bBfYuD+AXJnUSNjJf975CT20t8grumI+/99Yr+tzGYBCXkPyAw/7b9+19hQuh/HxPiiKioKP4LTCgB/pdEiIgGkUQ4RHtAvBIWTUTCleB4vLIyQUlFCYMjoHH/Sf6CRhOUEcpEzL+Jv2wT+I2/WMcY8+cZ3e8bGE991W71RZdqGfKJT6vY6sTblWqx4UACQFeQPlTPHh+c6mfOVi4TXGN+t5WWlfH9a5tbyIKLlN6VjSHfp9q6x+00vy5oVjwbK3z3aVYzZKEhZGGGIzEwPvtdDZV58UNwSNBk99B9Tbe4AKXvCw1ub0JE5+5LLUBDu57QDSpEPAre3JY8MbRnf7rkeAlVo79s3ePRK+e9SMVFifWijuaYvpNdp7sULkXH84THBZupN7YJUw1jdtMPdQmWkY7jTmt/P/dI0mata1zc2lLNC8t6ztvbezYGX9u9gnC5/9HR7fQMoUC9R9bpChG86HAvBra5O+1giL0CXRo5mALYaF/QDDMpfN2XpOD1xXaP51b3276/MKfeO1u2K9sKCR+/onsWdgJRIxH9LvZQz3EVLfcDFszVcibjEbUrGKr7SlTozbtZ+3DP1zPSNKP35RqIlUx9zvX8ZUB712gbqdXd0G21R3KOfwJVFRbDFn/zwEZPiPaoQQgB7lC+QylDt7saNiLQE3be+HaBqR4LVvuMyo6PfmXyza/bow++98s4Zukv096V41ww+Pocb2b5rjR/VNxY0mjLtpXpr87ldV7tfLsjO9SWutvS2DWwUvTea+uhdk+xpxqPOrfEXV6X2xIg+WXOVXh6k5/7XMvM1jK5aAD3ioKz3//CUPXyDSeDhHVA0fjxGIyN22dlJ68qG3bA9u13r6yJju1/OLJNcVpQVJC9yS2Ul+10Kb0heSzveNLhF+SENYx93Y0OeVJIvtMBe5P0mylEF9mHG8dV0aVoxupy/v2v3m83mKCEGPVvNxC5LXZU3L+RzOyPpKeaxAG3JipvPqm03KGD0lCofHOZFitUVQu8/XBj+GSXY2Uv9u2FYiul5vznXorGCvdP1Hf7V1L5y7r8ao+/61dle6JCeuv3zk7w6NA2pdZGJR8umTHlQ6N3ikYzMhpSv0TxLptbv4deodcUxbC7052j9JnZU0dQ2Zi7zlhTP1Exl5K7Zn914xS1QLdpRUZEgsh6eMXB8EiStKpTh7Nl4B79ymPfrO7ovvYzBywkr4Z8iB565LVPt/DqM1zxhounj9iGZg+7ez7DnrA/6iMzaTt0xSPj0daCN6Na9+Jsjuj1OrNRrONCb5LlJcICwhvFVlxfu+W7w2Y7DWrJXuUQ18F7pfBAZmswYrza4IRNTvezMj67Rri93JGrTmq+/kMBhamZ17Km9mxIL/G2QZSfH0reKXZStPiK7JNtyjk7trFZ5+3icpntm99seR5b+ChrrTnfV6oQD9LneElRy9ncuMIwXErDatbN2WT8tvts76csRdkPJaa+wbVG0g5FCU8/NW/VGankW7eL8ix9cg58WZd3bMAlsHfMOeiMSJ/oap9QsmBg57ZO7zJafdrsTXVD/tsv3TtDYqPsxDZpv2reeonZ6VezzAVplJJ9Lix3Jhzunqx1ezb7fFfYAP0FUX5vP/GMsCQrZZl2AUs6vEXLDVdaf6Q1Z+NAepNQU8E6nVufpvZnf9zb9CVo4c77jdUbsrUEL/anrn6a3SD9ia8JPPaYJOjdF95V9/iufZWF5mN80DXpw7yomE3XqTWhfBNpJtfK5arOG0vvOJhOpWjFEW2qsDHyvBaPtcf69a7vOyBV9GKXrQdCCjPG5xaUzPYJkpSTubz2k1Sw8Y0BdVl7zder7GvxEva3/YMCpUZ2SUy2SJXGfg0fHl94V9a6T47CcIpLoaTEnxS5nZ5S/1RM+LWUVdiAp5lNplsp36jOsiynuq8Vom5bK+f3aglLKZQdVg0WSctfXrXgmuhTmpPQFfRmm7eawY7iCuFECLE2pznCm8y9WgYjvrlGTIclS2gZhhSFrVp3aeHgbOmRfZIXdFcV3umOPHntsGqAhCVfLyrIqkm57QnOcMfatXTJ85mmDPmUfak5F+6pP292rCNcI+zJeICxR9QYbyqePn53+7v4Ny+cLKgv6JVZ4l6tMW8nbnnEDt5gaPl1sWHojupDRE/5ZeZD987VprPMU7Per+uctkzy3GlcnTfss/H2+ovhaetsKpPJBwXsqvYszJ8wLn4i8CDRIPztaqvOIR9nmzvF5/YgnjaapsCJQgfrAra3VZS3uA9hQwOrhY9SRZ9tZB3e6mmO7hfIkUK83CobJbvJhAeVM7VJfNoykRI7emro/XVCGenJqQ71iPtt4xdP9z/ZsHH06iZNdy2DZL9n8aOBlFMKNuZ8bMJT8yypS+StAwV3RpNjzYPGGopEe9gFgYBd1EO/WIQmxkJxyOaqmENQ9mk1vWCJDDO27rBxN04jkoSJFTfUdrs/hwq+MloerCVAuuo4f1L37LZOO+mxkZhVWjV7GZtve6msLRdkpCgYnJUCRNZhvmyyaRU9pYWNmCRmap4ai1jlqLxs4JdizIORwM5ik9tOIlku5wXcirYYFt4QOwCrVFoYVsu43FYbempoXXDITGnn5eLUD3b+Z0+Wz8sSZ3eVvZ12GNAtBYOQY4+f8pydWX/4CvAymhHy4oGVgko7eP6uXKajadS7tQFlssABK6s0QV1Bu6a34gNPnncdWv9tAC5IviDvuKY0PO2yJn/CUZmv2amyMfOCpx7O74nBGAVeLs6bqtZQsn3yUbVS5jiWPT/ZsDqXQKu5tTPCYPhj/6krDjuti8y6woZHFlJ3VPjfuuw/KdF18QKuqnK3OFlXNRdld14y3wTFrNl8bX5PXGmtyjaVy4rP9/Rr16W9m9ofejZhJfPsuQ3b62XUHitdQPXQZ6O6no7jeVYTVY43K0ak+It6hnwmhvRoNn6o6N151XtN2rtLd3bsL1XV8VWT793nAe8xjMIWpUQafQq0ZJWXjxK8k+tMTouMJWoG29UXH5rxuNkJpp4xUHx+w+x8S5Zc8Dh//12/W7Znu9LeI93m58QnZgYtp+PtUz1Ogkqf5kvOXCkwRMPDQb2Xc2T9xzb3Ak5ll14lmlXAhnPiattiD8fbJs40BpaIrihy23GCPJM7nlLedfDgkFuNMm2r63hpoVtCTtcvXVajYEm97ZqwiFfjIdHBrU/WHBvzLMreEvTuY+z6I+O+0fvHnJzcBh0OxSPCxYWVZRM0pnpdlc7mf7muWX01XYd/sgqX4eZFEyg4u+NIVtSpwAEDRem2G1pEoUIL7Lih2+6+59Wlzy6lFl11nbf0IqzsmBe2HPimvMUEoaDwYByekoKcNG5iZR2pWiBYhXgmJ2RnBq9265IKm/7w5oma+spNHZ7bjeXHSrEZ99DN+1oSk17BGvffd9tYs2Dx+Ix3o3jKukuJQCj7491zFhiZQMfqJ8aqTXjnjJVe18ADe2VkEBGN+qnEsIAXovVni8L2S06Fvg6ewwdIFVlcPq6S3/PVN/B4/P4S408VuyOH+TbO2EXkqz20qN2zmSYWPjtKHMrPjZXoIwgm+LzMHAy9zB8SrHaGVuyQImUr0cxnZZRX6iFUOyCvtinA0uT2JSvJ+3P5c/sn1z9hNw73PzOkNq6P4seVvZKKWW28sS8W+NQsqmm/9WmvXtjpB0K1EdezGgZGU/VF/QM2YW7PujA0aZ6fJ5HCDR0+Igp3r36rT91u+Uk19Y79cv9y4vREC3usPSO5rMzCdEN8crW0yHVUVfTMAUT34SfWIquFOhPIpnUuyNLEoBdGr/Yt2/stWpQoIrmx7EHO0Kfm/cwrwg480VYhO9y/t0vpyGmqz2FCxvor9GoFVy0rcO4WsBl5dGzfwrMNRqsDmjVHsxslTmNPb7PNbrbm90QaNChG83cumBykOw99YFz2tz/08LruOCO9wfax/i3Lsrfotm0CTTlxfHWZU9eumn2WU8w6lj+5sFv3cbLAWreQ+aGhuMDZ4g7ZB7Uu1ypt5oxy6L5ZW+JhUs+dOlbXHVHauTMneuW+169rkl8fM5pk3OK9+7hhVePmvv3JzcNnVojlr7O48QWV9/7j/En26teBrYNhJdtz0gC5D/NvPjxg9l127LcZ+fzOymkw06AXZ1YK9gg8UyK2fdItTBXM9ao2fXG4chfmlpFH+s1UcYlRhqZwHD+9fTYgXkp0l8E9/RRXUYW0iyH7/UoNcsCkZec+rjgkGewg7DEfOG2EsKgXyHxYtQuQcisPGNJ1eSwZ89lJTftrvxBOd5XPwECPBwDknXvk5CZU61u8PKntsx5SvHiIvD9p24axdwc+lXbuqJO1WGmOaTnp6dsT4lekCwvXqDS+Ao9vFDt4oLfkVoDxF7lQUkvWjeMjz9IIzS9OdlUgmz9PRs6TXWHre8nLNJrufUZ1Pf0gYDOJ+X5xtGmBaYp+v3znk5dSEm7s+f2jx3YdXz2n31mAnb+1Omqd6EvBHqdMFyn9Smr81CPevaut2vRGK1p44np48mU3JlJT5fbCyyoE6fD17OpZcNU6z1iLz5MCTuUTGyL1Oi7hnc7VXi3fvYd50PNpSqedodmYTGh/UKuBrX547b62GC1C75EMV3tmU+a4VLPUTNjYqfIz851OqyRO7zsviN1Z6jd3bufXzwIt0ZIxobMZBqkt73F6GqObJ5CTuxXdwZT3FZQ36R739h4RnW8WS824jmmoOarIc/3CoXJd1swQ36vbe48PYWgmpbFBvD64gB76l7Jb4+RegHTGik6Z1X9kkHFpz7Tw7so6zRtd5DyllWMVOWnzL7vHbh2SExY6+Kn5F8thS9mo7RIdKns7Mh1LH/dFll+wanPPu5+NZ4fnHeENQSc1qx09IjklgmKekrsp6FtYDbjXrwvrCa8Kpl4hIPLWhc4Iqnr6b+2KfXsMMf84TjAnvuJD2NrARznV35YHYyiHzExVHBd0+dskTFLi4qQKbR82TUhKBF2QXXbVlbHn9UDfDbnuwI253XrNOmMb0WNqwQsTTqXT830NUxmTfSeSKQoJDlrvRLLvbBhUiIMtt9lVtCvomr/X6wMzm6cET/ncTW29FV5tf8b0SP/ZK5tRUuygSWvNVS9T3bfr1fDWbb+nMpekNHqqojdfffymuvPYUaMbDesXxtgrYgI22qgZjuifdVufYFBzkYjrG8pv79ovfVF8r6xmWmQarWHn863o73294XV4i4fvnuopVru6YMq9sqwva9gN2twTirWs0OAd+NJ+lRLDaPsycvTLxEpb+bGSbVMf7I8FyxyNcXQWOhuEMXgx/E6rbKxR6LGRAF1Cw+sw4WJdsZXLzKokJ/zZOY8+YaZN5rXJrqfy6lccbEze+6DfRnmvoMldkQyZJuYt1w2eAvW9lR/VH8yRKNkCKl6n+oW1IchVmAhJOaQc/4nr+Xrku5QzuRquiBeq44PssqEFPJP3VZzPqvOaPq8W5tU/1oklvnLLPPGxJM5oU4nV7JQUu0dw9fchhWMiG+Trhi+t8h/N+T5o0VLnt3a99dqWaimzVa/Jnn5rVE47M96I+TSdce2immzOqSiDq+zLDBPaTE5ICXe6EyV7t6oifcOGj2pjT+cv1lTZnFffc+3r8KuR4Jy3ukkCtWNemfk6QWuiEpm5az5pB4tE2UHhsfez/1Z2EcxNcljOmBDL63bOOjbS8nlN4DHY8LNjdt45KYi3bTkU/giESKBO4YPN11ELE6NfRxRC0zQae7NQV+YKfGgHivR3CU3dkUlxiBSR2NibfiVZeX4oVWz3tr2OQYMzfREhj0zSJt6kujRclj6w73gXs60Nh6y9xrsJ0JHyCQncMoNR0DF/zx4+eD26Nrh7BD+6PW/quCTOsN6nZqFDRpzZCRuOXb0+ZOrSPJgunluz8S7S7cqKnJML+GtZ+ruxBOL51JfAyiz08smas4FlErw5/ELFyd4u/kb884NCjwvObtjmGnomlZwzUvuleu3HYdF4TbcaxrNpacwt5v4I5YbHGyfO3ku/ZdaxYc9JD/265g8RaQrnYnoidorpf6z4OnPy8o1PAbHd599sKIq9/Ut2jAVm2yjxuPNB3bLTOrym7H7eSTmK3kJis88Cmg//ebJKYVzPxO9+n2jIpVqne42v9DHnKsq0bvTL+qCyLwtk6CDCE4R3dE5W+21Uzla2EG+8Wv+0VyfMXGnmMKNiXj66cIaKx0yahMznHjyO8I55f+DNt/f6TaWP9xQkyod/zObden4HxuATRea0fIe/1FgfYNua5Slo4mQ8QLveqqPhlqm45hgbc81x38PHvqP6vvde9QVPORSdR6OV/bXkXPp4UoUYp60ut4EVT48mBx6TFmt9K0OljWUORw+c2pBR8NyuffdD51ZfZ91SafuLtWreNq7J9YklgGx9nwi6gvm1PyfUFdOSbfnIz19g9Hr31SBvI0J3Qdi8zEk1ny60+HNc48K8VTNjZHVVSTvj/oTbHf0MntNNBeIxbTPfx5oKYjSeDr0WZdGCTBpNTpsWRr9yJjbVOG3qVBdrXfClu6dupgFP4OZ03rtX39hd0XqbFWfP90E1xuXZ1hdDD48fDn5fSO3YMS64JWLD9OvuPSVrG3jgHmyj6RvF1hNme96HOQpekr2hwZqfPKatMXbQ0u1DUoRZ4Mq6By9DZu9u6D7hccEiFPOslzrXX8gXJJcYb+u+u/RwgB/iKs4uNUnwnDbZPFGrMOmhtNLFUhOvi6IPI11FwhLgao45bPtrnp17fbY3D0YEz7rkPulh7/82/y5koL3UP6Kf0Dt9cI3O5BQj6Osn0ZDpZrlCK93aLOGarWUip0XGy5NyZuMzrq4PD94/Wu+c3lYVtXOZWbmw0JvCBr1osrB+q+oXakyLTXjFvIpYarfP5KgfrM/MJMDkvt8NY16J79WlKMP1iuP68mHUEJHDN510ECF+K22rPNN3aN6snpTGPBItX+g9maWLrJIfPalatZk1HHvzxuRI2+VyjJTVzvqLuL2NY6+7HZ4MhtvxFNBtSjRpDfOEralbkAz/TXahGrjcrvCQzy+iqRrDE5SMB188BFxnQ698VAiu9C65MV65Z6GMz+2+wYpwkb0LRJ/ak4UPP46mVsydZImTejZlqyG+VtzXEPmc5fzwExG5M2Ndd2Ngt/udA9deqH9X0QuZR6mKvItuCPen5HgafOtnvQHehc7PWXQd6d7LLhNIXnikFrtNR1A2QuH+qMs3036h7Te+mtRdSzylF+e0xitL8wJcs2VM7ETmlp2l7S/Vu1DRWTOXL7UZPot4vv0G6NN1cVUrXTT9afFz8PGy896dE3tYTQECuVXm5d3+7dKDr7xFIkS3Lfj2WIgnoN4opE8uBOvOIK8830o4vykpMLS9cBxXX2T4rqbzteYcw7WmXutLYzCWyooKHhH96K6uU9RhiQheEE5ZPStxf4AU5SJxhLnL03MuKm9aM8TkDW77k+vPSqqlG9d56jxgpmpHmnyWjBqceqe0JfNQfMPrPmex8TzEYI7oLVgegye5ujousNSW363Ctb1XP3EK2V5qNtMUMtxfreYZMmKq8D3b3Ab2ZbDUNS1+sMbAOuRpjMa+Nv9jfVsqEBKi5ZsSzLY9AmgxNI2Qkd4PCFOsDc5CynOr7sOTa0uai4OnXg3WO73ZueydnWlw2/VKr0ZxB3NFTyvfhIkRfung69v1w7dI6DxtUSj2E2XFZFPwAqIlQrfsVZiVd4nPwBH3k9ioktRI0d05uAmzDpGgZ1uFM6Leypd/KHtwMLSzMGL6YjtVkD/rUpio38TV0pCv96Kd9tdLtDTST5UpNIB2k72hmv6RznvPO+9vO6VsWGYTUpGzPemZR/GK93zxKScq6+UrYztcEhJYal6VUv4RJV61rgB8VMvn0UPvaPkrliovL2LCFCKQ1oq+UyNej6ZxRbVOFJHbzMFnxaep1TT1DWKGaUMVeBxm8nOPlqjfXNrX6dE7d62Knu0Yre1eG6MbKXJ/znhDwH29N9YXhgdCKitFzvRvsRE0QTgKXEp3QOwIFXwsaaeShw5wNgkbe/OiN3AK7iiygKwwz9VujhF8nol9ZVqYThxsy3k3ly7+LTp6NvHLo+cdZNUz3tulD3XePM3wZXfiHnVe6I4Pz6VfvkH9NoN1UksU9+8Lxsy9UD0Qmq8/HXAi+uGwHWaN6qbBru4t1QVkSZ25SXXWXpd9lQzztZpdu/rqLRP16m7TQsZ52zuYiQ0KrRVv+x3Z21OijeIuPnGKP3+1/FsdI362fWFyHRXzhQcWXpYBNBwKwO2t3EfECWhJjuPih9nqORE9HrOpEU0zpr15VT7gHcuF2tf2g68qz62dbJyduFGWlKCwvfTY/ZDS5d9G3EIWZu4Hq/FlzN8sv7+DN4y8+1vv/cJ1X5+NBn/hD9/8jayz7YvTzYWFhvts4Gsnk9XC9z0grfZDE+e79uuaThu+7R5+9+lbyMbvIwGJ3+fbvi9b/Enb2jxhTRfwD3/S/m9fhFgr8w8uQjjQWEsn4YFfzyVyj0JyZ4eUwLBUBhuk/zjsypAHbBiLxzKJNM5PbtzTliQQD3JPJ/44BUgAuHP4Mrnn+7gauGN+aJUHDInco44EGlWKuXg0n9O/KCoHMLB+0DOW+QeZH5Nzzy6DHCfw3GP/viQKi8I9qMn5gfAnTRwz8CQG+PcZ8b/PiP//f0b8P1bkf1/p+ftKz//TKz0/H25frKQ/HZb/F67w/X314e+rD3919eHvc3l/Xwv4n3stAKWI/vdeC1D8/+daQBICqaz8v+NegCJa6V+5F6D8X9wLwBJQBAwKroQC0Sg8BkNEE1AgFo1RRqOIWDwR/F9xLwADJyLw/757Acvtfr4XYEprOrCpfMDu3KcVF12KWTHWxcC6NRv1gLRm/mMJdf5khfZOh9HbX7Ravoe3Huq13nL6LFh33S+Y1j+HXQ4w9woD1vsS87re0xTq60xR4uoKZg0awcXzC1k9/G7dIWdSr+NgeYpaI25pPU3NR8VGNuibUo/YHBBB5O6ur03Mu3pFr533iqwi6fYEIs6SerdpzuKwYt1Zv2DfvFiq4T5C7hHRzTxHTn67xixZN165/MyHdFykg5K0cKkkj0BV0pkLz2MSmRYE8bQqPWb5NJsAUymKmuWz1rlcdnTdpa242OdHfGqYQtrPOtC/EDw2nWOaSu043rX+cWZ+fsPX7VQW+Sirg/fzgVaDVYmYNcYT6gnuaTIP+lpmLHlW2p85a6t/Ydmee2veZO24SPS4mNHie0nD14+1QJRBHhjZ0Jlq9PJqvkGyV9YBtfB4K0NZd8AlaoXVxy0Ek06KO4h8V1q12rtLTNz+HMyGD7adv0MrdGPhaM0tPvW6A69XmuSY9ZwU757Zrsy7D1OeIAy7RTi/TOxolPyoZOTbXRnyPQ+/feJt3VV7madNJD9Lc6yelDZxtLXsCXvGUa1uVPYWgT7E3Fl9dnfQDZ6vH/BN6sbHtoXfOVOgFb0mNX/ugdTTgvBB8r2V4nqkp/OHHYgKH7Nkz1nu6Fp/09zyrv35RLwRaEfq4JUMyP5uOyU4+9a5tD9k0OCAzLRAZhS/PWnmzcQrYfjC8++erynFW+U+3xTvsMlyCX24Wv2r0V03oakeX5e45zZ7JCMuaS5dOBB1jT9nv4KH5/8Av8qZhA== \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_d6d70833-b958-4cd7-9e27-29c1c08bb1b8.msgpack.zlib b/docs/cassettes/qa_chat_history_d6d70833-b958-4cd7-9e27-29c1c08bb1b8.msgpack.zlib deleted file mode 100644 index 78f2d19299061..0000000000000 --- a/docs/cassettes/qa_chat_history_d6d70833-b958-4cd7-9e27-29c1c08bb1b8.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_e2c570ae-dd91-402c-8693-ae746de63b16.msgpack.zlib b/docs/cassettes/qa_chat_history_e2c570ae-dd91-402c-8693-ae746de63b16.msgpack.zlib deleted file mode 100644 index f942fbce3a078..0000000000000 --- a/docs/cassettes/qa_chat_history_e2c570ae-dd91-402c-8693-ae746de63b16.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -eNrtewk4VXvbtylKoVOpHGRRSbHZG3vbm8yEDNuUKdIeFjZ7sge2eUqllEgpFVKhJIrQIDp1KHMlJREpEhkSkelba9Opc87zvt/7XN/zXt/0dF3VWut//+//PfzugXWv2NwgkMWmMOiCVyl0DsgikDjQDft4bC4LDOSCbM6+HBrI8WOQL9rjnZwvcFmUtm1+HA6TrauhQWBS1BlMkE6gqJMYNI0glAbJj8DRgK6ZVJDP5iKRQQ55JWQapkQD2WyCL8hW0gV2hymRGNBZdA50o2RJUQSsttAAIoOopAYosRhUEH7MZYMspQg14M+0IJXKAEwYREXAkhEMkAh0wAogsNkUNgcIYXABDoNMCDH8mc3CIgHa/lderpCoAIUNOBPYAYAZCAvNYFNgqQ3/LocX9ITGIINU+JEvk4PQUkcjOFwWkQHT0qGnKOh/NocFEmjQjQ+BygahBxyQxoRMChHCvJDqSPgZg0FdtAInhMk/w4dL51sd5vXHtS4kLp1A4xMQqQxfb0g8jjcL5LAoIOQymJYMskksCnORXMkJJLBIfiAbINDJAETIZdHZAMgjgSwmhw34sBg0gOMHAsZcDoPOoDG4bMDYFzIGG4DZAzB7dZgrk8CCjoWgwObLwGRBLmZxKODCLYQJVgj/6i+n8xcgDwBUBiMA4DIBCh34k7TftYWsRKH7KkVEwFaGMEZhgWTYHousvX4iZRD9QRLkuogIr4hcP5BAhoTqFFh50Q+SNfnan+FXSCCRQMgzIJ3EIEMHJBf4hlKYagAZ9KESOOAVyPV0kG/a5CsBIMhEEKiUIDBnYVdyEYHJpFJIBHhdw5/NoF9dhAoCluXvy1dgXCAIsP2SS/CQEMZWGvYhUJzQAZS6NlYdWcRDQLij0KkQ7hFUAiRPDpO/fufnBSaBFAAxQSzGYHLOwuZrP9Mw2MmXbAkkvNOfWMKuTr5EYNEw2sU/P2dx6RwKDUzONbX/+3GLiz+O01JHodR1rv+JMTuETkq+xIdw2Z82Q84MQZAYEI/k88gcEuRmCpjc9tnbm+TjTaTpo92g8DbWJHr42FI0UVzQiot19CEGUjW9HdkOeA8uNQRLMjUnm9OYtgiUjqaONlpLE41DoNSR6ih1FMKU5s5202JS7E1dvJnB9vZODoEo1A4W3cMPidbGeVtTPHbgMVgfNycbK02UjbWThbYLimdJ4TBC/CyDUW7+riwfJ4YbnkL08SCG2Lir45hkGjJYD4Ck4wZRyPpWgdYetv47WTxNNBUkOPi5UHY4WtjZBKDdvCFrBBAtQgICSM4erq6apJ/EQ+voIJCLEmKQ2lgk/Ofad2xQQbovxy/5AloHl8cC2Uwo44FxOZDJOFx27EUIh2D9o9zFzJeNt/4BYemLZhAmkyt2sChqgKYO4AQyAU2kpjaAwugidXS1MYCFrfNV08VjnP8hBK87swh0tg8EQ/PvkM8l+XHpASD5iuk/BHsFDHbIk7D4UH5DgDwo6EHEolTJV90Qjgs5H2FlVrwQWQgGy5dAp4Tyj02u4KM+OJQXTCZxyWS/oGAaEheqrUUhglyST8niFihjwMdAAiFo7OQLWpra1xZXvuPuCqQrEoFCIpCoW3A6IEFhBivDZLA4CDZIgqoMJyS5TY1G4MExpq+FQmthIMPrQUmFROWSQScu0YxBg5DJ1gOYLJDKIJBv8xBQpgWpFBoFcgz/38UKxk6+iIY2l/+dgMMIAOns5FxtvluR936mYIEwf1iJH2y0cTjc3X9M9J2VFkSCw6Bu/5mKDf4sDUqTxi7/O8Eii2wk+yrvOzWCQk5u2wTdeGsTtTE+PiBJWxOF9YGE1cFqobQ0iVpYLTJWmwj6FJruQJgSoPyPcOLjLznXzN3O2NbKtNQN8TOQEHh+yobW6Qw2neLjk+MEsiDHJF8hURlcMpQsWWAOxMvR2D25BEvCkYg+BBQZ1CHjkGgkwgRKQ9+5/QG7i3Cm5Zf6mJyF7P67YLXC4aUC/D/C0N/5eY4jgXEGuXK2sbBoiO1ofHtNPCPgpNXzUrp/vpW1k2IN7qAsafX0y0PZM18fHxM4gjFwa9XvDAseDl+6XvhWzL6Yl6xV5perFfquz80VXfymntE0HHVXvbIi4vzs24m09E8bCO9kfGYPxTZeVSUcclS0urDbze3dvj3oQ1tGD/SPv+vNERQvNn5PCbHqGcjvP7XtDqYHmW6Dry9IFpLfNIjbm3jdlP1tw7joG4DQ/cFzazMuY+OmDnxiDLrWNVpvi3ygLfKjMUH7/ARtYOdlQaPqPGfmpdCeCb0VQxH2npc53vHuE9xpdunVLZ8jr/NmZvrUK48oiEYWcLwwEuCJtV5Gwnfzt6zzSYzpNX/gpXo891Jgqscm1VGdV8tlqqPb726zP64gKKn60tVvQHqTKu8tvcbgvHdK4NMzBV1Lhydrury/phmbrS2uDeTWDjkbBtXZK2sUuN85TFU87nGb5p98x6ea0HK/rWA05mMH5nxJjsrWzcWmn0BfB1XxWdLAfb8goccrXeNC18wlnaAfK6diOvVvlNpeHtujOHibun+Jq95vSg0XG5+cdAlq2ooVjRKEnSUs8LTJBmsLee4/aQM3/cdtIEgjgmQYGgsNYNveMCUKncmF+67duzFaOIwagNPR1sGqAVpoHZTXn7orDsiDivh3BggCmYBAIjXhBuJ7Zff2YbBoBH4TRySwQYy20r+bg//Tm4NdDo6EXQ6hWsGmOG1bHtkkxI6J9LFhYQMtzQlUf38XdZBmw+A50TCa2j+qL/aP5sBai2uzM8AXybMJCeaaOdr6Bdhj/E1NcCZEK0cLvKOfG3uHKYWDNdvpw3LB7vIOBmkWVhZElB3PASSSeJZ+tjoO/qHUoEBLW1PNQLQ6aMrUZpr7/mgOnNFYJo7iukOLG2xsTMNiHHG2aD8Czo2gbcKw8CVoou0CTHaZmxGIgcY/iYfUQf/Pm4NsHOaf6w3W/W/pDe78pTcgQD9pBUPVn+JLoSef3/bPtA5XF6s9P6STS/9xQP/L+otsTdT/6e0F+l/XXsAkOJzOv769IJBAApaAImG0UFhtMklHC4nWwZLIPkQCTkcTp03872wv0FgiDov1AYn/5fZi/fYf7YVzWt21/Lsn46f7tpYGpaUAy/aOfS03LX8p8qjA49hyQaFN0bSRkKmnHhZXHLmvi3KvUvBNKIP5ae+ouRn52t7AM/NzY33DdzJ6K+fHtYI1et8OG0bN8VenxobfjM6bG9z+HFj5ImJcdu6O29evNZ+/Zho+nW+c8W6G6Fr9jyvansycGU/9JuizM/K8cYyiW0l3u8lltEbLZOTXnux9ERIbQulP9MzP4nfYiX7o1YhfOqfXEyAppNDKiMgqldrT6q9+ZLkUe/x3B6kXxwYKOLGF/unJRZ2dbbrVCqJ5BSItdTdVvadNNSlmv05oC7e/Uuo0z6/SfbbxKClst3pQ0OVu1njhFxktxEyjuET0ybPXyKoK08mPeiWubLk/nXUY0bt29+swcZGeQIsvyu3diYVeArlYzJNtjCPJFdWJRtppoubN4e6HI2RduTvFpcP8vEzUVcKjeTTuoKrXacS9y6J713E2n8Z35Ltj6Ae7xr1Q1E6DzcAevTyjykyhL/qG08cCLPWNe4K2Jn9cG2kVfSehpTiQ5yB2WOweSNoc4LNxY+IapLb11R6Ra6ZfLoWpvoplcL0qmytbNrTZrhzdfCV1zcPHfbapW8UUVxtq7VO6dZkXhW9nba4wNCJ82uM38GXDqbLZlKqNZz1KrIRvEoobgcFUXPU3mqZFtZvH/SbHDZcR/ek3fdANJ5pAj/4l9eGe3VpPCDrquhXd1qscVSuXMwvuPWFUVJ21kNh3tGgHtr7cPTJmwhH9+fYlbLD8yqdHx7cspZvsm027nPrmLULrucPH9NCuDwcUjgMiVy9kvO1Je52+K5+OObuv2Ho2obqtmuWtLnfpfTxiMvyoXOBXIfK0v2PUPuxu9be+sR11co9PuntpbemoiLtf0pQQ9DExEJUge7/6UJm27ife48ekcUVTrQcq+DAkzXpjc2TnagxGuNgyj7S0YMvA6GXvsymbySzFQ3uEWttHJNzEm+RPPfstK2zLA5ndxX6xiaVyBeHHWY53ZYQJVzMpM6O1PrvUmwSNzCeJEVW7AzS9pWQ7C649GMVHctQkNW20pnZ2xgdtdS/x0a1fZZqdbPyKxW2qE+YhDjWfVJ7DprnOLtdXuvvIZDjilssja8U9ZoLPU8CYT5ENGkWtG8KyPzzXVI/zullre3LVYOLXKo/f929O78+VVSpsDy4mvzkigjYXIz95sj7ljPfy7PXpyk9bk+rSGOl3Xr2ksR72vt91zzACFeNoseSxsLvoamTxWmrHxd9uDw9IyDYOLSmK07Qv7FC42s+9fad596yq+YMJYZct2rYjn8cFNk4/TwzX2CE96flop8uJSJPPxxVsql3j9hztHmvo3vCuq8x7woLuFqc0yDp24Uj8gw6UwECz75Lwr8Fihq45OvnnFJx4T5JUS0OZTW73ajAXf4t7ekpGrKhkdlpUOuppnleutDc+X1zwN6lld/LnHuVdO6Q8sjT8l63bXlFDjoYIngG5B1P8q4jT8pr3ve4mvHOQOGT+YS/+0LQ68MtLVGmv+VspXrL66l/GNDRkxNctNSKcy1P9dXVWRGb7x7dV6dGR2MDPBj3SpWMjRnceSeAKu8KFXcAIlcjSTGpFVKHu4GHM/bLb47WfpgdRlg/r4upjNHVs9ujLjLzStZcFN/LMn6f4TaCTojq3INrNtUTWjx89WPG2322G8mDZkKnxw8pvBh1v7wr79qofpKWUdjeRmd2JF/Qn+m81ttapXkYLd6yUaDmD+5zd7ox8cU/muf4JzOBqYYUVHAUHb5R96+H3hyn3vl6nqPXcDnkzHCde7Dz5dHZODfMwCi+ENUs7alD49ffsS4aRUeOSZ9DHTV4FbBF1J0zv09OindzTKlTuKrNjgOQ/mQ1u3Pc5J/Dy5eDc/ey8Tc3bTeKKep+Obb3+UVrSZWNyB/vAVGifk1ApLj3BTa27HDO9WzxyTO+M9PKQiC/4Y7tTxi+sKwy8zmgQnxSddg6+Y/voxCqXj91tHdffW+nnhgc68xJPnN0hS1q2zuqxctcn9bWSS9xV0qTOKF6sQecclKVgJL1P+m9ZvcWMPuxkFRCBj5yW2K2Xj9jSr503svoq41BxB1S5Av2lzY8YcWeX4Z7p/3K5K6R52XNLxi9902uqUDq2m1ouEJ7Mt1irNmFZLpRNMlbL1lNuK97F5zPH0zaJFVaHKlr1bsuceZSxN91PovrL+iTViRm5PVc5Rm+b5mzspJdihj/bpWquwGWe1Yxh66eTJfIpZxXuUu47lKhjOYcqbm6umItvHAnJ3hnVie1JqY0ekTBr8W671R0RxT7/e2D8vnOpbs/60+2Q8fJZ059yJW5dT8x/Nbhqf6qC/okgHTHjdbtRR4PGLr+bEr9nNL52n/CF+aPs9iadR2rXL95Osd77S0OExGUJITlzp6o+1x6zYx3ilg1PXu97U/DlVrTNBxu5c3rnNMqU0rNm7OQ+zk/KRgSvW/3o8pGRbov5rRH0jcy6tNWY86Fdz0oblvvtqhYbbhr8zZ1UGDdxwWLSMPLGOXEZlyQL6099BQKb8F8QiXYp0RunHdzqXci7zl35pUv/kpZ3vPUm06iwutFnYX1t2dt0X2cdaeny1p+9m44VGroo7fx19srUBta9+Ezjd+RfHLA3qp5u4yUa2+2gGMTePEyQKO56T9o949zw2SRPWGWdKlXBxV/iepT3ffQT+dBP3unjs91aXWdeCIndzaidGkQZn8DtTHhnEX52B28q9t6HlMyx2pmAvhqRHNkxu9Il7Z+fd4QsUROTIWpEUmVLKSly9BXdtud8J5f1v7wr7KZl+lDlVM6xT031z/cPjPwG3myafGX5VVJlCMRrnNEteVmWp1eU+17yF9LdJNUhu2XNQ6BttfmzBydYbfE6IWfsd2e/CUwRKog9EeBuOGUhEyB1c/mF8cBqg56v+w+waQESV8XDhxsZBrdbr8Wf2hMeeuN9NjnJbM/5gk7JLxvehRZXmLlKW+4kETaupjzKni4QYOxOolwdD3wcfOh03LCP3TE1xVa1KbrdLr0yWbnXdjUpWhf0BTtcDLEGI/vnW5yi91ZuuO7dOSTxZv2LiTTfYzZN3FuHRMqqAu2TuMV0wQAqVyB72NzMJyaD9uVu03mmqWpp9JYjz9HjHrsyKk5aXil7jJU3PPcxQyF1/4WbfQO9+3Xd8gsTX+385Lvi7HKRW9iOpQp4q9Lwmz1LIku9k0V/ZVaZdGzcN4sazovcgJt8ZDwW3eMrUTT94PCdA5ujutfdkUbLkbry8/KEEoPSE0bFaDdw5fI2SyVn9x9bV1+9pEE4xkJ15dajbfqepdbOD1q1PZUiS9KLO4hWSNc+Pcmho8uCstsnm/vtNq4qIYps13sor/24zHh5+8X33+ru+CKcrUzbXcvvXjssID9WBBQ0oOfy07o+ciVaFSvd5ru/MkrmV42G39bePjGhOxhSG3gWhZw4I7Gsyu7r9qeDMXvoQY5oY/PtdtqSqeUyl4yBrokN1yyfPW4nVqnpZV2lmBaUdWmnFIcv3X63Qj/dNi12elzvFdNOQ1QSo3AGv1P5VBeiVt7RK/C4rf9LK2bZQ0Vu1PTvjcPLNm3BX2o97/fr2q6d8bTVoi07XR0dY3Yt8Vy7zFG4WXG37gN1o0i7zpbjhsqnVj19VWV7Pe5lSD02s4Mtefx9WFbo7y4GKBdn5BxW/XTUHKkE9Va65FeeY4WEfNEua/X7mdNKeh/utA69YIz3Afb5Yh5ts5/Lb87ntZx8smJSI2nPDpTRg49eaqU4/Mpr5Z9HHvfrG/TdCc7O0MlN2VTX21zkWmBY9Wm7+dKZz6eCJsqabUliBwZ7tB2jxWR0a/qMRDZvM/W4/1XYcm+ZaYpPYk87crygdau28jOpNyNVcutftqet+/3tpMBhe3BJfbb8xdH1bg0ahpTKGV7b6gtt+24pGqMBzNGvjA2rnDoyqqJmomL3sW/0Sa+0S09Snj6/v/62yCoe/VSCS89Lj+NKu3RVXnUasXru7ty/7ZZwxptAOYq7/7hzSmnWNlmT0tpcydM4Wan3ifsSfj19MGo202hQFyF5Z9ON8pRIxzxPPfkD3XUq7rggKR4aLz5xl9rbYp0nqaXw/mXNzr1WO5U/FHHy4hpqWgT2WCeZET5NGM+Lwb+SUju9+xl758r4qGOHDz5LtPY10dz4DgjmmZuYyfkgKyPXvbnnfKk2684LD/yA02RCbvOg8iQ2Wq9zRiAkI/bCI50XGyX3RKmcKZngivTr6SbrWs8cOh1jnPUxM1TOM1c7wyNwZ+mUrRfnRmy38LSzYONcQuqmG3Gb11rYHTp0sjlrmRh7+42+GxGMp4blnZvOEgCVyg2bJ67KKyTWTr4QQIa0Tszw9suMCFg8UxgX8j14wGaax1Q492uid4Xk5KVTaseS8Akqndak2PlnEadC/a3H2eECx+WHRE+BvN9UCncjDQ/JO0i+UT7/Ld2i9+NrRNeAshS1UQP3QUHhVnT364zrBTNfylW/GYqdfDUDfHbX0hp1SkgJN862kqgJi+neJokO/+Kzv7rkTFuebEbWwbuFTmG3AmTu7Ilc/VoiI05A93Bv5fZb31Cb1slL+KCvARzn7qS3nQ33E1PKLnVKxd8bPbL3l0lv8Ura1AHE0MdTD66fl/cc+1Xi0C3wS8saudTVJx7kWo/nVR/v3WGUuFFy+sWMTD01zzSP1S0mq1Zyv2S8bmrO3gofz6ikRsYqX7OLMHGAQGUaTclaM8k7nJ644/yeWnb00TVSlZgzD3FdgmrXfLM9T0mu7URJT6ZeU3qbdIeNuVX5paJ/a3IwuEbtbPfG9covYvJGU8ePRyrKU6Ef/K4NtbVxylq3q9sggqZvC9W9Qe80njIS19enE0s/x8ra3A02S0Xjm4e+NJ73v1jjoISQehk7vD08olxPP3I4M+vaBpbIYxuS85GoDbLn6i4JqnoreWnPQLlMTmRyT/nsla+R6KQ4v2gloVWnaR3C50bCNeyDngqP7x5LQwR1BQCjtUtJJ8pzTl0XjNWSXn6lfzAD4f5gOVJ6S0K67c0vnzacE8taX5ieUV9S9zL3lRWwsW1dhfi4xxEz5SWTThXROZGKu+qnVVl5dplrdr9aX/0bzi+g/Jtq9ruyCIzEaEX0gYip8/i+LwOuFbHI0GUS+jbDG6ghqz6HzxiFnW2Nrrh3RCAme3vzhbMd/phzmZfItj2KozIyNhyDTMmhJDPjvZln2sKFD8i1uF5U+j3sxN5Onp1Wpliox/jBd76CMaFvGdp6V0Ju2mwfjjveoTjI5XYUf97OaxaP1I080eTafA9/W+Cr1zCxYNijuvyybcxJ7GYM63DRBOK0gciw528HAG7++5ppoaL9ZfH4C0o1nNk9RSmVaHOTkE9trUnTS3WcKzud2J14j2udw1uVmI7oIl5melwP+LLH0Co0dokZTbjjDZAtP5lyaOJzmpi+xNcWj1ebARkBHLWXV+VykqN/4oLrUmaf9BeVE+Gt/eiA7pXK4hjO+7u9J07HZVZE5RzlcKcf47PKxhV2nB5Nu27/4VemNDte9IVVwmn9z0Jnpx7sk5oeKPxVq+5Flz1ay4NXTKybtt5+rCfPdORmWtsXt3einhlxpg/e9pw5/DlQvrxVrJTYZ9/QOIR3XDV9ZnU1OtjIQe0987bYLzdlPsWVFodJ5lyZyLGYL35Y8EA/vKi/cszyaO89H8XC7MvJ1xnRTTllcvXD7ywr0Bp2p3lrqz4ZCJX094kc3503cUgGSDjljek8P7u/oEZcSENQ3Md8AusnfXdf64xv47RN36561e2nGY1lv76Uyq2tJiV69/kevo0XG9ezU6/efPfhIL4lYpLoeIS8ukVmawkvNjN3D6FO3apoTXZanELU8rznrxt7WZoBCkFN08vRyz+1hQes6PauCJ72llh7Diu+L7uxcGzJlzp0ppKKkQzJ925l/ZF19BctMori6yPELe8FTiRBFKSTbsbiTowX2fLIPc/rDj3QqX/7LvGT9rIbqHmbtfW5qSn9wzb591O2LHnYORoroSVEBSpWxaIZxI5bLjJ1h3qFdCJ3yVdiVuIJG2iRZ1REJ0XG3neUNJ+s09G31JV89DHpnZOWeYtN01ho5NaU6r5nuaFIdhtx+f0lK4tLrvc9zCPSM3JGhpwFHYdfo4SzB71Tu/dJJB5t1T/1ktD4XDRI+Zvo19/OHnhaMN+wfDji8H2lkUKzXeU2XlMZZ0YT9Mzta6cOpR+Yeix60Fb4aujRoQMlCbnvqCdXynUIG5zoflkYLnP/WT8u+9uEzHq9SEfzy4b4o4MOGtXU5xZ54dXUZwPUNazdguAF7MHC6yIfnvc4rpffvrpwVs7GMEEjFamGb9mcZoF32ZOVqnw/P+Oxvvu8BvC76oXGGvWGkP72Hpckv4SnOrL743pNTxw2WNOmWZsTDFYovlU6/HGk4+HG603inuPrZTNmBUTiA4Wn7v3yKNx9BzuUNyKqE3lD1eRh3pfAdZb2qY6qapORzs/f/PL55snm19ueRr/viKNOpSnFTh7KqLoZIzh968v667VnS7d7GhwVN1Dp2byR9XnQ6GPJdoNGCV/1czmvyVMOAdpdRXS72siiNXgV9ZYXlZGGHTE6MdZpfS19tfENjZsZXS9CXd6V9Q5EDmRyo2JcMzYcS4pkAU6f429nVmb5rgu+dX/mN/pD1mRppmNOKVM3bu3AlSxUZP6bnhcdBIURUn3nDEJo9wa916uIT1dP5hurYkS2Bsx5bbro1VJwTyo5fUlda6Ge8eMncjwNp4P7MpUY44c05A/X7DiLKB8fFvwsvNJ9aMdI5JT1XIVG5fuQ55ZHJx9F2iHTvj2LkyzefrGkV2MDzlBxr76h+U2ciFp7vM4uzDyRWqlU4V3yZGXWuNc8nq0nFvdh/aVtvqvwvKkOn2fVlW0h4pcD4mrl5hunVw3db89tpPldufS2ED0oOxrLO8DInzofIaICBB84Vynn8y537VFye43G6dzmxocGESrMHh334MekFE8LKZGTKtkd6QrrFYyFlSe21NApadFul14Yd7xbM2h77+STc05TRYbekQN3i284REkvL7Hec8Gh5EIiufvtA3RSd0PhDfaqVTz7tTbnJsnVD0a+LGm+dSlm9nZQfcTEiMcjdp1lg75+9GytsHFKsvCVhvxzn953j+4f7mmo7tWNWn+Gtix0AnHRw7F+b+eSKaGxUbxJuMGn/ISdhkJHd6qtvDZWYFPv1nDfK0smwLB2luErt3OpP+aY69l7DU2elqs9v4a0SAydtRp4Npd343AAYZ67V5WRr2xZd0OpsreIPFZdt2HV1LUxsKZ3sJs733snAlcTU+70sDuzs4c797TgnkWX8/zkqnjQQLCg4l5e2ejhOcq97rHTD3k9YWOn20TlPBSna4qXzS3X3qySqdj9+nhNjtO6pSkZuTI3sZslLUdbQ16uUU/Ctz4+3DbynHEMo5y9AyH5vHbsHKLyCfZeHI/6zCC2qWX+yd5H6jZLhYomXoRfyI1rPXUx/rKolNNS5jue7urMtfgqjzfaJRsvfTt/fdPHUWVmS72BKZIxrZx8nN7iMdaf3mfCxIUrvBxPqFaOUCjN6sYm563CfNssfDV67xuHi5ZSlxRcK0V7mt/NTx1pkzWWHHRsLgqTf031O1Qj67EzUPkjmmWrW+e6/NCumxtrh+mx4Psy5sCWTREOVS0P6UY1T+ViOnQEZnWl9ibjliWv1Vnmdnoo5UguCT+zC2UeJRjjUJ7vsuHV9d/t9y13C1nDVX+lmnHc+jR9RqC9I2Zi9XoN8ebap1VuXaYYtalzx10NLUojGd4MDTECS6GIFip95l7k/ceyUWs7sRLVs++kixIK8R+F59YkUfM2ThZbj+C9X358s/cjZ3uyXd2KyLDwOsLqN5lLfTrkbPxL31WpDr8ZnyNh+ro98+rCcgkcemIit2xWoGzWjxo2nLFBoWTfwOyZyoKcCYQG831PC+/R0VufVr//kOzuluS00a221iV1KCSC8Gms5e1oUOnK7TKk2CPsyqT2E4WXO6bHq0Tf7N8bcul11tXIZddPktuY1HuIswpzwp+uvV5mP1yoknVcSkrOtfPar6Xbi2uUjdvnqEHmZkZW1VL6Cbd2JbTPYAp37EPcTL5CUxDR2SOCiZybMLkoeePcfFP7Q0X9WI/ygZbkqB1Fhl3eEtvLyppZ314JalwGYjPrZAh4vc4b/UqpjJe6IRamds31OOlnq66FJ3+5w6jK0d3FQHbNUDtq1uu/eVAkrNBRcaF3ToE/HyB+Zdu2uhXsFTfthQrF89472h9cUoh81IC3ahBErFCxKlB5Eq8h3WxrY9WCRiJj1UxVEHY2+F03Yq8Z2W9TqW1CqCRoPG6ya1B1ueGI3K+Gtt/2WMOq3nhVr5C7c90SgYWX2kdrrC51Av/pS+1/erZxRcT/7bONf95L51Kp//CMxdFFbxKB+p/NL1LgWT4lmMg7kIv08bHxc8F5hGhS7MzNnXYEW/ma6Dj+s2OOBJYvlwYPKsI0YZ4Lc4Ke0I2n0t8V9FSKUILHBf9ikR0UX3UApQ7gIZ5BFDAYYPgABMDGxhbBZASDLJAMEH6MRfLf3APsEDYHpKl70k1h7nT4EZ4O6gL2VAIdfie30ZNuDPDxAL95hThwYGG4bC6kewhAoQcxqEEgG6AR6CEAxInJVgeM6Yu86SBIZsPDkgF0yNfBsLs4fmAIQGCB/OlNJnQGQIDfrkLn/11J6GhTPwKFDmsB4Zfr68cBVEwZznqAK0gBQA5AoKrD74w1twJ+BDZAhPdCjAHYk2QCC+LPgphxICUADkjyo1MgkwI+DBYA0v0IdBL8nP/yFmCCLP6wBZ0EAgz6grYgj68ppI6zH7hIB2GNQmdzWFwS3xAMwJOriUSROH4UegBfeYC4YAT+cz4Fl0OhUkJhBpDOHPhdJDx9wD+Cy+G/DoapyItqg5AirAUTw0dBK2waZGeQxTcXmwLLxfpuZsgSAP+FLyw7pD7F9+eNNC6VQ4HIYc9A3iAQocuFZT4rP0gBKgWy6CI55Aj+YDQTwuSCWHyjL2rO1wcHuRLWFLbb4stpyG2Q41ggCFM7L7iIDai4Exg/uUdrKwDyIIRCUIBFhkwE8phUBotv/+9SskACm0Hns2ZAwUiErAYP4wIQZEACyY+vszpgxQF8KCwoVfxhMDZfSEgcSD/aXzT/jhm+vfhqQ6iEB5VhvP6FiA2DgE+pBpAgYfioIUD2hXRb8DiXBS5ggc0fQP5uAn4KI4KAyQ4nQIUI7SRz/BALQi4QbgUgxJnBq2SQ+be1YArH77uGkGAAGESgcvlxBtmJAJCocGryoUCyqQRRCNCTBUzzmdII/gz4HT8QxOCA3yOI/HMEfReODAU2oILaCjOFssHCqQtw+ilIqJQAEMo2TnxzwXHi5u6h7ulJR6l7QgnKcyHfwrELm5zNJfoyCNQFQkh+KI/BPKAthjC1iib/MC6bH32QYAg2EyRBmpD+CCG4uugBoDqUsiDekCILsctghQAMLodKoUM6KfHZB0OLC/6gM4JAKHFDz1S0Fo3nx6XxwQvF0wIe4RW+KUAeSOLCx+gC5jx4unsBzOzFBX6s81X5LtmP+IBHxVkgGwIJzNPqh8S68Amu8LnwTv6p/A0Ldz5QjoWTyOJWtYVJ9O8FjvBzSlyYKyeC3/HLx9LCSPvCsXysQeEYRIGTNbQbKr3f/QlHPJzM2QAC2AWVN8AKFgQqMmE/3QLw7DnfEN9zOZ/Ama8kvGbLT2pOIHVhToa/uvDMGJLXlw5Xox9MzH9YE6Kzh4oJZcGHEIk64A7VbhqX/T0+oawE1Ru+bnD53cIGFnsReF4e9jKLACcfSI9gOOFBHoQCk68y/c+W4Vebn83D9oNKCdQpwCmRQA2B7Mp/vJig/+oB2NLfhYCPhq8XJITwACUcKKX4/INdcEkl8CX1ocAhQuD4qS2ox4H6lx8c4YvFXgn8QcpH4UIphmqxFZXKhfX9nlRh+S25vr6QPyzsnYFgBgsuMipWNMjBABtSjARVXyfYED+nUCi6YaTyizX/SBYFTn4QP+1FbEDIhCOc7yvmHw7nRzt8BAwWWFwii68YXH0JrO/5k6/M99Gav2bRP6ogXLVZMPhg43Og1oXIhVMpBG4GicLPWT+yGbxLd8F7cP+kBliZwXOIUKtJhiwNZXY1vgx/ND38A+B8AfEHgxGQl6HEzyPApuU70ZdLIYN8beDYYSziAtKAnxcWewlY5b+E68+NINzY/anB8/6vtHH//irm31/F/Hvw9d9fxfwHg68XtVA4nX/tZzHY/4c+i8Fpaf1/9lmMFhbzvzC3egFH+4eDqzgIkZqaRKQmVgeLI6KIPtqaRJw2gaSF0wZJKKzOf+fgKgYk4dD/1HcxQgJ/+y7GltGOXFHR57pSd4txCubxsfbb0vor1mOy1ouuMDWqKykwX7sreWjVmqnhuLNSuQe8OF3PwsKT3rUvrSp/Sq16Kfq89AneINLjAAN/dsPh3OxvUz1jL8Lspms+TteZJnrXY7XKJ01dNK5efo8JdazpFmk3y0vd1Tfw+7fIkDK3grCs9ynhOc8dtgQ/e292x3mEjPFWa6rff24zSnYSLSTAG3gziEot0ZE9dUTjxEmzIuXiW5FCyISIa+vXBGavb0kUa2bZi1d88k2VT009Ulw+KHdWIDaFFhvWv1T3/KrU85b79FSmGNFO9foqtXZVS8BjaytyRdbvXJnWLZK9BhRvsnVJRKFeif762UFA730VIljIzcle0K5ZypxVKGrav1V1i69D/+vLWKP+PV79JhKv7MP8O1hKfqi9tm68jx2Bj7KdeNgV3Zpb6xI1EAjRrCtK+UMnZgSza5rFsvTb7JapyDZure5ahqfJXCw+aXal8WsoUi0iVO+d2a4tp9LkdIebxnu4ARkDp8qPaUUWuKpjKaUJ9th3Egksbf1QOcGZocILYWXM1avLHMpq9cTdmejMzC/1XTSjtAGtvKsfGG75UvMkmrUjZw+dXn9W7ra9lHhxfoNBbnKcys322vh0R5trhrcif615Yrj4y0c9xo70QMjn/wO6mGOu \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_efdd4bcd-4de8-4d9a-8f95-4dd6960efc0a.msgpack.zlib b/docs/cassettes/qa_chat_history_efdd4bcd-4de8-4d9a-8f95-4dd6960efc0a.msgpack.zlib deleted file mode 100644 index e9b74f559bd39..0000000000000 --- a/docs/cassettes/qa_chat_history_efdd4bcd-4de8-4d9a-8f95-4dd6960efc0a.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -eNrtenk8le3Xr5lCmlQS7qg02Nve2NjGxzzPc0jb3jc2e2oP2KYUlShTRRqoiEyliDIWGZonyRCSoZAQQsi5743n6fk9v3PO+37Oez7n/eP4I+7rWte61vqu71rX9elaR3MCQTqDSKVwFxApTJCOwzOhD0by0Rw6eIgFMpjR2WSQ6UclZNnaODhmsujEth1+TCaNoaGoiKMRkVQaSMERkXgqWTEQrQiSvUECgUjxZWR5UwnsNmqoLJFCYzFlNQB3d2WskrICoKymogBgMCqqCgBWTUVNHRrBqKGhf1GengqALJlKAEmQuCwTDGYi/tSHwBFwCBRKSRYSASl4Kjzm5UOlk3GwbllvHANUVZENz/EDcQTIny6utVl+VAYz6ebfbbyFw+NBGqR3WUVSoW8IkaYAEEAfEo4J5uGpFArIQSApLwAEaQgciRgIZi+tSirC0WgkIh4Hzyv6M6iUAkieCVKYCCabBv5zOo/FAOkInC8kkVRiAxmhZ6Zoy4bApABopIo6ElUUjGAwcUQKCWQwECQcZE82jTNf8fsEDYcPgJQglgOVlL20+ObvMlRG0nUrHN7G4W8qcXS8X9J1HJ2sqlL8+zidRWESyWBSjoHtP7dbnvxrO2UkGo1Uu/03xQw2BZ903QdHYoBlf1sMMulsBJ4K6Ui6isrGU6kBRDCpzcEL78MKJBK0lUAknmAZZG6GUg42QWEtGaYGqsbBXhSUAyVY3XI/2dDX397b31YFRzJCoNWU1FQwykoq6hgMBoFCopBoJBqhilJRR8E/N1fAJ4EUX6ZfUiYajb5BBxk0iL5gVDZkE5PFOJoFBRp81pRDhqyDQLxmY/EXR7ZkGUJBT6oyphMVACU1wAGkAUooJRUAjdVQUdfAoAATK8cCg+VtHP9tjG870nEUhg8UZ6MVTuXg/ViUAJCQZ/Bv2VQBswmCCjafTiVBgyRqEIJKJ/oSKUlX91b9yzQYTKMyQMSy0UkFrgj7pcREmBkWLDEbwUmapNJ/nzLFy0JUui+OQgzhmJ5UxaFmUEhwEAHPIhD8AoPIKGyIijLRG2ThfUqWl9DoVNgWWBmZkXQNjb25PLHCjTwILhQCjUKg0PcZTDoRD6UCjAeNSmciGCAeKhdMdlKbAhkXDOeBtjIao6wKxU4TIFLwJBYBdGB5G1LJEHsYmgCNDpKoOEJ5MIIOhYVEJBOh2HL+XS5FjKQsDLT43j8FmNQAkMJIysFwmIGq/l2CDsL6YR/+UqOCxWIr/73QiipYBItVLv+7FAP83Rq0Eplx758CyyquoRgFwSvSCCIhqW0H9OGl4q2O9fFRU/NWxaiBIAGrjlL1xqkRsD5KKAIeT1C5ZWCMMMDh/UCEA4fCSTmGbtZ6VmYGeQ6QboOljGrn5vWCcsrLm6yt5OZgqu6Mc1ZBH0KDBHOSCgWkB+3H6/ljmCFkL2u8lYpbsClRj21hErCUUqqqGGUoaMv5FOxnbmjIsvdXDVRB480pFAc7iHaglynSDOvj6mNuY0v383dVtg72cbSwsFZSsmEEU6zRIQS1/XhzF3qQs50bg0yxtlELVjMj7bd0tjRge9ONHeygaOKYftqKmgDEXyIEi/ZykiGgJENAKaaE0kCvpJgmQOBwQBv592qtCZhCJ40NhcTWhHITIhMI/caRQQciE9S2plLAUlfE79mJsKFxDq+kHAqVQSH6+GQ7gHSIqkl5eBKVRYBKPB3MhtC113NLKlHHY0GUshoWg1fGYVFoNYQ+VDxXtP2Zy1nw+cA5y45kwwSn+NZvkZGJE+Li/PA6hlhsuFNePhC2GOsUYJ6xfp2pq/K33QePXovx9PSMjImM8VgvlPPi8Ggt9f3gt5O8fKJmXZ9/DOguTr33OlxGPOfb2704PzVdsa2hZrExZCTp1GP4e2l6YSqj5uXi6ItKs4nGzPmNNR2HvVIyTHQWF156zR/2mq1RW5h43z1+L8pQy1NGOK24jv/OV0fbxjVDEdy0TbiDJjb+1kd4B56fklxLckzrOlpyK7slWlZrs5EB2lcntb83nP3F/0d85bniLcjPcwaC9tjDZp2u9jUfNioe2ea/Nq2ul2A7vSP/4zYTgbvGnajoioXYc6oFpHLBT8qX8JMncWndbNJ0hUBRsuW6SuFPp7uYJfntnw7RHrZQ7MO0ItQWbvCyjmbYbyzaOSuDdzaV5B05YFCrVKmWYrJn59jQGl7uEbMfu+OvrLGQzMgNbS5zOsw/ysVjgypyweuAow6+T1PWm5lWHuhusBU3lssPJSQZ5SYfO2RdGzm1Rkhn7PK3pIJQGj1iF7/EJkJ03KCwkNLbvhsXdA8IX0au4fY6YOnHlGfftcBUOftrjd7GVNy5bblZ68FYRPONGjNjqlblNb5dF5/H02b9sjHaMVEKMdmnbxd8HyyXxpxNPnWtvzeoy2PMWy5gWmjdvmv6Nlek0g5W5Po/apsuRIOr7j+w9d8bJhTGl8L6dXVh7RaWZz9egfechu2MnuEt/2qLz299yx+gVTXKdY/dVmv/8OrhW2taLruTJX39s47AY+utRZSHJVuv5SP3sUI1vRfvDM+hL2+QiJikJkxnDOCKJGIwIoEpVuRyuwe2Wiqb9zp3fMqnx9f1Z4toNfeTja2QO8UlR1NE+dGfkuY1lHs3fLgp8Ypl4y7/qfhZ5gVL1OlOqU73E3EPE9/sGNOuMWcO7M/PmOBvsi/jPxvS/oh95rPbroIcf/3Yqfbp5m1JIvJBt/D5iefyUmbxImWBlz9Vetxc+K7zlX93FDnqdYNwLfH7vW0xxR/OED1ftuVLry2t3Hz1pG/d9zR9ukDNrGCdmXCOSax8ossLSZnEzOPFWtsCmoYKHvjasKc742j8rVqS5x7cKp4+XgGIovLuni/vvjecdndBv5W8M1bMgBjJT75oXGr5OOfExNXxlA4DItes9KavKp0dFz0LI2mXpNHvtI9ZfL79RfmQJHl1yQZxNcJg9bG1VbcNQ252bcGfadchhW7PbJfrYpeMuN2XcFeTd8s+LyAZeOQm88mXDf3NYu/unFHagclB6herPD9omePKX/eZcFBXQI0aO3MwsjhItjnQfs/OzsCUc9UnEXdITyTPl7rm9o9RgoIPxzVGpD+vEKIODBuKWZXbpLbICI2tuXMaUfMun9wgLTLpsXDVuWGu54pLjlBT+K/agdPva1+/MFiz2jr80Xtj7HHWnI5q0U+tLaUZ+PvP7EfX2GruXMUSWpzaJf2YN+zH13FB6q7tiS+/9xdp4jrXy+O1KgO1Etd71Rn3X+ihmymKBvtF2+7bEvPwhWKPyP6X07mr8B2un+ZzoxxJ8rWSd1cNnH+EDfN7LspduS8kJdSJJ6je8Q1XLVeirQt/sDI+7dPlrJC4QYZQ6Ttm7bfzUeButekt7S5pmf4dpU8r50JCm+4UzfRENRKUFQ+mc12O6SgsErlddKYnVnCSbzd3ndyeH096X6XEKJ9pvVg2YnJcb1LHm1zfAT5ARL9opBV55RoY9f2M+jjglt+80drz7vlMRJ2O2qqpre/3b0H1Cr0g2ievih1lthC6+eQ/P3GYww4JZzzWFA/7ML3hccfPZKS9xsaiUPnt77YVrsqVMRetNOlPkT7ZE22ptFHSI3TD674jF/K6b1Qob6RdxQU076N+yt1sYfBC6kYcxvn5nQyTtQ8UHrWXtR532EV1bD2dZHA5MMV+P7ZzrG5zCIoVlDbaOgI0fU0juWhdtwvUqBONL43WJYsntNUCkTPjxpPbZI6UjaklRCUU3z2Yle4lLWG05eFMzJrJ4Ixu6Q0WTsd4vnF/ehWwSpOlsyNR9PGx8kEcz1f79NW2nfG7uk6k8lm+Mx54+NySUJ4a6PbSUNtnLBRb4Yh4AnjOXxc/eKdNPKbmmwe1Jyh1DUVtMOlacqAA4/ot0Zo6SnbLi3zRT1+rd0aKVeijUgYSebb0HWwVjzG9KX6cUdNGeLDpA6/qFzDDuj4z/+HYffms6vFbzDY8lle+vDJm44wfzsqUvWUfrfb8W5Cq1VI5665IsrPClHb8kHsSS9t0chENXRGTcUdPt1j4TQyK9TRZDXBhEKSxiIrTKZ5tMTtPFQY/8GN8ySN+jxbRMZ/U0zosPYfWHhRSnRY1rt2unIfd2so/5Gnl98CssOyF16rQq543qiJqAsJ7C1obk+qGZle/nR2LDadJzojp9LmIhEgMIBQs++xG1j0fLNE8xpd8r6rHfT5PtNwuiPvSQ8Ib965Lb/esk/MckKswLBBK/bVv7uKqHx6bEteVFcl7DMfRtdZovNjkeD1Ty9YzYs+Z43yjr7PqGmMCrmx6Vi+wnpVw6AXb/pFiG/4ESg7c8HHXvXVVKSGbrQbNFP8QaAjMyBQXS3lcolP5zAsrprk3ZV9Itwh6412gPm2/hHiFWx2XP/rtGB7Vmdgp5cK1rnJt7K3Z0qGX428e2FmGq1SqtIsNDevomQ3Y8KWzX72d1hPfqFw86io+MKr/oWJHJGvRO9+uIdHRocVcfL3nz8mbqUziT1+uiHn1MIS2p7M2T+hV91enT6amt76u538vXXVbLTr+4S5aVdOHBuYN9oYTx8QjAgyGC/OFDpSOgmZeRK78DsTOiqxg9kT9COlGxcCmALUwfsfHwtkx0x4P/VMuxiWWctt3ze3K/nX0VEnFYYCvvUcDL/osNaKL75LI/BPf5rIK925fsO/X5Oq7O/p4U0qP3LpRSKt/YZywT/XrwLbk8FzvjnvfRH/UqkcSfihf4u+ozBC75VfvkJTpMjdr7haaawERRfRudd5BVED+prGy9Jm1I/YD5oobwibfH/tZIdxt07GKn+vnaqPapusNH3jajp3XXNUnUkN+OfN8J+/gWTmS+3iJwtCBs7g77jdbK6MCjKix6wxqyqUbLj+T0k4JDRc59Qs9P/D+Ym3xhSMdXNjyRZXYh8lVmPkhcTk1RFXbu1DuV6OTb3t97tbHSxhQoughWuEXwbYG08jU75VXSzdNNSh8tSmn0+PFVGoYHohr22I+0gPdh1QMBP2ehQvcO3QA/U7OYeLX2OZprFCW1/TovBBaEKybsO2+4qAul190eOp4UtqeyAdBOw0wM8bMcK8/erUGuCMYq9/pJFzNYF98HIv4KtYcPjN0p0K7FNPH0P6ZmRA0kkj3lrmv9OPwcK9Eo7LHlMSgTWLIBpvqS/MqXdh1c9nWqUGaaTR676rn8u9zW3en92ccaPz2fPxUv8IsN+oPh0R2h7j4Q7F1tfh79/H5Z0tA/aY929luiAsXgnrQYy0M1zYPQ7t9ru/mzlTTZ7582Hgxp3+TkgXKW306/I+pp9wuEzPfwdYP4paFlgcFkoZ7+VKn8XEjtyzzE1rSJFwbDVTXf1CM06zhwX7feuJTIWnLU2v7/VvS31zwFzyztbj5PfLK5SM3VFsK1Z5EbHxIEBQY2lH/1FVfYvS6jAxetLOqNOyb4Pnw0bK76aVP6eeJAmebtuQG6l+9PT/W9xC5bWpdBZIpEqKnw5ca2fXszFvhotvIj68ixAy/Txvfs8pxPbEm5Et0x7YPexP8nXlUtq5L+r6P3zLPQyKMjd3+4YlJvozfVbbduur+u16iueoZPUOLTSaO5YnWT+9Gd1t8vNZmn+/f/kYvcspR+rXjWb172iNipc1NpXqF72zWspDsoi6b7AEpxWbj1VE14z+fFH7zlat4pBthRGuwMr+XkM/7nb4/REVJICZL2WswvnFt45MXrqXJjXG01j6NwEYFpQGWdn9TvlTs5HDZhULBfR8fRV8a2tE7Nxj2fRfqBFbvU+CP2rSy0TSPkQsCMifHzT5Ph2c8ZIQFJBrurdiqNLvfQDD8m+EqwUvxojGGRUFHlcO31byMiEXmrRH/lnSwt2fsHb3cynD27J3IaZOv0xMHioW2Ue1jWL/CPc+HmP+g0aM0W75UuKeEF1X9cfax5FePdDXqE+4tXE03bWJ/pIEKDR/zi545SGdS8l2YVxiC2vdPoVLUmxUvzP2RmPBsvfvcwH4rr32BDxNeSum15PVE5BOwD0sNtzw+U3JYplwZKCb2VPl8OZiyIMX7mVj9amGqBZFVtaX0e8il6Rv0Y/km1ja3+RjB9+3CQvu7XCyQPK25tyR/PDKhPqt+vYk2gROfco3OJ0o/2UJQLKn3aXra9YGn9MQOn+gL3s8QZyaSCKZeklHtr9A/Bz+X6Vsd/rQwPWHW6Ok7zPWgPPPbJcmuPyoMeEQ8S4ucGA4/S9Wajuf/MkEJaOJFLtlF9nR+/SIttHdt7XdspOywQ16Q3bn4Wxfx+k/lvUj1Drdtp/IxBwu98mJlP58eE1JuEqauOUQoXjW4rXSXR9hsTPjax4Oyu0Jlbs4bZV/7ErJJTS/f9FRb8+Nh8dFLCkfTP8TPfH7vHJ5XNzbF45iR7nN3Bvdxb49Wh6taaQYtKZkqqCPVjVskcyckhoYe6RAbuo29+gY/Ohtx5OhEetO1N5ozPUcUuro3DzWrfG18dZcf4I1NmllQ31OhRqo3cZE3f6ITWRi2N6Hwm63B5QztUNxnkVCLycHtcb3pKgoGRaQ7gt4GITykt8lCAoG7bPHVwgdVlY0igwmrtC9VSRd9+zmFO0sJK8E8fYF/FU/akl4rhznZWEkkzSmferO9sUsvxrl6XmSsUCmy1N3FImho+/0HWMMhDa8I3Q9BYRNP1YpuW6xGdcWni16puXp4UlRuWvXohCzfRvDRKvlhqaa1F+yt7k46Is92g1KteMIGvzJ5lEn1kMFPexGS9xukcvGdwUZ5x5dJ/c8FJjXWdt1C60jrBI3ptJgJb5XY2ex19Fajvmc/KIfRFRKwEBkgxykRzfeekI7dIbb5RN4RJRcZ4fETr1UDdat4D0onP1cw7hKZf3Ds6dz969aJPxb61L1kQk6ZNt+aZLT/PLBuz5isf2v6faVtl14q1CUzJe9k+dQ8q79L+P5r9kfR5fgrW0M+7617Yf/5XcasdtzQGUTF+hnZdYLql9/cu6En/FGfVX2hctriXgxq9hG3tjDGPYZ1TnDsGE+t6uef0pKU+qxK3sFTg86qlejLWdvmJ8+3YQN3fpD0ibJ00vh6LvQd/j51dWT1DLfmHE0kzRGqlqEHPnd3HAvx3a1fUy51w+i02nkXrcigI7nMBN6tpVXFFX+s3y1PuhkRTDyRGBWnKH1onijddcdOhmf3nSc75mMFO8cP7dTVtRFjeU9l6sdu6ZqYj2NZfakd9T6pkZi/41pwX0VE5eRmmfR3qPpG506ns5u5eC7fKbwhJluYcSf03EM0je/RNuDHs3ilzfG3W+yC2BsbaoNf6Y2vxbjq/iEV5mQ2cc72SXiB8BQ7LQu1kDkt9H6kPTG81kV44VdBQUik84TiYm1CywObkwaHJ8Utt517ZbA+UNpimt8x9gguVlTkj7Kf4f3tHTGmbeCkwHah4C8RZ+Ryv7jdCtSNQGwcPfp8uPTA1InUBzkul/e0Szy7eOwHpqlC/+yXX3MRU3HfrNPoIemInxMyrOs+6752GZm8vj4bIhz/QrSgXgw4Q/HbTm3ucGbXfGjMmGdkt++oq6xdO8I3+85Gf+2E+S5x6dKrDk7CFRdWbeO1eNA+0RBqETTfEPkulberG1mutkX84kHqYx3MizvFlv0DLX94iuEflUcrbJDU5r7JVrrwte5+xrg7oajhzZlfMz7DKbkLJtSA0a9FIs38oo7T1UYyinsmBvyEDK/Iv4+VFqN2Haw/D8w8LVujv3ij6XplahHllsmjxfmRjarcG++ef72QX+64YSu/gPj2elfE6rL9wT0qjwO08Z2tUtqbUsp6UuWTnRanOjAvj9vfDztJCJBBsaUqTV/xYXrOVhUnlpwOb6OU7Btyiw7lds0VC/RnZe7CfuN6+9KBK/Tqs5bK1dF9RtHr/ffnXRHQDRezfJqZWHdm38feExfnBh2qeIw0GqfKu1uV7vpc0JuxlnEM/VwiMyfvtkBcuGpyjbjwzUUR3NDG7E84W/BL0Cdo6lRpgM6DronBa1qCdXX+HVdjhepd+K6Ha8kVDYQOj36+kmQV9cntvH5D+E+RwBacTaCkss1n65MvD065ECIMGeqrC0OcNYYnH7UfUnTZwVjFXaN16Ll7bQ8eJR7NkMCLObv9HExEPtCwVWy2KxlWkkp4xJcvY3zn5f2GAnNBviPb8bEIx6ze6o/YL487Tacb32IvJaQ8jpoOGxhPyPjyB56P6tOdfPmkl3CHhQn3GlOJmGTr8tcDuS0PWuL23glIzUFr9Z088Tin90bxkKfqo5uKOgb07MCacIkdpboYlIN1jiD7a57u6FxBtOKBxg3JzG76HydL1gXMXIk+U3LvethnPjErskmebgTu8MVVd719pknmJ0UHhsh2H17S67ObRz/Gpkbf9sgf0OyXcNzaWT836j7cFlh8rme/LsHMCdOvtt6aK0Rmp2z3a+WFdzJhIatcZ832b8pUlAyWdz9K7lVFvnWvGKa12Z9r7+odtHua4RhMDZGxAsW3Fl+/sbk+ZJQ6M7vLl4rtvrXXY2pD8rkf+DH/7cZrLzxN2ppLCX1LrnBavOx7MyQs9WLKmm6vOcPL8Xr4X4MdXrr1veZ7pF5MOM+fcck/FOg+IHiRFcz/MvHX/LB984acxC2u0e7j/nvVpvku1Mnl7LKsBJOK5aJrTwtuZFWEa9w+JPJxQO7J4cn2j+Xh8oUh4wm/CB4BsTXjHxcQPxVEqkMlUmpLHyHDB7TPPJeKrsYdaiWavlr8TvRb41fb0J4gYTMSnty/N74oXMYQ5Xf9oEF6KHp+OEckIYvFHVYxmap4rG96/oKXHaZc6s0gDdhWOZtxSvZxy2k36YKtzUci3D73pq/RDXvocnTw9b6qsZyMyO5uxeG5jNN7tDI3rbGpuBIvvXuPpJEOz9Tk/qkPlYOpeyb5d08nxRUSZrN3jF5d9ezpL6sMnAbXQFRpVMTUbtST4y710LWBq3fy1OMw/bjGwPb64za9g7YTplX9qTV1WFGtO8DtyV3vR9zPK6aezG4hHDtDbLutdKVTPL/86nV3pzeJlYe+bf3VI1x8kxQ5vvvDOisv56bRjkmelvl4hbkRbKfovcginJ4BxkI3K3Nr3M4i4466E+9srA8cBr8PphEIbTuHZIsaW83cQw/6zR5nawi+cI/00zrlaNQ6UV2ipQJobnFvRmYVZKtQAmZPCOahZB5cSmfKlAvaeM3tNLq3cXTHJpeayOOv3fMGtfYpNe84//bsJSv86/KyeWp1QFfe9kuxG3LCNIzqGs9ihd3G3bDavMK+F/v8SB0F8QfVN6OtDqR2vrkZ4cx2ljw3VNfboihFZ9Oenbpgmdpqk7Y1htdjbrP6y+Mu3Q2vG0/s/E7iW1dxNC1TkHujD7Jwbo9FakJZwtXgoTiv8C0VQ4yjr8IxG36sG6y1s7iDyXgaaKoVfAFtHl4lyIPEqOT6XFaaP6+eSCrl/3QtQbBhU7bog0etmffNM8QXJuUlwxQfx6lUogsXAHtekrbVI/KlEInrXTuLDDXqG4avOM2zeTRmpoZttZp0ay7WOSni5nc9y7xv9063+mH7w0cNNlSeGrGNzZOaoThPldaDEm8VD0zFoHUVT696MX5XT1O62YmB1uKZQlZsT5m5jab65HDny+yqdD7XdWrEgPuYZO5rlXUIqfdaXvbST4RHmuXEsidvDkfyHbVMwE2PyDu9JRl1mkg02FZcbwa/cUUsvH77mb3GxEpa+Dz/K7c5X48mjzbE9goPQeaQ1zW9H4fUm6LwMa4y6Qlnd5dufKxbjZExbxMreZvslR6vfSJl+yBV1JFvvBZPHXn/TGzXINAaLF/yY7Ql4riv/n2qob1l3zlrzcCNV856eF/aqoL5NekifbIxaXxsQLv0x+GHWSbUkCKMb8/T53sEXnU3zLzKIqsXl+Xq96g2xyha4mb7A2Iz8s5rdUdLxIWu9p+R0hHwnLb4OXziQdmkxMmSH4ulujWzXxw35IfWfF2cGbkmbRkiWq46T7N5fyIg4vhIR0fBrkxnjRu0l32pXuyA9CuLP0eiC3+d3xjV9LG7xoF7cepWza+fXjUbBKzmmrqHH0aiMxoXZ0YzeRaTtJIXP7J7XqL5lHYY/ZrWXdQ5MjZdRr04OlPTWPpCt657cX7nItZ/bLo1/vHc4v35W1MJv4a9FgW5uBYXebkMXOdvdAFcXP+Lp/O9//Onc7wfjqkI/U0jgZxHDM6jQ7uwV6js8tMlA35ED5VdfvWEX73dqCwARwcBHAXAMRhEBhNHYQI+VDrA2R1SgsBRGEEg/GoBMHGMAAYScGKAANMPhKTgV0d4gkYE8SADoPoA8NstEQwECQBnj2AmwKQCSxo4a1a0IgEzH4AN7U2gUuSZQACFGsSZXxJVABg4NvSNY/6LzMrmdBAEGCDsBLwvGRdMJLPI0GICAL+R/qYJNgNPZIBID4oHxZjoiwTQSMAmEKQHEsEg2GAcYGlphaBRIVnIaByLSaVQyVQWA+A8uQMMNoMJkqHVBhCqVAo8ZEMBNQBbEo4CP/XJeVD0AA7i8IMupAHGCGAxWDgSiQ0QKYFUUiDHQgobgDTRIPj0KMu6KSBIYMD4cLwPgr2FDGcvh4MA0EhwUOBHW2h/R1ivIQhvRWUQYQihrQ38cEQK7AXEEJavHxPYbUB11ARcQCIAMgEcCQk/RSvtAfxwDMAbXgspBuAQE3B0SD8dUsbkBBbE+1GIUGw4kQcpfjgINGic8yYM0EA6p0sCwhqgUpa8BYNX2OAIYb0kR2RADjOYdBaeAwQV8GApodB4ph+REsBxHvBeAoEzzpFgMYkkYgisAPKZCT9xwm0DnC1YTM4rMyxFWHYbhByhL0EMbwXNMMgQzlCUYbgYRNgu+grMEBIA5x0Zth1yn+j7+0Iyi8QkQuJwZKBo4LyhP5emOar8IAdIRAjRZXEoEJzOFhrE7yWzOKAve87xBwuFEvaUkw9Lb94c0jnCXIWkHZdCxAB2u+Gov4VHeQ8ApQlIgagAmwxBBAbTSFROwv1pJR3EMagUjmoqlKXeEGpMIsQriDIgDu/H8RlKKShziXQG8y/AGBwjIXMg/8j/4vkKZzh4cdyGWAnC79CMfwgxYBJwJBUAPGQMhzU4CF84DzkRZ9HBJS4wQLhjZAUCAA9B5w0C+sYOwG5vaCWB6YdYMnJJcA8AMc4QniWAtH/MBRGZfiseQoYBYCCOxOLkGYQTDsCT4JrlQ4Rs2x1IxEEjS5zmKCXj/Klw6wAQSGWCKxlE+D2DVoyD6gsI7EbvgZVC1WBp1yU6/ZYkJGIACHjIOnDggvPE1W0/0sODgkZ6yCpAEy5wAsO5C0POYHn7UnGkJUHIfqgmwjqgJbqw9G4lzmYsxkpZRTBoIB7yBP9nCsH1WxMAkVDJgnRDjizlLpXOBqgsJolIgXyS5agPgiaX4kGhBoIkBdj53crL4PmxyBzyQvm0xEd7kEFl0aHYaMCmA2YwrSkwHTktIxyFS+iDS6QgUpZapGC8fHGQbzAzIU1KSMCSCu3qCNLJABkkw4YtJRMZKm6QgDISMLF1RCgjMcBKedWD697SHlDagL5/ptIy2EslxYOiggSMidA35ChkN8ds29+KkNESC6C1Sz7AL+5ECguq2lDNpYOc0g6bDllDYkPVBTpD4CBwIIXrCUhhQHTlHC1wvJbrGycUVE70vKFKBJu1tHAl25achjZbDhCENVTPQJIPAg9HAE9c2QqqNQgakZMTkCo/XCCRyjmIOIcrib2EjT3oQwLxTLii0nBLOUtkcCzkVCAmnIi+cI5DNtFBHyjey+bQIEpCjFqCyQg6ythwvSTDq+A6D2UFlcGETlAqTG2oQNKZHI2gD8QuIhwaQI9IhrUuXxTAP+six3cSCFtDYZG9oayCQ8Mpp3AIYE5xkggMBvEsDvyAUTCEHnOpDDKWJzinBCcJVjj9V2UlUX0hbxhQeYF1mv3FdQ14BxeYsfBKDl85C5a+fCD6wJFfXqrAGdYz++3K8udhSgAZUDi8wZXKx2E1rGllW06VosE0gY95aDV0LVqpBDAP4GsAA0DANw06lB6QIRpAaOhvn0B4uMISECu3AI6AI8dJeM6Kcxw6gKSlxi3O7NKYHmSvLwVOkL+UGP2FJiRnC+UJcZmq4eFIAL6fkVmMlcr+21UK7r6SZwDL90Q4fDgObeBjC/IjCD4qIVZAJZ3jMuXvyHDuKb/Dw/CDLiFLDIPTBsKVM7x8tP9rBFYyBTZihTlLFkJ8YCzf7/65Cr4U4jiW+sD5Dff3KCy5xwRJpL80wn/8Sc8/RZFw5yadSgLhi+vSzUwWQvFv91lOFYZs/+d9Sff31fAusuF/axb1pTERKlQEVAeIsCQFGkNDvyFIQRwZ+uA0KirATaVkGnxMQtkNjaKQqP/fMfrfvWPUSQ3lQGcRbbB6NB+mv1oA0x9pZOxkgSHp2ZJcnQOZGGtj0wBblKUKWuXPjlEMdDX7D3SMZilh/7Mto5v+Ny2j6P8rLaP/mZ7Q/7J2z0xVZeX/7v2eKv91/Z7KcLcnSun/oN8zC40i/9uOTyzBW8kbq4zGo5Rwat54NSVlbyU8BkShvXE+ympK/+mOT4qDk729OcrZh0J1xqihnc0x3r5K/iYG+naB1kQ0nWWFtg/URxqYslj4vzo+0X92fKLMmfou9kiUuZIbaGRgbIczCjb3PuRkysQbqziF6KnQ7UlGztYEVXQA3QptqYR0tQRV/QP2m4FWwdbqJH9rRjDF0cvKMMRU38nB2MUgxMrXEIfR+492fKL/X3d84jDqWFDdx4fwH+745JH9q+OTC/6/Hqa9VcIGtEjVtIvrfS5796mAjjeSZ8W2q19xwnLpO/k0KI+rbjihXle6f6omM6uzdNu9Z6YRES9H6yOGuHfnNa92JDIV3KmC1BaqbtjsLq+o3IaMr9OvIz4EXpDuOlytOz9z4+fJh/W8KeNpGIX7U5vkbms+BP+QQufGbz5TT9KpuRiv/Ip+TPX1VhlBZemSPj+UhJVP1Gtv1IH0tuO5hnb7Ztp4uYKfdPe9dbrnsm/LVMY+ROwXgXdDb/iu8HQ42u2P3uG/2WlxdcpX2XJSeCYoOIpK873aJ20KbOWTuWe47uPW2MgQk5tHYmWk/Jrsci3HgV3c9CS9/WTEcZ2SbWv3jzCjyouE1r9+ulbVdatJjebGohIDV0kr5GOqSNDpk2P05xddrnjyX4wMjhK6otx+Tuh1osclccFXLd/x9BQZJ4Duf6hCSxnTdzj5UVVZm4uvHDtura1wxaMpBX1+t9jox74XrlaJFVjwChRuBgT19zDDTU+9vTmNrSSwZWbEnM5rHLM/P79jUKq4eDNdc7TvcHBFciRLXuPyseEC7fcJqVLulLCP+i9mrh84I4fuOBPYnmP4Y29mo/SDW2EWnbqfr4Z9bGkk90mV7wguO58+2TwVfetLWISAnAmZOvT2/SKevO/UhYIPHlnlWTV7TyFVGdY7BU+2UgLoogIyX5hX7na3PK3gmQq7fSm36/b05uX/9Jvg8b8JseJ/AFM1m9w= \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_ffe06d69-33c9-4ca3-98fb-8c70cde9dba2.msgpack.zlib b/docs/cassettes/qa_chat_history_ffe06d69-33c9-4ca3-98fb-8c70cde9dba2.msgpack.zlib new file mode 100644 index 0000000000000..2d239a04348b9 --- /dev/null +++ b/docs/cassettes/qa_chat_history_ffe06d69-33c9-4ca3-98fb-8c70cde9dba2.msgpack.zlib @@ -0,0 +1 @@ +eNrsvcmTG2mWJzZz7PwHdPVBsooR3QAigFhIBpOsCm5JZgWXYkQmKzsjm+2AOwBnONyR7o6IQLIpy2nJTIc58dhmPYdWlapkvUkaHaSxsTbTUQf9A20y0yFv+i/0fu+9b3EHgksu1TOmqiUzALh/y/ve9/blL393Ghdlkmf/+u+TrIqLcFjRh/L1X/6uiL+ax2X13/52GleTPPr1x3ePfj0vkn/enlTVrNzb2EiTNAmzszgbd8dJNZkPukm+McvLqtzob/a3Opu7HfpnOI6zauM3gzxa/B+/m8RhRNP9d3/7aRkXnX389Po/3olH4TytDsJsPJyESYbf+Kff7g+H8ax6/c+fVPF5tTGppmk7nM3SZBhikRvn+OZPzpvfTtPrX93Y7F5rJ1OafOMsHszaf7zxx/zl1f9Jxuxgtjn9/Pof46zz6WE7zvj3nd89jUdxERev/zezzbOzs+44z8dp3B3m041f33l09Ppven97O8+ymIH1+m9P4njWCdPkNP6Pn87GBe2x8yAr4+G8iDtPBYwlvfM/FnE5I+DG/81vyyqs5uVf/maYR/H/9X/+bhqXJS3mv3/8CwOi/+df/Vd/96vOYVycxlHn1uL1/zIMh5O4M8jL7d2dfufW48P/hJ2UZYcWUhV52tlP0/ys87hIxkn2+m/++He/6tzGK69/ff/B0a8/S8LXf9fr9oLTsMiScvIPB2FZdR7mUTJK4uj1Pz2Lo3bQ2ww+macBHd52sLmzt93b6+0GHz88+gceyEz0+u+m4TmO9cbu5uY/4ks6qs4BoUE1ef3bXn9nq7dFkx8lU4LifzrsXdnqb21u96/1uld3dq7t9tqfHW62P7vbv/a7+HyWEEhe/9PRZN4O+r3gUX4qs/d2MfsOz/5rwoXXf7P592amo8Usfv2/W4y4HhDSFGVc3ZhXo87V33wWFovX5pTvZgTgJBv/5u5ROH79P7d2d6/GvXg07PTia1d7rb9XGHXuJzigzd8yvIvXf/txUt0nfKbz/s2dsIpf/9O9IqEV9r0VXtvburpHEAN8dLanhFO0nf9hsKji8h/OO7MiP190+OBe/+bhg8PD/zCLi2lS4rqVnVlOKLt4/R/42hGGdIb5JC+qG2vr/+uvOvfoeNKFQZ7Ogzuv/3ltFG1fjQfh9tXetc3N7c3N/tXt4Xa8eS3cHg12RqNRfG2nv73Vv/aP552csUCnBgJcgK40k2zVzRS9/udLvau9q3v9W7d621f2+jvbt2/fpo9X+1uEeXu7V7bu7W5euc03+t8SIhcE3//7X/3r//fffvRv7jy+ffT5k7sBzuXmBx/hX0FKQLnRirNWECXFjVY4r/LWzQ/oR8Lzmx8RbQntAbb4BOlX+RoXsEPLSk5vtH7V+XSfEHA6ozs+SONWMBRsuNF6cPdGHI1j+1YWTuMbrdMkPpsRNL0Hz5KomtyI4tNkGHf4QztIsqRKwrRTDsM0vtFrB+WEtnPSqfLOKKluZHlj2CIf5FXpDZpkUXzeDkY5Lh8erpIqjW8eHDwMnuRndK5RsE87zvJpPi8Dpmpl8BfBQZL+9MOta9cP8vFHG/JKbZ6TeHGWF5E/U5bO2gxMUK3OlOhG2g6YuNKqq5go94DocbVoB4R201lFp9IKNurDRnE5LJIZsMAb+dY8SXFJZLQyOCNiHmAHa2lYjGM7acCTrgdhGdB1ofeLmAchmpDGRZCUAR1lnqf4EvehGxzGdJvCFCvKRx36n/5SBlE8zUta+Hw4wXiA0cdPjtoB/YMuLeEubSgIsyi4FQ4W+x8/oEdxNXnurCSygfXG5+F0lsZlNziaxMEsx3boNAkIQT7iHRCRiLOoDAbxIqfBaH+0HoAmOIvTtHNWJBU9QAueJTGWU9HFwR8gx4uSF0BrJ4o+La/TpoNhmNFYwYi+oJMNseMZjnlEZFMG580Shk6DMk9p990P+NCDwwUd0jR4TF8BN4MHGb1LS+zMFE1ChyZ8DkHJb7R5H6N5JnwZc1a0WX7kp0X51Ty/TtsriG22aRsAx5R+ofEGCwKZgJ+wiX/LM5zvXgOnaWKiOx4+HDBfD54RRcejKV2IoIjTGy3afZ4Rm01bwaSIRzda30USEKTkQYdFXpZCqmgZNPYC2zeDb4QlEYVyY1iWG2W1oHOexHHVnSZZd/dKuDsa7MZbW5tXrw0H/Wvx1Z3dwXB4bSe6EoZb10ZXiEASXewPev2t3uYOsaT+7k64GV0bEX+6SoS9pGlAeMeEAYsbrXIS9nd2O3+6O7gyePHwQXbwi3jy7PRhGsVfPR4N9w/DXxZ3X9y99+n5J2n+KDv/5PPyRktgMqN/5mEUuBW26IxoRHwG+OTGEcKTWHHhjsti6Db8otyYJONJSv+X7e4MroXxJjHR0bWtaLA7HG5f2xrt9K5u7442e/3t/tVwtHXt2nC3tz3YHvVHg2hwZRTuXIui7WgnHu0Mui9W7vbZTjF+ePenH25vXT/q97++e7Lx6edPT/cPf5kXX0+Hn39aPTm40t/i39MsOvrsSo/29UFA/8kz7JnOP31RdkFD75v10tV6nB3Qj2vr11s3P9qQ3dewKBmC+rwDAo3CUzz7fBYTG+vSn60V41QkDdDfLOnNQPLK5OuY1tnbPe/tvs80HX6jO2si/Zun2eqfb/Xfaxp+Y3kaSLAx8R0iiJ13hlDzpeVhp2F58u7jleEoLJLOLCFZIepU4aBbno4b5IKozzQmQp7WaMaH/bhP17Hx7LT0BHOSCNP49sXvZblBFqDYR3yB5G/850OZt8rHJIi37dfdKp91eLsv7Xf4T5SUszRc7AV0x+Lr9qdXH8jgG97ozZl+TqQ9CYM1utl0ZUvZKkkImH8viMLiZL0x2R6xt6rxHf7T6VTyUjEerPWvtYOtTfp/f/36iicJGsVCntzebQf4/05v5ZOzgtDQPNvvXYXkzP+4tvJxUkOI9dkXejs7JOjv7OIfV1a+QNIocVHz/C49vktP715d+bAepI59DcPKP1aPDYLRGYzfaZ9QjeyzWDUWvbsaegMSluJCH+1hyBXD6uFb1EmTctWpDcLhybjI51m0B21pTU/xHQbby/JqrcsYsrfXIb3zJKkIcSAfDcKiU5FyffKWCTeDze8/z2Q+Hayah4Ek+PzmrV10XT7acJfUMLawXGRDYWDLGnMVjqdhRkSzYN15TJ+Jvf0siW583Ll/72h757N7t361W2MU5g9aXxDlj/LqiMF2IxiFaUlXORkFa//G/YC7+EdnJIbnZwSRKjwIF8RnbwRLX/3FXwRffHn9gz8yolSAxaytv7RPdGfzcrJGEu8cElS5fv3VB3/Ez1x+UV5uBxkJbdAF19YJXPoDYf8oGdOPl/3t0OeXwWXh7sQlniezy3uy+uAVvfvqA2+3TCxJYiTFEJw5H++xNuBLY29SJTwJvzbIHwT9Pwj6JOhfgB0QZjy0CIneD4Fzq5+eF6n38HcV+ZsD66R7pRglvBl4kJWLMe/M5gMig5M4el4lU38nbuajzc09/h+Lr/zXG4ecqiXs/UesC0dnwLNibxgWkTdKOZ+CZbca6rh5+v2u/AWD/OHK/+HK05UHRlreLFqLbxxPoz95URKG3PwA8kHr54wo51VrL7A3myXdsJsX41abn2FyQQ/cKuIwGhYkXByQECI/JrQNfLora6PHvmCRwUgf7m089YCebhnhHRc9YXTdC4JeYL8GWuOFJ0wH7NeYyV/mGwiQKKmv2sF3Wkp/eSlvvpDfZYnLNPIDI3p9WZcQfpyjTPMx4AsjIf8CayypUe+42/cATM3miJn/QJB+RIJ0nP14FOl4vrnZ3/2OZIlRwVq1DZWAUbvVDlp1sza+4Rnxh2/axmdn3MZV4WGVh9/Ko8UfMOy/ZAz79pu/el/EOs6e0HlmAMHhfDDO6QnsMor5GSHqewxPWcSAeNgJnVd+lgWCDlVYnuAUqjwopyGOvh2IzhrSvulIeVQAMaMv+JxGo2SYYLQJzcVf0fnIgs9lvG7wNB6lItrygop4REgwZVOJWw3gH9G8cUq4RIdHw5ZTfp6/KtwYOe0+mIUl6dsCuHaQxmGR0dnl02BKDC08iUtvKkB1GozygmBdzQm1Cfgzeou+LmKCZzKlgz3F2gH+r+YWz+hlAmIRl/O0on08JMwuFsEhXJMwDdFk/M1e8CA4y+dphOtRJhHwO015MDgehRfJGjHJ2mEcB0/47gbmQtD3fPvmFd3ur/FU2ZwFC8KQfFUDOiIesBsc5Nm4vpqjCV1Y3hIxHIdScvvxcRjOlIxgnIIE6MQczRArX0tIl8+Iha/TBghu09ABXu4dISJpDUkeERjzES4awTFlvBwzvcn4wQLwO6VzI9jjBsY8ywhnR7PShTwNU7rioCzzMvawgfdWYnW8IDvW/pMHJZ8kfVOEtdVVk7ACpWKnMi2BscEB7CyGTb4M1mS5E9JKePgJHNVBSF8SUhUxLFMJjmkdHtFhOmfyOZwXBZblzYdrGcW0jng45/kdUNuEmAhHwPhQr2ifFak8tdWW+bwYKpbSqcXd4F4y7ga9riMjdN7vREa6wW1DBILHWbwXWDKwLzcRUhK9jttIYCb0TrGWUxCxEvd7IReiG+xnOjChZMTLP8nys+AMkCVILoJQT3BGMwQhBCUigkcY945PZYLbiF0RhM3nBPZg7XZ+dD14FidBTNeWzpyEvv46nQIIOL1Jw9IiQhhnI+e0Dap4OMmSr+axnHlGhzXE93KkhIEMUGI8AQ6gTnWO7NEnzFmqYj5kMOTBt9/8dTWBoRz7ZopK//72m3+P3+QGxnwoNH9Jd5DUYB58Ximm5ZaoxopIS4RTKFeCFRUGvASDgNArK7Fq2ngy9l+cEpFJ6HGf4srPPBSp+EEqKMyP0wFwtMQM11eup0cfmH3wHgEuAijwEWdVEO2hB4/kXOg6fB7m3plsrVvGitUSaOLzWZozT7YLJL5BwjYPnNNdY6RPgMtVAPcUb7cbPKiIfhZl5WAltMgw0fqmDaIwqHjHytGBoo2HSpw8P0mXkBbDqBISaGOQdhzzHBcKCFASHaEVKQAMk7917zBYA/uLqklHFikPrgeEZnfwa0SyTPM3pp+6Q1pYAOo1D5Upk4CUhgSNUUJrWztNwiBUROZBp+GLHB7H4JRkGXNpaqzZLC6imxys9dYxKOQDnlUwybsZaXISB8etQwYXLsevPv/T7vFx1usek2h43HqGO4vrCpAbxs0P0vqJ7mIMeuVneHqtz5PNmWwC5TrlLB7STob23oDNXg/iLpEoGps2IheW2dK8grZE8/LwELzkPDLiF2kbm1/bUuBN5lPGW7pKwMb9LAcPJpaLAaMEStiQlj2jfdIyWT76kyfB2kEyr+Fo25GvIk4XLHVkNZ4jZzGEzAZiSHPg0hLPBLMkzpp8TS/MlE52hWOaaQ0JEHS1xPROPgVRuxMza8SBmbi5YO3JnTsHzL/NrWS/WRXLh1FIBIqJBtS/gZyJmdzchy7Exko5N5BVpEMgAtOMlK/C0gUiUvZEP2MRRMRYrsn4UDVssbTI2QCIuWL0O14Wsj4IS8JoA08+kzGm0f3bWZiTQ0AiboIDbqzSH3B4IovNQrqZYWrVjm5wtyxFsk8X7TpYmDQTNAi9hFcy5fbPuCKxgZZRlvOpkd3C0zBJjWhDZC7iNTt05kVh4YS8hHNMYw08ziYJnX0C7Wc6zXGOwTAuWDTiUCd6vYyrOV23wZw4ZA5pQLinILHMBbQ+hMDqCb2HDQGW1alTmp4EdCytEtklRNxUucTlmQ+LiEr4VLGWQxdrgSvL8i0jkROHQVWSUhSKDCIpiS7DSjCN7j3GNTIyE2n4hhlD6J4nEHfzFHgLKk9qVF6khr2dQVymY05UsYiLAuSkwNPxqUCTdv803qcdLfMVCbpg/HAMhM9CVgcCQdMC6ZntgAvZc5WdlTO9SYOYFdLpgPDP8r4a4SJiQqyhMq8KLDCUVXl5MOES4McQbaHV0PKwBMBcY4Cd3Bxnp0mRZ1BdgjUmhpBanyUnyYz95MptSEglEkX4lMY6ZSXSpSHeOoG9fg4e8IvG4PDLd4V4Bo0l0JWhSDwhriBkho55lgt0wbFJezK8FERZJ2SBoE0nTFyUEEik0YrV3T0Mz9x1L+h2SRQcirqIvx8PoKGH7gv8f+1pPIuZ+fEdgJBUrosQ26d7rfo7Dqa2uxesDEBawLogXqYIWewA2KQ7nRqZR8B7P69I9//lfju4d/ezu0/XjULL+N2ZhieGY5kX9tPRM0bZu9lpm+TNASlrs3Va7YMpnzlTkr2giZxMfOmOTwA80mvY6wkaePECL1xJW8+Irs4JpFs+e7rgGeMC/dLJM9xeIrPgm3qtLPC//ea3lvYVpNCdxhFfKqIe58D0tUM6xCwQCxSxIBpnYm4YrjEbMDA3DhwRo7OyZv2JFlk4pQuiSuUqBdtqMjgmj/i4gyxPkjQ1mj0va8IWEyvCPz0QYglOrZQVuy/iM/yq4rvRUEMj3uA6FwvzlLmxtcsv0aXCYngGTKAAF/o0iRukoPY+YDQfqy2FAWIJAuDFFMBqEt6GVUFiNZFFQB31Uvi8utT2lGxRFHhXk3hegH8Og0sTeoo3lLP1l5nmNFwwBkWxaOG0nSUqA4WCdMcK4hSphEJ8STZV2phnCoj6ARqLxXHG93GL0DtN5yTJ1RQFd3gWZ5Yuygpkayu2gRq5HdpQgiiG+EOIzQxD1mfv/UJ0MWc1IhoA+wgYJ6EQLXJoKLooPWxVGUCsz2dEY3FP3ctWVpDoJKZwPoVhrgpGB1GBRT8+cZIoYJ1kjSi4X5s0gfkSJiO2AMZEVedgAiLPlpCmWNccsaGHFX/w5AgiDEQrw2t44pTUCyG6tHyCb5A7MgqkbRy1kRvqcgKrN2r1m+RnTGTO8g79XVkbKSYBgWeeDNTUH4QezMKkwIrXRiQaQYiyZ9HGytm+ZWcETR7PE8YttZWJgaQ0KwbM15lrZt6LpVgGItiFWNKr2zGBWqxBMs1pB3Rr+RlS2NrKzuelwNxYy7ASAnexUH5pcHkbvKVGon2SzzAwTGPF4Yai1quEB4jMmWSw2L4CsRI3/PtcDWv+uJ+QJp2oAeT+9aCpyAiKFeFYhWZr2zMkF8vGNs8yCMJQm4xODg5PRGQGupGxVJGopFLHVJYM9d22kq6MpNfQEsBRHEeQ0QlerJ6ZzwHCgYztP7XW11Fw6c7zSXAjOD5+uXbeDhbPk4BkCv7n18+T9ePjV89fJjd6r/4su9RWonzp/BIGUu2FRBddySV6+ZI5GGxdKK/Y1y4V+iNeE81RLfxYA94UJeTS195zLO4is4hxmN/qKKOJgok9DrfnfegPwjbsxomt4F4Bp0mpOZH7J1yJl0XHfjyOv6JNv8w6vVf66fg4yul8zE+9S+K7UNMDra+cz2DaA6aDxnSqOSOZ41sO4PYE9dpBVONtHx9X4ZzBD9jTzvkA8NcL/EX/kGXgmwzfZOvuFI6PU1paEsi/X+i/s0sNYxkWR2sTjYuFFcKyKCEWS1DPLuloCKVkPVi0ReFDumrEiybn6gSq1HxojpjO0WdYaiWN5vSeSkuCrk4TrR2OmcRfNMb0OCspPDEos7NYIaKQhVHfoOHbJPRO5AWbsWD3Y5EWUjdpnad5ErH5e5RUwMB2QNcZ9A5nVcTjeRoWyddqHYQpHqat8DxBzJuoAPm4A5NNmkzyPDIc2Lc38+GTCABzuE7ILgBiMpXRlIb5jOnh2iAehlA92IPBeMpCuNI1diwCc5ZgVq63xZBLaE36Kgsh5Umw+ZOgE+z8xJKLKj8hWTeI5oVK7bxC1UCaC1YUTYqa7Kxko6ahkTj+8ZMjvuMErpI9NxIOZGDHNvtJnQph4/KVRCEzghlgKVfYMaJZ7V7hdOmc2g3kExGyjgkeDho6y6+TYlWwq4r4pNLkqTgCvEu6xBqWyDzgBmYLKABzEp2RaTckxURtaSMdVEwiZsrILgpGCeWQLB7jLOqcg+Wd3MhdcRZdeL8gz6ZjWCUn0+AOxLg0lWNY279DvIowgwav7YNjLpRXsUzDm4IbBckcnXhGpxrFdSmMTQns+hgK7KwjTNUlISe4g3Y1CQtf4YzEWOZTDG4W4BRSHZ/6SPYg7OvifROrASwqxp9hVPlytS7vNFiGKnbNcpTZjhXuxzEb00g1qlIDzXawf4f94rTSTM1ftH67S3O2bC8Tvwp7qoyYxCdHvJfx+iw2Qi8u01DoZobjVhIcR0bzEA9gJPKTGBg8fwjLNNbgw3qD+kTYMSwIKG7TyuNShICkuuFqYGiQKXPbw4ZWJUCHdEK03NzD3WVNg6TWN6DZuqjJyzdoGfk0FCCE7X+ymMHoVqqVlo964eEPf+UcCLiqFRbTOBSgp7G6y8KM/Ap1i80vxAlZmSYBQMGL1wfxJCTIFmxpFg2RnaOqAMhSzcEbrm7Wo+4CXZLsWMApAQpAPQY75ARY2AILdBwB3drKaFWJKqcEurYh1/w+HWIxJ/4fKqUX5x9kEFYNImsEHfiyIvNLe4vN+uktls6xFjNnk7UzYO1VZPQCtoTjDJFVQ8KPB2JRZPeoI1gwG6TEJgEVQ9gkXJ2GRBY1TZSbi1j6CiF4I11iWE2YAOVKzldvohs89L4mSOpkjPH9zrabAsw0i3EZYIqwlwQIERYdCBlT3B/n1ydQW8STgycyV4wNTOtPwiKPPG8hZrp8/V2A5LijoVVwaxlrUel7pe/eCdaY51YGfdUzbdDTIqd4ruTRBnG2N71JsNbbNdxcBGsWC7xgmyWTnr8SIPqnt2/RSE8P/qwfrN2Zh96d7l25btW++QzXegAxLSgTFnyNF5oEUJjJnh6sM6VFeFHGBIaX7wOXd+kTQSLXvEgCQ8lGFl4GnfIM/iaWbMXplY9GOglfDI0+mALFEaxgDHhi6Ldn0Q2eTTjEqCYIzxCDBfeEuZ4ec2e+6QOVt0Sk2Wp8K2alYzZTGjp7RXz+iic08P6dNj3XPDHshbdMD3n8Tkmm4qJvCRRnL59dN3jMZsqaSQ5SXUkaVAZTzFFjM4neHkO7+Dj2t24zWhy3kKNz3KqvA3Pe+eUjcRyGkJzDr+Pu23mBF/FwdJbvmcictVsJc/7sJFjkcxw4aeIVZE5MMInTmVghgqgIR5XwaQ26J8b17Td/deooGeQNmnEAa5FTQDkiS2y/oOrW2yzRRZCdHz54csieIYjjGQqKhJ6yoevprpMsvZiJfVwXr/8y/MiZoTz+HCspBoca8ulJZBv9S6J4RCOG0FSYCJvYjzvhU1OVwYSRVWYhigi0eG+z4tDKSrdEDTBShZvABZGwEi7khmmrfde6cJYCjoDxsRSAEMFXJvGjZNZIW56H8PIRxRObVVwN1zVcB8NKAjHtgqgOUf6EOMophLsIGGrWrRujjcJMR1jNVz8N4RrFwYk9KiTx7CyQHEG624fzAUS6sSGUoLoEyyHSvs2Iuj6iTPFwknvfm/Wuy4FMwlnl/cpZqusALAd5HUFjNCh8ePSQAwaeqc3MwPxBJSddLgc9ncl5apAS7Sw8w2fED9HcoKKCMsOwEH+9NXAP8zF82dapYYI2LS+QoDC1gneXQ9+ABQMiTfGpTMHQNyFmQ/XCyiW6AufltAzWHiYcINO7trO7ruhqDqK/2dnatEdwnHFsWw08BwSevaWYNzEqcICZDx2RnkiBI9ITDnDk4LoQ9NuQi8Y2TEyOPoIjVIJ7wgisVsxpGWJGrUo2z4y8gvmA8mar/t0ioRHClb1atOy94+yu8cxtYI40FFduPW4PEWw23m/EOgtT5lMQzLaJajTm7gkYGz9vDd5KQCAQDSH8iz0EQUmRLzxYScggpcxg2ABpUWIwUA8R0QMfg93CTNwvfGhTuz2mVxFL0LXdASA+qSF6ltmVqvKlkR3iY5INE/6wR6EyUS3K5TUoDsc9lBgCjosphOyExL2gDBd88zVIBFGzg5yYmUbcXSVWqtf8a6e0MP2TRRKXjxmoxm1qgzzFMAdjArMVUo7p3/CkNuiOf6Hi6SCOInFaqP6v/AHIWoRnGh3jHxXkG/rMTJEeEimE5OdQXHTXV1zLsFwVesr+/qRU4VkDOAiX2xL4LS5HVLEZqpbCO+RHVkvnHEpmItriYjkY1fCv1cGgVn1wIcDwR4vNgn5iB4DeVwmpRMGbAMFVzRjSh7C2zafBA47leML2jooYADvk18CUxQpjF+IRDtyNUw7XER+lQEBRQbfP6zJ+RGKj+364ItQ+8S3CX2dI4EVHLVqBo1KqcNYgA+kCQp+70iWJyDg13vhUd4viBEVnprst/d2yHZHVFWODtNCCPgliIPZyNhky94oNT+dIKJoBIIHaA/aeIX52APvo2v6jR+vffvPvfH2bmfocepJ7NQWznwUnK4YQT10EUjBy9hQ6YqIYQ5DpslLiPZlzqAatdz5DxBgtGMb5+rqZxNKq3IrKukBGd/Lg8D5xj3zIKmgHN1QY3/2wnCDclzlsgpQHWMrYfSu/ONemU3lLgiqRb7mrytfECgsvZc3rN5gPT2JjeEItE47fspHCzvifzQlf2FVnXklUGTAhpTaIwD2qoXTY/OPP6WS8g3ukUH9kof54Enweh5N1CbsfGjzzpFj1eMBgQAO9UJcPAivBeozJQnUC/lo3wEaHLM86RGpG9EcUO6RnWBLdL+BWw2GmYkTXAHlAUH3zGUsQ6ci5Mnk4lXsQF8nrneX0JOE3z48lD+ZJisMTx7jKQDBwVLobtiLgbiLSmEOLQFDpHtE5DledtYGoXqkJzjVjW6aJ7Jfdw1XnhWTp46Szi10CegP2Y2LTWRFlA7umGsSqeHHIXjgeF/HYRtDZvANrPaYRJFSyiMUuSuP84o4EviIoTXQWdnGiihcHZAX3Hx0+C9buJ7RKWhv7qR+Fp8mYIx0OgVoBOzj1BpgsHMcAjOGa0TCQiDA1i5njn+LCZmw/UfGjwPGpqcuGyMkTGugV6oAOmTnIQqNMv/3mr8vknMSkMcOZ9YNZKKopIrVHccgYyxY0jlszS9IdAyeikm6ct+8UtQ1KVcSJuPICNMZtXISzSelfyEFekWhhXtIwBRORMkcchkVGPSR91JjkkygCpWIXvnXmCI8AQYPaIQijhgTPwGhiydqyGY4BKY2sqjeUb5nOBULLs4vIz+fLeJRDby81KqYYw7/Ec0nGE6m8bNTmM2LkLOResCWCM4MUVdkGzTO0SWSrkhSPySGXS9DqBndxeaccsSgLFAOPgSVs0yaniyUqNp5qFhIsSKHn+xQaBQrRdoTBHztFfoQZW1J+TIAQX0fN6CGBb//B4WGwdo+GGuT5SbD/IDgUSg5NRYQFuQbIiWcAqieFo0xnXp5JJrQ8grurZL+jWaJZPsd+ncUEa0F7dTuFwcfhnAQZpDslkDQGcxvvUk3mpfr0rBcAhVmGMKmLXwNBrT7ayZaMX0ZlCNowgfZra4NjkxQ+GKprZA1HdnWK0lEjG1uqSVFuRL3A5pWuEbMkWj4lyAr71Qdw3FESMTiZCw5z1Disj2mnHc0LphUyDK+ND9wMJiELSRbXt0mLGIYkAawdKuFb5n/K9ziKmQSn3IXiyKswbmWkFJEIMCNVZwUsWX7WL1hEcEcRXDpHFAKtFi56Ij3xy/NX+KZuJ2eBLTACGxzypIbSYr9qB/R+cHxc8GeJiSitnKGX0Bo77BWRkAA7Rn1qGkASNNK47Vt6aXcn5mD50lf1sxiiABMc0BbJoChda9oc2dLlJK42idRhOS/EXScq5897m0uunY+5Gk6AtGuOl9lEvEw8PBG+1RhUso08k65nHmdDXNYZkJ46gYZfoq4OyYiebRC28z3JL/sU+WUm0SwpfbuA5DRJ+sF4nogkgEKcROdjjW+zSuEghpInSiFT9nbABTOEj5vsIatm5ANIUaWmH+DejFWNHecmd5UAE8wmCwnPF53amGXY1kCz3UUg50xjoUpjz/cC4YWowjQLR1HIIpDEUNe83y6w05iScUL7QAnDTpn1EMPGZRPrOOnyJ+LkhT+eSKM4v0lkitPUBDqP0lw8AkqU2ZwLZoMfWe4SGYCu2DTU5XIIAxZvdRFYpUCL6YAQYS+nzUfkYjWWvYX7OqZmsGDE9eDh018cBGu/CIsZQvm8rLO26r8gUSRmPKS7iDv21Ji52sEvTNQvn4ZJ8+CsB8Yc+AbzTrmYDmD3Dli+qGJnCF4K4QeIeT2SsRdIlgdyoiJ1XkkKZiPQilYnThtIPFOsM3aB7JqU3JnNC05E41whlsk4FBc2E8ny4L/oWGAv1oheZthstDVZEOockklYmiljO6XKdOoSlUjrKI5nzqzB+FWy4dKCRZ4jXWSCJM4hXPk5SQ9iphwa8zh70M/oIgE5EDkvYSYLuo+RpHuYoBLwYj++Q4PaOUE0rE0heBAyCYlxexkiHNQzJKWat9eIV0F0JQ6DmXtF2FtyZp9AkPO9iSEUAxgOsCHNwSlFJ/Pi8cpKY+L9h0y4Dt/dtSu3gk8IkEjH6XVE5NH0exOimUt6q7r/C45Ys8W4xA87YZ8gI5/dJWkFCcycIoyq+hDY+pkuHtdSDntWjoSwt9uM1OYAeA1SyyQBJ2KXPjIlS4225nfZAi0pJG0XBGyVCByWy5ClM76FaPujfaQ4MVnet1HZNq3qISPV9eAJCH4jcxTrwHuaukFsn0T8k7qTyCALkkUEVzTgQdZeo5+cWSyAs3FNnEoRcrKzDUUjOAgZQzw21EyOeaWXFQ8ljMyk85kwzkZeuVBjG4WDfHBmfhEcI6lVIOj63/UTn0EFSkcdllPIwfzU4fUknY8TTXt5TBSbRF0s0toysFq5JIgIySMXTSz1FZbC5CvDO73kcRPXm2TWCNZV24JPxix8DSGxAZkDmzwVk/4MoZvuB9suzQaEpCBc0HjE9PfaTkpQjfvzMSz62P3aIdC1nn60lByBzRhwhaVNHPAT5GhiBOEIdTPZZZIepbNBl8AbFUdohsNhXojN1gvuCby6L5rNq1Fv1uLIpfDrAY8us7wRzt/rrY6y8fa/OqhmGSjswhWWBFZL10wQYFu8ebBlIwHxyIKFxt+rcxqmRNYrOoNkL18SeAuXgdjI9rUp2mp0GkEGCitRh2L2MkOrt9gnQTH01p6cEfwI7eDBnXZgbD4SPMNWH0MpeYIFn/MoPlsOmkeke2zYCKQz3ibtwHi+bIIoIjNstOCexEHSjQINhyAuFlreu2xbrFqMQOpjxYb3gi9eHrfw53FL9oFM3SRCDi4+PU8ifEE7wu92Y4vn+mOJX2l3JX7GSETBeCT2DxxLSV588enTA350HiW59xl3znx+9epLuao6HxHLOEVGE9EvPcDEj1PVODJASNJ5/OgqpKYQkkosgNV1TNEEfgkchdVpNp0jnomhMqb5O7q941bNsxV7AVPseeDtiStY+BDvx1oJLLh0lRy+KQ50GV/2yz8+/PTwiKOI+H4jqsUUi3D+HIknpkN7+TLYtzefrwKKZgWvXhkEZtJC6gzL72yaw4uTZGYtABrpSIgHmz5ArCGzXIaUrvPIXRnBHUKoyxXTSmAV4QUCGuDKFVv7DOI9Uf9F8Mnh40eIHmw49SHniKiwwNWykbO8nTs2hoYpku4EKk/lR32RDof1MQzpLdDK4L7+jHfuCdBg1/TelKVyoG2iouosFFeR2WNnKr6UOLJo46218qlNlxOZWRLQ0+IsRFxaaz6JHfEuRXgysmyc1ix6So04xt2r82PIUke9IPwQq/uYhmV1NmQbYgSHRVlZRi5lSiY5hHDgUTe4M48NDjeD20xUm6ViSvRHSWrIOXQf9tkvkZ2PSSXMloir1QhYAoFjhL4QjapGoxD/4pFmx968ZGjhV2pnXN6lCRNtLkHwpzYbSWWwiJvAZccMHVlhqzE7jIjzwEaqobAYS1MApsTlcAvEXsx+OcZ4zV3dU/q5Z+nocUvCFeQ7xieRqjSMwUrPctbHLdbkOWxhacOKkY3j5atgLFoqo/J1eCK3W4EKb4UHTcEFQAq58kxFLIPfk5QmK2fIDzaKuxb9KfIDERtPKqgjyTMT4SyExCBHkpnYeX1xBYbYsi/1SgV66BJ64PkkLFsQYcGW0FLHfBl0YHUpggdYCBMe95Eg1hYwPLFyBT1wxFvEb3LlD92Vp1/lu32OQGON0A5y18GSnnsisdKWuH1Oh8iYJBbKMCvP1H0PJL5cOsKgaBZCX6J9SLYqi4Oa81aDjFAqDzzQIoWIhSS0L8rEFPhhxG+egKERSvbV244VQhBmc+NoxVvOWjCCbQXEtS3bq2J1TskFtyaVKnaPEgJurwdPjchpQjkNUdXUmXK1CGrKpknerpViI39HmLuUvBmcsyeVsgyIIGB1Is1LYejWp4sM0JizDQ2nY817j6tg3NX0vOGinolhqCUQjlO4mWg7qEnqj4SWuKZeQsltKAWuXQnzvPg8HNZfZ/7zoHICjMlEaAREsBlnOp1nXG1JwsGXqi9pLdrrTAQOK6NH+fvR8naGbko4jolZUDZYoG8PF1B58qBzC+GOawfJCnXHmkalfJKUqzGW31r1JFHSOk7ngwrI5m6bnruzpU53jppVpVetd6FDtOVxWFcYEXBFPO/vbnsZiBHJgfl4HtusCI7+CXZ2r1qlujSlfDyVkrVJ6w6NEsRZxn7MjLp+YlaOaYU1C1RIWBaFkmAq1QGnyLGe5FNb9pC+g/9ybusxTdlnPCHsRRI97P7+91D85kjlmcOJUWldUrtzr8zXraXULeP3co5Q7E6LAzI54OR6W1IMcKltD19aWUusRXI2xiahrpW5Uc3qSZJRPmR9yRa3miKFiC1qqdU5+8Tfynge5VL2TFVOLHGq1facESThvxkxV6RG1fH0gZZFMIjscIWNEIYOmCUJoYATrFbkxK88hXBIcCJTnYkXKqEllWon5mXCoC4ql+lIGuMJHmqsPP6urFgWPOCM79FiNcD3gmTE1muxq3CMf2M7fsyAeg8UChrRYY2sw8RHZ1M1lO+zet3E/iOmU0fXa6YEjKsUeq+RDKeCDRNmrpXI/gdGmzE7ykaO9hesugQIaC5RIFzrJjkqY0DerGO5bDvScmGS3IC6gSlsDQf4o9NrjuMih4cm+oJ21A1EHJYz4nk8O4ufZOKJNWqWtGY8Zz8e82A0UluPuzKlc2AGVdkHV0YrpnN0k0IWkU+ESbL8PtsYrA+6HvcsAdl2B0fLa9STxgEb551QO8Zc1IwQa7Rh87xxDeVnBmITGBp22qkkMYfLd96sfAuioESZN1bOdZywV/VY2Z0YbDGHMacrRHM3jD+CzJagosHHjBSEGLyICB374kdso96YkG6cbsBxG9KFzUwYGE03W/fPFICQYGN2n0Q282cm8BLO4Yz3SYU4T4LEYUUMgnZ4yKn+LFffSUqOQFhIsWa4I6e3CwLe2q0iXGVGbJaVsgUXTK0T1RsbJtTelqqmHUJUTqJQ2zmH84uwUE6MmM8plUFejEMEnJeLjBPeCFxRMR9zfSNes+AmIr44xy+QoQW1HDFNvAqyiVQu4yIFbVPEoZQqj/B7GLE+XVhpNzLiqVRawYxwZ5kIYGT5xlIx0JVMsVZjLtJGVzqzcU9iDRMzmlWx1STc0LCZdKDENjbum1FFh0wKcblWCgdjQXd5G5JHyTsgwrohcpUJhGW2WK8NqcpBKIYKoQpabkndi9bl4daMYWzSmAZsOaWMBOXxmC9CLVNXA0IcWEWnJa1JiwG1tQqT+bdoTm2/HhOydLTKXCyV2mpVRpRquFJUKCcqrMFIg1w4Uxifur9QqHmboWkvgsqKHMkJyxMaUUKIYtoofnE3XumnmwGDE8E7PxbJ1XkQFKKJ2HqmJDfTXFTJl0rnMqzvo7NLw4HK6kpdOWdXql+N/plkyqdIQmJZXEo7a/SRrabHa5YTVouwFSBMBY5GvVEt+FZLpirFLyp7T9TVSIuB33zkvmby5fkEwVaNpw2zjdLwrHQhQUOWl7mwdfBiDr+0leI8WImZ1RgFbuXJiS1ytabp20g0Q2CNSXMFOsRTW192bP2LpaOOHqXh8MwMQW2eh1sITtta7NpLMRteRWhvXM/7agow2ihwGxjA2c10zOpqfABEz+KqzYyszsXa1m4CCVW5uFbuK73ZBOeZpQqr5KLFJjyB9R4SernEMFP1tlxvZWZCJGA0Z4eVKXMZcHoEdlswfWaTvidoTREB55LPnZW5UWKKiKI46nEcTMOsFb3gqqzsZ6lN5Q7ourNnhxrtd91bd4ig0BFNHemPSs1KuY6sJ18nejKM7RXlfEzwBKlxBKHP3xeC4okwApvgQjcsSv0ujG1Y3LzkOAeWldkOHqsDgEiJmOlTyRvBduRUBgnhZDgzudQL6yCMjCMfHlrVTSVg0nAM3KPMURQZxuA2KwvliS5HEA4ygi5dHHLTbrDNaVI0Wq/niTFbuz9ZD85Yb+Mux1ohZaDmGAsAS7NcDTOeycFLM5bpri6rXwaNrRUi4nK2V7wl8RqK+IUeNjY1ze1pXnE/sRugHexoBDMe5tS5EMU4jKwp7KHfGNVqEMr9oPjTzfhYDUYkU2kL30Mk3snql39ce0KKQXtJhuJSOPDh+vEdYqjv7wSnScEBtjYGy6TF254EmkNfq44t/X+hpaTJqXHhWZuPuKnpkOjbQX7u56G2ayHPINi0JUI8bzeKPhrLKxlvUhOfNz8sQj9CTLOvQUjt/Kdx4HUsKbWYihBPvDtenszIVbYKsM2sNPWpNBvMGEamMap1JeW09IrZuSKivLB4OV+5rLyML84FYk4TlstVMDWGS4KajjPNyiNJJw6ne8YR1kgBkigipKqrGcskt6wb1jlknVaMSEU80TqL5kLLbKTneKtcWSFToo7j1BoGkbLtxKE2hxMhyw3tt1mxq0Ui2HvaJRGMOU3HlvRTu56J6yB1hCS6gh2fzWVICJDytac254Yp5h4hPpcDNlKQmBAZzCxgNfo/KCa164EFKk4POet3yBZRRvUpEoRCLkjzVL7fkwcqTR8UjQkBQaifPeSsigf2rT0/BJKUqSxCugZ7LzhXxKQZombWScAOOIEiptMV7TmyAe3T5ClIbplK/4ajlUmlAuiGZELUOkVYXN7zqHPpch0lWUS2wgYEZ/MtxfrKddu5kvi83giBYavl7QyIDc8qDHw6MqjauCUsQq6KgHINld+2hh3jzQ01n1wMr2BmyYjXUwkImzUaibuf0g3QIB5zw3ubm+IW03Pz0FflQa9s7JY8WoapdOCgdeuqjQezVLOGTd3xx9vwEZWdG6Gcq9OCJL/UjtZ11bC17t3TWGjrniv/rJ5WrzSg8kC/4s5y/ps+bCdA9JWXdot6eiYcz2a1GTosdgpbZYxnOJUwKtTwMkA25XL3gpcPwEckQ1p5869eqRedJv7V5VJMHlUehTw3yaDc2Log2bncC3rwoDg/vwv198SM2tEB9JltvIL7qpQUsgRsWuFJrJAw6aUuhblB7gXiXdQ7XA1P67AWjtesiy8G3S2tBtRgO7Vg1iXr7RO28tUjiOBMn2fKCGvOIhRtkFIolUnScRTNpJr7K8eVmZdMqmthFDZFGWYkpFZbDonKh3Mby+7VW0BGTDJcVwMF004bLKVrMReZR52wL5ozJRYmDxmuBVfgm2PMnph2R7cl7dkVOtY+R2yrj4rwLNNsLOCYzR21RZ9c4wQt+iUZcaQjLJf/tk2bNNqKExhcdya2ZWBW8YXYWSWGUx1MZQkXy9jGDywxLVuovi3lzaEV0YMpezal91Oz1ROXYkE4j0441HwkA4nEmGHUrqGRVYjU03tWufCzKWwnY60DShfEto0SofDly263++oV3xcXJQN1Cb7dkJ8Ikw4MRfAJv3zJ1hvL3fcfwDXoG5DULVx4jgR2oYbpGaoADABm3o6fU2irx8Yxxz3ySoz7HGyXqBfbS9kFDKkIwR6lNgYwNVpn84JOw9Q8llI248Qkx2SIUh2HqXMeCuX9+PH+weEeGsQ0N8cFvXoEnP4Fv/Xpty2p2r0t/9qRf92WKCAkefDI//X2JvEfeBgkbkVMARws7wl0Cril721mOWdbJlPtgYCgaIgdRjypEyt2XXGjrz67uxd6nPMMqSSB+tNrNklURiQaz7kUAReOESVOmxd5TLrtWqAIJpp8Gr36Z6R4clgMzwH7OTxwXDD5Ud48XSk9izQk8duY8GcNuClZXhVLaZTPIXl/NedYOu2aoc+xMfO4hSNASko5H7jaLpw0ZYYTyx1WCNuPOC7AXm36JEpW0Hcc/3Rb3+Jj1Awb8Q8hDEYaUMMmgehBDpbB9ZEYGVoLgf6WGFlIKySxLMb3YnZ5fibf+C/Pi9S8ioAbIx7Y4Qh8h1y0GlSA9UD8wDmMz6V9njeYgMONZsIjzWfRPu3Y22jDJaSiNrrSj+XxT+KFP5w+Z8ejY+BoPjsYv4SjlKFKN9YufIXs467NHPF3b5yY6zWlEACextzuhQtiEErgu+eF/c5/3X37vAFveQuxHHb8q91AmrLodcLXaMQSP6/y5/jCH1k+exDXMFIe6RqE8DCyo8DO9sYRJIEIxoXIn53NDdF7T4/YZgWyGUnh++Y19G0S4j1QE8Y3/szvlf6LorUwtM3bW2h9FaYLEilvExPj9cvn52Bq/tvy2by4DSNBBR1KynSatzWgY+ltdQSAotdOtDbojjnMI1idvKPEx4vWgmFG+XBeunF2uxoWFQdPFsS4MoYNflUL0/MZf/0W0F6xhpA4YGmQKYp+81xjjt3Ljfvau8plmKLgiORjoQOMF/jkv1bHAsLCOznRYKbxfGj580w+uZf6hHgc/HXbxJ6sHU7mFSJ41veUkjw3cSn1q+UiBGm2pyYElYmnMTGbgAtmgYxKtjqo415jTltiabwvxU+CI9/yYSNEmKfAPbHV3QmMxWrf2duB5GMnoIpooFHy210+uMC4rp54pvW71uvCi78tArGp+sNt5Ng6qNgtoWmu5m0sXNYwXS8B3U8Sy0f6os0dxG5vm4qLpvSBa9xoZhok447JLHQ1CfEeJygyUFTlt5aoemCHJx25EAVZjHZrkpLw7L01HFZ6UQxJomdJZBBrfA/HUpki73Tlk6lGbWnkkvZiMwUtUdKgXptAIgk1NZsDoUxMAL3lhaVC4HOuU9JSSYqxkRn3NHL1JVBUG5pxQH/tFugvfkgrI/9e/SNzSBLi5YeOCmWDeYodRcfHWUfMaFJGBvrRopRvrZVOXmcyZNpuymhD74AbfTnl+XIWhye15ZqYwIUUwlmYeEC6Za/aTgYy23W8vy4c1fIc5O/APQuUhwT1iv97V1C4lkdj0ow4dB7ahNI/9IjupqTJl/VutGwqFIVcy55IumssvbHOJjl3vTMM2So7xrjCrjeNBhAJcNk2CWW7OWnd8ywtCU0pBDV+mtovrs8rW3JR3MI4M6SEXS3tBLXFEFTk7EChF1R+30WeSTnYuubMEdIcrcijGLtnqb4SzSZDNsBt58Uloi558EaB8/cqu/f0Np79rJBqOQQuUVvM+ukSkHp2nH3Bh49+VHLwoioalsmRlPIDbiVLyuwVrBX2ZqRCJjHXvuMwmBw+dL690ON8cLHvh67HoQZ2sOVpYQbXZoBiECz9eHHxZvh3jy0+IS6qXD0O/KrBE/Ow0c2Oj7R8thLpckCGzQGKU/UsVJ2MC9azhc4GlwOAGFOuWh1wcgWXwPYs1nOQjn2kQQeHvJOHNH9OzG3K+rxICSR3f3bbR0Ou44PftTBLbBS5X2iBNWOjIL39gnXZyPMViztUQvI2OO5x08PAHJkNG1jaidh5xD5qfNa+gwkPoReasTwPy3Uaug95tBlT0oCEjCyRP97X0hlNHFcADYbbWgaPi83RmpfeaKRDmJjqtgnnUg883xUMSf+7vYwwAMvtMFPlma0B9RxTt5smpNpeGciLgMVm9SWA/ew9kO/lS5f919vUGEDmvnkVahKIWLrMtNrPJhWenHH+Dq8aRqJckpfDVBoGvJhPZybIp9H8UDI1GSVewOLDFQM9GKycWgri8GVL45GYGxIO0amkRQ3b5W2AU8TBOOp1svlHfquGfECIPzT5/GFFH050AhKtp4nXcUebt8otOs44bmEh1g8CWWxi7n7G5hN4e5m2KX3w+ocAJV6i6IV4zE2oHt+uV4H7wZn78cIjOKjMV1gCzQLjoK6AfblGpkIpH4xZX8Lx8XFLRXntqmspbhe/dd+XNDxdvQfSCC7axcqb4AvychsmGo7VuN+cV6fUjiM0fXr3fjj/EHHMLL8iSMFVFTLSrvpPpn5JgUE84opesJ/QzggPIPt8qS4bUwm3jOt00e9Jxl3knPGZZRdD9af8QYLunMuqbpXtmhb3+lnNrsy1xtwBxOO4YsSSpmasuIrUzA+faedYFtc5i0JwBPUbT2AMM0UhGcNM5pZS9FqZjYQrZKpfKaoHOHIbqSj+kQY9Wuoc7VXJ5bOFrGwogUSHO6XGxLLzqs5iAV8lj3mA0lJKoZTrFYv9NLbMjf2xTNVw300qPJfgIV5dMx4OvHL2Nd9+CIfB8IS1Jq2uIQGVWlCk25RPNCXPOq4lWcWyNy/5Yv/gQIF11/7K1nXJ4OPWk1oMC3HjnHPDKDNIUWpGrqWfuOnipbQ1jckLRCZsiN6wrszSvQcHdx/tP7xrHAxcHQxxMLKOTKQaW1t1ot9zsRzxPR3sP/rYvI31zWf+6qzLxGYS0m/sUja/CHu8/fjOXdeVitMKzNKIIOFHe9rS4s9Gh6HsC4kGCxaoudhdgjA0DlYd57YYVK0grljXTSBDWOk7TFVyTrt+Uks+Njna2JfrqjCaQ+I1+AQ2/IiDv4cxqUCR5HXdM0dnAcGFZG1lBT+hk80Htj6qgX8i2VOn4hRbuqZMVl2WW5rq5mDO53rKcTVcesk4nzyve2J6eHEVoSqxVYQYZVnd61r1MXeXPZA0WsQQJk2HRNuSMILKXKLz6/IbLEhSKlzjXrzEdPhyic+HY5NUVPi/Rq6zNNaOVCEm/FgBfkF/OfUsDLlglukazF7L8gKK5vuCDbLjGD8tYzptbBwBc3uMjGEqKbniA8Nld+BUarMCxl2YNFTFluRvHcAo0FkNJ7xchbJbnVe6WYzxiID+yeE7jKFQ7L4oLbA+d++EUSTBRHyagyKJRy6W3aa/adkkhZrXv9KcgoxZiTEDY+qI0mFXxQxjeOLo1kEix8C1AGpL8mK9a3fCVfNxcZrmXokEGCOwmROeasu3PLziuA0wb62PorDZUEsGnNZi/UBA7SBOK6+PFhyopN5hRQjKMmd825oDMrUQ4MH3V8ffQTY49kSJ3690QDP/SMOyZv+jCQk+xP6zEBN0w99TVKAxfv/CwrHjyd9ZXKAxvoPAcPnt4gLD1YoMx9mf//mfY6JjkR7kC3noIkEC2pWTJPDpBxElaMYfSJiQLf7QAsXyzf59ihRA5B9cqIDe/QOJFTTUjylY8JE2hAtF0e8oXhxLOsb3FDB0lO8hYthd/KBCho763cWM+rJ+f4IGzbskavDhH79F4oD7SYQO/tMTPKyZ+EPSgX4r9fNrrglU8uR+Q0VbevzI7Ttu/QB2FZSCeXcb1L6bQi3QDyXA26X0MkX2y4bD5kh0Hxtu2lg9W5RnaJWFq7kVZsFFwD4oY9bqd4PPkvhMJmVnr0Q0iYXYm1LaFNWaiiCdyLTKlOdMrdp2gL6rYymcIXPPZ5ErHBElJcy+XTFn37aBiKatgPksixGK5Dl/3NZPGpZwf7LYTzMywe/pQlHM1Lgp49pZo+1WwoKZKaMNU6tN0w1Lbqmpl/HkLXZ4FmaYl7GFeOrbLd/H6GdZ5ZmNMJPAR8n3+j2Ii/d+JClx/w9S4n9JUuIPKbP9/iXO/2ykxKN3gdoPJkr+yKKaeBJuu8JL0kZ7nAsaSxsTopTcBKTUFHuS4qRNTZJGmi/dQbaKl0TcDh4oarDDxKvdoo17OL44VP5JFKrWY0qK5O2ZMsamIZX52faWk+roWt6MI3O1Gqp09x2GDcYqqn1cDxFouxIvOoFf7qOMTVVgm6nnRa1PJEeOEVDvQOI3tPXzxgY06FkSoViXJFx62XrMYZoZQrZeMXsFOThqCnkE5XbOFPUyksVM3xfxTuYSFE37XtW3i3t+S7BOreGUqe5mstW4nqk6y1zlIU2rL1iqlwLpsxy1koTWN9pccZibqeTOvQjoM9SCsOQb4/IipG6xQUFC0np0ks194agU4ntwzYkYtOcShkzgDOPOotZ2O6ZbZ+LUpMWpodI2UVdaYYj70BYi48A+TtAHuowRVM0yOvuNsbJScsNHzC+kgkBmC07ERZHDV068WaeD85ggWeQDDCDF7bVvIhe2Zz+2d+bctlt2gLEITE+9pA5CxYvTOPaC25pmJy5ARVhXxWzpVUlSsAPYlCYpBu2XIfODQFSU83rIct5+N7hPp30KOV10jtqya/WvpYyXOGtDblURljIpiiSwYCNXmAVQAaokWA2JATO95WOdJANuSUMKR8pVCW3EoURU0M2SsgJWUsh8OrAuEY3cDZvLWnDrLUNPGYagfELKOdJW4GjqBft7Aj4rdQtuJ2IdRFWpGNURDggM6CC39sk8M53Nv/3mr/1U5n2XA7Svya//HnHq6bff/NVBjmylqiLZcWMj5bHOaNzumLBvPugm+QbdjarcwMidzd0O/ZNXv0GLelwcZz+HtjNM45d4Cw9p3nSVoAXbDRJY37gSjqOdEwUp+Fl/S/jpBYmqQJEbHES/vDg8s4DHHg9gdnxB/IBuDr4hkOCLeSEjfJdtMkt7atXN4Ivel8Gz2FYdI0hz4Rs5WQ5a1AR3iaeAblh6VRlAjLiUiL0nUi2wC7/co3heoF8JStIfZ1/0vww+D3NvJnQo4xaJGh25F9xJk4GEUj/RuiOHeXpqy+Uc8FSNAvg8VVj8KjkFHycRh7P06ONef2tzp9vb3N3saYUPBM1tfUnnMV+13/vEAkqpVpYSLyubE8ka7sVxBAUQr144bb+72d+9sutNu92cltDoT57sBXelvAjLCat2J5M+1r7qlpoTeEy5xzdtf7vb621fueKtY6d5CFxbZy84XGRxMU6+rhfd4OAbWx1g1Rk/uH3wlK8pBt/90m9fw8PvZxkpykOMwG2E9myhyir4TDjsUo8pjPvJnKhW/6q0wMHYV7601xrllLvosxIm6GmzUU6IT2xs745Gve1rcSfcHl7pbEfRlU54dXOzMxpuh7vb/TjcunqNxrn6ZXBI6mRmUnQPkGs/UVCM0F8FbBPWrkamoZxEtICoPPQpekMwedN5bNF5bO36eHHty0YDb1rHA69te8wS2lCMpAemn4j0Drf9Je94TeWXDqW3+WVQb/OCri7otiJRK0S6xGiKwKQ3tW5RUV2rLqy89m3HBZ0MZCpYaxehYRGzFdJ0Tb4YXn26vpub29s7DK8+w6tH9OpReBJmPg4/iwfjGSGxZGkVHbFMEX02jLMjnjILOqlEMdKr/IYl9Hp0la9tbfV5CT1ZAhGyes8N0LL9g4faSunCVh00DV4nClRvx4HXba+OvSUKgOisI1Z7SNCeEradSri/adn0ZgpI69++sutTwN42SH4oLV3loj6bcHqiuZCSKkS6JTqE/ow+z4LeFl/FPg+w86VXqBKXXMtT7hEq3aoVVcX6Ovu1sqlvplebV/vb2/5id7+sNWag2VzJ3D3LHvYfaG1kv4285KMQv7qHqhhSHcjrS/GWi3pl5+qmvxAiQH69O+YcUmRrzxw5VsL3otO4F9rYDUV3SjFlv+3YCBI7WzUO0iPKVatahf4nJn/cI1ZeDSmoG3yUtcKSMI1fyLPfuB69BroeIl2f5CTCHc7BkPw6NrSypVI3e5I6pLVeDv26MPf5Nt4ypSbesoyt7W1/GX0ib5oN7QQ/FYPAHA5dz6/OxwXNQFrSBl7o0Bt4nwhKPRh/xSD7GYH3cZmchBtEaDqxPnuctdofBEELKcG3UeC2FewFrd3tqzvyfZKZu9yi72N9GubbJ/MBihnGEX5wQtrR5uYe/+9P3aMPUQA1eduTInS29l7SB/r4c1hk8MYTLpXNz9DXMMThW5FIA4inLfrlFQ8B3e4uYU61eDx6ImtujkaEln/R4X6e8Kq+ixzqpp0pKIoV8z3m8o7Sd2/FHi6TtG++JjqW2xH8MTgp7zHb7vVZ+pVE6LeufETIQnz4+Qy0t0t/tvjtV1j5B68++GhDsuVv0l+TOIxufvDBR4M8Woit+EarFSTRjVaVz1r0hHkUAySjYC1Fp+VDIrbwoY3j6gEx4rUW/EAdKMJxaz24ceMGEKA4ob/NrgJbDquLqbo8FRJ0u2EUrV3G05fXr8syJfr5fSbjEqPvNFsRI2bWTNicT2wpXdJJh5OHyHJfu7wmLq6SBJs0LzqodTpFRR16f/3yujwal99tox94R+FD+mFYTT4Jz0lVklFJoHL4kWQpXWE8shd88cXlS5fbAf3jy3bwxeXj4zV8Oj5ev/zllwZj1KvjXqA38A994wt540vvDQ1Mv1sS8UXyJGnScfM3V6JEH5AdyWOuw4q+RWLi7H41TY9CJGp+cVm2ipmz3P1dVos0xh8QIBH5jb8J/Je/dOh7/QP6px4TAfQujL6ALoj22mWkgNFLa1wGgHDjpl2BPRQuSCTdB/JiP03XWtMX5x21DdNVXu8S94crYs2YfdfO193hnndh2smqu+JRcscb/MmN4PIkLDsvwvPLrxSz6KD92yZ/BGUxvGEv8CxPFyMSgXFvT7fcx2mSdV+UP9N2yOWNuNxt3VweC7TiBqcXbrwIT0P5Vi6wYlHHfBeWi2xI66pNP4wwDTHR5LToZnG1kc2mG2hyR9v4+dZGXO5s0OCd6TTtDCd0gvSwvwzaHigI8tiEdsinltCLj7Lw1PxAf+q3/EuU2F+Y/rmf+OcwmNC1u/FmMtdSC+ZJvKAnW2LpuAHy+tMPt65dJxIbrO2ndDLB/fXWTe/rjzbCxnzlDCWz3Xo6Jck9uNiNhfHDg3lVoeYLiCSoQafKYUKsLaeyy9ElHK2vGErmPh3zWFMSSVrB+TTNStk47fvs7Kx7ttXNizExos3NDXq2FbCx+Uarv90KJuiBW8nf8BPfys9vtDaDzaC/Tf9rrZwQ/wGK0ZnkGa1aih/daGn5rtugc+bbjpnLfgHiQ3ThRovdyBfP4D3+Ik8y8/zNC1/4iJsJAW/7PeT9X7m2fy24Rlvp4b+9Ln27FVyh/27yf81DXwMd8eoF0AXI3gL4cv7/a7gPk2II/w3toEfzDRfy7+JGawewlZ/f8D6mCs578tYC/yZo9vUj/XsLo+Ch9xmj3xik/16jbHf7Oo78hZF2urvbMhb/9T5rutrd2tWtyZ+8smvdK1dlQPnzfUbU0XRpWzpM/33G6DcG6X+nURykdD91UMl+vxusZJQGqHi+N453wY39aEPIboNwb4Bye3xlgxiL93GeCmmNs3mTxaTJikneke8oaX8CDeFCso6F8RPNRbrFNtnQRnNR32OVbAE7JQ5mVrsvX7xxvfrMv8yKReV34FVrDjPQn364vXU92Fj3mezGm3YiL//LbKQiMddtA0LvG4GOB/5lFjoKv7LLvLf/yzeukn7/0RcJtksK2otEUKEbzmYOjo0f3rjYxrPfceEfbcxTlWQ3SH41+nJc0F/iTxaJEX+3oMKpC858DwtCB07EVG5dQ1bmn2sCs8w16dWe4O3b3aLY3JOLnHi61klPV+1J2TzUNK7C1s07XCrzE/RP7otxdCsI/iII7pbw1cDa+VS7iRwl0HW3eoi+40f22VizF3hmGGg4SnQteGozV/nQ6AMmR90Dsakr4snOw6bsfLspO9fkdR20RfdoID2EbkvQWbnMHXS2mx+s1EQS9IMj7mRO/a0IXEPiD9k+1BGHfAdRC5AMW2jkHXbScBCT5Cd9SDTp9rF55ObKr4GcyxfpHddiXfkd+mfHBFvUF3PbPINeEy7gonXzgh94QatgY/7zXRaK0I9OLfSjvkguBHWn9vvN5e++F6wabrD6/If40ZUvbt1sfGFndsTizZTwvQ+wOss74rS76PiOzvK9QEp2+4fnff3jHB1i51A3dNXqjjiwji6jWVfji+91YtPwPJnOpx2+sCiKiTZBHaH3nWkyK+treSiPBw+4/fcTedw4i9YePnhySATmHR76PZw1+mZ1uNXevIwvPG88pT67T+mxmxf+9P1oSFjGnVLaKjWW4jVcotm9Tz8KojnHUMf2xBBrfOOuXtj6ia7thb99Lxi5MsuyoLLj6iXXF/em/gqtm2/69XstsFnct2MapddXd2H949bNC3/60a6DDRlsYJ37/qb7+/uhuEZzNSYy3940f32vSVyOTH0aF8zUuun+XpJJLxCoazD39F76UwSim0Yw+2CFJKhx+STszG7eMvG+zbrUa6u8retc3JuLdBe1rJDEFpRWVEOBSGla3kTCUoKNXcbIkibwrn5Qkp3EhQqwtd84zgWuULp7nhMVw7D3/U0jLfJJnGThSfiC5OWNQThYhOOkdfMW/bH/8QNZCWrEx1IHHS1IOAhN7402WTadqjR2EgDntIKoNN34DHFB8Eecph2TrTXMZ9LdtMqlzSkSNxa2ie+4CKfldW50qI2bvZ7oNlhXBnd9sridXtH9aGNGiEMqCOwmqyXaC8RVAlgSRbGVy8NsCMeuoLz8RMpAMSe29kaB+eaHctugxRB2Psia/WCa4U0ygPZVNVkupqg6P/LTovxqnl8nwBbcG08S7jS0A4k5iqcIiHdBsHsCC9wz3PKPYFrNxjedOKxfuEcO5wMuzC3h9LVw5iMbbToo4vCklIbEcsFMgUqE1EtZwLamV0krGhkV54xAWkYlG4rGOWEcJu2acUl9UaEZWJbXfUMbyxCuT7nMsVsWcCXKG/UgV4WJSUA2h62HJtLei222oexuKgmRRlSNNufgFKm2pHINTJtkE7r91dzeCXo5TG3vM90QEz63OXMsRqxcPhSU7/Mb1+wFDzTO3rRkCEz70cQFsKUmZG3tMI7f0Z7ihwxsdXo7HYlAtbSGhttghoquFXfdl0B4pqvc85BDGcvmqk3Ism0zyAv0Tvmg0Z9nT3o42K7eLt7ZZvXY6BrTxpTzY/jcOG9izWQbrNeKajECCK2KuSNckiOhMB+BONF5aus1icN0gXV+XoIk+YTcEEVzE95yvkfaa3bFCTskZpiUtvurnZq7wnGv7POqCOuF6rk9dQm85XhvW3hRkz3Z01MGa7K7CRILMTzdO8TWc1bNrCCZvZCM3nU/F9N0xKlngSLQ3HVgd2fQ9jIyJOeJDgTl973V+iGJ3Hd6BdDk72Q6FlevUFlDXrszmAHY1X6jxV6mPTSn+cn1lqHbkvHTCjZokFEypvVh5pvSXaRr6T0XcHwXwkxL9IaxvOUCC8WFxof3Zy8XzVDnL/vL3dznSKrl3jTctLyUyn5aKXjfNJaxnX0RMCpdVivTaog5MRrNhLCIGabaF5/xssVjlUXj/fe7amCz1z7v9YejYhDSiVjmCMThGHiim5Am9W42Q/HtpWX5au12fnR9maSGxXlyyj7XcEDz9zd73V7v2uZW66YX549QTiGXyNEaYLdc77YK0fk98mL+q3g4yZKv5pJ5GWd0Y4cuoaPR87POOr1k76Vqvj9NI8gS1VJm708L/oHLejIZ13KESIjvcM8qTDJ3/QDNUcVKVZakAOG+nL5cGPRDL15uySSdUQfJ2H/Rdkr2xAdtO4yhJigOIPRMmjNpXtAMpN8UKbe0z0pNttmGKVkp+DxztLmRD2GPO1h72ynbTIfWTS+8H8gnp2xEYux74Gd52a26oH/XfEfbkNve8VwyVIrqWKiXpgoni7918JkMEga6FEXVwvjl0kNlMNPjaUvJCWlb2ezOBJTSoFYFoxHPb907DNYgFRIx7mgxYn5wHQl/d/BrREpT8zeXVCplEExbW22hKLVRRwmtbe00CSH689XgQafhi5zzFk5JC7HHebSUhmeWGKF88VpvHUPbroVazd7dOM52/Aj87eZP0SPl+iGDD9fvV5//aRfVFOT7jzb4oXbt4Wcma5jz91TmlarIwwlJCJiBhvlZY4i1Pq9KeziDBNq6AH426HVp11KbUIuzSD5hPq/glK6vkKc3FTW1JWwbAFzbWvcD8qX6tQXkvhYdl85N0n0P7bW1tD3tW+8H59K8123RxBjEM82XbkvbsawiTrl+Lcv8XoqfXzGXLZ0gRLkkZhJ/Sb5G6puyStO+V5dtyJpcHJvRc4fbJRP3suVobB7A2pM7dw7W/QxE7R3kpSMyIZSS+nIhzbh6M1F3T9Jv9dqIogdktK3pVlxlJdMmGwsLUQKtOevAG9sBNlwNGNuRL+QBhKXbRogMV+msaKZTWNRmY0k3kWxGoE1j1f7AwxNZ/IoOmK5lXrsOJmZBBB3CXxEOtdu5O/OKU3m5nobRscLTMEm9xM1m43teFOdQ0U1MKuYjBi5SwTopTcY3/KBxwaqDdmVG27M5mueh4VjO2emu3Zppr10Xipo+mCU3y/uLQ0tD1mWhw4ZWy+YrGJdSU0/EpODnaNm91L1NikChG0yQVGq7RfGZhSi9jMFOR260v9AW34Lm0gHLKs7MqxCyy2hJ9Au5wqhGAjgSl0g7Z3mRGnlBC1/UE4q1RHl8Kkfn+HXIFS1utLjZYIulMUOKOJ3uPUhRv7fZ3dza7V+7gHHjho+FY65My9N2V7jLzNfB5i16Dr3cbW5wKyWZBl6zvzqpt+lZYaM5peveisGEDUu+kvbRLU1b+HpD3GZjS8k1RqLxs+QkmYGMGXZOyuW6yf2XKSvRCg1f1AksNXHwIFowlMz4pStvmfIE3aXobEy/ZtPtEnpmXsxygbGpf6QiC/iWTsvSWzvgkg9cToVzriV3WScBBhE1IHUeYYyEF8z8VJrbQ0u5D/aHYsfC349dB0z5Aj3n1p7Gs5jFD77rEHjL9Q+Uj9I8Bf3T6qSMf99PFe13A9ekkdsiekB9waaGRKtj2Yy+Ds5YmhDL7ZFTvZ9Xs7z65X47uHf3s7tP1439ji9sx6T5ey/sp6NnfAfvZqdt9FY7nOSz9aWumu9+hbRx+43W8wEhwMnqK9VUpNk2SgR34vXa5tT1i/d74caMKKZUQIQflL/gFqhSijyUIiPyoHuswzXhwRU5ClAIUgODvv3mt2ZQw68kEyNa0iVsLut7iUWan0p8g1Nkf0p4cV0zZH2aBJLqSsugURKJaLN6R863J8rWs9I8RuBwsDxJ0rTULkjYjTYvsnrq0wPhklx4VFiqFFQ4w6+qoxrTXWhkbRDAYmGesk3ofXIpRRC0BydmwARCQFyRpDrxrL0PGNm0RwaIJaGu97hRl70Nq3WEDWKsleiol8Ln1SW/aL1owbyrSTwvIEANg0sTekqqP8wqU/sBdSI+iqc3gbFSWxZ5gYR39N0SgYbazIVpQu7eLRxRyiWqHCwQqZ+ksy3PfJtZYY5tFY26+q4kaotYeZrOudeVp1w7nLCo+N6kw2H8EunQG6DY33bov0Q+wFrcEXhFDKUpZaxVUBhhDE1diEXEOSCk8xfEP7Qhp+0ODZMWk4OppURaFroCQZx3L1spVpKsmF351FvKWaFUCAmxUgPH9mqds7GUqHdt0qS0BZORN04sco4DEv1NqoAMY3GWZCXbYCHAoQ8sC/+2hxomTtF1SAtblVJIzzI+Vy/YoqAlZStES6lFKc6miZYnO8s79Hdl/YKYyvSS5RukP2h/lDDhhmVrIyl15E6kzUWcUq83N3M9dEdng7b4XMRi7bqPEOTXtT14rak3rJdR5LeVqLvQgK5sf2Hy2EZrY36uiFENjGU1bhUVlrZEEVbDeVcqDF142zrEyL6fVMC9XGvM0OfVDFrD7VdgTigWO1VsAGgtH5DVUN5ibeKG/5e5wUv2VlsKxOOet/P7199hOVr6Y7VlQW5SwUVFa14ow/oAQAD8LLP1f9Rcp1U5tYQUg60yjUn8C8nakr7bVhaSkfoYWkZkyx5o4rX5zJU3TfxBat2Uo+DSnedcf+bl2nk7WDxPAhKD+Z9fP0/Wj189f5nc6L36s+ySqR946fySKcInwrau4xK9e8kgCDY+tA3S2sGlQn/Ea2IOUqc9VoA3xQZw6WvvOVYAucUgHuS3XHPnia3n4nbMdUm1wqHZdjWfmWJzBSGOkBeRDXhZWXA8jr+iLb/MOr1X8uE4yulo9PveJQlFUHsk9/yZwb2DCwwi2qnmUrbDSg4O1PbsvFZEvOXjKpwz3AF12jSDHn+9wF/0D14DvkDV3+fZuoP/cUrrSgL+1wv5V3apYY7HumhZYudg2ZNQK0pIviFgZ5d0qCFAiwMSW43wfl0wUnqT87bXW8ShNAyevpCgzrhoLpWzIN1oeUtrB6qdiZnEXzTG9MQa0vxjcB1nweaKrIBdrai+Z1/Ui8AVsir2KLCC5ZTEPAhP8yRi1+wo4ZJa7YAuPmg5DquIx6iTohnp0t2by4ueJ1N4KqT25bgDE26aTPI8MtKK79zk0ycJjDZnJmQ/NbHRyqj3w3zGdH5tEA9D7aXtN8hS4orKA8yMliBXrrfFkUY4HeVTlgPLk2DzJ0En2PmJpRRa3TOaF6rz8QpranNz2YqpSVFTmJRu1IwLS9RyItU3YLHsDvMNHbDckGI+G2dcx+W5VH5LSCQu4bQaoJSH993bY5R0OO1F+HXcgTe6Y0DUuml+0IaOcFXXK8K8U/xSmKEC5CwZlhuTSadIJ6PWTRnG1XM2MMOATX5NePX9uPSOURRqNIYLoOT3243bqFXdalfDu5SG2/DrSTaUAuFhajjTVOtjht7VfG9WbXjjEqtexStXytkQ0SQ34T7zgNzW7gxtSUN0nJQ6dYn4n037abNHtrWqUMXKX2FKUFt+zMJyboR2bd69koCR6GzEh9UFmTwRYv/O9XeyZvS2+70dgkqtMJQTIsLZLE1UgmCBmqHCLVnzsuzEM7omUVxXAdjo6deSsoE5arg404LQrCqGZieiJCasAoSzEqG00pI0FDVCYd7x+cQMpaMWUi8wsUW0YQQ2Pn9jIyxXGwmd5Us7Sqscb/ZldeBxzE6HlCh1ao6lHezf4dBJWmmm7gEUHTXb9QtfjiT2gENXjJjOKECiEd/eM1vGVspWSnVo4I0yyzgyCrqEEkUiu4vl0vONs/BrbdSsVat/nCPdBJUl/MtraghUfnrAdxZDg5UYWhw2jA8CdAiPxHWblMYeZyfyEHOlUr7zjrRnd1kpR3vA1VcAmL8udjC6LYNi4+Z3MPHJpVgmHasvSXcl+ZiFcDJPFjP4UEp1wjFmEkLYpfNXzlMNkseltxs4hGtlHLuyWaPuhVxHjc6VRCw2kZFA6TUPN5U32ZGYe9VZhSwLXhg8NZKiWY/6pXVJAkA5fYlhxU1hLIHsCR+GK/AOjCGWURlTRKImJy6frRIAv084V8zRVFeFB4nngVzLmnRkfVoDX/NgQcxSH7N+eosVWa7brXM2ZUYGrKUcfBuA3OE4y2FTsdLIA/HccJCXI9cwCbqawn45X612y23OdV2lb0vhjsRxxuV+udW5MsfVW+kGD72vCZ46GV/TfmfbTQEpzRaCdzcbaBEWnVyLOXpRkgRwi35y/LFU9hLI1p/UBh6lUGBdvv7ug8qJTIbMIpbCWJhr3Q7u3gnWWJirAp9CtL229IqoEi4hjzYYjCVSTVq73q7h6SJYsxjhxWYv+Rv8lQDp3y/sqne1s9lDvSk5yxA+8w6KTCfVxofzGW0AMB3BZjWMOwPWHVo3P719S0MAnh78Wf+tJvPebq9HMs2VK9daN+/MQ48M9a5gnOvWiMMzBjxNUCas75nYt5xLEdGE68y7ENOfMV1lqPonz8D32QpRQoYdnY7U7uVVEwrOEDHBWp1EdOSjkU7Cd1cDPLmGL8JHjWNCXMsWRVAYkAPla0ogSqnDKmwpiCd4SdFo76x5S8TsrIljxayEfWbKd+NcHWNv/l7i8xWIKPaK0OL377RpLU1kBbwYrNzG3RVsEvKll9F3c0hwlXY7fMxenZq/AZpSiWrpMOMeNQCWKPkwJJyP/P0xf7uzebUjG+iMizCCwW3jw3BruMxA97dus7qDKyf1xurbXFKD3mX+fqd3jVQiGy+78WEUx7POVx3liMvLuPPLR3YZZyE06/BrQoffi7DwttBaL3f0gsTQ7xNW649eD6pdu5Ww6JydcIcDut+msiWgNInTmZiQg6gI0XUbgm4pdjsSz9TWfOr4qxTCd63NRVvlbA7xaULWsMF2kmoAIwHSNjn8ZAUR/u7FeFs3/eZFrNbXynd21+sBv4082aVU2O8Q6tscsh7bIuNaGc/5QzwRPVbxBlLfkEmBJBTRvyQRQKyW0JsKE6Rf663NJEAtOyaBpjI7U6pCoPeOyrjZco3b9y3Yh3FW4o1GGocmMajVVHpEcXMY3Cs7T1tdpTZ+ZCmpATScNs3GA1azZTY/tH5NmimhDDoxDR41robrrhN3QAR9zBkpKJQwTxMS4E5j6VeFXDcZUndOkIBDiWgoMzM62EqEA/GXhKTCnQHliUMRtzqcD6D2jY1EIh3hUMTROaJ1fcRrY0IP73uz3nU5sQnIgfu1yolrrSvkbVZFDfScanIEk2AD+sHa4dFDDhg1zz5T78/SMT2oTMOJpeSKM8ERTYZA//gzfEb+AC0XooSg4TAsJA7TupeH+RghhTZ8wfXWUjnNNVPicMWlVB8gzgCtEU61HQMOzGS+DDX4TcjKFYRxTUtPcpqVi+FE4wLL7oJ2Pu8Ow42H0JeKjdZN+SPoXdvZVfMG3xdz0P3NztamPeI3wJ8Td1aD/4DAvxc0M3vESF01e92L0oRWF8VJOEi11SrMEW2oQ2Ob3SLIFyHCTMLQwwhStfhkMmQTWhPUPDMKSillOC3k/OtPjAA6lb39tOxG8txdE560gfnSUHOda5lKSemlOo3YysJSyak0ntF8MuMmnkBw5Oeto1jpHbShIcwVYmtHKH3k6wxWDTJXRGYwIlCMmsswQ2voB5Ev/z65hZlk1nUvCevB1O6T6WzE2nRtm4CSTyKJDmd2yWo30iBeiSKRnROOJrXmSipOa+INcGAo4aEchl0INQxJhINBsGCCpPHAtkXayuyhvJY9JKv8fvLqVZJXlbp97YwuzBd0+CWbx7OYT9MErdlEvXqHr2k4w6aamZoNUuwTDLRpi7RPnt/URq5sEZ5pKLePL9I6KGFRjh4SVYM0+FACgK6701+mP2G5KqeQQzyTUvV4DRCmW9aW3GoJj7Ltkbh5Vhys7PujhgJOvjBZIZzFe1FWoJECVmflWcOGywnlZj4iJlTixVeSIslq3N8K+QVvSuZTQejtZTveqQrH+4tL7zBxXYA68iHkEV3QEik/X3ktrBSj9YBs9yMEVJGUFOz72Unau0zspqVhRxehpdhQHIlXI13tzCD7Qgt1NLAknR2IxUeiew9qezehq8tmgjjrnpkAV9ZM8GlDj+V5bZDnMggdGh2L2C7hF2QrkfEpus5T5SwGGRbnN7sAWYqJjWzH1ntkGpxzESq2OEHUy5CAOYDnc23/0aP1b7/5d2La96yeLOXNC+3zKu+nkP5mwcmKcSTIKAIRHjkjPKEz0eohuGZZKS+dzDlwmBY+n7nkjkbHM9kG8z1aoFtXWVdDmtnk7wb4A1TAJm7bgcTKotDzSVhOOI/Ryg+H9xv5dfatQ/NWcF/eWmdJLUHRBniEYCMG4HVMgawNBHO2zlI6nQhxVEFJPLqI6arFSA3mw5PYOEgmBHPOy7Apri6SIJtzy0xuOCevJGpiMelvNuTUPWoTbWx68Bv8nOUsr5LRYgPe84WDF53S488bENv3MO+RYswjizGPJ8HncThZN51Q9dZ5GieAAUCq2Vkb57IIXMQo6kG/tZ31W+0q/JuChO3XWZ51iEmM6I8odrSAYyVJbCgQeQSMTMXFrznrOBMN3sxYyE1HLoiMh1PRHFlcvHDu4ki3lefH2tHzD3hh+kuzmA5beaWWdDZFg2Qh35Kj9cET0bluStIx1icoZLGnGzCcDaWZAFOklatJtpfdI4bIy5/Qx02LQlb2sR+Tps0GQ3b/a7GA2LQng8EvHI+LeGxza4y1LbAeWO5JlnAMvngEaZxf3JFkPaSriKGBo8BKukOaPXEhsjWNqptbaLrS33TIdv/R4bMGrt1PaLsotImAw0fhaTLmmNpDYH3AwWR6S03xECcDGC/yO1IPHlLSRZ4b+9VNvl2B5JDol2rCYDzkVt4ZewNUnkaw/kTdNzaLR57QJI5Qrqx3TzkcWHPuNDeqTM5J9h/zobMKPgvF1mgSZ7XWuXiHOOvFLK8bAIzSmLIkouLBLw0X0AjEgktMsHRbDsZFOJuUPs0Z5FWFZorykt/DmfjyHAHD9nYo1uijxs1O0gUov3QWN7EvwsvBJqDda9lJsUB7zjOTL9KWzXCwcmkUMqUbmfYT5etB7ItnFzWZ8YQRO4cxttQ4bpgJdS4p+KLGM/Yx83nxjSnksrIZmyuP6P1hlzDP0iY1pEpSbjDMB14uQawbcI/eKec8ySLFO2DgCVexKWvDUru2buQqJxH33HbxYkJBQbbajlr5Y3MvXjO2VBIxYe1MI7RQyDsyA4TuDPL8xLSWoS+SsnQX9d7+g8PDxk29p++gS89Ssy+5pPlMna0ac+HaVhv3vDDBCNFG0tXQbNoApLQtGeVS2YbHH4dzErBRlwXNd5LB3IZV065MJ2zr5kcTArAg9EuttKwI2DnS+3ys5o3aUAwVJQmWdGpfW5cVu0rwwXAZI3I6NqPzlI762sQ3LePiRlQ6YV7pGoleMppTArFIS/oAMClKIoarNCAibbVsjGmnHc0LJkkyDK+NcckMJrGj6O5QG+Ad8WbMfeE6Fm2an8E6NqbsFNoglpFlDqW4b1wDpQ6VqyxLGSpdcAIpydm5izPnccAOWEbOkjKvOHxr1eHxmbN+qd+yjOcQILh0jjBUgtGlY7ruUfzy/BW+qPu1Wc4PjLJw6RgpILTmr9oBvR0cF/xRImJLKxyaFtDGSmovPAeF2hFq03L7WNEi274nlnZnmqsKAavqhw9zQ4H4Q8Xq1aVPoNp9rwyOa01PGzsUnIiPXuoh2kFHEqcEC8zPe5vvEGGWdAWRBmhjBjxDu8CNzSssrErfwQ6jU8fGnXfkuLvow7HsIfL6F0rvwdWxaLe5uzQLOI29SNESz0frueFpc8tboLUNTM+0kvfQurn8pRdAuOyeqpe7fEMdy+/lpmrMUndVmbpCEgdqraex6foHOXueiGw7nIRQ4GPNmLFWrEEMKxSxYSMaoPdpRKoHD2KqgViDQs49nUpNvQdlHKtdb5yb2m+EOMFsspCUdLE2Glu4dMcmZozctZnmVJQmwMFL+haOXLr6ealJtK2FWLpctqYTm0hcJ0dI2KpLtLO5OTt/x7JBdCP2caeNfMeyUMBDq5+/yIcnEgmIWGC45eShchKnqcmuHaV5aHp6YgfsboX0gx9ZMxHhlGjkNNTtS2/gPC2t7QGuBbBx7WAtaB7aPu3SsvntVxjFymf5DGHV2vF7KLeAy5UO4w1dxcZ469qV3nZ/56r5psNbZozkOvFNv7auXkta4KkLsj9MOve0OEnr2dxok/k+ydymYWXrZr3jpi2301ZjJbi0CvQPpfcmqoWLA6Yd/ML2zgTKmjoQthQCX7E3depks0sz1R64w20/tde1lIJACZdIg5+kblkj+UNXKSE/RsfgfqGxSw/XKoid2bzgSjxc3ITTXjldE1Z3KQXBfxHewVOqWZ8sHrM30pRI0PAimYT1hzK2U6o2pQF2kkiM2AJnnJZuhuxvs+CR59CRCSXNhohjzUlWF2fakC3jJGRz+OgZUR5gP/LR/Tj4BZGxSCpCmKh3SKt+7LWminPRtLA2kSBhyCwiBtFjuHAGAuoD8yYbAfVIcMPRsPhb0SUtucCRwJHLTJLgUgxgWcW2tGxHKeYeL2OorDSd3H/IZBUwyVu7civ4hMAJD12vI2qGFik1WXK5lHzTCNiCs2roubkslWP7JhxbxqhodymNzVPxchk7AkvyXD/JJUZagmtPzFFejqA0I7VZekNqtibUZFKnI+LwUxSNKjU3l99nj6kUf1DjkU3LtNYAnJorH2eP/BZSwm1ppv2Dhx4heHOf13cpyrXT7fX7O0Qo6p1kXV0uDrvxivaJS+K9srm19SuqNvvtZl0gucFd1IUQ1NUQZAFjjQty8T85R5sHwvUSQi5faNN46EiEeSB/GOYvzoKkl/VaSAqOKYpk8t4aFSv9bvGs5mgRMNP5QBnXD1iIzey1E84SUmeV6t31Kx8a4le6kvVY63IdSotCJlpnaZ1evAwkVw6iQTXdWTqnUVAtWv6weSiP6QXSngHG5dFQxwLo4YfhRPmQWOYcee+o07th7IkdnALbva19Wr+RuQpEpOeRy6aVmrpL2eyVkfe84pcmpzXJrIemq6Zen6NYbDK03GbsDWxxm/g0TmETIOLEvr9AASJUHYllJhxHf6/tplxfqofgmga/b0EE9AFGMmn8/7X3rdttHEma//kUNfB0izyDKqGuKNCWPDQt2+qVZB1R3e5uSysXgSIJqwBwUIDYHA337NPsn32E/TePsk+y8UVEZmUVQIq62J49x54eEXXLa2RkRGTEF1siMTaREDAkNv1wbVECXDikmtMmmszAiiEkuDROdmLPzCqOVBZLOUJ1QhQU7um8wWmx4U7GaHuO2Ox2gF0DmHlNyL5GaPlEMx+JcRlujxBoJsIEBHxIxC9PypaI33J+uzgilYEgtBL7FTJPxB/KwrlY2gFI1nM7iS5m8X5b0uE90HrTncPYIjeJKpYNTFYHJM9iJeoByAmUlmIlpqqSnUVhx7VLT1z86at9IS14QvS9h1/3PXPsIKEAfPBg9miu4JLJ86S82IyYZ1ZhBBioU9xf6oHxD7JoZo2HuY0k0xFz0dGZKfbu72CwiXFJRvZCD8N5ZGRQ5NiFV4X6vmE49r0f3zLCZ0/62Pd600mvz79fTSd0SV2lZ7bDl6/0EfW7R52ukQqYE3qiBPY86LHrAV3++dkjvLSeTBf2CvxHr66uXgrX4jpojywroL3QtqWTOXWDOjWgB6Ml8CNu3AgQNGidiXuvtQoZOFv+CHINmz0hnnOkBo/Bqdf7wnx539e+9VqOO6UTEsKuDNw/8bsTiYg7Ze3Edqi0tRzoJ+6MUrz0mh8+/vPRc46QYFYFX30D59t4jTTpad96B5aJ8TrhTK5XV4aomUvSNsdKOJ8Y4cOz6bm12GoMGhEjTuAx1BphuoDAS4zkpFlGQjFERndWvHmAlogi4CALJzg5xz6Hjk4UeOn96ej7Jwjn6rhYQuoWwfUSy80GbHJ3vrYu+MxctSewW6zcuJZlCcYsLqH0Fdi+950+xjffyKDhuM35UprKIZlTVZ84Z+ei6aM/E9eHcmLJx2nrymVFgUlP4PKraE8kUZ0/NwhROJa1hJfNFlWLlG9Ur7JqHfko8+LIcQcH33AxX70Q+CU+tkQ1rGLy0avhXfATqFdWxBOM6bMFdEaQWOB9vS4NeXdjekwwj2V6urWdTCuzx8AWwY6Q78mlvp2+UUXE5dRWvWXJFX4KdEPsHy2WBkdsh883W7wD+yd7th5TbY6BCfjrNkEIr1UbaQE44TXBrI1A0PAlPnxkLw7a3XDEpkGNKEvD7me0MWP5yLEj+9/wUlFgs31muPvKdnviHIprpkARw9Vl1Gp/QgI9tt+xh+hGR5WEO5POa8ecVKgKxevnqbADHUycujujKBRCI7RtAcS6YVtxx6H/By6J6xs21rcVKydiFTGujrB0W6r6wQS3Cssy1DSdm+BwLXYLSVlU7Daop1KJ+HA6h/J2IxIJxmasUMfG2vNh/l16D9EQZnHNJQ11X0bLYJHyC895APBMWMmRYSX8VO4dcBgLW0JsIQ/MkPN7TyVM1rLRv9HsM+nJkVUxry/UHRFUf6du+IzSZQE7AfVD8LxYhla4ndbICE90hgfWE2GXBelvl/XUgL3zSunOgGE5usGooyBaCB2EoylOtnzV2MxOYDoFG+9L91alemcIR7AW01XZvLqVcpM975mR3E1w3Ab7VuiLertIbxKYCOiZ1QombmfRrNrFvQAhOKI5i6iItVQPh3UtsoV12rKJg+ymyyapfUaUfaBnLePLNnyA4c6gSEbc402iGVYB8BDfXYkQbxA8rL8oVm2Nk105gG+WxecMRvtw1chUJkq94+zJ1s7ZbD1ntHqJvd1Ar9fUPp8z2OzRyui4bn803YzhxOL4bLwddf9dvoFX24Y6Suqv/xXpLO8JWjzIoyQBXMI1qqg9MxKwdoGyNgeALax2UcP9RquHks8HnhaGLI3VN4+jCNWIo2cARUPPm+WwQnRCUyQ6SJQlDgTRhATcxem6tHH37KTtpVlujUS1gfl2jAZsL7BuR7RsiH5L171YvRnEqEMtbJl5C6LVSSHwWZLzZwaMu7PFzOZeontwz1lb1PcZ+2ad0RoAmiFOft37UMrXgJ1Y4/AcTuNyQq89bzJLeF9tALgYV47Gzwe908w7zHUY5dBmscC4tLqHm1Z4FGOszI2xsemR/tron22cpMlizEqhhdCfAe2CDdbVRgDm+RRRs699A1q/xSiQ3domENGmXpfryULSd6hJAP2eabKbxlI45d+8Sj7ARmDWyhaokXdbCB4KXzHVO/TMpjDD8cywCUuEg0gLndhFzkf0DjZlgy7P/RZf2ZWqhuZjovIASSy0JI1i2m/HfP1grKzugDnCrw2kYEi+k8vtlLLvTU/48E5MfhxJ3umj61Soh7E6NOpEao9gxlN3Hb4uLwWbCIxI3VTERGoOVpq0StsMVahA96v9DpKNio68QXFeJD7XZcI/Za+Pk2YnXLI26SHEsCZNvgnV4IGELYhDmwzXNNOzLenVpsVT0yNIXD2y9VTdEIpHuOmH3XKbuDr2NDKenNRn9TsRfUQm1zbAMfi58AeOqKgnG9YG35xFnXKBVFpfaWVlwLNxpKLyJPgDnwmWS/b71kmAT7jrKyydith8ZJ3JOn2ykY7tfj3fbLXSC8jEuLAIs+dFAexSOesywpQdDo285p3YxrR3ToFmAuVWbLK9jf7EkL4loHNLfxhZHsOhfgW2f4b2WhO3pjVLremY/WSh2F3mlMSdc9LmSmzQxP3ZQ+6Ez8Xuni1IgLwLx6aCOMTcONJTned77txjeCQYjw9wJxa74lxGUbbT5sBwuupElKgriZuitJ2I9AM8RlqFuV4iBqT++jykN+UX/QDo+hsq6mT0sQCQ5exwubh4X7EsjYH4+NWyuO6MoJsZwGKSGtRiNZd0TlnCWC0yPi1+RgzQc00ONxaZtT4zyirDP3nUMjhRePXlnEFuiLQmy/WpZ4dA1jt89BmGyJOiZXE2O93Uye23zW/J8e07uyB1oC7D4V04uHFKI4Taz08ZT1Pg2hQHsJYMTzjMNjorsRqjyk02DvY+U4h9BdTuorJ9Ji4bcGtozsoEhK6UZDcNtLI9tuKsHsSR59b9XWzObdb9XE+Gm9xvGyYs3hHgOoIhdk9jxAwzXYrP0kpH3BxeNvH3AirF3aat9K4oEu7uvdKwnnkne5LqzYVYC4W5K669urvYE/Cm8SjGotKoM39jxyBF8fSU+VQLCE29aFcWPl/sQ57fxibve4Jsb/6KaaHvORj3ilzeZkDn97+faxqTUlKAtMCBdRdokgIgUZrICUa54axTIiOpswQSkSY84mY5G9WHo5hgGaad4w10At79xPmsKa92QW6wnqayClyP8Qa5VEiOKmLrtm6qcwXvEjiUai3Fuh4dtmmYdGldrS1nfCf1wqB/p3NNIEMCPyuokn9U/cNtuhZus0y+nuJYWdMgynaSdWkGkRaOSS2+NNL3qTqmUGPgTHbS3OaNx/EggYxlfDJQ20lVXNSNi/WY1T/Ovur9vIZfk1VKnLGS45C2oe2W3DeOiPsupq8t2v8u+O+esASAz8Cp2aBzgYbKmU23d2pdWJr9wmWWHAo0R7yC41IlPLNvzfD9DbdPJ5GoU67j4GPSAtkQUetixxhyRBvqyfIQq2NervosybTFmL41YGJxqXCn+WNqpzZZKCxXiazEqSWNox/r/mbIv+H8jrw99YVpqAQjrMdN/aTH9Calk8ch3uj9krecToopV4qfIeahQf9rTpU6UPgdtUccxzBrzEPtSdqSk5vxuWurBc08OuHF9lCrUOXQedZ0tUDk0gk1bKJvKVutZfGzqcr58HtB+Wse8h4niOhQPNzuI7SVWDXoEX5eZp/e1E2QBhHUi16sa3bUYzWOD8tKPS0kfiZneZWEzKPfMsvHU6Lx4txAyl1at4qJ8T2DF4/aeyS2xmxtWMzzhq1JMWatsHJbv9bmCAFDxNSOiAPCLPASRqGg0sLQkYLj7A973gXbQsYI/FcE4mO1pNrhsIyzSdDANTWjp5BtxDA2TRpmWVj74ITTxw2dJnEbluXPSgzo1GxhJ3nYPOKzwr6XavQdXmYwkwI5S4wCI3tU1CnV6rS6O8OY1k7ZdGpT1otoWvv1bRPav79EfHNl22XijSa8r3AcJ0nEfm6v+1ulYwbLhgOP61kpJ49R6r2ZLjmkzDqNG5BDmzNdERFbOVRPxUi3xBnRG+PCYI3K4qNEtEZ3jxf/cPGu+q1gQWx+NOC0fpxR0FWg0WuCiyIZpnksx8vCdWlX/DzsL7Z+FHIu5mYGfHTRlmVnQQmnm1UaydYmD7TAPQZLX+E9jOVUXarrWe2kHWlSb3Hzyk2At3rlQHgwnALv3UW9meFJXcXFxXh7qu8uHgv9LYvZvvEL6CAriKMv8AjVlG4i8/eMpDJmw5KYoJflmabmMaxLmqJmAqcbW9NDOdAqDDFb2ZMKRcJduAKsRB/PBUuFuLLYT1r+a5ZPBTu+7Ny+zdeiJw7G95G0eZK4l+wl0m2YeO3Oyvk7E3Y/M9AAzfjyLrNP64pTAxqBVY5AeP5YFt6S1l2Jtd92OVNtacyQVmM+1eHVNAM6Au47o/hMXtiXN1eKOiM2Crj9IsUnAr/rFtaLlrPvBop4NFoThGnzaS8HixuYGsD4v/bYjUFmoGVN1MbuN7wXNiETqCywIKr3Gfmhnq5UlbgrodDvHPOTrl9Fs9L2nY2wbqB1JKZchoBthc3BVy1HUJzclpOkrtuZxu0EaQ4SM0+6q5ugeSncl8L12E8822RBvxHmjWDG3T9Wq89942hTKHScHCFBhJiecNNWMviNur2RDLBzQwTuY+rOXkMT6iBrWFY4GIiDgpKIs8JUZXByvMXyal1UnDIEXdQOGk+TWm2bFhTALe+us4zk1LgQyml0aEFAsqW9Y+Ztuk5JjfWslO3EOZ+1eSnVbcbJCaNijAt1vYlKIi87o2ezpNQtSCkkKjHRABYrxGxGYru0GRm4qjfiNi35Dky/nraT4e2reP/2IfZWwRZTseuvV+pFRe34651acm2uFpOCm0LqSgFwqyWpWfW+F+7ZjHXOwrR+X02oriNRtugA8zg3Eh9HzOs+A7ER5vLidakjZkCNGvSuzmYoU+R0+sF1E2DdlUQ86OQefneO+A3x6iNdaGOFCO8IAq1gnw87G2OZbONs7CmfgbzbfxZOYOu518iO9sAF4JqCXLwy6APNrmJw59wxB6tZ16zJtjwDLagYbOYARrMiEJLfrG1Qq4MgiVD/6XhPbYC8f1nPY22LbkdS6hl7SXGM9qUBDMPhcpNk1fqRq6xOG/3iBHiRilnmGw/aHhaSPDqURzap4gdI6TdU845E9I5R9qiJV/S/XRbIYVrfPVivFv63T5/37uMXO8MTw8Zp82RZXMwVtwPL3qIvWWD8Ji24plgQ7BRS4zezujKj5yRcak4sNOUCC+xL9jNArXKab2uVIB91tKhrOAmcWs+8DRHJJj/uS4pc2DToxYpdgEABbBxrjSSDK8PTViscK1CEjgbvgGxZUCunOkBbAd0wwFXjQj6DPfVUs3URp9Ki+q0Mjm/fBkFwdWWSN4KLNb6s78gfCpcpfPD2bTH1YW2Gq9Xbt2z5tZLnwUM41LhW6KurYOdv4qxnjpLZM6moLoBYeIxJ4c67WDU2K1xZciQHN9J4pSGag3YjPhNjzyrI8XDJrDU1tcm6dr5e0tyZZIsCZX06NSAEc0QZnRZV43LD++7OzrffHzw62t/ZCYON7nGShPDqaie65llEz4hbIotqIn9S+bNzKJ68CG/fR9H/IxmQAIKzaXEwFcsfB2U6Wgh7qm25b+HmGMhnOtNE3Aizg4hrZOL2vsLeGkSWAZr/8IRdIJkE5oh599RTrXUggpRAtG1zULPHiMhiY5HYeFeg60tmWt7umHQNjoDyuospvQ8PVa4D56VwOgkwWk8W3Qne4cRvQHyQE38TTKe+rzUrWXJMM1msoUvCxIe8uYxQ81mcfK6v8rkI38BM/LnmXPQNZi6jVJhCxcaPdsJKLIfYEKAsLA5wNuke3JUxofIZz6aG64uDwb60QBAB+CdMAKe13ufFxr/0BoRgsd788XT1uTSWZugrMb3+UB6TXlDqu2KPfXUhNzcLXy+rbtG4Zcrty20jZnZfxaHYK5qfV5jnV6vFK3j3vFrMbX22fTRtR5yfE+yK7TFaDAPhvBJ9YaN1djKcOvlep32wwW+MEMhdwivAXrqfiGGr+5Hetc0munqsjLLbcGWg1zX9dXnZLRy3Oq3QQrpvmtu2HUSLHJxgG2GqAWG/UtOB04adDL447OfWbfeEb39gs3cAPl9BxH1W0sbKwMP6KjItlK+W9vZm2c2zV7cjOykSPqfdl0WDRi22ZXng/bCcrkrDtvTtC9wT0ty2uOxdp3C+16Ww8h8bxML3bP0jpPstJm7dOPf40Hp3GDUBdttJp0dszJ38Gl1CLJxSkVO/EtAH9yuy+D/fYHcxfIBvcan1ZrHNfL+bEKB+HMB5mhTLQ5JEzLDJrVcQTjYrsHfddq+ril9/hUCD+alTRQLL6sp7aFJ0OfWop+019ehpNUSHbnW8lBcnr9xXugvi/VqZmiXxHEcY7QWBOx85DNqok8V4fW1n+OGrAsdjTsOyQP3tS+/pJYlucyYF/VyPQF6d85MPp7OhtX6XHquaZp/Vm6848Gyz6NvtDGHOoO8T7/lFWdrNjBcmbmwWe4vlRizk6wWJNyw+GcpfvJrLjRZ/j4g7cNzCofFn3j06W6/gW76332yKr4y78zZujBPLbov0rm3TzjMTyMVyiznTNV6+LITyyrVJzxr58ZQBKTjYi9Y8oIi9567B3Lols1QHJ4I4SD1zFnLQHHCD45w2OrHI5xJ/ih0atKPe7CQ4P3UOsx9Y5whu/aEo4QYbHAk+5PxMuYXEXTRJBksRdI3c66D5ufgfixP90OLooLuHJimTAbasSJujpTcdT01Nx9NT36DiNAmL8B2D9fCoqMnWHm+0XXUdHaVxK5XGIIqqGJ/xAD1gdzQj4Uoq+vGiFmXguFSvco4DMGhTxEKnM404UH95dtYy4HwlGtMBfKTBh9KnkHTsf2+8M+kzJ0oLelfjO3VcVouLHetO+40Ecu283fHoP6FkcdYxTEaeNE87C0vfFopvv2pP6d332zc7X8Am577sq251TEyRRmXyYu7LCY7AL8Osc1nzTXs+ZIvoFK3UUM/c8scO2bSIRl/rlFGfl8XrLZ038TOXgjN9aWJnZFHj86t+M75KGduHtyuDbyhKnSaBxWyU5D71uiVikZZNy7h10sadq50HsgZb0AAGf4FDaGG80E3kZ4Q8VYtiUu9YOy5pp/ffYXI6mK8W8+/r6esCkBMWX6N3HyzJ4GOwxYnP18Siqxi/AlrFJ6qFd3G2qBi3V8Vca6oxpn72FVJnSlFHN0722HLqVqxAsI4XHSvOnkHX1ONDg5psgc/koBSYqcbxQRKQtKLXkYsBvvHNqUSxEYr6XRP/IXn02tZLDqPkyCMuy5wU1updoQggCDI+bJzPaJ8UPEJjfnJ7LGPgGJq49ouloE3DqVONU25fiAlYQ1Vwo2HqR6Ith7ksF21JQuxjDmWbdbkyCpO+CF7H2j+7N7US1PL6ALgY5zRhh+4F3AqZJ8JI5Y49O528mB+pjy2fklyasiWuRk/Fajc2VdwPXG7Exw8sagk34liI1qxQNXyaZIsH0CKfWGhjsLcZWhDfsItCbU2ch5qPnmwcK8afijRLl1nKDSNrGdDN4/pDqfM9ZUPt27eFd8R9fUxNXJBUMWPbp4iHpJ//5dAlekbHxnNFGC7VhuX9N816Yey5wdXV7ZtuI1xv0f4j5bzvmoz9F3OSScy0W7/Ljb6K1V9OD43/nutVgpfOYd+0OHR7L+YRNLeu325nqKRg8eN2bhecWEacVTB2VFq8OXyNo7XmT3IKe11emmjNvolsUF9EXq1U4ov54SbF0YgcFnM1KrKZtA2f1PSkO0h9JznQdePER9QbY/XlJ6bet28bRJRwoOE1LDYtVoXGssuxgmmanF+fVyJMzRmkgHsGW/xCoMSK6jW3/+f17NykDyk8zU4Eb1oDusMU8zMM5pwHxhmnrVULJDQv6Ko8EVPtlP2iV8tLFXSBJK3y7oSdndWD04IsuPndF8e0TMYGY69Y0cVrrYDUrpmmdHaiX3kZvpizg+el2I1pwEoTi/IlG57hxsa8UzmQCXWmHhPNvAVsp3gCmggWXnhXXvOgOSin95/Ao8TcoeqpChzCaPXs2mXkYOBYo8R2/S94qlVRExptGHogT4Nfgrc8297TfS+6pq9b15OrpMmaOlNf+Q6HYOQRZagc8+Sy1E+/ch4jMJHVF3hxNljaRtlR74SZCxN4XJ4wXD/MyNT5qyvbqp2XG1KguFKYjG512WbIfcdbc8ZmHXuIyFKc2ZFmfCExFY3LSftcLdg5al3fALdg5QgstJYYIacNEyYuNtsEzct8zclglprqS2iTNkSMogrNxUoo20Bf6B7TQt2ccrojdfGYtCNoipobEOz8IoXKoTzJshxqenwpf5usbkwLUIIM/5FI0EYHNsGs3LCLUkZwJa85Y6U444Wkl5ND2Vlpd1x20uJZAZ8xiGyM7kwiRuug59hJkNzyLyxwJjx+zUq2ImxKKI1Ci7q+ko78pagm1tNNovPt1uvEiR88eqSj9sA+5YNRAUGhlWCB4xESyiADTDvHFbB1ZcG7yDiN7/pq8bo0x6yc8IF2kzFyvhlQ8J1vHj568OTg8QNzhszY/HAvlnbMRSSzGbPO9D6jDbOTxM6jgyffmq/RvvW52zp7Nm4xWWCHNO5j5qls4Yfff23bgdcs7Jlp5E3Cv1l8pkgf7eqxq6aPe/d6fOM+KtngHpaemNk0UQAGapbkokvWamxKiyliETgO6nRhAdJbadzk5NX4YBYr/Yb53QLwWjtPW+BSBosLfWkygsNEe2kpF2LGk4XHs0ga6cSFzPjGEIkdcs4/ZqEAXfQdtm7ZnFVmpqcCTPFG/Cw2OANvDQ3CSFVpF3HgywkCy9V4g0cZfwbHgY+LYRhUADSvphagmRcH6+CBNQ4sGv7iCeYRgkqm3SPrvuWaNDZridlti7HBzkPNvqnuvA78GDy0SJopTg3SwtJ9yriOU9GIqe3BzleyMaEFeFKf9c3Z85hB2IUE+FB8uaqvYaKuY5dZVs1k/rkuaebRfcQ97DPDKypBURJ3CTCXZlCVx20Z6WAH4TNiRhGgLy3A2DbmLcpwYpjrYPWPlXYZZTyhof/T0S3K0LEMfq7tkP2t+aaYTMRTmuf0eDktT5qAS4sMorDNOnYWS7OZCylzJXYwlKklcoxRpfKSsY5y0NPxVCaDcd9aTXJCClsro8ERbqJwzOoSabdEkBzjLLSab4WKFTt4QpoQcNAdHZu7amSyE652LkRbHZcVmmDw37phoKQdU0sa30FwOJ3+tj+gQfI5tDaduZp53uHf88nNKLcQf17MfyP558X8lykV9phfTAByRuu/ggQkvf1I6efF/NcXf17MP1r+eTH/EAHos3j0bvEHw2ra92L+008/oSZS/Og9vsTz6yQX0VQbwUWuP4nc8mL+aQQX7t6nFlo2lvOvKbUQCX9yseXF/FPJLS/mv6DggsnsCC1CnB8otYA0PlpskUI+Qm4xXfikgosU+uGSS6tRv57o8mLelV0w58QMbpBccFwq8gp+OZJK2z7/mef93//5vyTNaOsECvlKimU1RRaMcm4BL/jbT2BSEmvep7PhHTSNkCOAxxL31oAMMat20xOeyokpdgMMT9fa7djzHJO39E4N3zC+Xnp8MKmWwSjw/jItL6RedoUQl1ux03dqfTOt10XVyouN2HX27rDvmsxGfe+YaOBUYBGl+vX5pAH0m0xr2OADPlc4tN71Jr2quZb2CMtyTgObzr/uHEm4dZVu3LqJCqwumRoNvmldtgiCxpr2iUlfd1dYteeXDbJqgV8rs2Rfv+M4hGUc3uXYDj9zDcSf2nBqN9oL6yctnv6MRPCLC5nf/EKy5cHvsuX/D7LlpxPzfhMp9b+KbPn8NqP2qQTQX1TEu/4AxsC2WRDeHlLN6O8PgWxzCmqn9TvgM57ThSwZSSZNLJszKNeKakUSp6Qfn1YThR/yJazRwuv0vYdKjHz65aBmavZ3DsWRSKCOAcaFovgGQl3ZAYR3Ym81yRRzGwc4HoCNY8SUSco/BeHmKBfNS8LI/HwA3BIBxCxRtp1S+g3iplbgAijWpUmSZHEcnGCxM0FQ4AWhy3JaO0D3LkTAMRXKIaMmbZ+D5cB7YSf2uknfxKfE7OU4gzAFYNULXQtzki5Nem45rV5IgBH1uz24gpWMWPtKfOFs7lpJgl40KIiF4HKao9EGuFZhrJasoUhCu/MFoHZl07GJ2aXD7LBq0glyRlO6hopT1LyEm6BEteNZo1wbws8iU9N6ansP2qBg9rOijRkntCLJOVRkI66NZxiT2aXN/KD+naVxSYXEu7ACnEWtkRy/cpps8bLhxCuQWSCoU8QusVrCngZoYi2QSye8uwmm19zCxJXL5QIeGCRFaHVwN6CxXi6OUYDkYBTnNsm/yJ4PDlWsAPknPUBZNw3kMycYk6j4+vBLZ+gOFVBBzn6V6Bs47o0yJG7QlmTDwiXjlIun7Xomqdiq7s8CGbAAavR3RDFvoL2IJtZqfyulmCBJy+l+wUlzi1oqBbAZC2nCBljWlmGXIPUxSRS8ifDEn02POdE3qWIV4+9b92Nx46HVKaheVvKZu7xkT9yboTIKFN0MXTO7BI8h2KvsTxwBIONo8vK4fWpNZRvdUzkrbRL660O2CFtIe4M4nIohVrk2S0ocE8hPfygBjfaIs7IF3u6f1nOOK9+z2exd0J6DJoz4QDFc+B2EbFV6iPlogcDt22Z7y3z6l8fxrhmeTgO/X95om/9XaK7jqnyLSlCmAAvRprwiDbckXeKeqA4398OoHgALJ9owH7mjY9/5mZQIEPw9E5e22Uf77iUcV5pGoIH2Ge2qxDzsMxp6+2i9rDznsw8ZTpFNrrbLJY1JAsCd5vcHEJ1bUJvsfgxfej+UFsr73fkWwyAMR4PYZvZjaFJZauzorQBd4jYF+0XtQNFhI2E8Rsu4JA9BoBTKPs1PyvUSqaAlhaOcM/0YvfT+Vixu28wYaSEH2SC0zXwOCApqpcJs1vve19X0WGJxniry49GiemMBTh9xOzsJKVvtLJZ/nb6BzEnCOGNJ0OV+U7VCJ9qjsh/jl0Si69t3IQoGUQY43O5If0erqxYI8opEo7rbSunAN2U5gdljRz+/sc1a10abk/dsc0LUkQyHts20nP/l6b73QFAiWajdNq7S4u+BvkIr1soNNDEm/8VtBl4r3+hE+l60E4WDYBBn0ch2gvFa972jy3m5PJ3+extdkb0KLRTaTXT98PDRM+baTcuyl56TJz34BfKymz4c2Ne9o3Hx5Mm+zS2y8v4i8uiRxLtjm5dwSLfxf1rTPh3lksq96cDw5WabkaPLzaBZn5EodTfJTk7CZFT6RTIe+slkMvSLfDDwT8ZJkSVRWcQ5jfjHlyHcTZuXv/SOzqbzuaIMPQL82Vlwu8yIYZxlDgmcIEs3kvHA+t7B6RDynVxC9x674lRHs7gNEWvNG0Q8opVIwvZ0/j50HCZRmNpOPJz7Ril5VrJ+Npajnkcm4zP346A6XXDmYSCHr6aVgMm8g5LDwUuvnar7PXJ8mwTeSKotXoq048vBERxdb8rQrWYHhfPburn0G+G3UZ9MMjjWvKf1eFnycYyu6lvwedt8nqnImamQttQnxetifmuWE4bEf0cMvqtD8UN5fHpOPEcgFJa+mPNJJjLCti/OBXbSBCXxRHn+Ldpv6+T2h277aa9tJ1N+jyzMZrs9ePR437s5u7PTxqZu2iTbSZbfIzuzqdsmed7f2GfgffycLU/PSeej5flGIhWBq/GcdZ/brFGtcWONhgmEKdJbIFVcw9Ev9DlkQk5ZfHF26U9rZdq+xK769cI/KepV7/4PZwyVYli0hKnXpAbR0y+5kUfluRfGzJgjpykpdu732bg1JZLZLzRlyz4txK9ayZAwTP5BK93R7TZnrmBzzDLw6HJ++6baVMLa1Cbb1r4V4Q4eat41Xhw2j/BckIK/AZCl4Bw7iYJvyZ1R92YvaCN0sxa8R7IDK90Jjvm+WTDoBvMzv8PPpE8MKVzLcext6Vbr3Gw97ZMt1O/3QAs3Cb4NWJmzNzpw3TBPMem2cr7gbPid6sCNnVH21eoM7ZR/WpByf7SGCOmi5b4Hyq52awOzd18izhV89sgFqv2OWfBXBlPyln1AdRt9iGg3VfyrwPsIcLL3/aLFiyPax9pRkB8Us3r7d23tO6RbqyMgfp0sFjCemzAFUqR9udW7z8eQX6yr1sNVcVrrI3oI0MlbpbfHZ3fn1fnd3n36VxoDI9AHlWP9uZmiqcj2jY8sXWwHvfv89yPLIrGC6Fnse1Ske/mRJVtLABVrf7fLVAPbvGiiUAoihuINz98XRRObUr7p3aZix8wSDvwo9YvJG1+ivvyqmt01JFOfF9Z+wiao3v3//N/UHNzXV46Xzrv3Dybs38Fm3wONIluIgbX5Cp1rtXuOxNnv2e4BNT31ZcDs2pBRvLbt3n/+nxvaruCkD5qyOk3+4i4NOdadGw/EOpd/vF7RYjXr6Yuii3UJ8zD1cwFlDdGCC7Y1LUtjj6qKY7zAhTGw3dPrrHt8iH4BD55lz8bdt4dOHzMTmfIZ+l0GN7n7JbSae1T8H6KBVkC/mipwISZEKILrZXWPi/xDXPwhOqH/bZsTus2zQn+7Zju6xQWdkToJUr9HDOMP0bi9xumGvjx2FxVd2sVguRRm6g27T8Eofq8XBmGPfWC+WsCM6g28NIzw/z3vH7Nqn49EeFUA6rV0iuGiAFDVuoP/Jvd6j5NkFCRJ1h+M4yRIo7Q/8LIoSNOkH+W0FZkL+VMN+nGeBfkoGtMvvJ94Pr+nL3h++31fX6fifXmfyjfvyJfNpa3DbyrRrzy8Go3MO17nE1vL32e0wONgFA37SURfJsk4jNNgFI+oXqi/UZb3fSg6WRI3N/QH1xdEYe7RjyxI4qHnk8acxn1/FKSDaBwmQTLIqIBBQGq0F2XBaEgPSetNktyL6TJO0fogDpOxH5JomPfTIOdRGlJ5cX8U5IOR5ydRkKRRPwypHfk4TIM4ylBJOMrcUrNB5MX0KnU8GVCvqMwkiOjDnOqnYmLYpfI+3UwzKhSDkPXDITUj5OqTfNj3pdH0MjqdcLnRKPV8jBNNvF6PUcMwG2J+hnFAH8bU/EFirvhfGiDpziDISMGg5iejxAuDEY19SLWn+djP6GaaYSAHGdUSUufyLOr73A+6TqMgjqlZw2EQJdTMLIjypE8jmuehR0Mwope56/YqHpKigMmJ0iBFfVQ0JjgPIpJcqdxR2pdaqdMRNZpKHwTxgGZPZgaNyYY5DQFdhjrORGc8pETI3EKPSk/oaSaVpCOaxLA/RKvRSHQ3yHIaR6piSE2kFuKCVk+WyBUNYTBMQ4wgfYxqiUzwjg50GMT5GE9G/Yg+izJQTBYRidDIR7mX5dTdtJ/SexgYak9EA081DIc0FukwCKmmOAxSXI7CINeLsU8UPuSZoxnJB6F0HzUPqfwUNQ+G8TiWkY+Ik6TeMCSKT/o8Ih4WBA0iX/ydAZMt47hLTMhszMWvw/Gr6fx1OZnOr2P5FxcXgXmnMQUeyHHSl7PpfHoPRx2flq/zrnrr7USRbW7/PtuePrqlv28eH7t55LQG85Q2D2KKwxzFRbQOh+Gw8odpMKAW0D1zS+/8fRYNB0GKPQYfhFjc8Qj1Z7TaY2okOFiIjWdACxY8hKqM89DeoP5hY+D+0TrP4gSrNB/ROs/oMhyCB0ZZxt0jdpvm0pyImM2YuBitXaxqYqC2cV67mZFpW0Y6csZtC4a0ZxGHysGaaOWPiAUGyZAGJsQGlo6JH4aJPBumHvESbA+ykSUebXLE+83lmP7QRkvtp/sDYsARsTRiwHpFLG0QD6kBIe5nuTSJh472sCFNAzYIzBZ4ODU7G/JYYJskPoqtZTiylzRWgwHml/qcpblHj5mV8W0vwU6Q6lWF/lFRY+p3mKF9uvOCNZKebS+1THBsmn6a9GBA4+GjaOwY1I8RCJQKHyWxef23Z5X0YDJdXcco5amwyPXxbLr68pOww1uzwt/Z0Ueyo5i7E5FIksUsnRJdjjJqGa3QLKR1m4B9ePJHr8YQAqKQxRBaIHEW9kkATIfcuZyIGUJnhmUGIRItJ941yJnTpOAFJAUM8XqIcogn+SQfgRdSnSOshZzEpyisSOLKIbiRlJiSYEjfkOhJDCdmAS1LIgw6CanEDekJ/x7TckoGEFTo5nAgfCcajewl/w3RUX4z9vQFfUILsvVmxH2lzmhfs3TYJ7aGhUvrPQ1TcI6Umg5GHA5SloUzEudoFUcRi2chpELWD+hqkNCXJP4RBwDDgjgJBtNn8YnKDHIaVpL+shAfRTR4CUTCymeRKuqPwPhpAhII6fgsIqnOzxMqOIOQDmGZlY+cxDCMakw9IP4JFYSlO5bY0nwEFYWk0JDnjCbDXI+FAFLmjaE0lCnBXgoJDJhlki6Bg2sIdiGkPChEVBVtJaMwB6vLqNsJ+DbUHBplYvtoMP+mVqZDbBRZDOHSG1LzM7oNcT6mgjPawWJzOYY0moHk5D4RDbH8PB011+ZNmtuEVSzIqAn1jCrNWc+CCAvhOhnFY9ZoElbChmj3EHpVhElJ7CXvLSGtkhBC+BA6RE6CfTwGRUe8BRHvpgmluQ95g8wxULxVJ3rJBJSQCI6NF1+hCdTxVN4DkeBFmqaYNzL+wyTDV0NaAhGURVZfRmPchuZGAzjy+KF8EXv8As3bGNoD1YI/tF2TzkUkhb2IdmxqaEaEIVdj6hTqpx2LphJLnZqd8TtMD/RSFKJCsIGmQr1IbYVoL7eLJp5eDj1po7Tc58eifI1oJEGSVFOOto2xBmNSRAe66kJerjGzSb2mv9ko1/VKAo3HL+SyPMPEc96jyzEXmDfLH2+TeKRX+hLTbjxMPF8Lk0rs0pdLTHtGFJQ3vOCaVnhSrl5xG7KRtCGjlcbvjsyVvKNNiLUJUmXMLdCXMpAZ15aZ8VFRKY6aS3nxt5cS4P+JFOjXyQnmeaNMLfVPcH52/uX6d72kLQiEg4yZtojUI1pwYVoRo6MKK5iWhrTsc/pLu6Q/HBFXUek7jSHL6z6egSvwztLHhpHR4qaVzts4X1Vxhg1JvhyCWdKHAzbjDGlJYZsiUgN3Bpfhy7GfwWbA3CwksXqUQQxOs5G91D2diqS+jIZoH/h8zLVok507pm/UyRDGoF9N9PnNlwyyRtTF+fl1S6Y4nwbmHVk25Xxya5Mz/fDp/39fVr+xfJ2S8ESkHpL2OhwQRyfRN09YFRVr5BASM+22KX1KyjKrz8NRLjcykqFGtFWORrzesNDDfk4y5SDVy4S2F/ylpYudNozZYEc7Sc5aJTWIRA8vEns1idVZGFXQfhNqPa08Eq+rkWj5Pgk9oyhlNTYPIUvShympBemIJRlStfOUZVWRa0jvHUCFHqOBORrIDYHkjBaGsVwnLEngRzweiIkiIckA1mGWK/s+GAANewo1ORT7Qc4yF48ECVmkyQ9zajZ9DsKA4D2EvIfi+LsRxn4IwcyDzSLnjZlNzZUvFleWpUd0JfspdY5E+IrkRUjsaQLBsALsesJ8jkQkNoOPQrGRD7HhEk8chSx0hsRH+XpIFICuwWpNpBMzSw5Jws8gT7FdPAcL9EKi6gHbZ+XGmHjmcBRDdCIRZoimj6DZpDG9O4CpnqRm4uREc0RpISQU+kPcG0brkdiPI1ylI8ik1EeefRoUbgAxY24BOgpjE6QM+aE3kr/P8pC6heGG2A9RjIRv9CeimRLlJoFSBEM4RNWYRHkoapCah/y2KDv0FgRZUgFC+TbERkDf0LyJ8Z2mh0acSudmhNgr+DQBg0p/Q9paoJFkEV4l8uzjgxxKUkTLn6Qd6CwQv2AdD6NWQ0MmIlSNAw1qJe1n4ZD3vijm44mYZSYi2KHMWYxOQHPjTmKKM7Z3DaLM1I8K8gSCa4R6qGQSx0mdy/iMhsTHyEjEJKB7eLnPUi1NO22bIxbZk+EY7etzkaknY6AFa/tJKRtGYwygivMeUSxzAow06y7DRApjLTEMR90RRgcijBV1NCe6AFOJYN4iMoH6QgsTpkHI8axJpGnz6ZDkzJy7PGDFNIxZLx3xkUIIjT8nuoj1ykwjTm5IxxrxVIQ8n6Mk6XOTDVHo8IUwsaV9PniyV6QY0nzCrgZvNuh49CcHrcc0ITSXOI5IoM9FMoA8MGBpRCY4jYlITYTeTawNBw+kwxBhQinlcSaFZkCLhSqBUI71hOMwGA9DPv/o81EEsYZkxHQGqZwKHaA/w2E6JoYkVB3lqWeXAKkuNIy0AqI4ZGUNZ1nEFeJIjumIQM0VKqMKhI74zdzOHfRXWBhl5XDHzBgz+fz2EskKCSaWxezag3B9HsxK9Y1eL6tf/xD8Zplkm/TRCCqRR/9HG2J+a4mEyQAKWZ59RxRVEKkO+/wPycr90IdB2w9xJ5V/5LY8+Aux5vwATIw5mTzrx/i/djG0hNJ+dBaFeBl0Sv/IA9oK4qJbAmxESfaXCDpksVE1Hg43C2o6wnp4nMNAHxa0E9H/+KVBP8hTP8iyR2wB6WPbLoht0P/kuU/82qeaaenR/8y9JKT7w3/zA1L0B9BZUxLAiOjpU9INRs1rfE18aGhqwxYWVQnsWPiHDYl5XLjF94mX8XsZjHzmO1T4CDURixhUCe0//fggGAWmHzCXhTjkDdO/PwZ75OMCUkZguPSTfyPWGPncL0gv/GtM76LsKJZ/acMtqLs4YJcBpLuDrKZ5TTHCMRhqRP3Mb164jkvZXXEgwz2NTDPvIcpUfu90HM/aPmfsP/PH8eL88nO43ibe7RyjevcRgwesg0cL9YVy3Haan/jPcIjjy6ZLGx54i7P16YJLvoEDdfPTfkffsGPiH28oebpCsSj+vDgvl7PFpFPFtry39OLjxaThk9o7Z8BtDuzV4rzNGxU0Abfl1KH3Ld95vjj3dg+qlfcv3rd7NuEvvefjYLjHoXLNlURNvy4vqUA7WcSbiBvNa+meHitfxOz6GQ0GA1BKR4kiHSrrAUOAWqb5zQ8X1WLp8jywKmZNePm7QZX52b9bElTy47HY+ULyicqTqlx5s3K+9u55k8V4zRmHaBwfCF7LV5cPJ7t38PzOHr8+PfF2cbnn5C/BdUBlLqrqEXDS73nVYlxUR6vFElhQVNrDVTnb7eE9X97zTYh2b+/zdjmLubxBpVjkp929TraUVvn1jeX3u83b20ykwn9s7zlZ/FFZsZv7QVXt3il+BJn8d6KT3ss7e8HJYgkslF2JdfTu3XdaJ/eCYjJ5AMwL5CUEee72xtV0/LrXdzpVdntVBnAtpK++Lk+KdbXadZqK/94US6IvGhgADGBYD1ar5fR4vSp3e2hgby+o18f1arkbdr7ErP2TBP8Hs2I1PnuMFKe7d3YFaar2aWmvx+XEny041YAn13vUWX69rLttvX7Edn/6kRbBnX9+i1D8SfnnZw8PTZj37nSyd3Xn5U97Oh0P56sFYJZ2N8vGfybuet/r1TNasme9jdeuOh29Enz8X7Kt3Ro3BhpTdO+eBzbQ2zZsCjkQKN7NEYCodufrqup78m/P6922W6as83V9tlnQT5/989vp5Oqna5tshg9/iTkYvtBiEKC62aW4Xt7AJBqup2Uqub1zPWPIbKHHi8mlDjg47X0vHwy8//iPplbzQ6vuvtsdb9PwgNO1B2+mNts1TRBfVWXv85s+WSjMCL0fOm9unZEba5Ng6FtXNuht8Knr5+j6STmjC3+1ACgFsYfr2RJNSYuPbc4Kb3VPilkZCOBSWe/2JsWS5rs76Fu+Q4VE8EgcsHsHX93p0OR2jg725HMfqIl3KsQZux9unYTraqe+f3jV3e90RvbePSObuwlgCe4z/IOzl+zimnEMOhPBOc8MQBKJUvc8+2YAXJD5CuCMzs/Pdza+Pd+yfAW/UYll94684Hax+aw7iHjiS/u3vj6dU0OfI7Tznscv33HaZJkAHkznp18Tt93Y328obFpO/ulOewJpzp5PZ+VivdrtkvEtW9fijghfI07iTva2Xm6spTu8lu7QWhofb2kGVhReOWdovDuS3+zN9LQguti2TdiHgf0oYKhTtL0hlwCK9qGAuHUI2zTYjvLm42W5Wi/n3e2hMxcgomUxPy036ecZbncL5ndpJYHmQZHautqh8c+3VCEfTJlMdfMgdnZk7nZrsa8rX6G1xa2pr3+RpkwazC3svIbwtRvkBiRe1SzlsgLuvN9oX3ljSFIi9oGX39SX7a3kXdolJ8sVnBWq94g5nxG7ZJa5yaGbDyVf8uHZtJrsNsS9yWPb1TmMh8Gz+XuSepqCuzVuL+9GRvbun3P6BzsSau49P/jq0YPetfVKtz+ywtuO1vu24d3lWjHN2W/uYoeDPncX8Ar3d/4fSUHT8g== \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_032e2b45-a78b-4778-afb5-f2f2ef296ad4.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_032e2b45-a78b-4778-afb5-f2f2ef296ad4.msgpack.zlib new file mode 100644 index 0000000000000..3fb8f17b9717c --- /dev/null +++ b/docs/cassettes/qa_chat_history_how_to_032e2b45-a78b-4778-afb5-f2f2ef296ad4.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_0e89c75f-7ad7-4331-a2fe-57579eb8f840.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_0e89c75f-7ad7-4331-a2fe-57579eb8f840.msgpack.zlib deleted file mode 100644 index dac7de115a208..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_0e89c75f-7ad7-4331-a2fe-57579eb8f840.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -eNrte3k8lG3fN6JIopUUBi0qw4wxYwvZyb5EJIyZkxlm5hyzMdbQohVp1yKEKEtKiz2VupBEtiIVyhKyZ33Pc+i6uu7reu7P83ye+/287/N8bn+o8zh+x+/47b+jju8Rlc4BGEwySOO/TaaxAAaewII+mAlR6QwggA0wWYfSqACLBBJT7WwdnVLYDHLLDhKLRWdqq6ri6WQVkA7Q8GQVAkhV5aBVCSQ8SxX6O50C8NikeoNEbusSTogCFWAy8b4AU0EbsT9EgQBCe9FY0IeCGZkD0BB4BLwUQSIzWSCDi8DTiAgWCUBQ8CxIBASbCTAQPGkgpohAEplAQlDJviQWggH4AAyARgAQPJZBLASZxlv5KztlhA/IoLJhZtBGTBbEHU8BacA/siTgaQhvAMGmESGTsECQiAgkQ6qzWX/hqIIwBhE2tk6QoMxASDZ4/iczZYQfm8mT7PdNyZBYPggaABABIk83EFrACCQzAYiMxWbQYAo8E0FmqigoIxQYIAWATcPkMlkAVSFMGfEni7nAgpCZCCc80x9hDMDmBplkeGv9X1fDRvvLWt4a4q9rYE54BAsgkGhkSAXY1pDtQYQ3A8BDpGAgDbHg0CAEC1oMCUmDZplUPIUCKQ4rwyTD0wzIsACdqYJwgmyEoDNAAuRxBAmg0CH+vtD2TATIQFBBIkCBhqF1FABBJPv4kAlsCmuRtTcXGuKQiWSaL2xS6sJeVJABIKh4GsQF7w2tYrK9eeSQE6D1sPtZiIUYZSIoZH8AYUTCQ1EA+kCigGw4SmApnRgA8MsYJBTjD2V/WgT4VUfIeSwyHd4QVgyOIQSAZ5IhTYEggMCGjfcnd+GZTDIcXKz/0GNwzAXiubAYRBBWksz6G5cdgEZ4doKHfOksJEYFi4SixBuEaWnQKBr6k8mCHESFPnzwFCYADUChQofyFyKEeaFUUGHpJAAPh3I7n0QqCWSy4rP/nLE5eAIBgPhD+QPCNo+/4xtMpitD1vCBwzYT0oAG8OpBfKY/ANCReAqUrGkLq+Jz8XQ6hUzAw/OqfkyQdntRYySLSwf+Op0Ja4fkhUL8PVtICAMLVTsu5DYaAq2CVVNB5QYhIfORaRQocJAUPCRPGp03X/jrBB1P8IeYIBfLVnzawuLsX2lAZvxNazzB1vFPLPEMAin+Jp5Bxann/zrOYNNYZCoQn25k99ftFif/2A6jgkapqOf9iTGTSyPE3+Q54sGfFgMsBhdJACEe8TdQaQQQ9CcD8S3Dnp4EH09vqq5noK0DPQhDNbPy53BMMI5aHHtQC22LNVQ343qqswxQruYkshtoTsAwkWgNNS0sBquJ0kKiVVAqaBU0EotioNS8iVyCigbJM5hki7I3ciAF+RpisIY0N3uMlhUJZ4BSZ6PR/vhgpreBr4ODnbeZp4uLgaYlmqWGo2Kw6D0YrJGKrRqO4+9jTySQzT1dDHQQkHRsKAt1sWbWapbqzmhPY9DBTsPCx5Zh64Bhmhs6uGo4Oas7sV38VfYY7gXdLLl7fxEPjdJEohYlxKHUNVHwT/bP2KAANF8WKT5FUxOXwQCYdKhJANFpkMlYbGZUKhSHQPWL9MVmkWxr+UcIr081hmIyvtgarrBqaIQtgYVQQ6mpI9Ca2hictroWwsza6bbR4jZOfxuCeU4MqGBDJQNp8jPk0wkkNs0fIGYa/W2wF8PBDnkSFh/KUiQQBFcJ5KJU8bf3IR0W2iTSwjh/IbOQIMMXTyMH87aNL+ZFfWBwUCCRwCYSSZxAKkorWB1D9gbYBJ97i0sWyyUkEJLKjE+BTJm9OPMz7jIhXVFINAqJQj8OQkJpDlDIVDJkT97vxV7NjE/FQsZ++FcCFugP0Jjx6eo8b6BKfqVgAFQoYOG9/2CjrqWlVfT3RD9ZYSASTTTm8Z+pmMCv0qDVqMyHfyVYZJECzd4O+kmOJBPjWzZDH55YLRSKgNLCYzRRREDdG6+ugdfQwKj7qKtjsBg8TusRVPvIBIgN7E06yGAhmVA9ZpBZ3PgWZSo+CC4yuhg0FoODVNWBijmBwiYCjmxvYxBWgqkDtSeAAuKJOUamSCM8gQQgHXkBGJ9u7GpjYG1hVLAP+WskIW3pvONMfDoNZNKgppPmCDAgz8RnEiggmwhVSwaQBvFyMHCNv6dJxGGweB8NDN4HremDB5CGUB36ye33uEuFS206ngLJziHE55MwugrakH4KOlCn09XEQX7inZ0i02Bdab7P+H3lTgjz8X6WUOyr/CpQEkXTO9dfTejYZSV7waH12vJHOOp2g3iNAmlX/3v+JJEfEwqV3LOdyRXVr/qr/a7zKSVmCSk5+qH3fpuKzfnYppE1U5HWEnRrLP9S9huLR6FPLsRneDi97t546orTEqO93+yUfyhSBfzKv2pfOd3dopl4c+R8hpKZJGCCnP2O6LNcg2uwPZpy2/E8UeyuW5mvAF8u+OFi3ZfJlPVx4zbmh6sf776vKc6fsVtFYQ9m//pvsVydN3GSo9T+Bw6i+5YOC6/bY6H1er3xyErGSXYMtX+Efkf8IXVf5UxJQHaF+Jfdp49rvz6iM3cSvPPAPXuJ31a5C/l2d9zG4/hC7z9LjDjgJJORCSDvGcmJHU34WGd7gBaG95XZtrn1wInuYh1O3yaT/ZUuFxxNE1ePnFC3zn7cNlDkG9DvGxbw+QzL5niEa64beEcV1VBeEFHXPhw3w8/HNz+/hG9ToJ3OcQE+vn9y8N38Hx98Aao3QIQdu3DkbeGGKJBpdDbc/ffvx2ipYZQRGA11ZYQmRk0ZgdZQ14K+0VjolzoO+o3DqeFw0AfqwJ96P3yeRf7OGYkn4pEolBp8CPjZsT3hMyaed8bwxjMBnLrCv5v+/+9NPzCA6kgiuamj1C3UjDRcjFTUWf4uJK1AFTzJnuFN8sOh0P7BoAmGbvxLV8X93vT32VmYBAagGJ4okqe3P9GexNFUd7I1s3BBuYFUe0tTTSPQwWofh6uFt3UBCPQ9BG8VvBXal2YbsCcoUMve39iW4apmo2Vqr8EBDLTcfAJ8OWoGvzR9C4bKHjeWIQjirbB++zCOwcYWJpZMljfdVcvTgsANQnlSXbhUopEl1eIX8TQ0cP+Jpo9WQ//Xmr7U/5OmX/gPTR/6pw4YCLV1si+ZFn9jx3/lTHB7sY3zcjq+4O8z+l92cEhWw/yTc8O/rG3+dw4g2H/dAQQm0dJS+28cQJJRf3v+wABQ58ara3kTsGpaeKIPRp3oreENoLBqmigNLYzW/81jAx5HUCNgUBj0v+bYILX2j2OD0+V32fna+Wm181kXL6ePOgjLN1djOPjYq3wW5llvBc5IIA7l5vGr3gkB4webegcS5MWWGnk5jjXut/2hPz/W5BnxwHXsRWXp/I++wUCtkxHzsWOtujL18HfEXF9O6dxUn36E/nypjpz1+MMPVbbfC2cnKoeZEdUR8yOS8x9c5gat52fGJtKajNQ+aN25bLOMVLHSXO34Ad2eS+SBFZPDfZf97MO/VmpjdIL2gjtOhX6+UWt61HhSy03vsoc49pMjx84rZ3idc2didRq4uWFI12p5wRW/6n1TW0T7BT6YhN6O2InLPL5UZ2dofdnUjlXirxqOJgdnZOSfnT4uc+B8xQGS/6SCiNvzBzaV5ceblmbKMGRfFzpuf815w0/NPNoifrTNa49cWBBhRCdMCitH2EGNdrH4lFPWAxo0rToZfScqurJ7aXddCQ6l77dFrDv5ZMyuq35KtCe6Bbtq+g/TCIfOlOZQ/b5VZemVggXCfTNd8l5Fb/2WvwGXd33xMRW17c0UO3z73FrPBtQRj5b8WwzNodenxJyLCzvvj9lY33jUiTvVPbSWWjnCOFtlLX2jKbwqkzwbEXRfD81OnF7JSnddh/BdJWpxOTP6xn3RNUtLUuQzrN1rp+ImUR/rDqUlPq6RkmxfcavkoopClZJL6jH8yt7Q9pRvJpjRq6W12yb3EMVDuvS+tuRJu9kd2GJ6v5Z++ryDvmgS0vuc7FhVtu80QckwJjrqWqDIS9NtReShstJrxDyihFjPtxeRP8Ya4lkyHhtayo8lNA2esB2mhIz218o8TC/k+66udPdH3SjOSirdvvKuEerY9oaDGQ3rS3QqjyGj102p6RfGuQ2ePbFVWUOY8uroqrEcS9GS7JWMIetDUTt8+k13Hdm7wvJwRcOupr1YjtWKjymlVsTLykLVhSzPgxf3iPd+W4nx6sRNvy68BD4RaonOO1AuP7nqg64b7Zu1Z7bePfm9qOfLj7671mY8L/Bo9566atMc6aJ2qYOrL0m+iUuUsE6sjTwaPW+i6dX4Rnz/l2tRd4O1Gki6yMusM8/opsmnUvrX7E2Q9BFyKm5+UivzyFhZc8eNzg/Mk6cCd2d9RISGmZ/jc/R31piduWu2scg1Cd+3weNuywaBJZpxA3aljjWUV97p0U+MdJMcf2hxrT4PCg1NnLI+ldk3tYV1UWSJmqF6VvqRGqGWnXaSj87k3r47BuLMd+1rMtNtu1dM9j/a5fO+U023f/XaOmd0jHLfd5ll9grOIzf2Upt7QkSuOohxR1JuUaSe16wqfHW2j/BEbnXG18HDwd32p79+WaNLNLwiQs1UG12/xun46AnxLQ+biyUs8GIFkT5vjErXZYWHyTrtnIsuVl812sWq2iOlNSHa8v6NyuXa6bWR3/dv0cwtMXn6tJ4b2cb5OoT0rTxuGiz/8vwmtdv9Ahpu9Kokyg23G9vkTGfXyn+L1bN/a4/T5rqvE7z2zqY8RikYOz3mcLC4STJ1sP7Bq/OF/VGh6HV+W9ukrB9TdcsuDxK/OBmoB0y6RhnJnjp0AmTanig8NzeeSJ+O5W82erPn4SbdyMz+rBlX8X3tT8yxWlOjouWHt6fk9BJcOo+TelQdtolcrbJ3AblhzprtR7rzbHO3pB/WmC5Zs8R6x+Da2U8TfhHCZ03c6yrCrvCdW7v96DGNTXnB2LuU01vH+LH1gPDqkedfNx8zy8isLs/cXdox/f6p5Nfnwxd6q8aTbU0wHISk755z3Mi37+WlDUPap4mlqkcoPRbl/HObaowf4zGfAKO3SRwJcWH3eIGtjZtEtdqXL2V7zmgojIc1eI23BjdM9hQHadvGuSab5RjNZJuPC0vS6cNLcLKay5iVaYokztjuddu6xrhzm7a4Ok0inbfWxu7TG0Feyazf/X2dldfkZg5//CP5tbeK3sde39eR9FCG/75pLtAp1i/6nvQxsjW0MZgiUL30XvFO9Q+xZYmzE7jDNxBdQW9j52Jl35+dtLwa97xd4PQXQR/NXZ8qTLLYw1XpzX5mvb0V+Z6XpfTGE/brxYXGjFBqvqQ4ZdZe087Z3HthB9vQXG+JySb70Wv001vLKqOZuckpyb5KIcoSCg/tvp2qJw0HX+e7VeRx691VUdxvcqrtsR8IZheVmFNSO6L5OKGnY6ov7NFvbNX9kPNB/F0Huzfi+9b79EmvWcTj2acim882zpqtGKg4HjZEir7v0ZHkf9DsRV706/nlAqYta746dsccZu0sRK4WPy3Fzp/IvbEVLR4gR/Xu7GhFsgqzy45sXjrlzN251cpw21Pt924eE9kOQp/ycuLp0qmZBPs75QdCtFK83xVnXfI/u+npC4UGgbL+ZXMKl+m1rdLouX199V+bLofuDTl+biR7yCdWRkzJ3X+J55luIfOQJu9HJ0r0sLXIsYtnz6zOCEzyzrHRm2KdBJec9PGrjx6xKXqkfXcsrASrUBTxdvrT6QT94NtMC/Ej3fWM1b8Vaoy36Ly5lBLq0PP+pQK6+MmbUv9dkQgR/gKa1Xjrb6HHhoss3ULjHEqvL2keHsq6z68brNMbb/xKm77nnESWxbN82va3U5IR+9bY2Ki/PJJSxhjcqZn3W+3lUhbf9iqr/qLPznK+Y0mRe1VvVcjQcbXH+6Kml40QwQ3XKVo7gBVj33zNGmd6XtYPaE+GEUR11NNvk5MfRX5qouSmkGxwoYrZS8ff633N076S6dGzadU16XdGoidUZjuzFKJGWqpvSXt41sVx3YVNRacn4xxs0t1zZG52tbRL+KpWkrofhi1rmjSergQ21tRRnnqp9eqKDbx84FeM2nGDNiBGmZtp1cW5X8pJx+h1BzvVdJ9RpTuKblRwR+q4nTkhH1k+uOrTU9dh89OpUuZU4Vv+OrqKJgGdXuGhAQ15oSr+z866ELucDwRIPIssOZS9IvC5yDNNvopHl2WXORg92S/ZP3TUrDQ0OkeY2lZaxwr+3rJi0HLJ1DJOxveyOOTwfevywRCdyXeA6N42Q+nWYdOHFV7j/Tpv9V6YmNoTMvkTrw/iDnW8GH6remG2f7rXZIdGyHFccE5vYQdJ7qbMdrdN2yeu1Fifk+yYEhK63Ns60l0VqB/5Nsd7NHyq/dPbZAHLsXbHiAKTsClTd8Xwp7axSDVJ3XWBOSud2xVWeaw2C+OIyR8pj8xwcry4wRolqxL34QCa/bw4XfVCv3Fn5KBhb3f6VOz1szafgpL2KOh0fMlJSv8g7CbAfZHW1C1/MLeDQyqdynOlrYp64H6+7rnN3RgZmTz+h63Hmkc1TPSNm+O8Qj+PN+h8k51NnXqwVuXBUYtzz5ds0AoK3v7AcMOaH8KdfvyayA72del93M7H21K746ILHmY0N7drtKgLnhL8vr3zBc3cpn04aXqt8A7hmP7JoxT5ytMJV7wex+UFGde9dwrgPz71JNdfRzZxmztu6N5Z0cs4y9wBM5no2i3B3n3tGtpGrYWRfVMWUuDj8OF87UPu9Q8aWLf9531nn6mnSVlWuPg2WG/d11xiPCuugfFZWSCiUSx95qXVq5O6tsnCLqVR4o6k3OBaU7kr653jAlTukWyyXh2sevZbRn3atudH5i6VvY2or1qnnyLy4xrfTM3ZuhkVlmzAhzOCKekyr/PDs7K6zm5Guo/FZE/1ItclEBDhp5ZOCxFP6ha+4fP6uCUzJvqV1Od30k/2WZk/aBRd2r1xpkdc987s8+SxxlUFpG7h0nH9esuSSyh5N5tDU8Y7PpVIihxC19o7KYl6gRib8i+MYG9wTD9/zbW15lIfPjGn8lh+l3XW0CSXxVn7X03ZsKlhLae8+TU2Ijng3ReBXfRuGerw++ygHEehjBO5m71XfaRcFipbgronVrAiJL93nvhb+taWhC6HNxT7Z5KHxt/r2iGPpWi8CGwR9Nc3YVaMhDAajxuGa4Qe+ZzJ3Fn+TsIm+I38gbGgjBf3B2S9Hh9cEl9gVx/o8kRaIjk7RTvitm5aXu7hAco5c9wBy+t3/KLLqqxsm5XuaHhdZb76eD94F/rTqScpTfabkvqrxZ+W5wwgzU86ki1V5bEd93uOXpw+3zHp5rHvO8fJ98QxQc0NkuJZAjq+ympTQj7D9OcFe936dfz3HXpWEe6dssGtIKgpZMX47ay8x8fCdos1pyPi2td/1PORRc6ENT1J2L+qf+Da1v1uHv0dli4bKZ1jVYmFyPRyv7Vn9uZc9guYJKw0HRstb/QNPPF4lEszuHhrm9+mN68UbTxak1RGNiz7zaxqvUWqtHnvl+gY5AdUQb66S7dgk9n9q+9aznxjKd1UdLMzaVn5OmSD4sNxfSnXusM14ch1di1pWxxkum5h7Df9FsbUy57jOz474xG00vj0B4d6f62r3/p3LxGxHx4LcwdtJhGRtUmH99VOpVdaEeQspyTljl2h9oW/d3cT0z7sigcUY5I2BoYI+G50Lp099TW/z2oye2CNNEU2qEqgc+U+TmJd0KNr03VWbgpXVxCeHiW8zevK7hTNiAFWv+TsKgsPb3GXxY3ZPzVLGPGWYAwNb7Z6VNNiC3aYiGv38oWNN3+88gA1S7LtlZldXW3quyfu/N4jqRtpdwM/icrMaJ6J0TxX6lL/Rs/wYvjZL7aDydf1m2M3yhFq2sjFEoEnxLYMHGsKDRqnVBnIdQ48SvHokA4LbGwVmBnlO/ojW+5T5/vyzs1vidxgNanifmx5VU1FTBv2Pqha0D84P1rRemQ84XqE+8WgTvNzvaiJzfe2CYaxK4U3qmpd/NTZXk4In3TIdy+Q9V/jGoVtCu1RlU3vzJgcBrJuNodysRdz/PoM62+K3v/s3BdYwvo2N7R2W0tX+2afK8LjFDlvkyt0HL65MrenLjLZfSqYcKZdZXeCj/j+VtGQqoGpj40qxVumNd+H5Pts3NSQ+smmLXqdE+Xr8OooQsbrMrNgE8kK9O4bV18dupHYjW5zXCcVTlPg3Dp/V38Wl9O1svh8Zc4c9Wjg5Ge0eUmXb7G1zWMRicqaQ9sDhc87SzjkPt/5iQT4Jkg/Ncu4sCatJWd+/5izz9d+RW6X4xPy92PGVfTNZbva85+le2wrjtGsmwn1mPpxSRB7VmY8aXnrsjqU6O6DMyP0ymVPiigZgTbLn3jTM35smoq5E86KeGGrePlVoaGvgMXmoIhbqrfHC9pqEy1vHKxbHtp/LWc+XNYr4KHdM0Iw9tEzStSU98PRvKLE467vjPm+3ErMJWy4TgplpLuXvN90cuMIvcr0u8zDji4NbEE+4DI7KhR62kWEwBXhX0cqOGhyb6L54bktib1mUUk7iKoNd4IfU1Lrjlp8PTwal2hS62G1uuOhwcVeg/sntrpb4FLd5eI/qrC0W3zyBTXWrP0eX8HB+p33ecI0OzB86a01Vqr2m0D4nE3xbkW3DI6514+bWs4esS6mE5V2U2+NFAZuuqgbiw191KVtuR3XeLybtpPUUZNrGl2ZLWiZ10S5+Ng7+v79dtX4szi7YydFn3HL+6qogsIc+0HCzTwlQtOJxDLFNGnTgZc9L9tZW+mxa+Q24kUzhY5xBSzWvxtda3GqRB09f9Am1z33VrdMopmDLt9vBsbiA60tpSU5BuHiJwzrhmlTAZWxYlfO98QUl1SPudKsBQeVQKXzW0vcHme5734w0dGaE03aYZYX/Wl8gx3Snpo7riii+U7kQaNqxbuVki1HHiDTDhXrm+ofm4rcvXKAryU2pJbQnsUtSw/oeEFLsakLfeKmkBCQg7+jdILkrAqITKTsuv1D9yB5/+X7Rb1i468aMpvZV4Sv1LpMPND34r+jx/fuR1pzgfT5+POS+yfvfDzl4RKBvRCSEn2DYlfUWCEHhpZ1PXoQgxJOD3d4/fYw//UhY+Xs1ZMTgzfqvJfF+qL0Hr1b8rzmftIA60H52tzcI27DzXZ7i1LrFCbTl8WpfT8Zdmd2tFiZLchQWiMh12gGTiknblJPnz1PSZs6d+pCwoETMdEY0/QX3gk56M+2EV3Xaz/+tt9tiax+3PwPo1g2p/mFvuyNu+DHvImPToYEyuYn4GAtCXHX48n1D7llW0cLysdeDjbN3PAbHJHd6Eg62IhDFyhW1rmU9BheXYO8J+YRriqUlnoQGz7UNrVjQ+13E/mcGbHP4LYe5nZXof69N5KngiKTpsMHJNrrpyysxaTabXqcRHDNQ7duPNuDe+fQ9CRlTebkwVNa0oNRLhVX51l5UwcC3gYFiyblGK9LPHM3S8rBUkBs0DzDxOfmJ+6UruG8G8e/hOQlX7n6ycjnsOS53xKWYV8YxeiHH65JFU3+WPlgdE/CLdtq3YwE1RXlvfN5fu7pJVWClYLvJjY59qndjeG80l32cdsaF9nbplVeN4VLDjg4TKyvSbKWrDmsrgE2vG04nofuqgmbrkuXi+hr4eRj8Ox1G1oD+9dZv3yJwbPaX35ti83xGysU2yV2Ydmzab5o+52CG1PN2tPlO+IfsK5cNnzwakmvMNn1VMilwpmPN1rrE1oY3g/5TWa4s0GREyZPdaLGpgmORWEKjS1ksU0sNzvhtLvJp8o2B7l1f4r1lL+5nuHVddXJk1ut3JkooX1rpyLZBVk3iU1eb9pB8v7W08Z/rPDZORe9I+fOmQ3GzCvxf/eL9GsbHt1X/U5EafDIYdU7rKb0gc3DHS6qAmLIt8NT4cfuCRFt18lsn80ooi45nthrdCh3F7HYF3nsNq1jje8Vj4n6qA9LpQYHZo5WLm9Mwr5mDS41ca+OrAuv+TEY1hPrS5nw+jbYvGVb/9nt8UMjia5BzZ/LgHclOZpnK0R1L5RO1Ybvkj1yKTw5eBpZfgiI6tAGDSyTC7w80lyWTW+n3OK0SlK6ApOLetd82jH53bmd/EK/9EbAEwkxuvn+pMbGS262DXkGekEKHcvno+9kfOitV19r7nGt7MnkjGY0LZC7sePeoaXOveNvbIsDAuS1zmmZrh9Q9NbXS2aFWqs+ZS8dKwlxfViGWv/Qs4Q4Kygk9jh2OLpujpBbILoh0mXM8lbx7ob8b+zQsrNtVsHNz6Q3nqWs78BkWvZfblt96ulxkdsvzm2brlYd/ahRKjX4YFvrnZHl44k59Bd5L3/4kFrGJ5UO6wf7N3MTrb9sEBk6DxJn+sx8vLuWNB+ejVaYvFP0bJWKcHe2yKolN9JstXbZdjQ8bP8tmlRASl9hQFK19dO7kib9qokVRb0iOt9Y25m6UX/OKmU8C33kbtVmjUkF/LTmt+lbO15tOnv9x4Zv114IVV/IRrpz1dy28jslbM0XslPhJnxTMWg5r3VLWEs+Xlh/teX1ph/X11ZIVkyFWXuV1N2fnTH0FXRu16+9vCXqoJ25h5H+eL0jylqp/5nifQunmal1Qh11BSJhWR73X4lv2W66zHA2toHoH5o4bVt7AOX3YT+utxBc8kznVUz1qudbQ17VX5e1s7Q5dz38vIS3e9wzIWPPxnCJ7KLDM73URy2BaPfZ9eEdFgSB9+bLJ39g+tRM6y5GEXbsz+kvHCany13oefskae48SXHfqcodGSv0S47mrzkxV61T7jYfk/qgaGK2t1LEKuUcgjxBKXNAWq7c+fLDa7NphqJ82DWd1229Gwp/vNz3uW/24OfxEIWI7qPnH19KvV+SvOreVY0LyY93z9lnRQR1SIBHjN24u57zTwfPvtZ3pFcLHvxNXqq45+XOPOXBh8iCXZhRqZI29RcT5UL+0SnOoZdNBapj91hczQWzut4Rt86MfciSzY3/3L1eUwJQCiVsV8y6VkGld84PNX13L1L/GnhU+jMrx4WCtpa9aGSffHP/teBElWzRD6KSjr4CH0huXyIjGudHCCOf65WG+jZJsJu45WvBXsHsqUMlVO3oRwFZolfGJ0d9r1WtN8J2NeJQKzfNS9ToF0/XnBie6HviHKH2IlmBklfPh7589ptS+XiKjRT/vbcvg6S5caGCX77U8mFrTom8EFZ/KrRh2db0TsHcKcXb9SVe91pEEoqmXE56Hr2qIbrhetTIvQjEkJAuSXzCIt5F7zhnedPsR2Do7ilKKKJQdP+1rsO7Ry6ynGI9syvXV6Dld4Vs3bvscVOLNshfo6X8OjSSPfqZ/83nb+3xZZNu1z2a+AzAE7IxpdjN3ujWzaup15fvnflUMnCUUFbvoOyEDGmu5TeT/kqdXTaefeM6kvFGzoBxMXiq7JPYSZyU6NeyALNuUfW7PUGvNj5s1PHrX6/77hmXZJ549Yv8tWvBu13CV87PXV0+mRMxO9Y0P3UVRWqd/lwsu0JKbmRSbj7MqUP/TciU3C7VGa0ju4/cC5qZrS21RczMfnvXrTM3mHdH7vrHwYi5qIjT0jO6BYSpuQiVef+w1xGzffN8C3fcwYochXbEP73j/i+DO1ds+CfgTleQzcPZ4WmI39FxPCDdT7AkcgFAyQP8LWD69sIgPBIAUcG3bvAEnQwQACYMmoOvVskAByD+jvZkgX8HwVRBWPgguNDeRJC2jYXwp4GBvPkFUmUEE8+FvvGsf6D5uTmMFGQCsBLwvlR8EJnKpvJAhPAd4S+cYDEIZCag4k5zp5mSfVUQaBWELQdgcMhAICwwHmFlZY2kgxAtjPxks0AaSAXZi4hIxALAE1ptBKMPafCQLQ3QRthR8DT4qkvRnWawgL6ELzRhqCIM32Qz2XgKhYsg0zgghcOTkMb9ib40oC3yhtGmTNg+PO0DYW0hwbmL7iAi6BTYKfClJbT/X6Gk0Na/wyhZizBKJSPQSQfhApARAAuBp6jAV7Fq2xEkPBPhDa/9A13LIMIIUCqdxXPs79hSHoSSRsJDRoPGeXeiCDrA4IEYYAwv+A9YUxhMCizSkWFUJpPFYBNYC5hNd7YaCk1gkcg0f57yMHoU/pM3zqNgs8gUcjCwACCFgcRI+FaftwWbxbtl/TP2kwTL/Z8DuUKWQPDuUWHZIfXJvn+LHP0FtbowzWNFghSgkHkgVB455Age9poOxfeCWDyjL2rO00cLciWsKS8fFu58eUH3F1Srkise/MU9mO0IKE0AGhQKsMiQiYAgOgXkJdzvUjIAPBOk8ViDUJZ6Q1ZjkaG4gkIGwBNIPJ2hlIIyl8xgsv4wGJMnJCQOpB/1HzT/GTML2FlYbSgqYXgqHK//QMSEg4BHqYwgQMLwogYP2RfOQ57H2QxgIRaYAAzo+B1evIjYNjR1RCjBgGUii4RcEHKBcDuMOTaGZ4kA/S9zMLr7p4YwTBvg4ClsXp5BdsIjCBS4ZvnAgF8lDhkPjSzENI8pFe8HwlfnCA7IAn5m0J+B1YvCEWHUrxJ6O8wUqgYLuy6E0y9JwgMuuys4/g413ufqpuLuTkOruCsoQxM8CDGcu7DJmWxvXxBPWSCE5IdqIswDWqIPUyup8TZjM3+WVSSTDhAgTQi/pxBcv3UQgApUsiDekCILuQtj70E2i0KmQTop8NgHQpML/qCBHICiDCuvhFk0HolN5QUvlE8L8egAMEE2A/KNNiw6wgIOaxocjjzIBI/hgvWBhaAg0xYQTLC9fPEwKh7aC+KkpoKwAqFdnQAGFUEFqLBgC8lEhYobRIBRQZjZOcHQaMTP8mqwgDKH94DSBvD9PZUWjb1QUtxp6ioIUzL0DSkKyc0T2+6XImSyEAXQ2gUd4Dt4Mo0NVW2o5jIAXmmHRYekoXCh6gL1ENgJPJPC9QSgMaFw5bUW2F+L9Y3nCpDnPW/4SQPos7jwZ7YtKA1ttuggyNZQPQMoPkgC7AEC+edWUK1B0sm8nIBYkfAcMshrRLzmSuEu2MYB8KEABBZcUen4hZwlM3kS8ioQC05EXzjHIZkYgA/k70Vx6FBIQhG1YCYTqJVx4XpJhVfBdR7KCpDJgjooCIc2VCAZC+h6AAbyk2HXIAzIVJjr4kHhD0T9woMOAJaGxqZ6Q1kFu4ZXTv9on3DMUChsnoCL3iNB7cuc7esLWRDyOCIQZMCNQcmCCgUDYiHatBGOJID2p7IHZSScKLwGy5OFQWYuHCLU4Wz35UUonJW8xKUvNlzthQyFt4DfY/C8xYC7IK9j4hk/ax7vQcpPlMk/Vr7fOxfcaRlw14MNy4KOLt5suPxBVQUkkHl15o8KBK/SXujvMJJOGWFhDGPyoAMYETqGQJ5SXgg6hi8bzoCFDeAch/gDgUgmCYSKdRAetjnPqb5sMhHgaQO3OHCBM6wBL5cX+z9tIdks/igK2v9+f/Lv9yf/fn/y7/cn/8vfn6RiUFoa/9IHKFj0/54HKKlodXXN/xkvUNQ0/jsA0FQ06u+foBCIRA2iD14TgyXifIhYFNYHi9fQQmt6E3xwGgBK43/EExRvjCb08y97giKg9MsTFAdrUBotUTyy01Tv/mqEuXEC/Var5c0j985Jd2U5kRp1gg4UXTtXuXG3/VwIUZU/s/NTRREXnPFpdxTf3eJgbdCzPCV7o8YkY8PAbNuDxO4LxSVXD8w131Os9AR7rX+0SWZel3KfUZTxdDWqYX9WchuXub0En5qqrafz6OIVm1dmkhsyHm2+QEo7Fl3/kSjxzm7IS13vUv/Fdfutk9OG0pfxDZ39MGrm+cbUGt8Qcadhc9SRBtYHwSSBQid7Je8tybGZEXzYaXO9iOn0bfs+rw8SWQUIbdkiroy7xLfTjnJjXZ9YNUoqakNwfbL8wz0rBfWqfVyGVzXinBG4R0e30tuM+6zlUt+uS0p9k4JMOD622igr4fHB/J1Rj6Zkbq3axzhYOH30kcBKlMuDdaZluyV2CpBFK74+3tpw7mblZk7g/BA3G6G2NpIutCUnbKDW+XbsCocU5lpE4XBnyoqPj+8KYJ8dt6SPmvOLWXRji9LiOPHuW9poYV5hGvJiNUaPjcBhRM/Wt5uE/UZJwqJmiBCXe/JtWysrPisKuhVEbRcsYdNcIto93+aRBSTvVkyM3RxzzjRBrB3viVr9yH5D2AD/TE0PeV70UK/K3ZgiheuC+qdqdXTZwv38ujptkfGKjxUbnz2cP92enBrT+NJ+7qzpAXtu0ulgs+72lWG2yRhSMTflzbvt21v2pAbn3Wu3I0XVHHtVFTpQvPj/iylvvIivl/Dx/R/iE/u+ \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_1046c92f-21b3-4214-907d-92878d8cba23.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_1046c92f-21b3-4214-907d-92878d8cba23.msgpack.zlib deleted file mode 100644 index 8d7e1cee2f48f..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_1046c92f-21b3-4214-907d-92878d8cba23.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_17021822-896a-4513-a17d-1d20b1c5381c.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_17021822-896a-4513-a17d-1d20b1c5381c.msgpack.zlib deleted file mode 100644 index 4df53705e923b..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_17021822-896a-4513-a17d-1d20b1c5381c.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_1fdbb4bb-8a28-47d9-b3db-1cd9a543ebc4.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_1fdbb4bb-8a28-47d9-b3db-1cd9a543ebc4.msgpack.zlib new file mode 100644 index 0000000000000..42eee9512a137 --- /dev/null +++ b/docs/cassettes/qa_chat_history_how_to_1fdbb4bb-8a28-47d9-b3db-1cd9a543ebc4.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_52ae46d9-43f7-481b-96d5-df750be3ad65.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_52ae46d9-43f7-481b-96d5-df750be3ad65.msgpack.zlib deleted file mode 100644 index 09df1e43f7a24..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_52ae46d9-43f7-481b-96d5-df750be3ad65.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_570d8c68-136e-4ba5-969a-03ba195f6118.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_570d8c68-136e-4ba5-969a-03ba195f6118.msgpack.zlib deleted file mode 100644 index 2c2707eb067d3..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_570d8c68-136e-4ba5-969a-03ba195f6118.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_6ccf0204-6e64-413f-a110-e5dcb8a1c329.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_6ccf0204-6e64-413f-a110-e5dcb8a1c329.msgpack.zlib new file mode 100644 index 0000000000000..b45b93c9210a5 --- /dev/null +++ b/docs/cassettes/qa_chat_history_how_to_6ccf0204-6e64-413f-a110-e5dcb8a1c329.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_6d0a7a73-d151-47d9-9e99-b4f3291c0322.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_6d0a7a73-d151-47d9-9e99-b4f3291c0322.msgpack.zlib deleted file mode 100644 index 318c8c5dfd4f1..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_6d0a7a73-d151-47d9-9e99-b4f3291c0322.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_71c32048-1a41-465f-a9e2-c4affc332fd9.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_71c32048-1a41-465f-a9e2-c4affc332fd9.msgpack.zlib deleted file mode 100644 index 76333fe35e9ee..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_71c32048-1a41-465f-a9e2-c4affc332fd9.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_73920571-8c26-4988-adf1-b0f695fee50a.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_73920571-8c26-4988-adf1-b0f695fee50a.msgpack.zlib new file mode 100644 index 0000000000000..85082258593ff --- /dev/null +++ b/docs/cassettes/qa_chat_history_how_to_73920571-8c26-4988-adf1-b0f695fee50a.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib index f30797332bddf..df00ba41ef729 100644 --- a/docs/cassettes/qa_chat_history_how_to_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib +++ b/docs/cassettes/qa_chat_history_how_to_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib @@ -1 +1 @@ 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 \ No newline at end of file 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_b1d2b4d4-e604-497d-873d-d345b808578e.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_b1d2b4d4-e604-497d-873d-d345b808578e.msgpack.zlib deleted file mode 100644 index 1d0910250c0bd..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_b1d2b4d4-e604-497d-873d-d345b808578e.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_d6d70833-b958-4cd7-9e27-29c1c08bb1b8.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_d6d70833-b958-4cd7-9e27-29c1c08bb1b8.msgpack.zlib deleted file mode 100644 index da575101ea01e..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_d6d70833-b958-4cd7-9e27-29c1c08bb1b8.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_e2c570ae-dd91-402c-8693-ae746de63b16.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_e2c570ae-dd91-402c-8693-ae746de63b16.msgpack.zlib deleted file mode 100644 index 81aa1af1c7d13..0000000000000 --- a/docs/cassettes/qa_chat_history_how_to_e2c570ae-dd91-402c-8693-ae746de63b16.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_e59541dd-405b-4032-847f-73becf6aefd0.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_e59541dd-405b-4032-847f-73becf6aefd0.msgpack.zlib new file mode 100644 index 0000000000000..3402a46e36bca --- /dev/null +++ b/docs/cassettes/qa_chat_history_how_to_e59541dd-405b-4032-847f-73becf6aefd0.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_e5aeea66-9653-49c9-98d8-113e54eb72cb.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_e5aeea66-9653-49c9-98d8-113e54eb72cb.msgpack.zlib new file mode 100644 index 0000000000000..58e4724e2c955 --- /dev/null +++ b/docs/cassettes/qa_chat_history_how_to_e5aeea66-9653-49c9-98d8-113e54eb72cb.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_chat_history_how_to_f48c5f7b-5281-4a03-84ed-d2e0cbd228a2.msgpack.zlib b/docs/cassettes/qa_chat_history_how_to_f48c5f7b-5281-4a03-84ed-d2e0cbd228a2.msgpack.zlib new file mode 100644 index 0000000000000..df4a1e2870dc3 --- /dev/null +++ b/docs/cassettes/qa_chat_history_how_to_f48c5f7b-5281-4a03-84ed-d2e0cbd228a2.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_182362b0-075a-4d45-ad05-c4f39d410624.msgpack.zlib b/docs/cassettes/qa_citations_182362b0-075a-4d45-ad05-c4f39d410624.msgpack.zlib new file mode 100644 index 0000000000000..64ef412e5ebd8 --- /dev/null +++ b/docs/cassettes/qa_citations_182362b0-075a-4d45-ad05-c4f39d410624.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_1a5b72f8-135b-4604-8777-59f2ef682323.msgpack.zlib b/docs/cassettes/qa_citations_1a5b72f8-135b-4604-8777-59f2ef682323.msgpack.zlib deleted file mode 100644 index 8a0c7c64f4d9d..0000000000000 --- a/docs/cassettes/qa_citations_1a5b72f8-135b-4604-8777-59f2ef682323.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_2903c47d-aae1-4662-bc1e-ee73ff774e88.msgpack.zlib b/docs/cassettes/qa_citations_2903c47d-aae1-4662-bc1e-ee73ff774e88.msgpack.zlib new file mode 100644 index 0000000000000..794b72fd9fb76 --- /dev/null +++ b/docs/cassettes/qa_citations_2903c47d-aae1-4662-bc1e-ee73ff774e88.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_2e2b7a87-3642-4ed8-9445-684daa93b0d7.msgpack.zlib b/docs/cassettes/qa_citations_2e2b7a87-3642-4ed8-9445-684daa93b0d7.msgpack.zlib deleted file mode 100644 index 078b6d9b47742..0000000000000 --- a/docs/cassettes/qa_citations_2e2b7a87-3642-4ed8-9445-684daa93b0d7.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_315df7b2-bf7e-4d1c-9363-be753a6d590f.msgpack.zlib b/docs/cassettes/qa_citations_315df7b2-bf7e-4d1c-9363-be753a6d590f.msgpack.zlib new file mode 100644 index 0000000000000..b1150c4cc009d --- /dev/null +++ b/docs/cassettes/qa_citations_315df7b2-bf7e-4d1c-9363-be753a6d590f.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_3376deae-9fea-4aaa-861a-d37d9121926c.msgpack.zlib b/docs/cassettes/qa_citations_3376deae-9fea-4aaa-861a-d37d9121926c.msgpack.zlib new file mode 100644 index 0000000000000..42ac84b57cbae --- /dev/null +++ b/docs/cassettes/qa_citations_3376deae-9fea-4aaa-861a-d37d9121926c.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_37eaab79-74cd-4806-bdbd-7340652c425a.msgpack.zlib b/docs/cassettes/qa_citations_37eaab79-74cd-4806-bdbd-7340652c425a.msgpack.zlib new file mode 100644 index 0000000000000..0f4112f3313ee --- /dev/null +++ b/docs/cassettes/qa_citations_37eaab79-74cd-4806-bdbd-7340652c425a.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_3e259b2f-5147-4c3c-9c26-b4eb8143e5f0.msgpack.zlib b/docs/cassettes/qa_citations_3e259b2f-5147-4c3c-9c26-b4eb8143e5f0.msgpack.zlib deleted file mode 100644 index a5374b1806d10..0000000000000 --- a/docs/cassettes/qa_citations_3e259b2f-5147-4c3c-9c26-b4eb8143e5f0.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_42b28717-d34c-42de-b923-155ac60529a2.msgpack.zlib b/docs/cassettes/qa_citations_42b28717-d34c-42de-b923-155ac60529a2.msgpack.zlib deleted file mode 100644 index 2af18f9a20fa5..0000000000000 --- a/docs/cassettes/qa_citations_42b28717-d34c-42de-b923-155ac60529a2.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_56f4b74f-36b6-4df5-ac95-f9e856401251.msgpack.zlib b/docs/cassettes/qa_citations_56f4b74f-36b6-4df5-ac95-f9e856401251.msgpack.zlib new file mode 100644 index 0000000000000..11bbd2e222f5d --- /dev/null +++ b/docs/cassettes/qa_citations_56f4b74f-36b6-4df5-ac95-f9e856401251.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_688b43cc-2766-4216-a9b5-245c18eb5675.msgpack.zlib b/docs/cassettes/qa_citations_688b43cc-2766-4216-a9b5-245c18eb5675.msgpack.zlib new file mode 100644 index 0000000000000..96023375a9394 --- /dev/null +++ b/docs/cassettes/qa_citations_688b43cc-2766-4216-a9b5-245c18eb5675.msgpack.zlib @@ -0,0 +1 @@ +eNqNegk4lG/3/4NQ9qRky5LIzhgMkew7GfvYwszYZmMG2UmUkOwkZN8pEiVUtuz7ln0PUbLv/6nv973e7+/3Xu/v+s8118z93Oc+5znPOec+n8/zzDzI90S4452xGJISZwwB4W7nQCAe4GMe5Lsj3DwQeMLDPDSC4ISFZ2uoGWd7uDt/JTl2IhBweDkxMTTCHW3nDBd1xriKOaMdxbSNTGXszKRwcFWsI8IbjrbXkJW0ADk5OWAMMQbOyjLaIH0JBwwMpe2DddQG3cfZo02dHJzhskhzcZS2IQ7jgFb3slNRNoGq4nVUTGWRDpJQoi4Uae7tZH9XU0nIXELWB66h7g1Xl0XeVZH1uosSxxm4YKVhaJS3g6Shjoq5NgquqY2DmcNQOpr/GBtitWEgUw+YubYTXMME+48xTsUR5WSPlvIk2hWHGTnZW5hJedgTzwvXMIXrGGOlDdD3nf7Y/h/+KBF0jcGODmhTcQc0CgVHm8gQ7WBgZlIo4jUQ7fwl/7etP3JvmDnU287MFPQv+T/8+C13sddQ93EQh6JgzsquMDOYE9zsvriWBgxnr+ElrQWy8Ia5KKNhzvfxxBijdM2cUHZmcCwx1vd1XbR0VMz08Rbm+j5QDVP0bx0HjP6/dAn2kspOFiCUOMIY6/W/zvNb5x/n0EZbuMDQFl5YBUWCNw6hgMM48tk7qmBRWHcFbi8nZwIixx4L9/6Y74SwgxPr5mGRCR7hLqLkiMAQYt7ivImFghH5u3DwYiBRSeK7XMnBAYEjiKhhHLBwZ4xjTKmjjzNOmAuOQKLsCIi8v8Qx2YJigkUqWAwG8acCY4pcEQiciB3K2RNR4I7A44hFiQjJwxPsCB74BzlEU4jOL/loBB5v54jIMtD5l0dTwMX/YqX0bz+gdhhHBD4m196bgMCXqtg5OCFEiBoEdywqphxtd1+EaFABJC0DAYuL5xkh3In7I6bIAYX1gBP9dUcUQhE4rDtBxBgbM7bny4PAwHFY4s7B88hZ+vJ4uKN45Hj+2h9WYlZidqIYBEr038qiDli0lZj7HwtWYp5gRbyCkrS3j4UJGKPnjHNwQ5q7uhFMNDFINUk3XR2Cs6OTFsxYQtJVCa+uct9TCqPrbKZibOptCiLYYbzt1e3BKA0wWkLnBkhZBWGHh8AMcMQhXgmtZe+ioY0yNFWTMsPJKsONPSFGhl5G2iZ2WE3lGyB1sKGLKYi4UtLCSMdciTgBM1a6IalKfPP4WwvzOLpjPXDE63BAihDd5xHmIUbFlhgVHjlpcTBEXNw/R5WYuJg6Yw+EMBdImksf68kFEgeBuSTAcpIQOZAEl4aecdnvmBLLQkQXgXEkOMXkQGTEZXJM7dy9Y6oN3J0dnTHCXP+rMrKJdRSTKy0jKSWdra+mGzMm78uD9yCuweNtkX93Jh45cWGevwJoS8D+X07m26EIInhPh5hKJ0kFHjkwWJLnFhfaTgEiTUxsKf5PYkUIzujfJTlW5IDUBd+CI/AOCjyKOHcsAatgrHKXz51AUICIS0vy4YlXoiDF545w8FSQ5kNh8QQFceIRwd0OgyeOfott/xSUAggiCfmz7u9jCRBYlg+O+F2B7t627sTAKUiCIRBJCT4HLwxcAQQG83lg/qEvzkdsiQqy0hJgcZC4NAJhLyOOhDjwEfAKRJX7CuI8eSrqIlAli5g3EATEThYJkobAkWCwg4OkiLKBUa3Sn3D9q6BFlFAorJfIX/GOyRQsJ+r+VfFGfzZSTLamlnGprh2eIKJHTAHSGQGPqdPDElMDkvpHWmXlpKTkwFK/01ryr7QaE/tDTKEzmhhyMWKb+NMXgon7050Yz2YesvC7+hq0VKxUAADQammqQonfGAAg0TtP+nvk2RVE/CLBQzWUgbJu9hUA4AK0VJWM779YT/O2MjY5a+1J8+dE3gtDm6upMTCdw5OQe12k+dLbaW2ZbvVrpKez9VXJta5fZjGxOizmos4uG0jR3LybN/Oy5khvVtBLklWWey3tte4zDIl7fQzpTDg6bUzCL0/gG7ZmUXsvfsjaNiErSUivPnv/NciRUlnbiQGqHPKMkfVhfC9XzkMKcm1R2mgauctFRpbCyFRDbGiso6OKY2wBmDFCA+nWNge0xDnuq0KnGvLKbvbdrimkfXIvE8kWoXPRZwDQbyk0pS4oHlozvhmlVfQ+m3qjgy7K/tHuIgGikuOgst3PY/LJzvsOFonj9NS0lU54+iNMuVyNc2pwOH7NRYhGpf/D50MP1V5PncL4FANUMfP9gbAc74oa3FfKPSUBSWb2RIvOtxIDdSu67rUb6Iz4RRkwM10bX/3SMndW1bT+RK85evTMZP2hd/2pQnLZ9BCdgGv79kiPVH7n5npBKGQ+f2eokT9c3n9FNM/LpD2VOZ5ep6pw6zi9U/7Fa6y/h26shlO8jl6+zqTaJNlJmtDqRt51YCY0NHaLEq79bix3UFo40mf7Y5hLJ7xHEHnpcMBM9MTvO9T7NEhYOG8+W+SDSmYsr12nTutCsoBEDgoDHopfu065OTsWpjjXer48Ay3NIjE1J57zwc1GVriRusiuBr4fkaUY4OqeTqHTPp0QPCtcYFoVrp79Dr+sbza58SIovcSS2aR7ABL3axaNvguh5uZ+RYvvjBcworsmP2pSfetRV/4rbybnhE9arI5QYgx9bzfTtcJBHt/Vj3prGqtrNctJXhT5yvFfeKEl4A9fuE9ot9wdLrU0gkIZGRmXutMsjY3PAZp6eiY3mXx3v4dHROjo6VXx3yJ8633jPEBBywq2b3rsNe1fXbji5rrTxp8RySK5NPEOz8LC4ubmliRm63n/ltWo/JOSljHbjhQoLCG0K0QMYWhoiMFs1LjNh9GwQO/efTlArO+MgMOVB+TUFDRXf/7qEBtwirb9qaOt/SAkhOgKE1VzmXXtGxhaX//piVCUeqVdYxiiI3Fl53B///6j6sbQruxvxgVx5/RzjWGjfvvQ4eFhUqCioiIrO5uo/Z35Og/PTaYnSUlmZ6cnllBR23p2pWvVg0xUN8TEepzA/SsEX4/u7u6N8eryuPHZz3MxVYIRcee6BSFRWjwen+Xhysqk0a2Wr+2bD7aW0/LBqV3TgWcnxBDHxsbSsUPuVcEsVyEhn5z6Nlfu5AGCXRb033UFQSx9ciL9HI0dHUJiYmI3bzptzjXjl7sTtHPp4sZQb5sjmJcXF/VeQCRkZEZsAkqHW+fhV9YEaPtgvYKGoKEUq+56h62b3RGERxfo6GyqMZMtUWwd7e2mZVZj7nU74KGhYrOIJ08SRSylPVYH6/2PwkJD7ZDjhfq3YJfbl2RTaTz5cr0YJl8G2wpaUohubm6Gh4eLzLvwxQnEtcH6wTIyZMDnxkbLQJRAwtkCtrqx2iL6yXFal7XcmkkTSeTRCDiz79mjROJpfZbTvIiBNBc2VVJSUlV9eOKjq9u5Od9KFLXPbxLjm52V5QSGYTAYdfWWk6O9ra0tEgCBQDCGN9m9DaydTIBOiG7Y9NGw8xNiP1oU0oTDFWtyQ10ZgCD17NCHDxeWl5eXllqamkrMX38O8O/LUiNWjeVbVFtPT3lREWNEc7Fp6Xti2PpzdaipqWWwUy+ePXvlOlL2tuJkfB1H3C2l/YIhgcmVOxciLbYHFMGqNHMHYW8cwudTcubC8t4qZzwTdY+lcBgdXZa1+WR3QB3BPiIA3NHX7w4mo2SfGM03cHYubLT8tbWloqz8QnHvgmzgqZ+n59vGcl5GLQ+PHcVy7FhFs1YqbvaV/LpJpJrI96q069OD6nSzj1QrOALGJyZQgdYHvvWaqbIRzfZUuXgzf1qKEOVM3L6JZVi4Ko9gwurPRMukeFr6qOt5j9MUmSy1vdM2f11orkmZRGRuZrB/tZJcRWCvUM73RJ9Iz6/o0D+9lzHRB/RIy7vhjPTOZkl1Oayt3WiilyVkF6gf3XIbXEp/8XWMYTR1cW7B65YVFeZ4qgTzlkZvTXTtUr6X1Lk9uz3cWGABx8DlvvBrYLmVb9UeHFW0Mi+vjE+JFTczhq3JeTadFGWp4pHRYD4Lhjhhp4YYyMufjt5q4dIraoa+GgMcblSqIsMRGpe9RIvtY+Uf8IzaBJT5DNVIEju+yR4hKdCZVVybQRHWG3y5lO7QjBTYZt1uOVh6wgaL+/RVMizkGYN0Ruel/hJTv/0invN3hTpZc8lJXr7R7Np8+XBnXpV+3uhFd45sx882/jxjKrx1qNIkfFjQ8OG5Qb1ny4tFxcUCTE+io+knUO+uMbEB7LdDhXiPHr1O91sh/2xJaaC5eIGjgf8ON79jdX7+8sMVibS98zdnxjfHSn/DEl3OwuZ9XT465AFuJqkcWvj1eaWbEO6uoDMY5mjQrkRCCX2uyxeRa3Tl9uwDMoEUXST/QdlHckro6s5h9y40hJQuZ/vnz/uH9Vc5AMoubzxeMmWiXsHdmpRO+0ao8gqTjPjozEfViOa5poZm/4/B8feJBhkn6cCPMfnjwWQCKwS5TTo6yuw+zQ8hjcHJ5Q8pJGzH1onrmgbFwI8LpzGU3DfAOK4bxEW0cxwfxpU0L9Cya2pFCmUqRQrVckCexTbOjvZ04PA4rlz1bAnWKGs0uTTkGaPYzB1tq/1LMyp/f97OMBDW/KhUaMyoQoDMIFJoPmMq9O3nmsJ35x9LsdI+4GKna0VWcp933/85WybdJbFh6fahri4iIsLyPbYKRgto6utvuNR+bfIX2if26nMPGr7HXaEKlUR2fpOLEMfZCly6dMl3+1vfoTYcDjc2Nh6xeBh8pH0BSL7tLxfdWnlme5OpO12htljEPcxSJyU5ebTWC+vbepXY7zk4JoeuyDaW5p4DPmz36/jdnj6JgB/54IRcXDFgocWlfFm/2POUqjtXm+1fQ3KuXZaZzagaucLLOONrSD7niapz97CygOW899BC9L68za27nE+pyIaTvzm058FOr30268cc0lTDu1iqU/SEcf2V1u2cfI+JD6lBWcMDt1btYxWUj+Rux5ZJjaIX64pXf7F9zRGe/o3NQbp8USmztn4VhXm60SlXVbRTu0zdlWThPC3c3j3SIQNNZq/t3e7pFI681IPifR1aFRx+qr1pH5frTGRQ0U74THrjF9/UJjVCkE3is4udZjjw0mz+Hu37yr6bIsnLdu+OGDg0/ic1Iub4vEDm79z+mzVZiyH8/a2t/Uu3wK0Bt5PTZYsyM0+dWYYuvjdvf/51tXCAb6rOd9wbxBrVjcRPTPRVDHBYf396G+0fARPuXiZZr45mlcUMfnFLc+ACz5ylNVjtaS3lSJCTL+d1fdG8xuK1E90BBL0//Hr5h4iWlp5uD3vVdhq518bUW9sXsr6MwEwIfdKN6EjLrRVt4GNKZX6sRkuaYiByNhWvEc0R3+Ax8NzAjC86Uucay0jF4kK0q9mUubjr931uo7y8gF8rlO7vaIBXqINUCyMo7Bi24+Ov7TLXohedHXNN/s3e4sqKQyt9iqxv/974W0IY3jc/XrvUdAt9GtaMFZW8uv1aYtP9HWo2S/b0lIR6SUyJYaEpPBsrml7t3CgdeBbklXTmOLT6fazSJnqFk5/hmEV1vWMnozNVMrD7e6DWMVnq88umxTsLbQ675U/Kr4gc7WX1ZUNB/fzFJu3+iic/h2NHZLAT6c9jX8+d3BgpY25taSIDujPO9MpH8nPrAGD0cHLEdxfT05nMyMQEM9nB7UVPm43Iw+q/q9Q0vDfKAafo6ky1bwwsu233oMerz8s/zCiddNqDcCgIIr5Gbl9v3RV70ZBj1oMD7ty7hzMetCUtQeYYXLu168Z0L0aTnZ3p66+hw4kq58KUiCuiVYGREWxg/G5Oh5koHYt858DAGtFxTwGDdLkrMjOy4YFBusM1Do42u7XFYfRszg3NA0bbat2tOkkfKEfI3hrlwMWvisiRAlTUYppsbFDoJcuy5K4l9cJKc83Xr8k4bMrLy4tL/O4aGXksfDsdHsntpwClvACdHmTs/oAdL4Gi1K39qr6d7A0DwJMIapErHUVDY8Wmik9Nkdi0KPXrdDlw0FmFv2UfL6c8ZHPIm9rSFl6ZVjpQmfxUJkhGqo0EkHT8ICfsprq2ppzJDHAh/A53ObzJmXu0cndIg3FfZuwA4J0yBWBeJ6gh/Ou04/q9HxKBrGVFVqIGhSg6GpqAXyUQdlHgoxMY0tnV2ipzO+Bnm1ErK+sqX07OODVH0tEoM90TEv37rNerRkeDZbA2Db4/eswf+pzMX/aRSyMBnnWwWndq81zY3t09ONjPTGQXvhIxdrwMuwdzWcrVWea8XZL8LNaugfHSpWiuL6dktWcHhBr5KKgsvqU4STQt0HfluIQ5/8K5z1lZpINPTpcbewDA/nV1RvlZtG+1ZLJugnZKikSzt+n5B52B84HTvmfrB9SOerqpcLU+W312FgU5RD+10foFCoUkLiafsEcaT5qjiyubFLkkHdrrMwLM008UL6jELbiPBYcoBnw41PGNpozJ585tyOD1sp5q6ZK95bnEfb6/0vG++iH8yOz8A7hj+SlhnfKd7UmG+fe4F2AKyeqmhwvRZosL2MntobCeUZQ+wViXQEB1VBM5KOJ4KybmBDYNOouqbrL/cXLkZVvv1zcwICTBbbFAPj19rvGkKLMfh8Q6tH8AvtG3MB+NmN0+e8853THmjcScmEaI/UfH+S/NiExFG0SOk5MEi9vMRDjxltTpXIX6HPZxTvR+BFM9ukoo2I5JF/p4E2p+5MmQMwJg/HPpitCQ7NPMei92ZkkWT0tZHp3toymKkI2x6ZrvDGp1r/eZx17RXERqJ0lLsO182zsrjGSZbdt8SdUE9lJIOc93npRpR12v8t2bu7I7aQDV5drOqvkveUL8l4cQPqmXbyKu1p7M2L82ZwC+GOwJSwTT05JwvWSW5LOYUXafGc63rXoWFze/siLrf7hdJn2OzN7qz4UQ8ZAn7Bz48VXG3hkchIaCTl+bCIeDTuCmd99wHzsKiyA3E1R/Kjkx5DKyqhZ+9ySupwhRiteGXKUJG55awlATeYL7uyYGDjqXqufqrq0redbkRIi3IUK1lWjSVbPPwQUzvcRbkqZ75+nUs2Ou0niIEWFbYoea1n61+m/YbpvfHEV9ryGzpqP7qv3v6X+i+U94CMVs2/BvBoCSTv3mOfNyyOXWPIPxN6I/9ik0rE0gFvDPCt2lesuXfAbpupl3S0yLdfmyoYWkwR9dqr6i3lrXenpUOT91W6MK2NuYTDzTyYWmdqk/hP04L1a33T+9KpXalS7lavoXQKekp19jP04a8CZid0x8/KDHFbuZeigpkKeb0t/vVWlewiKJJFSpdeNcBTICTw+Cglop3xPvGW7w83v9NWtJxRfX9kIaDTMbfxCso1DTjBpyLUnDRpKp38hdn/Qw5mJoaqUxkvFQ2rZO7WqZNdKEfx/9dnW+vZ9nKGo64YnPpbiQEOey7iBlfgE2vQDuzoDGg0zDbh4aiFCCGj9TBQxvn0dfPc4plQNNFuVMWpFyWrgXYOn8VTghtPWy4DvEXZfqp2ZnMt0bhfSrjZGsq+Z6rZP6cYO8xRKMcqdRs2KH8bYjrOMQ/i+v4ytYs7vCJns9VYSRqSXDCz+FWqEu8QU3AUqdHgPODAakpSOZbGI/6s1zWmvJQzc8DWzQ3nOitub/D6t7KuJvPkmMt/J1ifZNzLU6GtPIWC4JcIleExYoLub0gHaXutWLI3ze26T0+oUROwKx/Tc3hzIJenwMWu5Ou1XnPb/77Nk1ICjk0e5pjWOtLt/O5iabrP3EQgmRH54EjE2GRiyVWNRtrImsdXT88PY9qt9tz8pUeTSOLy4un3w1uzVXHApmrTPr+SmLnzr/g4ME2Hef5HfsSbP5Zbobpmc7OGh8Mv2VliT2JXZLhumKTa+LFAmJkpHtcwWXBQjwkQjlp55LvACXN5wduLf8VKX+dgAQpFhmfYDUwXgfKATfuTqgGDA1cZCebnOXKej6jSdZHdPWJU6xDQdLoFDl3a7EieRTN0+O6oC9nfS6cUnJvHPkoaYmChMn83tDUtGJYke9AbGNlJwiljUzaFvOhuPS1NPKw0nrW9E/D679V6T3DYOVLo0f00ZMWyHFvzk4zK2tuv6YeLdz3KTll976bquhDJa2/oOzl1/e/eugbFR/2Pv3zwPFjhiAGYFtUoDJVgS2+0MtWyMXnmNgWhx/FHA4W3qjHDtVw9F+RQgCTUyc+uB11n30o1SL9TYV8PNbX2NGNCcoRVcwwb21+8N3LzNaTun+9P6/8Jbo2+tAq5qZ9YttDgCwtSRyf33HeQRrxZEIsR/fFSGln3V0lflK5hd9LQGEVj+McThi7rYlBcT/pgr55QqUirZnpd6+DOdIgEjOM78W6mxRK8gAvzyU58LClgKT3q+CglMRz7Ie69TE5++cZqFHrTU1SpKOBu/9Fu3tSc810EOg2mxsABAQwHikEc7b61K1uvN+bk45ornCxWOXiNu75d9LU0sMXc6+wOV3I3d3d8mBL/AoIOjzZ+r+lrD4wabE4y4kPvvNp9NAipC+rOy0il++lg3jfnsbaN+TuzcX6KJK/kkWGq6eTb/IYIBAD48oAUBbu2wsBJOUOLX9i3GTmLNQIrvzMXlqvjApV5eRsfCp8dewWQGTIPDRRY0EeMJ3MPMpvLzbclSOJPXkvmxG23GHZ0FxoFWA49hnYqHoTAdkdNk3VP9CF3dtQrWN4iaulfiZzz0eHglV9nIR8t1bvcQp820NOywFHpQSShVletEV4HUZCOpYHLt0joLCYXGT/w+D8NxMRI+/3T/QMi1vf11NIdI8ob8mmt44SwpEqqvURrpxOIVkhlJPJWqSFhcJKew/mNg52FWX5OO7pvTshNKzmndgbSfZormF7oP31uGkb27ZRK6x1KOdb4iRPjhoZVuueMetEC6eTBX6YTFblfHb+vrW1qaKyDsL4SuP+a/GmJVZHfQUSy36DJL6PbCenLN7bY7sbNdlyZhqmAZiNGmAmS15JzBrdKtZ8RC/PnudVwMRa2wEP7zy6XqSnHzfwEAsVDlg/4vBdY1I6vPnK6rDbgV+4byqCOHhEQS/WSbSIP10+bAsJxOPxacc3o6Bigo83iV1LKUlfuKyaz297AnR19IVfLW5GKTBg8sllkZGRqHAs+fPw7keq2ef7lTbLvxSr4LdSBimpKDw9T26dsvz1cycbCrtRL11BeYkHxkhy5PFoT8mteeBujZ264tSNH3+A6Ob8TUkIW/R0/av5T2l591r1uqPpSEQwikbNrx56mjvR73fQVZ+vpm9csUX6saVxmmD2FpR7PzSC45bWwznVsYk5a/7u1uGL3ceJimLWmbUJnYs5up/6XwOXt96MRRoVcvIdknRh9A+6Vtt8ELeZ7P/x3xLHi0LSFiC+2DeRPbAUsa/alZSOvUSx+VLHBzUasHS/mFPAgyTaV7axvbuRN5lqsKuvhlDVXlIbdmkxO7MvSHy/0eIgtS790sMhTPV+OVwbA+MBKPU59mokU+ab59kORQaw7TaOClCMjWibe6CWqlxOaoM8M5vFxpOD3VOh/XArCK8vN+J5PcY3bnZSaahzRolLevqszb1ku2XsEGFAuL/Jkiz+80xLXdKgkar5wG+VN1cWdMWt8IFqoKohNGByclnz905bBfut+Y7CDSTEB7ejH/6spfBLWjeqIsIXqd2kfij1Vtj4i/cXDT0FrhsLC9+T1unbPAw9D57njeNMwiWidJdqeeIH3NCY8A2stzRnPMXGceWEnGRpTv0GOfyNHRZ4D0uo/clny3RpgADlLkKAuZrK1C5UWcuoXUtILN7mNZa4aS94EeFSDSbDIaJKjSOv/oddPjdKIqQqMMPrpGL0Hf0tCbnT7lYkStEi6P1qqbXIDKMOSuCE8NylkoIpJONtcluqpdL+wb4MfQCLc9tCPjx/swk3R8S8/j60uydh94hFMR7BB8cJFmXj8nDD5JhGUwmsElKl8M75flS6cM64RaRAIUqc2vfIPJy6r6QxuBvxHnCrUm6v+jYlQg11c6QEP18yRT2jNUNU+LUhzv/QYha51+PfS97S8rGboyzTyn5/cwknIqONuuBClFz3KAc//vJR58TSna1K+3TX49X5hApnUOTcIMMrTg+E2PjZ5q8xUMuZ8xKz2ZmZvyPdv/Qo2morN3nc76tejwx389AVyNXBib3RmX2EkBCQsU3ut+nBQUFbW9vl1WeJ9tLiO1C5ufmVr2JJVYMUVwc5R52pO2MFbWkQt67dw+JRJpZLtBUJ/bbiAswUaV2bVTodYrO1yvUcESpS+KXdOXS6vHL3WVvyckg0GGFXsWaXNf78MFiw7orN2KCLtps2zGpXQQ0f4Ylom43o16BRuFXkuY4NH9c7GJsPH/rRBXKuuM0u7nUr3wjTW/x8RiYIlT5utE3JqqEhWG1SYq7ki4SmVeuuwymDEXBBiPVaebo9S8+0+RQNM2ah6ZP8guJGB88pJZNF6aipcRe1xdnE15Vt17nOAiK+fzp0le3h96ucjyIdbKBlUkoRbQA1ea3UaPJxMMjqsF7L8RHRhorJ0OzJ3//JCNba3BFTvMXr8enNAk2kUVyqUtni2vM/fX+ZutxFXmfcauUFndLsEciTSwJzVWXlnx8D942mhVyzLc/B00WcrLWhjwFgl6SBFBKD0pLESVtJgJ6FGuZ5WsP7E/kXNhOz/t3nz0yKLIy+OFCPp1k2cG0aSHP/qKE9KJHdiKqL7dz0+3Ga53cig+q2SMP/jygEbLXce3cSaAwY6zlXfxxtJh17QG/NE3SY2Xy5YDYd7GMlu2PqqXA0lHdnswNlmpGaVmFw81NCSYyXUv8TyTar4D01LlKW0STR6GJtiMSNRvQKsST1eiGLwVFAh7cIjV+O18Oy5ef6xr4yAtHNRbUZDbrhokshljCyr5YT7CVFjTvBL8aI+VfEjFrEsQraUdeszLEyh2EdN6aGNdiBYLG7OUOxqtHtPXBQmz3rcpJToxaeBvsM4Ce6c23X4Qe6+Yx2cjeU+ry96Ht0rVsh+MAYKxYvf7ZbndXv2T1D5t7IEjInGQLb0+lYwG0jY7zrGI7IPhy1TnKHR222i8j/Lp9xrWHW5GJj1qadZNjD2wso+uJDm+ccFbxpr94zXNb+jLw0qlIYRvfXfeLRzB048eI73HBCNnxdXFEUZ1F0mYYfdx6Z+Unt6YPVxY8WirY5OrpmecNpXHHgy3pmZsn2eoDBZFbSQFw0Oin4D4gyPUGf/mxW3zPpXyD+0IfG3qwy/Uahjrlr5YBoOH09CTKMv9II4pFZtWDMdzvEFXfpKi8cNkJxOLe4J2b+dr++JtMFk/sxlSD8d03Xnet5OLatq48ip84RX9/bNYa5Sf1YfmedMT0cLa3lRhwB2HSNuGcQc+SzHK1N0nfoci4wsO2JxN6ta0RuU3lW5a3sdEm6X2S3foqWX65oXwzGFTC+ajNbdf+6eydLKPMss7DZ20LauWL3GcK+8ZlBQLvPJD7vUnrnGrpwUb8/kFcmi95f7WsT28kWmuTR19/RBeZBnHfFwaCMgzKs+ZC9tpF1bavwfxOHAu/z7pWNqyysFIC5y+snm0yszTYflXg805vqpYB7ghT0V1Y/XHcZ/W01+gbPXA+XrViLDrfWj+9a/5VaHlX9404ASCI5KSlvM17tqXUVoO3G3dKVkio0Edc9Lm15iuRA14tBSfq+FfDsiEeS+O1iFCfOirgI/zY4lmhsXqHwWWf/dt+hOxFIdb1zXiSFN2lrSZtk+vAy7lPJhQhDiMXAS6m/Sd1D4rHN1xeyB9iJ96Z9ZagzE8NoR2XmaRcq7qSG5625a9JXbU0lcjhNbpYee2ohjcBll7pRpHWwirzS8og82zTKDUH1Jo53AYvUni1rsgdc3O3fFud9tFJkp1wRDNx39JvWAWCgTulMRrb+sniyFNbydZ0wcFiXWM59ekI7hupGupdo2yPxaxPtUoNhf3WLIMf0QMfGxtb2358ethzSbHo/djhE9j1vZlbG4finGiywN1iYT6DYqMnautPvV0lMlHXwkyvhnBfSUJJ2OkUDgnIooJPWgHgzVckIFfPe5GdIXegWPCsGIk+8U/50D4FgRbSAEHak9/as52N+YCPU06jKyysZz/7doYbodmu2fqVnz4vOWyzXNWO4KXRi2tDVnLr9/RvXATNKM+mz+dLU1KqJ02crnefkBYPFfVJ40c5UpDR6zIbI/hp9Hidn3E/+znuNLm4VjvqMBo/EmDm094u035G3as4dYTLTnuTUlyavBzk5nNVHk75XTU/VFEzil1eHE/49aHfl7n+ANP3KtOIeBOTdsRcakrY7XBNG3eQNtfkfdjsXwG9AJz/3mWq49E9oKrBF63/3JK4C1rTL18Z/PBzCNucNUMd6isu6XU+RdcbsSQXHpjRqBjo/fObo335S5klzJz7w93RVDFHf9X8Snr2o+N2To0h1tA4Dd8LN+LSz7yyS37NvO4pn5QnB37+ihe+v5j68mOBbQ9GYX+LGYbGoxrckncLWD24/V/vsd9NBgCS17//C6BQ85p/DMMsWG7de7RzsUojyvHJKttO+CWFB4f3CsKtBRvnvSlydSp1e3gLWMhNhfKeimpp8XAbqnj3g8h5x3Fhb3QvpkZuisJbcw/a9yWU1aq+Jhj2SYYZuoKcIy+GsD98dcpfVrYemSKaaPIlo1P8mLv4bmRa+MWr9eRmuTTrHRfo8juuEbJdbALzX9uStvJ/GRr66Sk8dVtG/9ulO5iaaZHBktrra2PRfV6PdUzG9Y+OhS71P1Q2KH7znaV8xSO3v/f2IMn1r3sBfRczMudsU9uxrN63/ShGrK/43ct0lb65Fn/CCLlIZr1aZTmgZPD2OehkxToKTmHCzpfT7/bKle5S9vCg+ZQqX2a2DWM4L4dFhw/PWXt/x2oquUspFYLaQl4ioiVPLtDESwZlmqrkANXygIU+5c9p4ttUzv5KoxB24Vz59OGjsIq1r18pKZxz09u5+pKZ5CIePK8VBpj5jCksykEp2wXN8J148QefLexORnnO+KNUyMaYrfPfOpkUFK6RprwjfQDIxTXNGb4oH3pzy1LGa631IqZu7Jztf7DMU06XKVAfmuXpHkB8aanpq5Yp33vw/wAEeDBJ \ No newline at end of file diff --git a/docs/cassettes/qa_citations_9709ee6d-416f-4bd3-89c6-23667b9f3cca.msgpack.zlib b/docs/cassettes/qa_citations_9709ee6d-416f-4bd3-89c6-23667b9f3cca.msgpack.zlib deleted file mode 100644 index 7cdac5fbab57a..0000000000000 --- a/docs/cassettes/qa_citations_9709ee6d-416f-4bd3-89c6-23667b9f3cca.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_9b14f817-4454-47b2-9eb0-2b8783a8c252.msgpack.zlib b/docs/cassettes/qa_citations_9b14f817-4454-47b2-9eb0-2b8783a8c252.msgpack.zlib deleted file mode 100644 index 634144fa57c02..0000000000000 --- a/docs/cassettes/qa_citations_9b14f817-4454-47b2-9eb0-2b8783a8c252.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_a02d494e-2ba4-4626-b982-3fac8e65d0af.msgpack.zlib b/docs/cassettes/qa_citations_a02d494e-2ba4-4626-b982-3fac8e65d0af.msgpack.zlib new file mode 100644 index 0000000000000..ab7111baad53e --- /dev/null +++ b/docs/cassettes/qa_citations_a02d494e-2ba4-4626-b982-3fac8e65d0af.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_aef87758-c785-4484-ba59-9a784e5e1252.msgpack.zlib b/docs/cassettes/qa_citations_aef87758-c785-4484-ba59-9a784e5e1252.msgpack.zlib new file mode 100644 index 0000000000000..0e18ac3d521bd --- /dev/null +++ b/docs/cassettes/qa_citations_aef87758-c785-4484-ba59-9a784e5e1252.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_daad793f-f08d-4b56-90e8-3f015a79a88e.msgpack.zlib b/docs/cassettes/qa_citations_daad793f-f08d-4b56-90e8-3f015a79a88e.msgpack.zlib new file mode 100644 index 0000000000000..3777c8d9d7a6c --- /dev/null +++ b/docs/cassettes/qa_citations_daad793f-f08d-4b56-90e8-3f015a79a88e.msgpack.zlib @@ -0,0 +1 @@ +eNqdVntsFMcZ5xEQSiIKKaFKALG5IIio9273du/pkMY+Y7DB2Pj8BFxnbnf2dn378s6ufWfqQiFAmqYiWyUlpa2ixI9DrjEQTAkYiiyUppQUEVQ1EJqGtmppogIiVQK4NHR27wx2cftH94/dnflev/m+33wzW7Jt0ECSpk7ul1QTGoAz8QDZW7IGbLUgMp/vVaApanx3VWW8pssypAtLRdPUUdTnA7rk1XSoAsnLaYqvjfZxIjB9+F+XoeumO6HxmQ+nDm30KBAhkITIEyXWb/RwGo6lmnjgqccmRLEhAXUJIkQoJUXzGxtUAj+5d1yzDA5GCTo3LFMFzVCA4z1KxK2ODCEhIrjEv8EzkZF/AqNyaEBFAqJjmJA1lYcTWTITWLooHTOGkFROhIhAombgpBGmiAUOGk8B4TE0GTorsxA0PJ1NeEbReCg7U0ndJFmNVCRVcjRVPEfjrw4MIMtQbjY1TW7m8L+TJwHICGIpMg0IlDETJlR0XCnTMpw4lDfkzLmWoiZxztxGj5nRXRCCpboVdcLd/XcUVKC4CjHJhHyRitodsJ15T/ky/V9OsA4PEWdIel7NkxPgJEHCyQnh8grLiARAkCc0Vc7glytPSm1QJZBbBFRAAJUnOOzbleVnHR+815NPGyYn5q8LRjcwGQ1TgrkhyMFxfv8DTw12BvKYtPthFRDtosTl+PG/AbooRpOEyySpSY+TQgzZpQz6b9GdrZbEIctKEKEJruN41fJYWWlZ7O4ycyBaLIxJyLgqOcxuUJwTBY0rdN6lG390DhgGyOSq6uxmyYC8U9jR1IxD2jTGTku0QM7Ehp1NnVkRAh6n+A+TZnWLGjLtgfHbfh/gOIhpDVVO43EC7L3JDkkvIHgoyMCEfXirq9BljN2XglAngYxT2JuzsvcDXZclzsXga0Ga2p9vDaSD5X5xn1MpEjcS1bQHKzGIojJfVQb3J5WgvQG/178/TSITSKqM+w0pA4ynV3flQ2MFOuBS2AmZ7312b854YKyOhuyeCsBVxse5BAYn2j3AUILswbHzhqWakgLtbKzq/nB54b1wjJemvaED4xyjjMrZPe4ePzzOGJpGhuQ07MN+g+rlNC0lQfvCZ83NnNCcUJYJFstYbEfp6qpwQmEjfGuwdkXRcqQIXhqWdHjX1FXVtURSLRXVFbUkHWL8QYYOB0Mk7aW8tJcmq1fwpf5yQdCWL6/l00bcDMeVutWcrMT9rVaLEKuoD1FrM1x8nRaozmRqWpKNxVxJrC4csdq41WFRL5W84fKW5kBpkcHF5eTquOrn69cWEhid1Sbxy/w0amCLdZOJrK5tlFpaK+WKgFQLk6sYmllFSSojlwfK5UgtXR0eAy8cYkgqjzBIsWHKeQZGuSFDNWmKdlckENhjQKRj/sKtvThlpoW2dGMewvd+lc2fOG9WrrpH4bndJZiT9vEaC/dRf5BYo7URfsrPEjQbZUJRNkysqKjpj+XD1ExIwQM1Bt4/Aqbh8lHKZznRUlOQ74tNSPbjDtlxJR34+HAgYVrXECTzqOz+BrI6d9aSZSUHczuL1IwkUKUON6x93GV9e0e6necsnhfb2hUq0sEyUgJanDCYN8H9zwmDAZEKsruCDDOQl4zyrg+vlSJpiqToo2kSnyBQlhQJ59N95w98ZHcHcLLfvl/B1FIQXw2yrFsN6hdjNfCZignrxL7nho1EIscmVhp1xWCVCMMeHa+F4Fg0tF9Bb9+vkHfxJoX606PapMTbFxbhQTMDKUgzwQQMJUIMQ3H+UBAkEpzAhgL+COQiR5x2zWEvTjF1fIqTCHL4dmNm7AsFCkg7PWYZQweYIF5poXPeyxYP41aiRHPWgAoJ3YCyBvh9sVIyBvBtgIy7/LOzJY1riirKYj9vIMcSiazUczerrKohVRKE3jg0cGHsPk7WLB43SwP2Yl/VRY32YBiGQQQGQpTAgrAghMhi3IZGvd2lXbfTabNAxtjbOPugyCzzRFmW8RQSClgWDuIyufev7/TmjqZ3pkxf+L0Zk9xn6kvxJu3H1JzOy/UNN6CvqujcnF+uH7lOXQGf9g7Y5dvmoye++f0r50ub5v3lROWzDy463X19c//Gq5HL3z5fuHPWpWndD5zfHq1LzS6ov3ijcDfre2jkz6lb//ji0+G6n13h0KaDnYcvHX740Jfb3uvc732t79Cz7776dyC8HJVru9LPDO1ecar23ORDS6sGB8uHLlVPC+x6+rVtB08TL219KrI/9CIz+PIPluycVdz20Ym98bk351U/MrLQfnxvz6PF0UWzp5R+Nzjlt+vUBa/OvD2bL4++onzy1uzElHBPyZk9s7pa71xZfLm1oeaFb80NfLyw/vrIGyPVm+Knhy5+hm51dJ74yc3Pz2lHv75HXjRvOzu8I92RKJ2xcl377+dd3d9Q/s8X//r8mhlV8UCg/IMfzhx6WNy1q2j38KE/1jyinvpTfA5snP61x24+Rl0VUxKz8nXPpi+P7Xjy/ePtV28//aNdw28dqJk/PfPCtR2/mVErdf3uC/5slXHqyuLQSuUDqiFrXvtoxJx5dj756ODaQ21H4r6n1g+LB/72+XPH0l9lI5vXRJYuvp6++vr7px8yX2lfv9D7eJe89Z2VC3zzlQcHFm8OfTJyreWMdOOnqPFfO2/PoLZ/COzU1mnJdxfslKZfbL+1bxD8umn4uY/7T0Z9R/rPiieH6if3nDkZ3tB/epHwRHrjta/ggt+5M3US/czx1JMPTJr0b2sqlU4= \ No newline at end of file diff --git a/docs/cassettes/qa_citations_eb11c422-09b3-4d5a-87eb-3bad2e73cf6c.msgpack.zlib b/docs/cassettes/qa_citations_eb11c422-09b3-4d5a-87eb-3bad2e73cf6c.msgpack.zlib deleted file mode 100644 index 701f3f5103fe8..0000000000000 --- a/docs/cassettes/qa_citations_eb11c422-09b3-4d5a-87eb-3bad2e73cf6c.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_citations_f1edb401-6027-4112-82ec-25736e8ebabd.msgpack.zlib b/docs/cassettes/qa_citations_f1edb401-6027-4112-82ec-25736e8ebabd.msgpack.zlib deleted file mode 100644 index a8d6e6501ae02..0000000000000 --- a/docs/cassettes/qa_citations_f1edb401-6027-4112-82ec-25736e8ebabd.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_0d3b0f36-7b56-49c0-8e40-a1aa9ebcbf24.msgpack.zlib b/docs/cassettes/qa_sources_0d3b0f36-7b56-49c0-8e40-a1aa9ebcbf24.msgpack.zlib deleted file mode 100644 index bb7df399be8d4..0000000000000 --- a/docs/cassettes/qa_sources_0d3b0f36-7b56-49c0-8e40-a1aa9ebcbf24.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_1950953a-e6f1-439d-b7b9-c3bd456e388d.msgpack.zlib b/docs/cassettes/qa_sources_1950953a-e6f1-439d-b7b9-c3bd456e388d.msgpack.zlib deleted file mode 100644 index 2ee32d2b9ab2d..0000000000000 --- a/docs/cassettes/qa_sources_1950953a-e6f1-439d-b7b9-c3bd456e388d.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_24a69b8c-024e-4e34-b827-9c9de46512a3.msgpack.zlib b/docs/cassettes/qa_sources_24a69b8c-024e-4e34-b827-9c9de46512a3.msgpack.zlib index 63e0b84cb9a9c..a9ddca1badfca 100644 --- a/docs/cassettes/qa_sources_24a69b8c-024e-4e34-b827-9c9de46512a3.msgpack.zlib +++ b/docs/cassettes/qa_sources_24a69b8c-024e-4e34-b827-9c9de46512a3.msgpack.zlib @@ -1 +1 @@ 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 \ No newline at end of file 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_53911d2e-f9b9-44b8-9baf-1c308201a7d0.msgpack.zlib b/docs/cassettes/qa_sources_53911d2e-f9b9-44b8-9baf-1c308201a7d0.msgpack.zlib new file mode 100644 index 0000000000000..a709d9557327c --- /dev/null +++ b/docs/cassettes/qa_sources_53911d2e-f9b9-44b8-9baf-1c308201a7d0.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_8f916b14-1b0a-4975-a62f-52f1353bde15.msgpack.zlib b/docs/cassettes/qa_sources_8f916b14-1b0a-4975-a62f-52f1353bde15.msgpack.zlib deleted file mode 100644 index 3c1d7aa01f8c9..0000000000000 --- a/docs/cassettes/qa_sources_8f916b14-1b0a-4975-a62f-52f1353bde15.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_95b6b784-8584-4b02-8307-8f2d93d4a166.msgpack.zlib b/docs/cassettes/qa_sources_95b6b784-8584-4b02-8307-8f2d93d4a166.msgpack.zlib new file mode 100644 index 0000000000000..0ed5821d57ab5 --- /dev/null +++ b/docs/cassettes/qa_sources_95b6b784-8584-4b02-8307-8f2d93d4a166.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_a21bad79-3773-48b4-9d77-406e29b0cbf2.msgpack.zlib b/docs/cassettes/qa_sources_a21bad79-3773-48b4-9d77-406e29b0cbf2.msgpack.zlib new file mode 100644 index 0000000000000..63b754d5a86df --- /dev/null +++ b/docs/cassettes/qa_sources_a21bad79-3773-48b4-9d77-406e29b0cbf2.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_cd7dde97-25c6-49ce-9a0a-4cd36e36da2d.msgpack.zlib b/docs/cassettes/qa_sources_cd7dde97-25c6-49ce-9a0a-4cd36e36da2d.msgpack.zlib new file mode 100644 index 0000000000000..b1da4edd576f6 --- /dev/null +++ b/docs/cassettes/qa_sources_cd7dde97-25c6-49ce-9a0a-4cd36e36da2d.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_dacfd0b1-fbd8-4cd2-b429-34c47e0bafb0.msgpack.zlib b/docs/cassettes/qa_sources_dacfd0b1-fbd8-4cd2-b429-34c47e0bafb0.msgpack.zlib new file mode 100644 index 0000000000000..e84f64ec59172 --- /dev/null +++ b/docs/cassettes/qa_sources_dacfd0b1-fbd8-4cd2-b429-34c47e0bafb0.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_def66576-2309-45b5-8699-f0287df8ca9e.msgpack.zlib b/docs/cassettes/qa_sources_def66576-2309-45b5-8699-f0287df8ca9e.msgpack.zlib new file mode 100644 index 0000000000000..5344b3ff78c60 --- /dev/null +++ b/docs/cassettes/qa_sources_def66576-2309-45b5-8699-f0287df8ca9e.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_sources_dfc82ead-8504-4ae8-b593-9b69f23e5a57.msgpack.zlib b/docs/cassettes/qa_sources_dfc82ead-8504-4ae8-b593-9b69f23e5a57.msgpack.zlib new file mode 100644 index 0000000000000..cf76e9506359d --- /dev/null +++ b/docs/cassettes/qa_sources_dfc82ead-8504-4ae8-b593-9b69f23e5a57.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_10b34088-2daf-4a66-86bb-d3a560d1015e.msgpack.zlib b/docs/cassettes/qa_streaming_10b34088-2daf-4a66-86bb-d3a560d1015e.msgpack.zlib new file mode 100644 index 0000000000000..2071bc5dc707d --- /dev/null +++ b/docs/cassettes/qa_streaming_10b34088-2daf-4a66-86bb-d3a560d1015e.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_16c20971-a6fd-4b57-83cd-7b2b453f97c9.msgpack.zlib b/docs/cassettes/qa_streaming_16c20971-a6fd-4b57-83cd-7b2b453f97c9.msgpack.zlib deleted file mode 100644 index 5d4ef73b723dc..0000000000000 --- a/docs/cassettes/qa_streaming_16c20971-a6fd-4b57-83cd-7b2b453f97c9.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_249e71c6-6cc5-40c0-b58f-7ec949c6a28f.msgpack.zlib b/docs/cassettes/qa_streaming_249e71c6-6cc5-40c0-b58f-7ec949c6a28f.msgpack.zlib new file mode 100644 index 0000000000000..3114f54a6742a --- /dev/null +++ b/docs/cassettes/qa_streaming_249e71c6-6cc5-40c0-b58f-7ec949c6a28f.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_3d8a2e68-7849-4c7e-ae6b-31f1f65f9b59.msgpack.zlib b/docs/cassettes/qa_streaming_3d8a2e68-7849-4c7e-ae6b-31f1f65f9b59.msgpack.zlib new file mode 100644 index 0000000000000..e1f74cd7100be --- /dev/null +++ b/docs/cassettes/qa_streaming_3d8a2e68-7849-4c7e-ae6b-31f1f65f9b59.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_3ef2af40-e6ce-42a3-ad6a-ee405ad7f8ad.msgpack.zlib b/docs/cassettes/qa_streaming_3ef2af40-e6ce-42a3-ad6a-ee405ad7f8ad.msgpack.zlib deleted file mode 100644 index be5177a930379..0000000000000 --- a/docs/cassettes/qa_streaming_3ef2af40-e6ce-42a3-ad6a-ee405ad7f8ad.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_738eb33e-6ccd-4b26-b563-beef216fb113.msgpack.zlib b/docs/cassettes/qa_streaming_738eb33e-6ccd-4b26-b563-beef216fb113.msgpack.zlib deleted file mode 100644 index eee957703136a..0000000000000 --- a/docs/cassettes/qa_streaming_738eb33e-6ccd-4b26-b563-beef216fb113.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib b/docs/cassettes/qa_streaming_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib deleted file mode 100644 index 81c7ed4fa3ac0..0000000000000 --- a/docs/cassettes/qa_streaming_820244ae-74b4-4593-b392-822979dd91b8.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_8807d58d-7581-4360-8bd5-619e99ff3ce9.msgpack.zlib b/docs/cassettes/qa_streaming_8807d58d-7581-4360-8bd5-619e99ff3ce9.msgpack.zlib new file mode 100644 index 0000000000000..e1a7a5c4b4698 --- /dev/null +++ b/docs/cassettes/qa_streaming_8807d58d-7581-4360-8bd5-619e99ff3ce9.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_987ef6be-8c4e-4257-828a-a3b4fb4ccc99.msgpack.zlib b/docs/cassettes/qa_streaming_987ef6be-8c4e-4257-828a-a3b4fb4ccc99.msgpack.zlib deleted file mode 100644 index ba32ff3407bc7..0000000000000 --- a/docs/cassettes/qa_streaming_987ef6be-8c4e-4257-828a-a3b4fb4ccc99.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -eNrtfHk8VG3/f/tCqxJtHFRKZsyYGWvITvadkMbMMXOYmTPmzGCEFiotlBZKoRAilDZZ6m5FUgmJirRQabNE9t85M1ru575/z/f7/J77+3r97q/HH8M513V9rs9+XfO5rrdtmUEgD4FgzvgzEIcP8qg0PvqAHNyWyQMDBSDCj8pgg3wmTE+3t3NyThPwoAYVJp/PRXTU1KhcCA9zQQ4VwtNgtloQUY3GpPLV0L+5LFBEJt0XpgsbJ2zfpMgGEYTKABFFHcBzkyINRufi8NEHRXMoCOQAVAAbCjAhhA/zhACVQwf4TBBgUfkoC4AAAXmAiBuUKBDMhGhMgA0xmHyAB/qBPJBDAwERyRA+AHFEI38lpwr4wTy2ACOGToTwUepUFswB/5EkjcoBfEFAwKGjKuHDMB0IhlDRBfw/UMQDJjBga+eMMooEo7xh7d+JqQL+AkTE2Y9JIZQtP4ADgnSQLpINRgfwgiEERLvxBTwO1oOKABCCV1QFFHkwC8RUgwgRPshWDFcFfqcxN4wRCAH4VCQAoIOYumEEwqY2+HU0prQ/jHX+wxhUYUEwKwhEAF8eSA2AOAxAwMXsIbJiiHgW1DVgAGFTWSxUWEwABMJaeagyQe7vmaYiCISpmP/nfFN5IIDAbMxebDameaoQAWA/gA5jM0P8PxHBG33DhukgC3vF4PJxJDwFh2rNF8b6ctC3RPQ3wkfZZ6MPfJ4ARJ9RzXFRd0b7YaQIeM3wTCZIxSzbNG5OOhNG+HF5v3fgfCqNBqLkUXeC6Sg3cbmMUIiriqrLD7NiNioKBxSFR1x2AAhycVQW6rsZ4lFxZ6lcLguiUbF2NX8E5pwZFR3HF3LBPzZnY8Lh0JDg8OOuGCJCDs0O5cTQUs1eiPocByDiKep4wtkQHKpMiMNCwwfHoqJMZXBF7cW/NnCptACUEm40lOMyxIPzfu0DI3GnbKg0O6ffkaTyaMy4U1QeW4N8/tf3PAGHD7HBuExj+z9ON9r4czoSnkjAk8/9jjAmUVyu6JeO6BOCL/+OCMjnCXE0GKUVd5KQQYPhAAiMa+j08aH5+fiy9SCGFgVcj6yz5RkK3LWceTYEextnV3WSNWxsRgT9nZ3NLQLhdURre6oDjqiprk0haVDImjginoAn4ok4FkPDAXYNpHgIWWw2pOGhxfB1gd00SBRzxNE/iLzOA29PZyEEU5a1GZNiGsywsyIj1jwORUin8rWcCfba60gOtoGcgCAnCt4nIMScZUaz5hjqAih3giCIrhesTtAKcqJaahmahwRAzEDYzp5PVreHqVYhPlaWgaEmeAbTmWnub+Tk8Qt7WtpEHGGUQw0CWYuA/eR9dxQWyGHwmXFpGmRKFg9EuGgCBSMzUJXxBci2dNQpwXvlmaOJNNXO6qc/S6eboA4aV2qDZR91ImBH4wPqBHUyQNTSIWvrEAmAuY3zGePRaZwxf2wAsGypBgZhb8Sxo4ulOB4C8vUEfD+c1jlnHprd0PSKM/0eEJk0poATANKzjf80FEqxUEBNi8mDhjAODEGTDIgbZTPujDvOUbym4CxNzovjDgfzGFQOFCqKi7hSUUwEh4YE02kCOp0ZFMwmaIeSSZAvKKD5XRgdwuXB2DQoQzg2EpdG1NDIG2357pDZqPAEHJGAIxCLQnBoEgBZEBtCFSz6HF3YkLh0Cqr9wj924MMBIAeJyySLzEO4+msPHshGPRib+ycZsra2dsmfd/pOioR20dIkF/2+F6rrX8gQ1dlI4R87jJJII7KRMyHfu+MgelzDMvTBR4ukTiNr0yja6tokEp2gTgLVQQpFW5NKoIBaGmStK6hxIRpKBrMmF+ah1gZp6DLOF8Y1qLKpIVgK0iMRUf9ERdVFMz2NJaCDTgJfExgTAtEFuDyQBVPp+cZmOGMqjQninEQeGZdp4mFraGNpfMkd96tr4ey4orU/LpMDIxzIzy/DCeShlonLprFgAR3NpTwwA6XlaOgRd0GLrkHSoBPoJF9NP20ChYYzsnPKpLJQJoNoceeZJD1FHTKZpKgLsKl6qDQEgmhHsTUDE4rDaJwxDg1Xqg66zkB0RR1FbImmoQsTztCKFxBgYUVHELqhloU73cEpWJ2iYclysDa0cVdUVYR9/VH3HR2B/7lhwYscHO1AQwOCD6I0v8cuhaD6fRH6/RqE+pg6BR0hXqx9/FC2QB4X5Q4lzxGwWCgtJgzRsJ0PuvGB0L1FiKIOSgwlxacq6mwaXex+WTdVfy6aiugDupEQIFSWmFq4qiILZqAR4It8J4/OCCFMH5RhdFUZ7eUdLiHx99fMTzVgWwfFMSo7tmUas7JjW8UxKzy6cUR3jKwxK7/4iycyZuVHd0P0MSs8+u157AY++p17zAr/u+rEWNWCwZgS/L+WVRHhw1zFX6T1NLGzNfWWkPgndcpl//c6Jcj2BenYV1pxhbJhJ8YVV4CVqTw9SdrqJFWAoq6pChAJGuifRDJFm4K+oahroQ8UIlEVIGloox9kDfS1hoa6hgb6QPD+XaEK+3qN+zEPjkqn4ggEdaxi9b2+5IMVCKmi0pgvFQE1yIr/H5eoLvwvrE6d8qOyEPBfqkoxLMxDzPBW7CAz4Tr/EAciJ1hrnYeLnT+FZGZiyRQI2MF4RMN4vWsw6PKz7EP8UZUKtHUAjd2DeCQOS0uD78sLoQtN1wd4EA1hbZDsbu+jwbGysVhPc6IwnbQNuetB40DnQDYdMgklCrU0rVkkG0jL3CbAKsAsAG/uxjOz9zdzt+ExflalbP2sKU4kU9DKNBR0dxQQIKfAdRaQWQgp1DHA0cKVY+aiwSUbawS7mjB+YY9I0PxvVKWIpH+xKiX7r1el/uCC/3oRqvgfilBUFgsOxsE8iAFx4k6q/Cs1qjOjZSVRTMdd+vOI/ssKWakk4j+pY/1lZZx/pyBG+esKYlgXbW3Cv1EQSyX8aT2MTsFqYJoEDW0alUbQItJBioYGmsFJvjQNijrJ73+yjOXnp+2nqeWnpYGVsc5+p/bDc9OxZP3fr27dllWT3zNtnOhnovNRy3kF+gm3e4dWJffD71Sm7vdqWkoq358F+OaPU7aftFCqfOBNcfe793lNhb/Nn//s2KaIttfNIx1tDwxsNnjvaUnZPNTX5tJz02CkrzSoYscH7Dl/5FtX24OUzSMRI813A5J81BI6w0dwI0MeV9Xq36EdPIY/Hx7x7M43GGHt3Ziu37is+qxMvyx3werarjpyitvLtlnIegbZQugzM8XsOPW0hV2ok93n6N6TjSt1JikovJ8k7VP2VFfra9Gy8cfc7qTvOia7NyriS2vd7OH5nsYT5I9VRf3mLHvwcSvpkfS59A2Cmm+h1U2fJTzfab7fJcO5p7DH5smKyqna+1d/FS4KHG/WOfdd0D7Q5PO5xzcrhp6EIH1eOetlrMabbNd0L4E2Rd7/+Dyq+Dh3zROXpqqghXSLuz2eRoUbTr6bhwMLa9uj3sc6uN4kNeldJw4mz0nNK7KEPOctfxfzcs8nKZqtSdl2k9BLJsX55MjzL1q3OhbqPkvhBNse0yhUElxZeTareOfx56m904ghlOkVgvYHNoTazk6HNW8p9VX+wqrZeTeSJZfuLDPcF+8/zsoi9ebhxI8vvpEues8o23Mktndda9iagrJFayY7piocHTgzzWyKsraeFG+Z7LnFutkWXx9JadK8OzrYObr7S0utBFcNq/kR08YlBrlMO7n+oUNindQatUdrvQcltGYXHJ61Q6bu2tc+L/0o2ee9pnZq3Rn981ZHLkoPD0wzLCjs0JawjwnZrrxkz45WO+3V8yZPbj2wJCr3AUOzR2LZgd65+ZH0XVkLYois0g9GVfdquo6ac9f2xGgvU3p7W/hM7tPdhRfiQ+/baMYbZ8n/dvaD0nSf4svEq6TlhsmeJP/ztQTXJhpVsT5X2f/Z3qkp3h2+keNa19jCDx8+uVS18jIUnva4LGbw6PQEuRZDiztVcpVhd84cplbkUvIMnsbbNRmTT9rB0h3ykXH7woXxLfO2GZ95s6qcseqF7vyZLxdWTk1wuUc/sJecax/98cQdWOXcMYXxvaaXE/bZz+wNG3H26kuXEjReU1xxed+U0In50S6n1UdqH4eZ7mxVH/qYeXXBa12Lk8zw9mqlvD0axucSkqMzBWWxPkaHx2dW8Y7PbUydQlT97WVg1a6P7Z4pwfdUHuIqe5zZrvs4EjTvcXaViKp3+cnE9dSJa9+1W3s3JKU+ZnfJeV+cJ387tLiqYVVtviTp7Cz+6vexBuuMBC53zd9J4Yoe+Ye2tekWDPxWZg9/jH3ewJjenrZhDi5nqf61yMWRZqtx61aou6ZV+dpdkR0O94q6qZRydvsE5oIh6IxWY+vLDRcMLBZHSc4MOvjCyfsCg1lABlr0qMc/VhImPrWw9pXuunPkbMiZk4ry21/c0l54b2/MoqXZz5PmD+BjM5pcGW/cDKRUK5lBuZnp3a+Taj4PzWGfiZnkeoOtWi+oKKuifTSqDpvh69Z41f/ydamJnsFWg3k5AZQU1StmWUK508s3TI3E+d6MSouXL6sI2lcXPFJV/mp4asqHj5cC8NcLzHa+8aNIfM45Zifp+n7tFPxD9tD7mRo7Ts+8Pqzi6OjdzMySPS+9qiDeJGe/W2CMnkSUa/9RneY2uzW2e641By+G7qU0+/YZntOTnD9w4MbOA4enHilZmZ6dljtY7bdd8nNC/7IjAScNoCunb57YYrr3YnH3zrP3QufAKUdl48LKhaa357pvvFv7+eCu8xssHq+sv7slO6lpcZdK2sIPUnmxG5k0zYo3z40/Kjfue+jtR5PztDrc3DlMSF0n940h/3nC9iMWS/oET12GrN6aE/TfJTXaSLnN8+9ayirtNtoHsl2Mb92doXp1076cW5uAiBmFu38769efdK2OL6Vsd2W7kcW20AC3g4sypdY3nMm8uqFduj5VZ8djryfkJT6et8xz6qmdPQq3WafdZj6wmf1RdZ6TQQKnz+QW3viN6aJ3bIXxibrUgwofHfxCEO796F0vwSl6cfxF8U8bGS6eWV+m7ZU519k+52vQYnmg5CvFpab2U4bXMvkLqz5Ib1h4WTlxp3uwQ0d5L3nwvtWiyx7Tl52d4Ls5e7tBSeOgBGsza5eBQRrnwJl5O5p7HWONF1YhC7N4LzTG62kuWVyT2JITZr14p/uuzMA8CZcp++3l8w3qqpjXhmKtXz2c02aomJIr47+FU9FpceOVfWvpwanLHTNSgeQvnWke5Xprmc9jby1rHB+o1DShu3SmwdALp2rVZRfOPD369n3Hnb7G9+M4ClFHQnsUP/ecuzRJ94tZ6ku27C4fPbPmPlKnRbJS/6XQeQt285c+ZfRn3TFNvr/2euHeV5f2pF4JO0N751uzrai1oveoQ+v0qO3SLy9GLqINv7/MY3LmVad5Jj2Q9MO1HDLVnm53jKaJ71zq1JoQeqrnU+1AmNrLfYNxKjEhlqdka+e8Uk4vHUj34zAd0hIeL/WvrD1N+vpE9vyW5sPPJ8feOr3bivJk7+1pM0uGs8NdqxbelOuXfUpqXc3rLrbJ81E4lKxU8cipsux8efLuxjWOL0vralMymFeiiieMLyUr12cCFkqNz0IHn+ZPOdz1fFb8uy7r3fkb1KObJq/RbpoDB9aoRMBRC4e6FaJerVh0w32qRSZicq1Z/lzi7QksYy2nzTXB0XpHug0VwClEuU0Tqzw7lG6+CkyMDpLzui+3NxxY9jxe1rFAI+voqhU34i3fVsUdCqu9Pfs3lfnkMDOZphhBQMPZkHfK71fYxtcgJUlUq7LWHM2c7OKCldunfkR89bVfIdcVxx/oNqrQeEEjay9oHnpcc+LRnWi5pyu2ehbo+1avtb2svr3vxLLqT+vyTG+kyslJzkD672UFP6OU+Ow8jTe3eRWbs2BianD7u1R9D1p2bkDmy6CnXtSRRwvrTGOCh1JLNO8m2EV71F8cUbll1XE55ebzJV3Ty3QzLjRCwDKjw83yR24BiZ90F6VV6qQcZHqk+oI6zl2Gmo/bXlCGk/d9ri+q0I65bEevPUjqeXVw8U0VzeQvk9JuVE5jD3Us19FZUkBenpd17jgkjNx6Kngr83CTC6ly5rxURYLl/C+nX0610thqnzGvoKH0ITNaamJ8/ISGDfr1sUZRi75s6EkuqtnYWZdgXi37sed1t3X8nRAqzrhV6VpsTmtIi2rF+XHvavp66tIevnAlLPuStM95sU6DLLvdLzKlydVZ0vZI/TH78wqrn+1O7K29px1QNQF/wanjXBDvFpn60IHd0N8c0bqGH8BvajZWXfo+k2je1zTxksHFW3KlO6uXnyyaUl1p7d+aINA0/CL1ol+dHdrUYxzRbvw1bUZ8v+xOU4XNwqOF14SDdTQ9n81tSjMsL99pD2D3VX41us1N+iQXf7Xk5uuNqnPzE+TqpAvea80qxG0KG1i48MvR2RoHfWvtMmdVzi/N1o9+MJ0pk/6yirBGCb8LV37kqm5q9eqYb5lVUoX15MUpSbt5Qb7mA/lyur20ra3a2fkWx2PVnq0f0E253+K6TcujjR/gFX/H2cxq/KKPnLkjQTWKl2gyMl5InJTNek5OxALN2/lykzYLkz0v5dxQlzT3n+W+q9Xy7Sd716eSpVllpBT5K1tb4lRpoXk+pQ/2bh/YWvnRu5od2G8Slvqyq6yt1j9w653wY8eYbmpqUXye2zl2U+FGqPdQYuVr9yqIe/CFzuGmlabHyDBTOO71XL/qSL7X6xo9A4OWkg0ZtVcfx58r2r14ceODCLvcuqtn7hBqJWrVpA8W9V/62hZ8PNtCkrCiJdJe//PTZ/GbhzZc0M30pdpbRd8+Vv8kOCGyQ3ua+fiCoUBTF6TvtIrCYsbay8TBDu9lw+/nhvfI+HeH3dVVdh4f1njtWn/B2vAH0UOv8juI19z1J0u6bVeb3fJGKPPNmbZvdbddd4Z734lPNEmn/EMS35aFf7jktcxhafn0ELWSiI3lT+8VeTvUbap3GPyU0peUK/WtEzf0PvIBpER+23JKt0BPa7EtPDehpb9w1q3Vj3YaLL8ksf/A42+drQ0MGYXx5ckSd0rCMvQPvnRea9lSyK+M+2jXG+aT9jkCeJ+R8m3wwgFKVE+n2fHW121dhoXT7M+wdk6qaK/5athHkF7/4NC3uxtlU5Pa1QvqjY33KnqYO89qnZshKVs7qGVKXor7tM2tJvFJ7KW2rkOZ6rIDndY33gY92JQk0HCubiHfbSDFuqcwij7UVh5466fYPyRsWVCw/vYsPe0iz3O2x9fx5aKW+iUfk7XzsAi9pbYt9t2HWdLB7lqRRv1bJp0lF7V4aBAfxXhbcR8Mley7/b5956SdWpLPKU8UeiS7VZ5JynW8vOvx1Fcmqad+V9iAAcNXuJ96LksrApD+tia6Y28e583LuU81bx0sW7etuffb1wGvcxZmPuHyy8HLucOdTkvv6k1XoQeVbF6plLVdel5Szv7L+wfe7Cv7kq5rdF+jZ0FavnxmG5dQfBoXOeWo09bo2O7ZDMuzg1tctsvVvT38mjX/9YTUhKX21hqraTrry7erbUZD78lV5vR0c5cW5qGNjOdDITKHzC+duHN0SVeDTF6/z+ZrdSnmI8amqyae567q6C1ekfhs4z0gJkjGqGR9TCFcge/vXN7BNjdi0QKu5/tMN+snZfpxVcBurRzn3OdKiSorGhZDm0urv3zpHFRLqXjbAurei0eahj6pff6to4N3XnPGrLnww6/zku5U1audXY0QppUGpd8hhfPubjs48Gqp6tHM+4xj1lpreQFVKRFtH+7gdb5J+jka1xoInz7FRx6UkTA5X140UFn2kh/q8CqqMda7697EwOkTGiK6lva/6mC9kNoR1PvpSSprUfmEyoz7D3OrT1zIjZmidnxXfQWtqe6UT1qKzwyZ/nkddl8enbR9csD/q0ZW4d3O2WfSpRz0zFNGqrsidILIzzaukr8WMfEWU2YOIyF+5GbOm2ryO05EcrH2gwca/Z2Ps8iZdwqrrkRMzdngRuv4eszJoYl05V7qK604q8SupMPzmf3ps0pVd997cd/Y/qTL69n4zOsUV3KzT3W93b52KH9gkPNVTkKByyxYvqTD7W0P4OlvlsY/tShFfuRTydDMPflJMl9Puk9/+ygAfl9ouaTj3LOy34z7tp96tXFhjUpvwAXPC7OqZ188SPJ8dsZBwv3m25gNw2Ewidq1bvXBA4LDC1+tSpOP2ptkXiN5NOfoefOYJ0XeL+u+Ulr5lXKnXzav3xdma9qCeN86vzcgb673+tNxzEvXpZZeGEj2io1MroEjdtaaqEd/Sr7zNn9DxRrZLJ1Nfrd8JhycD3XEQiHXIc13fcKZGZsa7Hu/esjW7LRUWXKBZ7Au/0FVps/QjsBTTRXU8bNHHAit1xXDzdI6c5tp8qp6WpO32j5vf2x6oSp+hq2MsO/NK/O6a5VzlKD9lfkp3bpBEqUTTlRID8r22OnPij9+stxrSVbFnmMGz7ed2h0h3Pr40w6Oii8809qDvSs8ZIX0tV2Fk6RWEzt2cczXSBkUXxu2Ls6XMzsW7b23fDjqrHNo9rmCVJdx+zIKTufFXSQK721QWpS3xjf5hVzMteH+0mvCZcTEwUeH5t/G3XZ4eFmtWxW34eb9AqJfWalLlUPEcOv2ptiIPmJikrrkRmGL/MtDn1hnG5rktuTVj5+5rMnc+e4JQ4WNjLCmNpuyWaDclubi58ER+eFF02x1tNYLUxO36pcM1d1c8Yrx7Fmm5+2mlvsuj3mDK5J1lKVnmlZMLHvSc4juWemTJB9gP3jjRrMwfFdr44H88rjsI1rGCcDVubGtarPvsPbAx1PciyNxhXp6+gm2t6Hzw1vUo3UWdEssNN7gRxnslHrqdRW5NK91LuuyTuxg0NwhqHxodkhC3eEsSZcKA5/hbXaC6Cxq8hSy3m2axJM9n5QeCD5/HnKYszHhyd2NJ4m7TkQNVF4iFLEfP9+Ck9vSU8ggr4yXXhTxdZHkvLnFLw7N3m0/XtHxVdx53ZTBjmOMu8zN2WfDDnKYQXcnut5vPByzJ3Jx6tFLOykq86HU+MEbd6IqN003fl0uu4SeeqoxXi6rpyjD3+oxUyL18E6m0exbj9plUm4/qzdct36HW3OJ/XC/9/wwqa1PfPQ8Ir7OvWunfnCjd0CdCn52FXz1IVDEyXG4Fy694tgn83fnnqZefKJBmdZNGu5csJnpsXBtnfOCjtyT2Ts8n975LWdjf7vaFLVawbfO5mnFloQVyrb1JxZRLc4VnE+rOyodvP9Zv0lFDuzgc2H7rh0su6wi6/bjH5XeTKxWLnpRtftD38NdCbJJj0n2djYXoyPadhbKmsSEmCg9LylonSTdqX+K8+708ImL2pHe8eNc52SHjFQW4+e6ZmXo1mc1RHuXNshs6Krft2bzGmqihYJ+45kuhZnxGiU95jqdlfisjKmr8wgh9DvbhKHI8DTbqQTLZgfPEpcsNVbutxy32zazEP2CnbvyBrpiE/39XZ1YpVJzsk+kGQx5Qy8Pjbv8LvbtlDUqoWq9bhcmqMm5dZzO19q9IaDhEii9JzMm6q3Lxgmynxh2pXX3c6/2vZdW/Fh4MkopKZ+xoOpErrKM2n3dpymmDrtbOrRsTUbeT744SX3bZ3ByQ8b03oYvc+Z1K8rLCouKBpacKzet+hiusDWk2K3rUWgT1S1f7Zby5OxvTlnW9K3nM1sTdk5dkvkhP7kqmcH38p+91bf2mULPoHXn9KicgZrNJY9CHXOvhkWFlPYwt+TcYAD3iIfihzM2EHGD4Hl72pNJZjoRRqrmg9J1KrVN+oqPA9uC17COzd9ruPILraKN6ap+29jRxniR3ILLYY6dyAS9pftMquDPYU27zJde/Wx++QYpb8Wp8CN3O8ABd/9Hj1LePJr65GCHpSD0fIxP8naNnkcn43oV63oHDU1X4pavCe/6cvjZDjeCfkNS4VfkcHCzEAenJtl9IawpegcWtzf3zex7k9PdnmIf7DFZVmVm282MNcterDJa182/UpVpc3T5CxWpOV1BM6sL2bmTrHWKyd8+fRbeDS5wLJI//HLmyTtzTHYr7ym9smKZzTT513vvlp9kb7mutr+ZsTfmhXlxW3NX/ukFecQZe9zMOiwlkY79pXrRsTqnrieU3Cqtk18bHWZdMlByvyG0ZcqXrym1MQkXDdLc3ao1P/9W0r1Ov/llbdMZCVxaU0l4cI3n21L52SODidcNrp8wstugTVEI718ytTx+Me1Y9bf++TlNZ/1dGlYfsNiGNAtqMuYavD3nFfIq9Joa0rqjad4sqwuL3sBNN3ta8FtVw0NCSnUnDyfuuTRJ8mP3b1bVIbIG11bMQ5SkXl02cNphfujKZeq9122PTjgeo7rv79jEO8suujL31GoLy7KV2gfmdrjc2kSuY6WHgm/nFnsqjx8KuZ+LryyRod3c/nlYyWxWsL5F6kHDdn3+osQK+ll2RO+hV8M6Tu2UJ9LBRm5bUpqM1uSnnqanTIy+oFzLsax1OOXRvLlkndFIQVuAIV23UCPG9nzl8Cen1SHLd9c8M3k/1XyhIMVr84S2qXvdMisbU2an1pbfl1IwWuCW2V9lnm7bpjvU6aDvDAaZ7wDlyhyyCmLjBs9OVJdeHVpylXvB8WOu8uYugq9egm1Z4vZja53UgpWyl54ObbrpPS6h9VGLeuv5B/NdHz/0L9t65KibmfPl5FVnsr0t1uze4J1mkjPxt4/nFDmkFF6EtOzKq3N1roXyb5p+mLX/SsLWI/erdrsGnyyzl2Mf9M88VtVweO6M5r6Y7SNTxo0bGbFOtNqXTZBd2zss8SpeVqBy6p7t2iXSU2RlF1pyOGtXdx4yh+LowwOTjjx7xta0aazqTULO2O5JUXZVvU5ozotrn4QbEd7bD+TNd5ryMK8oIkVmyVsjJ53goGemz55OnlUi9/XqecW4BSddHer5DPnPtpLXK9Z+O57eXe6mnOupQ48JbWo8u+7x4R6rB6r0geEr1ESvqc8VOtddt7ysc/upa+0TUJka+OWmef4tiU1ZUMy0NfLW7Tf9jz8euuBfTUxZjCzW7zsiVBEatuhbzQh8sZnnsGwwPOlW64aL6z4OT1KWlPhSSn5Ut9Nr/GKvs/sLu59FVTLm1EzuzdgTaed4RXXmjt4tevtSi7fX6tg8qDRPVp3+8J1wXKu9UdfTt/nQxBk+b4X1Wpsd7d/qq7g+nXmxa3W0x/11K47sXjpzROagUemV9mTzIwMPP/pOkb3p+yB/kd+S6Bq/LQknGxu06/YayxHUJHreln4tyagMJH3Ikf0awXwtmXSzFFT6fMXhdOwxybKdK5VXR3JqV8xfr/ZlnXP73Zi7Pg8XbOHKkGSV90Q64DmOprzSVw9ZWROuKte8SzlJKJdzO95DHXcdd3TEanLrcF2KWoIabcfD2ohoRv61yTfOZMl5GA4fMN/WFdqj4z10aQqpE4joH+lLv/Z+U+dEzNQTx0E4688vgHHj/krQjuTKfwLa8YAFIiQHlQP8uLeK3dj5AYLBiYExGKYDu8yC4AEXBBTBZPxg7EAOa+BCIA0UgT+wU1cIDALpP1A8fPjPoDV4wNIPEKJz02GOMh8I4MDBonZxV1UAoQrRZyr/H/p8n5wHggACYkJg87KpIRBbwBbBWbDjw18oYWzQIATEe3G8OM7YMJRJZyYsYDD5CLDSgwoDIB+gsvDYeSZpFYByDHLoCGAMOwO+QvSRy4JFsrMFLD6E6hUQ32MQSQ2jCvOFWBAfQplAeQWpNKYIR4NKhyoR4iH8H3dg0B4YV9jNCBbIFsNwftDkixkSY3BEYjBADgZ5wYT7h04IwB1F66gConsdGCtUgC9SCZ8noGE4GTwqI6Yh7NgdGD2c/A6KMjJzAlZiCCE6n4kTMynuuApAzW6CtdJB7h/aMADVdwkxJBQYRGUJsFslmJ6oAI2FuY8fhPK2Mgiiom/Qadlcvogom+oPYwecQBDMx0zxJ9ilUeboGJhrJXEVRtTa2kY8qxiiNEoQE5cFBYCAl6KTSF2Ys7p7rMd7eXGIeC9FVbThBz4JUzki8GXAVJa4I8o/6p4YDXSIAdZ7pbpoMgHy3cNxCBekoZLQUCOJFYqFki4A4hl4jDYqiBh8hsHbYAGfBXFQmUTX3IBgtFFsDw4cBLJUMeFXkkaVxxSwqRhIiyvgIyJ/NINQikQ8YBcE8oIgMBjzTSomNo4Lo76LIcwEfJgDs2EB6hXY5Q1AfC8HHW2M6Y6DvbLjgDqAPYvKwZxSyYtjKAZ8YWfvKAUR6EuACKgslvAnQAxlRDiK+AIMOaO0MVQbgsWrKBqDMR2i+hOOpgc6wGVhSQI7X/9uQpNfTYhObcykQhxMiu8OvRKNI13ADYR+iTJU30wqghqbhoHHvqP4ePRf7MsHaUwOhOYKkVJBDpOKBjEWhNjxPeb/ovs2GFYQ85xf4G2I2PHF/SDkhwUxRcCAl0CdQKTxmRAnQCQ8Znfst+i9qIeAj4ZzKEYAcx7sNBq7gCKaQsAXXQjAev2IaVQQnljFyH8FrBNlFNGRP8Y7Kj7E+HXgjyhHxUKtQfXFAl7ULCLFRAVgQaLoF3UX+REfu5kFjrIlUvqo5CJ5tLGEg0oqylTiDCByOkcQgQU89FEHixfAEiPDwawjuk0hUrg45EHx3BBHfLkJm4RBxdCOKEWUkjoesIZR2s4gjw2wQTYWDWLm2agzoR1IeMDc3hm7WgZ8d2dDzM/Ec6BsgowfrI9GuNiEXhwyHjCD0Gc0ulC9i9i2/8XopuLUg44Vy4Adz0McARolqI/zQFEoYayj3LCEqDXRNQSLfFEcY/YDOQiaI0VLC+bbo/4kcjxYpEVfDKoK+40O/J7ixUKjk41mBTTAUf8BWX44Ghb2NOj7VKhtcVxIlIhRUkxqEASLFiLR4soSinXjCPqxQBof82AuVbxQQIiIQ5HF+Vj2Z2ALC8oTD/RDk8woO1zUmmgaE6vJFE0dQhECExuFxRWG90T46AoKY/kUdUgeX0QR9ENTGoSZBjCE2BjV0Y0C+MMPxUBdEOOGI2D7or6LmUbkvj/TFeYzLJZAxOCo9ZhourAQMBioBlGLA8EwDwvElZZs1BkAsbfpAE5MkPO7tRbNIVh2FiU0ES88CBFvIshYTmCIPBRbCkSphjua4HTEywI2BYazFVmLh2UdUYbCQG/ilyKg8fcLKP+43P7IFFhm42FZBlMsH926+AqwNRddymAaJMqfP5c9bJSOOJ9il+xUAUsT7LoeugGjo9sQ1FKqYqfjMQRYBIgnwBYWlD4YjEOYMLpDCKFiOhcZlSGA6KBIGiylwGLKmASiBWQ033LEwWb5cyXS+Q+u+D+44v/gisc0rjhdXYui8dcCi4n/m4HF6hTS3wNYTCIR/417lOlEwp8jiwnaFKq2Fo2o4Uen0qigHw2kq1NBTXU62c8P9NP0/Tsgi4lEX6q6+v8Dsnj+h3+CqvCwNfU3NYODEQ9fLp8Owi5GwVw67O7yH2Tx30QzP9Xg/NdBrf52sv+PQK3+flqgUceu7L7g2HV+mDN2hfcVjlnRRTXbMSs99l1PgG7MxqwCxBOMVel/VMvHqgZUx6zp+WN4p/vjdG7MWv/XU8n/xP5Ys/5f9r9U/n6ii87Px3DYY/cGxqr4+DEl+L/xX1T+D6ukwls= \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_ded41680-b749-4e2a-9daa-b1165d74783b.msgpack.zlib b/docs/cassettes/qa_streaming_ded41680-b749-4e2a-9daa-b1165d74783b.msgpack.zlib deleted file mode 100644 index b80c1d22f879e..0000000000000 --- a/docs/cassettes/qa_streaming_ded41680-b749-4e2a-9daa-b1165d74783b.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -eNrtfGdUU1u3KApWVFQsWMAY7JKQkIQkICDSRKSDdCFlQwJppAABQcRjRcDYsCEqTRBERIooImAvoGJBFKzYaQJKE97aO8Fyzvnud7937xhvvMHxB7L3mmuu2ddca85NTEYIJBSx+bxh2WyeGBLSGGLwINodkyGEgiWQSPxHOhcSs/jMVAd7Z5cUiZD9ZB5LLBaIDHR1aQI2li+AeDQ2lsHn6obgdSEuHWIy2bwAUSqdz5Q+4Ueg2TyBRIw2QHl5Eah6BB0UgUzUQZFIRH0dFJVMJFPAGxIZD37ifHx0UGgunwlxADhaDIWJMT/wYWhMGgaH00MDEIjH4MPvfP35Qi4Nxo2m00SQPhEdmcGCaEzAT4PSxFQWXySWnfqdxlwagwEJAF4FCllOQDhboINiQv4cmhjKYvB5PAiRgCwrCIIEGBqHHQKly2fJTtMEAg6bQYPHdQNFfF42gBdDPDFGLBVAfx3OkoggIYYWACBkZ+0BEabWug5SIEweCo8l6WFxp8MwIjGNzeNAIhGGQwP0pAuQ8fO/DghojCCABKNQlCxdPvnUrzB8kSzNlsawd/4NJU3IYMnSaEKuPjH/1/dCCU/M5kKyDDOHvy6nGPy5HAGLx2GJeb8hFkl5DFmaP40jgop+mwyJhVIMgw9wyI7h0hl8fhAbkj354uvL8Pelc40CVlqFWWJtuCGW0lWBYY54XihllYerfSCJYGluzZJIuKFYkb6Z55pQyBWDJ+tRSQR9EhGPwWNxWDwWjwm2c4TM3EOEBB6Hoi+mC8OYUgvPIA+8KZ8KEd0dfPV5NrYrPRnOJJYz1VTgCZkFuwRzmWzzcLyUQl7NIdiyKVa2QTZBlkFYKzehpUOgpbutMMAQBaiThLCZRnb+q0nOBAvIxiIccneS4NjOwatWsi3DCOFOQU4r1/AsXfUFRDP90DXmAb+Qh8eRMTgFhfo4IgUH/zs1aBsciBcgZslS8Hj8CSEkEgDvgjamA5GJJaKYVGCH0O3rGVwgPKDj4/Y2P01YI9Uc2KSs1JbP00Hp4VH2DDFKD6dHROEpBkSqAQ6PsrJ1yTZTLOPytyaY5yKk8UT+wAwtBk0+g8GS8IIgZpbZ3xr7edjYgSZh8oV8DnjJ4Ydi+EJ2AJsnO7ak9E/DUJiAL4IwCqJl2e4YJ3ncwFibZ8sdD4P4tKzw7z06XwHEFwbQeOxwhHRZKeI5oeFhoUyGhMlkhYRycdRwIoFNhyQM/7OKKQIhH6YFRsYVyY7jKacUA4OmmwXEhcPgcRgc/pxILGQzgKfC8hDwhWKMCGKAaCaWyp7ocGlhsJsaEfBAoUB3hig2j8GRMCFnCd2czwXGLTJECYQQh09jloRhhEAtHDaXDXSL/FRESpEslQQmF/8VQMwPgngiWQYJsQzcxV8hhBCMH+bhJxoilUq98PdAg6hgECqVUPI7lAj6lRq8HldU/FcABYrjOFF22CA0hs2UPZkHHnwpZAKDpI8n6ZH9aWQqg0IlQ/r+eCqTgifQIBKOkmtmiTGjMVgQxhkxYVmGuYedqa21WaE75ldbxNgLkJ1ElsHji3hsf/90Z0gIFCPLYnD4EiaIt0IoHeByMvWQnaUw9Qn6DCZFn0YnU/wp+pgVIJINYvthualwsM6gcYDuQhiyfBbBCG1AJBLQhiguzYiiT8ThkF1nQzqsa17AFQ2zObGjlZB/yi5uN86cLNl3uCyXEpzu8seH+c07tGrchzMY3to1nFm4qyPnLW95t/SCr7nrA3Nl9vjU1Tm3vQf6HyebrN9yPOdWd4vJ+n7jQ+z+Xt/npR/1n/f3t78rG+h8V51sMtDvM+AL1U+XuJJye/ndLbT2rI+dALxroL677Pj6/r47AWMmU6luO7LT1sd4HXiW+e5q/XUlb0jj/BO1gsRa5U+8K0ZbQ0tW6QbjC2/5mc3Qavl2hF7VT/s89aJUQ+OU+ZE6R7snbZ4HlrMfkT+EW814YqHK32lmhA4Kd9eZOS9rQrzU3zFAH2NzoSTBe9b9R2kRqIHUoPi1VM7HpQn1jh/LH+2cv9HN8eLd2G2pIcVuUUoqRbqtL1sb4vLHdIy4ONPjcvzk0mxXbbMJO4JG3VjzqvRKluW5chHOVmXctplOh03V9bHG91/4jW0KG1mtEeNwVlBLu1h75MY1V02M8851xiY5maVepVktMrP9jxpqr0qLxlOq9/slD+yfu9hkasYjK+FCdbM1Nz+vNBfkc+M/Sjr9xFSpygVpt2X+0kyvTNxtu0+tJdeqZp6Y5mUXFvOh0+8uK/RQ5ZP1THLY06Z5FQ/zfcQPEhe67uFOZ7i+i9Wdo+nCm2/xeWpkRWfVrdJAb4L54R3btTfw/JVpj0O2inJjCvaQhTGZ94tqE7RVaqevf7/mleXG5REenOM3Rz1LoaQElO7bTpJiFlLePdrSvJuoFpB4yBgnuxxdF/BB3Sl8tkiwe8+YQxN06hYbHsp6ND5ROd7uPqXqSrjzy1vrEsIGPi4N8trwrNxd6P3xftLI9AhIxUG0eVhyAePImVj9trsum3bVeZvWcS8aYKc07rD6+LrYI7dLiN3A3nx1+tbpXgHfCy+h1eaVhPbtLpibU1b+rod1VzbrcHDODIe9CUqLxsdtUk3EiTm1mKYY4ru8OZlG2lOx5Q2Xq3we1tk1qlGnPDt1SVJZpR3REzEpa/l7fN2m4BKduW7KUlerM+u6vSsLYwQvKsdh+vTzHu/apd11Zc7qbTKs64bpDkUN6r3Xa2pckyZoPiv5Ep9w7OtsE7WK+vLmjMdj1kX0Ckq231TJr7rObq0yef12NH+0ScyKPBPSNL+V7yMe5u3d2mNVpvYk7X748gbjyrUD0s1Bfs/mHk5ckuF/IviKwfNrTtPO1Gtan5mW6pU3B2Vun71T9ink0bPpPJUtjjqZjo1OK7cEB4W0T3yQqkN6WrdgsX5Bgr6Vuc3VTGiXEzrN3niG515ohCjvjcH+tds2pcz2rpj/+vWYU7QVJz5NXWVqXJEVyEg2/KPpoKq7SrYkMFxiErb+xrtgn6aT43S/ah+L8v2sqm+uPuxYbknttpH5U2/m1F26LtH9uGfdHjv/Q8zlmp9GFepekFXxkoQOHSXKxt/q5jZtfndsS9PJutO9BDLH9apfjKXwvGNCa4vgpcygPDn4ZH8KOVbjpFXnG5sx+prSPP+BuW3Lz1mMLKy7ZPckk9J5VG/0Mbtlk4IMjS9ra1QsOq5/2ye2sTNhzFip+2i+RN9dtOvxab0e1eHuJQlemoXkRfWJm69OvBqdmo6tiE06OcVmu5ae4auJs+vml5d7K+uTzgdNqM+/6RipMbJwVYtArUivdOCjWXFmSOSWzvH7zaepyGzPLcpsPTmKOGxPdGZJ/TfPRrXxrz57aZ2qaHWiHTZSq+36iDnUqnTs25llswt6HkwuiJhb3PtBHBh7IwP6+jlLkM1dUWksqB35ednGoOCg68MbA/JmBjI3XjZsf/D9gO3VxKzUjW6tfaZZd5PGpk+p0Yw6UrRn5pF7GcRVe7XW5lseHUWXfkh3P6halRL3PmdFpGGz+MNoi3Xk04RD3OJW4u29mW/XzfRjBLmRsgij/Q7QX0dOv5/mEmrQd/uAVSnNdWxdePIHN98T/EPDvHIpXcsdSpZOuhi+Kl+PWqFZpVKxMGYa7xRlGyr3yFatduXRM9aPobpram6WRa37g7mPNrJd+cuHlyXGlbY8seb2MJWtZmr7ojoelpVzS5JYDl2qtXa2wlFNjX6vI8NLNqTVZy4rriXvbZ6aOZv85Da5y1hTOev5oWK/SbPMw55ah15OTkMxL4h7ltPcZi8KfH+tbnhjU8W3eTkPZBVV6CMdPKXsZ9PKvT2cx/p5b7Qu0T6uYnfw1Gue23C3ces492ouujc/zFCu+RSuXb9p/RROwsPJ8/YYbZ1stZUbuUq6P0hQvp/wUGAsvvD91vSQE8e8YnAXmK7qCXrb1oZonfrO9fTj7xhbV2ppknTuypGjtFSjBtUVV1PTE2ftN+z+417VwNlbk7fPz57ZsWLZ+sPXzq1crdL7aYL2Pd2ckDvpTSp37K1YtxebdV3J3ZBCwX2Mqk6beyb+YMR+avac6tPu3620Nty6XHbaNxmv4equ1spL2TnTtXBa7J5UlV3ril/Y9L/XKalJ0zjll/chrTnhinA3wbmRUGT61Ah67RUXojr7nN4CgtaLlcVzdz1cd2S1t96DafkGjs6RrNgNl09/jP0ANWrebfGKxsw79PKq9JrF7ufMBKMzHlcKlXgbDKmzWWF6Z2U70M8uLfsc1PFQubC2KtatmzCdbn8t0Cb3/OItZyZNL37gdbIeW0XcYIcd720bspPnpjvRdKT9H69EmLOv8QFGhxvRK2oqj75ONTml6uJiPLf1+kaZcaTPg8/3S+k+3s93qLhZqDwfiE1ae8j5Prbx6NmVE97bhxlPzZ6znt76KaHmKV716x1twRSTcT763cTJZMMRL5YdXzgh40F+4YjD9kuK8o0Cfd9s435jCY61EyUq9hW78145Xj5d6j0WXd+cIDAaMWf6wQ0Yv9cx1dGBnZE1b4JyaKXZ3AXTzHacfXexmn15p+u6U7qjN7xMduNEdxJPnd/vbPrAclbcs2po9q0FqlHtYyVTpmzI0Xi1smZU247SpANFT+flkOb1Wl47JWnweqr8WmMXaUnwDNXO4p6Ezycz9Kyqm6tTajc7Pz7REt/5QPrpeAE1JmpL2Tq6ye7tGAct/bADCepxqeom2IoYupJ2HDr47dggzeiZy2/PR1MrvuF4fc0uMfTMSSFJ62irn99acsH6846mpZSijuMe1B11+SY2S0JHFxnMFvnFPeyI5RenWpWqJI4Rigc+koLONyV9KPLFj92+wFtZNGVYpG6Z9BlvxOcn1DchJ9K3vKknLHiz8o+Mt8Upp2Rxj5Y0qzvbXDDb9CggzmvBybxxdtf8jq41iVS6c+6xSmiDdoa//6yX6/tiI7rRM8oGQnOcbps+HGtG/LrI2u3Ns/rnUZXXsaTlL/Jdj2mVEXoidY9Kk9qVTKhxM3MDZ7o11LvcmfrNeHzWyoD7aZMNrj/2/5q8Tme8c/kNxrQTlJ7GhWcnWHXdCWCuRo2ffuQCtfNa+CNzrd5TftW0vJeT36h67r4UVORhnFUm1Rw1XfdsreM2ut+Gfrs1L0X8MaeYo9U+NG9PssTXxux8vPyLYOTZjuqI4g0ZHpWPGvW2j7zHTs595Vj5UX1KrV3t/PrZ926+NIjHk+yNeY+7J2WeLgvcb5BW7GHeNEGVWb3qUrNXWtOtrtr5XQ1bPk8pDtBxn5N3cFOpVd5Rz2m7p3Cj2U7iB63cwJybtSOio3TM487NqvCIOzOuYR7OsSVkvbuOa9va7k4G52gQhWjSO2Zfy6fGp/bDGf2rbI5Cj1bHqaRN6324O9AwmLji6YF7VC2Lhwn2+NLabeTtp0PtLs1pMHY8Xrp37JVdh+6a7bUuTppzVvKIO355/t5JacbOpxdzj8aQcxtGf+tMaVmGW96bqr0u8/yJpLFSo4qWPqu1Z75af6ioGr8u+ZVSTnxDYezyhZNCbETLb5Vuc577pPfU/ZOnLJJalpl2FLwsLzqi850Q8MCibuT6llnsRJ53zpc9Az1LY5Y2q1aUDlffuYV8d6MrL3rR22ns5Mq5V84t8FjtsGLt5ppT+sG4xAMFUd0u+afbF+lVt4RIspomJNpmZ1qvivKOty6OJuWM2bWJtNqtoXRf4NJOI+OJn1yzqz9d/ONa333tTWd5hns/ntuoFe6zbZ9d8f6InTf8Wq5YeWo2mLzelSRWD/SWVK5pbMPYYFXvrY1b8ur7MKvXJeTZw9/F7qLvXn/kSfrCIiPvmK7t43v6cIUJm9TN00oqGz68m4wlKakrNXZv6VcDmf7AwOqDTyecWVW4qaV3scGnR2Jzlaz3hlWL/PZuH7U6JERpBPXWsbHbU5+XKg/crLpIMi13EO1oi9s2IS+zOrxlMa7XfLZlk90ttn3GtBKnr5fcnx3lrUkixzyrvH5aeqK5u4ugPCo7nNe+6+C33ACs9dxC84rrC3eUfKldO+zAOPU5Lj7Ku980zSiOr4nTaq4OWXDHtuhNS2/48nOVz32E1n+MW93fZN3W3hu8PjDsdfnabuO8pRcMI790LNj09GDjA0jtcIJz8ghU/3FN/XV2woyRp5XnDdN+MDHmzrK6gkWmPfUfH8QUNsQFNXxxxZRv8fWxqrxYQFTyu+cU0POeZ/+UMVpsq5fnwbl64mzh9ZjYASucUkQk5amy2vfEe/eVX0y91OtxfyOxGZ1VkLBs5kX7p9HpVlG1466K02/a51wSRmWiR88KjV6oYRavS2aZFXol20UxLj3ZbVerrLb44KbWF+UWZdf3p3OvxXx8dh3NmFZgckWv5XPXMJ/MGa0HH09bn2U60DvCZZa6drLRwOfr/UQP95rQApPYl7kjJLcKapfavpj8JZAncEuZMEv7pvcau9xZb5qE8/JX+PoljdrVuoT/AHvi+fiLjLblw6dov3R7OinClXMgId7yzdaH0ZjwJePj/J19DuyKj8yL3JS0OKxDY5Sp1ZJp2vtd22blGZcoFXKvKx/J2Z/R0/GqnHlZT63t0orwCyWafk3f35Vbne28W3XdM9H0E8104FXyCVPvt/FmNT4vtT+a1Bp9SbDQ/aS1b6wyq0j0gJU7u3LW4XWpOgOJjztzjdxy1il/6sWNqGx/46kU7tVz7TnuS6CW4GA3wQKf9/2eTvXkPza7O5BKmITGr8GqEzQ8VDzvjFitZt+G+n7TQB/HfrvtQFvxxzEPja+LF2qWYFp9vyklx3eq7slAc5bPP7YzvL37nZ6vM8U6YcfM8vbZ0ezHR91nVz5Lv0bs68q33Zu/rLFgW/Frvw+9D1uUutpuhEzWala5kK/8Tu+JY+9sST3rqYlayY6tD24VBD0I4/XsfGnrkEfi6pUVfbKOmcEuYsbv4B25H3E11cyppHb7yJ3fkiIT/YKW1OyqvhBvtD12PhXdNXdYcjDR0tQzeuSlA4HexiWNiWVjcNkbCaVfRhzaJk0Mb924rOLR1TbvRyY1jtjqV1NrklLPmxG3zzndg08pyDm83vX28Dx0Ue2dCdtvGR8pV+5pDOfM6SsPoH/9fqkzPG5pKEGS6xC9tn+Z0+6P8/fvkyr5LnN+Pyw587n4a//IGx4X/Rg3KkU1vbMoERVjRkk6Q97lfHlrOvPdyJf7pHePNISeeSsN11mRP4u5a2RrZ3ff6fQvOQOHbE2VnbSMF2kVF87i1d/Z6HYloTXT8Su1MSx6+dIW4ccNW+ri2pYmvBQUSi9zUOLb4ZcnzB5ekFbVZ9d5IPjopoo2R1rTaFKrs/nD3ZFtr2lxuqfaF/Xcm1Nmpd90sc2jaf2s9xI3aZsyMXlN/6bncfHqwRv7u5Zq1I09du0u32eaptOiDKPKKZ80okNu9H4pzZ846fXTF1/7um+bvpt+ZKVdrudF307S3vpZ+s3n6W1zeKPVyWVOZx8fMGy7U5T4NRN1vzK3LyT/7Y68ddanFvi0W8mWtikXQnVO4pNRzTvmPB47bcX46yc+ZFV/uHJKdiu3vb/SZGFW/OS+NxrHjXQjz8tMRh2eHZsZi2G9677dbDl6S/4NBkkqbH52JGqY35WmrWrVh95+Da+yrD2wy6rzJLOaURi5xqGmTylPf1779ZGJW1TtLVMkF0LUsSNGquosED88lLTb4tGcspx9bcHNmcpLTsxetvtiGf2zXUK/jhLmwrsOsQ41Kc1s64ubRfHrvlXdwERAp1nNCy/ndId0nCRMeRB9r5Jc1qg9M2wkZFzhbu28MJnar7fqlvTqwYsm525XH/l+U/3Gq4GS+or8Y/vvmKA9A8dbFm0iT5p5FDWr2696XuBw+zNLOuMNvl7SVLt9XTli/nqnjYe/AhdoG2doHDt97Yh1X+avG+lK2uW4Sb16xOs+u/kDr1q7XPjpvOz2Fo9puaZ5F/gcrVna2+fqpJBdb6k1bcbOtTHGBIajs+qaHrfvclWLxfZMks0fuNSV5n2P91I5+zCWTP0gmb7UNlZYkWEyjPnow/ZLFd/2tQxEr9ITb18Y1fEkvZlee/Ca8hN+nD2xQCgYYXMRXdOL71Z+vsjtHEl3zBr7UYsX5pmNdpe+qvDqu/jowPC+xaqnVdspWV6pbacpS8mBtz5GatkvpEfPV9O+8ZTSk7rVSmUDlrbddo9l5dxG/bt76zZo2SWeNElavVG5UdzYmmV/NmNYjH1K0PWGS88PaF5WV4uY98083tKWbyzzLL8a+Yb5/Pa2hrI02UZaPe9EaZfPo1HxC+cZn3M6+TRSMtldMmwHK+VeCvFsd/I7W2H/lsTeNmsxS3951AnlNW2OX62CQ/Q+FLz0Iepjbgy82VQpQj8Yt/9hHh49bf+X+6nFh1IPx8keV0BrJ181DjQuXXTtqDd7gnHfqgLG+Sa7mFvdc0WpiyYVTQ0e7SCdvK1jhfXZIyb7i+e6d1gfDii9taQLbRiD+U69zci8SKS0nFiB+ZZU/KDDcsTFrCozxr7eHubNm7b6tyrVF84/V9LeKXF78Sp55zxyQdXizNbou/vtXRKItzSTzyd9IVd793X1M/bP1Fn/aFMdZmPP2Z6nBfbB5AManY/ZC/tePlw10eTdhzsLxjeYvqohlVWx8TzmZKXdnH1Skv9Tt9Fx/d+PjRxXL933Sv2Pvt3KUwp6zYhnaJRKLmbl+j7PForPUmxUW8IA89DViY96y7e8SzkyQ8dwjH8ftnKCrbHm7h1Gfxzh8U77yERFX9isDtblnvvXxiW+Ja1y0lp2uvPjiLsnZ/BNee1QWJNzT2gtRWnfBJ/uXfaPPk2Psth7rV0j7pr2k0sZbtembNuXbu/En3aUElTUOBBm8d3AtzXJL1xIeOz7Xb215DFX2n/SuMftwSXjPKfAoAAqfeMlo+X4qOkmZO55aYeR1qr6ynJ/ygD6y4ejw3Y8PZa6bU5ntPQo+1himfOOV/2H8m3QqX4au6NXTyee5+Q26Ox/v802Tl3ybm9Z5WKD80zLFW/j42tIrYTnljMPpHxI2MweIUz4GprNKpnZNMXR4v6jqMywJN3bF/K1RioPrCD2HDQOZR2f5d6leUDtfNDZluCxtCtVU11tmzTGr0IxL83WmT4ncRm1pD7JOnHejhsX1PYeCGg5NjV0TfXdvnaTe+JCG63jLykOI2iPv9/77L6h60SLA2G3zpyUo4tTJVqL+sQqzuJ7y97P9uF+sHFab3cLN3Hfheie8qT2NoMbk10suo5NOjezJ7swraOowTXteHtixxnZpzVr2hbTv67e163juyt/22tu2P1QW+9lR03Sho0vK/r+TEe6xu5LzoqC/u+f306jzqZcCTe96vXCYjVV1ci7R7VvWy//sUpC3cYZQozKpPMb2WYJy1bGJRRfsA8mPm6eG12RZvO4/VhLe8/wY+05lp/n3u/ZOPOqanLst5WUkizjrT7BSsuqXIhLLCfh+7TIqGfNTmelD7AaMzVcldS/R6cvWyX0DJ2u2sd7mehy2BgbOXGxkr66MrcwBK9Gfzdx/9w4+vcIF1GzwfDx2ZGaY8PZd87PKe6av8OmwrvnXjv94axsrfHZuVHqYfUelq5FRf6PjMNVb5t1VMbOuZfxZs2MFzOfLT37brnMjVw/3yHo9UL6senva0LOLD39hlaRKX1rV2uQvnP9ruFx2o4ptJfdx/v2lbFyD1Nwlrq2ym9u23S8KSrjubg83LW3UvuqRlb1VoPbH8rrEtZ+fPNRLYuYijM2i/hQrW8smrdw4+eQlntpvWMNqCpRup2FWL8c+4ZJMkzb3JzwoAuN2Z/YJzcvtb92ypaQLK4ee/OC4PXp8x2kmkPbZlL49aqePefTqgXjF0n2Lr8vW5cSXG23bEqlV7R2kmVPclSjZsksvdk2VZDNgKplk+P9lLQ6QiJXd1h0A/bStSWBfdv2bh7eHeCLwpK6pI1BZ6Yv3j9vPq3ns3fViL7OArvEb/M9eye6b+9cfjlt4GmOtL1+ycg1E9Y++n7jKfverI4o3qyyhnnxo6ZHbc4JYL9JWXsds4dsXfxlaejLMXV1ReqFbxi7vg7fuD7Ha9hA9zWTgW6TT5tNH14waTyjgVuX/tJ3oGhJa26rZn/s6y6ToNGpajXVvgP9Ecovc30fu5S9XL8lvevBd/AmoyPg4YvcYzMqvgxE9iU0bulvTxgYDp8hlJXM3PtONKCUlP51IbxssA4uEWHZWAFfBEYDkEo4nSZmsHSRYkSdsnkEGnmGa+ARaIGQL4CEYjYkAs+KEV8ROxwCj3gdFJrB53DkRTlfiYTNhIvbEAUiQXp6ZAyJRiZgiBQCHkOlECAMkwwRyAw8xGBSyHBdHFAplPrSuHDxVYEtlC1m+QKyaUyamObrz+aIIeGvQ0w+Q8KFeOLfh3i+Qkgk4YhhEongWVEM+4FIpIAbfD+I5c/vgYzgV7hfQdkiMY3HgAZBGSwhn0vzVRTsYG5xWBIWT4D5ESH1Il+kjhqGlPnt+DwIHoFL+xAsG6QA/RMNTcD2ZXMFSP+A/BWTjoU7AERQAEwg1ln+v6mDNYyGLfIVwAuL4DLTX7Ep1heJOL4Qj0bn/LbiPA6bDi+jUDtGXrdHK0Z+ZYiAJWNxyEAAxGcLYBHAyMCQWCiBIsEAXG4HYuEKYHC4wguXLPXwLoN1XiyFQMATqUtxOAMcgumnSCLg+bBQgYDFvnJ7YZDwRAaZQMeQKXgGhgiRGBiKHkQB5kOnUel0Mo5OZyJ9FCFyttFmP2zOETYhC+R9JNyNwQKY+UI2g8bx5bIDhEhx9hchiGBZiv+eaj2snj4eT6D8pBrWThAkRaTGYvh6QK5hNH4g3SaIZOPAprDsOGF4+gqbleEST6KluZijTw5aiadzQigrWD8bOzZnucKVYVN5T8XvwtdFJJ1rKm/xsPj7Fo90+bAsZYnukn9RAf83JfVTg8OrFYV9CkH/Pynsb/0zguN4UmkYBuKF8KUYiUAkFkI0LgY2PjYDwiB9GsdJ+v+GqH/BSrrchmVpCPZ/00+gB/cTpIbQhFLZEwt5wV8H9ady/2C5WB4K/+WwgtUnqL9tJmAIISZghQ2sSJYKO8FvZdvcCLRchmgDtH0QOvK/6ERa8q87kRgsmlgX/C7gQEgZWh6MVf0i0AqNiOTxWNGlARulB1+CogkhFI2HoolESKASo/z5QhSyOkCCofFEoRBMIwoEwSARFgWMESVmQQAKZgweELAhwDGK74+CW2HYwMeYKIW7osR8lBwDMmcQKxZl7Y+SgrWZfN5CMSqIxw9FxuWgOigRTQqeaeI/wQwuLoQgFOyHEBxVUVxaGJsr4YLJTBRsBr9ggslgsEUQ1pvnzbNkB2BReCzKPgS2MygUJpiGWr3aFiPgA1hANE0i5vP4YDMRoZAOJpRICuIkF8w2A1IFgRi8sudBBigHDo0HtyZoe/NMUYjEYcMEGGAZoSQiCVC6FMUGBsgJQSjkSVEAkwCIz5SnwM2DIKYIlg/CfSjMLSBcqlAHEyXgwEqBrQqs7wLjNYfgpfgiNixCsLQZi8bmwVwAC5EEsMSoRWZ8F0OUG8RGQWIUjYOFTV1vMYpFE6Ho8FyAGAWrmEkTAvwg4AvEiGIhBovHBrpBNA/xWGC3gt8jPSwosF0gTWdA1ig+T84tFDZoDS5A1nI4tggwDMxZwkAEwUd5S/RweIaYxeYFIcyj6HIhIO8RCImYzQFpAEAAeBbDTgS7PrKERIw4OgzFVLANAUaEchHDS4ERERfIGWgZFpcI3gTB7woxA0mgkL4XmHbAPjvg14lcsNOzATisGaANeG9SDCOoWIABDhtIVAEOFIE0CgqAfcvJQoSu4BzhhwpUCXOK+IO8RwcxOhfYVgG0i1xFItQiDxr/F/UQFqOAm0A8YAowyUBEUJiAw0cc7geVIDqCeIeg5gMvpQOpwdkUCpgMRGOwEJ6BSwHPZQtF4p8CEyFEAnIAf9w/cT5oM4i8ELaBVUJw34zoL0Ai2AgQSB0UCGQ0xGpoQL6wHyIalwghuS2IILgBb1AEKAYQHR1CrbB0Ri2ig5lMMQsjJ1IOuBgFLM4cHmWCHerPY3C+NsghIAwFhdA4EsTPgJxoKAYHjln+bEDbohA2DbyR2zSClEsL5MOtTqgQvhga9CDmrx40SByILxBqEX4xjBREA/mqcnP6xUk47CAI5Y12RsQF+4m7hyfW25uHx3qDjd4b7QY7MOy7sMhFEnoAH4R6BBDQD2IijANMMYGhF+khi0lEg2EVIxJADMAJ44cLwfHbEAVhQcgCuAEjct/lC6UovkTMYfMAT2gEfSgYlOuDxw+BODow84sICuGxJFzEeIE/ye3RCRLxJUKgGwOYdJQ1bNY82ByRTQtBKJc+JDcKNk/ecQrLK4AGeIMtE2DSw6JW88GqLpCQi+JCXJgwuTMhSac3j4BFWTm4YAhYEmowvCIZjHwN4DZQwA9XUghbHlK8eUQsypINngGjgG6EbIdfgpCF3ArAXDkPcJbA5klA1AYxVwghoR0mHVDDkYLoAvYQWAmISOF4AvFEwFyRrQXWlyK+IargI9qjg0gEkyWfOOhtcqbBYgoFAVmDeAZx/MHeDgAY7MGlQKzBCNiITwBULFoIm49sRMjmypHKZeMEUjOQu8ARVUCT+yxbhFCIRCAx7IgBsI8DmoSQP9C3ghwBMElgUXIxgbQVyB3YNBeeBcd54BUgQQQ7KB82bRAghWIEI+QPrIsNqwZlyubCWBWJAvQjLiK8cyCYGp6ESwdeBasGCaewCmCbQpwICoMYEkT8KIsw+GAnD4MixQCySyBOMGjTPyMrhx+AUpyzAE7rn7ZuAK/gBlssPBOxV2SC/MkfmA+secVUHeS1qfUvKcuPzZQJiYA66NBg5EOsGsY0uCwSpQSwmcDbPJgN0qLBSADbAZwGiFAYONMQAvcAhIATR8Qvj6hIcP5ABDGYBSAALgiT8Jgtsh06Q4rzBTIqf2cK6A3gwQ7yE4nFT2kCOAfgJ2yFqUZGYlFwfsaViAYj+y+pFNwtulCEUuSJsPpoiNnA2xbgIxTeKoFVgJCOsMz7XTJInvKreEQskITILQx2GyBX5LVia/+zBgY9BSZi0HLkFMKHS0V+99dZcFJIQyj1h/1bAOKJjpw9McTh/MQI//LDPH+AYuEDFcio4WMkWp6ZoYEUf8tnkSgMaP9rvmTy62x4Fflp70fvfQA4P4FghQFuS+fDsDzFcV1+OFEcXeGTK8QVwPskcG/4oI8l/zioJfzTf///vv/+zz3oqXpUvN5/1oQ+7b9zaPz9cPoEBZ92dJHrBYzcYgxR4DwmFEFiI4nYH0P5z7vS/5O28/+1jvIUPPG/ain/n3SCE//3OsEJcB84Tu9/0Ameisdx/7YX3J9JwNPp+gSmP8mfziCSSf4kKpWkR9Xzh/AQg0T5X2uq/5dN5VnOgEwz5CuSXXXDlAc/I1ntysWtWsPAmeLwWCszi5UWdkwHahDdxTxIxLenE1aSpW5Ua/M1kANO9PM7Db0fn5HQBasdBSInN1xYeEgwk+5rHegZDDHNAy083CngdOtsxmJ48PzDcXpYpqlAj2uq52vu6+nqyXFbZUsWCOgrXPjuHM+gYIKVRBKCCzY387AWuFsGGCKR2UjXED62sIGEjRROgwFOg4FdhmqAH3QZQ5BqwzIwwv4eIQ1RK8VigT2PIzUE2yYQJgT+p3EhZ5D1GsH3n0/2DH6sgmOvWeFBC3dYHQzhRSusTU1dGRR9prkZ3zXI01wKCQOZK1yE5jRrF7dfPlbRwxP+5mOVn6T/X1L1v9D8T4OoZCaRiWfAzf///S7/OtM98J00fJkOX3+i4YsfBtguMaY2wiCGC5VG5JmZMcOYljQLPStH90A3aHWgGQetg+bTA0GcUczA/rwqwiKRCAAgpzv40ven8HQG98jft0gQDPRIYIZ8I/YFGWoAfEBmw/swT8LhAFwsPhu59faCv4hjQmFoA5wOGqAS09AGEYq9GP0jh4NXH9zI0eABZL0SEY0jxxapgwa5I3ySFQ2iByuyRSxf+dlYAeUTOXbs//+S+SkGOI1BD1Hefz+sD1kpDF4iDlkBwNdG8LXa0PUDfujQNX/FdfOQ5R+5OxnCwU/MH7LMK6obQ5V/nSGreLgcNnSZ/1GRG7qOD9+5D90db+hGfH8aAy42gZWHrAgUxeqhyj9GBA57Q/mwQ+MxhyzvPwqrQ1UC2CGrepfBFqyhu+/DDTZDlnmklW/Ics/3H7qOL++wG7L8LxqqnJsN2WOOy1BlfPE/Wf1QjPBCCPpnZx+yO/vQTehZEEcwhO/w4Zbood27MVS5h9s0/ylYD81mFenQVbzi87chXbb7x/D/0fvQSvCFQ7hco/hQd+gmuYrvhIesAH58mD106/W/fpA+dO+3hu4FPvx5/j9b/z/F+iF1s8cWDeUGLfhz0aEb6uG/ejSE2Uf+hsc/zalD8IQPicVD92sE5M9x/VO/HbJdmf9c6A9R7Q/+3SSO9J9Efygw/u95RYvEfHDq+8mtl7m9nYXP2LH/B9tfbiM= \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_e313d2c2-b2bb-4f84-8227-b91d988ded24.msgpack.zlib b/docs/cassettes/qa_streaming_e313d2c2-b2bb-4f84-8227-b91d988ded24.msgpack.zlib new file mode 100644 index 0000000000000..4ba35baa90167 --- /dev/null +++ b/docs/cassettes/qa_streaming_e313d2c2-b2bb-4f84-8227-b91d988ded24.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/qa_streaming_e89a5def-f040-4fd6-a34b-6815eae5ed9a.msgpack.zlib b/docs/cassettes/qa_streaming_e89a5def-f040-4fd6-a34b-6815eae5ed9a.msgpack.zlib new file mode 100644 index 0000000000000..7641be9751c3a --- /dev/null +++ b/docs/cassettes/qa_streaming_e89a5def-f040-4fd6-a34b-6815eae5ed9a.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_00d455e1-c681-4665-9470-58dbeca050d4.msgpack.zlib b/docs/cassettes/rag_00d455e1-c681-4665-9470-58dbeca050d4.msgpack.zlib new file mode 100644 index 0000000000000..8c0a417af68c9 --- /dev/null +++ b/docs/cassettes/rag_00d455e1-c681-4665-9470-58dbeca050d4.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_0b44b41a-8b25-42ad-9e37-7baf82a058cd.msgpack.zlib b/docs/cassettes/rag_0b44b41a-8b25-42ad-9e37-7baf82a058cd.msgpack.zlib deleted file mode 100644 index ce8f169759f96..0000000000000 --- a/docs/cassettes/rag_0b44b41a-8b25-42ad-9e37-7baf82a058cd.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_1a0d25f8-8a45-4ec7-b419-c36e231fde13.msgpack.zlib b/docs/cassettes/rag_1a0d25f8-8a45-4ec7-b419-c36e231fde13.msgpack.zlib deleted file mode 100644 index 00533d8deec1b..0000000000000 --- a/docs/cassettes/rag_1a0d25f8-8a45-4ec7-b419-c36e231fde13.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_28625cc3-0f77-4143-af51-ce0fd6682120.msgpack.zlib b/docs/cassettes/rag_28625cc3-0f77-4143-af51-ce0fd6682120.msgpack.zlib new file mode 100644 index 0000000000000..eb5a63ac8ea43 --- /dev/null +++ b/docs/cassettes/rag_28625cc3-0f77-4143-af51-ce0fd6682120.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_2ac552b6.msgpack.zlib b/docs/cassettes/rag_2ac552b6.msgpack.zlib deleted file mode 100644 index c79c610d7f9b2..0000000000000 --- a/docs/cassettes/rag_2ac552b6.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_46f378c5-858c-488f-8aef-8b59a6280791.msgpack.zlib b/docs/cassettes/rag_46f378c5-858c-488f-8aef-8b59a6280791.msgpack.zlib new file mode 100644 index 0000000000000..95af75a39e78c --- /dev/null +++ b/docs/cassettes/rag_46f378c5-858c-488f-8aef-8b59a6280791.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_6281ec7b.msgpack.zlib b/docs/cassettes/rag_6281ec7b.msgpack.zlib deleted file mode 100644 index 92a7fb7d961c3..0000000000000 --- a/docs/cassettes/rag_6281ec7b.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_663b93ba-f0a7-44c4-a894-fe895bd5b009.msgpack.zlib b/docs/cassettes/rag_663b93ba-f0a7-44c4-a894-fe895bd5b009.msgpack.zlib new file mode 100644 index 0000000000000..1217db8ad325a --- /dev/null +++ b/docs/cassettes/rag_663b93ba-f0a7-44c4-a894-fe895bd5b009.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_7b0971b5-8579-4a89-bd2e-9029dda4c4f1.msgpack.zlib b/docs/cassettes/rag_7b0971b5-8579-4a89-bd2e-9029dda4c4f1.msgpack.zlib new file mode 100644 index 0000000000000..9263148fa7008 --- /dev/null +++ b/docs/cassettes/rag_7b0971b5-8579-4a89-bd2e-9029dda4c4f1.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_8a92d539-f85d-434b-b911-51a1cf9b81da.msgpack.zlib b/docs/cassettes/rag_8a92d539-f85d-434b-b911-51a1cf9b81da.msgpack.zlib new file mode 100644 index 0000000000000..fb38ad8f17a1e --- /dev/null +++ b/docs/cassettes/rag_8a92d539-f85d-434b-b911-51a1cf9b81da.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_8b420650-2d9e-4f5e-a8d8-ec36ae07423c.msgpack.zlib b/docs/cassettes/rag_8b420650-2d9e-4f5e-a8d8-ec36ae07423c.msgpack.zlib new file mode 100644 index 0000000000000..b995e59714317 --- /dev/null +++ b/docs/cassettes/rag_8b420650-2d9e-4f5e-a8d8-ec36ae07423c.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_d6820cf3-e14d-4275-bd00-aa1b8262b1ae.msgpack.zlib b/docs/cassettes/rag_d6820cf3-e14d-4275-bd00-aa1b8262b1ae.msgpack.zlib deleted file mode 100644 index 09146a28c64dd..0000000000000 --- a/docs/cassettes/rag_d6820cf3-e14d-4275-bd00-aa1b8262b1ae.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_e6314a96-aab8-4ecc-bbf9-094fa2aa0e50.msgpack.zlib b/docs/cassettes/rag_e6314a96-aab8-4ecc-bbf9-094fa2aa0e50.msgpack.zlib new file mode 100644 index 0000000000000..753be22c1b306 --- /dev/null +++ b/docs/cassettes/rag_e6314a96-aab8-4ecc-bbf9-094fa2aa0e50.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_e75bfe98-d9e4-4868-bae1-5811437d859b.msgpack.zlib b/docs/cassettes/rag_e75bfe98-d9e4-4868-bae1-5811437d859b.msgpack.zlib deleted file mode 100644 index f61ca4ecef6c8..0000000000000 --- a/docs/cassettes/rag_e75bfe98-d9e4-4868-bae1-5811437d859b.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_ebb3cbd7-7c75-4cc0-a198-ff7c54a0c43a.msgpack.zlib b/docs/cassettes/rag_ebb3cbd7-7c75-4cc0-a198-ff7c54a0c43a.msgpack.zlib new file mode 100644 index 0000000000000..33e0796e1b5d1 --- /dev/null +++ b/docs/cassettes/rag_ebb3cbd7-7c75-4cc0-a198-ff7c54a0c43a.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_f5ba0122-8c92-4895-b5ef-f03a634e3fdf.msgpack.zlib b/docs/cassettes/rag_f5ba0122-8c92-4895-b5ef-f03a634e3fdf.msgpack.zlib deleted file mode 100644 index 2efa24570d409..0000000000000 --- a/docs/cassettes/rag_f5ba0122-8c92-4895-b5ef-f03a634e3fdf.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_feabc04f-b509-4452-8e2b-d7c7b7585a18.msgpack.zlib b/docs/cassettes/rag_feabc04f-b509-4452-8e2b-d7c7b7585a18.msgpack.zlib new file mode 100644 index 0000000000000..446cc7c103613 --- /dev/null +++ b/docs/cassettes/rag_feabc04f-b509-4452-8e2b-d7c7b7585a18.msgpack.zlib @@ -0,0 +1 @@ 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 \ No newline at end of file diff --git a/docs/cassettes/rag_ff01d415-7b0f-469d-bfda-b9cb672da611.msgpack.zlib b/docs/cassettes/rag_ff01d415-7b0f-469d-bfda-b9cb672da611.msgpack.zlib deleted file mode 100644 index 8012a1a14c145..0000000000000 --- a/docs/cassettes/rag_ff01d415-7b0f-469d-bfda-b9cb672da611.msgpack.zlib +++ /dev/null @@ -1 +0,0 @@ -eNrtVV9v3EQQV8UXWa2QkND5znfn8zVGeYii0iIaFdSChNrK2qzH9jb2rru7zuUa3QOhrzyYTwAkSqqoBR4QL1CJN3jgC4RPw6x91z8hqFV5hJNO55vZmfnNzm9+PjjZBW2EkpceC2lBM27xj/nq4ETD/RqMfXhcgs1Vcnj1yq3DWouzt3NrKxMNBqwSfVMKm/cLJjOeMyH7XJUDIVN1tK2S+a8nObAE0z88/cSA9jYykLb50Z1u47xqPvD7w/5wdPn7Dc6hst4VyVUiZNY8yR6IqkcSSAtm4bhzNz+wqioEZw7j4J5R8nRTSQkt5uZ0B6DyWCF24ZEGU2Eb8MWxsczW5uAI88Ifv5+UYAzL4NsbH67AfXmyUVjv5i5vzvr5eJ1GQTCm75GSrY8mayPf93v52ButXeA4Iw6WMR6CsFoV3kZRqJm3qSHBRgUrTHNkdQ2/XHjsWle++ebdxxwdGOHZeQV/7/HnC8NvaJEJ2Xz90znvFttzF90chr5/ceGtdp6u8NNz/it7lTLwArJjHBvyozmpdwVXWh4lOIzm6fta9MhoSm5CRUb+KCDDMBqOo0lIrm7dOvxUsOYUp0oypbICnnDGc/B4V6N5JJXXWr7bXHZ9HWRm8+YwmExa2nyOM9PIgT8v/bZPl+ykEfX70/54jfYoXg7gaGPYq4Rurym2ogQaybooenSbWZ7HGI/kjbFqKjIa7VPDWQFxXcX3jXgAMVbIMtA0GroJP/dKm2ts38SFQIqiO1w5EzWTsYSysvPn0QF6XbrV6TbXM0O8PbdgaDTy16bDychf9KiQSEjJIUZeZ8YBw6XAtbMQMxHjxul5DJJtF5DQyJGnR5XOYo6g2k4TYZbOFPmFXpOrWWxtEddiFWBxi7FDATpO6uUNJWzeViuUzNyGYIKgBZsrbZeGYYAADTCN93cOw0zpHVO5tIarCmKHSchd0ba3QjKOjVUat+vl6MXin8Vk/VVigl+0moEuygGm9iqtcAIDJwrG/q8y/0WVmf4rlbkcBC+rzFvX92nHsjhnJkelmfhBMGLpcDyGcDiZhjANJuOQh5NJyCGFYcr4MJhylvjjURqMp9Pt0OfBOISQJ3w7BNSokkmRIkPdygncg9v0Ga3R25HY4BNaLP5s4s9HrfEWCozjIr2LQsdxJ3GdcV6ICltDxDXHFcOInRnTnX4suYbPt1+r1rUawW11QW9as0v6quaWp3r0TcvYVUREP1M1YRoIk4QZI5yIWpIqTVpdQRJ7TJoZuIkSy8yO6RNUA2JzwFOOkM5RCUAmEpUSDTh8QNUj7VbsWWIV6TK0MausffJBSuZYO1HyHUt2pJq1/u5oj9yrjSWGzdHI7LmDKwQagBhwLHTFS7YnyrrEDAlxUvJCOoeFCwP9O/LjZf2I7K+gLMgdudmBResStjNutMERdS+XqrbxLtPCya9jBF1Fu/l3Ie76Vxcb4w2WyIqIpl63DnSBn7uvnWqBbwzYY5itPXN38RcRsNwq \ No newline at end of file diff --git a/docs/docs/additional_resources/arxiv_references.mdx b/docs/docs/additional_resources/arxiv_references.mdx index 461399688f617..fb843aa0c3cdc 100644 --- a/docs/docs/additional_resources/arxiv_references.mdx +++ b/docs/docs/additional_resources/arxiv_references.mdx @@ -28,19 +28,19 @@ From the opposite direction, scientists use `LangChain` in research and referenc | `2307.09288v2` [Llama 2: Open Foundation and Fine-Tuned Chat Models](http://arxiv.org/abs/2307.09288v2) | Hugo Touvron, Louis Martin, Kevin Stone, et al. | 2023‑07‑18 | `Cookbook:` [Semi Structured Rag](https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_Structured_RAG.ipynb) | `2307.03172v3` [Lost in the Middle: How Language Models Use Long Contexts](http://arxiv.org/abs/2307.03172v3) | Nelson F. Liu, Kevin Lin, John Hewitt, et al. | 2023‑07‑06 | `Docs:` [docs/how_to/long_context_reorder](https://python.langchain.com/docs/how_to/long_context_reorder) | `2305.14283v3` [Query Rewriting for Retrieval-Augmented Large Language Models](http://arxiv.org/abs/2305.14283v3) | Xinbei Ma, Yeyun Gong, Pengcheng He, et al. | 2023‑05‑23 | `Template:` [rewrite-retrieve-read](https://python.langchain.com/docs/templates/rewrite-retrieve-read), `Cookbook:` [Rewrite](https://github.com/langchain-ai/langchain/blob/master/cookbook/rewrite.ipynb) -| `2305.08291v1` [Large Language Model Guided Tree-of-Thought](http://arxiv.org/abs/2305.08291v1) | Jieyi Long | 2023‑05‑15 | `API:` [langchain_experimental.tot](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.tot), `Cookbook:` [Tree Of Thought](https://github.com/langchain-ai/langchain/blob/master/cookbook/tree_of_thought.ipynb) +| `2305.08291v1` [Large Language Model Guided Tree-of-Thought](http://arxiv.org/abs/2305.08291v1) | Jieyi Long | 2023‑05‑15 | `API:` [langchain_experimental.tot](https://python.langchain.com/api_reference/experimental/tot.html), `Cookbook:` [Tree Of Thought](https://github.com/langchain-ai/langchain/blob/master/cookbook/tree_of_thought.ipynb) | `2305.04091v3` [Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models](http://arxiv.org/abs/2305.04091v3) | Lei Wang, Wanyu Xu, Yihuai Lan, et al. | 2023‑05‑06 | `Cookbook:` [Plan And Execute Agent](https://github.com/langchain-ai/langchain/blob/master/cookbook/plan_and_execute_agent.ipynb) -| `2305.02156v1` [Zero-Shot Listwise Document Reranking with a Large Language Model](http://arxiv.org/abs/2305.02156v1) | Xueguang Ma, Xinyu Zhang, Ronak Pradeep, et al. | 2023‑05‑03 | `Docs:` [docs/how_to/contextual_compression](https://python.langchain.com/docs/how_to/contextual_compression), `API:` [langchain...LLMListwiseRerank](https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank) +| `2305.02156v1` [Zero-Shot Listwise Document Reranking with a Large Language Model](http://arxiv.org/abs/2305.02156v1) | Xueguang Ma, Xinyu Zhang, Ronak Pradeep, et al. | 2023‑05‑03 | `Docs:` [docs/how_to/contextual_compression](https://python.langchain.com/docs/how_to/contextual_compression), `API:` [langchain...LLMListwiseRerank](https://python.langchain.com/api_reference/langchain/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#) | `2304.08485v2` [Visual Instruction Tuning](http://arxiv.org/abs/2304.08485v2) | Haotian Liu, Chunyuan Li, Qingyang Wu, et al. | 2023‑04‑17 | `Cookbook:` [Semi Structured Multi Modal Rag Llama2](https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb), [Semi Structured And Multi Modal Rag](https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_structured_and_multi_modal_RAG.ipynb) | `2304.03442v2` [Generative Agents: Interactive Simulacra of Human Behavior](http://arxiv.org/abs/2304.03442v2) | Joon Sung Park, Joseph C. O'Brien, Carrie J. Cai, et al. | 2023‑04‑07 | `Cookbook:` [Generative Agents Interactive Simulacra Of Human Behavior](https://github.com/langchain-ai/langchain/blob/master/cookbook/generative_agents_interactive_simulacra_of_human_behavior.ipynb), [Multiagent Bidding](https://github.com/langchain-ai/langchain/blob/master/cookbook/multiagent_bidding.ipynb) | `2303.17760v2` [CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](http://arxiv.org/abs/2303.17760v2) | Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al. | 2023‑03‑31 | `Cookbook:` [Camel Role Playing](https://github.com/langchain-ai/langchain/blob/master/cookbook/camel_role_playing.ipynb) -| `2303.17580v4` [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face](http://arxiv.org/abs/2303.17580v4) | Yongliang Shen, Kaitao Song, Xu Tan, et al. | 2023‑03‑30 | `API:` [langchain_experimental.autonomous_agents](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.autonomous_agents), `Cookbook:` [Hugginggpt](https://github.com/langchain-ai/langchain/blob/master/cookbook/hugginggpt.ipynb) +| `2303.17580v4` [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face](http://arxiv.org/abs/2303.17580v4) | Yongliang Shen, Kaitao Song, Xu Tan, et al. | 2023‑03‑30 | `API:` [langchain_experimental.autonomous_agents](https://python.langchain.com/api_reference/experimental/autonomous_agents.html), `Cookbook:` [Hugginggpt](https://github.com/langchain-ai/langchain/blob/master/cookbook/hugginggpt.ipynb) | `2301.10226v4` [A Watermark for Large Language Models](http://arxiv.org/abs/2301.10226v4) | John Kirchenbauer, Jonas Geiping, Yuxin Wen, et al. | 2023‑01‑24 | `API:` [langchain_community...OCIModelDeploymentTGI](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI.html#langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI), [langchain_huggingface...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint), [langchain_community...HuggingFaceTextGenInference](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html#langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference), [langchain_community...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint) | `2212.10496v1` [Precise Zero-Shot Dense Retrieval without Relevance Labels](http://arxiv.org/abs/2212.10496v1) | Luyu Gao, Xueguang Ma, Jimmy Lin, et al. | 2022‑12‑20 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts), `API:` [langchain...HypotheticalDocumentEmbedder](https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html#langchain.chains.hyde.base.HypotheticalDocumentEmbedder), `Template:` [hyde](https://python.langchain.com/docs/templates/hyde), `Cookbook:` [Hypothetical Document Embeddings](https://github.com/langchain-ai/langchain/blob/master/cookbook/hypothetical_document_embeddings.ipynb) | `2212.08073v1` [Constitutional AI: Harmlessness from AI Feedback](http://arxiv.org/abs/2212.08073v1) | Yuntao Bai, Saurav Kadavath, Sandipan Kundu, et al. | 2022‑12‑15 | `Docs:` [docs/versions/migrating_chains/constitutional_chain](https://python.langchain.com/docs/versions/migrating_chains/constitutional_chain) -| `2212.07425v3` [Robust and Explainable Identification of Logical Fallacies in Natural Language Arguments](http://arxiv.org/abs/2212.07425v3) | Zhivar Sourati, Vishnu Priya Prasanna Venkatesh, Darshan Deshpande, et al. | 2022‑12‑12 | `API:` [langchain_experimental.fallacy_removal](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.fallacy_removal) +| `2212.07425v3` [Robust and Explainable Identification of Logical Fallacies in Natural Language Arguments](http://arxiv.org/abs/2212.07425v3) | Zhivar Sourati, Vishnu Priya Prasanna Venkatesh, Darshan Deshpande, et al. | 2022‑12‑12 | `API:` [langchain_experimental.fallacy_removal](https://python.langchain.com/api_reference/experimental/fallacy_removal.html) | `2211.13892v2` [Complementary Explanations for Effective In-Context Learning](http://arxiv.org/abs/2211.13892v2) | Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, et al. | 2022‑11‑25 | `API:` [langchain_core...MaxMarginalRelevanceExampleSelector](https://api.python.langchain.com/en/latest/example_selectors/langchain_core.example_selectors.semantic_similarity.MaxMarginalRelevanceExampleSelector.html#langchain_core.example_selectors.semantic_similarity.MaxMarginalRelevanceExampleSelector) -| `2211.10435v2` [PAL: Program-aided Language Models](http://arxiv.org/abs/2211.10435v2) | Luyu Gao, Aman Madaan, Shuyan Zhou, et al. | 2022‑11‑18 | `API:` [langchain_experimental.pal_chain](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.pal_chain), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain), `Cookbook:` [Program Aided Language Model](https://github.com/langchain-ai/langchain/blob/master/cookbook/program_aided_language_model.ipynb) +| `2211.10435v2` [PAL: Program-aided Language Models](http://arxiv.org/abs/2211.10435v2) | Luyu Gao, Aman Madaan, Shuyan Zhou, et al. | 2022‑11‑18 | `API:` [langchain_experimental.pal_chain](https://python.langchain.com/api_reference/experimental/pal_chain.html), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain), `Cookbook:` [Program Aided Language Model](https://github.com/langchain-ai/langchain/blob/master/cookbook/program_aided_language_model.ipynb) | `2210.11934v2` [An Analysis of Fusion Functions for Hybrid Retrieval](http://arxiv.org/abs/2210.11934v2) | Sebastian Bruch, Siyu Gai, Amir Ingber | 2022‑10‑21 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts) | `2210.03629v3` [ReAct: Synergizing Reasoning and Acting in Language Models](http://arxiv.org/abs/2210.03629v3) | Shunyu Yao, Jeffrey Zhao, Dian Yu, et al. | 2022‑10‑06 | `Docs:` [docs/integrations/tools/ionic_shopping](https://python.langchain.com/docs/integrations/tools/ionic_shopping), [docs/integrations/providers/cohere](https://python.langchain.com/docs/integrations/providers/cohere), [docs/concepts](https://python.langchain.com/docs/concepts), `API:` [langchain...create_react_agent](https://api.python.langchain.com/en/latest/agents/langchain.agents.react.agent.create_react_agent.html#langchain.agents.react.agent.create_react_agent), [langchain...TrajectoryEvalChain](https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html#langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain) | `2209.10785v2` [Deep Lake: a Lakehouse for Deep Learning](http://arxiv.org/abs/2209.10785v2) | Sasun Hambardzumyan, Abhinav Tuli, Levon Ghukasyan, et al. | 2022‑09‑22 | `Docs:` [docs/integrations/providers/activeloop_deeplake](https://python.langchain.com/docs/integrations/providers/activeloop_deeplake) @@ -49,7 +49,7 @@ From the opposite direction, scientists use `LangChain` in research and referenc | `2204.00498v1` [Evaluating the Text-to-SQL Capabilities of Large Language Models](http://arxiv.org/abs/2204.00498v1) | Nitarshan Rajkumar, Raymond Li, Dzmitry Bahdanau | 2022‑03‑15 | `Docs:` [docs/tutorials/sql_qa](https://python.langchain.com/docs/tutorials/sql_qa), `API:` [langchain_community...SQLDatabase](https://api.python.langchain.com/en/latest/utilities/langchain_community.utilities.sql_database.SQLDatabase.html#langchain_community.utilities.sql_database.SQLDatabase), [langchain_community...SparkSQL](https://api.python.langchain.com/en/latest/utilities/langchain_community.utilities.spark_sql.SparkSQL.html#langchain_community.utilities.spark_sql.SparkSQL) | `2202.00666v5` [Locally Typical Sampling](http://arxiv.org/abs/2202.00666v5) | Clara Meister, Tiago Pimentel, Gian Wiher, et al. | 2022‑02‑01 | `API:` [langchain_huggingface...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint), [langchain_community...HuggingFaceTextGenInference](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html#langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference), [langchain_community...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint) | `2112.01488v3` [ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction](http://arxiv.org/abs/2112.01488v3) | Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, et al. | 2021‑12‑02 | `Docs:` [docs/integrations/retrievers/ragatouille](https://python.langchain.com/docs/integrations/retrievers/ragatouille), [docs/integrations/providers/ragatouille](https://python.langchain.com/docs/integrations/providers/ragatouille), [docs/concepts](https://python.langchain.com/docs/concepts), [docs/integrations/providers/dspy](https://python.langchain.com/docs/integrations/providers/dspy) -| `2103.00020v1` [Learning Transferable Visual Models From Natural Language Supervision](http://arxiv.org/abs/2103.00020v1) | Alec Radford, Jong Wook Kim, Chris Hallacy, et al. | 2021‑02‑26 | `API:` [langchain_experimental.open_clip](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.open_clip) +| `2103.00020v1` [Learning Transferable Visual Models From Natural Language Supervision](http://arxiv.org/abs/2103.00020v1) | Alec Radford, Jong Wook Kim, Chris Hallacy, et al. | 2021‑02‑26 | `API:` [langchain_experimental.open_clip](https://python.langchain.com/api_reference/experimental/open_clip.html) | `2005.14165v4` [Language Models are Few-Shot Learners](http://arxiv.org/abs/2005.14165v4) | Tom B. Brown, Benjamin Mann, Nick Ryder, et al. | 2020‑05‑28 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts) | `2005.11401v4` [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](http://arxiv.org/abs/2005.11401v4) | Patrick Lewis, Ethan Perez, Aleksandra Piktus, et al. | 2020‑05‑22 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts) | `1909.05858v2` [CTRL: A Conditional Transformer Language Model for Controllable Generation](http://arxiv.org/abs/1909.05858v2) | Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al. | 2019‑09‑11 | `API:` [langchain_huggingface...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint), [langchain_community...HuggingFaceTextGenInference](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html#langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference), [langchain_community...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint) @@ -433,7 +433,7 @@ for retrieval-augmented LLM. - **arXiv id:** [2305.08291v1](http://arxiv.org/abs/2305.08291v1) **Published Date:** 2023-05-15 - **LangChain:** - - **API Reference:** [langchain_experimental.tot](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.tot) + - **API Reference:** [langchain_experimental.tot](https://python.langchain.com/api_reference/experimental/tot.html) - **Cookbook:** [tree_of_thought](https://github.com/langchain-ai/langchain/blob/master/cookbook/tree_of_thought.ipynb) **Abstract:** In this paper, we introduce the Tree-of-Thought (ToT) framework, a novel @@ -490,7 +490,7 @@ https://github.com/AGI-Edgerunners/Plan-and-Solve-Prompting. - **LangChain:** - **Documentation:** [docs/how_to/contextual_compression](https://python.langchain.com/docs/how_to/contextual_compression) - - **API Reference:** [langchain...LLMListwiseRerank](https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank) + - **API Reference:** [langchain...LLMListwiseRerank](https://python.langchain.com/api_reference/langchain/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#) **Abstract:** Supervised ranking methods based on bi-encoder or cross-encoder architectures have shown success in multi-stage text ranking tasks, but they require large @@ -597,7 +597,7 @@ agents and beyond: https://github.com/camel-ai/camel. - **arXiv id:** [2303.17580v4](http://arxiv.org/abs/2303.17580v4) **Published Date:** 2023-03-30 - **LangChain:** - - **API Reference:** [langchain_experimental.autonomous_agents](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.autonomous_agents) + - **API Reference:** [langchain_experimental.autonomous_agents](https://python.langchain.com/api_reference/experimental/autonomous_agents.html) - **Cookbook:** [hugginggpt](https://github.com/langchain-ai/langchain/blob/master/cookbook/hugginggpt.ipynb) **Abstract:** Solving complicated AI tasks with different domains and modalities is a key @@ -704,7 +704,7 @@ labels. - **arXiv id:** [2212.07425v3](http://arxiv.org/abs/2212.07425v3) **Published Date:** 2022-12-12 - **LangChain:** - - **API Reference:** [langchain_experimental.fallacy_removal](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.fallacy_removal) + - **API Reference:** [langchain_experimental.fallacy_removal](https://python.langchain.com/api_reference/experimental/fallacy_removal.html) **Abstract:** The spread of misinformation, propaganda, and flawed argumentation has been amplified in the Internet era. Given the volume of data and the subtlety of @@ -759,7 +759,7 @@ performance across three real-world tasks on multiple LLMs. - **arXiv id:** [2211.10435v2](http://arxiv.org/abs/2211.10435v2) **Published Date:** 2022-11-18 - **LangChain:** - - **API Reference:** [langchain_experimental.pal_chain](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.pal_chain), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain) + - **API Reference:** [langchain_experimental.pal_chain](https://python.langchain.com/api_reference/experimental/pal_chain.html), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain) - **Cookbook:** [program_aided_language_model](https://github.com/langchain-ai/langchain/blob/master/cookbook/program_aided_language_model.ipynb) **Abstract:** Large language models (LLMs) have recently demonstrated an impressive ability @@ -992,7 +992,7 @@ footprint of late interaction models by 6--10$\times$. - **arXiv id:** [2103.00020v1](http://arxiv.org/abs/2103.00020v1) **Published Date:** 2021-02-26 - **LangChain:** - - **API Reference:** [langchain_experimental.open_clip](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.open_clip) + - **API Reference:** [langchain_experimental.open_clip](https://python.langchain.com/api_reference/experimental/open_clip.html) **Abstract:** State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories. This restricted form of supervision limits diff --git a/docs/docs/concepts/architecture.mdx b/docs/docs/concepts/architecture.mdx index 923ee5a705f20..66272190080b9 100644 --- a/docs/docs/concepts/architecture.mdx +++ b/docs/docs/concepts/architecture.mdx @@ -65,7 +65,7 @@ A package to deploy LangChain chains as REST APIs. Makes it easy to get a produc :::important LangServe is designed to primarily deploy simple Runnables and work with well-known primitives in langchain-core. -If you need a deployment option for LangGraph, you should instead be looking at LangGraph Cloud (beta) which will be better suited for deploying LangGraph applications. +If you need a deployment option for LangGraph, you should instead be looking at LangGraph Platform (beta) which will be better suited for deploying LangGraph applications. ::: For more information, see the [LangServe documentation](/docs/langserve). diff --git a/docs/docs/concepts/embedding_models.mdx b/docs/docs/concepts/embedding_models.mdx index 978188421c6fd..a91018036c0af 100644 --- a/docs/docs/concepts/embedding_models.mdx +++ b/docs/docs/concepts/embedding_models.mdx @@ -3,7 +3,7 @@ :::info[Prerequisites] -* [Documents](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) +* [Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) ::: @@ -25,7 +25,7 @@ Embeddings allow search system to find relevant documents not just based on keyw (1) **Embed text as a vector**: Embeddings transform text into a numerical vector representation. -(2) **Measure similarity**: Embedding vectors can be comparing using simple mathematical operations. +(2) **Measure similarity**: Embedding vectors can be compared using simple mathematical operations. ## Embedding diff --git a/docs/docs/concepts/rag.mdx b/docs/docs/concepts/rag.mdx index eb4752b6ffe2d..0180aa74a87a5 100644 --- a/docs/docs/concepts/rag.mdx +++ b/docs/docs/concepts/rag.mdx @@ -1,4 +1,4 @@ -# Retrieval augmented generation (rag) +# Retrieval augmented generation (RAG) :::info[Prerequisites] @@ -91,7 +91,7 @@ RAG a deep area with many possible optimization and design choices: * See [this excellent blog](https://cameronrwolfe.substack.com/p/a-practitioners-guide-to-retrieval?utm_source=profile&utm_medium=reader2) from Cameron Wolfe for a comprehensive overview and history of RAG. * See our [RAG how-to guides](/docs/how_to/#qa-with-rag). -* See our RAG [tutorials](/docs/tutorials/#working-with-external-knowledge). +* See our RAG [tutorials](/docs/tutorials/). * See our RAG from Scratch course, with [code](https://github.com/langchain-ai/rag-from-scratch) and [video playlist](https://www.youtube.com/playlist?list=PLfaIDFEXuae2LXbO1_PKyVJiQ23ZztA0x). * Also, see our RAG from Scratch course [on Freecodecamp](https://youtu.be/sVcwVQRHIc8?feature=shared). diff --git a/docs/docs/concepts/retrieval.mdx b/docs/docs/concepts/retrieval.mdx index 0ded476b80016..69a2f755550a0 100644 --- a/docs/docs/concepts/retrieval.mdx +++ b/docs/docs/concepts/retrieval.mdx @@ -143,7 +143,7 @@ retriever = SelfQueryRetriever.from_llm( :::info[Further reading] -* See our tutorials on [text-to-SQL](/docs/tutorials/sql_qa/), [text-to-Cypher](/docs/tutorials/graph/), and [query analysis for metadata filters](/docs/tutorials/query_analysis/). +* See our tutorials on [text-to-SQL](/docs/tutorials/sql_qa/), [text-to-Cypher](/docs/tutorials/graph/), and [query analysis for metadata filters](/docs/tutorials/rag/#query-analysis). * See our [blog post overview](https://blog.langchain.dev/query-construction/). * See our RAG from Scratch video on [query construction](https://youtu.be/kl6NwWYxvbM?feature=shared). @@ -221,7 +221,7 @@ They are particularly useful for storing and querying complex relationships betw LangChain provides a unified interface for interacting with various retrieval systems through the [retriever](/docs/concepts/retrievers/) concept. The interface is straightforward: 1. Input: A query (string) -2. Output: A list of documents (standardized LangChain [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects) +2. Output: A list of documents (standardized LangChain [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects) You can create a retriever using any of the retrieval systems mentioned earlier. The query analysis techniques we discussed are particularly useful here, as they enable natural language interfaces for databases that typically require structured query languages. For example, you can build a retriever for a SQL database using text-to-SQL conversion. This allows a natural language query (string) to be transformed into a SQL query behind the scenes. diff --git a/docs/docs/concepts/retrievers.mdx b/docs/docs/concepts/retrievers.mdx index 3af42544004ee..1fb55a3f1c588 100644 --- a/docs/docs/concepts/retrievers.mdx +++ b/docs/docs/concepts/retrievers.mdx @@ -18,7 +18,7 @@ Because of their importance and variability, LangChain provides a uniform interf The LangChain [retriever](/docs/concepts/retrievers/) interface is straightforward: 1. Input: A query (string) -2. Output: A list of documents (standardized LangChain [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects) +2. Output: A list of documents (standardized LangChain [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects) ## Key concept @@ -29,7 +29,7 @@ All retrievers implement a simple interface for retrieving documents using natur ## Interface The only requirement for a retriever is the ability to accepts a query and return documents. -In particular, [LangChain's retriever class](https://api.python.langchain.com/en/latest/retrievers/langchain_core.retrievers.BaseRetriever.html) only requires that the `_get_relevant_documents` method is implemented, which takes a `query: str` and returns a list of [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects that are most relevant to the query. +In particular, [LangChain's retriever class](https://python.langchain.com/api_reference/core/retrievers/langchain_core.retrievers.BaseRetriever.html#) only requires that the `_get_relevant_documents` method is implemented, which takes a `query: str` and returns a list of [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects that are most relevant to the query. The underlying logic used to get relevant documents is specified by the retriever and can be whatever is most useful for the application. A LangChain retriever is a [runnable](/docs/how_to/lcel_cheatsheet/), which is a standard interface is for LangChain components. @@ -39,7 +39,7 @@ This means that it has a few common methods, including `invoke`, that are used t docs = retriever.invoke(query) ``` -Retrievers return a list of [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects, which have two attributes: +Retrievers return a list of [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects, which have two attributes: * `page_content`: The content of this document. Currently is a string. * `metadata`: Arbitrary metadata associated with this document (e.g., document id, file name, source, etc). diff --git a/docs/docs/concepts/runnables.mdx b/docs/docs/concepts/runnables.mdx index dea928568a735..93af2cecadc32 100644 --- a/docs/docs/concepts/runnables.mdx +++ b/docs/docs/concepts/runnables.mdx @@ -125,7 +125,7 @@ Please see the [Configurable Runnables](#configurable-runnables) section for mor LangChain will automatically try to infer the input and output types of a Runnable based on available information. -Currently, this inference does not work well for more complex Runnables that are built using [LCEL](/docs/concepts/lcel) composition, and the inferred input and / or output types may be incorrect. In these cases, we recommend that users override the inferred input and output types using the `with_types` method ([API Reference](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.with_types +Currently, this inference does not work well for more complex Runnables that are built using [LCEL](/docs/concepts/lcel) composition, and the inferred input and / or output types may be incorrect. In these cases, we recommend that users override the inferred input and output types using the `with_types` method ([API Reference](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.with_types ). ## RunnableConfig diff --git a/docs/docs/concepts/vectorstores.mdx b/docs/docs/concepts/vectorstores.mdx index aa5bcae7a2cd4..1a909453744a9 100644 --- a/docs/docs/concepts/vectorstores.mdx +++ b/docs/docs/concepts/vectorstores.mdx @@ -59,7 +59,7 @@ vector_store = InMemoryVectorStore(embedding=SomeEmbeddingModel()) To add documents, use the `add_documents` method. -This API works with a list of [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects. +This API works with a list of [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects. `Document` objects all have `page_content` and `metadata` attributes, making them a universal way to store unstructured text and associated metadata. ```python @@ -126,7 +126,7 @@ to the documentation of the specific vectorstore you are using to see what simil Given a similarity metric to measure the distance between the embedded query and any embedded document, we need an algorithm to efficiently search over *all* the embedded documents to find the most similar ones. There are various ways to do this. As an example, many vectorstores implement [HNSW (Hierarchical Navigable Small World)](https://www.pinecone.io/learn/series/faiss/hnsw/), a graph-based index structure that allows for efficient similarity search. Regardless of the search algorithm used under the hood, the LangChain vectorstore interface has a `similarity_search` method for all integrations. -This will take the search query, create an embedding, find similar documents, and return them as a list of [Documents](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html). +This will take the search query, create an embedding, find similar documents, and return them as a list of [Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html). ```python query = "my query" diff --git a/docs/docs/contributing/how_to/integrations/index.mdx b/docs/docs/contributing/how_to/integrations/index.mdx index eeb0f73b3fdbb..63b09faa70edb 100644 --- a/docs/docs/contributing/how_to/integrations/index.mdx +++ b/docs/docs/contributing/how_to/integrations/index.mdx @@ -1,17 +1,20 @@ --- +pagination_prev: null pagination_next: contributing/how_to/integrations/package --- # Contribute Integrations -LangChain integrations are packages that provide access to language models, vector stores, and other components that can be used in LangChain. +Integrations are a core component of LangChain. +LangChain provides standard interfaces for several different components (language models, vector stores, etc) that are crucial when building LLM applications. -This guide will walk you through how to contribute new integrations to LangChain, by -publishing an integration package to PyPi, and adding documentation for it -to the LangChain Monorepo. -These instructions will evolve over the next few months as we improve our integration -processes. +## Why contribute an integration to LangChain? + +- **Discoverability:** LangChain is the most used framework for building LLM applications, with over 20 million monthly downloads. LangChain integrations are discoverable by a large community of GenAI builders. +- **Interoptability:** LangChain components expose a standard interface, allowing developers to easily swap them for each other. If you implement a LangChain integration, any developer using a different component will easily be able to swap yours in. +- **Best Practices:** Through their standard interface, LangChain components encourage and facilitate best practices (streaming, async, etc) + ## Components to Integrate @@ -22,8 +25,7 @@ supported in LangChain ::: -While any component can be integrated into LangChain, at this time we are only accepting -new integrations in the docs of the following kinds: +While any component can be integrated into LangChain, there are specific types of integrations we encourage more: @@ -36,7 +38,6 @@ new integrations in the docs of the following kinds:
  • Chat Models
  • Tools/Toolkits
  • Retrievers
    • -
  • Document Loaders
  • Vector Stores
  • Embedding Models
    • @@ -44,6 +45,7 @@ new integrations in the docs of the following kinds:
    • LLMs (Text-Completion Models)
      • +
    • Document Loaders
    • Key-Value Stores
    • Document Transformers
    • Model Caches
      • @@ -60,18 +62,30 @@ new integrations in the docs of the following kinds: ## How to contribute an integration -The only step necessary to "be" a LangChain integration is to add documentation -that will render on this site (https://python.langchain.com/). - -As a prerequisite to adding your integration to our documentation, you must: +In order to contribute an integration, you should follow these steps: -1. Confirm that your integration is in the [list of components](#components-to-integrate) we are currently accepting. -2. [Implement your package](./package.mdx) and publish it to a public github repository. +1. Confirm that your integration is in the [list of components](#components-to-integrate) we are currently encouraging. +2. [Implement your package](/docs/contributing/how_to/integrations/package/) and publish it to a public github repository. 3. [Implement the standard tests](./standard_tests) for your integration and successfully run them. 4. [Publish your integration](./publish.mdx) by publishing the package to PyPi and add docs in the `docs/docs/integrations` directory of the LangChain monorepo. +5. [Optional] Open and merge a PR to add documentation for your integration to the official LangChain docs. +6. [Optional] Engage with the LangChain team for joint co-marketing ([see below](#co-marketing)). -Once you have completed these steps, you can submit a PR to the LangChain monorepo to add your integration to the documentation. +## Co-Marketing -## Further Reading +With over 20 million monthly downloads, LangChain has a large audience of developers building LLM applications. +Besides just adding integrations, we also like to show them examples of cool tools or APIs they can use. + +While traditionally called "co-marketing", we like to think of this more as "co-education". +For that reason, while we are happy to highlight your integration through our social media channels, we prefer to highlight examples that also serve some educational purpose. +Our main social media channels are Twitter and LinkedIn. + +Here are some heuristics for types of content we are excited to promote: -To get started, let's learn [how to bootstrap a new integration package](./package.mdx) for LangChain. +- **Integration announcement:** If you announce the integration with a link to the LangChain documentation page, we are happy to re-tweet/re-share on Twitter/LinkedIn. +- **Educational content:** We highlight good educational content on the weekends - if you write a good blog or make a good YouTube video, we are happy to share there! Note that we prefer content that is NOT framed as "here's how to use integration XYZ", but rather "here's how to do ABC", as we find that is more educational and helpful for developers. +- **End-to-end applications:** End-to-end applications are great resources for developers looking to build. We prefer to highlight applications that are more complex/agentic in nature, and that use [LangGraph](https://github.com/langchain-ai/langgraph) as the orchestration framework. We get particularly excited about anything involving long-term memory, human-in-the-loop interaction patterns, or multi-agent architectures. +- **Research:** We love highlighting novel research! Whether it is research built on top of LangChain or that integrates with it. + +## Further Reading +To get started, let's learn [how to implement an integration package](/docs/contributing/how_to/integrations/package/) for LangChain. diff --git a/docs/docs/contributing/how_to/integrations/package.mdx b/docs/docs/contributing/how_to/integrations/package.mdx index 0480ffbd54739..990f097fd2a19 100644 --- a/docs/docs/contributing/how_to/integrations/package.mdx +++ b/docs/docs/contributing/how_to/integrations/package.mdx @@ -2,23 +2,109 @@ pagination_next: contributing/how_to/integrations/standard_tests pagination_prev: contributing/how_to/integrations/index --- -# How to bootstrap a new integration package +# How to implement an integration package -This guide walks through the process of publishing a new LangChain integration -package to PyPi. +This guide walks through the process of implementing a LangChain integration +package. Integration packages are just Python packages that can be installed with `pip install `, which contain classes that are compatible with LangChain's core interfaces. +We will cover: + +1. (Optional) How to bootstrap a new integration package +2. How to implement components, such as [chat models](/docs/concepts/chat_models/) and [vector stores](/docs/concepts/vectorstores/), that adhere +to the LangChain interface; + +## (Optional) bootstrapping a new integration package + +In this section, we will outline 2 options for bootstrapping a new integration package, +and you're welcome to use other tools if you prefer! + +1. **langchain-cli**: This is a command-line tool that can be used to bootstrap a new integration package with a template for LangChain components and Poetry for dependency management. +2. **Poetry**: This is a Python dependency management tool that can be used to bootstrap a new Python package with dependencies. You can then add LangChain components to this package. + +
      + Option 1: langchain-cli (recommended) + +In this guide, we will be using the `langchain-cli` to create a new integration package +from a template, which can be edited to implement your LangChain components. + +### **Prerequisites** + +- [GitHub](https://github.com) account +- [PyPi](https://pypi.org/) account + +### Boostrapping a new Python package with langchain-cli + +First, install `langchain-cli` and `poetry`: + +```bash +pip install langchain-cli poetry +``` + +Next, come up with a name for your package. For this guide, we'll use `langchain-parrot-link`. +You can confirm that the name is available on PyPi by searching for it on the [PyPi website](https://pypi.org/). + +Next, create your new Python package with `langchain-cli`, and navigate into the new directory with `cd`: + +```bash +langchain-cli integration new + +> The name of the integration to create (e.g. `my-integration`): parrot-link +> Name of integration in PascalCase [ParrotLink]: + +cd parrot-link +``` + +Next, let's add any dependencies we need + +```bash +poetry add my-integration-sdk +``` + +We can also add some `typing` or `test` dependencies in a separate poetry dependency group. + +``` +poetry add --group typing my-typing-dep +poetry add --group test my-test-dep +``` + +And finally, have poetry set up a virtual environment with your dependencies, as well +as your integration package: + +```bash +poetry install --with lint,typing,test,test_integration +``` + +You now have a new Python package with a template for LangChain components! This +template comes with files for each integration type, and you're welcome to duplicate or +delete any of these files as needed (including the associated test files). + +To create any individual files from the [template], you can run e.g.: + +```bash +langchain-cli integration new \ + --name parrot-link \ + --name-class ParrotLink \ + --src integration_template/chat_models.py \ + --dst langchain_parrot_link/chat_models_2.py +``` + +
      + +
      + Option 2: Poetry (manual) + In this guide, we will be using [Poetry](https://python-poetry.org/) for dependency management and packaging, and you're welcome to use any other tools you prefer. -## **Prerequisites** +### **Prerequisites** - [GitHub](https://github.com) account - [PyPi](https://pypi.org/) account -## Boostrapping a new Python package with Poetry +### Boostrapping a new Python package with Poetry First, install Poetry: @@ -52,7 +138,7 @@ We recommended pinning these to the latest version: ChatResult: - """Override the _generate method to implement the chat model logic. - - This can be a call to an API, a call to a local model, or any other - implementation that generates a response to the input prompt. - - Args: - messages: the prompt composed of a list of messages. - stop: a list of strings on which the model should stop generating. - If generation stops due to a stop token, the stop token itself - SHOULD BE INCLUDED as part of the output. This is not enforced - across models right now, but it's a good practice to follow since - it makes it much easier to parse the output of the model - downstream and understand why generation stopped. - run_manager: A run manager with callbacks for the LLM. - """ - # Replace this with actual logic to generate a response from a list - # of messages. - last_message = messages[-1] - tokens = last_message.content[: self.parrot_buffer_length] - ct_input_tokens = sum(len(message.content) for message in messages) - ct_output_tokens = len(tokens) - message = AIMessage( - content=tokens, - additional_kwargs={}, # Used to add additional payload to the message - response_metadata={ # Use for response metadata - "time_in_seconds": 3, - }, - usage_metadata={ - "input_tokens": ct_input_tokens, - "output_tokens": ct_output_tokens, - "total_tokens": ct_input_tokens + ct_output_tokens, - }, - ) - ## - - generation = ChatGeneration(message=message) - return ChatResult(generations=[generation]) - - def _stream( - self, - messages: List[BaseMessage], - stop: Optional[List[str]] = None, - run_manager: Optional[CallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> Iterator[ChatGenerationChunk]: - """Stream the output of the model. - - This method should be implemented if the model can generate output - in a streaming fashion. If the model does not support streaming, - do not implement it. In that case streaming requests will be automatically - handled by the _generate method. - - Args: - messages: the prompt composed of a list of messages. - stop: a list of strings on which the model should stop generating. - If generation stops due to a stop token, the stop token itself - SHOULD BE INCLUDED as part of the output. This is not enforced - across models right now, but it's a good practice to follow since - it makes it much easier to parse the output of the model - downstream and understand why generation stopped. - run_manager: A run manager with callbacks for the LLM. - """ - last_message = messages[-1] - tokens = str(last_message.content[: self.parrot_buffer_length]) - ct_input_tokens = sum(len(message.content) for message in messages) - - for token in tokens: - usage_metadata = UsageMetadata( - { - "input_tokens": ct_input_tokens, - "output_tokens": 1, - "total_tokens": ct_input_tokens + 1, - } - ) - ct_input_tokens = 0 - chunk = ChatGenerationChunk( - message=AIMessageChunk(content=token, usage_metadata=usage_metadata) - ) - - if run_manager: - # This is optional in newer versions of LangChain - # The on_llm_new_token will be called automatically - run_manager.on_llm_new_token(token, chunk=chunk) - - yield chunk - - # Let's add some other information (e.g., response metadata) - chunk = ChatGenerationChunk( - message=AIMessageChunk(content="", response_metadata={"time_in_sec": 3}) - ) - if run_manager: - # This is optional in newer versions of LangChain - # The on_llm_new_token will be called automatically - run_manager.on_llm_new_token(token, chunk=chunk) - yield chunk - - @property - def _llm_type(self) -> str: - """Get the type of language model used by this chat model.""" - return "echoing-chat-model-advanced" - - @property - def _identifying_params(self) -> Dict[str, Any]: - """Return a dictionary of identifying parameters. - - This information is used by the LangChain callback system, which - is used for tracing purposes make it possible to monitor LLMs. - """ - return { - # The model name allows users to specify custom token counting - # rules in LLM monitoring applications (e.g., in LangSmith users - # can provide per token pricing for their model and monitor - # costs for the given LLM.) - "model_name": self.model_name, - } -```
      -## Push your package to a public Github repository +### Push your package to a public Github repository This is only required if you want to publish your integration in the LangChain documentation. @@ -270,6 +185,319 @@ This is only required if you want to publish your integration in the LangChain d 2. Push your code to the repository. 3. Confirm that your repository is viewable by the public (e.g. in a private browsing window, where you're not logged into Github). +## Implementing LangChain components + +LangChain components are subclasses of base classes in [langchain-core](/docs/concepts/architecture/#langchain-core). +Examples include [chat models](/docs/concepts/chat_models/), +[vector stores](/docs/concepts/vectorstores/), [tools](/docs/concepts/tools/), +[embedding models](/docs/concepts/embedding_models/) and [retrievers](/docs/concepts/retrievers/). + +Your integration package will typically implement a subclass of at least one of these +components. Expand the tabs below to see details on each. + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; +import CodeBlock from '@theme/CodeBlock'; + + + + + + Refer to the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) guide for + detail on a starter chat model [implementation](/docs/how_to/custom_chat_model/#implementation). + + You can start from the following template or langchain-cli command: + + ```bash + langchain-cli integration new \ + --name parrot-link \ + --name-class ParrotLink \ + --src integration_template/chat_models.py \ + --dst langchain_parrot_link/chat_models.py + ``` + +
      + Example chat model code + +import ChatModelSource from '../../../../src/theme/integration_template/integration_template/chat_models.py'; + + + { + ChatModelSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + + +
      + +       + + + Your vector store implementation will depend on your chosen database technology. + `langchain-core` includes a minimal + [in-memory vector store](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.in_memory.InMemoryVectorStore.html) + that we can use as a guide. You can access the code [here](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py). + + All vector stores must inherit from the [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) + base class. This interface consists of methods for writing, deleting and searching + for documents in the vector store. + + `VectorStore` supports a variety of synchronous and asynchronous search types (e.g., + nearest-neighbor or maximum marginal relevance), as well as interfaces for adding + documents to the store. See the [API Reference](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) + for all supported methods. The required methods are tabulated below: + + | Method/Property | Description | + |------------------------ |------------------------------------------------------| + | `add_documents` | Add documents to the vector store. | + | `delete` | Delete selected documents from vector store (by IDs) | + | `get_by_ids` | Get selected documents from vector store (by IDs) | + | `similarity_search` | Get documents most similar to a query. | + | `embeddings` (property) | Embeddings object for vector store. | + | `from_texts` | Instantiate vector store via adding texts. | + + Note that `InMemoryVectorStore` implements some optional search types, as well as + convenience methods for loading and dumping the object to a file, but this is not + necessary for all implementations. + + :::tip + + The [in-memory vector store](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py) + is tested against the standard tests in the LangChain Github repository. + + ::: + +
      + Example vector store code + +import VectorstoreSource from '../../../../src/theme/integration_template/integration_template/vectorstores.py'; + + + { + VectorstoreSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + + +
      + +       + + +Embeddings are used to convert `str` objects from `Document.page_content` fields +into a vector representation (represented as a list of floats). + +The `Embeddings` class must inherit from the [Embeddings](https://python.langchain.com/api_reference/core/embeddings/langchain_core.embeddings.embeddings.Embeddings.html#langchain_core.embeddings.embeddings.Embeddings) +base class. This interface has 5 methods that can be implemented. + +| Method/Property | Description | +|------------------------ |------------------------------------------------------| +| `__init__` | Initialize the embeddings object. (optional) | +| `embed_query` | Embed a list of texts. (required) | +| `embed_documents` | Embed a list of documents. (required) | +| `aembed_query` | Asynchronously embed a list of texts. (optional) | +| `aembed_documents` | Asynchronously embed a list of documents. (optional) | + +### Constructor + +The `__init__` constructor is optional but common, but can be used to set up any necessary attributes +that a user can pass in when initializing the embeddings object. Common attributes include + +- `model` - the id of the model to use for embeddings + +### Embedding queries vs documents + +The `embed_query` and `embed_documents` methods are required. These methods both operate +on string inputs (the accessing of `Document.page_content` attributes) is handled +by the VectorStore using the embedding model for legacy reasons. + +`embed_query` takes in a single string and returns a single embedding as a list of floats. +If your model has different modes for embedding queries vs the underlying documents, you can +implement this method to handle that. + +`embed_documents` takes in a list of strings and returns a list of embeddings as a list of lists of floats. + +### Implementation + +You can start from the following template or langchain-cli command: + +```bash +langchain-cli integration new \ + --name parrot-link \ + --name-class ParrotLink \ + --src integration_template/embeddings.py \ + --dst langchain_parrot_link/embeddings.py +``` + +
      + Example embeddings code + +import EmbeddingsSource from '/src/theme/integration_template/integration_template/embeddings.py'; + + + { + EmbeddingsSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + + +
      + +       + + +Tools are used in 2 main ways: + +1. To define an "input schema" or "args schema" to pass to a chat model's tool calling +feature along with a text request, such that the chat model can generate a "tool call", +or parameters to call the tool with. +2. To take a "tool call" as generated above, and take some action and return a response +that can be passed back to the chat model as a ToolMessage. + +The `Tools` class must inherit from the [BaseTool](https://python.langchain.com/api_reference/core/tools/langchain_core.tools.base.BaseTool.html#langchain_core.tools.base.BaseTool) base class. This interface has 3 properties and 2 methods that should be implemented in a +subclass. + +| Method/Property | Description | +|------------------------ |------------------------------------------------------| +| `name` | Name of the tool (passed to the LLM too). | +| `description` | Description of the tool (passed to the LLM too). | +| `args_schema` | Define the schema for the tool's input arguments. | +| `_run` | Run the tool with the given arguments. | +| `_arun` | Asynchronously run the tool with the given arguments.| + +### Properties + +`name`, `description`, and `args_schema` are all properties that should be implemented +in the subclass. `name` and `description` are strings that are used to identify the tool +and provide a description of what the tool does. Both of these are passed to the LLM, +and users may override these values depending on the LLM they are using as a form of +"prompt engineering." Giving these a concise and LLM-usable name and description is +important for the initial user experience of the tool. + +`args_schema` is a Pydantic `BaseModel` that defines the schema for the tool's input +arguments. This is used to validate the input arguments to the tool, and to provide +a schema for the LLM to fill out when calling the tool. Similar to the `name` and +`description` of the overall Tool class, the fields' names (the variable name) and +description (part of `Field(..., description="description")`) are passed to the LLM, +and the values in these fields should be concise and LLM-usable. + +### Run Methods + +`_run` is the main method that should be implemented in the subclass. This method +takes in the arguments from `args_schema` and runs the tool, returning a string +response. This method is usually called in a LangGraph [`ToolNode`](https://langchain-ai.github.io/langgraph/how-tos/tool-calling/), and can also be called in a legacy +`langchain.agents.AgentExecutor`. + +`_arun` is optional because by default, `_run` will be run in an async executor. +However, if your tool is calling any apis or doing any async work, you should implement +this method to run the tool asynchronously in addition to `_run`. + +### Implementation + +You can start from the following template or langchain-cli command: + +```bash +langchain-cli integration new \ + --name parrot-link \ + --name-class ParrotLink \ + --src integration_template/tools.py \ + --dst langchain_parrot_link/tools.py +``` + +
      + Example tool code + +import ToolSource from '/src/theme/integration_template/integration_template/tools.py'; + + + { + ToolSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + + +
      + +       + + +Retrievers are used to retrieve documents from APIs, databases, or other sources +based on a query. The `Retriever` class must inherit from the [BaseRetriever](https://python.langchain.com/api_reference/core/retrievers/langchain_core.retrievers.BaseRetriever.html) base class. This interface has 1 attribute and 2 methods that should be implemented in a subclass. + +| Method/Property | Description | +|------------------------ |------------------------------------------------------| +| `k` | Default number of documents to retrieve (configurable). | +| `_get_relevant_documents`| Retrieve documents based on a query. | +| `_aget_relevant_documents`| Asynchronously retrieve documents based on a query. | + +### Attributes + +`k` is an attribute that should be implemented in the subclass. This attribute +can simply be defined at the top of the class with a default value like +`k: int = 5`. This attribute is the default number of documents to retrieve +from the retriever, and can be overridden by the user when constructing or calling +the retriever. + +### Methods + +`_get_relevant_documents` is the main method that should be implemented in the subclass. + +This method takes in a query and returns a list of `Document` objects, which have 2 +main properties: + +- `page_content` - the text content of the document +- `metadata` - a dictionary of metadata about the document + +Retrievers are typically directly invoked by a user, e.g. as +`MyRetriever(k=4).invoke("query")`, which will automatically call `_get_relevant_documents` +under the hood. + +`_aget_relevant_documents` is optional because by default, `_get_relevant_documents` will +be run in an async executor. However, if your retriever is calling any apis or doing +any async work, you should implement this method to run the retriever asynchronously +in addition to `_get_relevant_documents` for performance reasons. + +### Implementation + +You can start from the following template or langchain-cli command: + +```bash +langchain-cli integration new \ + --name parrot-link \ + --name-class ParrotLink \ + --src integration_template/retrievers.py \ + --dst langchain_parrot_link/retrievers.py +``` + +
      + Example retriever code + +import RetrieverSource from '/src/theme/integration_template/integration_template/retrievers.py'; + + + { + RetrieverSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + + +
      + +       +       + +--- + ## Next Steps Now that you've implemented your package, you can move on to [testing your integration](../standard_tests) for your integration and successfully run them. diff --git a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb deleted file mode 100644 index 3f4410516a2b4..0000000000000 --- a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb +++ /dev/null @@ -1,472 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "pagination_next: contributing/how_to/integrations/publish\n", - "pagination_prev: contributing/how_to/integrations/package\n", - "---\n", - "# How to add standard tests to an integration\n", - "\n", - "When creating either a custom class for yourself or to publish in a LangChain integration, it is important to add standard tests to ensure it works as expected. This guide will show you how to add standard tests to a custom chat model, and you can **[Skip to the test templates](#standard-test-templates-per-component)** for implementing tests for each integration type.\n", - "\n", - "## Setup\n", - "\n", - "If you're coming from the [previous guide](../package), you have already installed these dependencies, and you can skip this section.\n", - "\n", - "First, let's install 2 dependencies:\n", - "\n", - "- `langchain-core` will define the interfaces we want to import to define our custom tool.\n", - "- `langchain-tests` will provide the standard tests we want to use. Recommended to pin to the latest version: \n", - "\n", - ":::note\n", - "\n", - "Because added tests in new versions of `langchain-tests` can break your CI/CD pipelines, we recommend pinning the \n", - "version of `langchain-tests` to avoid unexpected changes.\n", - "\n", - ":::\n", - "\n", - "import Tabs from '@theme/Tabs';\n", - "import TabItem from '@theme/TabItem';\n", - "\n", - "\n", - " \n", - "If you followed the [previous guide](../package), you should already have these dependencies installed!\n", - "\n", - "```bash\n", - "poetry add langchain-core\n", - "poetry add --group test pytest pytest-socket langchain-tests==\n", - "poetry install --with test\n", - "```\n", - " \n", - " \n", - "```bash\n", - "pip install -U langchain-core pytest pytest-socket langchain-tests\n", - "\n", - "# install current package in editable mode\n", - "pip install --editable .\n", - "```\n", - " \n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's say we're publishing a package, `langchain_parrot_link`, that exposes the chat model from the [guide on implementing the package](../package). We can add the standard tests to the package by following the steps below." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And we'll assume you've structured your package the same way as the main LangChain\n", - "packages:\n", - "\n", - "```plaintext\n", - "langchain-parrot-link/\n", - "├── langchain_parrot_link/\n", - "│ ├── __init__.py\n", - "│ └── chat_models.py\n", - "├── tests/\n", - "│ ├── __init__.py\n", - "│ └── test_chat_models.py\n", - "├── pyproject.toml\n", - "└── README.md\n", - "```\n", - "\n", - "## Add and configure standard tests\n", - "\n", - "There are 2 namespaces in the `langchain-tests` package: \n", - "\n", - "- [unit tests](../../../concepts/testing.mdx#unit-tests) (`langchain_tests.unit_tests`): designed to be used to test the component in isolation and without access to external services\n", - "- [integration tests](../../../concepts/testing.mdx#unit-tests) (`langchain_tests.integration_tests`): designed to be used to test the component with access to external services (in particular, the external service that the component is designed to interact with).\n", - "\n", - "Both types of tests are implemented as [`pytest` class-based test suites](https://docs.pytest.org/en/7.1.x/getting-started.html#group-multiple-tests-in-a-class).\n", - "\n", - "By subclassing the base classes for each type of standard test (see below), you get all of the standard tests for that type, and you\n", - "can override the properties that the test suite uses to configure the tests.\n", - "\n", - "### Standard chat model tests\n", - "\n", - "Here's how you would configure the standard unit tests for the custom chat model:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/unit_tests/test_chat_models.py\"\n", - "from typing import Tuple, Type\n", - "\n", - "from langchain_parrot_link.chat_models import ChatParrotLink\n", - "from langchain_tests.unit_tests import ChatModelUnitTests\n", - "\n", - "\n", - "class TestChatParrotLinkUnit(ChatModelUnitTests):\n", - " @property\n", - " def chat_model_class(self) -> Type[ChatParrotLink]:\n", - " return ChatParrotLink\n", - "\n", - " @property\n", - " def chat_model_params(self) -> dict:\n", - " return {\n", - " \"model\": \"bird-brain-001\",\n", - " \"temperature\": 0,\n", - " \"parrot_buffer_length\": 50,\n", - " }" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/integration_tests/test_chat_models.py\"\n", - "from typing import Type\n", - "\n", - "from langchain_parrot_link.chat_models import ChatParrotLink\n", - "from langchain_tests.integration_tests import ChatModelIntegrationTests\n", - "\n", - "\n", - "class TestChatParrotLinkIntegration(ChatModelIntegrationTests):\n", - " @property\n", - " def chat_model_class(self) -> Type[ChatParrotLink]:\n", - " return ChatParrotLink\n", - "\n", - " @property\n", - " def chat_model_params(self) -> dict:\n", - " return {\n", - " \"model\": \"bird-brain-001\",\n", - " \"temperature\": 0,\n", - " \"parrot_buffer_length\": 50,\n", - " }" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "and you would run these with the following commands from your project root\n", - "\n", - "\n", - " \n", - "\n", - "```bash\n", - "# run unit tests without network access\n", - "poetry run pytest --disable-socket --allow-unix-socket tests/unit_tests\n", - "\n", - "# run integration tests\n", - "poetry run pytest tests/integration_tests\n", - "```\n", - "\n", - " \n", - " \n", - "\n", - "```bash\n", - "# run unit tests without network access\n", - "pytest --disable-socket --allow-unix-socket tests/unit_tests\n", - "\n", - "# run integration tests\n", - "pytest tests/integration_tests\n", - "```\n", - "\n", - " \n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Standard test templates per component:\n", - "\n", - "Above, we implement the **unit** and **integration** standard tests for a tool. Below are the templates for implementing the standard tests for each component:\n", - "\n", - "
      \n", - " Chat Models\n", - "

      Note: The standard tests for chat models are implemented in the example in the main body of this guide too.

      " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/unit_tests/test_chat_models.py\"\n", - "from typing import Type\n", - "\n", - "from langchain_parrot_link.chat_models import ChatParrotLink\n", - "from langchain_tests.unit_tests import ChatModelUnitTests\n", - "\n", - "\n", - "class TestChatParrotLinkUnit(ChatModelUnitTests):\n", - " @property\n", - " def chat_model_class(self) -> Type[ChatParrotLink]:\n", - " return ChatParrotLink\n", - "\n", - " @property\n", - " def chat_model_params(self) -> dict:\n", - " return {\n", - " \"model\": \"bird-brain-001\",\n", - " \"temperature\": 0,\n", - " \"parrot_buffer_length\": 50,\n", - " }" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/integration_tests/test_chat_models.py\"\n", - "from typing import Type\n", - "\n", - "from langchain_parrot_link.chat_models import ChatParrotLink\n", - "from langchain_tests.integration_tests import ChatModelIntegrationTests\n", - "\n", - "\n", - "class TestChatParrotLinkIntegration(ChatModelIntegrationTests):\n", - " @property\n", - " def chat_model_class(self) -> Type[ChatParrotLink]:\n", - " return ChatParrotLink\n", - "\n", - " @property\n", - " def chat_model_params(self) -> dict:\n", - " return {\n", - " \"model\": \"bird-brain-001\",\n", - " \"temperature\": 0,\n", - " \"parrot_buffer_length\": 50,\n", - " }" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
      \n", - "
      \n", - " Embedding Models" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/unit_tests/test_embeddings.py\"\n", - "from typing import Tuple, Type\n", - "\n", - "from langchain_parrot_link.embeddings import ParrotLinkEmbeddings\n", - "from langchain_tests.unit_tests import EmbeddingsUnitTests\n", - "\n", - "\n", - "class TestParrotLinkEmbeddingsUnit(EmbeddingsUnitTests):\n", - " @property\n", - " def embeddings_class(self) -> Type[ParrotLinkEmbeddings]:\n", - " return ParrotLinkEmbeddings\n", - "\n", - " @property\n", - " def embedding_model_params(self) -> dict:\n", - " return {\"model\": \"nest-embed-001\", \"temperature\": 0}" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/integration_tests/test_embeddings.py\"\n", - "from typing import Type\n", - "\n", - "from langchain_parrot_link.embeddings import ParrotLinkEmbeddings\n", - "from langchain_tests.integration_tests import EmbeddingsIntegrationTests\n", - "\n", - "\n", - "class TestParrotLinkEmbeddingsIntegration(EmbeddingsIntegrationTests):\n", - " @property\n", - " def embeddings_class(self) -> Type[ParrotLinkEmbeddings]:\n", - " return ParrotLinkEmbeddings\n", - "\n", - " @property\n", - " def embedding_model_params(self) -> dict:\n", - " return {\"model\": \"nest-embed-001\", \"temperature\": 0}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
      \n", - "
      \n", - " Tools/Toolkits" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/unit_tests/test_tools.py\"\n", - "from typing import Type\n", - "\n", - "from langchain_parrot_link.tools import ParrotMultiplyTool\n", - "from langchain_tests.unit_tests import ToolsUnitTests\n", - "\n", - "\n", - "class TestParrotMultiplyToolUnit(ToolsUnitTests):\n", - " @property\n", - " def tool_constructor(self) -> Type[ParrotMultiplyTool]:\n", - " return ParrotMultiplyTool\n", - "\n", - " @property\n", - " def tool_constructor_params(self) -> dict:\n", - " # if your tool constructor instead required initialization arguments like\n", - " # `def __init__(self, some_arg: int):`, you would return those here\n", - " # as a dictionary, e.g.: `return {'some_arg': 42}`\n", - " return {}\n", - "\n", - " @property\n", - " def tool_invoke_params_example(self) -> dict:\n", - " \"\"\"\n", - " Returns a dictionary representing the \"args\" of an example tool call.\n", - "\n", - " This should NOT be a ToolCall dict - i.e. it should not\n", - " have {\"name\", \"id\", \"args\"} keys.\n", - " \"\"\"\n", - " return {\"a\": 2, \"b\": 3}" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/integration_tests/test_tools.py\"\n", - "from typing import Type\n", - "\n", - "from langchain_parrot_link.tools import ParrotMultiplyTool\n", - "from langchain_tests.integration_tests import ToolsIntegrationTests\n", - "\n", - "\n", - "class TestParrotMultiplyToolIntegration(ToolsIntegrationTests):\n", - " @property\n", - " def tool_constructor(self) -> Type[ParrotMultiplyTool]:\n", - " return ParrotMultiplyTool\n", - "\n", - " @property\n", - " def tool_constructor_params(self) -> dict:\n", - " # if your tool constructor instead required initialization arguments like\n", - " # `def __init__(self, some_arg: int):`, you would return those here\n", - " # as a dictionary, e.g.: `return {'some_arg': 42}`\n", - " return {}\n", - "\n", - " @property\n", - " def tool_invoke_params_example(self) -> dict:\n", - " \"\"\"\n", - " Returns a dictionary representing the \"args\" of an example tool call.\n", - "\n", - " This should NOT be a ToolCall dict - i.e. it should not\n", - " have {\"name\", \"id\", \"args\"} keys.\n", - " \"\"\"\n", - " return {\"a\": 2, \"b\": 3}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
      \n", - "
      \n", - " Vector Stores" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# title=\"tests/integration_tests/test_vectorstores_sync.py\"\n", - "\n", - "from typing import AsyncGenerator, Generator\n", - "\n", - "import pytest\n", - "from langchain_core.vectorstores import VectorStore\n", - "from langchain_parrot_link.vectorstores import ParrotVectorStore\n", - "from langchain_standard_tests.integration_tests.vectorstores import (\n", - " AsyncReadWriteTestSuite,\n", - " ReadWriteTestSuite,\n", - ")\n", - "\n", - "\n", - "class TestSync(ReadWriteTestSuite):\n", - " @pytest.fixture()\n", - " def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore\n", - " \"\"\"Get an empty vectorstore for unit tests.\"\"\"\n", - " store = ParrotVectorStore()\n", - " # note: store should be EMPTY at this point\n", - " # if you need to delete data, you may do so here\n", - " try:\n", - " yield store\n", - " finally:\n", - " # cleanup operations, or deleting data\n", - " pass\n", - "\n", - "\n", - "class TestAsync(AsyncReadWriteTestSuite):\n", - " @pytest.fixture()\n", - " async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore\n", - " \"\"\"Get an empty vectorstore for unit tests.\"\"\"\n", - " store = ParrotVectorStore()\n", - " # note: store should be EMPTY at this point\n", - " # if you need to delete data, you may do so here\n", - " try:\n", - " yield store\n", - " finally:\n", - " # cleanup operations, or deleting data\n", - " pass" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
      " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/docs/contributing/how_to/integrations/standard_tests.mdx b/docs/docs/contributing/how_to/integrations/standard_tests.mdx new file mode 100644 index 0000000000000..5462b966a6404 --- /dev/null +++ b/docs/docs/contributing/how_to/integrations/standard_tests.mdx @@ -0,0 +1,393 @@ +--- +pagination_next: contributing/how_to/integrations/publish +pagination_prev: contributing/how_to/integrations/package +--- +# How to add standard tests to an integration + +When creating either a custom class for yourself or to publish in a LangChain integration, it is important to add standard tests to ensure it works as expected. This guide will show you how to add standard tests to each integration type. + +## Setup + +First, let's install 2 dependencies: + +- `langchain-core` will define the interfaces we want to import to define our custom tool. +- `langchain-tests` will provide the standard tests we want to use, as well as pytest plugins necessary to run them. Recommended to pin to the latest version: + +:::note + +Because added tests in new versions of `langchain-tests` can break your CI/CD pipelines, we recommend pinning the +version of `langchain-tests` to avoid unexpected changes. + +::: + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + + + +If you followed the [previous guide](../package), you should already have these dependencies installed! + +```bash +poetry add langchain-core +poetry add --group test langchain-tests== +poetry install --with test +``` + + +```bash +pip install -U langchain-core langchain-tests + +# install current package in editable mode +pip install --editable . +``` + + + +## Add and configure standard tests + +There are 2 namespaces in the `langchain-tests` package: + +- [unit tests](../../../concepts/testing.mdx#unit-tests) (`langchain_tests.unit_tests`): designed to be used to test the component in isolation and without access to external services +- [integration tests](../../../concepts/testing.mdx#integration-tests) (`langchain_tests.integration_tests`): designed to be used to test the component with access to external services (in particular, the external service that the component is designed to interact with). + +Both types of tests are implemented as [`pytest` class-based test suites](https://docs.pytest.org/en/7.1.x/getting-started.html#group-multiple-tests-in-a-class). + +By subclassing the base classes for each type of standard test (see below), you get all of the standard tests for that type, and you +can override the properties that the test suite uses to configure the tests. + +In order to run the tests in the same way as this guide, we recommend subclassing these +classes in test files under two test subdirectories: + +- `tests/unit_tests` for unit tests +- `tests/integration_tests` for integration tests + +### Implementing standard tests + +import CodeBlock from '@theme/CodeBlock'; + +In the following tabs, we show how to implement the standard tests for +each component type: + + + + + +To configure standard tests for a chat model, we subclass `ChatModelUnitTests` and `ChatModelIntegrationTests`. On each subclass, we override the following `@property` methods to specify the chat model to be tested and the chat model's configuration: + +| Property | Description | +| --- | --- | +| `chat_model_class` | The class for the chat model to be tested | +| `chat_model_params` | The parameters to pass to the chat +model's constructor | + +Additionally, chat model standard tests test a range of behaviors, from the most basic requirements (generating a response to a query) to optional capabilities like multi-modal support and tool-calling. For a test run to be successful: + +1. If a feature is intended to be supported by the model, it should pass; +2. If a feature is not intended to be supported by the model, it should be skipped. + +Tests for "optional" capabilities are controlled via a set of properties that can be overridden on the test model subclass. + +You can see the **entire list of configurable capabilities** in the API references for +[unit tests](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelUnitTests.html) +and [integration tests](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.chat_models.ChatModelIntegrationTests.html). + +For example, to enable integration tests for image inputs, we can implement + +```python +@property +def supports_image_inputs(self) -> bool: + return True +``` + +on the integration test class. + +:::note + +Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details: + +- [Unit tests API reference](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelUnitTests.html) +- [Integration tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.chat_models.ChatModelIntegrationTests.html) + +::: + +Unit test example: + +import ChatUnitSource from '../../../../src/theme/integration_template/tests/unit_tests/test_chat_models.py'; + + +{ + ChatUnitSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + +Integration test example: + + +import ChatIntegrationSource from '../../../../src/theme/integration_template/tests/integration_tests/test_chat_models.py'; + + +{ + ChatIntegrationSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + + + + + +Here's how you would configure the standard tests for a typical vector store (using +`ParrotVectorStore` as a placeholder): + +Vector store tests do not have optional capabilities to be configured at this time. + +import VectorStoreIntegrationSource from '../../../../src/theme/integration_template/tests/integration_tests/test_vectorstores.py'; + + +{ + VectorStoreIntegrationSource.replaceAll('__ModuleName__', 'Parrot') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + +Configuring the tests consists of implementing pytest fixtures for setting up an +empty vector store and tearing down the vector store after the test run ends. + +| Fixture | Description | +| --- | --- | +| `vectorstore` | A generator that yields an empty vector store for unit tests. The vector store is cleaned up after the test run ends. | + +For example, below is the `VectorStoreIntegrationTests` class for the [Chroma](https://python.langchain.com/docs/integrations/vectorstores/chroma/) +integration: + +```python +from typing import Generator + +import pytest +from langchain_core.vectorstores import VectorStore +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests + +from langchain_chroma import Chroma + + +class TestChromaStandard(VectorStoreIntegrationTests): + @pytest.fixture() + def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore + """Get an empty vectorstore for unit tests.""" + store = Chroma(embedding_function=self.get_embeddings()) + try: + yield store + finally: + store.delete_collection() + pass + +``` + +Note that before the initial `yield`, we instantiate the vector store with an +[embeddings](/docs/concepts/embedding_models/) object. This is a pre-defined +["fake" embeddings model](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.VectorStoreIntegrationTests.html#langchain_tests.integration_tests.vectorstores.VectorStoreIntegrationTests.get_embeddings) +that will generate short, arbitrary vectors for documents. You can use a different +embeddings object if desired. + +In the `finally` block, we call whatever integration-specific logic is needed to +bring the vector store to a clean state. This logic is executed in between each test +(e.g., even if tests fail). + +:::note + +Details on what tests are run and troubleshooting tips for each test can be found in the [API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.VectorStoreIntegrationTests.html). + +::: + + + + + +To configure standard tests for an embeddings model, we subclass `EmbeddingsUnitTests` and `EmbeddingsIntegrationTests`. On each subclass, we override the following `@property` methods to specify the embeddings model to be tested and the embeddings model's configuration: + +| Property | Description | +| --- | --- | +| `embeddings_class` | The class for the embeddings model to be tested | +| `embedding_model_params` | The parameters to pass to the embeddings model's constructor | + +:::note + +Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details: + +- [Unit tests API reference](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.embeddings.EmbeddingsUnitTests.html) +- [Integration tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.embeddings.EmbeddingsIntegrationTests.html) + +::: + +Unit test example: + +import EmbeddingsUnitSource from '../../../../src/theme/integration_template/tests/unit_tests/test_embeddings.py'; + + +{ + EmbeddingsUnitSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + +Integration test example: + + +```python title="tests/integration_tests/test_embeddings.py" +from typing import Type + +from langchain_parrot_link.embeddings import ParrotLinkEmbeddings +from langchain_tests.integration_tests import EmbeddingsIntegrationTests + + +class TestParrotLinkEmbeddingsIntegration(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[ParrotLinkEmbeddings]: + return ParrotLinkEmbeddings + + @property + def embedding_model_params(self) -> dict: + return {"model": "nest-embed-001"} +``` + +import EmbeddingsIntegrationSource from '../../../../src/theme/integration_template/tests/integration_tests/test_embeddings.py'; + + +{ + EmbeddingsIntegrationSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + + + + +To configure standard tests for a tool, we subclass `ToolsUnitTests` and +`ToolsIntegrationTests`. On each subclass, we override the following `@property` methods +to specify the tool to be tested and the tool's configuration: + +| Property | Description | +| --- | --- | +| `tool_constructor` | The constructor for the tool to be tested, or an instantiated tool. | +| `tool_constructor_params` | The parameters to pass to the tool (optional). | +| `tool_invoke_params_example` | An example of the parameters to pass to the tool's `invoke` method. | + +If you are testing a tool class and pass a class like `MyTool` to `tool_constructor`, you can pass the parameters to the constructor in `tool_constructor_params`. + +If you are testing an instantiated tool, you can pass the instantiated tool to `tool_constructor` and do not +override `tool_constructor_params`. + +:::note + +Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details: + +- [Unit tests API reference](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.tools.ToolsUnitTests.html) +- [Integration tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.tools.ToolsIntegrationTests.html) + +::: + +import ToolsUnitSource from '../../../../src/theme/integration_template/tests/unit_tests/test_tools.py'; + + +{ + ToolsUnitSource.replaceAll('__ModuleName__', 'Parrot') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + +import ToolsIntegrationSource from '../../../../src/theme/integration_template/tests/integration_tests/test_tools.py'; + + +{ + ToolsIntegrationSource.replaceAll('__ModuleName__', 'Parrot') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + + + + + +To configure standard tests for a retriever, we subclass `RetrieversUnitTests` and +`RetrieversIntegrationTests`. On each subclass, we override the following `@property` methods + +| Property | Description | +| --- | --- | +| `retriever_constructor` | The class for the retriever to be tested | +| `retriever_constructor_params` | The parameters to pass to the retriever's constructor | +| `retriever_query_example` | An example of the query to pass to the retriever's `invoke` method | + +:::note + +Details on what tests are run and troubleshooting tips for each test can be found in the [API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.retrievers.RetrieversIntegrationTests.html). + +::: + +import RetrieverIntegrationSource from '../../../../src/theme/integration_template/tests/integration_tests/test_retrievers.py'; + + +{ + RetrieverIntegrationSource.replaceAll('__ModuleName__', 'Parrot') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT') + .replaceAll('__module_name__', 'langchain_parrot_link') +} + + + + + +--- + +### Running the tests + +You can run these with the following commands from your project root + + + + +```bash +# run unit tests without network access +poetry run pytest --disable-socket --allow-unix-socket --asyncio-mode=auto tests/unit_tests + +# run integration tests +poetry run pytest --asyncio-mode=auto tests/integration_tests +``` + + + + +```bash +# run unit tests without network access +pytest --disable-socket --allow-unix-socket --asyncio-mode=auto tests/unit_tests + +# run integration tests +pytest --asyncio-mode=auto tests/integration_tests +``` + + + + +## Test suite information and troubleshooting + +For a full list of the standard test suites that are available, as well as +information on which tests are included and how to troubleshoot common issues, +see the [Standard Tests API Reference](https://python.langchain.com/api_reference/standard_tests/index.html). + +You can see troubleshooting guides under the individual test suites listed in that API Reference. For example, +[here is the guide for `ChatModelIntegrationTests.test_usage_metadata`](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.chat_models.ChatModelIntegrationTests.html#langchain_tests.integration_tests.chat_models.ChatModelIntegrationTests.test_usage_metadata). diff --git a/docs/docs/how_to/agent_executor.ipynb b/docs/docs/how_to/agent_executor.ipynb index c52c126a066c3..3c9ab38bcdf0e 100644 --- a/docs/docs/how_to/agent_executor.ipynb +++ b/docs/docs/how_to/agent_executor.ipynb @@ -802,7 +802,7 @@ "That's a wrap! In this quick start we covered how to create a simple agent. Agents are a complex topic, and there's lot to learn! \n", "\n", ":::important\n", - "This section covered building with LangChain Agents. LangChain Agents are fine for getting started, but past a certain point you will likely want flexibility and control that they do not offer. For working with more advanced agents, we'd reccommend checking out [LangGraph](/docs/concepts/architecture/#langgraph)\n", + "This section covered building with LangChain Agents. They are fine for getting started, but past a certain point you will likely want flexibility and control which they do not offer. To develop more advanced agents, we recommend checking out [LangGraph](/docs/concepts/architecture/#langgraph)\n", ":::\n", "\n", "If you want to continue using LangChain agents, some good advanced guides are:\n", diff --git a/docs/docs/how_to/custom_tools.ipynb b/docs/docs/how_to/custom_tools.ipynb index 8046b7b00e4a4..8becb03c7c91c 100644 --- a/docs/docs/how_to/custom_tools.ipynb +++ b/docs/docs/how_to/custom_tools.ipynb @@ -162,7 +162,7 @@ "\n", "@tool\n", "def multiply_by_max(\n", - " a: Annotated[str, \"scale factor\"],\n", + " a: Annotated[int, \"scale factor\"],\n", " b: Annotated[List[int], \"list of ints over which to take maximum\"],\n", ") -> int:\n", " \"\"\"Multiply a by the maximum of b.\"\"\"\n", @@ -294,7 +294,7 @@ "metadata": {}, "source": [ ":::caution\n", - "By default, `@tool(parse_docstring=True)` will raise `ValueError` if the docstring does not parse correctly. See [API Reference](https://python.langchain.com/api_reference/core/tools/langchain_core.tools.tool.html) for detail and examples.\n", + "By default, `@tool(parse_docstring=True)` will raise `ValueError` if the docstring does not parse correctly. See [API Reference](https://python.langchain.com/api_reference/core/tools/langchain_core.tools.convert.tool.html) for detail and examples.\n", ":::" ] }, diff --git a/docs/docs/how_to/graph_constructing.ipynb b/docs/docs/how_to/graph_constructing.ipynb index 5ca45d736453f..d036720b674a6 100644 --- a/docs/docs/how_to/graph_constructing.ipynb +++ b/docs/docs/how_to/graph_constructing.ipynb @@ -52,7 +52,7 @@ } ], "source": [ - "%pip install --upgrade --quiet langchain langchain-community langchain-openai langchain-experimental neo4j" + "%pip install --upgrade --quiet langchain langchain-neo4j langchain-openai langchain-experimental neo4j" ] }, { @@ -102,7 +102,7 @@ "source": [ "import os\n", "\n", - "from langchain_community.graphs import Neo4jGraph\n", + "from langchain_neo4j import Neo4jGraph\n", "\n", "os.environ[\"NEO4J_URI\"] = \"bolt://localhost:7687\"\n", "os.environ[\"NEO4J_USERNAME\"] = \"neo4j\"\n", @@ -245,7 +245,7 @@ " allowed_nodes=[\"Person\", \"Country\", \"Organization\"],\n", " allowed_relationships=allowed_relationships,\n", ")\n", - "llm_transformer_tuple = llm_transformer_filtered.convert_to_graph_documents(documents)\n", + "graph_documents_filtered = llm_transformer_tuple.convert_to_graph_documents(documents)\n", "print(f\"Nodes:{graph_documents_filtered[0].nodes}\")\n", "print(f\"Relationships:{graph_documents_filtered[0].relationships}\")" ] diff --git a/docs/docs/how_to/graph_mapping.ipynb b/docs/docs/how_to/graph_mapping.ipynb deleted file mode 100644 index cd98ca00b67a3..0000000000000 --- a/docs/docs/how_to/graph_mapping.ipynb +++ /dev/null @@ -1,458 +0,0 @@ -{ - "cells": [ - { - "cell_type": "raw", - "id": "5e61b0f2-15b9-4241-9ab5-ff0f3f732232", - "metadata": {}, - "source": [ - "---\n", - "sidebar_position: 1\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "846ef4f4-ee38-4a42-a7d3-1a23826e4830", - "metadata": {}, - "source": [ - "# How to map values to a graph database\n", - "\n", - "In this guide we'll go over strategies to improve graph database query generation by mapping values from user inputs to database.\n", - "When using the built-in graph chains, the LLM is aware of the graph schema, but has no information about the values of properties stored in the database.\n", - "Therefore, we can introduce a new step in graph database QA system to accurately map values.\n", - "\n", - "## Setup\n", - "\n", - "First, get required packages and set environment variables:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "18294435-182d-48da-bcab-5b8945b6d9cf", - "metadata": {}, - "outputs": [], - "source": [ - "%pip install --upgrade --quiet langchain langchain-community langchain-openai neo4j" - ] - }, - { - "cell_type": "markdown", - "id": "d86dd771-4001-4a34-8680-22e9b50e1e88", - "metadata": {}, - "source": [ - "We default to OpenAI models in this guide, but you can swap them out for the model provider of your choice." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "9346f8e9-78bf-4667-b3d3-72807a73b718", - "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - " ········\n" - ] - } - ], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()\n", - "\n", - "# Uncomment the below to use LangSmith. Not required.\n", - "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", - "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"" - ] - }, - { - "cell_type": "markdown", - "id": "271c8a23-e51c-4ead-a76e-cf21107db47e", - "metadata": {}, - "source": [ - "Next, we need to define Neo4j credentials.\n", - "Follow [these installation steps](https://neo4j.com/docs/operations-manual/current/installation/) to set up a Neo4j database." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a2a3bb65-05c7-4daf-bac2-b25ae7fe2751", - "metadata": {}, - "outputs": [], - "source": [ - "os.environ[\"NEO4J_URI\"] = \"bolt://localhost:7687\"\n", - "os.environ[\"NEO4J_USERNAME\"] = \"neo4j\"\n", - "os.environ[\"NEO4J_PASSWORD\"] = \"password\"" - ] - }, - { - "cell_type": "markdown", - "id": "50fa4510-29b7-49b6-8496-5e86f694e81f", - "metadata": {}, - "source": [ - "The below example will create a connection with a Neo4j database and will populate it with example data about movies and their actors." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "4ee9ef7a-eef9-4289-b9fd-8fbc31041688", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from langchain_community.graphs import Neo4jGraph\n", - "\n", - "graph = Neo4jGraph()\n", - "\n", - "# Import movie information\n", - "\n", - "movies_query = \"\"\"\n", - "LOAD CSV WITH HEADERS FROM \n", - "'https://raw.githubusercontent.com/tomasonjo/blog-datasets/main/movies/movies_small.csv'\n", - "AS row\n", - "MERGE (m:Movie {id:row.movieId})\n", - "SET m.released = date(row.released),\n", - " m.title = row.title,\n", - " m.imdbRating = toFloat(row.imdbRating)\n", - "FOREACH (director in split(row.director, '|') | \n", - " MERGE (p:Person {name:trim(director)})\n", - " MERGE (p)-[:DIRECTED]->(m))\n", - "FOREACH (actor in split(row.actors, '|') | \n", - " MERGE (p:Person {name:trim(actor)})\n", - " MERGE (p)-[:ACTED_IN]->(m))\n", - "FOREACH (genre in split(row.genres, '|') | \n", - " MERGE (g:Genre {name:trim(genre)})\n", - " MERGE (m)-[:IN_GENRE]->(g))\n", - "\"\"\"\n", - "\n", - "graph.query(movies_query)" - ] - }, - { - "cell_type": "markdown", - "id": "0cb0ea30-ca55-4f35-aad6-beb57453de66", - "metadata": {}, - "source": [ - "## Detecting entities in the user input\n", - "We have to extract the types of entities/values we want to map to a graph database. In this example, we are dealing with a movie graph, so we can map movies and people to the database." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "e1a19424-6046-40c2-81d1-f3b88193a293", - "metadata": {}, - "outputs": [], - "source": [ - "from typing import List, Optional\n", - "\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_openai import ChatOpenAI\n", - "from pydantic import BaseModel, Field\n", - "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n", - "\n", - "\n", - "class Entities(BaseModel):\n", - " \"\"\"Identifying information about entities.\"\"\"\n", - "\n", - " names: List[str] = Field(\n", - " ...,\n", - " description=\"All the person or movies appearing in the text\",\n", - " )\n", - "\n", - "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\n", - " \"system\",\n", - " \"You are extracting person and movies from the text.\",\n", - " ),\n", - " (\n", - " \"human\",\n", - " \"Use the given format to extract information from the following \"\n", - " \"input: {question}\",\n", - " ),\n", - " ]\n", - ")\n", - "\n", - "\n", - "entity_chain = prompt | llm.with_structured_output(Entities)" - ] - }, - { - "cell_type": "markdown", - "id": "9c14084c-37a7-4a9c-a026-74e12961c781", - "metadata": {}, - "source": [ - "We can test the entity extraction chain." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "bbfe0d8f-982e-46e6-88fb-8a4f0d850b07", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Entities(names=['Casino'])" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "entities = entity_chain.invoke({\"question\": \"Who played in Casino movie?\"})\n", - "entities" - ] - }, - { - "cell_type": "markdown", - "id": "a8afbf13-05d0-4383-8050-f88b8c2f6fab", - "metadata": {}, - "source": [ - "We will utilize a simple `CONTAINS` clause to match entities to database. In practice, you might want to use a fuzzy search or a fulltext index to allow for minor misspellings." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "6f92929f-74fb-4db2-b7e1-eb1e9d386a67", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Casino maps to Casino Movie in database\\n'" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "match_query = \"\"\"MATCH (p:Person|Movie)\n", - "WHERE p.name CONTAINS $value OR p.title CONTAINS $value\n", - "RETURN coalesce(p.name, p.title) AS result, labels(p)[0] AS type\n", - "LIMIT 1\n", - "\"\"\"\n", - "\n", - "\n", - "def map_to_database(entities: Entities) -> Optional[str]:\n", - " result = \"\"\n", - " for entity in entities.names:\n", - " response = graph.query(match_query, {\"value\": entity})\n", - " try:\n", - " result += f\"{entity} maps to {response[0]['result']} {response[0]['type']} in database\\n\"\n", - " except IndexError:\n", - " pass\n", - " return result\n", - "\n", - "\n", - "map_to_database(entities)" - ] - }, - { - "cell_type": "markdown", - "id": "f66c6756-6efb-4b1e-9b5d-87ed914a5212", - "metadata": {}, - "source": [ - "## Custom Cypher generating chain\n", - "\n", - "We need to define a custom Cypher prompt that takes the entity mapping information along with the schema and the user question to construct a Cypher statement.\n", - "We will be using the LangChain expression language to accomplish that." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "8ef3e21d-f1c2-45e2-9511-4920d1cf6e7e", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "\n", - "# Generate Cypher statement based on natural language input\n", - "cypher_template = \"\"\"Based on the Neo4j graph schema below, write a Cypher query that would answer the user's question:\n", - "{schema}\n", - "Entities in the question map to the following database values:\n", - "{entities_list}\n", - "Question: {question}\n", - "Cypher query:\"\"\"\n", - "\n", - "cypher_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\n", - " \"system\",\n", - " \"Given an input question, convert it to a Cypher query. No pre-amble.\",\n", - " ),\n", - " (\"human\", cypher_template),\n", - " ]\n", - ")\n", - "\n", - "cypher_response = (\n", - " RunnablePassthrough.assign(names=entity_chain)\n", - " | RunnablePassthrough.assign(\n", - " entities_list=lambda x: map_to_database(x[\"names\"]),\n", - " schema=lambda _: graph.get_schema,\n", - " )\n", - " | cypher_prompt\n", - " | llm.bind(stop=[\"\\nCypherResult:\"])\n", - " | StrOutputParser()\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "1f0011e3-9660-4975-af2a-486b1bc3b954", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'MATCH (:Movie {title: \"Casino\"})<-[:ACTED_IN]-(actor)\\nRETURN actor.name'" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cypher = cypher_response.invoke({\"question\": \"Who played in Casino movie?\"})\n", - "cypher" - ] - }, - { - "cell_type": "markdown", - "id": "38095678-611f-4847-a4de-e51ef7ef727c", - "metadata": {}, - "source": [ - "## Generating answers based on database results\n", - "\n", - "Now that we have a chain that generates the Cypher statement, we need to execute the Cypher statement against the database and send the database results back to an LLM to generate the final answer.\n", - "Again, we will be using LCEL." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "d1fa97c0-1c9c-41d3-9ee1-5f1905d17434", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_community.chains.graph_qa.cypher_utils import (\n", - " CypherQueryCorrector,\n", - " Schema,\n", - ")\n", - "\n", - "# Cypher validation tool for relationship directions\n", - "corrector_schema = [\n", - " Schema(el[\"start\"], el[\"type\"], el[\"end\"])\n", - " for el in graph.structured_schema.get(\"relationships\")\n", - "]\n", - "cypher_validation = CypherQueryCorrector(corrector_schema)\n", - "\n", - "# Generate natural language response based on database results\n", - "response_template = \"\"\"Based on the the question, Cypher query, and Cypher response, write a natural language response:\n", - "Question: {question}\n", - "Cypher query: {query}\n", - "Cypher Response: {response}\"\"\"\n", - "\n", - "response_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\n", - " \"system\",\n", - " \"Given an input question and Cypher response, convert it to a natural\"\n", - " \" language answer. No pre-amble.\",\n", - " ),\n", - " (\"human\", response_template),\n", - " ]\n", - ")\n", - "\n", - "chain = (\n", - " RunnablePassthrough.assign(query=cypher_response)\n", - " | RunnablePassthrough.assign(\n", - " response=lambda x: graph.query(cypher_validation(x[\"query\"])),\n", - " )\n", - " | response_prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "918146e5-7918-46d2-a774-53f9547d8fcb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Robert De Niro, James Woods, Joe Pesci, and Sharon Stone played in the movie \"Casino\".'" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chain.invoke({\"question\": \"Who played in Casino movie?\"})" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c7ba75cd-8399-4e54-a6f8-8a411f159f56", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.18" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/docs/how_to/graph_prompting.ipynb b/docs/docs/how_to/graph_prompting.ipynb deleted file mode 100644 index 0b83559e7e195..0000000000000 --- a/docs/docs/how_to/graph_prompting.ipynb +++ /dev/null @@ -1,540 +0,0 @@ -{ - "cells": [ - { - "cell_type": "raw", - "metadata": {}, - "source": [ - "---\n", - "sidebar_position: 2\n", - "---" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# How to best prompt for Graph-RAG\n", - "\n", - "In this guide we'll go over prompting strategies to improve graph database query generation. We'll largely focus on methods for getting relevant database-specific information in your prompt.\n", - "\n", - "## Setup\n", - "\n", - "First, get required packages and set environment variables:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], - "source": [ - "%pip install --upgrade --quiet langchain langchain-community langchain-openai neo4j" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We default to OpenAI models in this guide, but you can swap them out for the model provider of your choice." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - " ········\n" - ] - } - ], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()\n", - "\n", - "# Uncomment the below to use LangSmith. Not required.\n", - "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", - "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Next, we need to define Neo4j credentials.\n", - "Follow [these installation steps](https://neo4j.com/docs/operations-manual/current/installation/) to set up a Neo4j database." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "os.environ[\"NEO4J_URI\"] = \"bolt://localhost:7687\"\n", - "os.environ[\"NEO4J_USERNAME\"] = \"neo4j\"\n", - "os.environ[\"NEO4J_PASSWORD\"] = \"password\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The below example will create a connection with a Neo4j database and will populate it with example data about movies and their actors." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from langchain_community.graphs import Neo4jGraph\n", - "\n", - "graph = Neo4jGraph()\n", - "\n", - "# Import movie information\n", - "\n", - "movies_query = \"\"\"\n", - "LOAD CSV WITH HEADERS FROM \n", - "'https://raw.githubusercontent.com/tomasonjo/blog-datasets/main/movies/movies_small.csv'\n", - "AS row\n", - "MERGE (m:Movie {id:row.movieId})\n", - "SET m.released = date(row.released),\n", - " m.title = row.title,\n", - " m.imdbRating = toFloat(row.imdbRating)\n", - "FOREACH (director in split(row.director, '|') | \n", - " MERGE (p:Person {name:trim(director)})\n", - " MERGE (p)-[:DIRECTED]->(m))\n", - "FOREACH (actor in split(row.actors, '|') | \n", - " MERGE (p:Person {name:trim(actor)})\n", - " MERGE (p)-[:ACTED_IN]->(m))\n", - "FOREACH (genre in split(row.genres, '|') | \n", - " MERGE (g:Genre {name:trim(genre)})\n", - " MERGE (m)-[:IN_GENRE]->(g))\n", - "\"\"\"\n", - "\n", - "graph.query(movies_query)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Filtering graph schema\n", - "\n", - "At times, you may need to focus on a specific subset of the graph schema while generating Cypher statements.\n", - "Let's say we are dealing with the following graph schema:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node properties are the following:\n", - "Movie {imdbRating: FLOAT, id: STRING, released: DATE, title: STRING},Person {name: STRING},Genre {name: STRING}\n", - "Relationship properties are the following:\n", - "\n", - "The relationships are the following:\n", - "(:Movie)-[:IN_GENRE]->(:Genre),(:Person)-[:DIRECTED]->(:Movie),(:Person)-[:ACTED_IN]->(:Movie)\n" - ] - } - ], - "source": [ - "graph.refresh_schema()\n", - "print(graph.schema)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's say we want to exclude the _Genre_ node from the schema representation we pass to an LLM.\n", - "We can achieve that using the `exclude` parameter of the GraphCypherQAChain chain." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from langchain.chains import GraphCypherQAChain\n", - "from langchain_openai import ChatOpenAI\n", - "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n", - "chain = GraphCypherQAChain.from_llm(\n", - " graph=graph, llm=llm, exclude_types=[\"Genre\"], verbose=True\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node properties are the following:\n", - "Movie {imdbRating: FLOAT, id: STRING, released: DATE, title: STRING},Person {name: STRING}\n", - "Relationship properties are the following:\n", - "\n", - "The relationships are the following:\n", - "(:Person)-[:DIRECTED]->(:Movie),(:Person)-[:ACTED_IN]->(:Movie)\n" - ] - } - ], - "source": [ - "print(chain.graph_schema)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Few-shot examples\n", - "\n", - "Including examples of natural language questions being converted to valid Cypher queries against our database in the prompt will often improve model performance, especially for complex queries.\n", - "\n", - "Let's say we have the following examples:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "examples = [\n", - " {\n", - " \"question\": \"How many artists are there?\",\n", - " \"query\": \"MATCH (a:Person)-[:ACTED_IN]->(:Movie) RETURN count(DISTINCT a)\",\n", - " },\n", - " {\n", - " \"question\": \"Which actors played in the movie Casino?\",\n", - " \"query\": \"MATCH (m:Movie {{title: 'Casino'}})<-[:ACTED_IN]-(a) RETURN a.name\",\n", - " },\n", - " {\n", - " \"question\": \"How many movies has Tom Hanks acted in?\",\n", - " \"query\": \"MATCH (a:Person {{name: 'Tom Hanks'}})-[:ACTED_IN]->(m:Movie) RETURN count(m)\",\n", - " },\n", - " {\n", - " \"question\": \"List all the genres of the movie Schindler's List\",\n", - " \"query\": \"MATCH (m:Movie {{title: 'Schindler\\\\'s List'}})-[:IN_GENRE]->(g:Genre) RETURN g.name\",\n", - " },\n", - " {\n", - " \"question\": \"Which actors have worked in movies from both the comedy and action genres?\",\n", - " \"query\": \"MATCH (a:Person)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g1:Genre), (a)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g2:Genre) WHERE g1.name = 'Comedy' AND g2.name = 'Action' RETURN DISTINCT a.name\",\n", - " },\n", - " {\n", - " \"question\": \"Which directors have made movies with at least three different actors named 'John'?\",\n", - " \"query\": \"MATCH (d:Person)-[:DIRECTED]->(m:Movie)<-[:ACTED_IN]-(a:Person) WHERE a.name STARTS WITH 'John' WITH d, COUNT(DISTINCT a) AS JohnsCount WHERE JohnsCount >= 3 RETURN d.name\",\n", - " },\n", - " {\n", - " \"question\": \"Identify movies where directors also played a role in the film.\",\n", - " \"query\": \"MATCH (p:Person)-[:DIRECTED]->(m:Movie), (p)-[:ACTED_IN]->(m) RETURN m.title, p.name\",\n", - " },\n", - " {\n", - " \"question\": \"Find the actor with the highest number of movies in the database.\",\n", - " \"query\": \"MATCH (a:Actor)-[:ACTED_IN]->(m:Movie) RETURN a.name, COUNT(m) AS movieCount ORDER BY movieCount DESC LIMIT 1\",\n", - " },\n", - "]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can create a few-shot prompt with them like so:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_core.prompts import FewShotPromptTemplate, PromptTemplate\n", - "\n", - "example_prompt = PromptTemplate.from_template(\n", - " \"User input: {question}\\nCypher query: {query}\"\n", - ")\n", - "prompt = FewShotPromptTemplate(\n", - " examples=examples[:5],\n", - " example_prompt=example_prompt,\n", - " prefix=\"You are a Neo4j expert. Given an input question, create a syntactically correct Cypher query to run.\\n\\nHere is the schema information\\n{schema}.\\n\\nBelow are a number of examples of questions and their corresponding Cypher queries.\",\n", - " suffix=\"User input: {question}\\nCypher query: \",\n", - " input_variables=[\"question\", \"schema\"],\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You are a Neo4j expert. Given an input question, create a syntactically correct Cypher query to run.\n", - "\n", - "Here is the schema information\n", - "foo.\n", - "\n", - "Below are a number of examples of questions and their corresponding Cypher queries.\n", - "\n", - "User input: How many artists are there?\n", - "Cypher query: MATCH (a:Person)-[:ACTED_IN]->(:Movie) RETURN count(DISTINCT a)\n", - "\n", - "User input: Which actors played in the movie Casino?\n", - "Cypher query: MATCH (m:Movie {title: 'Casino'})<-[:ACTED_IN]-(a) RETURN a.name\n", - "\n", - "User input: How many movies has Tom Hanks acted in?\n", - "Cypher query: MATCH (a:Person {name: 'Tom Hanks'})-[:ACTED_IN]->(m:Movie) RETURN count(m)\n", - "\n", - "User input: List all the genres of the movie Schindler's List\n", - "Cypher query: MATCH (m:Movie {title: 'Schindler\\'s List'})-[:IN_GENRE]->(g:Genre) RETURN g.name\n", - "\n", - "User input: Which actors have worked in movies from both the comedy and action genres?\n", - "Cypher query: MATCH (a:Person)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g1:Genre), (a)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g2:Genre) WHERE g1.name = 'Comedy' AND g2.name = 'Action' RETURN DISTINCT a.name\n", - "\n", - "User input: How many artists are there?\n", - "Cypher query: \n" - ] - } - ], - "source": [ - "print(prompt.format(question=\"How many artists are there?\", schema=\"foo\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Dynamic few-shot examples\n", - "\n", - "If we have enough examples, we may want to only include the most relevant ones in the prompt, either because they don't fit in the model's context window or because the long tail of examples distracts the model. And specifically, given any input we want to include the examples most relevant to that input.\n", - "\n", - "We can do just this using an ExampleSelector. In this case we'll use a [SemanticSimilarityExampleSelector](https://python.langchain.com/api_reference/core/example_selectors/langchain_core.example_selectors.semantic_similarity.SemanticSimilarityExampleSelector.html), which will store the examples in the vector database of our choosing. At runtime it will perform a similarity search between the input and our examples, and return the most semantically similar ones: " - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_community.vectorstores import Neo4jVector\n", - "from langchain_core.example_selectors import SemanticSimilarityExampleSelector\n", - "from langchain_openai import OpenAIEmbeddings\n", - "\n", - "example_selector = SemanticSimilarityExampleSelector.from_examples(\n", - " examples,\n", - " OpenAIEmbeddings(),\n", - " Neo4jVector,\n", - " k=5,\n", - " input_keys=[\"question\"],\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[{'query': 'MATCH (a:Person)-[:ACTED_IN]->(:Movie) RETURN count(DISTINCT a)',\n", - " 'question': 'How many artists are there?'},\n", - " {'query': \"MATCH (a:Person {{name: 'Tom Hanks'}})-[:ACTED_IN]->(m:Movie) RETURN count(m)\",\n", - " 'question': 'How many movies has Tom Hanks acted in?'},\n", - " {'query': \"MATCH (a:Person)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g1:Genre), (a)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g2:Genre) WHERE g1.name = 'Comedy' AND g2.name = 'Action' RETURN DISTINCT a.name\",\n", - " 'question': 'Which actors have worked in movies from both the comedy and action genres?'},\n", - " {'query': \"MATCH (d:Person)-[:DIRECTED]->(m:Movie)<-[:ACTED_IN]-(a:Person) WHERE a.name STARTS WITH 'John' WITH d, COUNT(DISTINCT a) AS JohnsCount WHERE JohnsCount >= 3 RETURN d.name\",\n", - " 'question': \"Which directors have made movies with at least three different actors named 'John'?\"},\n", - " {'query': 'MATCH (a:Actor)-[:ACTED_IN]->(m:Movie) RETURN a.name, COUNT(m) AS movieCount ORDER BY movieCount DESC LIMIT 1',\n", - " 'question': 'Find the actor with the highest number of movies in the database.'}]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "example_selector.select_examples({\"question\": \"how many artists are there?\"})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To use it, we can pass the ExampleSelector directly in to our FewShotPromptTemplate:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "prompt = FewShotPromptTemplate(\n", - " example_selector=example_selector,\n", - " example_prompt=example_prompt,\n", - " prefix=\"You are a Neo4j expert. Given an input question, create a syntactically correct Cypher query to run.\\n\\nHere is the schema information\\n{schema}.\\n\\nBelow are a number of examples of questions and their corresponding Cypher queries.\",\n", - " suffix=\"User input: {question}\\nCypher query: \",\n", - " input_variables=[\"question\", \"schema\"],\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You are a Neo4j expert. Given an input question, create a syntactically correct Cypher query to run.\n", - "\n", - "Here is the schema information\n", - "foo.\n", - "\n", - "Below are a number of examples of questions and their corresponding Cypher queries.\n", - "\n", - "User input: How many artists are there?\n", - "Cypher query: MATCH (a:Person)-[:ACTED_IN]->(:Movie) RETURN count(DISTINCT a)\n", - "\n", - "User input: How many movies has Tom Hanks acted in?\n", - "Cypher query: MATCH (a:Person {name: 'Tom Hanks'})-[:ACTED_IN]->(m:Movie) RETURN count(m)\n", - "\n", - "User input: Which actors have worked in movies from both the comedy and action genres?\n", - "Cypher query: MATCH (a:Person)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g1:Genre), (a)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g2:Genre) WHERE g1.name = 'Comedy' AND g2.name = 'Action' RETURN DISTINCT a.name\n", - "\n", - "User input: Which directors have made movies with at least three different actors named 'John'?\n", - "Cypher query: MATCH (d:Person)-[:DIRECTED]->(m:Movie)<-[:ACTED_IN]-(a:Person) WHERE a.name STARTS WITH 'John' WITH d, COUNT(DISTINCT a) AS JohnsCount WHERE JohnsCount >= 3 RETURN d.name\n", - "\n", - "User input: Find the actor with the highest number of movies in the database.\n", - "Cypher query: MATCH (a:Actor)-[:ACTED_IN]->(m:Movie) RETURN a.name, COUNT(m) AS movieCount ORDER BY movieCount DESC LIMIT 1\n", - "\n", - "User input: how many artists are there?\n", - "Cypher query: \n" - ] - } - ], - "source": [ - "print(prompt.format(question=\"how many artists are there?\", schema=\"foo\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n", - "chain = GraphCypherQAChain.from_llm(\n", - " graph=graph, llm=llm, cypher_prompt=prompt, verbose=True\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "\n", - "\u001b[1m> Entering new GraphCypherQAChain chain...\u001b[0m\n", - "Generated Cypher:\n", - "\u001b[32;1m\u001b[1;3mMATCH (a:Person)-[:ACTED_IN]->(:Movie) RETURN count(DISTINCT a)\u001b[0m\n", - "Full Context:\n", - "\u001b[32;1m\u001b[1;3m[{'count(DISTINCT a)': 967}]\u001b[0m\n", - "\n", - "\u001b[1m> Finished chain.\u001b[0m\n" - ] - }, - { - "data": { - "text/plain": [ - "{'query': 'How many actors are in the graph?',\n", - " 'result': 'There are 967 actors in the graph.'}" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chain.invoke(\"How many actors are in the graph?\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/docs/docs/how_to/graph_semantic.ipynb b/docs/docs/how_to/graph_semantic.ipynb index 94578939d7b48..f2832853e1ca0 100644 --- a/docs/docs/how_to/graph_semantic.ipynb +++ b/docs/docs/how_to/graph_semantic.ipynb @@ -31,20 +31,12 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "ffdd48f6-bd05-4e5c-b846-d41183398a55", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], + "outputs": [], "source": [ - "%pip install --upgrade --quiet langchain langchain-community langchain-openai neo4j" + "%pip install --upgrade --quiet langchain langchain-neo4j langchain-openai" ] }, { @@ -57,7 +49,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "eb11c4a8-c00c-4c2d-9309-74a6acfff91c", "metadata": {}, "outputs": [ @@ -91,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "ef59a3af-31a8-4ad8-8eb9-132aca66956e", "metadata": {}, "outputs": [], @@ -111,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "c84b1449-6fcd-4140-b591-cb45e8dce207", "metadata": {}, "outputs": [ @@ -121,15 +113,15 @@ "[]" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from langchain_community.graphs import Neo4jGraph\n", + "from langchain_neo4j import Neo4jGraph\n", "\n", - "graph = Neo4jGraph()\n", + "graph = Neo4jGraph(refresh_schema=False)\n", "\n", "# Import movie information\n", "\n", @@ -170,26 +162,15 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "d1dc1c8c-f343-4024-924b-a8a86cf5f1af", "metadata": {}, "outputs": [], "source": [ - "from typing import Optional, Type\n", - "\n", - "from langchain_core.callbacks import (\n", - " AsyncCallbackManagerForToolRun,\n", - " CallbackManagerForToolRun,\n", - ")\n", - "from langchain_core.tools import BaseTool\n", - "\n", - "# Import things that are needed generically\n", - "from pydantic import BaseModel, Field\n", - "\n", "description_query = \"\"\"\n", "MATCH (m:Movie|Person)\n", "WHERE m.title CONTAINS $candidate OR m.name CONTAINS $candidate\n", - "MATCH (m)-[r:ACTED_IN|HAS_GENRE]-(t)\n", + "MATCH (m)-[r:ACTED_IN|IN_GENRE]-(t)\n", "WITH m, type(r) as type, collect(coalesce(t.name, t.title)) as names\n", "WITH m, type+\": \"+reduce(s=\"\", n IN names | s + n + \", \") as types\n", "WITH m, collect(types) as contexts\n", @@ -220,20 +201,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "f4cde772-0d05-475d-a2f0-b53e1669bd13", "metadata": {}, "outputs": [], "source": [ "from typing import Optional, Type\n", "\n", - "from langchain_core.callbacks import (\n", - " AsyncCallbackManagerForToolRun,\n", - " CallbackManagerForToolRun,\n", - ")\n", "from langchain_core.tools import BaseTool\n", - "\n", - "# Import things that are needed generically\n", "from pydantic import BaseModel, Field\n", "\n", "\n", @@ -242,8 +217,8 @@ "\n", "\n", "class InformationTool(BaseTool):\n", - " name = \"Information\"\n", - " description = (\n", + " name: str = \"Information\"\n", + " description: str = (\n", " \"useful for when you need to answer questions about various actors or movies\"\n", " )\n", " args_schema: Type[BaseModel] = InformationInput\n", @@ -251,7 +226,6 @@ " def _run(\n", " self,\n", " entity: str,\n", - " run_manager: Optional[CallbackManagerForToolRun] = None,\n", " ) -> str:\n", " \"\"\"Use the tool.\"\"\"\n", " return get_information(entity)\n", @@ -259,7 +233,6 @@ " async def _arun(\n", " self,\n", " entity: str,\n", - " run_manager: Optional[AsyncCallbackManagerForToolRun] = None,\n", " ) -> str:\n", " \"\"\"Use the tool asynchronously.\"\"\"\n", " return get_information(entity)" @@ -270,74 +243,103 @@ "id": "ff4820aa-2b57-4558-901f-6d984b326738", "metadata": {}, "source": [ - "## OpenAI Agent\n", + "## LangGraph Agent\n", + "\n", + "We will implement a straightforward ReAct agent using LangGraph.\n", + "\n", + "The agent consists of an LLM and tools step. As we interact with the agent, we will first call the LLM to decide if we should use tools. Then we will run a loop:\n", "\n", - "LangChain expression language makes it very convenient to define an agent to interact with a graph database over the semantic layer." + "If the agent said to take an action (i.e. call tool), we’ll run the tools and pass the results back to the agent.\n", + "If the agent did not ask to run tools, we will finish (respond to the user).\n", + "\n", + "The code implementation is as straightforward as it gets. First we bind the tools to the LLM and define the assistant step." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "6e959ac2-537d-4358-a43b-e3a47f68e1d6", "metadata": {}, "outputs": [], "source": [ - "from typing import List, Tuple\n", - "\n", - "from langchain.agents import AgentExecutor\n", - "from langchain.agents.format_scratchpad import format_to_openai_function_messages\n", - "from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser\n", - "from langchain_core.messages import AIMessage, HumanMessage\n", - "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n", - "from langchain_core.utils.function_calling import convert_to_openai_function\n", + "from langchain_core.messages import HumanMessage, SystemMessage\n", "from langchain_openai import ChatOpenAI\n", + "from langgraph.graph import MessagesState\n", + "\n", + "llm = ChatOpenAI(model=\"gpt-4o\")\n", "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n", "tools = [InformationTool()]\n", + "llm_with_tools = llm.bind_tools(tools)\n", "\n", - "llm_with_tools = llm.bind(functions=[convert_to_openai_function(t) for t in tools])\n", - "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\n", - " \"system\",\n", - " \"You are a helpful assistant that finds information about movies \"\n", - " \" and recommends them. If tools require follow up questions, \"\n", - " \"make sure to ask the user for clarification. Make sure to include any \"\n", - " \"available options that need to be clarified in the follow up questions \"\n", - " \"Do only the things the user specifically requested. \",\n", - " ),\n", - " MessagesPlaceholder(variable_name=\"chat_history\"),\n", - " (\"user\", \"{input}\"),\n", - " MessagesPlaceholder(variable_name=\"agent_scratchpad\"),\n", - " ]\n", + "# System message\n", + "sys_msg = SystemMessage(\n", + " content=\"You are a helpful assistant tasked with finding and explaining relevant information about movies.\"\n", ")\n", "\n", "\n", - "def _format_chat_history(chat_history: List[Tuple[str, str]]):\n", - " buffer = []\n", - " for human, ai in chat_history:\n", - " buffer.append(HumanMessage(content=human))\n", - " buffer.append(AIMessage(content=ai))\n", - " return buffer\n", - "\n", - "\n", - "agent = (\n", - " {\n", - " \"input\": lambda x: x[\"input\"],\n", - " \"chat_history\": lambda x: _format_chat_history(x[\"chat_history\"])\n", - " if x.get(\"chat_history\")\n", - " else [],\n", - " \"agent_scratchpad\": lambda x: format_to_openai_function_messages(\n", - " x[\"intermediate_steps\"]\n", - " ),\n", - " }\n", - " | prompt\n", - " | llm_with_tools\n", - " | OpenAIFunctionsAgentOutputParser()\n", + "# Node\n", + "def assistant(state: MessagesState):\n", + " return {\"messages\": [llm_with_tools.invoke([sys_msg] + state[\"messages\"])]}" + ] + }, + { + "cell_type": "markdown", + "id": "087e745b-6ce6-4f1f-9a52-a6de597971bf", + "metadata": {}, + "source": [ + "Next we define the LangGraph flow." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "6763e87b-a6d2-44ed-9000-7440b51b325f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import Image, display\n", + "from langgraph.graph import END, START, StateGraph\n", + "from langgraph.prebuilt import ToolNode, tools_condition\n", + "\n", + "# Graph\n", + "builder = StateGraph(MessagesState)\n", + "\n", + "# Define nodes: these do the work\n", + "builder.add_node(\"assistant\", assistant)\n", + "builder.add_node(\"tools\", ToolNode(tools))\n", + "\n", + "# Define edges: these determine how the control flow moves\n", + "builder.add_edge(START, \"assistant\")\n", + "builder.add_conditional_edges(\n", + " \"assistant\",\n", + " # If the latest message (result) from assistant is a tool call -> tools_condition routes to tools\n", + " # If the latest message (result) from assistant is a not a tool call -> tools_condition routes to END\n", + " tools_condition,\n", ")\n", + "builder.add_edge(\"tools\", \"assistant\")\n", + "react_graph = builder.compile()\n", "\n", - "agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)" + "# Show\n", + "display(Image(react_graph.get_graph(xray=True).draw_mermaid_png()))" + ] + }, + { + "cell_type": "markdown", + "id": "c038c048-5a1a-4d6a-a904-387a85e3e549", + "metadata": {}, + "source": [ + "Let's test the workflow now with an example question." ] }, { @@ -350,42 +352,48 @@ "name": "stdout", "output_type": "stream", "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", "\n", + "Who played in the Casino?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " Information (call_j4usgFStGtBM16fuguRaeoGc)\n", + " Call ID: call_j4usgFStGtBM16fuguRaeoGc\n", + " Args:\n", + " entity: Casino\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: Information\n", "\n", - "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", - "\u001b[32;1m\u001b[1;3m\n", - "Invoking: `Information` with `{'entity': 'Casino'}`\n", - "\n", - "\n", - "\u001b[0m\u001b[36;1m\u001b[1;3mtype:Movie\n", + "type:Movie\n", "title: Casino\n", "year: 1995-11-22\n", - "ACTED_IN: Joe Pesci, Robert De Niro, Sharon Stone, James Woods\n", - "\u001b[0m\u001b[32;1m\u001b[1;3mThe movie \"Casino\" starred Joe Pesci, Robert De Niro, Sharon Stone, and James Woods.\u001b[0m\n", + "ACTED_IN: Robert De Niro, Joe Pesci, Sharon Stone, James Woods\n", + "IN_GENRE: Drama, Crime\n", + "\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "\u001b[1m> Finished chain.\u001b[0m\n" + "The movie \"Casino,\" released in 1995, features the following actors:\n", + "\n", + "- Robert De Niro\n", + "- Joe Pesci\n", + "- Sharon Stone\n", + "- James Woods\n", + "\n", + "The film is in the Drama and Crime genres.\n" ] - }, - { - "data": { - "text/plain": [ - "{'input': 'Who played in Casino?',\n", - " 'output': 'The movie \"Casino\" starred Joe Pesci, Robert De Niro, Sharon Stone, and James Woods.'}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ - "agent_executor.invoke({\"input\": \"Who played in Casino?\"})" + "input_messages = [HumanMessage(content=\"Who played in the Casino?\")]\n", + "messages = react_graph.invoke({\"messages\": input_messages})\n", + "for m in messages[\"messages\"]:\n", + " m.pretty_print()" ] }, { "cell_type": "code", "execution_count": null, - "id": "c2759973-de8a-4624-8930-c90a21d6caa3", + "id": "a9fe9d6b-2eb6-47e5-a085-ca35dc5e3654", "metadata": {}, "outputs": [], "source": [] @@ -407,7 +415,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.1" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/docs/docs/how_to/index.mdx b/docs/docs/how_to/index.mdx index 76f74934e572b..1ce6cc2737a57 100644 --- a/docs/docs/how_to/index.mdx +++ b/docs/docs/how_to/index.mdx @@ -292,7 +292,7 @@ For a high-level tutorial on building chatbots, check out [this guide](/docs/tut ### Query analysis Query Analysis is the task of using an LLM to generate a query to send to a retriever. -For a high-level tutorial on query analysis, check out [this guide](/docs/tutorials/query_analysis/). +For a high-level tutorial on query analysis, check out [this guide](/docs/tutorials/rag/#query-analysis). - [How to: add examples to the prompt](/docs/how_to/query_few_shot) - [How to: handle cases where no queries are generated](/docs/how_to/query_no_queries) @@ -316,9 +316,7 @@ For a high-level tutorial, check out [this guide](/docs/tutorials/sql_qa/). You can use an LLM to do question answering over graph databases. For a high-level tutorial, check out [this guide](/docs/tutorials/graph/). -- [How to: map values to a database](/docs/how_to/graph_mapping) - [How to: add a semantic layer over the database](/docs/how_to/graph_semantic) -- [How to: improve results with prompting](/docs/how_to/graph_prompting) - [How to: construct knowledge graphs](/docs/how_to/graph_constructing) ### Summarization diff --git a/docs/docs/how_to/installation.mdx b/docs/docs/how_to/installation.mdx index f56946f921af2..081fe32fd8546 100644 --- a/docs/docs/how_to/installation.mdx +++ b/docs/docs/how_to/installation.mdx @@ -51,7 +51,7 @@ pip install langchain-core Certain integrations like OpenAI and Anthropic have their own packages. Any integrations that require their own package will be documented as such in the [Integration docs](/docs/integrations/providers/). -You can see a list of all integration packages in the [API reference](https://api.python.langchain.com) under the "Partner libs" dropdown. +You can see a list of all integration packages in the [API reference](https://python.langchain.com/api_reference/) under the "Partner libs" dropdown. To install one of these run: ```bash diff --git a/docs/docs/how_to/local_llms.ipynb b/docs/docs/how_to/local_llms.ipynb index 2bd4c44556251..dbd7c34190973 100644 --- a/docs/docs/how_to/local_llms.ipynb +++ b/docs/docs/how_to/local_llms.ipynb @@ -675,7 +675,7 @@ "\n", "Given an `llm` created from one of the models above, you can use it for [many use cases](/docs/how_to#use-cases).\n", "\n", - "For example, here is a guide to [RAG](/docs/tutorials/local_rag) with local LLMs.\n", + "For example, you can implement a [RAG application](/docs/tutorials/rag) using the chat models demonstrated here.\n", "\n", "In general, use cases for local LLMs can be driven by at least two factors:\n", "\n", diff --git a/docs/docs/how_to/output_parser_custom.ipynb b/docs/docs/how_to/output_parser_custom.ipynb index d77e1ff9c6ae7..1949e3dd067b7 100644 --- a/docs/docs/how_to/output_parser_custom.ipynb +++ b/docs/docs/how_to/output_parser_custom.ipynb @@ -12,7 +12,7 @@ "There are two ways to implement a custom parser:\n", "\n", "1. Using `RunnableLambda` or `RunnableGenerator` in [LCEL](/docs/concepts/lcel/) -- we strongly recommend this for most use cases\n", - "2. By inherting from one of the base classes for out parsing -- this is the hard way of doing things\n", + "2. By inheriting from one of the base classes for out parsing -- this is the hard way of doing things\n", "\n", "The difference between the two approaches are mostly superficial and are mainly in terms of which callbacks are triggered (e.g., `on_chain_start` vs. `on_parser_start`), and how a runnable lambda vs. a parser might be visualized in a tracing platform like LangSmith." ] @@ -200,7 +200,7 @@ "id": "24067447-8a5a-4d6b-86a3-4b9cc4b4369b", "metadata": {}, "source": [ - "## Inherting from Parsing Base Classes" + "## Inheriting from Parsing Base Classes" ] }, { @@ -208,7 +208,7 @@ "id": "9713f547-b2e4-48eb-807f-a0f6f6d0e7e0", "metadata": {}, "source": [ - "Another approach to implement a parser is by inherting from `BaseOutputParser`, `BaseGenerationOutputParser` or another one of the base parsers depending on what you need to do.\n", + "Another approach to implement a parser is by inheriting from `BaseOutputParser`, `BaseGenerationOutputParser` or another one of the base parsers depending on what you need to do.\n", "\n", "In general, we **do not** recommend this approach for most use cases as it results in more code to write without significant benefits.\n", "\n", diff --git a/docs/docs/how_to/qa_chat_history_how_to.ipynb b/docs/docs/how_to/qa_chat_history_how_to.ipynb index 0c82ac75f9a55..c1874135bb3e5 100644 --- a/docs/docs/how_to/qa_chat_history_how_to.ipynb +++ b/docs/docs/how_to/qa_chat_history_how_to.ipynb @@ -29,7 +29,9 @@ "1. [Chains](/docs/how_to/qa_chat_history_how_to#chains), in which we always execute a retrieval step;\n", "2. [Agents](/docs/how_to/qa_chat_history_how_to#agents), in which we give an LLM discretion over whether and how to execute a retrieval step (or multiple steps).\n", "\n", - "For the external knowledge source, we will use the same [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng from the [RAG tutorial](/docs/tutorials/rag)." + "For the external knowledge source, we will use the same [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng from the [RAG tutorial](/docs/tutorials/rag).\n", + "\n", + "Both approaches leverage [LangGraph](https://langchain-ai.github.io/langgraph/) as an orchestration framework. LangGraph implements a built-in [persistence layer](https://langchain-ai.github.io/langgraph/concepts/persistence/), making it ideal for chat applications that support multiple conversational turns." ] }, { @@ -54,136 +56,131 @@ "outputs": [], "source": [ "%%capture --no-stderr\n", - "%pip install --upgrade --quiet langchain langchain-community beautifulsoup4" + "%pip install --upgrade --quiet langgraph langchain-community beautifulsoup4" ] }, { "cell_type": "markdown", - "id": "51ef48de-70b6-4f43-8e0b-ab9b84c9c02a", + "id": "1665e740-ce01-4f09-b9ed-516db0bd326f", "metadata": {}, "source": [ - "We need to set environment variable `OPENAI_API_KEY`, which can be done directly or loaded from a `.env` file like so:" + "### LangSmith\n", + "\n", + "Many of the applications you build with LangChain will contain multiple steps with multiple invocations of LLM calls. As these applications get more and more complex, it becomes crucial to be able to inspect what exactly is going on inside your chain or agent. The best way to do this is with [LangSmith](https://smith.langchain.com).\n", + "\n", + "Note that LangSmith is not needed, but it is helpful. If you do want to use LangSmith, after you sign up at the link above, make sure to set your environment variables to start logging traces:\n", + "\n", + "```python\n", + "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", + "if not os.environ.get(\"LANGCHAIN_API_KEY\"):\n", + " os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", + "```\n", + "\n", + "### Components\n", + "\n", + "We will need to select three components from LangChain's suite of integrations.\n", + "\n", + "A [chat model](/docs/integrations/chat/):\n", + "\n", + "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "\n", + "" ] }, { "cell_type": "code", "execution_count": 2, - "id": "3b156b76-22a1-43af-a509-137acdccc5d0", + "id": "c5bba77e-6774-4005-8442-468c9f8d23f0", "metadata": {}, "outputs": [], "source": [ - "import getpass\n", - "import os\n", + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_openai import ChatOpenAI\n", "\n", - "if not os.environ.get(\"OPENAI_API_KEY\"):\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()" + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" ] }, { "cell_type": "markdown", - "id": "1665e740-ce01-4f09-b9ed-516db0bd326f", + "id": "36d59333-dabf-46fd-bc52-75990f0767c9", "metadata": {}, "source": [ - "### LangSmith\n", - "\n", - "Many of the applications you build with LangChain will contain multiple steps with multiple invocations of LLM calls. As these applications get more and more complex, it becomes crucial to be able to inspect what exactly is going on inside your chain or agent. The best way to do this is with [LangSmith](https://smith.langchain.com).\n", + "An [embedding model](/docs/integrations/text_embedding/):\n", "\n", - "Note that LangSmith is not needed, but it is helpful. If you do want to use LangSmith, after you sign up at the link above, make sure to set your environment variables to start logging traces:\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", "\n", - "```python\n", - "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", - "if not os.environ.get(\"LANGCHAIN_API_KEY\"):\n", - " os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", - "```" + "" ] }, { - "cell_type": "markdown", - "id": "fa6ba684-26cf-4860-904e-a4d51380c134", + "cell_type": "code", + "execution_count": 3, + "id": "b74d449a-fdda-45e8-8f7d-c40a5a4e2d4f", "metadata": {}, + "outputs": [], "source": [ - "## Chains {#chains}\n", - "\n", - "In a conversational RAG application, queries issued to the retriever should be informed by the context of the conversation. LangChain provides a [create_history_aware_retriever](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.history_aware_retriever.create_history_aware_retriever.html) constructor to simplify this. It constructs a chain that accepts keys `input` and `chat_history` as input, and has the same output schema as a retriever. `create_history_aware_retriever` requires as inputs: \n", - "\n", - "1. LLM;\n", - "2. Retriever;\n", - "3. Prompt.\n", - "\n", - "First we obtain these objects:\n", + "# | output: false\n", + "# | echo: false\n", "\n", - "### LLM\n", + "from langchain_openai import OpenAIEmbeddings\n", "\n", - "We can use any supported chat model:" + "embeddings = OpenAIEmbeddings()" ] }, { "cell_type": "markdown", - "id": "646840fb-5212-48ea-8bc7-ec7be5ec727e", + "id": "be6adeca-b883-4a3e-9488-49fac5c727b0", "metadata": {}, "source": [ - "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "And a [vector store](/docs/integrations/vectorstores/):\n", + "\n", + "import VectorStoreTabs from \"@theme/VectorStoreTabs\";\n", "\n", - "\n" + "" ] }, { "cell_type": "code", "execution_count": 4, - "id": "cb58f273-2111-4a9b-8932-9b64c95030c8", + "id": "be98ef2a-de81-4b7f-8e20-a7bc2d7ee399", "metadata": {}, "outputs": [], "source": [ "# | output: false\n", "# | echo: false\n", "\n", - "from langchain_openai import ChatOpenAI\n", + "from langchain_core.vectorstores import InMemoryVectorStore\n", "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)" + "vector_store = InMemoryVectorStore(embeddings)" ] }, { "cell_type": "markdown", - "id": "6bb76a36-15b1-4589-8a3d-18c6f5fdb7e0", - "metadata": {}, - "source": [ - "### Retriever" - ] - }, - { - "cell_type": "markdown", - "id": "15f8ad59-19de-42e3-85a8-3ba95ee0bd43", + "id": "fa6ba684-26cf-4860-904e-a4d51380c134", "metadata": {}, "source": [ - "For the retriever, we will use [WebBaseLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.web_base.WebBaseLoader.html) to load the content of a web page. Here we instantiate a `InMemoryVectorStore` vectorstore and then use its [.as_retriever](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html#langchain_core.vectorstores.base.VectorStore.as_retriever) method to build a retriever that can be incorporated into [LCEL](/docs/concepts/lcel) chains." + "## Chains {#chains}\n", + "\n", + "The [RAG Tutorial](/docs/tutorials/rag) indexes an [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng. We will repeat that here. Below we load the content of the page, split it into sub-documents, and embed the documents into our [vector store](/docs/concepts/vectorstores/):" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "820244ae-74b4-4593-b392-822979dd91b8", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "USER_AGENT environment variable not set, consider setting it to identify your requests.\n" - ] - } - ], + "outputs": [], "source": [ "import bs4\n", - "from langchain.chains import create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", + "from langchain import hub\n", "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "from langchain_core.vectorstores import InMemoryVectorStore\n", - "from langchain_openai import OpenAIEmbeddings\n", + "from langchain_core.documents import Document\n", "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "from typing_extensions import List, TypedDict\n", "\n", + "# Load and chunk contents of the blog\n", "loader = WebBaseLoader(\n", " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", " bs_kwargs=dict(\n", @@ -195,240 +192,196 @@ "docs = loader.load()\n", "\n", "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = InMemoryVectorStore(embedding=OpenAIEmbeddings())\n", - "vectorstore.add_documents(splits)\n", - "retriever = vectorstore.as_retriever()" - ] - }, - { - "cell_type": "markdown", - "id": "776ae958-cbdc-4471-8669-c6087436f0b5", - "metadata": {}, - "source": [ - "### Prompt\n", - "\n", - "We'll use a prompt that includes a `MessagesPlaceholder` variable under the name \"chat_history\". This allows us to pass in a list of Messages to the prompt using the \"chat_history\" input key, and these messages will be inserted after the system message and before the human message containing the latest question." + "all_splits = text_splitter.split_documents(docs)" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "2b685428-8b82-4af1-be4f-7232c5d55b73", + "execution_count": 7, + "id": "73920571-8c26-4988-adf1-b0f695fee50a", "metadata": {}, "outputs": [], "source": [ - "from langchain.chains import create_history_aware_retriever\n", - "from langchain_core.prompts import MessagesPlaceholder\n", - "\n", - "contextualize_q_system_prompt = (\n", - " \"Given a chat history and the latest user question \"\n", - " \"which might reference context in the chat history, \"\n", - " \"formulate a standalone question which can be understood \"\n", - " \"without the chat history. Do NOT answer the question, \"\n", - " \"just reformulate it if needed and otherwise return it as is.\"\n", - ")\n", - "\n", - "contextualize_q_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", contextualize_q_system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")" + "# Index chunks\n", + "_ = vector_store.add_documents(documents=all_splits)" ] }, { "cell_type": "markdown", - "id": "9d2a692e-a019-4515-9625-5b0530c3c9af", + "id": "ffd8ccaf-9d43-464b-8b4e-2ba64f8222fd", "metadata": {}, "source": [ - "### Assembling the chain\n", + "As detailed in [Part 2](/docs/tutorials/qa_chat_history) of the RAG tutorial, we can naturally support a conversational experience by representing the flow of the RAG application as a sequence of [messages](/docs/concepts/messages/):\n", + "\n", + "1. User input as a `HumanMessage`;\n", + "2. Vector store query as an `AIMessage` with tool calls;\n", + "3. Retrieved documents as a `ToolMessage`;\n", + "4. Final response as a `AIMessage`.\n", "\n", - "We can then instantiate the history-aware retriever:" + "We will use [tool-calling](/docs/concepts/tool_calling/) to facilitate this, which additionally allows the query to be generated by the LLM. We can build a [tool](/docs/concepts/tools) to execute the retrieval step:" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "4c4b1695-6217-4ee8-abaf-7cc26366d988", + "execution_count": 8, + "id": "f5b7914b-28f7-400b-a987-621d8fd533f5", "metadata": {}, "outputs": [], "source": [ - "history_aware_retriever = create_history_aware_retriever(\n", - " llm, retriever, contextualize_q_prompt\n", - ")" + "from langchain_core.tools import tool\n", + "\n", + "\n", + "@tool(response_format=\"content_and_artifact\")\n", + "def retrieve(query: str):\n", + " \"\"\"Retrieve information related to a query.\"\"\"\n", + " retrieved_docs = vector_store.similarity_search(query, k=2)\n", + " serialized = \"\\n\\n\".join(\n", + " (f\"Source: {doc.metadata}\\n\" f\"Content: {doc.page_content}\")\n", + " for doc in retrieved_docs\n", + " )\n", + " return serialized, retrieved_docs" ] }, { "cell_type": "markdown", - "id": "42a47168-4a1f-4e39-bd2d-d5b03609a243", + "id": "1346cdde-a1af-43f2-9387-396e931f8ba5", "metadata": {}, "source": [ - "This chain prepends a rephrasing of the input query to our retriever, so that the retrieval incorporates the context of the conversation.\n", + "We can now build our LangGraph application.\n", "\n", - "Now we can build our full QA chain.\n", - "\n", - "As in the [RAG tutorial](/docs/tutorials/rag), we will use [create_stuff_documents_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.combine_documents.stuff.create_stuff_documents_chain.html) to generate a `question_answer_chain`, with input keys `context`, `chat_history`, and `input`-- it accepts the retrieved context alongside the conversation history and query to generate an answer.\n", - "\n", - "We build our final `rag_chain` with [create_retrieval_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.retrieval.create_retrieval_chain.html). This chain applies the `history_aware_retriever` and `question_answer_chain` in sequence, retaining intermediate outputs such as the retrieved context for convenience. It has input keys `input` and `chat_history`, and includes `input`, `chat_history`, `context`, and `answer` in its output." + "Note that we compile it with a [checkpointer](https://langchain-ai.github.io/langgraph/concepts/persistence/) to support a back-and-forth conversation. LangGraph comes with a simple [in-memory checkpointer](https://langchain-ai.github.io/langgraph/reference/checkpoints/#memorysaver), which we use below. See its documentation for more detail, including how to use different persistence backends (e.g., SQLite or Postgres)." ] }, { "cell_type": "code", - "execution_count": 8, - "id": "afef4385-f571-4874-8f52-3d475642f579", + "execution_count": 9, + "id": "95d7aa8d-0624-4512-910f-9ced77bfd070", "metadata": {}, "outputs": [], "source": [ - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "qa_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", + "from langchain_core.messages import SystemMessage\n", + "from langgraph.checkpoint.memory import MemorySaver\n", + "from langgraph.graph import END, MessagesState, StateGraph\n", + "from langgraph.prebuilt import ToolNode, tools_condition\n", + "\n", + "\n", + "# Step 1: Generate an AIMessage that may include a tool-call to be sent.\n", + "def query_or_respond(state: MessagesState):\n", + " \"\"\"Generate tool call for retrieval or respond.\"\"\"\n", + " llm_with_tools = llm.bind_tools([retrieve])\n", + " response = llm_with_tools.invoke(state[\"messages\"])\n", + " # MessagesState appends messages to state instead of overwriting\n", + " return {\"messages\": [response]}\n", + "\n", + "\n", + "# Step 2: Execute the retrieval.\n", + "tools = ToolNode([retrieve])\n", + "\n", + "\n", + "# Step 3: Generate a response using the retrieved content.\n", + "def generate(state: MessagesState):\n", + " \"\"\"Generate answer.\"\"\"\n", + " # Get generated ToolMessages\n", + " recent_tool_messages = []\n", + " for message in reversed(state[\"messages\"]):\n", + " if message.type == \"tool\":\n", + " recent_tool_messages.append(message)\n", + " else:\n", + " break\n", + " tool_messages = recent_tool_messages[::-1]\n", + "\n", + " # Format into prompt\n", + " docs_content = \"\\n\\n\".join(doc.content for doc in tool_messages)\n", + " system_message_content = (\n", + " \"You are an assistant for question-answering tasks. \"\n", + " \"Use the following pieces of retrieved context to answer \"\n", + " \"the question. If you don't know the answer, say that you \"\n", + " \"don't know. Use three sentences maximum and keep the \"\n", + " \"answer concise.\"\n", + " \"\\n\\n\"\n", + " f\"{docs_content}\"\n", + " )\n", + " conversation_messages = [\n", + " message\n", + " for message in state[\"messages\"]\n", + " if message.type in (\"human\", \"system\")\n", + " or (message.type == \"ai\" and not message.tool_calls)\n", " ]\n", - ")\n", - "\n", - "question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)\n", - "rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)" - ] - }, - { - "cell_type": "markdown", - "id": "53a662c2-f38b-45f9-95c4-66de15637614", - "metadata": {}, - "source": [ - "### Stateful Management of chat history\n", + " prompt = [SystemMessage(system_message_content)] + conversation_messages\n", "\n", - "We have added application logic for incorporating chat history, but we are still manually plumbing it through our application. In production, the Q&A application we usually persist the chat history into a database, and be able to read and update it appropriately.\n", + " # Run\n", + " response = llm.invoke(prompt)\n", + " return {\"messages\": [response]}\n", "\n", - "[LangGraph](https://langchain-ai.github.io/langgraph/) implements a built-in [persistence layer](https://langchain-ai.github.io/langgraph/concepts/persistence/), making it ideal for chat applications that support multiple conversational turns.\n", "\n", - "Wrapping our chat model in a minimal LangGraph application allows us to automatically persist the message history, simplifying the development of multi-turn applications.\n", + "# Build graph\n", + "graph_builder = StateGraph(MessagesState)\n", "\n", - "LangGraph comes with a simple [in-memory checkpointer](https://langchain-ai.github.io/langgraph/reference/checkpoints/#memorysaver), which we use below. See its documentation for more detail, including how to use different persistence backends (e.g., SQLite or Postgres).\n", + "graph_builder.add_node(query_or_respond)\n", + "graph_builder.add_node(tools)\n", + "graph_builder.add_node(generate)\n", "\n", - "For a detailed walkthrough of how to manage message history, head to the How to add message history (memory) guide." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "9c3fb176-8d6a-4dc7-8408-6a22c5f7cc72", - "metadata": {}, - "outputs": [], - "source": [ - "from typing import Sequence\n", + "graph_builder.set_entry_point(\"query_or_respond\")\n", + "graph_builder.add_conditional_edges(\n", + " \"query_or_respond\",\n", + " tools_condition,\n", + " {END: END, \"tools\": \"tools\"},\n", + ")\n", + "graph_builder.add_edge(\"tools\", \"generate\")\n", + "graph_builder.add_edge(\"generate\", END)\n", "\n", - "from langchain_core.messages import AIMessage, BaseMessage, HumanMessage\n", - "from langgraph.checkpoint.memory import MemorySaver\n", - "from langgraph.graph import START, StateGraph\n", - "from langgraph.graph.message import add_messages\n", - "from typing_extensions import Annotated, TypedDict\n", - "\n", - "\n", - "# We define a dict representing the state of the application.\n", - "# This state has the same input and output keys as `rag_chain`.\n", - "class State(TypedDict):\n", - " input: str\n", - " chat_history: Annotated[Sequence[BaseMessage], add_messages]\n", - " context: str\n", - " answer: str\n", - "\n", - "\n", - "# We then define a simple node that runs the `rag_chain`.\n", - "# The `return` values of the node update the graph state, so here we just\n", - "# update the chat history with the input message and response.\n", - "def call_model(state: State):\n", - " response = rag_chain.invoke(state)\n", - " return {\n", - " \"chat_history\": [\n", - " HumanMessage(state[\"input\"]),\n", - " AIMessage(response[\"answer\"]),\n", - " ],\n", - " \"context\": response[\"context\"],\n", - " \"answer\": response[\"answer\"],\n", - " }\n", - "\n", - "\n", - "# Our graph consists only of one node:\n", - "workflow = StateGraph(state_schema=State)\n", - "workflow.add_edge(START, \"model\")\n", - "workflow.add_node(\"model\", call_model)\n", - "\n", - "# Finally, we compile the graph with a checkpointer object.\n", - "# This persists the state, in this case in memory.\n", "memory = MemorySaver()\n", - "app = workflow.compile(checkpointer=memory)" + "graph = graph_builder.compile(checkpointer=memory)" ] }, { "cell_type": "code", "execution_count": 10, - "id": "1046c92f-21b3-4214-907d-92878d8cba23", + "id": "e5aeea66-9653-49c9-98d8-113e54eb72cb", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Task decomposition is a technique used to break down complex tasks into smaller and simpler steps. This process helps agents or models tackle difficult tasks by dividing them into more manageable subtasks. Task decomposition can be achieved through methods like Chain of Thought (CoT) or Tree of Thoughts, which guide the agent in thinking step by step or exploring multiple reasoning possibilities at each step.\n" - ] + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAALcAAAGwCAIAAABkfmPEAAAAAXNSR0IArs4c6QAAIABJREFUeJztnWdAU9f7x092SMgiYW+UqigoCk7EvVBx1L2tVq2ita1trbXWX1tHh3XjqLN122q1ThTrFsE9UIYKgswkkJA9/y+u/0g1JKBJ7rlwPq+Sm3vP/ebmm3Oee+45zyGZzWaAQNiEjLcABAFALkHYB7kEYR/kEoR9kEsQ9kEuQdiHireAd6UsX6uQG1Ryg15v1qlNeMupFQw3Mo1BZnMpbB7NM4COtxz7ENUlObcVT+8rnj5QhkawjUYzm0v18KaTKXjLqjVlzzVKuYHOpDzPUoa1cA+LdA9pzsJbVI2QCNerlnldfvUfcXAzdkgzdmgkm0oj4a3ondAojU/vK4ueaUqeqTsOFIVFsvFWZAUiuaSyXH/69xKRP6PTQCGTTZx6o3ZUlOmv/iMmk0i9xnvDZn3CuCT3jiLthGTgND+eiIa3FidSVqD9a23h0Fn+3sFMvLW8ghguKcxWP7gq6zvJB28hLuLgyoJe43z4nrD8HwjgknuXZIU5qoQPfPEW4lIOrips28cjuBkUIS3s/SVFT9S5d6oamkUAAMPnBpzbV6qUGfEWAmB3iUZlunG2YujsALyF4MOYr0LO7i3FWwWA3SWX/y4Pj3bHWwVuMJgk7yDGjTMVeAuB2CUVpfrSfE2ztly8heBJ+wTh9VMSE95dyvC65P5lWechXq45l0KhePz4MV6H26bbcK9bqThXJ7C6xAzuXa4MaurmmrONGjXqyJEjeB1um4BwVmaazEmF1xJIXfL0gTK0hev6qnU63dsdiPUjvPXhtYErpNIYZEmxE09hF0hdUvRUHR7NcUbJO3bsSEhIiIuLmzJlSnp6OgBgwIABUqn04MGDMTExAwYMwH719evXJyYmtmvXrn///snJyUbjyzvSH3/8sXfv3hcvXhwyZEhMTExGRsabhzucJrHc51kqZ5RcSyB9Jlz6XBMW6fi7m/T09HXr1vXt27djx45Xr15VqVQAgJ9++ikpKalNmzZjx46l0+kAAAqFcv369fj4+ICAgKysrG3btnG53HHjxmGFKBSK5OTk+fPnq9Xq2NjYNw93OCwOpQC55E2UMiOb6/jneUVFRQCAESNGREVFJSQkYBsjIiKoVKpIJGrVqhW2hUKh7Ny5k0R6+citsLDw3LlzFpfodLqFCxe2aNGipsMdjjuXqpQZnFR4bYDUJSq5gc11vLa4uDgul/vNN998/vnncXFxNvaUSqW//fZbWlqaXC4HAHA4r5o/JpNpsYhrYHEpSjmenbBQxiVmQGeSyRTHPz0XiUTbtm0LDg6eO3fulClTysrKrO4mkUjGjh2bnp7+0UcfrV27tlmzZpa4BADAYrn62QqFQsJ3LAGULiEBCpXkpDo2JCRkzZo1GzZsyM3NXbx4sWV79aeef/31l1QqTU5O7tOnT/PmzX187D+LdupDU4XMQGPg+UtB6RIAWFyqUu4Ul2B3rbGxsZ07d7Z0hbm5uYnFYss+lZWVAoHAYo7KykrbJnjtcIejkjslSqs9kMYlviFMtdLxLfHDhw+//PLLESNGsFisq1evRkREYNujo6NPnTq1Y8cOLpcbFRUVExNz4MCBDRs2tGzZ8ty5c1euXDGZTJWVlXw+32qxrx3euHFjx8rWakwif4Zjy6wTlOq1LjyoFcZnD5SNohx8MyyTybKzs1NSUtLT01u3br1gwQJ3d3cAQFRUVFZW1okTJx4/fty8efPu3bubTKaDBw+mpqYGBgZ+8803t2/fVqlUMTExV65cefbs2fjx46sX+9rhoaGhjpV96XB5RHseR4DbXxrSUUg6tWnHd3nTloXhLQR/NErTrqV5U5fgeSkgbXHobuSwSPfSfI2N4Z+//PLLsWPH3tzerFmzR48eWT1k+/btDv+jv8bly5cXLlxo9aOAgIDCwsI3t2/bti0srEYTFOSoIzrwHKqxzkBalwAAXuSq009JhyT517RDZWUl1nn6GiRSjV/Ky8uLSnXuH0Oj0UilUqsf1STMtqrti/OGzw1w5+P5f4a0LgEA+Dd2o9BI+Y9UNY395PP5NYWTOMJkMv38/BxV2r1LsrBINr4WgfdOGKNToijrRhXeKvDk2UNlp4EivFXA7RKhLz3gPbfUfdZ7SOs9h9YWxvYSUOn4z+CC2iUAgIh2XDqDfO2YBG8hriblj9LGrTh+jVw0Dss28Eav1bl7oVKtNLVP8MBbiIs4s6s0vDUnJAKKyTgEqEswWnbhk0jgxPZivIU4HYPOfODXAv/GbvBYhDB1CcaTe8rzf5a16S5o1RW6WxuHkHZC8vyxquswL68gPPvj34RILgEAGI3g2j/irJtVrbrwQ5qzhb4ESBFjl9J8TWGOOu2kpF1fYUxPAcA/Wn0dgrkEQ1VlvH9Z9uSewqA3NY7ikCiAzaVyBFSjkRjfhUImy6Q6ldxIIoHM63KuB7VxK07LLnwyrO0/IV1iQS7RFz3TKir0qioDiUxSVDp4sEF+fj6dTvf1dfAsZTaXSiIBFpfC9aD5N3ZjcWDPxQJv32tt4AppXKET0zf8+usero9PvzHRzjsFIYC1jkPABHIJwj7IJbbgcDhublD0fuILcoktqqqq1Go13irwB7nEFnQ6nUKB/QbEBSCX2EKn01WfidNgQS6xBYPBoNFgSZSII8glttBqtXq9Hm8V+INcYgsej+f6+Z4QQuy+V2cjk8nQnTCqS+xAoVAs+SkaMsgltjAajYR+GuookEsQ9kEusQWPx0NxCXKJHWQyGeqhRy5B1ArkElvQ6XRnzysmBMglttDpdAYDnskRIQG5xBYcDofJhGhlNLxALrFFVVWVRqPBWwX+IJcg7INcYgs0CgkDucQWaBQSBnIJwj7IJQj7IJfYgsvlouc4yCV2kMvl6DkOcgmiViCXIOyDXGILGo2G+kuQS+yg1+tRfwlyCaJWIJfYgsViMRhwJcLDBeQSW6hUKq1Wi7cK/EEuQdgHucQWaMoWBnKJLdCULQzkElvw+Xw0mxzNJrdDZWUlGveK6hI7oNHRGMTOHe0kEhMTscsil8spFAqbzcYi2aNHj+ItDR9Qi2MFLy+vmzdvWp7gyOVys9nco0cPvHXhBmpxrDBhwgShUFh9i1AonDBhAn6KcAa5xArx8fEhISGWt2azuWXLli1atMBVFJ4gl1hn9OjRXC4Xey0UCj/44AO8FeEJcol1evToER4ebjabzWZzdHR0s2bN8FaEJ8glNTJq1Cg+n+/n5zd+/Hi8teDMO93jKCoNkmKdXmdynB6ICPSIjQjuLhAImMaQ3LsKvOU4BTqT7OnPcHO3Mx7vLftL5BL9xUPi8kJtcARbWYVGcxEVOoNckKX0b+TWc6w3reblrd/GJYpKw9/JRd1H+3E8UHdLfaDsueb6ifKhs/2ZLOsRSJ3jErMJ7Pwub9CsIGSReoNXELP7aN99Pz+vaYc61yVX/5GweIxGLd0dIQ8BEfcuSrkCSmQc782P6lyXFD1VcwSoFqmHsLjU0ufWU/q8RYtDchegxUDqIVwPul5jvWGps0uUMr3ZhB4j10NMRrNaaf12FfWqIeyDXIKwD3IJwj7IJQj7IJcg7INcgrAPcgnCPsglCPsglyDsg1yCsA9yCcI+yCX1k+Mn/u7WI0YiETukNOQShH2I7RKnTnKuU+H1e7q1K8YTFRW/2LRp9a3b6VQqrXev/lnZmd269h6UOGzrtuT9B/5IOXUN2+1xVuZHMycsX7amXduOAIDbd278tmXdkyfZAoFHdKvYqVNmCYUiAMDkKSNCQxqFhDQ6dHifVqsZOWLCnr3bDx44xeO+HGS1ZNk3mQ/v7d51xIakzEcPNm5alZWVyWS6dewQ/9FHn3A53DcLP7j/lLu79VF5Mlnl4KE9Z0z/OCc368qV8+HhTdes2gIAOHL0zwMHd4nFZT4+fj269x05YjyDwdBoNKvWLL969SIAICoqOmnmPB8f34GDujZt0lytUefmZvF4/D69B0wY/yG2mKTBYNi+Y+PplGMyWWVwcOikidPjOnUFAPz5155z/6YMHzZ269b1Eqk4PLzpvE8XBgW9nIaYk5u1dt3PWVmZQg9RYGCwA39Bp7tEKpXM+XiKVqMZMWK8t5fPhUupd+/e6ta1t+2jbt5Kn//VnF49E4YMHlkll/11aO+n82Zs2rALyxORkXFNo9Us/WGlSq0KDWn0x64t//6bMnjQcCxDa1rapcGDRtgoPC/v6WfzZoSENPri829llRXbd2wsKytZ8csG7NPqhddkEQu7dm0dNGj4il82YlPPd+zcfPDPXUOHjAoODisoyNt/4PfCF88XzP9uz97tp08fmzxphlAoOp1yzLICwvOCvI9mfCISel5Lu7R7z3aFomrO7C8AAL+s+OFs6slxYz8ICWl0NvXkN4vmrV75W1RUNADg0aMHBw788dlnCw0Gw6+/Lln247cb1u8EADx/nvfJp9N4XP6HU5MoFOrvf/xWxx/KFk53yb79v0sk4vXrdkQ0awEAaNeu0+ChPe0etXbdzwMHDMUuGQAgJqb9xMnDMm5c6xzXDQBAoVK/+Xqp5VrHxnY4nXIMc8mNG2kKhaJH9742Ct+1eyuZTP7px3Ucdw4AgMPhLl2+6O7dWy1btn6zcNtEREROnTILey0Wl+/es23h10u6xL/MTiAUeq5ctSxp1rzikiI3N7cxoydRqdT+CYMth3ft0qtrl54AgBYtWsrlsn+OHZo4cbqssuJ0yrEJ46dOmjgdANAlvse4CUN27Nz064qN2FFLfljp4SEEAAwdOip5w0qZXMbj8jZuXk0mkdev28HnCwAAZDJ51erltfkKtcHpLrl1O/298KaYRWpJSUlxfv6zFy8Kjh0/XH17WVkp9qJZsxbVf8W+fQb+77v5z5/nBQWFnL94tlGj8JCQMBvl37l7Mzo6FrMIZjIAQFZ2JuaS1wq3TevWbS2vb968bjAYlixduGTpQmwLFqyIy8t69uiXmnrqy/mzZ838LCyssdWi2rbteOz44Zycx8XFLwAAcXHdsO0kEik2pv2ZsycsezKZL+V5e/sCACTicgadkZFxLTFxGGYRAIBjl0F2ukuqquTh4U3rdEhFhQQAMHHCtPjO3atv9/AQYS/cmP/5FTt17MLl8k6nHJs0cfrVKxfGjJlsu3ylUsHnCSxvORwuVhNYLdw2zGo7S6RiAMDSJau8PL2r7+PnFxAW1njZ0tUbN62a8uGo/gmD5348/81f0d2dAwBQq1VKpQIAIOB7WD7icnkqlUqpVL52CI1KAwAYTUaJVGwwGHx9/GqvvE443SVCoafk/3+A16gpTyZ2vbRajSUusw2NRuvZs1/KmeMRzSIVSkX3bn1s7y8SecnlMsvbigqp5aTvAuY2AIBV2e3adoyNaf/Xob3JG1Z6e/uOHzfltR3E5WUAAE9PbywPsVwuE4k8sY+kUgmVSrWRuwszPfZFnIHT74SbvNfscVZmds7jNz/i8QR6vV72/z9YSUkR9iIgIMjb2+fkqaOWFYwMBoNer7dxlr59BorF5ckbV0ZGtvL29rEtqXnzqDt3b1oWCr54MRUAEBnZ6q2+3yuio2NJJNLhv/dbtlj063Q6LFYYPmysSOSZ88bVMJvNJ08d5bhzgoNCmzVrQSKR0q5fthybdv1y8+ZRNlbXYLPZ/v6B5y+ctX2V3hqn1yUjR0w4cfLIvM9nDh821tPTKz39quWjmDbtSCTSuvW/DHt/TN6zJ5t+W4NtJ5FIs2Z+tujbz2fNnpQ4cJjJaDydcqxXr4Rh74+p6SzhjZsEBYU8f543Yvg4u5LGjfng3LnTX341e+CA98vKSnb+vjm6VUyrlm3e8ZsG+AcOHTLqr0N7Fyz8JK5TV4lE/PeRA8uWrn4vvOmhw/uuXL3Qq2eCRFIuFpc3aRKBHfLv+RShUMRgMC9cOHv7zo3p0+a4ubn5uwX06T1gx85NRqPRzy/g+PHDUqlkwVff2z77xAnTli77Jmn25L59E8lk8l+H9r7j16mO013i4+P784/rN25e/ceuLRwOt13bTpaPgoND53+x+Pc/fvv40tSoyOjpH85Z/tNi7KPOcd2WLVm1fcfG9ckr2Gz3qMjoqKjWtk8U0SyyqKgQu2WwTUBA0E/L123esvann//n5sbq1TNhxvS5DkkTPWvmp15e3ocP78/IuCYUijrHdfMUeWGhiV6n27BxJZvtPnToqJEjXqa6EIm8TqccKyjI9/L0njH9Y8v2uR/PZ7PdD/+9v6pKHhrSaOkPK1tHx9o+da+e/RSKqgMH/ti0eXVIcFhERGRBQf67fyOMOs8A3bE4r+8HAWzeW9oL64ya+/H8QYnD3q6Emvhm0TyD0bBsySrHFus8Bg7qmtBv8Ecz5uIt5CUlz9T3L0mHzvZ/86P6MJfzzNmTZ1NPZmRcs/SMKRSK0WMHWN15+rSPB/QfUsuS58yd+uxZ7pvbO3bs8tWX/3sHyQSjPrjk5MkjeoP+x+Vro1vFYFtYLNbmTXus7szlWJktXROLFi7TG6zEg3W6W64HuLrFQUCLjRaH2M+EEa4BuQRhH+QShH2QSxD2QS5B2Ae5BGEf5BKEfZBLEPZBLkHYB7kEYZ86u8TDj16vp540XEgkEk9kPUdrnV1CpZIkxVpHqELARXmhmsm2Phyuzi4Ji3SXFlvPMIwgNDKJPiSCbfWjOrukaSxHpzHevVjhCGEIWEg7Xi7wpPo3tj4A+y3Xx0nZVcpgUQVedJE/WpSZwJgM5vIibckzlcifHttLUNNub7/qdNaNqrxMpdEAxC+gDlOqquSWORCuxGw2qZQqtr05pPgi8KG7scnvteYENWXZ2s9cr5k+ffqzZ8/wOvu1a9e+/fZbvM7uQNAK9gj71NtetYyMjCtXruCtAgAATpw4kZ2djbeKd6J+uiQjI+Pq1audOnWqxb5OJyEhYf/+/fn5Dpsd43pQi4OwTz2sS5YsWWIwGPBW8TolJSXr16/HW8VbUt9cMnny5IEDBzo2e4dD8PHx8fb2XrZsGd5C3oZ61eLodDoymQyhRSxoNBoqlQqzQqvUn7rk6dOn9+7dg/wHYDKZqamplqQYRKGeuCQnJ2fBggUxMTF4C7FPaGjo5Ml2sjXBRj1pcQoLCwMCAvBWUVvEYrHJZPLy8sJbSG2pD3XJs2fP+Hw+3irqgEgkcnd3NxqtL8sKIYR3yebNm1NSUuwmZoWNkpKSUaNG4a2ithC7xRGLxY8fP46Li8NbyNtw8uRJDodDCPHEdgnCNRC4xfn444/T0tLwVvFOpKen//nnn3irsA9RXZKWltanT5/27dvjLeSdaNu27d69e/Py8vAWYgfU4uCMXq/X6XRstvVhyZBAyLpkzZo1hYWFeKtwDDQajUQiQX5XTDyX7N27V6fTEagPzS4XL15ctGgR3ipsAfVTjzcxm80DBw4kXO+Ibfr27ZuamlpRUSEQ1DiKHV8IFpdkZWWJRCKhUIi3kIYFkVqchw8f7ty5s15axGAwHDhwAG8VNUIkl2RnZ8+cORNvFU6BSqXeunXrzJkzeAuxDsFanHpMSUlJdnZ2fHw83kKsQBiX7N+/v3nz5i1a1GFlN4SjIEaLo1ar165dW+8tcujQoRs3buCtwgrEcIlerz969CjeKpyOh4fHvn378FZhBWL0l3C5OEwHdz1dunSBc0gsMeqS4cOHv7kCZv2DRCL17WtrJWS8IIBLCgoK9Ho95M/DHMWhQ4f++ecfvFW8DgFc4uXltWvXLrxVuAgfH5+UlBS8VbwOYe6EGwhms7m0tNTHx85ity6GAC45dOiQyWQaNszBq0Eiag8BWpyioqKqqiq8VbiO//3vf5cuXcJbxX8gwJ3wpEmTyGQCuNlR+Pr6ZmZmdu7cGW8hryBAi9PQ0Ol0Wq2Ww+HgLeQVBHDJ5s2b+Xz+iBEj8BbScCFATa5Wq+HskXQSGo1m3LhxeKv4DwSISyZOnEihWM+PXi9hMpklJSWVlZXwTH4mQIvTAJHJZGw2G55cLPC6pGfPnlQq1WQyqdVqCoXCZDJNJhOTyWwID4dhA964xMPDo7y8XCqVqtVqhUIhFoslEkl9mmBhg1WrVkE1DBZel4wZM4bJ/M9SCHw+f+zYsfgpch18Pr+srAxvFa+At8UBAIwePTonJ8fytnXr1ps3b8ZVkYvAsr/D05cIiw6rjBo1ik6nY695PN748ePxVuQiSCQSPBaB3SWDBg0KCgrCXjdu3BiqTmuncv/+/RkzZuCt4hVQuwQAMHLkSDqdzuVyYetociocDqe8vBxvFa9wfFxSJTWYTI4sc+bMmUKh8Pvvv3dgmVQqmc2Ht6fObDYrlUp4pkM70iXnD5Zn36ryCXWrKNE5qkwnwRPRyl9omsRw44eI8NZCABzjEr3OvGPxs85DfTwDmXQm7K0YhlZlLHqizrxWMeLTQDJ81Ur//v2PHDkCSferY37R33/IGzgj2D+cRRSLAAAYLEpopHvrnqIDKwvw1mIFlUqlUqnwVvESB9QlGacrKAxKeDRRp8w8uFzJ4ZNbdIJLv06ns/QC4I4D/voFOSoO3/rK54SAxaO8eKLGW8XrkEgQdXg6wCVkCpnvyXCEGHzw8GaY4MtqNnHiRHhW+3OAS6TFGnhc/xaYjGZZOXRLIgsEAnhS8kERQiPeBKrl2whzS9LQUCgU8Kw+iFwCKYsWLYJkPWTkEnjhcrnwjPZFcQmkLF68GG8Jr0B1CaSoVCqdDpbHYcglkLJ8+XJ4Ensil0AKi8VCcQnCDvPnz8dbwitQXQIpBoMBnr5X5BJIWb58OTzz0/BxiUKhyM55/I6FTJ4y4rvvv3KQIuggk8kmkwlvFS/BJy6ZOm1Uh/ad3wtvisvZCcGCBQvwlvAKfOoSeHoCELUBh7pk1JgBFRXSv48c/PvIQW9vn317jmHB2vYdG0+nHJPJKoODQydNnB7XqSu2f+ajBxs3rcrKymQy3Tp2iP/oo0+4nNfHlWk0mlVrll+9ehEAEBUVnTRzno+Pr+u/mgP5+eefGzduPGTIELyFAHxcsvjbn774MqlVyzbDh42l/f+gvV9W/HA29eS4sR+EhDQ6m3rym0XzVq/8LSoqOi/v6WfzZoSENPri829llRXbd2wsKytZ8cuG18rcs3f76dPHJk+aIRSKTqccc3Nzc/33cixQ3ePg4JKmTSKoVKpQKIqMbIVtef4873TKsQnjp06aOB0A0CW+x7gJQ3bs3PTrio27dm8lk8k//biO484BAHA43KXLF929e6tly9bVyywuKXJzcxszehKVSu2fMNj1X8rhzJ07F55JoFDouHvvFgAgLq4b9pZEIsXGtM/KzgQA3Ll7Mzo6FrMIACA2tgMAAPuoOj179NNoNF/On/30aa7L5TsFNzc3BgOWcaJQuESpVAAABHwPyxYul6dSqZRKpVKp4PNerYzJ4XABAGLx67Mj27XtuGzpammFZMqHo35Z8QM843femvXr1584cQJvFS/BzSXVh8qKRF4AALlcZtkilUqoVCqTyRSJvKpvr6iQAgDc3a1kuWzXtuPW3/bN/OiT4yf+3rtvp/O/gXORy+XwzMfBxyVuTDeJRGx526xZCxKJlHb9MvZWp9OlXb/cvHkUhUJp3jzqzt2blhyNFy+mAgCwgIZOo1dVyS2HYD1Rw4eNFYk8c965yw53kpKS+vfvj7eKl+DTqxYZGZ167tSevTs4HG7ziKiwsMZ9eg/YsXOT0Wj08ws4fvywVCpZ8NX3AIBxYz44d+70l1/NHjjg/bKykp2/b45uFdOqZRsAQOPGTU6cPLI++ddpH84+dHjflasXevVMkEjKxeLyJk0icPleDgSqrMCUdx8Tdfvfyvfa8GiMOlRLzZtH5eZmnTl7IifncdOmzYODQmNjOiiVipOnjpw7d5rNYs/7bCEWqHK5vMgW0Rk3rv1z7K+s7Efduvb+fN4iLKyLaBZZVFR4+fK/gwePVCir7t65eTb1ZF7+0379EidNnF77GwS1wliYpWzRife2F8AprF+/XiwWh4eH4y0EOGYG6LZFzwZMC3LjwDIYoq5Ii7XXjpaO+iIIbyH/YdmyZeHh4ZCs5IHGl0BKUlISJAkHkEvgBaq4BIr+EsSboP4ShH2g6i9BLQ6koLgEYR8UlyDsg+IShH1QXIKwD4pLEPZBcQnCPiguQdgHxSUI+9S3uETkzyB0lUSikPlesIwwtVDf4hKT0VxRAl0mzNojKdJQ4EtqXN/ikqCm7Cqp3hFi8EElNwSEs/BW8TpQxSWOSWO9a1l+uwQvnxDizZXKvV2V91A+ZJY/3kJep6qqikqlQjL9zDEuMZvBnuXPW3QWCH2ZPBF81bc1Kst0JXmq4qeqxGl+gIS3GrhxZEr8tJPS3DtVLA61vEDjqDIBACaTmQQAiezIX9LDh6HXmd5rw4npKajF7jiwfv360NDQhIQEvIUAB98Jt+/n0b6fh8EAzEZHpqVPTk7m8/ljxoxxYJkUKgnClZOqA1Vc4vg7cioVAKpDa3CygUQx0hgNq1Wob/0lCGdQ3/pLnA2bzYYk1HclUPWXEKAuUSqV8KxN5jLqeVzicHg8HpvNxluFq0FxSd2QyWTw5HtxGSguqRsNsy5BcUndaJh1CYpL6gaDwaDRiNHr70BQXFI3tFqtXk/gZ85vB4pLEPaBKi4hgEvc3d1ZLOjGfzgbFJfUDYVCgeISfIFFhw1oNBo818tloLikbuj1+nqQv7WuoLgEYR8Ul9SNhtn3iuKSutEw+15RXIKwD4pL6gaZTG6AdQmKS+qGyWSCZ51Dl4HikrrB5XIbYPSK4pK6IZfLlUol3ipcDYpLEPahUCgOnFD3jhCgxWmYjB07FsUldYDFYjGZTLxVuBoUl9QNlUplWWur4YDiEoR9UH8Jwj6ov6RuNMynfSguqRsymQz1l+ALAVzSMEFxSd3gcDgNcHQ0ikvqBpaHDm8VrgbFJQj7oLikbnA4nAZ4j4PikrrR78h4AAAVFElEQVTRMFscFJfUDTqd3gBzIaG4pG7odDqdToe3CleD4hKEfVBcUjca5uhoqOISR2YYdyzDhw9/+vQpifQfhWFhYQcPHsRVV0ME3v/ogAEDsFQDpP+HwWCMGzcOb10uAsUltWLYsGEBAQHVtwQHBw8aNAg/RS4FqrgEXpew2ezExEQKhWJ5O3LkSLxFuY6kpKT+/fvjreIl8LrkteokODh48ODBeCtyHRwOB5686lC7hMViJSYmUqlUFos1bNgwvOW4FBSX1IH333/f398/ICAgMTERby0uBaq4xM6dcHmh9ta5ytJ8jVqBWzYio9FIIpHw6jJhsqgUGvANdYvtLeAKXZfejTDr9uVlqq4dk7Ts6sH3pLu5w9LD42JIJKCQGeQSfcapsr4Tfb2DoVt52AXU6JJH6VWPb1T1HOvncknwcmJLYYf+HkFNXTFwDqp1+6xX4xqVKQtZ5A36Tg64cabCNZ3VUMUl1tuR4mdqx665WT8gU4BOayov0HoFOb3dgeo5jvW6RC42+ARDETfBhl8jVkWp1gUnIkB/iVZt1GkbXPqh2qBVmXQ6VzQ5qL8EYR8CxCUI3IEqLoFFB+I10LhXhH1QXIKwD4pLEPZBcQnCPiguQdgHxSUI+6C4BGEfFJcg7IPiEoR9UFziIoxG4/37d/BW8ZaguMRF/Lzi+6yszO1bD+At5G2AKi5xVl1SWPjcSSVXx/bQbp3WFQNBnARU40sc5laJRLx23c83b16n0mht2rS7eDF104ZdoaGNAABHjv554OAusbjMx8evR/e+I0eMZzAYOblZs+d8sHzpms1b1j55ku3t7Tv9wzmdOnXBSisuKUpO/vXmret0OuO98KYffDCzaZMIAMDqNT9euJg679OFyRtXvnhR8MvPyYEBwVu3J1+/fkWpVAQGBo8ZPblnj74AgOU/Lf73/BkAQLceMQCAPbuP+vr4AQBu37nx25Z1T55kCwQe0a1ip06ZJRSKHHURHAhU414d4xKj0bjg67nSCsnHH8+XSsW/bVkX3SoGs8iOnZsP/rlr6JBRwcFhBQV5+w/8Xvji+YL53wEAtFrt/76fPzvpc18fv+07Nv6w9Ot9e47xeHyJRDx7zgf+/oFJs+aRSKSUlOMfz526MfkPrEClUrF1e/Lcj+drNOrW0bHFJUWPHz8clDiMx+VfvHxuydKF/v6BzZo2Hzfmg/Ky0uLiF1/N/w4AIPQQAQBu3kqf/9WcXj0ThgweWSWX/XVo76fzZmzasAvCNTPqYVzy6NGD7JzH3y5a3rVLTwDA8+d5J08d1el0crls955tC79e0iW+B7anUOi5ctWypFnzsLezkz7v3q03AGDq1KTpM8bdvXcrvnP3P3ZtEfA9Vvy8AWuYe/VMGDdh8LETh2fPmoelRpr36cJmzVpgJfj5+u/YdpBEIgEA+vUbNOT9nleunG/WtHlAQBCPx5dWSCIjW1l0rl3388ABQ+fM/gJ7GxPTfuLkYRk3rnWO6+aQ6+BAoIpLHKOjrLwUAODn93JOb0BAkMlkUqtVN29eNxgMS5YuXLJ0IfYRFkmIy8uwt27Ml02vt7cvAEAsLgcAXL9+pay8NGFAZ0v5er2+vKwUe81kMi0Wwch9kr1j56asrEysVpNKJVZFlpQU5+c/e/Gi4Njxw/8R//8lQwVU/SWOcYm/fyAA4P79O++FN8WqFpHIk8fjS6RiAMDSJau8PL2r7+/nF/As70n1LTQqDQBgMhkBANIKSYcOnadNnV19BzbbHXvh5vaf6TC3bmd8OX92dKuYLz7/ls1iL1r8uclsfcRuRYUEADBxwrT4zt2rb/fwQHGJHRzjkibvNYuNab/5tzWlpcWVsoorVy8s/HoJAIDD4WI7BAWF1L40Docrk1XW8pA//tji5xewdMkqrH62VE4Y1W+C3N05AACtVlMnMXgBVVzisDvh2UmfBwQEFRTm83mCdWu3YwFKdHQsiUQ6/Pd+y25qtdpuUa1bt33w4G5W9qPaHCWTVzZu9B5mEZ1Op1KrLIsPM5luUqnE8jYgIMjb2+fkqaOW0gwGg16vf4cv7URmzpzZr18/vFW8hLJ48eI3t77IVRsNwCe0tvfrBoNhwqShCf0Gt2rZxtPTCwDA4/LpdDqXy6uqqkpJOZ6d80ir1aZdv7J0+TfR0bFCoUgqlfxz7FCP7n0DA4OxyGPP3u1tYztERESGhYWfOXvizJkTRqOxoDB/9+5tFy6ldu/WBwtZ8vOfjRwx3nLq/Od5Fy6cFQg8SktLVq1Z/uJFAQmAAQOGkkgkhaLq3L+nJZLyqip5WVlJUFCIt7fviRNHrl67aDaDzMz7a9b+pDfoIyIia3+9CrNV7nyKd5DT74mYTCY8WW4d0+JQqdSYNu3/2LXFYHiZmoDjzlmzemtISNismZ96eXkfPrw/I+OaUCjqHNfNU+RluzR/v4B1a7Zt2LRq955tJBIpPLzpkME1ZkH6YNJHUol47bqfORzugP5DRwwb9+uqpbfv3GgdHdurV0JWdmbKmePX0i717TOwY8f4znHdli1ZtX3HxvXJK9hs96jI6Kio1g65Ag5n06ZNwcHBffv2xVsIqHE2efopqVYDWnXzqH1BRqMRy25lNpuLil9M/XDUiOHjJk+a4VC1+JN2rNwnhB7ZiefsEy1btiw8PByS3D6OqUu0Wu3MpIleXj4to1rTaPT7929rNJpGjd5zSOENkxkzZmApKmHAMS4hkUi9e/U/d+709h0b6XR6aGjjbxctf+2GE1EnBAIB3hJe4RiX0On0kSPGVw8qEe9IcnJyeHh4r1698BYC6vn4EkIjlUoVCgXeKl4Cy5MCxGskJSXVtzthhMPh8/l4S3gFanEgZdWqVampqXireAlyCaRIpVKNRoO3ipegFgdSZs2aBc+alsglkOLt7V2LvVwEanEgZc2aNTdu3MBbxUuQSyDl6dOntRll4RqstzhUOtkMIF2pDV8YLDKF6opMuHPnzhWJYBlEZ70uYfMokuIGtzhrbSgv1HAFrngIFxIS4u7u7oIT1QbrLhH6MMwmVJdYgUIhefi4YsGC77777vHjxy44UW2w7hKRP91dQLl7QepyPVBz/US5f7gbi+uKYC43N9doNLrgRLXB1son5/8sN5vJrbp6UOkNPSe9TmPKOC0W+tJje7mo47ykpEQoFEIyxMTOKko3z1bcvyIjkUlu7hQXqvoPZpMJAEDCaRUlOoNcUaZzc6e06MBt4fwhanBif9VpsxnIJXqlHLe1tg4ePMjhcPAaAUoCwF1Ac+dRSa516fTp05cuXSoUCl161hqw3/dKIgGeiMYT4Vf1MSuo7sAvDJYJ+K4hKysLnpEDqFcNUlavXg3PJFACuIRGo8Ezr9pltGzZEm8JryCAS/R6vWWaTwNBqVTOnz8fbxWvIIBLOBwOi+WKBRXhoaKiAp4uNWKMHFAqlXgtJowXAoHghx9+wFvFKwjgEh6PB0+07xrYbHaLFi1qsaOLIMB/VKfTVVZW4q3CpaSlpa1duxZvFa8ggEsYDAY8I0BdQ15eHlRfmQAtDovFevHiBd4qXEr//v2xTHGQQACXsNlseGa5uQZ4+tMwCNDiCAQC2K6as1m3bl1mZibeKl5BAJfweLz79+/jrcKlnD9/Hp7E0cRwiUgkEovFeKtwKZ988klwcDDeKl5BDJfodDpLEr2GQKdOnaDqSIRIig34fH5BQQHeKlzEo0ePVqxYgbeK/0AMl7Rp06akpARvFS7i7t27doeGuRgC3AljAWxmZma7du3wFuIKEhMTYRspQYy6pGnTplA9I3UqLBYLtudWxHBJZGRkRUUF3ipcgUajGTFiBN4qXocYLvH29q6oqHj69CneQpzO9evXAwIC8FbxOvbH0EPC1q1bPTw8hgwZgrcQ51JZWUmlUuGZ+4lBjLoEANCrV6/ff/8dbxVOh81mw5PcxgJhXBIUFBQQEHD16lW8hTiRe/fuTZs2DaqnwRiEcQkAYNSoUfv27cNbhRO5d+/exIkT8VZhBcLEJRjDhw9fuXIlhPFd/YZIdQmWk27lypV4q3AKhYWFubm5eKuwDsFc0rVrVxqNdubMGbyFOJ7Ro0f7+fnhrcI6BGtxsIV4OnTokJ6ejrcQR5KVlaXX66EaN18d4rkEAJCSkvL48eM5c+bgLaShQLAWB6N37956vX7Pnj14C3EMn3322YMHD/BWYQtC1iUYSUlJ48aNa9++Pd5C3omTJ0+azWZI1g2uCQK7BAAwduzYVatWeXp64i2knkPIFsfC7t27BwwYQNCMBEVFRV9//TXeKmoFsV0CALh48WJ8fDzeKupMVVXVhg0blixZgreQWkHsFgejsrJy3rx5W7ZswVtIvYXwdQk2dnrJkiWQB4AWDAYDJKsE1wFzfaGgoCAxMRFvFfb58ssvTSYT3irqRn1ocSzk5+cnJyf/+OOPeAupb9SHFsdCcHDwlClTRo8ejbcQ6wwfPlypVOKt4q3AuzJzPA8fPvzss8+qbxk5cqTrZbx20oMHD6rVatfLcAj1qi7BiIiIGDt27NSpU7G3/fv3z8/PP3z4sCs1rF27Njc3d/jw4ZYtw4YNYzKZrtTgQOpVXFKdGzduHD16NCcnJycnBwDQpUsXV06rHD16dHZ2NolE8vHxcXd3X7Fihb+/v8vO7nDqYV2CERMTk5GRgVkEW+CsrKzMNad++PChTCbDhq+WlJTo9XpCW6Q+uyQxMbG8vNzyViKR3Lx50zWnvnz5cmlpqeVtfn4+UfpyaqJ+uqRfv36vpWJTqVSXLl1yzdmvXLny2paysrL+/fu75uzOoH665OTJkx06dAgMDKRQKJbA6+HDh3K53NmnzsnJqaiosMyWoFKp/v7+nTt3Pn78uLNP7TzgmtvuQNatW5ebm3v58mWs/i8uLpZKpTdv3uzWrZtTz5uenl5SUkIikby9vQMDA+Pj4+Pi4gIDA516UmdTT+5xzGbw7KGq7LlGITMoZUYKlayU6S2farQapVKpqKpisVienl5OVVJUXGQ0GNju7u5sNp3+ah1IrpCm15nYXCpPRPUKZAQ1IVJmfcK75Mld5b3Lshe5KoG/O41JozIoVDqFRqeazHBl2CKTyHqtwaAzGPRmrVxdJdEENWW3jOcFvgdRlr2aILBLnj9WXTgkZnLcmDwmx5NIf00AgNlklpeplBIljWbqMlTkFeiK1WffGqK65MSOMnGR3quxB5MDV0KYuqKQqMufSIObsbuPgGKJPqsQzyUmE/hjSb4gyIPrRbD6wwbSArlJoxo2B9LON4K5xGgw/77kuV9zbwYbioV2HYhCotZI5cPmwDi9j2D9Jb99/SyotV/9swgAwF3o5ibi7f4RxoSlRKpL9v9ayPEVsPhEfbJaG2QlVQyKtu8Eb7yF/AfC1CXpKRVuAvf6bREAAM+Ho1FTHmc4vY+4ThDDJVq16VZqBdenQaxswfHlXTwEV959Yrjk0mGxd2MPvFW4CAqNzPfj3DgLUeZSArhEVWUsLdAJAmCsSK7fODLvm3ZyuYP/+qJQQdZNiEbIEsAleQ+VZFo9vKmxAZlCMhrAi1w13kJeQgCX5NxRsoX1pwOtlrCErCf3YFmHjgAjB9RKk0+wU1yi02lOnt1w+95pvV7rKQruGje2VWQvAMDFq3vv3D8b33H0ybMbqqrE/n5Nhw/6ysszBDvqRVHW3yd+LXiRyeWIPIVBzhAGAOB6sqWlUicVXldgd4laYZSJtT5OKNlkMm3b/VlFRXH3+Inu7h5Pnt7cdWChVqdu1yYRAPC88MGFK7uHD1pgNBr+PLps36Hv5kzfBgAoLc/bsO0jNouf0GsmhUw9c36rE6QBAACVQSl+qnJS4XUFdpco5UY60yki72f++yzvzoLP/uZxPQEAraP6aHWqy9f2Yy4BAEwe+wuXIwQAxLUf8c+p1UqVjM3iHT+9lkQiz56+1Z0tAACQyORD//zkDHlkColEAjqNic7EPyqA3SVqucFJT30fZV0xmgxLf32V2N5kMroxXyWAZ9BfjvwQ8H0BAHJ5OY3KyMpN6xD7PmYRAACF7MQLyBExlXIjcol9yFSSXuOUJDZVCgmXI5oxef1/TmftV6dSaJiH5FVio9HgIfB1hp43Ucv1VCoU2cZhdwmbR9VrjM4omeXGVSgrBHxfGq22I4CwKkShcFF/l1ZlYPOg+IHwr81sw+ZSdWqn1CWNG8WaTMar6X9Ztmh1dvonmEy2SBh492GqwaC3vee7Y9SbaAwymeLs89QKKKxqAxqDxPdkGLRGKsPBF6xNy37Xb/x97PTaispif98mRSU59zPPfzFnP51u64Fi725T9/z57drNU9u2HkAiky9d2+9YVRa0Sr1PCCxDYmF3CQDAN5QhLVN6BHIdWyyVSvtw4poTKetv30u5lnHYUxjUse1QCsXOBWndsq9aXXX+yu5jKWu9PcOCA1uUi/MdKwxDIVaGt4DlATgBxpc8z1Jd/LsiIMoZnSbw8uRawbA5/jwRFI8mCFCXBDVhUakVJoOZXEPAbzabv1na0+pH7iy+QlX55vbmTeNHv/+tA0Wu3zK9uNTKihR8rnelvPTN7Tyu1+ez99ZUmkah8wpgQmIRYtQlAIAHV2SZNzVe4aKadpBWFFndbjDoqVQr15pOd7P0eTgEmbzcaLQS0tYkgEym8Hk1DkgrvFvSdahHADRTdQhQlwAAWnTiZZyp0KkNdDfrgj0EOA8qxjpwHYJConZjA3gsQoA7YQs9RnlVlcjwVuEKVOKqHiOdO021rhDGJUFNWcHhNPFTWB6TOomih6Wtu3L4XrBEJBiEcQkAIKaXgMc3lz2BaKifYynKFDeOdGvcCq7FhAkTvVbn3AGxpBx4hjky9oSBoszyiFhWq3gHdws5BOK5BACQdkKan60XhnpQ6USqC2tCq9SXZIljenCbt4fRIkR1CQDg6X3l2b2lAj+OZ5gHgOK56dtg1JnKn0q0Cm3CZF/PAHinxRPVJRi3/63MvF5FZdAYPBbXi0WmEMMvBp1JUa5UV6oMOkNsT0HTtjBOD6gOsV2CZUHKva14cl9RmK0mU8lUBoVCo9CYdIPeKeMN3hoqg6JX6Yw6o9ls0qkMYVHuYZHs0OZsvHXVCsK7pDqV5XqlzKCSG/U6k0EPVy4kGoNCo5PYPCqLS+UJidGZaaFeuQThJOrDPQLC2SCXIOyDXIKwD3IJwj7IJQj7IJcg7PN/PioelnZIG1UAAAAASUVORK5CYII=", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "config = {\"configurable\": {\"thread_id\": \"abc123\"}}\n", + "from IPython.display import Image, display\n", "\n", - "result = app.invoke(\n", - " {\"input\": \"What is Task Decomposition?\"},\n", - " config=config,\n", - ")\n", - "print(result[\"answer\"])" + "display(Image(graph.get_graph().draw_mermaid_png()))" ] }, { - "cell_type": "code", - "execution_count": 11, - "id": "0e89c75f-7ad7-4331-a2fe-57579eb8f840", + "cell_type": "markdown", + "id": "973eb33b-f078-497d-bbbf-998963695b43", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "One way of task decomposition is by using Large Language Models (LLMs) with simple prompting, such as providing instructions like \"Steps for XYZ\" or asking about subgoals for achieving a specific task. This method leverages the power of LLMs to break down tasks into smaller components for easier handling. Additionally, task decomposition can also be done using task-specific instructions tailored to the nature of the task, like requesting a story outline for writing a novel.\n" - ] - } - ], "source": [ - "result = app.invoke(\n", - " {\"input\": \"What is one way of doing it?\"},\n", - " config=config,\n", - ")\n", - "print(result[\"answer\"])" + "Let's test our application.\n", + "\n", + "Note that it responds appropriately to messages that do not require an additional retrieval step:" ] }, { - "cell_type": "markdown", - "id": "3ab59258-84bc-4904-880e-2ebfebbca563", + "cell_type": "code", + "execution_count": 11, + "id": "4d7911cc-c075-46bc-af7b-88a2e2a2551e", "metadata": {}, + "outputs": [], "source": [ - "The conversation history can be inspected via the state of the application:" + "# Specify an ID for the thread\n", + "config = {\"configurable\": {\"thread_id\": \"abc123\"}}" ] }, { "cell_type": "code", "execution_count": 12, - "id": "7686b874-3a85-499f-82b5-28a85c4c768c", + "id": "e59541dd-405b-4032-847f-73becf6aefd0", "metadata": {}, "outputs": [ { @@ -437,515 +390,393 @@ "text": [ "================================\u001b[1m Human Message \u001b[0m=================================\n", "\n", - "What is Task Decomposition?\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Task decomposition is a technique used to break down complex tasks into smaller and simpler steps. This process helps agents or models tackle difficult tasks by dividing them into more manageable subtasks. Task decomposition can be achieved through methods like Chain of Thought (CoT) or Tree of Thoughts, which guide the agent in thinking step by step or exploring multiple reasoning possibilities at each step.\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What is one way of doing it?\n", + "Hello\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "One way of task decomposition is by using Large Language Models (LLMs) with simple prompting, such as providing instructions like \"Steps for XYZ\" or asking about subgoals for achieving a specific task. This method leverages the power of LLMs to break down tasks into smaller components for easier handling. Additionally, task decomposition can also be done using task-specific instructions tailored to the nature of the task, like requesting a story outline for writing a novel.\n" + "Hello! How can I assist you today?\n" ] } ], "source": [ - "chat_history = app.get_state(config).values[\"chat_history\"]\n", - "for message in chat_history:\n", - " message.pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "0ab1ded4-76d9-453f-9b9b-db9a4560c737", - "metadata": {}, - "source": [ - "### Tying it together" + "input_message = \"Hello\"\n", + "\n", + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", + " config=config,\n", + "):\n", + " step[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", - "id": "8a08a5ea-df5b-4547-93c6-2a3940dd5c3e", + "id": "d28f25f4-1caa-4997-a886-888d55034995", "metadata": {}, "source": [ - "![](../../static/img/conversational_retrieval_chain.png)\n", - "\n", - "For convenience, we tie together all of the necessary steps in a single code cell:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "71c32048-1a41-465f-a9e2-c4affc332fd9", - "metadata": {}, - "outputs": [], - "source": [ - "from typing import Sequence\n", - "\n", - "import bs4\n", - "from langchain.chains import create_history_aware_retriever, create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", - "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.messages import AIMessage, BaseMessage, HumanMessage\n", - "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n", - "from langchain_core.runnables.history import RunnableWithMessageHistory\n", - "from langchain_core.vectorstores import InMemoryVectorStore\n", - "from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "from langgraph.checkpoint.memory import MemorySaver\n", - "from langgraph.graph import START, StateGraph\n", - "from langgraph.graph.message import add_messages\n", - "from typing_extensions import Annotated, TypedDict\n", - "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n", - "\n", - "\n", - "### Construct retriever ###\n", - "loader = WebBaseLoader(\n", - " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", - " bs_kwargs=dict(\n", - " parse_only=bs4.SoupStrainer(\n", - " class_=(\"post-content\", \"post-title\", \"post-header\")\n", - " )\n", - " ),\n", - ")\n", - "docs = loader.load()\n", - "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "\n", - "vectorstore = InMemoryVectorStore(embedding=OpenAIEmbeddings())\n", - "vectorstore.add_documents(documents=splits)\n", - "retriever = vectorstore.as_retriever()\n", - "\n", - "\n", - "### Contextualize question ###\n", - "contextualize_q_system_prompt = (\n", - " \"Given a chat history and the latest user question \"\n", - " \"which might reference context in the chat history, \"\n", - " \"formulate a standalone question which can be understood \"\n", - " \"without the chat history. Do NOT answer the question, \"\n", - " \"just reformulate it if needed and otherwise return it as is.\"\n", - ")\n", - "contextualize_q_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", contextualize_q_system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "history_aware_retriever = create_history_aware_retriever(\n", - " llm, retriever, contextualize_q_prompt\n", - ")\n", - "\n", - "\n", - "### Answer question ###\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "qa_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)\n", - "\n", - "rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)\n", - "\n", - "\n", - "### Statefully manage chat history ###\n", - "\n", - "\n", - "# We define a dict representing the state of the application.\n", - "# This state has the same input and output keys as `rag_chain`.\n", - "class State(TypedDict):\n", - " input: str\n", - " chat_history: Annotated[Sequence[BaseMessage], add_messages]\n", - " context: str\n", - " answer: str\n", - "\n", - "\n", - "# We then define a simple node that runs the `rag_chain`.\n", - "# The `return` values of the node update the graph state, so here we just\n", - "# update the chat history with the input message and response.\n", - "def call_model(state: State):\n", - " response = rag_chain.invoke(state)\n", - " return {\n", - " \"chat_history\": [\n", - " HumanMessage(state[\"input\"]),\n", - " AIMessage(response[\"answer\"]),\n", - " ],\n", - " \"context\": response[\"context\"],\n", - " \"answer\": response[\"answer\"],\n", - " }\n", - "\n", - "\n", - "# Our graph consists only of one node:\n", - "workflow = StateGraph(state_schema=State)\n", - "workflow.add_edge(START, \"model\")\n", - "workflow.add_node(\"model\", call_model)\n", - "\n", - "# Finally, we compile the graph with a checkpointer object.\n", - "# This persists the state, in this case in memory.\n", - "memory = MemorySaver()\n", - "app = workflow.compile(checkpointer=memory)" + "And when executing a search, we can stream the steps to observe the query generation, retrieval, and answer generation:" ] }, { "cell_type": "code", "execution_count": 14, - "id": "6d0a7a73-d151-47d9-9e99-b4f3291c0322", + "id": "1fdbb4bb-8a28-47d9-b3db-1cd9a543ebc4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Task decomposition is a technique used to break down complex tasks into smaller and simpler steps. This process helps agents or models handle difficult tasks by dividing them into more manageable subtasks. Different methods like Chain of Thought and Tree of Thoughts are used to decompose tasks into multiple steps, enhancing performance and aiding in the interpretation of the thinking process.\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What is Task Decomposition?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_RntwX5GMt531biEE9MqSbgLV)\n", + " Call ID: call_RntwX5GMt531biEE9MqSbgLV\n", + " Args:\n", + " query: Task Decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Task Decomposition is the process of breaking down a complicated task into smaller, more manageable steps. It often involves techniques like Chain of Thought (CoT), where the model is prompted to \"think step by step,\" allowing for better handling of complex tasks. This approach enhances model performance and provides insight into the model's reasoning process.\n" ] } ], "source": [ - "config = {\"configurable\": {\"thread_id\": \"abc123\"}}\n", + "input_message = \"What is Task Decomposition?\"\n", "\n", - "result = app.invoke(\n", - " {\"input\": \"What is Task Decomposition?\"},\n", + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", " config=config,\n", - ")\n", - "print(result[\"answer\"])" + "):\n", + " step[\"messages\"][-1].pretty_print()" + ] + }, + { + "cell_type": "markdown", + "id": "06e285cc-7a03-4038-aad0-558efc768bdd", + "metadata": {}, + "source": [ + "Finally, because we have compiled our application with a [checkpointer](https://langchain-ai.github.io/langgraph/concepts/persistence/), historical messages are maintained in the state. This allows the model to contextualize user queries:" ] }, { "cell_type": "code", "execution_count": 15, - "id": "17021822-896a-4513-a17d-1d20b1c5381c", + "id": "f48c5f7b-5281-4a03-84ed-d2e0cbd228a2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "One way of task decomposition is by using Large Language Models (LLMs) with simple prompting, such as providing instructions like \"Steps for XYZ\" or asking about subgoals for achieving a specific task. This method leverages the power of LLMs to break down tasks into smaller components for easier handling and processing.\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Can you look up some common ways of doing it?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_kwO5rYPyJ0MftYKoKRFjKpZM)\n", + " Call ID: call_kwO5rYPyJ0MftYKoKRFjKpZM\n", + " Args:\n", + " query: common methods for task decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Common ways of Task Decomposition include: (1) using large language models (LLMs) with simple prompts like \"Steps for XYZ\" or \"What are the subgoals for achieving XYZ?\"; (2) utilizing task-specific instructions, such as \"Write a story outline\" for creative tasks; and (3) incorporating human inputs to guide the decomposition process.\n" ] } ], "source": [ - "result = app.invoke(\n", - " {\"input\": \"What is one way of doing it?\"},\n", - " config=config,\n", - ")\n", - "print(result[\"answer\"])" - ] - }, - { - "cell_type": "markdown", - "id": "861da8ed-d890-4fdc-a3bf-30433db61e0d", - "metadata": {}, - "source": [ - "## Agents {#agents}\n", - "\n", - "Agents leverage the reasoning capabilities of LLMs to make decisions during execution. Using agents allow you to offload some discretion over the retrieval process. Although their behavior is less predictable than chains, they offer some advantages in this context:\n", - "- Agents generate the input to the retriever directly, without necessarily needing us to explicitly build in contextualization, as we did above;\n", - "- Agents can execute multiple retrieval steps in service of a query, or refrain from executing a retrieval step altogether (e.g., in response to a generic greeting from a user).\n", - "\n", - "### Retrieval tool\n", - "\n", - "Agents can access \"tools\" and manage their execution. In this case, we will convert our retriever into a LangChain tool to be wielded by the agent:" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "809cc747-2135-40a2-8e73-e4556343ee64", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain.tools.retriever import create_retriever_tool\n", + "input_message = \"Can you look up some common ways of doing it?\"\n", "\n", - "tool = create_retriever_tool(\n", - " retriever,\n", - " \"blog_post_retriever\",\n", - " \"Searches and returns excerpts from the Autonomous Agents blog post.\",\n", - ")\n", - "tools = [tool]" + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", + " config=config,\n", + "):\n", + " step[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", - "id": "f77e0217-28be-4b8b-b4c4-9cc4ed5ec201", + "id": "8e8f8d1e-0255-4b14-81e5-8f5c015194a2", "metadata": {}, "source": [ - "### Agent constructor\n", + "Note that we can observe the full sequence of messages sent to the chat model-- including tool calls and retrieved context-- in the [LangSmith trace](https://smith.langchain.com/public/3c85919e-9609-4a0d-8df1-21726f8f3e5c/r).\n", "\n", - "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/architecture/#langgraph) to construct the agent. \n", - "Currently we are using a high level interface to construct the agent, but the nice thing about LangGraph is that this high-level interface is backed by a low-level, highly controllable API in case you want to modify the agent logic." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "1726d151-4653-4c72-a187-a14840add526", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.prebuilt import create_react_agent\n", - "\n", - "agent_executor = create_react_agent(llm, tools)" - ] - }, - { - "cell_type": "markdown", - "id": "6d5152ca-1c3b-4f58-bb28-f31c0be7ba66", - "metadata": {}, - "source": [ - "We can now try it out. Note that so far it is not stateful (we still need to add in memory)" + "The conversation history can also be inspected via the state of the application:" ] }, { "cell_type": "code", "execution_count": 18, - "id": "52ae46d9-43f7-481b-96d5-df750be3ad65", + "id": "7686b874-3a85-499f-82b5-28a85c4c768c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'agent': {'messages': [AIMessage(content='Task decomposition is a problem-solving strategy that involves breaking down a complex task or problem into smaller, more manageable subtasks. By decomposing a task into smaller components, it becomes easier to understand, analyze, and solve the overall problem. This approach allows individuals to focus on one specific aspect of the task at a time, leading to a more systematic and organized problem-solving process. Task decomposition is commonly used in various fields such as project management, software development, and engineering to simplify complex tasks and improve efficiency.', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 102, 'prompt_tokens': 68, 'total_tokens': 170, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-a0925ffd-f500-4677-a108-c7015987e9ae-0', usage_metadata={'input_tokens': 68, 'output_tokens': 102, 'total_tokens': 170})]}}\n", - "----\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Hello\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hello! How can I assist you today?\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What is Task Decomposition?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_RntwX5GMt531biEE9MqSbgLV)\n", + " Call ID: call_RntwX5GMt531biEE9MqSbgLV\n", + " Args:\n", + " query: Task Decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Task Decomposition is the process of breaking down a complicated task into smaller, more manageable steps. It often involves techniques like Chain of Thought (CoT), where the model is prompted to \"think step by step,\" allowing for better handling of complex tasks. This approach enhances model performance and provides insight into the model's reasoning process.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Can you look up some common ways of doing it?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_kwO5rYPyJ0MftYKoKRFjKpZM)\n", + " Call ID: call_kwO5rYPyJ0MftYKoKRFjKpZM\n", + " Args:\n", + " query: common methods for task decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Common ways of Task Decomposition include: (1) using large language models (LLMs) with simple prompts like \"Steps for XYZ\" or \"What are the subgoals for achieving XYZ?\"; (2) utilizing task-specific instructions, such as \"Write a story outline\" for creative tasks; and (3) incorporating human inputs to guide the decomposition process.\n" ] } ], "source": [ - "from langchain_core.messages import HumanMessage\n", - "\n", - "query = \"What is Task Decomposition?\"\n", - "\n", - "for s in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=query)]},\n", - "):\n", - " print(s)\n", - " print(\"----\")" + "chat_history = graph.get_state(config).values[\"messages\"]\n", + "for message in chat_history:\n", + " message.pretty_print()" ] }, { "cell_type": "markdown", - "id": "1df703b1-aad6-48fb-b6fa-703e32ea88b9", + "id": "861da8ed-d890-4fdc-a3bf-30433db61e0d", "metadata": {}, "source": [ - "LangGraph comes with built in persistence, so we don't need to use ChatMessageHistory! Rather, we can pass in a checkpointer to our LangGraph agent directly.\n", + "## Agents {#agents}\n", "\n", - "Distinct conversations are managed by specifying a key for a conversation thread in the config dict, as shown below." + "[Agents](/docs/concepts/agents) leverage the reasoning capabilities of LLMs to make decisions during execution. Using agents allows you to offload additional discretion over the retrieval process. Although their behavior is less predictable than the above \"chain\", they are able to execute multiple retrieval steps in service of a query, or iterate on a single search.\n", + "\n", + "Below we assemble a minimal RAG agent. Using LangGraph's [pre-built ReAct agent constructor](https://langchain-ai.github.io/langgraph/how-tos/#langgraph.prebuilt.chat_agent_executor.create_react_agent), we can do this in one line.\n", + "\n", + ":::tip\n", + "\n", + "Check out LangGraph's [Agentic RAG](https://langchain-ai.github.io/langgraph/tutorials/rag/langgraph_agentic_rag/) tutorial for more advanced formulations.\n", + "\n", + ":::" ] }, { "cell_type": "code", "execution_count": 19, - "id": "837a401e-9757-4d0e-a0da-24fa097d887e", + "id": "809cc747-2135-40a2-8e73-e4556343ee64", "metadata": {}, "outputs": [], "source": [ - "from langgraph.checkpoint.memory import MemorySaver\n", - "\n", - "memory = MemorySaver()\n", + "from langgraph.prebuilt import create_react_agent\n", "\n", - "agent_executor = create_react_agent(llm, tools, checkpointer=memory)" + "agent_executor = create_react_agent(llm, [retrieve], checkpointer=memory)" ] }, { "cell_type": "markdown", - "id": "02026f78-338e-4d18-9f05-131e1dd59197", + "id": "e4a842f4-d295-4d94-8469-4412c89965d9", "metadata": {}, "source": [ - "This is all we need to construct a conversational RAG agent.\n", - "\n", - "Let's observe its behavior. Note that if we input a query that does not require a retrieval step, the agent does not execute one:" + "Let's inspect the graph:" ] }, { "cell_type": "code", "execution_count": 20, - "id": "d6d70833-b958-4cd7-9e27-29c1c08bb1b8", + "id": "032e2b45-a78b-4778-afb5-f2f2ef296ad4", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'agent': {'messages': [AIMessage(content='Hello Bob! How can I assist you today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 11, 'prompt_tokens': 67, 'total_tokens': 78, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-d9011a17-9dbb-4348-9a58-ff89419a4bca-0', usage_metadata={'input_tokens': 67, 'output_tokens': 11, 'total_tokens': 78})]}}\n", - "----\n" - ] + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAANYAAAD5CAIAAADUe1yaAAAAAXNSR0IArs4c6QAAIABJREFUeJztnXdcU+fi/5+ThAwyIAmEKUuWKC5wo9i6rjgKalXQWq3eqtdxW2cH91Zr9Tpar7Xf3tpW6657FeveSsVVqSKIbGQkhAQSErJzfn/EH6UYUDEnz0nyvF/+gSfJ83yCb59zznOegeE4DhAIeFBgB0C4OkhBBGSQggjIIAURkEEKIiCDFERAhgY7QHtQyg1KmaFRaVI3GI16x+hWorlhVBrmzqW682hCPzrTnQo7EVnAHOMfEAAAgLRSW/SHuuSRms2jmYy4O4/K5tLoLApwhG9AY2CqOmNjg6lRaVQrTGwPamgXdkR3DofvBjsaZBxDQYXM8NsvtVQ3jC+ih3ZmewUwYCd6XSqLNCU5arlY5+lN7z9GSHNz3SsiB1Dw1mlZ/t2G/mO9wrtxYGexPX9cq/8tQzYwxatLfw/YWeBAdgUPf13RZQAvOp4HOwix3D4rb5AbhqT6wA4CAfIqiOP4Dx8Xj53t7xfKgp3FHuTeUpY+Uie95wc7iL0hr4LfLSuclh7C5jnkPXv7eHxHmfObcsI/A2EHsSskVfDwpooByUK/EJdo/5rzMFMhq9INflsEO4j9IOONWNYpWexAngv6BwCIHeDhzqXm3VbCDmI/SKdgXY2+MFsVFefk9x9t0HMI/8ohKewU9oN0Cv6WIes/Rgg7BUxobpS4ofxbp2Wwg9gJcikoLtUyWJSwWCfs/3sleo8QiEu1Br0ZdhB7QC4Fix6oBL50u1WXk5Oj0+lgfbxtmGxqSY6aoMJJBbkULHmkDu3Mtk9dGRkZ06dP12g0UD7+QkK7sJGC9qauRs8T0Pg+dmoF292AWbqxiGv/LITFshUyA6FVkAQSKaioNWAYRkTJZWVlc+bMSUhISEpKWrNmjdlszsjIWLt2LQBg6NCh8fHxGRkZAIDs7Oz58+cnJCQkJCTMnj07Ly/P8vH6+vr4+Pjdu3enp6cnJCT8/e9/t/px20Jzo6jqjWqF0eYlkw0SPXtoVJrceYSMolu1alVpaenixYvVavXdu3cpFMqAAQOmTp26Z8+eTZs2cTicoKAgAEBVVZVOp5s1axaFQjl06NDChQszMjKYTKalkG3btr399ttbtmyhUqk+Pj7Pf9zmsHk0tdLI9iDRvxERkOjrqZVGgh7HVVVVRUdHp6SkAACmTp0KABAIBIGBgQCALl26eHp6Wt42cuTIpKQky88xMTFz5szJzs7u27ev5UhsbOy8efOaynz+4zaH7UFVK0ygA0HFkwUSKQgATmMQciJOSkrasWPH+vXrZ82aJRAIWnsbhmGXL1/es2dPSUmJu7s7AEAm+7Nzrnfv3kRkawMGk4qbyfj41LaQ6FqQxaY1yAm59Jk3b96iRYvOnTs3duzYgwcPtva2rVu3Ll26NCYmZuPGjR988AEAwGz+s2eOxbL3A8P6Wr27C4zSIJGC7jxqo9JERMkYhqWlpZ04cSIxMXH9+vXZ2dlNLzWN0tDpdNu3b09OTl68eHH37t1jY2NfpmRCB3kQd3FMKkikIFfg5kbMidjSgcJms+fMmQMAePz4cVOrJpU+exqr0Wh0Ol2nTp0sf62vr2/RCragxceJgCugcT2dvxUk0Tf0DmBUFmpU9UaOrX/vy5cv53A4ffv2vXHjBgDA4lm3bt2oVOqXX345duxYnU43fvz48PDw/fv3C4VClUr1ww8/UCiUwsLC1sp8/uO2zVyaq3ajUzAKIf8nSQV1xYoVsDP8Sb3UYNCaRUFM2xZbUVFx48aNM2fOaDSaBQsWDB48GADA4/F8fHzOnz9//fp1pVI5evTonj17ZmZmHjx4sKysbMGCBcHBwUeOHJkyZYrBYNi1a1dCQkJMTExTmc9/3LaZ71+uDwhniTrY+FdBQsg1ZLX8sbo4Rz14ggsN2GyNjB+q3pjozfF0/imeJDoRAwCCotm3TsvFZVrfYOv/++vr65OTk62+FBgYWFFR8fzxxMTElStX2jppS2bNmmX1rN2pU6empyzNiYuL++qrr1orLec3BceT5gr+ka4VBABUFmpunZGNm299/oTJZJJIJFZfwjDr34XFYvH5fFvHbIlUKjUYrDzSbS0Vg8EQClsdFvnDx8Xv/juYwXL+22EyKggAuHywJqIHJzDCHXYQODzMVOi15rghhP+3IQkk6pRp4o2JojM7xRoVIX2EJKc8v7H4gcp1/COpggCA1GVBP68rh53C3jTUGc7vkbw1NwB2ELtCxhOxBZ3GtHdt+ZSPglzkkkhSpj23RzLl4yCKC/QFNoe8ClpahX3rn46d7efr7BM68+8p/7immPihs4+KsQapFbRwcZ9EozYNGONltwHV9qSioDEzQxYYzhow1gt2Fjg4gIIAgJIcdWZGbVgs2yeIGdqF7QSnKq3aVPJIXV2iVdQaBowR2vyBkAPhGApaKLjfUHBfVZKj7tSHR6NjbB6N7UFlMKkO8QWoVEytNDYqjSqFUSk3Ssq0oZ3ZkXHcoCgX7XtqwpEUbKI0T62oMaiVRrXCZDSazTbtvTEYDLm5ud26dbNloQCwOFTcjLvzaBwPmtCP7t/Rya9uXx6HVJBQZDJZamrquXPnYAdxFUjaL4hwHZCCCMggBVuCYVhkZCTsFC4EUrAlOI4/efIEdgoXAinYEgzDPDxcdPF7KCAFW4LjuEKhgJ3ChUAKWsHHxxU3X4AFUtAKrQ3MRhABUrAlGIY1nymHIBqkYEtwHM/NzYWdwoVACrYEwzD7Lx/jyiAFW4LjOHHL9yKeBymIgAxSsCXodsTOIAVbgm5H7AxSEAEZpGBLMAyzwwIgiCaQgi3Bcbyurg52ChcCKdgSNF7QziAFW4LGC9oZpCACMkjBlqAhq3YGKdgSNGTVziAFEZBBCiIggxS0QtMGOAg7gBS0gtU18hEEgRREQAYpiIAMUrAlqF/QziAFW4L6Be0MUhABGaRgSzAMCw4Ohp3ChUAKtgTH8bKyMtgpXAikIAIySMGWYBhGpbrEfk8kASnYEhzHTSZX3IERFkjBlqB5xHYGKdgSNI/YziAFW4KmL9kZtPXNM2bOnCkWi6lUqslkkkqlPj4+GIYZjcZTp07BjubkoFbwGRMnTmxoaKiqqpJIJGazubq6uqqqCsMcfr9F8oMUfMaIESPCwsKaH8FxPC4uDl4iVwEp+Cepqanu7n/ui+nr65uWlgY1kUuAFPyTESNGND0dtjSB0dHRsEM5P0jBvzBt2jQ2m21pAlNTU2HHcQmQgn9h2LBhwcHBOI736NEDTWKyDzTYAdqD2YTXSw0KmYGIDqXk4bNB4/G/DXq3OEdt88KpVMAX0XlCN5uX7Lg4Xr/g4zvKnJtKrcrkG8pqVDrYw1wOn1b+WM33dus1XIA2ZrfgYArm3VIW/qEe9LYvheLAPXY6renczsqhqSJRBybsLPBxpGvBgvsNT7LVgyf5ObR/AAAGkzpmdtCZnZK6Gj3sLPBxGAVxHH9wQzHgLRHsIDaj31jRnXNoOVfHUVCjMtXVGBgs5xlM6iF0e5rfCDsFfBxGQaXc6GRXTiwOjcWmGvVm2EEg4zAKYgBoGoywU9gYhcyARkI4jIIIZwUpiIAMUhABGaQgAjJIQQRkkIIIyCAFEZBBCiIggxREQAYpiIAMUhABGaSgDRCLq6vFVbBTOCpIwdelsqoiberY/Hy0ElI7QQoCHMcrqyra/XGT0ehYkx/IhkPOoHtJHj7M3r1n68OcbABAdFTnOXM+iIp8Ni8zNy/n2/99VVxcIBR4hYR2LCzM37XjKJ1O12q1W7d9e/HSGb1e1yEweOLEd958YzgA4PCRny9dPvf2hCnbtn0rk9dGREQvWZQeFBRSLa56d8YEAMDKzz9aCcCIEaM/WrYC9vd2MJy5FRSLq3R63TtTZ7077X2xuOqjjxdqtVoAgEQiXrJ0Lo1G+/TjL3r06JWZeXXsmAl0Ot1sNn+a/uHNm9empM348INPwsOjVn3xyanTJyyl5eXlHDy4e/Hi9M9Xfimtkfxn3WcAAKHA69NPvgAAzJg+Z/OmrVPT3oP9pR0PZ24Fhw4dOWxYkuXnqKiYRYvnPMzJ7hXf9/yFUxqN5rN/rRUIhAMGJP7x4PesWzfSUqdfu37pwcP7+/ZmeHl5AwCGDvmbRtN45Oi+pJFvWQpZ/cV/BQIhAGDcuMn/++6/CqXCg+cRGRENAAgKComN7Q716zoqzqwghmHXb1w+eGhPWVmJZb2iOrkMACCVSthstkUmDMP8/QMlkmoAQFbWDaPRmDZ1bFMJJpOJzeY0/ZXJfDbz18fHDwAgq5V68NBWYa+LMyu4a/fW7Tu2jB+X+v6sBTJ57crPPzLjZgBAQEAHtVpdXFwYFhZuMBgKC/O7d48HANTVyYRCr41fbmleCJVm5VfkRnMDAJjMDjaRnpw4rYIGg+HnfdtHJSXPn7cYAFBTI2l6acTw0YcO7/0k/YPhw0Zl/3HPaDROn/Y+AIDL5dXX1/n4+DEYDKjZXQunvR3R6/U6nS7y/98CK5T1AACz2QwA8PDwnD9vCYPBLCkpio/r++P3PwcGBgEAevbsbTKZfsk43FSIRqN5YUUMBtNyUiby2zgzTtsKstnssLDwo8f2CwRCtUq1c9cPFAqluLgQAJD3+NH6DSsXzl9Gc3OjUCjV1ZUCgZBKpQ4bmpRx8uiW77+uFldFRkQXFj65kXl5x0+Hmcy2Jo+KRD7+fgEHD+9hslhKpWLSxHcoFKf9j00ETqsgAOBfn65Zt37F56s+DgwMmjv3w6KiJ0eO7Jv9/kJfHz8/v4B1G1Y2dSlHhEdt/nobk8ncsO7bH7d+c+nS2ZMnjwYGBo0dM4Fm7VqwORiGpaevWb9h5f99+6VI5JuSPKltZREtcJhljSRl2iuHpUmzOtikNJPJZNnly2QyXb9xeeXnH3315Xc9e/SySeEvz54vit5fE0Z1c+mpxM7cCrZGeXnpPz/8e7++A8M7Rur0umvXLjKZzMCAINi5XBRXVJDN5gx5829ZWdfPXzjF4XBju3T/4IOPRSIf2LlcFFdUUCj0mj9vsaWzBgEddO+GgAxSEAEZpCACMkhBBGSQggjIIAURkEEKIiCDFERABimIgAxSEAEZh1GQSgNcgbPtHugdyKBQXXqYjCMpKPRnFD9QwU5hS+QSnV5rxhzmX4AoHOYXgGFYZBxXXOo82xVJy7UR3Tkv8UYnx2EUBAAMmSy6dkSiVTvDvLXS3Ibih8peIwSwg8DHYUZNW9BpTLtXl3V/Q8jxdOOL6A6VHQAAcADk1doGuaEsTzXxw8A7d+707t0bdijIOJiCFk7/nF/6uMHXx09Ra7B54TiOa7VaFouQ/aq9AhgAgKAoVteBngCAvLy8JUuWHD161KWnjeIOyIIFC4grfNOmTQkJCb/88gtxVTSnurr66dOnMpnMPtWREEe6FgQAXLp0CQCwefNmgsqvrq6+fv26RqM5ePAgQVW0wNfXNzAwEMOwSZMmqVROdcv/kjiSgpMmTQoICCC0ikOHDpWWlgIAysvLT548SWhdzeHz+atXrz579qzdaiQPjqGgWCzWaDSrV6+OiooirpbKysqrV69aflar1QcOHCCurucJDw8fP348AGDBggU6nc6eVcPFARQ8dOhQVlYWi8UKDw8ntKJjx46VlZU1/bWsrOzEiROE1miVmTNn/vTTT/avFxYOoGBZWVlycjLRtVRVVV2+fLn5EbVavXfvXqLrfZ7u3bvPnTsXAPDNN9/Yv3b7Q2oFb968CQBYsmSJHerav3+/pQm0LH1keR7z9OlTO1TdGv379+/Xr58j9pq9GrBvya2j1Wp79erV0NBg/6plMtmkSZPsX69VdDqdyWR68OAB7CAEQsZWUC6Xl5WV3bx5k8OB8AgVx3G5XG7/eq1Cp9MpFIq7u/uECROMRiPsOIRAOgW3bt0ql8sjIyMtyw4hAAAdO3bcsGFDSUlJQ0MD7Cy2h1wKFhQUGAwGou982wbDMBI+LgsNDY2IiNBoNCtWONumEiRSUCwW8/l8y80gRCxXYHAztIZIJIqLi7NzhyXRkEXBpKQkPp/v5eUFOwjAMCwmJgZ2ilYZM2bMqFGjAABNveiODnwFTSbT6dOnt2/fTpLTn8lkqqmpgZ2iLSx3abdu3Tp27BjsLDYAsoKlpaUSiWTkyJE+PmRZ3k+v1zvEcIFly5YJBM4w4hWmgg0NDYsXL/b394eY4Xn0ej2hT6JtSGJiIgBg0aJFdXV1sLO0H5gKFhQUHDlyBGIAq0gkEsdar3zNmjWrVq2CnaL9wFFQLBYfO3asZ8+eUGpvm4KCAqFQCDvFK8BkMjdu3AgAuHPnDuws7QGCgrm5uUuXLk1JSbF/1S+DTCbr2rUr7BTtoby83BH7ayDMHWnacIGcJCYm/vrrr1CeDb4+u3btmjZtGuwUr4ZdW0Gj0bhr1y4y+3f37t2BAwc6qH8AgGnTptXW1lZUtH+TeftjVwUnTpw4fPhwe9b4quzfv3/IkCGwU7wWXl5eV69etVwdOgQOOYmTIKqrq5cvX75r1y7YQWyAUqnEcdzDwwG2S7ZTK1hRUfH48WP71NVuvvnmmylTpsBOYRt4PF5lZaVDnJHtoaDJZBo3blx0dLQd6mo3jx8/1mq1I0aMgB3EZsTExCxatKioqAh2kBdgjxNxdnY2n88PDg4muqLXISUl5euvvw4Kcqqd6IxGY1ZWVkJCAuwgbYGuBQEAYN++fQCA1NRU2EFsj06nMxgMZL7HJ/xEfODAAZJf4N+5c+fq1atO6R8AgMFgvP/++/n5+bCDtArhCp48eTI+Pp7oWtqN2WxeuXLlli1bYAchkDVr1mRlZcFO0SrEnohxHFer1WQ+C0yePHnVqlURERGwg7guxLaCGIaR2b9PPvlkxowZruDfkydPrly5AjuFdYhV8NatWwsXLiS0inazf//+Ll26OFMvTBt06NAhPT0ddgrrEKsghULR6/WEVtE+jh8/XlBQkJaWBjuInWCxWFu2bCHnyFZirwX1er1SqSTDpKTmZGZmHjhwgLhFChGvBLGtIJ1OJ5t/jx492rZtmwv6l52dvXv3btgprEB4p0xycrJMJiO6lpekpKTks88+c6ml05qgUCiWNWrJBuEK9uzZkySPKWtqajZv3nz48GHYQeDQqVMn+6xR9qq4ygO62traKVOmuOZKuiQH/lR2O1BeXj558mQX90+v1y9evBh2CisQrqBMJhszZgzRtbSBVCpNT0+/cOECxAxkAMfx7Oxs2CmsQCO6AqFQ6OvrW1dXx+fzia7reaRS6dSpU128/bNAp9PXrVsHO4UV7HQt+NZbb6nVaqVSKRKJ7LaZQnl5+aZNmxxoFoVrQmArOGjQoMbGRsspAMMwyw92W7SqqKhoyZIlzrHwj00wGo0bN25ctmwZ7CAtIfBa8M0336RQKJbBCpYjVCq1T58+xNXYRE5Ozo8//oj8a47ZbCbnL4RABVesWBETE9P8RC8Sibp160ZcjRays7M3bNiwdu1aoityLGg0miveEa9bty4kJMTyM47jXC6X6EV8r1+/fvLkyZ07dxJaiyNCoVAmTJgAO4UViFXQx8fnww8/tDwmxjCM6Cbw7NmzR44cIe2oJLgYjUZyDpwjvF8wISFh3LhxbDabw+EQeiF4/Pjxq1evbtq0ibgqHBqz2UzOpbde6o7YaDBrVOZ215H69ntlRTUFBQVhQZ0b6gjZPOPy5cuPHhavWbOGiMKdAyqVSs6J+i/oF8y7rXxwXSEX61mc11qLqKlfhiD0er0ogFNV1BjWldNrGF/oT4plq8nA0qVLL1682NQpZrkiwnH8999/hx3tGW21grfPyWurDAPH+XIFbnaM1H7MJrxeqj+1Qzw0zccvxJFWSiWOuXPn5ubmSiSS5r1jTfeIZKDVa8FbZ+QKqXFgio+j+AcAoFAxgS8jeV7wxX01knIt7DikICwsLC4urvm5DsOwQYMGQQ31F6wrWFejr63U9R0tsnse2/Bmqt/dc2ScJwGFadOmNd/QIDAwcPLkyVAT/QXrCtZW6nCcwEs3ouHy3Z4WNOp17b+FcibCw8N79+5t+RnH8YEDB5Jni41WFVQpTN4dHPtaKjiGLa8m6T5e9uedd94RiUQAgICAALLdF1tX0KAzG7SO3YQoZUYAHLghty0dO3bs06cPjuOJiYmkagLtMV4Q0Q7MZrz8caOqzqhWGo0GXKM2vX6Z3fynantERAkGXNgnef3SmCwqnUVx51F5fLegaPfXKQopSC7ybivz76kqChr9I3lGPU51o1LcaACzRacEhdm73yiDGRgabVBYgwo3GYwmo8HNTffL91XBMezIHpyoeG47ikIKkoXcW8obJ2q9g7g0NrfLMHKdK9uGHyxoqGl8dE+bmSEbmCyM6PFqIiIF4aNRmU5tlxhMlLA+gTQ6eXfEaA0Mw3g+bADYHG/e3UvyvDuqUTN9qdSXvRB3iRl0ZKY8X71rdRknQOAb5e2I/jWHzqL5xYjofM8ty4pqnr7sowGkIEwkT7VXj8qjBgUzWA7zCOqFMDn0zkNDT22XKGUvtaIVUhAaJY9U5/ZIO3Qn1164tiKkV+DR/4nFZS9uC5GCcFDVGy/uc1r/LITEBxz9ptJoeEEHM1IQDmd2SUJ6B8BOQTgd+/r/+tMLuiGRghC4e77OBOg0N8e++XgZGGy6Wo09uqlo4z1IQQhknZKJwiGsLQEFUZggM0PexhtsqWBuXo5O91ojA65cvfDGkPjy8lLbhSId9y7IA2IEhI4hbzefrx99+ISNJ7/SGFRhEDfnt1YbQpspeOZsxrz507Vaja0KdFby7qiYHo49CulVYXCYj++qWnvVZgq+ZvvnIijlBq3azOK61tQWjpAlfao1tDJ80zYP6M6czdj09VoAQPK4oQCA5cs++9uIMQCAc+d+3btve1VVhVDoNSopZUraDMsSH0ajcfuOLWfPnVQo6oODQ6e/OzthwODni83KuvHD1m+qqip8ff3HjpkwLmWSTdJC5Gl+Iz+QqI1YCovvnTr/vyrxEy5HEB4aP3LYXB7XCwCQvnrI+DHLc/Ku5OZnspicvr1Shr8xy/IRk8l04cq2rLvH9XpNx7A4g4Go2Q5eIdyyvMbw7la+u21awT69B0x8eyoA4D+rN23etLVP7wEAgLNnT/5n3WcREdH/Sl8zOHHYT9u/2/vzdsv7v/zqiwMHd48elfLpJ1/4+vr/699LHjy436LMxsbGFZ8vp7vRFy9K799vkEwmtUlUuNRWG3CckFvAgqI7P+5a6CMKnZj86aD+acWl97dsn6fXP1Nq/9GV/r6R/5i5pWe3kecu/Zibn2k5fuzkhvNXtkVH9k8ZvYTuxtRoG4jIBgAwmbA6qfWHJbZpBfl8gb9/IACgU6cuHh6elgHiW3/6Nja2e/onXwAABg18s6FBuf/AzvHjUmtra86eOzntnVnT350NAEgcNGTqtJQdO7/f+NVfNoKrq5frdLqBA98cNnSkTUKSAbXCSGOwiCj5+K9f9Y1PSRn9bDXpyPA+GzZPyi/Mio0ZDADo3XPskMTpAAB/38jb9048KcyKiRpQUfU46+6xIYkzRg6dAwCI7zGqqISomZ1uDJqqlSnkRI2Uqagor62VTpr4TtORXr36nTp9oqKyPD8/FwCQkPCG5TiGYb3i+56/cKpFCf5+AZ07d92zdxuTyRozehydTicoqj3RqEwMvu27A+V11RJpSa38adbd482P1yuedQvT6c+8p1KpHjyRQikFADzMvQIAGNT/zy1IMYyoTjoag9KotK+CKrUKAODpKWg6wuXyAAC10hq1WgUA4Dd7icfzaGxsVKvVzUvAMGztms1bt/3flu83HTq85+Pln3fr1pOgtHaDoPVEG1QyAMCwN2Z1jXmj+XEu18qmLxQKzWw2AQDq68VMJoft7kFIphbgmLmV725j65vmq4q8fQAACkV900t1dXKLiF5eIgCAUvlnR5FcLqPRaExmy64KDofzwT8/2rnjCJvNSf/XIsuCmQ4N24Nq1NlgFH4LWEwuAMBg0Im8Q5r/YTHbuvVhs/larcpgtMcObUadkcu33t7ZTEEWkwUAqK19dtMgFHr5+vjdvp3Z9IarVy8wmczw8KhOnbpgGJZ164bluF6vz7p1o3PnrlQqle5Gb26npaPH3y9gXMpklVolFlfZKi0suB40o972Cnp7BXl6+N75PUOnf9YvazIZjUZD258KDIgGANx/YI+FuI16E9fTuoLUFStWPH+0skhjMgLfkFe4cGay3E/8cqi0rBgDWG7ew6ioGC6Hd+DQHqlUYjAYjh7bf+Hi6Slp7/WK78vj8sTi6mPHDwCA1dZKv/vuvyWlRUuX/NvPL4Dm5nbs+IHH+Y+CgkK8hN7Tpo+rrZXKZLXHjh/Q63Qz3/sHjfayVw4F95Uhndw5rXxtWKgUBpnYyPK08R0JhmF8T7/b937JfXwdB3jZ04fHTn5lMumDO8QCAC5d3xXoHx0V/mxZs6w7x5lMdo+uw0VeoQ8eXbx3/5RGq1Kp627eOVZUcjfQv1NMdIJt4wEAtAp1aAxT4GPlgt5mCvK4PG9vnytXzt+8eb2hQTlixOjw8Eg+X3Dp8rnTZ36pr5Onpc2YOuU9y4OpXvH91GrV6TMnLl06y3ZnL1mc3qtXPwAAl8P18/X//f4dCkbpFBNbUVF+I/Py9RuXhELvj5atCAgIfPk85FTQnUe7/WutMNj2l18+3iGBATHFpdn3sk+VVzzy8wuP6z7S0i/YmoIUCqVTZIK0tuzBo4vFpdm+ojB5XZWPdygRCpbckwyd4kOhWHksaX1lrdtn5Xot6DZY8PxLjsKpbRWJ47x8ybe40c/rn3oGCd09XOgBSUNto1HZkDLP+uBIcjUSrkBMX07hI00bCj4pvL3rwMfPH2cxua11HY8esaBvfLKtEublZ+49/O/nj+M4DgButeNmzoxvA/2jWytQp9J17s38jtjIAAAClElEQVRu7VWkoL3pPoh/82QRP5BHpVm/FwwJ6rroH1Z2bcVx0NrwGneWLc/sHUPjrAYwm804jlOpVvo1eVzv1krTawxKsapTr1aXk0MKQmDAGGHuPblvlPWdmul0poAOc0C/bQPUFtcNTBa28QY0ZBUCXQd6spgmneYFnSZOgLZB5ynE2p7cjhSEw8gZvsVZlbBTEIvZjBffrkqa4dv225CCcKAzKMlz/UtuO7OFxVkVqcuCXvg2pCA0/EJZ4+b7ltyugB3E9piM5oLM8rTlgXzRiweXIAVh4iGkj5nlm3OuRKN0npWx1XXaghvlkxYFunNe6mYXKQgZrwDGvI0dzSplZY5Ep7bHiAHi0Ch1T/+odjOr5qzryHvpVfJRpwx8MAwbNdOvJEd97ViNuyeT5s7gebtTHWeWsVFnUkrVJp3eoNYNHufVIfLVVrxECpKF0C7s0C7sooeqgvvqwky5INDdoDNT6TQag0bCFYtxHDfpjCaD0Y1OqRNrQruwIwZwQmLasywiUpBcdIzldIzlAACqSzRqhUmtMOp1Zq0tFvq1LQx3CtOd7s5z5/KpPkEv6HZpG6QgSfELJWSKCQmxriCdiZnJ1/i/Eh7eboRNhEDYEuv/Sly+m7TMsddFKHmgEvo5w4wnp8e6gqIODFKuefKy1Ev1IZ3daW6oGXQAWm0FA8KZ146I7Z7HNlzcW9U3qa3RGQjy0NZ+xI9uKgqyVd0ShXwfemuD20iFRmVU1BquHRaPXxDg+RKPhhBk4AVbYpc8UmdfrReXaKk0sp+YBX4MhVQf1sW990ghm4fu9B2GFyjYhE5D9i3pcBww3R2gqUa04GUVRCAIAjUbCMggBRGQQQoiIIMUREAGKYiADFIQAZn/B1qlvCqU0zzIAAAAAElFTkSuQmCC", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "config = {\"configurable\": {\"thread_id\": \"abc123\"}}\n", - "\n", - "for s in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=\"Hi! I'm bob\")]}, config=config\n", - "):\n", - " print(s)\n", - " print(\"----\")" + "display(Image(agent_executor.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "markdown", - "id": "a7928865-3dd6-4d36-abc6-2a30de770d09", + "id": "5423e086-35e2-41ef-a313-6aba053bc02b", "metadata": {}, "source": [ - "Further, if we input a query that does require a retrieval step, the agent generates the input to the tool:" + "The key difference from our earlier implementation is that instead of a final generation step that ends the run, here the tool invocation loops back to the original LLM call. The model can then either answer the question using the retrieved context, or generate another tool call to obtain more information.\n", + "\n", + "Let's test this out. We construct a question that would typically require an iterative sequence of retrieval steps to answer:" ] }, { "cell_type": "code", "execution_count": 21, - "id": "e2c570ae-dd91-402c-8693-ae746de63b16", + "id": "6ccf0204-6e64-413f-a110-e5dcb8a1c329", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_qVHvDTfYmWqcbgVhTwsH03aJ', 'function': {'arguments': '{\"query\":\"Task Decomposition\"}', 'name': 'blog_post_retriever'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 19, 'prompt_tokens': 91, 'total_tokens': 110, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-bf9df2a6-ad56-43af-8d57-16f850accfd1-0', tool_calls=[{'name': 'blog_post_retriever', 'args': {'query': 'Task Decomposition'}, 'id': 'call_qVHvDTfYmWqcbgVhTwsH03aJ', 'type': 'tool_call'}], usage_metadata={'input_tokens': 91, 'output_tokens': 19, 'total_tokens': 110})]}}\n", - "----\n", - "{'tools': {'messages': [ToolMessage(content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\\n\\nTree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\\n\\n(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user\\'s request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\\n\\nFig. 11. Illustration of how HuggingGPT works. (Image source: Shen et al. 2023)\\nThe system comprises of 4 stages:\\n(1) Task planning: LLM works as the brain and parses the user requests into multiple tasks. There are four attributes associated with each task: task type, ID, dependencies, and arguments. They use few-shot examples to guide LLM to do task parsing and planning.\\nInstruction:', name='blog_post_retriever', id='742ab53d-6f34-4607-bde7-13f2d75e0055', tool_call_id='call_qVHvDTfYmWqcbgVhTwsH03aJ')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='Task decomposition is a technique used in autonomous agent systems to break down complex tasks into smaller and simpler steps. This approach helps the agent to manage and execute tasks more effectively by dividing them into manageable subtasks. One common method for task decomposition is the Chain of Thought (CoT) technique, which prompts the model to think step by step and decompose hard tasks into smaller steps. Another extension of CoT is the Tree of Thoughts, which explores multiple reasoning possibilities at each step by creating a tree structure of thought steps.\\n\\nTask decomposition can be achieved through various methods, such as using language models with simple prompting, task-specific instructions, or human inputs. By breaking down tasks into smaller components, autonomous agents can plan and execute tasks more efficiently.\\n\\nIf you would like more detailed information or examples related to task decomposition, feel free to ask!', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 168, 'prompt_tokens': 611, 'total_tokens': 779, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-0f51a1cf-ff0a-474a-93f5-acf54e0d8cd6-0', usage_metadata={'input_tokens': 611, 'output_tokens': 168, 'total_tokens': 779})]}}\n", - "----\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What is the standard method for Task Decomposition?\n", + "\n", + "Once you get the answer, look up common extensions of that method.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_rxBqio7dxthnMuzjr4AIquSZ)\n", + " Call ID: call_rxBqio7dxthnMuzjr4AIquSZ\n", + " Args:\n", + " query: standard method for Task Decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_kmQMRWCKeBdtXdlJi8yZD9CO)\n", + " Call ID: call_kmQMRWCKeBdtXdlJi8yZD9CO\n", + " Args:\n", + " query: common extensions of Task Decomposition methods\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "The standard method for Task Decomposition involves breaking down complex tasks into smaller, manageable steps. Here are the main techniques:\n", + "\n", + "1. **Chain of Thought (CoT)**: This prompting technique encourages a model to \"think step by step,\" allowing it to utilize more computational resources during testing to decompose challenging tasks into simpler parts. CoT not only simplifies tasks but also provides insights into the model's reasoning process.\n", + "\n", + "2. **Simple Prompting**: This can involve straightforward queries like \"Steps for XYZ\" or \"What are the subgoals for achieving XYZ?\" to guide the model in identifying the necessary steps.\n", + "\n", + "3. **Task-specific Instructions**: Using specific prompts tailored to the task at hand, such as \"Write a story outline\" for creative writing, allows for more directed decomposition.\n", + "\n", + "4. **Human Inputs**: Involving human expertise can also aid in breaking down tasks effectively.\n", + "\n", + "### Common Extensions of Task Decomposition Methods\n", + "\n", + "1. **Tree of Thoughts**: This method extends CoT by exploring multiple reasoning possibilities at each step. It decomposes the problem into various thought steps and generates multiple thoughts per step, forming a tree structure. This can utilize search processes like breadth-first search (BFS) or depth-first search (DFS) to evaluate states through classifiers or majority voting.\n", + "\n", + "These extensions build on the basic principles of task decomposition, enhancing the depth and breadth of reasoning applied to complex tasks.\n" ] } ], "source": [ - "query = \"What is Task Decomposition?\"\n", - "\n", - "for s in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=query)]}, config=config\n", - "):\n", - " print(s)\n", - " print(\"----\")" - ] - }, - { - "cell_type": "markdown", - "id": "26eaae33-3c4e-49fc-9fc6-db8967e25579", - "metadata": {}, - "source": [ - "Above, instead of inserting our query verbatim into the tool, the agent stripped unnecessary words like \"what\" and \"is\".\n", + "config = {\"configurable\": {\"thread_id\": \"def234\"}}\n", "\n", - "This same principle allows the agent to use the context of the conversation when necessary:" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "570d8c68-136e-4ba5-969a-03ba195f6118", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_n7vUrFacrvl5wUGmz5EGpmCS', 'function': {'arguments': '{\"query\":\"Common ways of task decomposition\"}', 'name': 'blog_post_retriever'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 21, 'prompt_tokens': 802, 'total_tokens': 823, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-4d949be3-00e5-49e5-af26-6a217efc8858-0', tool_calls=[{'name': 'blog_post_retriever', 'args': {'query': 'Common ways of task decomposition'}, 'id': 'call_n7vUrFacrvl5wUGmz5EGpmCS', 'type': 'tool_call'}], usage_metadata={'input_tokens': 802, 'output_tokens': 21, 'total_tokens': 823})]}}\n", - "----\n", - "{'tools': {'messages': [ToolMessage(content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\\n\\nTree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\\n\\nResources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.\\n\\n(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user\\'s request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.', name='blog_post_retriever', id='90fcbc1e-0736-47bc-9a96-347ad837e0e3', tool_call_id='call_n7vUrFacrvl5wUGmz5EGpmCS')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='According to the blog post, common ways of task decomposition include:\\n\\n1. Using Language Models (LLM) with Simple Prompting: Language models can be utilized with simple prompts like \"Steps for XYZ\" or \"What are the subgoals for achieving XYZ?\" to break down tasks into smaller steps.\\n\\n2. Task-Specific Instructions: Providing task-specific instructions to guide the decomposition process. For example, using instructions like \"Write a story outline\" for writing a novel can help in breaking down the task effectively.\\n\\n3. Human Inputs: Involving human inputs in the task decomposition process. Human insights and expertise can contribute to breaking down complex tasks into manageable subtasks.\\n\\nThese methods of task decomposition help autonomous agents in planning and executing tasks more efficiently by breaking them down into smaller and simpler components.', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 160, 'prompt_tokens': 1347, 'total_tokens': 1507, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-087ce1b5-f897-40d0-8ef4-eb1c6852a835-0', usage_metadata={'input_tokens': 1347, 'output_tokens': 160, 'total_tokens': 1507})]}}\n", - "----\n" - ] - } - ], - "source": [ - "query = \"What according to the blog post are common ways of doing it? redo the search\"\n", + "input_message = (\n", + " \"What is the standard method for Task Decomposition?\\n\\n\"\n", + " \"Once you get the answer, look up common extensions of that method.\"\n", + ")\n", "\n", - "for s in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=query)]}, config=config\n", + "for event in agent_executor.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", + " config=config,\n", "):\n", - " print(s)\n", - " print(\"----\")" + " event[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", - "id": "f2724616-c106-4e15-a61a-3077c535f692", + "id": "4e3452e7-89ce-4f18-8def-e0983b823347", "metadata": {}, "source": [ - "Note that the agent was able to infer that \"it\" in our query refers to \"task decomposition\", and generated a reasonable search query as a result-- in this case, \"common ways of task decomposition\"." - ] - }, - { - "cell_type": "markdown", - "id": "1cf87847-23bb-4672-b41c-12ad9cf81ed4", - "metadata": {}, - "source": [ - "### Tying it together\n", - "\n", - "For convenience, we tie together all of the necessary steps in a single code cell:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "b1d2b4d4-e604-497d-873d-d345b808578e", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "USER_AGENT environment variable not set, consider setting it to identify your requests.\n" - ] - } - ], - "source": [ - "import bs4\n", - "from langchain.tools.retriever import create_retriever_tool\n", - "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.vectorstores import InMemoryVectorStore\n", - "from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "from langgraph.checkpoint.memory import MemorySaver\n", - "from langgraph.prebuilt import create_react_agent\n", - "\n", - "memory = MemorySaver()\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n", - "\n", - "\n", - "### Construct retriever ###\n", - "loader = WebBaseLoader(\n", - " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", - " bs_kwargs=dict(\n", - " parse_only=bs4.SoupStrainer(\n", - " class_=(\"post-content\", \"post-title\", \"post-header\")\n", - " )\n", - " ),\n", - ")\n", - "docs = loader.load()\n", - "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = InMemoryVectorStore(embedding=OpenAIEmbeddings())\n", - "vectorstore.add_documents(documents=splits)\n", - "retriever = vectorstore.as_retriever()\n", - "\n", - "\n", - "### Build retriever tool ###\n", - "tool = create_retriever_tool(\n", - " retriever,\n", - " \"blog_post_retriever\",\n", - " \"Searches and returns excerpts from the Autonomous Agents blog post.\",\n", - ")\n", - "tools = [tool]\n", + "Note that the agent:\n", "\n", + "1. Generates a query to search for a standard method for task decomposition;\n", + "2. Receiving the answer, generates a second query to search for common extensions of it;\n", + "3. Having received all necessary context, answers the question.\n", "\n", - "agent_executor = create_react_agent(llm, tools, checkpointer=memory)" + "We can see the full sequence of steps, along with latency and other metadata, in the [LangSmith trace](https://smith.langchain.com/public/48cbd35e-9ac1-49ab-8c09-500d54c06b81/r)." ] }, { @@ -984,7 +815,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/how_to/qa_citations.ipynb b/docs/docs/how_to/qa_citations.ipynb index d2b61428771dd..13d230315b801 100644 --- a/docs/docs/how_to/qa_citations.ipynb +++ b/docs/docs/how_to/qa_citations.ipynb @@ -19,7 +19,7 @@ "\n", "We generally suggest using the first item of the list that works for your use-case. That is, if your model supports tool-calling, try methods 1 or 2; otherwise, or if those fail, advance down the list.\n", "\n", - "Let's first create a simple [RAG](/docs/concepts/rag/) chain. To start we'll just retrieve from Wikipedia using the [WikipediaRetriever](https://python.langchain.com/api_reference/community/retrievers/langchain_community.retrievers.wikipedia.WikipediaRetriever.html)." + "Let's first create a simple [RAG](/docs/concepts/rag/) chain. To start we'll just retrieve from Wikipedia using the [WikipediaRetriever](https://python.langchain.com/api_reference/community/retrievers/langchain_community.retrievers.wikipedia.WikipediaRetriever.html). We will use the same [LangGraph](/docs/concepts/architecture/#langgraph) implementation from the [RAG Tutorial](/docs/tutorials/rag)." ] }, { @@ -29,7 +29,7 @@ "source": [ "## Setup\n", "\n", - "First we'll need to install some dependencies and set environment vars for the models we'll be using." + "First we'll need to install some dependencies:" ] }, { @@ -39,28 +39,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install -qU langchain langchain-openai langchain-anthropic langchain-community wikipedia" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8732a85a-dd1a-483c-8da7-a81251276aa1", - "metadata": {}, - "outputs": [], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "if not os.environ.get(\"OPENAI_API_KEY\"):\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()\n", - "\n", - "if not os.environ.get(\"ANTHROPIC_API_KEY\"):\n", - " os.environ[\"ANTHROPIC_API_KEY\"] = getpass.getpass()\n", - "\n", - "# Uncomment if you want to log to LangSmith\n", - "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\n", - "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()" + "%pip install -qU langchain-community wikipedia" ] }, { @@ -87,12 +66,20 @@ "\n", "from langchain_openai import ChatOpenAI\n", "\n", - "llm = ChatOpenAI()" + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" + ] + }, + { + "cell_type": "markdown", + "id": "916f7524-51cf-4afc-90b9-faccd2b44ef3", + "metadata": {}, + "source": [ + "We can now load a [retriever](/docs/concepts/retrievers/) and construct our [prompt](/docs/concepts/prompt_templates/):" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 7, "id": "4e17c3f6-8ce6-4767-b615-50a57c84c7b0", "metadata": {}, "outputs": [ @@ -108,7 +95,7 @@ "\n", "================================\u001b[1m Human Message \u001b[0m=================================\n", "\n", - "\u001b[33;1m\u001b[1;3m{input}\u001b[0m\n" + "\u001b[33;1m\u001b[1;3m{question}\u001b[0m\n" ] } ], @@ -129,7 +116,7 @@ "prompt = ChatPromptTemplate.from_messages(\n", " [\n", " (\"system\", system_prompt),\n", - " (\"human\", \"{input}\"),\n", + " (\"human\", \"{question}\"),\n", " ]\n", ")\n", "prompt.pretty_print()" @@ -140,121 +127,111 @@ "id": "c89e2045-9244-43e6-bf3f-59af22658529", "metadata": {}, "source": [ - "Now that we've got a [model](/docs/concepts/chat_models/), [retriver](/docs/concepts/retrievers/) and [prompt](/docs/concepts/prompt_templates/), let's chain them all together. We'll need to add some logic for formatting our retrieved Documents to a string that can be passed to our prompt. Following the how-to guide on [adding citations](/docs/how_to/qa_citations) to a RAG application, we'll make it so our chain returns both the answer and the retrieved Documents." + "Now that we've got a [model](/docs/concepts/chat_models/), [retriver](/docs/concepts/retrievers/) and [prompt](/docs/concepts/prompt_templates/), let's chain them all together. Following the how-to guide on [adding citations](/docs/how_to/qa_citations) to a RAG application, we'll make it so our chain returns both the answer and the retrieved Documents. This uses the same [LangGraph](/docs/concepts/architecture/#langgraph) implementation as in the [RAG Tutorial](/docs/tutorials/rag)." ] }, { "cell_type": "code", "execution_count": 4, - "id": "4cd55e1c-a6b7-44b7-9dde-5f42abe714ea", + "id": "e69a4698-9258-41bd-a9d2-0d2a03cd8872", "metadata": {}, "outputs": [], "source": [ - "from typing import List\n", - "\n", "from langchain_core.documents import Document\n", - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.runnables import RunnablePassthrough\n", + "from langgraph.graph import START, StateGraph\n", + "from typing_extensions import List, TypedDict\n", "\n", "\n", - "def format_docs(docs: List[Document]):\n", - " return \"\\n\\n\".join(doc.page_content for doc in docs)\n", + "# Define state for application\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str\n", "\n", "\n", - "rag_chain_from_docs = (\n", - " RunnablePassthrough.assign(context=(lambda x: format_docs(x[\"context\"])))\n", - " | prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")\n", + "# Define application steps\n", + "def retrieve(state: State):\n", + " retrieved_docs = retriever.invoke(state[\"question\"])\n", + " return {\"context\": retrieved_docs}\n", "\n", - "retrieve_docs = (lambda x: x[\"input\"]) | retriever\n", "\n", - "chain = RunnablePassthrough.assign(context=retrieve_docs).assign(\n", - " answer=rag_chain_from_docs\n", - ")" + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", + "\n", + "\n", + "# Compile application and test\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "code", "execution_count": 5, - "id": "42b28717-d34c-42de-b923-155ac60529a2", - "metadata": {}, - "outputs": [], - "source": [ - "result = chain.invoke({\"input\": \"How fast are cheetahs?\"})" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "8b20cf8e-dccd-45d1-aef0-25f1ad1aca6d", + "id": "37eaab79-74cd-4806-bdbd-7340652c425a", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "dict_keys(['input', 'context', 'answer'])\n" - ] - } - ], - "source": [ - "print(result.keys())" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ae5ed9a7-c72a-480d-80c6-0a6bd38b9941", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "page_content='The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\\nThe cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\\nThe cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson\\'s gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned a' metadata={'title': 'Cheetah', 'summary': 'The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\\nThe cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\\nThe cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson\\'s gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned at around four months and are independent by around 20 months of age.\\nThe cheetah is threatened by habitat loss, conflict with humans, poaching and high susceptibility to diseases. In 2016, the global cheetah population was estimated at 7,100 individuals in the wild; it is listed as Vulnerable on the IUCN Red List. It has been widely depicted in art, literature, advertising, and animation. It was tamed in ancient Egypt and trained for hunting ungulates in the Arabian Peninsula and India. It has been kept in zoos since the early 19th century.', 'source': 'https://en.wikipedia.org/wiki/Cheetah'}\n" - ] + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "print(result[\"context\"][0])" + "from IPython.display import Image, display\n", + "\n", + "display(Image(graph.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "code", - "execution_count": 8, - "id": "31f20897-0a7a-44e8-aeac-75d54f6e3789", + "execution_count": 10, + "id": "aef87758-c785-4484-ba59-9a784e5e1252", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Cheetahs are capable of running at speeds of 93 to 104 km/h (58 to 65 mph). They have evolved specialized adaptations for speed, including a light build, long thin legs, and a long tail.\n" + "Sources: ['https://en.wikipedia.org/wiki/Cheetah', 'https://en.wikipedia.org/wiki/Southeast_African_cheetah', 'https://en.wikipedia.org/wiki/Footspeed', 'https://en.wikipedia.org/wiki/Fastest_animals', 'https://en.wikipedia.org/wiki/Pursuit_predation', 'https://en.wikipedia.org/wiki/Gepard-class_fast_attack_craft']\n", + "\n", + "\n", + "Answer: Cheetahs are capable of running at speeds between 93 to 104 km/h (58 to 65 mph).\n" ] } ], "source": [ - "print(result[\"answer\"])" + "result = graph.invoke({\"question\": \"How fast are cheetahs?\"})\n", + "\n", + "sources = [doc.metadata[\"source\"] for doc in result[\"context\"]]\n", + "print(f\"Sources: {sources}\\n\\n\")\n", + "print(f'Answer: {result[\"answer\"]}')" ] }, { "cell_type": "markdown", - "id": "0f1f9a49-8f3f-44dd-98df-0218b5fb93a6", + "id": "b64cdff1-724e-460e-9795-23fb666002c6", "metadata": {}, "source": [ - "LangSmith trace: https://smith.langchain.com/public/0472c5d1-49dc-4c1c-8100-61910067d7ed/r" + "Check out the [LangSmith trace](https://smith.langchain.com/public/ed043789-8599-44de-b88e-ba463ea454a3/r)." ] }, { "cell_type": "markdown", - "id": "a7619ba1-33bd-48bf-8637-be409c94037f", + "id": "765ecc32-accc-4dcc-89b6-f5bfca633efb", "metadata": {}, "source": [ - "## Function-calling\n", + "## Tool-calling\n", "\n", - "If your LLM of choice implements a [tool-calling](/docs/concepts/tool_calling) feature, you can use it to make the model specify which of the provided documents it's referencing when generating its answer. LangChain tool-calling models implement a `.with_structured_output` method which will force generation adhering to a desired schema (see for example [here](https://python.langchain.com/api_reference/openai/chat_models/langchain_openai.chat_models.base.ChatOpenAI.html#langchain_openai.chat_models.base.ChatOpenAI.with_structured_output)).\n", + "If your LLM of choice implements a [tool-calling](/docs/concepts/tool_calling) feature, you can use it to make the model specify which of the provided documents it's referencing when generating its answer. LangChain tool-calling models implement a `.with_structured_output` method which will force generation adhering to a desired schema (see details [here](/docs/how_to/structured_output/)).\n", "\n", "### Cite documents\n", "\n", @@ -265,8 +242,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "id": "0af2c3a1-870c-428e-95da-0c2fd04d5616", + "execution_count": 11, + "id": "2088e137-2afe-45cc-a5dd-c54d63713c14", "metadata": {}, "outputs": [], "source": [ @@ -288,7 +265,7 @@ }, { "cell_type": "markdown", - "id": "68b95186-faf5-46f1-8715-ebbc38207d5d", + "id": "60c958e5-896b-4737-a5f8-353b6bdd907d", "metadata": {}, "source": [ "Let's see what the model output is like when we pass in our functions and a user input:" @@ -296,17 +273,17 @@ }, { "cell_type": "code", - "execution_count": 10, - "id": "2e2b7a87-3642-4ed8-9445-684daa93b0d7", + "execution_count": 12, + "id": "daad793f-f08d-4b56-90e8-3f015a79a88e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "CitedAnswer(answer='Brian\\'s height is 5\\'11\".', citations=[1, 3])" + "CitedAnswer(answer='Brian is 5\\'11\".', citations=[1, 3])" ] }, - "execution_count": 10, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -331,7 +308,7 @@ }, { "cell_type": "markdown", - "id": "7b847b53-987e-4d3a-9621-77e613d49cfd", + "id": "7085ffd9-15d6-4c14-a485-420a5952d335", "metadata": {}, "source": [ "Or as a dict:" @@ -339,17 +316,17 @@ }, { "cell_type": "code", - "execution_count": 11, - "id": "3ee49bbd-567f-41cc-8798-d5aad0fe1cea", + "execution_count": 13, + "id": "855b1d4d-5519-47a5-9cc3-4a6f8dafd451", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'answer': 'Brian\\'s height is 5\\'11\".', 'citations': [1, 3]}" + "{'answer': 'Brian is 5\\'11\".', 'citations': [1, 3]}" ] }, - "execution_count": 11, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -360,20 +337,20 @@ }, { "cell_type": "markdown", - "id": "bb8bbbb5-2afc-401f-a140-648c3d2c4522", + "id": "f9c86861-4b66-478a-8451-47bbdcaa292e", "metadata": {}, "source": [ "Now we structure the source identifiers into the prompt to replicate with our chain. We will make three changes:\n", "\n", "1. Update the prompt to include source identifiers;\n", - "2. Use the `structured_llm` (i.e., `llm.with_structured_output(CitedAnswer));\n", - "3. Remove the `StrOutputParser`, to retain the Pydantic object in the output." + "2. Use the `structured_llm` (i.e., `llm.with_structured_output(CitedAnswer)`);\n", + "3. Return the Pydantic object in the output." ] }, { "cell_type": "code", - "execution_count": 12, - "id": "3cb835f3-3cf5-4144-bf6b-24558b9faf31", + "execution_count": 26, + "id": "e93107ec-33ec-4507-9c80-45a2b13f0d05", "metadata": {}, "outputs": [], "source": [ @@ -385,50 +362,55 @@ " return \"\\n\\n\" + \"\\n\\n\".join(formatted)\n", "\n", "\n", - "rag_chain_from_docs = (\n", - " RunnablePassthrough.assign(context=(lambda x: format_docs_with_id(x[\"context\"])))\n", - " | prompt\n", - " | structured_llm\n", - ")\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " # highlight-next-line\n", + " answer: CitedAnswer\n", "\n", - "retrieve_docs = (lambda x: x[\"input\"]) | retriever\n", "\n", - "chain = RunnablePassthrough.assign(context=retrieve_docs).assign(\n", - " answer=rag_chain_from_docs\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "3e259b2f-5147-4c3c-9c26-b4eb8143e5f0", - "metadata": {}, - "outputs": [], - "source": [ - "result = chain.invoke({\"input\": \"How fast are cheetahs?\"})" + "def generate(state: State):\n", + " # highlight-next-line\n", + " formatted_docs = format_docs_with_id(state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": formatted_docs})\n", + " # highlight-start\n", + " structured_llm = llm.with_structured_output(CitedAnswer)\n", + " response = structured_llm.invoke(messages)\n", + " # highlight-end\n", + " return {\"answer\": response}\n", + "\n", + "\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "code", - "execution_count": 14, - "id": "2d8d2a01-608d-479f-85f1-eb8d14b11bc2", + "execution_count": 27, + "id": "182362b0-075a-4d45-ad05-c4f39d410624", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "answer='Cheetahs can run at speeds of 93 to 104 km/h (58 to 65 mph). They are known as the fastest land animals.' citations=[0]\n" - ] + "data": { + "text/plain": [ + "CitedAnswer(answer='Cheetahs are capable of running at speeds between 93 to 104 km/h (58 to 65 mph).', citations=[0, 3])" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "print(result[\"answer\"])" + "result = graph.invoke({\"question\": \"How fast are cheetahs?\"})\n", + "\n", + "result[\"answer\"]" ] }, { "cell_type": "markdown", - "id": "da8341f5-a48a-4c07-8445-a313e20c36a2", + "id": "c2b8258c-0c1e-41df-bfce-819bc1892382", "metadata": {}, "source": [ "We can inspect the document at index 0, which the model cited:" @@ -436,15 +418,17 @@ }, { "cell_type": "code", - "execution_count": 15, - "id": "02d19f2b-2e15-492f-b44b-577990d15a86", + "execution_count": 21, + "id": "8cc4254b-525b-4286-b119-87c8dbbbeb7c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "page_content='The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\\nThe cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\\nThe cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson\\'s gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned a' metadata={'title': 'Cheetah', 'summary': 'The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\\nThe cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\\nThe cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson\\'s gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned at around four months and are independent by around 20 months of age.\\nThe cheetah is threatened by habitat loss, conflict with humans, poaching and high susceptibility to diseases. In 2016, the global cheetah population was estimated at 7,100 individuals in the wild; it is listed as Vulnerable on the IUCN Red List. It has been widely depicted in art, literature, advertising, and animation. It was tamed in ancient Egypt and trained for hunting ungulates in the Arabian Peninsula and India. It has been kept in zoos since the early 19th century.', 'source': 'https://en.wikipedia.org/wiki/Cheetah'}\n" + "page_content='The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\n", + "The cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\n", + "The cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson's gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned a' metadata={'title': 'Cheetah', 'summary': 'The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\\nThe cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\\nThe cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson\\'s gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned at around four months and are independent by around 20 months of age.\\nThe cheetah is threatened by habitat loss, conflict with humans, poaching and high susceptibility to diseases. The global cheetah population was estimated in 2021 at 6,517; it is listed as Vulnerable on the IUCN Red List. It has been widely depicted in art, literature, advertising, and animation. It was tamed in ancient Egypt and trained for hunting ungulates in the Arabian Peninsula and India. It has been kept in zoos since the early 19th century.', 'source': 'https://en.wikipedia.org/wiki/Cheetah'}\n" ] } ], @@ -454,15 +438,15 @@ }, { "cell_type": "markdown", - "id": "94f2898a-ef4d-423a-b002-910fef7a65c9", + "id": "5f5c8187-93ba-40a8-a006-2f17491cd48d", "metadata": {}, "source": [ - "LangSmith trace: https://smith.langchain.com/public/aff39dc7-3e09-4d64-8083-87026d975534/r" + "LangSmith trace: https://smith.langchain.com/public/6f34d136-451d-4625-90c8-2d8decebc21a/r" ] }, { "cell_type": "markdown", - "id": "fdbd1407-8a5b-4c35-aa2b-9d26424edb93", + "id": "8b965cbc-f5a4-465a-9220-c30dbd437c34", "metadata": {}, "source": [ "### Cite snippets\n", @@ -474,8 +458,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "id": "fbf708aa-e8ac-4dea-bb57-82229597e2e0", + "execution_count": 28, + "id": "89794b32-f84d-46fb-9a8c-9a6df908b383", "metadata": {}, "outputs": [], "source": [ @@ -504,37 +488,35 @@ }, { "cell_type": "code", - "execution_count": 17, - "id": "beabab7b-7b6b-4eef-b874-e92d1ed8707c", + "execution_count": 32, + "id": "5adb77c4-e185-4ed3-8be0-d380ad50f649", "metadata": {}, "outputs": [], "source": [ - "rag_chain_from_docs = (\n", - " RunnablePassthrough.assign(context=(lambda x: format_docs_with_id(x[\"context\"])))\n", - " | prompt\n", - " | llm.with_structured_output(QuotedAnswer)\n", - ")\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " # highlight-next-line\n", + " answer: QuotedAnswer\n", "\n", - "retrieve_docs = (lambda x: x[\"input\"]) | retriever\n", "\n", - "chain = RunnablePassthrough.assign(context=retrieve_docs).assign(\n", - " answer=rag_chain_from_docs\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "9709ee6d-416f-4bd3-89c6-23667b9f3cca", - "metadata": {}, - "outputs": [], - "source": [ - "result = chain.invoke({\"input\": \"How fast are cheetahs?\"})" + "def generate(state: State):\n", + " formatted_docs = format_docs_with_id(state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": formatted_docs})\n", + " # highlight-next-line\n", + " structured_llm = llm.with_structured_output(QuotedAnswer)\n", + " response = structured_llm.invoke(messages)\n", + " return {\"answer\": response}\n", + "\n", + "\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "markdown", - "id": "b42ba8c6-4214-49f5-b920-f0e028f301c2", + "id": "0f23cbe0-3d71-4f9b-903d-07801682f05a", "metadata": {}, "source": [ "Here we see that the model has extracted a relevant snippet of text from source 0:" @@ -542,47 +524,49 @@ }, { "cell_type": "code", - "execution_count": 19, - "id": "56b01963-8680-4782-9c3f-384c197f0c2d", + "execution_count": 33, + "id": "3376deae-9fea-4aaa-861a-d37d9121926c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "QuotedAnswer(answer='Cheetahs can run at speeds of 93 to 104 km/h (58 to 65 mph).', citations=[Citation(source_id=0, quote='The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.')])" + "QuotedAnswer(answer='Cheetahs are capable of running at speeds of 93 to 104 km/h (58 to 65 mph).', citations=[Citation(source_id=0, quote='The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed.')])" ] }, - "execution_count": 19, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "result = graph.invoke({\"question\": \"How fast are cheetahs?\"})\n", + "\n", "result[\"answer\"]" ] }, { "cell_type": "markdown", - "id": "28676cf1-4a2e-44d2-8b2f-36303a12a371", + "id": "740eff91-9ccd-44c3-a707-978a560f412a", "metadata": {}, "source": [ - "LangSmith trace: https://smith.langchain.com/public/0f638cc9-8409-4a53-9010-86ac28144129/r" + "LangSmith trace: https://smith.langchain.com/public/e16dc72f-4261-4f25-a9a7-906238737283/r" ] }, { "cell_type": "markdown", - "id": "fb2d90a4-0370-4598-9f4b-e8e9a554346e", + "id": "ab0e894f-5c85-4120-995c-8348c129d736", "metadata": {}, "source": [ "## Direct prompting\n", "\n", - "Many models don't support function-calling. We can achieve similar results with direct prompting. Let's try instructing a model to generate structured XML for its output:" + "Some models don't support function-calling. We can achieve similar results with direct prompting. Let's try instructing a model to generate structured XML for its output:" ] }, { "cell_type": "code", - "execution_count": 20, - "id": "4e95bd8a-2f15-4e20-a1d9-225974b8d598", + "execution_count": 38, + "id": "2ec10eb1-da72-4393-b639-489c0a4f3d4d", "metadata": {}, "outputs": [], "source": [ @@ -604,26 +588,26 @@ "\n", "Here are the Wikipedia articles:{context}\"\"\"\n", "xml_prompt = ChatPromptTemplate.from_messages(\n", - " [(\"system\", xml_system), (\"human\", \"{input}\")]\n", + " [(\"system\", xml_system), (\"human\", \"{question}\")]\n", ")" ] }, { "cell_type": "markdown", - "id": "2d3bd0f7-e249-4bc6-bd46-6fb74ebf0118", + "id": "74cae200-0a88-4264-a5ad-a115b4a7d35c", "metadata": {}, "source": [ "We now make similar small updates to our chain:\n", "\n", "1. We update the formatting function to wrap the retrieved context in XML tags;\n", "2. We do not use `.with_structured_output` (e.g., because it does not exist for a model);\n", - "3. We use [XMLOutputParser](https://python.langchain.com/api_reference/core/output_parsers/langchain_core.output_parsers.xml.XMLOutputParser.html) in place of `StrOutputParser` to parse the answer into a dict." + "3. We use [XMLOutputParser](https://python.langchain.com/api_reference/core/output_parsers/langchain_core.output_parsers.xml.XMLOutputParser.html) to parse the answer into a dict." ] }, { "cell_type": "code", - "execution_count": 21, - "id": "5861ca8c-63b7-4918-bdc6-fe4e53fe03ca", + "execution_count": 41, + "id": "1426de65-f247-455d-bf15-b58e08e0189d", "metadata": {}, "outputs": [], "source": [ @@ -642,33 +626,33 @@ " return \"\\n\\n\" + \"\\n\".join(formatted) + \"\"\n", "\n", "\n", - "rag_chain_from_docs = (\n", - " RunnablePassthrough.assign(context=(lambda x: format_docs_xml(x[\"context\"])))\n", - " | xml_prompt\n", - " | llm\n", - " | XMLOutputParser()\n", - ")\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " # highlight-next-line\n", + " answer: dict\n", "\n", - "retrieve_docs = (lambda x: x[\"input\"]) | retriever\n", "\n", - "chain = RunnablePassthrough.assign(context=retrieve_docs).assign(\n", - " answer=rag_chain_from_docs\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "f1edb401-6027-4112-82ec-25736e8ebabd", - "metadata": {}, - "outputs": [], - "source": [ - "result = chain.invoke({\"input\": \"How fast are cheetahs?\"})" + "def generate(state: State):\n", + " # highlight-start\n", + " formatted_docs = format_docs_xml(state[\"context\"])\n", + " messages = xml_prompt.invoke(\n", + " {\"question\": state[\"question\"], \"context\": formatted_docs}\n", + " )\n", + " response = llm.invoke(messages)\n", + " parsed_response = XMLOutputParser().invoke(response)\n", + " # highlight-end\n", + " return {\"answer\": parsed_response}\n", + "\n", + "\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "markdown", - "id": "e5264571-48c2-492d-a750-640f9fff3e71", + "id": "54b74634-a90f-4b96-90fb-2b1bdd3e24eb", "metadata": {}, "source": [ "Note that citations are again structured into the answer:" @@ -676,51 +660,125 @@ }, { "cell_type": "code", - "execution_count": 23, - "id": "a2b4bdc9-92dd-434c-b61c-11ec44c92905", + "execution_count": 42, + "id": "56f4b74f-36b6-4df5-ac95-f9e856401251", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'cited_answer': [{'answer': 'Cheetahs are capable of running at 93 to 104 km/h (58 to 65 mph).'},\n", + "{'cited_answer': [{'answer': 'Cheetahs can run at speeds of 93 to 104 km/h (58 to 65 mph).'},\n", " {'citations': [{'citation': [{'source_id': '0'},\n", - " {'quote': 'The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.'}]}]}]}" + " {'quote': 'The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph);'}]},\n", + " {'citation': [{'source_id': '3'},\n", + " {'quote': 'The fastest land animal is the cheetah.'}]}]}]}" ] }, - "execution_count": 23, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "result = graph.invoke({\"question\": \"How fast are cheetahs?\"})\n", + "\n", "result[\"answer\"]" ] }, { "cell_type": "markdown", - "id": "940db8d5-8f43-44dd-9738-04fc7464baac", + "id": "0285feff-1d57-4aea-bd41-390224cd02e3", "metadata": {}, "source": [ - "LangSmith trace: https://smith.langchain.com/public/a3636c70-39c6-4c8f-bc83-1c7a174c237e/r" + "LangSmith trace: https://smith.langchain.com/public/0c45f847-c640-4b9a-a5fa-63559e413527/r" ] }, { "cell_type": "markdown", - "id": "9d4180b0-5d29-4bfa-85be-2a6161a872c4", + "id": "ab06819d-09fa-4f5c-8838-c22f5e32af17", "metadata": {}, "source": [ "## Retrieval post-processing\n", "\n", - "Another approach is to post-process our retrieved documents to compress the content, so that the source content is already minimal enough that we don't need the model to cite specific sources or spans. For example, we could break up each document into a sentence or two, embed those and keep only the most relevant ones. LangChain has some built-in components for this. Here we'll use a [RecursiveCharacterTextSplitter](https://python.langchain.com/api_reference/text_splitters/text_splitter/langchain_text_splitters.RecursiveCharacterTextSplitter.html#langchain_text_splitters.RecursiveCharacterTextSplitter), which creates chunks of a sepacified size by splitting on separator substrings, and an [EmbeddingsFilter](https://python.langchain.com/api_reference/langchain/retrievers/langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter.html#langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter), which keeps only the texts with the most relevant embeddings.\n", + "Another approach is to post-process our retrieved documents to compress the content, so that the source content is already minimal enough that we don't need the model to cite specific sources or spans. For example, we could break up each document into a sentence or two, embed those and keep only the most relevant ones. LangChain has some built-in components for this. Here we'll use a [RecursiveCharacterTextSplitter](https://python.langchain.com/api_reference/text_splitters/text_splitter/langchain_text_splitters.RecursiveCharacterTextSplitter.html#langchain_text_splitters.RecursiveCharacterTextSplitter), which creates chunks of a specified size by splitting on separator substrings, and an [EmbeddingsFilter](https://python.langchain.com/api_reference/langchain/retrievers/langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter.html#langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter), which keeps only the texts with the most relevant embeddings.\n", + "\n", + "This approach effectively updates our `retrieve` step to compress the documents. Let's first select an [embedding model](/docs/integrations/text_embedding/):\n", + "\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "d2814d13-49c1-4368-b6b7-d61865ba0849", + "metadata": {}, + "outputs": [], + "source": [ + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_openai import OpenAIEmbeddings\n", "\n", - "This approach effectively swaps our original retriever with an updated one that compresses the documents. To start, we build the retriever:" + "embeddings = OpenAIEmbeddings()" + ] + }, + { + "cell_type": "markdown", + "id": "db6d8f11-9a6d-446e-b311-1e3ca8c85371", + "metadata": {}, + "source": [ + "We can now rewrite the `retrieve` step:" ] }, { "cell_type": "code", - "execution_count": 24, - "id": "9b14f817-4454-47b2-9eb0-2b8783a8c252", + "execution_count": 44, + "id": "932e6e39-ca75-4763-9b0c-fa6bb7351414", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.retrievers.document_compressors import EmbeddingsFilter\n", + "from langchain_core.runnables import RunnableParallel\n", + "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "\n", + "splitter = RecursiveCharacterTextSplitter(\n", + " chunk_size=400,\n", + " chunk_overlap=0,\n", + " separators=[\"\\n\\n\", \"\\n\", \".\", \" \"],\n", + " keep_separator=False,\n", + ")\n", + "compressor = EmbeddingsFilter(embeddings=embeddings, k=10)\n", + "\n", + "\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str\n", + "\n", + "\n", + "def retrieve(state: State):\n", + " retrieved_docs = retriever.invoke(state[\"question\"])\n", + " # highlight-start\n", + " split_docs = splitter.split_documents(retrieved_docs)\n", + " stateful_docs = compressor.compress_documents(split_docs, state[\"question\"])\n", + " # highlight-end\n", + " return {\"context\": stateful_docs}" + ] + }, + { + "cell_type": "markdown", + "id": "73ee7ba2-20e0-4099-a6fd-d02fa77ac58a", + "metadata": {}, + "source": [ + "Let's test this out:" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "315df7b2-bf7e-4d1c-9363-be753a6d590f", "metadata": {}, "outputs": [ { @@ -730,82 +788,47 @@ "Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail\n", "\n", "\n", - "\n", "The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in)\n", "\n", "\n", - "\n", - "2 mph), or 171 body lengths per second. The cheetah, the fastest land mammal, scores at only 16 body lengths per second, while Anna's hummingbird has the highest known length-specific velocity attained by any vertebrate\n", - "\n", + "2 mph), or 171 body lengths per second. The cheetah, the fastest land mammal, scores at only 16 body lengths per second\n", "\n", "\n", "It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson's gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year\n", "\n", "\n", - "\n", "The cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran\n", "\n", "\n", - "\n", "The cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk\n", "\n", "\n", - "\n", "The Southeast African cheetah (Acinonyx jubatus jubatus) is the nominate cheetah subspecies native to East and Southern Africa. The Southern African cheetah lives mainly in the lowland areas and deserts of the Kalahari, the savannahs of Okavango Delta, and the grasslands of the Transvaal region in South Africa. In Namibia, cheetahs are mostly found in farmlands\n", "\n", "\n", - "\n", "Subpopulations have been called \"South African cheetah\" and \"Namibian cheetah.\"\n", "\n", "\n", - "\n", "In India, four cheetahs of the subspecies are living in Kuno National Park in Madhya Pradesh after having been introduced there\n", "\n", "\n", - "\n", "Acinonyx jubatus velox proposed in 1913 by Edmund Heller on basis of a cheetah that was shot by Kermit Roosevelt in June 1909 in the Kenyan highlands.\n", "Acinonyx rex proposed in 1927 by Reginald Innes Pocock on basis of a specimen from the Umvukwe Range in Rhodesia.\n", "\n", - "\n", "\n" ] } ], "source": [ - "from langchain.retrievers.document_compressors import EmbeddingsFilter\n", - "from langchain_core.runnables import RunnableParallel\n", - "from langchain_openai import OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "retrieval_result = retrieve({\"question\": \"How fast are cheetahs?\"})\n", "\n", - "splitter = RecursiveCharacterTextSplitter(\n", - " chunk_size=400,\n", - " chunk_overlap=0,\n", - " separators=[\"\\n\\n\", \"\\n\", \".\", \" \"],\n", - " keep_separator=False,\n", - ")\n", - "compressor = EmbeddingsFilter(embeddings=OpenAIEmbeddings(), k=10)\n", - "\n", - "\n", - "def split_and_filter(input) -> List[Document]:\n", - " docs = input[\"docs\"]\n", - " question = input[\"question\"]\n", - " split_docs = splitter.split_documents(docs)\n", - " stateful_docs = compressor.compress_documents(split_docs, question)\n", - " return [stateful_doc for stateful_doc in stateful_docs]\n", - "\n", - "\n", - "new_retriever = (\n", - " RunnableParallel(question=RunnablePassthrough(), docs=retriever) | split_and_filter\n", - ")\n", - "docs = new_retriever.invoke(\"How fast are cheetahs?\")\n", - "for doc in docs:\n", - " print(doc.page_content)\n", - " print(\"\\n\\n\")" + "for doc in retrieval_result[\"context\"]:\n", + " print(f\"{doc.page_content}\\n\\n\")" ] }, { "cell_type": "markdown", - "id": "984bc1e1-76fb-4d84-baa9-5fa5abca9da4", + "id": "4095cb9a-71e6-4ffc-8ed4-1ec9c7bdb748", "metadata": {}, "source": [ "Next, we assemble it into our chain as before:" @@ -813,46 +836,47 @@ }, { "cell_type": "code", - "execution_count": 25, - "id": "fa2adb01-5d8f-484c-8216-bae35717db0d", + "execution_count": 63, + "id": "08088f0f-209c-48ce-9b94-23e1bd3d465b", "metadata": {}, "outputs": [], "source": [ - "rag_chain_from_docs = (\n", - " RunnablePassthrough.assign(context=(lambda x: format_docs(x[\"context\"])))\n", - " | prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")\n", + "# This step is unchanged from our original RAG implementation\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", "\n", - "chain = RunnablePassthrough.assign(\n", - " context=(lambda x: x[\"input\"]) | new_retriever\n", - ").assign(answer=rag_chain_from_docs)" + "\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "code", - "execution_count": 26, - "id": "1a5b72f8-135b-4604-8777-59f2ef682323", + "execution_count": 64, + "id": "2903c47d-aae1-4662-bc1e-ee73ff774e88", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Cheetahs are capable of running at speeds between 93 to 104 km/h (58 to 65 mph), making them the fastest land animals.\n" + "Cheetahs are capable of running at speeds between 93 to 104 km/h (58 to 65 mph). They are known as the fastest land animals.\n" ] } ], "source": [ - "result = chain.invoke({\"input\": \"How fast are cheetahs?\"})\n", + "result = graph.invoke({\"question\": \"How fast are cheetahs?\"})\n", "\n", "print(result[\"answer\"])" ] }, { "cell_type": "markdown", - "id": "d9ac43ab-db4f-458a-9b5a-fd3e116229bd", + "id": "a86b6b89-dab3-4533-96e7-93c7f4a18346", "metadata": {}, "source": [ "Note that the document content is now compressed, although the document objects retain the original content in a \"summary\" key in their metadata. These summaries are not passed to the model; only the condensed content is." @@ -860,8 +884,8 @@ }, { "cell_type": "code", - "execution_count": 27, - "id": "80625506-8764-4adf-a467-33f465d0f51f", + "execution_count": 65, + "id": "9cd14ad3-de62-4092-9021-1af6dee8f263", "metadata": {}, "outputs": [ { @@ -870,7 +894,7 @@ "'Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail'" ] }, - "execution_count": 27, + "execution_count": 65, "metadata": {}, "output_type": "execute_result" } @@ -881,31 +905,31 @@ }, { "cell_type": "code", - "execution_count": 28, - "id": "672c5691-5d54-4271-9d97-93571eebda91", + "execution_count": 66, + "id": "9067f521-4ac8-42eb-a730-2d335803c9b2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\\nThe cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\\nThe cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson\\'s gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned at around four months and are independent by around 20 months of age.\\nThe cheetah is threatened by habitat loss, conflict with humans, poaching and high susceptibility to diseases. In 2016, the global cheetah population was estimated at 7,100 individuals in the wild; it is listed as Vulnerable on the IUCN Red List. It has been widely depicted in art, literature, advertising, and animation. It was tamed in ancient Egypt and trained for hunting ungulates in the Arabian Peninsula and India. It has been kept in zoos since the early 19th century.'" + "'The cheetah (Acinonyx jubatus) is a large cat and the fastest land animal. It has a tawny to creamy white or pale buff fur that is marked with evenly spaced, solid black spots. The head is small and rounded, with a short snout and black tear-like facial streaks. It reaches 67–94 cm (26–37 in) at the shoulder, and the head-and-body length is between 1.1 and 1.5 m (3 ft 7 in and 4 ft 11 in). Adults weigh between 21 and 72 kg (46 and 159 lb). The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.\\nThe cheetah was first described in the late 18th century. Four subspecies are recognised today that are native to Africa and central Iran. An African subspecies was introduced to India in 2022. It is now distributed mainly in small, fragmented populations in northwestern, eastern and southern Africa and central Iran. It lives in a variety of habitats such as savannahs in the Serengeti, arid mountain ranges in the Sahara, and hilly desert terrain.\\nThe cheetah lives in three main social groups: females and their cubs, male \"coalitions\", and solitary males. While females lead a nomadic life searching for prey in large home ranges, males are more sedentary and instead establish much smaller territories in areas with plentiful prey and access to females. The cheetah is active during the day, with peaks during dawn and dusk. It feeds on small- to medium-sized prey, mostly weighing under 40 kg (88 lb), and prefers medium-sized ungulates such as impala, springbok and Thomson\\'s gazelles. The cheetah typically stalks its prey within 60–100 m (200–330 ft) before charging towards it, trips it during the chase and bites its throat to suffocate it to death. It breeds throughout the year. After a gestation of nearly three months, females give birth to a litter of three or four cubs. Cheetah cubs are highly vulnerable to predation by other large carnivores. They are weaned at around four months and are independent by around 20 months of age.\\nThe cheetah is threatened by habitat loss, conflict with humans, poaching and high susceptibility to diseases. The global cheetah population was estimated in 2021 at 6,517; it is listed as Vulnerable on the IUCN Red List. It has been widely depicted in art, literature, advertising, and animation. It was tamed in ancient Egypt and trained for hunting ungulates in the Arabian Peninsula and India. It has been kept in zoos since the early 19th century.'" ] }, - "execution_count": 28, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "result[\"context\"][0].metadata[\"summary\"] # original document" + "result[\"context\"][0].metadata[\"summary\"] # original document # original document" ] }, { "cell_type": "markdown", - "id": "88ab8fd6-f6b4-4ba5-b022-f10cca983490", + "id": "c4325c9c-c09a-42ed-98d8-9111d387d517", "metadata": {}, "source": [ - "LangSmith trace: https://smith.langchain.com/public/a61304fa-e5a5-4c64-a268-b0aef1130d53/r" + "LangSmith trace: https://smith.langchain.com/public/21b0dc15-d70a-4293-9402-9c70f9178e66/r" ] }, { @@ -917,13 +941,13 @@ "\n", "Another approach is to post-process our model generation. In this example we'll first generate just an answer, and then we'll ask the model to annotate it's own answer with citations. The downside of this approach is of course that it is slower and more expensive, because two model calls need to be made.\n", "\n", - "Let's apply this to our initial chain." + "Let's apply this to our initial chain. If desired, we can implement this via a third step in our application." ] }, { "cell_type": "code", - "execution_count": 29, - "id": "daff5cb9-7639-4d30-b6e7-d795736a2b58", + "execution_count": 67, + "id": "9b8f73b9-2365-40fb-90c5-458bc056c1d8", "metadata": {}, "outputs": [], "source": [ @@ -951,79 +975,106 @@ }, { "cell_type": "code", - "execution_count": 30, - "id": "6f505eb9-db02-4c49-add3-1e469844d7ca", + "execution_count": 80, + "id": "80344f87-0e51-4202-ab6a-35dc36548ecf", "metadata": {}, "outputs": [], "source": [ - "from langchain_core.prompts import MessagesPlaceholder\n", - "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " (\"human\", \"{question}\"),\n", - " MessagesPlaceholder(\"chat_history\", optional=True),\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str\n", + " # highlight-next-line\n", + " annotations: AnnotatedAnswer\n", + "\n", + "\n", + "def retrieve(state: State):\n", + " retrieved_docs = retriever.invoke(state[\"question\"])\n", + " return {\"context\": retrieved_docs}\n", + "\n", + "\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", + "\n", + "\n", + "# highlight-start\n", + "def annotate(state: State):\n", + " formatted_docs = format_docs_with_id(state[\"context\"])\n", + " messages = [\n", + " (\"system\", system_prompt.format(context=formatted_docs)),\n", + " (\"human\", state[\"question\"]),\n", + " (\"ai\", state[\"answer\"]),\n", + " (\"human\", \"Annotate your answer with citations.\"),\n", " ]\n", - ")\n", - "answer = prompt | llm\n", - "annotation_chain = prompt | structured_llm\n", + " response = structured_llm.invoke(messages)\n", + " # highlight-end\n", + " # highlight-next-line\n", + " return {\"annotations\": response}\n", "\n", - "chain = (\n", - " RunnableParallel(\n", - " question=RunnablePassthrough(), docs=(lambda x: x[\"input\"]) | retriever\n", - " )\n", - " .assign(context=format)\n", - " .assign(ai_message=answer)\n", - " .assign(\n", - " chat_history=(lambda x: [x[\"ai_message\"]]),\n", - " answer=(lambda x: x[\"ai_message\"].content),\n", - " )\n", - " .assign(annotations=annotation_chain)\n", - " .pick([\"answer\", \"docs\", \"annotations\"])\n", - ")" + "\n", + "# highlight-next-line\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate, annotate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "code", - "execution_count": 31, - "id": "eb11c422-09b3-4d5a-87eb-3bad2e73cf6c", + "execution_count": 81, + "id": "688b43cc-2766-4216-a9b5-245c18eb5675", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "result = chain.invoke({\"input\": \"How fast are cheetahs?\"})" + "display(Image(graph.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "code", - "execution_count": 32, - "id": "5b8bbc02-f753-4abc-87ec-211aac3dc3d0", + "execution_count": 82, + "id": "a02d494e-2ba4-4626-b982-3fac8e65d0af", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Cheetahs are capable of running at speeds between 93 to 104 km/h (58 to 65 mph). Their specialized adaptations for speed, such as a light build, long thin legs, and a long tail, allow them to be the fastest land animals.\n" + "Cheetahs are capable of running at speeds between 93 to 104 km/h (58 to 65 mph).\n" ] } ], "source": [ + "result = graph.invoke({\"question\": \"How fast are cheetahs?\"})\n", + "\n", "print(result[\"answer\"])" ] }, { "cell_type": "code", - "execution_count": 33, - "id": "c7882b76-db21-40ee-bb31-ff438880adf6", + "execution_count": 83, + "id": "a8a02c3f-12dd-4e79-adc9-87a31b210abd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "AnnotatedAnswer(citations=[Citation(source_id=0, quote='The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph); it has evolved specialized adaptations for speed, including a light build, long thin legs and a long tail.')])" + "AnnotatedAnswer(citations=[Citation(source_id=0, quote='The cheetah is capable of running at 93 to 104 km/h (58 to 65 mph)')])" ] }, - "execution_count": 33, + "execution_count": 83, "metadata": {}, "output_type": "execute_result" } @@ -1034,11 +1085,19 @@ }, { "cell_type": "markdown", - "id": "803c6155-48af-40db-b4b0-1ecc5328e99b", + "id": "54e65f9b-5a80-46ad-91ac-3a946184fc8f", "metadata": {}, "source": [ - "LangSmith trace: https://smith.langchain.com/public/bf5e8856-193b-4ff2-af8d-c0f4fbd1d9cb/r" + "LangSmith trace: https://smith.langchain.com/public/b8257417-573b-47c4-a750-74e542035f19/r" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b4eca9be-14ae-4e6c-9693-fea8bdbf7372", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs/docs/how_to/qa_per_user.ipynb b/docs/docs/how_to/qa_per_user.ipynb index 08d0592f803f7..acead6ed5910c 100644 --- a/docs/docs/how_to/qa_per_user.ipynb +++ b/docs/docs/how_to/qa_per_user.ipynb @@ -34,17 +34,17 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 2, "id": "7345de3c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['ce15571e-4e2f-44c9-98df-7e83f6f63095']" + "['f907aab7-77c7-4347-acc2-6859f8142f92']" ] }, - "execution_count": 5, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -56,8 +56,8 @@ "embeddings = OpenAIEmbeddings()\n", "vectorstore = PineconeVectorStore(index_name=\"test-example\", embedding=embeddings)\n", "\n", - "vectorstore.add_texts([\"i worked at kensho\"], namespace=\"harrison\")\n", - "vectorstore.add_texts([\"i worked at facebook\"], namespace=\"ankush\")" + "vectorstore.add_texts([\"I worked at Kensho\"], namespace=\"harrison\")\n", + "vectorstore.add_texts([\"I worked at Facebook\"], namespace=\"ankush\")" ] }, { @@ -70,50 +70,50 @@ }, { "cell_type": "code", - "execution_count": 6, - "id": "3c2a39fa", + "execution_count": 4, + "id": "51676afa-2c9b-4f35-b2f0-accf34bb93f1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[Document(page_content='i worked at facebook')]" + "[Document(id='f907aab7-77c7-4347-acc2-6859f8142f92', metadata={}, page_content='I worked at Facebook')]" ] }, - "execution_count": 6, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# This will only get documents for Ankush\n", - "vectorstore.as_retriever(search_kwargs={\"namespace\": \"ankush\"}).get_relevant_documents(\n", + "vectorstore.as_retriever(search_kwargs={\"namespace\": \"ankush\"}).invoke(\n", " \"where did i work?\"\n", ")" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "id": "56393baa", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[Document(page_content='i worked at kensho')]" + "[Document(id='16061fc5-c6fc-4f45-a3b3-23469d7996af', metadata={}, page_content='I worked at Kensho')]" ] }, - "execution_count": 7, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# This will only get documents for Harrison\n", - "vectorstore.as_retriever(\n", - " search_kwargs={\"namespace\": \"harrison\"}\n", - ").get_relevant_documents(\"where did i work?\")" + "vectorstore.as_retriever(search_kwargs={\"namespace\": \"harrison\"}).invoke(\n", + " \"where did i work?\"\n", + ")" ] }, { @@ -132,7 +132,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "68162d05", "metadata": {}, "outputs": [], @@ -142,7 +142,7 @@ "\n", "from langchain_openai import ChatOpenAI\n", "\n", - "llm = ChatOpenAI()" + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" ] }, { @@ -150,22 +150,18 @@ "id": "b6778ffa", "metadata": {}, "source": [ - "This is basic question-answering chain set up." + "This will follow the basic implementation from the [RAG tutorial](/docs/tutorials/rag), but we will allow the retrieval step to be configurable." ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "id": "44a865f6", "metadata": {}, "outputs": [], "source": [ - "from langchain_core.output_parsers import StrOutputParser\n", "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_core.runnables import (\n", - " ConfigurableField,\n", - " RunnablePassthrough,\n", - ")\n", + "from langchain_core.runnables import ConfigurableField\n", "\n", "template = \"\"\"Answer the question based only on the following context:\n", "{context}\n", @@ -188,7 +184,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "id": "babbadff", "metadata": {}, "outputs": [], @@ -207,42 +203,90 @@ "id": "2d481b70", "metadata": {}, "source": [ - "We can now create the chain using our configurable retriever" + "We can now create the chain using our configurable retriever." ] }, { "cell_type": "code", - "execution_count": 12, - "id": "210b0446", + "execution_count": 9, + "id": "b21d1ac6-a25c-416d-b411-bf33203b53d0", "metadata": {}, "outputs": [], "source": [ - "chain = (\n", - " {\"context\": configurable_retriever, \"question\": RunnablePassthrough()}\n", - " | prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")" + "from langchain_core.documents import Document\n", + "from langchain_core.runnables import RunnableConfig\n", + "from langgraph.graph import START, StateGraph\n", + "from typing_extensions import List, TypedDict\n", + "\n", + "\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str\n", + "\n", + "\n", + "# highlight-next-line\n", + "def retrieve(state: State, config: RunnableConfig):\n", + " # highlight-next-line\n", + " retrieved_docs = configurable_retriever.invoke(state[\"question\"])\n", + " return {\"context\": retrieved_docs}\n", + "\n", + "\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", + "\n", + "\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "067d0eaf-a8f8-4a2c-8f55-028b5ea93a55", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import Image, display\n", + "\n", + "display(Image(graph.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "markdown", - "id": "7f6458c3", + "id": "eeaff86a-d9fe-4836-ad83-55490334f423", "metadata": {}, "source": [ - "We can now invoke the chain with configurable options. `search_kwargs` is the id of the configurable field. The value is the search kwargs to use for Pinecone" + "We can now invoke the chain with configurable options. `search_kwargs` is the id of the configurable field. The value is the search kwargs to use for Pinecone." ] }, { "cell_type": "code", "execution_count": 13, - "id": "a38037b2", + "id": "d0eaa304-40da-489f-b79e-1c9329ad43ce", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'The user worked at Kensho.'" + "{'question': 'Where did the user work?',\n", + " 'context': [Document(id='16061fc5-c6fc-4f45-a3b3-23469d7996af', metadata={}, page_content='I worked at Kensho')],\n", + " 'answer': 'The user worked at Kensho.'}" ] }, "execution_count": 13, @@ -251,22 +295,26 @@ } ], "source": [ - "chain.invoke(\n", - " \"where did the user work?\",\n", + "result = graph.invoke(\n", + " {\"question\": \"Where did the user work?\"},\n", " config={\"configurable\": {\"search_kwargs\": {\"namespace\": \"harrison\"}}},\n", - ")" + ")\n", + "\n", + "result" ] }, { "cell_type": "code", "execution_count": 14, - "id": "0ff4f5f2", + "id": "3db2444a-c924-4f5c-b03f-a1a77b48c76f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'The user worked at Facebook.'" + "{'question': 'Where did the user work?',\n", + " 'context': [Document(id='f907aab7-77c7-4347-acc2-6859f8142f92', metadata={}, page_content='I worked at Facebook')],\n", + " 'answer': 'The user worked at Facebook.'}" ] }, "execution_count": 14, @@ -275,22 +323,20 @@ } ], "source": [ - "chain.invoke(\n", - " \"where did the user work?\",\n", + "result = graph.invoke(\n", + " {\"question\": \"Where did the user work?\"},\n", " config={\"configurable\": {\"search_kwargs\": {\"namespace\": \"ankush\"}}},\n", - ")" + ")\n", + "\n", + "result" ] }, { "cell_type": "markdown", - "id": "7fb27b941602401d91542211134fc71a", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, + "id": "44b4ae47-2bf8-4a9c-98f6-a8bd6ecbe4fd", + "metadata": {}, "source": [ - "For more vectorstore implementations for multi-user, please refer to specific pages, such as [Milvus](/docs/integrations/vectorstores/milvus)." + "For details operating your specific vector store, see the [integration pages](/docs/integrations/vectorstores/)." ] } ], diff --git a/docs/docs/how_to/qa_sources.ipynb b/docs/docs/how_to/qa_sources.ipynb index eccf8d070e390..e7833ce6001a3 100644 --- a/docs/docs/how_to/qa_sources.ipynb +++ b/docs/docs/how_to/qa_sources.ipynb @@ -13,8 +13,8 @@ "\n", "We will cover two approaches:\n", "\n", - "1. Using the built-in [create_retrieval_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.retrieval.create_retrieval_chain.html), which returns sources by default;\n", - "2. Using a simple [LCEL](/docs/concepts/lcel) implementation, to show the operating principle.\n", + "1. Using the basic RAG chain covered in [Part 1](/docs/tutorials/rag) of the RAG tutorial;\n", + "2. Using a conversational RAG chain as convered in [Part 2](/docs/tutorials/qa_chat_history) of the tutorial.\n", "\n", "We will also show how to structure sources into the model response, such that a model can report what specific sources it used in generating its answer." ] @@ -28,8 +28,6 @@ "\n", "### Dependencies\n", "\n", - "We'll use OpenAI embeddings and a Chroma vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts/embedding_models), [VectorStore](/docs/concepts/vectorstores) or [Retriever](/docs/concepts/retrievers). \n", - "\n", "We'll use the following packages:" ] }, @@ -40,106 +38,138 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install --upgrade --quiet langchain langchain-community langchainhub langchain-openai langchain-chroma beautifulsoup4" + "%pip install --upgrade --quiet langchain langchain-community langchainhub beautifulsoup4" ] }, { "cell_type": "markdown", - "id": "51ef48de-70b6-4f43-8e0b-ab9b84c9c02a", + "id": "1665e740-ce01-4f09-b9ed-516db0bd326f", "metadata": {}, "source": [ - "We need to set environment variable `OPENAI_API_KEY`, which can be done directly or loaded from a `.env` file like so:" + "### LangSmith\n", + "\n", + "Many of the applications you build with LangChain will contain multiple steps with multiple invocations of LLM calls. As these applications get more and more complex, it becomes crucial to be able to inspect what exactly is going on inside your chain or agent. The best way to do this is with [LangSmith](https://smith.langchain.com).\n", + "\n", + "Note that LangSmith is not needed, but it is helpful. If you do want to use LangSmith, after you sign up at the link above, make sure to set your environment variables to start logging traces:\n", + "\n", + "```python\n", + "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", + "os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "83814ea8-c214-4d9b-b360-a578a7ed5914", + "metadata": {}, + "source": [ + "### Components\n", + "\n", + "We will need to select three components from LangChain's suite of integrations.\n", + "\n", + "A [chat model](/docs/integrations/chat/):\n", + "\n", + "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "\n", + "" ] }, { "cell_type": "code", - "execution_count": null, - "id": "143787ca-d8e6-4dc9-8281-4374f4d71720", + "execution_count": 2, + "id": "7be1032f-ea27-4103-a535-86b8730796db", "metadata": {}, "outputs": [], "source": [ - "import getpass\n", - "import os\n", - "\n", - "if not os.environ.get(\"OPENAI_API_KEY\"):\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()\n", + "# | output: false\n", + "# | echo: false\n", "\n", - "# import dotenv\n", + "from langchain_openai import ChatOpenAI\n", "\n", - "# dotenv.load_dotenv()" + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" ] }, { "cell_type": "markdown", - "id": "1665e740-ce01-4f09-b9ed-516db0bd326f", + "id": "09f98df1-ed09-487d-aab1-b3a22ffc873c", "metadata": {}, "source": [ - "### LangSmith\n", + "An [embedding model](/docs/integrations/text_embedding/):\n", "\n", - "Many of the applications you build with LangChain will contain multiple steps with multiple invocations of LLM calls. As these applications get more and more complex, it becomes crucial to be able to inspect what exactly is going on inside your chain or agent. The best way to do this is with [LangSmith](https://smith.langchain.com).\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", "\n", - "Note that LangSmith is not needed, but it is helpful. If you do want to use LangSmith, after you sign up at the link above, make sure to set your environment variables to start logging traces:\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "02d000ac-0563-4da9-af48-761659a41f91", + "metadata": {}, + "outputs": [], + "source": [ + "# | output: false\n", + "# | echo: false\n", "\n", - "```python\n", - "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", - "os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", - "```" + "from langchain_openai import OpenAIEmbeddings\n", + "\n", + "embeddings = OpenAIEmbeddings()" ] }, { "cell_type": "markdown", - "id": "fa6ba684-26cf-4860-904e-a4d51380c134", + "id": "c9fcc22d-12a3-4887-a7e8-6f651ffef9ae", "metadata": {}, "source": [ - "## Using `create_retrieval_chain`\n", + "And a [vector store](/docs/integrations/vectorstores/):\n", "\n", - "Let's first select a LLM:\n", - "\n", - "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "import VectorStoreTabs from \"@theme/VectorStoreTabs\";\n", "\n", - "\n" + "" ] }, { "cell_type": "code", - "execution_count": 2, - "id": "5e7513b0-81e5-4477-8007-101e523f271c", + "execution_count": 4, + "id": "d8d16b63-6866-49d3-96a3-8fdb20e4591b", "metadata": {}, "outputs": [], "source": [ "# | output: false\n", "# | echo: false\n", "\n", - "from langchain_openai import ChatOpenAI\n", + "from langchain_core.vectorstores import InMemoryVectorStore\n", "\n", - "llm = ChatOpenAI()" + "vector_store = InMemoryVectorStore(embeddings)" ] }, { "cell_type": "markdown", - "id": "6b1bdfd7-8acf-4655-834d-ba7463a80fef", + "id": "fa6ba684-26cf-4860-904e-a4d51380c134", "metadata": {}, "source": [ - "Here is Q&A app with sources we built over the [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng in the [RAG tutorial](/docs/tutorials/rag):" + "## RAG application\n", + "\n", + "Let's reconstruct the Q&A app with sources we built over the [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng in the [RAG tutorial](/docs/tutorials/rag).\n", + "\n", + "First we index our documents:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "24a69b8c-024e-4e34-b827-9c9de46512a3", "metadata": {}, "outputs": [], "source": [ "import bs4\n", - "from langchain.chains import create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", - "from langchain_chroma import Chroma\n", + "from langchain import hub\n", "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_openai import OpenAIEmbeddings\n", + "from langchain_core.documents import Document\n", "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "from typing_extensions import List, TypedDict\n", "\n", - "# 1. Load, chunk and index the contents of the blog to create a retriever.\n", + "# Load and chunk contents of the blog\n", "loader = WebBaseLoader(\n", " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", " bs_kwargs=dict(\n", @@ -151,192 +181,154 @@ "docs = loader.load()\n", "\n", "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = Chroma.from_documents(documents=splits, embedding=OpenAIEmbeddings())\n", - "retriever = vectorstore.as_retriever()\n", - "\n", - "\n", - "# 2. Incorporate the retriever into a question-answering chain.\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "\n", - "question_answer_chain = create_stuff_documents_chain(llm, prompt)\n", - "rag_chain = create_retrieval_chain(retriever, question_answer_chain)" + "all_splits = text_splitter.split_documents(docs)" ] }, { "cell_type": "code", - "execution_count": 4, - "id": "0d3b0f36-7b56-49c0-8e40-a1aa9ebcbf24", + "execution_count": 7, + "id": "dfc82ead-8504-4ae8-b593-9b69f23e5a57", "metadata": {}, "outputs": [], "source": [ - "result = rag_chain.invoke({\"input\": \"What is Task Decomposition?\"})" + "# Index chunks\n", + "_ = vector_store.add_documents(documents=all_splits)" ] }, { "cell_type": "markdown", - "id": "a8d9ac25-38bb-4ce7-ade9-b02a05ce3b27", + "id": "7cd9a4e6-8df7-48c8-879a-63660b963adf", "metadata": {}, "source": [ - "Note that `result` is a dict with keys `\"input\"`, `\"context\"`, and `\"answer\"`:" + "Next we build the application:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "def66576-2309-45b5-8699-f0287df8ca9e", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain import hub\n", + "from langchain_core.documents import Document\n", + "from langgraph.graph import START, StateGraph\n", + "from typing_extensions import List, TypedDict\n", + "\n", + "# Define prompt for question-answering\n", + "prompt = hub.pull(\"rlm/rag-prompt\")\n", + "\n", + "\n", + "# Define state for application\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str\n", + "\n", + "\n", + "# Define application steps\n", + "def retrieve(state: State):\n", + " retrieved_docs = vector_store.similarity_search(state[\"question\"])\n", + " return {\"context\": retrieved_docs}\n", + "\n", + "\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", + "\n", + "\n", + "# Compile application and test\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "code", - "execution_count": 5, - "id": "29462727-01bc-42e7-82ed-9a0dc04b5774", + "execution_count": 9, + "id": "53911d2e-f9b9-44b8-9baf-1c308201a7d0", "metadata": {}, "outputs": [ { "data": { + "image/png": "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", "text/plain": [ - "{'input': 'What is Task Decomposition?',\n", - " 'context': [Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.'),\n", - " Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.'),\n", - " Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.'),\n", - " Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content=\"(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\")],\n", - " 'answer': 'Task decomposition involves breaking down a complex task into smaller and more manageable steps. This process helps agents or models tackle difficult tasks by dividing them into simpler subtasks or components. Task decomposition can be achieved through techniques like Chain of Thought or Tree of Thoughts, which guide the agent in breaking down tasks into sequential or branching steps.'}" + "" ] }, - "execution_count": 5, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "result" - ] - }, - { - "cell_type": "markdown", - "id": "00b19e47-3e70-4a79-b458-bef55adb7517", - "metadata": {}, - "source": [ - "Here, `\"context\"` contains the sources that the LLM used in generating the response in `\"answer\"`." + "from IPython.display import Image, display\n", + "\n", + "display(Image(graph.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "markdown", - "id": "1c2f99b5-80b4-4178-bf30-c1c0a152638f", + "id": "e18645d6-b32d-4c8d-8c94-b8e8e7372c7f", "metadata": {}, "source": [ - "## Custom LCEL implementation\n", - "\n", - "Below we construct a chain similar to those built by `create_retrieval_chain`. It works by building up a dict: \n", - "\n", - "1. Starting with a dict with the input query, add the retrieved docs in the `\"context\"` key;\n", - "2. Feed both the query and context into a RAG chain and add the result to the dict." + "Because we're tracking the retrieved context in our application's state, it is accessible after invoking the application:" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "1950953a-e6f1-439d-b7b9-c3bd456e388d", + "execution_count": 10, + "id": "cd7dde97-25c6-49ce-9a0a-4cd36e36da2d", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "{'input': 'What is Task Decomposition',\n", - " 'context': [Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.'),\n", - " Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.'),\n", - " Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='The AI assistant can parse user input to several tasks: [{\"task\": task, \"id\", task_id, \"dep\": dependency_task_ids, \"args\": {\"text\": text, \"image\": URL, \"audio\": URL, \"video\": URL}}]. The \"dep\" field denotes the id of the previous task which generates a new resource that the current task relies on. A special tag \"-task_id\" refers to the generated text image, audio and video in the dependency task with id as task_id. The task MUST be selected from the following options: {{ Available Task List }}. There is a logical relationship between tasks, please note their order. If the user input can\\'t be parsed, you need to reply empty JSON. Here are several cases for your reference: {{ Demonstrations }}. The chat history is recorded as {{ Chat History }}. From this chat history, you can find the path of the user-mentioned resources for your task planning.'),\n", - " Document(metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Fig. 11. Illustration of how HuggingGPT works. (Image source: Shen et al. 2023)\\nThe system comprises of 4 stages:\\n(1) Task planning: LLM works as the brain and parses the user requests into multiple tasks. There are four attributes associated with each task: task type, ID, dependencies, and arguments. They use few-shot examples to guide LLM to do task parsing and planning.\\nInstruction:')],\n", - " 'answer': 'Task decomposition is a technique used in artificial intelligence to break down complex tasks into smaller and more manageable subtasks. This approach helps agents or models to tackle difficult problems by dividing them into simpler steps, improving performance and interpretability. Different methods like Chain of Thought and Tree of Thoughts have been developed to enhance task decomposition in AI systems.'}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Context: [Document(id='c8471b37-07d8-4d51-856e-4b2c22bca88d', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.'), Document(id='acb7eb6f-f252-4353-aec2-f459135354ba', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.'), Document(id='4fae6668-7fec-4237-9b2d-78132f4f3f3f', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.'), Document(id='3c79dd86-595e-42e8-b64d-404780f9e2d9', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content=\"(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\")]\n", + "\n", + "\n", + "Answer: Task Decomposition is the process of breaking down a complex task into smaller, manageable steps to facilitate execution. This can be achieved through techniques like Chain of Thought, which encourages step-by-step reasoning, or Tree of Thoughts, which explores multiple reasoning paths for each step. It can be implemented using simple prompts, specific instructions, or human input to effectively tackle the original task.\n" + ] } ], "source": [ - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "\n", - "\n", - "def format_docs(docs):\n", - " return \"\\n\\n\".join(doc.page_content for doc in docs)\n", - "\n", + "result = graph.invoke({\"question\": \"What is Task Decomposition?\"})\n", "\n", - "# This Runnable takes a dict with keys 'input' and 'context',\n", - "# formats them into a prompt, and generates a response.\n", - "rag_chain_from_docs = (\n", - " {\n", - " \"input\": lambda x: x[\"input\"], # input query\n", - " \"context\": lambda x: format_docs(x[\"context\"]), # context\n", - " }\n", - " | prompt # format query and context into prompt\n", - " | llm # generate response\n", - " | StrOutputParser() # coerce to string\n", - ")\n", - "\n", - "# Pass input query to retriever\n", - "retrieve_docs = (lambda x: x[\"input\"]) | retriever\n", - "\n", - "# Below, we chain `.assign` calls. This takes a dict and successively\n", - "# adds keys-- \"context\" and \"answer\"-- where the value for each key\n", - "# is determined by a Runnable. The Runnable operates on all existing\n", - "# keys in the dict.\n", - "chain = RunnablePassthrough.assign(context=retrieve_docs).assign(\n", - " answer=rag_chain_from_docs\n", - ")\n", - "\n", - "chain.invoke({\"input\": \"What is Task Decomposition\"})" + "print(f'Context: {result[\"context\"]}\\n\\n')\n", + "print(f'Answer: {result[\"answer\"]}')" ] }, { "cell_type": "markdown", - "id": "b437da5d-ca09-4d15-9be2-c35e5a1ace77", + "id": "50cca598-8a10-4cf9-bafc-b56f966bf73d", "metadata": {}, "source": [ - ":::tip\n", - "\n", - "Check out the [LangSmith trace](https://smith.langchain.com/public/1c055a3b-0236-4670-a3fb-023d418ba796/r)\n", - "\n", - ":::" + "Here, `\"context\"` contains the sources that the LLM used in generating the response in `\"answer\"`." ] }, { "cell_type": "markdown", - "id": "c1c17797-d965-4fd2-b8d4-d386f25dd352", + "id": "d74c8dac-54ed-4335-b6cc-4a7a97b4b5ce", "metadata": {}, "source": [ "## Structure sources in model response\n", "\n", "Up to this point, we've simply propagated the documents returned from the retrieval step through to the final response. But this may not illustrate what subset of information the model relied on when generating its answer. Below, we show how to structure sources into the model response, allowing the model to report what specific context it relied on for its answer.\n", "\n", - "Because the above LCEL implementation is composed of [Runnable](/docs/concepts/runnables) primitives, it is straightforward to extend. Below, we make a simple change:\n", - "\n", - "- We use the model's tool-calling features to generate [structured output](/docs/how_to/structured_output/), consisting of an answer and list of sources. The schema for the response is represented in the `AnswerWithSources` TypedDict, below.\n", - "- We remove the `StrOutputParser()`, as we expect `dict` output in this scenario." + "It is straightforward to extend the above LangGraph implementation. Below, we make a simple change: we use the model's tool-calling features to generate [structured output](/docs/how_to/structured_output/), consisting of an answer and list of sources. The schema for the response is represented in the `AnswerWithSources` TypedDict, below." ] }, { "cell_type": "code", - "execution_count": 17, - "id": "8f916b14-1b0a-4975-a62f-52f1353bde15", + "execution_count": 11, + "id": "ab70db7e-397b-4ffe-9346-b488b57527c9", "metadata": {}, "outputs": [], "source": [ "from typing import List\n", "\n", - "from langchain_core.runnables import RunnablePassthrough\n", "from typing_extensions import Annotated, TypedDict\n", "\n", "\n", @@ -352,31 +344,32 @@ " ]\n", "\n", "\n", - "# Our rag_chain_from_docs has the following changes:\n", - "# - add `.with_structured_output` to the LLM;\n", - "# - remove the output parser\n", - "rag_chain_from_docs = (\n", - " {\n", - " \"input\": lambda x: x[\"input\"],\n", - " \"context\": lambda x: format_docs(x[\"context\"]),\n", - " }\n", - " | prompt\n", - " | llm.with_structured_output(AnswerWithSources)\n", - ")\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " # highlight-next-line\n", + " answer: AnswerWithSources\n", "\n", - "retrieve_docs = (lambda x: x[\"input\"]) | retriever\n", "\n", - "chain = RunnablePassthrough.assign(context=retrieve_docs).assign(\n", - " answer=rag_chain_from_docs\n", - ")\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " # highlight-start\n", + " structured_llm = llm.with_structured_output(AnswerWithSources)\n", + " response = structured_llm.invoke(messages)\n", + " # highlight-end\n", + " return {\"answer\": response}\n", "\n", - "response = chain.invoke({\"input\": \"What is Chain of Thought?\"})" + "\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { "cell_type": "code", - "execution_count": 18, - "id": "7a8fc0c5-afb3-4012-a467-3951996a6850", + "execution_count": 13, + "id": "95b6b784-8584-4b02-8307-8f2d93d4a166", "metadata": {}, "outputs": [ { @@ -384,7 +377,7 @@ "output_type": "stream", "text": [ "{\n", - " \"answer\": \"Chain of Thought (CoT) is a prompting technique that enhances model performance on complex tasks by instructing the model to \\\"think step by step\\\" to decompose hard tasks into smaller and simpler steps. It transforms big tasks into multiple manageable tasks and sheds light on the interpretation of the model's thinking process.\",\n", + " \"answer\": \"Chain of Thought (CoT) is a prompting technique that enhances model performance by instructing it to think step by step, allowing the decomposition of complex tasks into smaller, manageable steps. This method not only aids in task execution but also provides insights into the model's reasoning process. CoT has become a standard approach in improving how language models handle intricate problem-solving tasks.\",\n", " \"sources\": [\n", " \"Wei et al. 2022\"\n", " ]\n", @@ -395,17 +388,287 @@ "source": [ "import json\n", "\n", - "print(json.dumps(response[\"answer\"], indent=2))" + "result = graph.invoke({\"question\": \"What is Chain of Thought?\"})\n", + "print(json.dumps(result[\"answer\"], indent=2))" + ] + }, + { + "cell_type": "markdown", + "id": "dd4108d3-f2e9-41fb-8528-fdac8c68b337", + "metadata": {}, + "source": [ + ":::tip\n", + "\n", + "View [LangSmith trace](https://smith.langchain.com/public/51d543f7-bdf6-4d93-9ecd-2fc09bf6d666/r).\n", + "\n", + ":::" ] }, { "cell_type": "markdown", - "id": "7440f785-29c5-4c6b-9656-0d9d5efbac05", + "id": "a795ee54-f87c-4224-bdfc-6f037c1e3630", + "metadata": {}, + "source": [ + "## Conversational RAG" + ] + }, + { + "cell_type": "markdown", + "id": "82c8e1ec-6f77-468b-a06d-f032a9fe3488", + "metadata": {}, + "source": [ + "[Part 2](/docs/tutorials/qa_chat_history) of the RAG tutorial implements a different architecture, in which steps in the RAG flow are represented via successive [message](/docs/concepts/messages/) objects. This leverages additional [tool-calling](/docs/concepts/tool_calling/) features of chat models, and more naturally accommodates a \"back-and-forth\" conversational user experience.\n", + "\n", + "In that tutorial (and below), we propagate the retrieved documents as [artifacts](/docs/how_to/tool_artifacts/) on the tool messages. That makes it easy to pluck out the retrieved documents. Below, we add them as an additional key in the state, for convenience.\n", + "\n", + "Note that we define the response format of the tool as `\"content_and_artifact\"`:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "cbbc4668-d9de-420f-9a4b-532b634f897e", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.tools import tool\n", + "\n", + "\n", + "@tool(response_format=\"content_and_artifact\")\n", + "def retrieve(query: str):\n", + " \"\"\"Retrieve information related to a query.\"\"\"\n", + " retrieved_docs = vector_store.similarity_search(query, k=2)\n", + " serialized = \"\\n\\n\".join(\n", + " (f\"Source: {doc.metadata}\\n\" f\"Content: {doc.page_content}\")\n", + " for doc in retrieved_docs\n", + " )\n", + " return serialized, retrieved_docs" + ] + }, + { + "cell_type": "markdown", + "id": "f0e4859f-efad-41d0-aca3-2a6f314464e1", + "metadata": {}, + "source": [ + "We can now build and compile the exact same application as in [Part 2](/docs/tutorials/qa_chat_history) of the RAG tutorial, with two changes:\n", + "\n", + "1. We add a `context` key of the state to store retrieved documents;\n", + "2. In the `generate` step, we pluck out the retrieved documents and populate them in the state.\n", + "\n", + "These changes are highlighted below." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "e38542b3-9d10-41a4-9af5-7495835eb45b", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.messages import SystemMessage\n", + "from langgraph.graph import END, MessagesState, StateGraph\n", + "from langgraph.prebuilt import ToolNode, tools_condition\n", + "\n", + "\n", + "class State(MessagesState):\n", + " # highlight-next-line\n", + " context: List[Document]\n", + "\n", + "\n", + "# Step 1: Generate an AIMessage that may include a tool-call to be sent.\n", + "def query_or_respond(state: State):\n", + " \"\"\"Generate tool call for retrieval or respond.\"\"\"\n", + " llm_with_tools = llm.bind_tools([retrieve])\n", + " response = llm_with_tools.invoke(state[\"messages\"])\n", + " # MessagesState appends messages to state instead of overwriting\n", + " return {\"messages\": [response]}\n", + "\n", + "\n", + "# Step 2: Execute the retrieval.\n", + "tools = ToolNode([retrieve])\n", + "\n", + "\n", + "# Step 3: Generate a response using the retrieved content.\n", + "def generate(state: MessagesState):\n", + " \"\"\"Generate answer.\"\"\"\n", + " # Get generated ToolMessages\n", + " recent_tool_messages = []\n", + " for message in reversed(state[\"messages\"]):\n", + " if message.type == \"tool\":\n", + " recent_tool_messages.append(message)\n", + " else:\n", + " break\n", + " tool_messages = recent_tool_messages[::-1]\n", + "\n", + " # Format into prompt\n", + " docs_content = \"\\n\\n\".join(doc.content for doc in tool_messages)\n", + " system_message_content = (\n", + " \"You are an assistant for question-answering tasks. \"\n", + " \"Use the following pieces of retrieved context to answer \"\n", + " \"the question. If you don't know the answer, say that you \"\n", + " \"don't know. Use three sentences maximum and keep the \"\n", + " \"answer concise.\"\n", + " \"\\n\\n\"\n", + " f\"{docs_content}\"\n", + " )\n", + " conversation_messages = [\n", + " message\n", + " for message in state[\"messages\"]\n", + " if message.type in (\"human\", \"system\")\n", + " or (message.type == \"ai\" and not message.tool_calls)\n", + " ]\n", + " prompt = [SystemMessage(system_message_content)] + conversation_messages\n", + "\n", + " # Run\n", + " response = llm.invoke(prompt)\n", + " context = []\n", + " # highlight-start\n", + " for tool_message in tool_messages:\n", + " context.extend(tool_message.artifact)\n", + " # highlight-end\n", + " return {\"messages\": [response], \"context\": context}" + ] + }, + { + "cell_type": "markdown", + "id": "0c7f4bcd-d1cc-48ef-9717-911ff6fc681e", + "metadata": {}, + "source": [ + "We can compile the application as before:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "2addebfd-4236-4eec-abb5-7d742c5b49c9", + "metadata": {}, + "outputs": [], + "source": [ + "graph_builder = StateGraph(MessagesState)\n", + "\n", + "graph_builder.add_node(query_or_respond)\n", + "graph_builder.add_node(tools)\n", + "graph_builder.add_node(generate)\n", + "\n", + "graph_builder.set_entry_point(\"query_or_respond\")\n", + "graph_builder.add_conditional_edges(\n", + " \"query_or_respond\",\n", + " tools_condition,\n", + " {END: END, \"tools\": \"tools\"},\n", + ")\n", + "graph_builder.add_edge(\"tools\", \"generate\")\n", + "graph_builder.add_edge(\"generate\", END)\n", + "\n", + "graph = graph_builder.compile()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "dacfd0b1-fbd8-4cd2-b429-34c47e0bafb0", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(Image(graph.get_graph().draw_mermaid_png()))" + ] + }, + { + "cell_type": "markdown", + "id": "60608d11-aeb4-4be4-a8c4-5dacaff2e377", + "metadata": {}, + "source": [ + "Invoking our application, we see that the retrieved [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects are accessible from the application state." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "a21bad79-3773-48b4-9d77-406e29b0cbf2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What is Task Decomposition?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_oA0XZ5hF70X0oW4ccNUFCFxX)\n", + " Call ID: call_oA0XZ5hF70X0oW4ccNUFCFxX\n", + " Args:\n", + " query: Task Decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Task Decomposition is the process of breaking down a complicated task into smaller, manageable steps. It often utilizes techniques like Chain of Thought (CoT) prompting, which encourages models to think step by step, enhancing performance on complex tasks. This approach helps clarify the model's reasoning and makes it easier to tackle difficult problems.\n" + ] + } + ], + "source": [ + "input_message = \"What is Task Decomposition?\"\n", + "\n", + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", + "):\n", + " step[\"messages\"][-1].pretty_print()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "6c528829-a4f8-4a2c-8e3e-700d63a0daa2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Document(id='c8471b37-07d8-4d51-856e-4b2c22bca88d', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.'),\n", + " Document(id='acb7eb6f-f252-4353-aec2-f459135354ba', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.')]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "step[\"context\"]" + ] + }, + { + "cell_type": "markdown", + "id": "b437da5d-ca09-4d15-9be2-c35e5a1ace77", "metadata": {}, "source": [ ":::tip\n", "\n", - "View [LangSmith trace](https://smith.langchain.com/public/0eeddf06-3a7b-4f27-974c-310ca8160f60/r)\n", + "Check out the [LangSmith trace](https://smith.langchain.com/public/cc25515d-2e46-44fa-8bb2-b9cb0f451504/r).\n", "\n", ":::" ] diff --git a/docs/docs/how_to/qa_streaming.ipynb b/docs/docs/how_to/qa_streaming.ipynb index faca44cf0e376..4c1fd3a9e1bbe 100644 --- a/docs/docs/how_to/qa_streaming.ipynb +++ b/docs/docs/how_to/qa_streaming.ipynb @@ -21,8 +21,6 @@ "\n", "### Dependencies\n", "\n", - "We'll use OpenAI embeddings and a Chroma vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts/embedding_models), [VectorStore](/docs/concepts/vectorstores) or [Retriever](/docs/concepts/retrievers). \n", - "\n", "We'll use the following packages:" ] }, @@ -33,33 +31,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install --upgrade --quiet langchain langchain-community langchainhub langchain-openai langchain-chroma beautifulsoup4" - ] - }, - { - "cell_type": "markdown", - "id": "51ef48de-70b6-4f43-8e0b-ab9b84c9c02a", - "metadata": {}, - "source": [ - "We need to set environment variable `OPENAI_API_KEY`, which can be done directly or loaded from a `.env` file like so:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "143787ca-d8e6-4dc9-8281-4374f4d71720", - "metadata": {}, - "outputs": [], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "if not os.environ.get(\"OPENAI_API_KEY\"):\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()\n", - "\n", - "# import dotenv\n", - "\n", - "# dotenv.load_dotenv()" + "%pip install --upgrade --quiet langchain langchain-community langchainhub beautifulsoup4" ] }, { @@ -81,22 +53,24 @@ }, { "cell_type": "markdown", - "id": "e2a72ca8-f8c8-4c0e-929a-223946c63f12", + "id": "7cccf0c3-e7ed-4373-8b9b-36438ecdd5ef", "metadata": {}, "source": [ - "## RAG chain\n", + "### Components\n", + "\n", + "We will need to select three components from LangChain's suite of integrations.\n", "\n", - "Let's first select a LLM:\n", + "A [chat model](/docs/integrations/chat/):\n", "\n", "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", "\n", - "\n" + "" ] }, { "cell_type": "code", - "execution_count": 1, - "id": "accc4c35-e17c-4bf0-8a11-cd9e53436a3d", + "execution_count": 2, + "id": "40808135-f8b9-4049-a645-a86a25a1e5c4", "metadata": {}, "outputs": [], "source": [ @@ -105,411 +79,270 @@ "\n", "from langchain_openai import ChatOpenAI\n", "\n", - "llm = ChatOpenAI()" + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" ] }, { "cell_type": "markdown", - "id": "fa6ba684-26cf-4860-904e-a4d51380c134", + "id": "672d05b5-5baa-4330-ac57-9113badaacb8", "metadata": {}, "source": [ - "Here is Q&A app with sources we built over the [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng in the [RAG tutorial](/docs/tutorials/rag):" + "An [embedding model](/docs/integrations/text_embedding/):\n", + "\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", + "\n", + "" ] }, { "cell_type": "code", - "execution_count": 2, - "id": "820244ae-74b4-4593-b392-822979dd91b8", + "execution_count": 3, + "id": "a25ac99a-793a-40df-8a4c-1d4be8eacf0a", "metadata": {}, "outputs": [], "source": [ - "import bs4\n", - "from langchain.chains import create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", - "from langchain_chroma import Chroma\n", - "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_openai import OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "\n", - "# 1. Load, chunk and index the contents of the blog to create a retriever.\n", - "loader = WebBaseLoader(\n", - " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", - " bs_kwargs=dict(\n", - " parse_only=bs4.SoupStrainer(\n", - " class_=(\"post-content\", \"post-title\", \"post-header\")\n", - " )\n", - " ),\n", - ")\n", - "docs = loader.load()\n", - "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = Chroma.from_documents(documents=splits, embedding=OpenAIEmbeddings())\n", - "retriever = vectorstore.as_retriever()\n", - "\n", - "\n", - "# 2. Incorporate the retriever into a question-answering chain.\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", + "# | output: false\n", + "# | echo: false\n", "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", + "from langchain_openai import OpenAIEmbeddings\n", "\n", - "question_answer_chain = create_stuff_documents_chain(llm, prompt)\n", - "rag_chain = create_retrieval_chain(retriever, question_answer_chain)" + "embeddings = OpenAIEmbeddings()" ] }, { "cell_type": "markdown", - "id": "1c2f99b5-80b4-4178-bf30-c1c0a152638f", + "id": "895c3fe2-a93a-4785-b775-4768d153d104", "metadata": {}, "source": [ - "## Streaming final outputs\n", + "And a [vector store](/docs/integrations/vectorstores/):\n", "\n", - "The chain constructed by `create_retrieval_chain` returns a dict with keys `\"input\"`, `\"context\"`, and `\"answer\"`. The `.stream` method will by default stream each key in a sequence.\n", + "import VectorStoreTabs from \"@theme/VectorStoreTabs\";\n", "\n", - "Note that here only the `\"answer\"` key is streamed token-by-token, as the other components-- such as retrieval-- do not support token-level streaming." + "" ] }, { "cell_type": "code", - "execution_count": 3, - "id": "ded41680-b749-4e2a-9daa-b1165d74783b", + "execution_count": 4, + "id": "b7b02d11-3f13-4e5f-b436-f06afc3fae3a", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'What is Task Decomposition?'}\n", - "{'context': [Document(page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}), Document(page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}), Document(page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}), Document(page_content=\"(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\", metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'})]}\n", - "{'answer': ''}\n", - "{'answer': 'Task'}\n", - "{'answer': ' decomposition'}\n", - "{'answer': ' involves'}\n", - "{'answer': ' breaking'}\n", - "{'answer': ' down'}\n", - "{'answer': ' complex'}\n", - "{'answer': ' tasks'}\n", - "{'answer': ' into'}\n", - "{'answer': ' smaller'}\n", - "{'answer': ' and'}\n", - "{'answer': ' simpler'}\n", - "{'answer': ' steps'}\n", - "{'answer': ' to'}\n", - "{'answer': ' make'}\n", - "{'answer': ' them'}\n", - "{'answer': ' more'}\n", - "{'answer': ' manageable'}\n", - "{'answer': '.'}\n", - "{'answer': ' This'}\n", - "{'answer': ' process'}\n", - "{'answer': ' can'}\n", - "{'answer': ' be'}\n", - "{'answer': ' facilitated'}\n", - "{'answer': ' by'}\n", - "{'answer': ' techniques'}\n", - "{'answer': ' like'}\n", - "{'answer': ' Chain'}\n", - "{'answer': ' of'}\n", - "{'answer': ' Thought'}\n", - "{'answer': ' ('}\n", - "{'answer': 'Co'}\n", - "{'answer': 'T'}\n", - "{'answer': ')'}\n", - "{'answer': ' and'}\n", - "{'answer': ' Tree'}\n", - "{'answer': ' of'}\n", - "{'answer': ' Thoughts'}\n", - "{'answer': ','}\n", - "{'answer': ' which'}\n", - "{'answer': ' help'}\n", - "{'answer': ' agents'}\n", - "{'answer': ' plan'}\n", - "{'answer': ' and'}\n", - "{'answer': ' execute'}\n", - "{'answer': ' tasks'}\n", - "{'answer': ' effectively'}\n", - "{'answer': ' by'}\n", - "{'answer': ' dividing'}\n", - "{'answer': ' them'}\n", - "{'answer': ' into'}\n", - "{'answer': ' sub'}\n", - "{'answer': 'goals'}\n", - "{'answer': ' or'}\n", - "{'answer': ' multiple'}\n", - "{'answer': ' reasoning'}\n", - "{'answer': ' possibilities'}\n", - "{'answer': '.'}\n", - "{'answer': ' Task'}\n", - "{'answer': ' decomposition'}\n", - "{'answer': ' can'}\n", - "{'answer': ' be'}\n", - "{'answer': ' initiated'}\n", - "{'answer': ' through'}\n", - "{'answer': ' simple'}\n", - "{'answer': ' prompts'}\n", - "{'answer': ','}\n", - "{'answer': ' task'}\n", - "{'answer': '-specific'}\n", - "{'answer': ' instructions'}\n", - "{'answer': ','}\n", - "{'answer': ' or'}\n", - "{'answer': ' human'}\n", - "{'answer': ' inputs'}\n", - "{'answer': ' to'}\n", - "{'answer': ' guide'}\n", - "{'answer': ' the'}\n", - "{'answer': ' agent'}\n", - "{'answer': ' in'}\n", - "{'answer': ' achieving'}\n", - "{'answer': ' its'}\n", - "{'answer': ' goals'}\n", - "{'answer': ' efficiently'}\n", - "{'answer': '.'}\n", - "{'answer': ''}\n" - ] - } - ], + "outputs": [], "source": [ - "for chunk in rag_chain.stream({\"input\": \"What is Task Decomposition?\"}):\n", - " print(chunk)" + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_core.vectorstores import InMemoryVectorStore\n", + "\n", + "vector_store = InMemoryVectorStore(embeddings)" ] }, { "cell_type": "markdown", - "id": "72380afa-965d-4715-aac4-6049cce56313", + "id": "e2a72ca8-f8c8-4c0e-929a-223946c63f12", "metadata": {}, "source": [ - "We are free to process chunks as they are streamed out. If we just want to stream the answer tokens, for example, we can select chunks with the corresponding key:" + "## RAG application" ] }, { - "cell_type": "code", - "execution_count": 4, - "id": "738eb33e-6ccd-4b26-b563-beef216fb113", + "cell_type": "markdown", + "id": "fa6ba684-26cf-4860-904e-a4d51380c134", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Task| decomposition| is| a| technique| used| to| break| down| complex| tasks| into| smaller| and| more| manageable| steps|.| This| process| helps| agents| or| models| handle| intricate| tasks| by| dividing| them| into| simpler| sub|tasks|.| By| decom|posing| tasks|,| the| model| can| effectively| plan| and| execute| each| step| towards| achieving| the| overall| goal|.|" - ] - } - ], "source": [ - "for chunk in rag_chain.stream({\"input\": \"What is Task Decomposition?\"}):\n", - " if answer_chunk := chunk.get(\"answer\"):\n", - " print(f\"{answer_chunk}|\", end=\"\")" + "Let's reconstruct the Q&A app with sources we built over the [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng in the [RAG tutorial](/docs/tutorials/rag).\n", + "\n", + "First we index our documents:" ] }, { - "cell_type": "markdown", - "id": "8b2d224d-2a82-418b-b562-01ea210b86ef", + "cell_type": "code", + "execution_count": 6, + "id": "e89a5def-f040-4fd6-a34b-6815eae5ed9a", "metadata": {}, + "outputs": [], "source": [ - "More simply, we can use the [.pick](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.pick) method to select only the desired key:" + "import bs4\n", + "from langchain import hub\n", + "from langchain_community.document_loaders import WebBaseLoader\n", + "from langchain_core.documents import Document\n", + "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "from typing_extensions import List, TypedDict\n", + "\n", + "# Load and chunk contents of the blog\n", + "loader = WebBaseLoader(\n", + " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", + " bs_kwargs=dict(\n", + " parse_only=bs4.SoupStrainer(\n", + " class_=(\"post-content\", \"post-title\", \"post-header\")\n", + " )\n", + " ),\n", + ")\n", + "docs = loader.load()\n", + "\n", + "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", + "all_splits = text_splitter.split_documents(docs)" ] }, { "cell_type": "code", - "execution_count": 5, - "id": "16c20971-a6fd-4b57-83cd-7b2b453f97c9", + "execution_count": 7, + "id": "10b34088-2daf-4a66-86bb-d3a560d1015e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "|Task| decomposition| involves| breaking| down| complex| tasks| into| smaller| and| simpler| steps| to| make| them| more| manageable| for| an| agent| or| model| to| handle|.| This| process| helps| in| planning| and| executing| tasks| efficiently| by| dividing| them| into| a| series| of| sub|goals| or| actions|.| Task| decomposition| can| be| achieved| through| techniques| like| Chain| of| Thought| (|Co|T|)| or| Tree| of| Thoughts|,| which| enhance| model| performance| on| intricate| tasks| by| guiding| them| through| step|-by|-step| thinking| processes|.||" - ] - } - ], + "outputs": [], "source": [ - "chain = rag_chain.pick(\"answer\")\n", - "\n", - "for chunk in chain.stream({\"input\": \"What is Task Decomposition?\"}):\n", - " print(f\"{chunk}|\", end=\"\")" + "# Index chunks\n", + "_ = vector_store.add_documents(documents=all_splits)" ] }, { "cell_type": "markdown", - "id": "fdee7ae6-4a81-46ab-8efd-d2310b596f8c", + "id": "e53c3449-9268-40d5-a7f6-a64a5f7d3641", "metadata": {}, "source": [ - "## Streaming intermediate steps\n", - "\n", - "Suppose we want to stream not only the final outputs of the chain, but also some intermediate steps. As an example let's take our [Conversational RAG](/docs/tutorials/qa_chat_history) chain. Here we reformulate the user question before passing it to the retriever. This reformulated question is not returned as part of the final output. We could modify our chain to return the new question, but for demonstration purposes we'll leave it as is." + "Next we build the application:" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "f4d7714e-bdca-419d-a6c6-7c1a70a69297", + "execution_count": 8, + "id": "249e71c6-6cc5-40c0-b58f-7ec949c6a28f", "metadata": {}, "outputs": [], "source": [ - "from langchain.chains import create_history_aware_retriever\n", - "from langchain_core.prompts import MessagesPlaceholder\n", - "\n", - "### Contextualize question ###\n", - "contextualize_q_system_prompt = (\n", - " \"Given a chat history and the latest user question \"\n", - " \"which might reference context in the chat history, \"\n", - " \"formulate a standalone question which can be understood \"\n", - " \"without the chat history. Do NOT answer the question, \"\n", - " \"just reformulate it if needed and otherwise return it as is.\"\n", - ")\n", - "contextualize_q_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", contextualize_q_system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "contextualize_q_llm = llm.with_config(tags=[\"contextualize_q_llm\"])\n", - "history_aware_retriever = create_history_aware_retriever(\n", - " contextualize_q_llm, retriever, contextualize_q_prompt\n", - ")\n", + "from langchain import hub\n", + "from langchain_core.documents import Document\n", + "from langgraph.graph import START, StateGraph\n", + "from typing_extensions import List, TypedDict\n", "\n", + "# Define prompt for question-answering\n", + "prompt = hub.pull(\"rlm/rag-prompt\")\n", "\n", - "### Answer question ###\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "qa_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)\n", "\n", - "rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)" + "# Define state for application\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str\n", + "\n", + "\n", + "# Define application steps\n", + "def retrieve(state: State):\n", + " retrieved_docs = vector_store.similarity_search(state[\"question\"])\n", + " return {\"context\": retrieved_docs}\n", + "\n", + "\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", + "\n", + "\n", + "# Compile application and test\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" ] }, { - "cell_type": "markdown", - "id": "ad306179-b6f0-4ade-9ec5-06e04fbb8d69", + "cell_type": "code", + "execution_count": 9, + "id": "3d8a2e68-7849-4c7e-ae6b-31f1f65f9b59", "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "Note that above we use `.with_config` to assign a tag to the LLM that is used for the question re-phrasing step. This is not necessary but will make it more convenient to stream output from that specific step.\n", + "from IPython.display import Image, display\n", "\n", - "To demonstrate, we will pass in an artificial message history:\n", - "```\n", - "Human: What is task decomposition?\n", - "\n", - "AI: Task decomposition involves breaking up a complex task into smaller and simpler steps.\n", - "```\n", - "We then ask a follow up question: \"What are some common ways of doing it?\" Leading into the retrieval step, our `history_aware_retriever` will rephrase this question using the conversation's context to ensure that the retrieval is meaningful.\n", + "display(Image(graph.get_graph().draw_mermaid_png()))" + ] + }, + { + "cell_type": "markdown", + "id": "1c2f99b5-80b4-4178-bf30-c1c0a152638f", + "metadata": {}, + "source": [ + "## Streaming final outputs\n", "\n", - "To stream intermediate output, we recommend use of the async `.astream_events` method. This method will stream output from all \"events\" in the chain, and can be quite verbose. We can filter using tags, event types, and other criteria, as we do here.\n", + "LangGraph supports several [streaming modes](https://langchain-ai.github.io/langgraph/how-tos/#streaming), which can be controlled by specifying the `stream_mode` parameter. Setting `stream_mode=\"messages\"` allows us to stream tokens from chat model invocations.\n", "\n", - "Below we show a typical `.astream_events` loop, where we pass in the chain input and emit desired results. See the [API reference](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.astream_events) and [streaming guide](/docs/how_to/streaming) for more detail." + "In general there can be multiple chat model invocations in an application (although here there is just one). Below, we filter to only the last step using the name of the corresponding node:" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "3ef2af40-e6ce-42a3-ad6a-ee405ad7f8ad", + "execution_count": 10, + "id": "e313d2c2-b2bb-4f84-8227-b91d988ded24", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "|What| are| some| typical| methods| used| for| task| decomposition|?||" + "|Task| De|composition| is| a| technique| used| to| break| down| complex| tasks| into| smaller|,| more| manageable| steps|.| It| often| involves| prompting| models| to| \"|think| step| by| step|,\"| allowing| for| clearer| reasoning| and| better| performance| on| intricate| problems|.| This| can| be| achieved| through| various| methods|,| including| simple| prompts|,| task|-specific| instructions|,| or| human| input|.||" ] } ], "source": [ - "first_question = \"What is task decomposition?\"\n", - "first_answer = (\n", - " \"Task decomposition involves breaking up \"\n", - " \"a complex task into smaller and simpler \"\n", - " \"steps.\"\n", - ")\n", - "follow_up_question = \"What are some common ways of doing it?\"\n", - "\n", - "chat_history = [\n", - " (\"human\", first_question),\n", - " (\"ai\", first_answer),\n", - "]\n", + "input_message = \"What is Task Decomposition?\"\n", "\n", - "\n", - "async for event in rag_chain.astream_events(\n", - " {\n", - " \"input\": follow_up_question,\n", - " \"chat_history\": chat_history,\n", - " },\n", - " version=\"v1\",\n", + "for message, metadata in graph.stream(\n", + " {\"question\": \"What is Task Decomposition?\"},\n", + " # highlight-next-line\n", + " stream_mode=\"messages\",\n", "):\n", - " if (\n", - " event[\"event\"] == \"on_chat_model_stream\"\n", - " and \"contextualize_q_llm\" in event[\"tags\"]\n", - " ):\n", - " ai_message_chunk = event[\"data\"][\"chunk\"]\n", - " print(f\"{ai_message_chunk.content}|\", end=\"\")" + " if metadata[\"langgraph_node\"] == \"generate\":\n", + " print(message.content, end=\"|\")" ] }, { "cell_type": "markdown", - "id": "7da5dd1b-634c-4dd7-8235-69adec21d195", + "id": "fdee7ae6-4a81-46ab-8efd-d2310b596f8c", "metadata": {}, "source": [ - "Here we recover, token-by-token, the query that is passed into the retriever given our question \"What are some common ways of doing it?\"\n", + "## Streaming intermediate steps\n", "\n", - "If we wanted to get our retrieved docs, we could filter on name \"Retriever\":" + "Other streaming modes will generally stream steps from our invocation-- i.e., state updates from individual nodes. In this case, each node is just appending a new key to the state:" ] }, { "cell_type": "code", - "execution_count": 8, - "id": "987ef6be-8c4e-4257-828a-a3b4fb4ccc99", + "execution_count": 11, + "id": "8807d58d-7581-4360-8bd5-619e99ff3ce9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'event': 'on_retriever_start', 'name': 'Retriever', 'run_id': '6834097c-07fe-42f5-a566-a4780af4d1d0', 'tags': ['seq:step:4', 'Chroma', 'OpenAIEmbeddings'], 'metadata': {}, 'data': {'input': {'query': 'What are some typical methods used for task decomposition?'}}}\n", + "{'retrieve': {'context': [Document(id='5bf5e308-6ccb-4f09-94d2-d0c36b8c9980', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.'), Document(id='d8aed221-7943-414d-8ed7-63c2b0e7523b', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.'), Document(id='bfa87007-02ef-4f81-a008-4522ecea1025', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.'), Document(id='6aff7fc0-5c21-4986-9f1e-91e89715d934', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}, page_content=\"(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\")]}}\n", + "\n", + "----------------\n", + "\n", + "{'generate': {'answer': 'Task Decomposition is the process of breaking down a complex task into smaller, manageable steps to enhance understanding and execution. Techniques like Chain of Thought (CoT) and Tree of Thoughts (ToT) guide models to think through steps systematically, allowing for better problem-solving. It can be achieved through simple prompting, task-specific instructions, or human input.'}}\n", "\n", - "{'event': 'on_retriever_end', 'name': 'Retriever', 'run_id': '6834097c-07fe-42f5-a566-a4780af4d1d0', 'tags': ['seq:step:4', 'Chroma', 'OpenAIEmbeddings'], 'metadata': {}, 'data': {'input': {'query': 'What are some typical methods used for task decomposition?'}, 'output': {'documents': [Document(page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}), Document(page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}), Document(page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}), Document(page_content='Fig. 9. Comparison of MIPS algorithms, measured in recall@10. (Image source: Google Blog, 2020)\\nCheck more MIPS algorithms and performance comparison in ann-benchmarks.com.\\nComponent Three: Tool Use#\\nTool use is a remarkable and distinguishing characteristic of human beings. We create, modify and utilize external objects to do things that go beyond our physical and cognitive limits. Equipping LLMs with external tools can significantly extend the model capabilities.', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'})]}}}\n", + "----------------\n", "\n" ] } ], "source": [ - "async for event in rag_chain.astream_events(\n", - " {\n", - " \"input\": follow_up_question,\n", - " \"chat_history\": chat_history,\n", - " },\n", - " version=\"v1\",\n", + "for step in graph.stream(\n", + " {\"question\": \"What is Task Decomposition?\"},\n", + " # highlight-next-line\n", + " stream_mode=\"updates\",\n", "):\n", - " if event[\"name\"] == \"Retriever\":\n", - " print(event)\n", - " print()" + " print(f\"{step}\\n\\n----------------\\n\")" ] }, { @@ -517,7 +350,7 @@ "id": "c5470a79-258a-4108-8ceb-dfe8180160ca", "metadata": {}, "source": [ - "For more on how to stream intermediate steps check out the [streaming guide](/docs/how_to/streaming)." + "For more on streaming with LangGraph, check out its [streaming documentation](https://langchain-ai.github.io/langgraph/how-tos/#streaming). For more information on streaming individual LangChain [Runnables](/docs/concepts/runnables/), refer to [this guide](/docs/how_to/streaming/)." ] } ], diff --git a/docs/docs/how_to/query_few_shot.ipynb b/docs/docs/how_to/query_few_shot.ipynb index 8955c4490c9ee..ac66dc89ee402 100644 --- a/docs/docs/how_to/query_few_shot.ipynb +++ b/docs/docs/how_to/query_few_shot.ipynb @@ -19,7 +19,7 @@ "\n", "As our query analysis becomes more complex, the LLM may struggle to understand how exactly it should respond in certain scenarios. In order to improve performance here, we can [add examples](/docs/concepts/few_shot_prompting/) to the prompt to guide the LLM.\n", "\n", - "Let's take a look at how we can add examples for the LangChain YouTube video query analyzer we built in the [Quickstart](/docs/tutorials/query_analysis)." + "Let's take a look at how we can add examples for a LangChain YouTube video query analyzer." ] }, { diff --git a/docs/docs/how_to/sql_large_db.ipynb b/docs/docs/how_to/sql_large_db.ipynb index 53f4bf6224d8f..154bda4dc9b24 100644 --- a/docs/docs/how_to/sql_large_db.ipynb +++ b/docs/docs/how_to/sql_large_db.ipynb @@ -55,7 +55,7 @@ "* Run `.read Chinook_Sqlite.sql`\n", "* Test `SELECT * FROM Artist LIMIT 10;`\n", "\n", - "Now, `Chinhook.db` is in our directory and we can interface with it using the SQLAlchemy-driven [SQLDatabase](https://python.langchain.com/api_reference/community/utilities/langchain_community.utilities.sql_database.SQLDatabase.html) class:" + "Now, `Chinook.db` is in our directory and we can interface with it using the SQLAlchemy-driven [SQLDatabase](https://python.langchain.com/api_reference/community/utilities/langchain_community.utilities.sql_database.SQLDatabase.html) class:" ] }, { diff --git a/docs/docs/how_to/sql_prompting.ipynb b/docs/docs/how_to/sql_prompting.ipynb index 831a7bca13a51..5908ccd14dd57 100644 --- a/docs/docs/how_to/sql_prompting.ipynb +++ b/docs/docs/how_to/sql_prompting.ipynb @@ -51,7 +51,7 @@ "* Run `.read Chinook_Sqlite.sql`\n", "* Test `SELECT * FROM Artist LIMIT 10;`\n", "\n", - "Now, `Chinhook.db` is in our directory and we can interface with it using the SQLAlchemy-driven `SQLDatabase` class:" + "Now, `Chinook.db` is in our directory and we can interface with it using the SQLAlchemy-driven `SQLDatabase` class:" ] }, { diff --git a/docs/docs/how_to/sql_query_checking.ipynb b/docs/docs/how_to/sql_query_checking.ipynb index e15609d7ba4df..ab1a875fdf61e 100644 --- a/docs/docs/how_to/sql_query_checking.ipynb +++ b/docs/docs/how_to/sql_query_checking.ipynb @@ -54,7 +54,7 @@ "* Run `.read Chinook_Sqlite.sql`\n", "* Test `SELECT * FROM Artist LIMIT 10;`\n", "\n", - "Now, `Chinhook.db` is in our directory and we can interface with it using the SQLAlchemy-driven `SQLDatabase` class:" + "Now, `Chinook.db` is in our directory and we can interface with it using the SQLAlchemy-driven `SQLDatabase` class:" ] }, { diff --git a/docs/docs/integrations/callbacks/uptrain.ipynb b/docs/docs/integrations/callbacks/uptrain.ipynb index 7dcf97c517517..51619215d09a0 100644 --- a/docs/docs/integrations/callbacks/uptrain.ipynb +++ b/docs/docs/integrations/callbacks/uptrain.ipynb @@ -336,7 +336,7 @@ "\n", "The **MultiQueryRetriever** is used to tackle the problem that the RAG pipeline might not return the best set of documents based on the query. It generates multiple queries that mean the same as the original query and then fetches documents for each.\n", "\n", - "To evluate this retriever, UpTrain will run the following evaluation:\n", + "To evaluate this retriever, UpTrain will run the following evaluation:\n", "- **[Multi Query Accuracy](https://docs.uptrain.ai/predefined-evaluations/query-quality/multi-query-accuracy)**: Checks if the multi-queries generated mean the same as the original query." ] }, diff --git a/docs/docs/integrations/chat/cerebras.ipynb b/docs/docs/integrations/chat/cerebras.ipynb index 76c0fb8e1720f..e6ad0cf8938e7 100644 --- a/docs/docs/integrations/chat/cerebras.ipynb +++ b/docs/docs/integrations/chat/cerebras.ipynb @@ -17,7 +17,7 @@ "source": [ "# ChatCerebras\n", "\n", - "This notebook provides a quick overview for getting started with Cerebras [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatCerebras features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_cerebras.chat_models.ChatCerebras.html).\n", + "This notebook provides a quick overview for getting started with Cerebras [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatCerebras features and configurations head to the [API reference](https://python.langchain.com/api_reference/cerebras/chat_models/langchain_cerebras.chat_models.ChatCerebras.html#).\n", "\n", "At Cerebras, we've developed the world's largest and fastest AI processor, the Wafer-Scale Engine-3 (WSE-3). The Cerebras CS-3 system, powered by the WSE-3, represents a new class of AI supercomputer that sets the standard for generative AI training and inference with unparalleled performance and scalability.\n", "\n", @@ -37,7 +37,7 @@ "\n", "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/cerebras) | Package downloads | Package latest |\n", "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", - "| [ChatCerebras](https://api.python.langchain.com/en/latest/chat_models/langchain_cerebras.chat_models.ChatCerebras.html) | [langchain-cerebras](https://api.python.langchain.com/en/latest/cerebras_api_reference.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-cerebras?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-cerebras?style=flat-square&label=%20) |\n", + "| [ChatCerebras](https://python.langchain.com/api_reference/cerebras/chat_models/langchain_cerebras.chat_models.ChatCerebras.html#) | [langchain-cerebras](https://python.langchain.com/api_reference/cerebras/index.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-cerebras?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-cerebras?style=flat-square&label=%20) |\n", "\n", "### Model features\n", "| [Tool calling](/docs/how_to/tool_calling/) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n", @@ -396,7 +396,7 @@ "source": [ "## API reference\n", "\n", - "For detailed documentation of all ChatCerebras features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/langchain_cerebras.chat_models.ChatCerebras.html" + "For detailed documentation of all ChatCerebras features and configurations head to the API reference: https://python.langchain.com/api_reference/cerebras/chat_models/langchain_cerebras.chat_models.ChatCerebras.html#" ] } ], diff --git a/docs/docs/integrations/chat/ibm_watsonx.ipynb b/docs/docs/integrations/chat/ibm_watsonx.ipynb index a3ef2d572397d..e6755d9a4b797 100644 --- a/docs/docs/integrations/chat/ibm_watsonx.ipynb +++ b/docs/docs/integrations/chat/ibm_watsonx.ipynb @@ -36,7 +36,7 @@ "### Integration details\n", "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/ibm/) | Package downloads | Package latest |\n", "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", - "| [ChatWatsonx](https://python.langchain.com/api_reference/ibm/chat_models/langchain_ibm.chat_models.ChatWatsonx.html#langchain_ibm.chat_models.ChatWatsonx) | [langchain-ibm](https://python.langchain.com/api_reference/ibm/index.html) | ❌ | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-ibm?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-ibm?style=flat-square&label=%20) |\n", + "| [ChatWatsonx](https://python.langchain.com/api_reference/ibm/chat_models/langchain_ibm.chat_models.ChatWatsonx.html) | [langchain-ibm](https://python.langchain.com/api_reference/ibm/index.html) | ❌ | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-ibm?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-ibm?style=flat-square&label=%20) |\n", "\n", "### Model features\n", "| [Tool calling](/docs/how_to/tool_calling/) | [Structured output](/docs/how_to/structured_output/) | JSON mode | Image input | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n", diff --git a/docs/docs/integrations/chat/llama2_chat.ipynb b/docs/docs/integrations/chat/llama2_chat.ipynb index dbcfce36fd917..d2cf635dd1945 100644 --- a/docs/docs/integrations/chat/llama2_chat.ipynb +++ b/docs/docs/integrations/chat/llama2_chat.ipynb @@ -17,7 +17,7 @@ "source": [ "# Llama2Chat\n", "\n", - "This notebook shows how to augment Llama-2 `LLM`s with the `Llama2Chat` wrapper to support the [Llama-2 chat prompt format](https://huggingface.co/blog/llama2#how-to-prompt-llama-2). Several `LLM` implementations in LangChain can be used as interface to Llama-2 chat models. These include [ChatHuggingFace](/docs/integrations/chat/huggingface), [LlamaCpp](/docs/tutorials/local_rag), [GPT4All](/docs/integrations/llms/gpt4all), ..., to mention a few examples. \n", + "This notebook shows how to augment Llama-2 `LLM`s with the `Llama2Chat` wrapper to support the [Llama-2 chat prompt format](https://huggingface.co/blog/llama2#how-to-prompt-llama-2). Several `LLM` implementations in LangChain can be used as interface to Llama-2 chat models. These include [ChatHuggingFace](/docs/integrations/chat/huggingface), [LlamaCpp](/docs/integrations/chat/llamacpp/), [GPT4All](/docs/integrations/llms/gpt4all), ..., to mention a few examples. \n", "\n", "`Llama2Chat` is a generic wrapper that implements `BaseChatModel` and can therefore be used in applications as [chat model](/docs/how_to#chat-models). `Llama2Chat` converts a list of Messages into the [required chat prompt format](https://huggingface.co/blog/llama2#how-to-prompt-llama-2) and forwards the formatted prompt as `str` to the wrapped `LLM`." ] diff --git a/docs/docs/integrations/chat/mistralai.ipynb b/docs/docs/integrations/chat/mistralai.ipynb index d399f416da830..8ed4de91727ac 100644 --- a/docs/docs/integrations/chat/mistralai.ipynb +++ b/docs/docs/integrations/chat/mistralai.ipynb @@ -39,7 +39,7 @@ "### Credentials\n", "\n", "\n", - "A valid [API key](https://console.mistral.ai/users/api-keys/) is needed to communicate with the API. Once you've done this set the MISTRAL_API_KEY environment variable:" + "A valid [API key](https://console.mistral.ai/api-keys/) is needed to communicate with the API. Once you've done this set the MISTRAL_API_KEY environment variable:" ] }, { diff --git a/docs/docs/integrations/chat/oci_data_science.ipynb b/docs/docs/integrations/chat/oci_data_science.ipynb index b5a8f040d901b..6196d2025c04b 100644 --- a/docs/docs/integrations/chat/oci_data_science.ipynb +++ b/docs/docs/integrations/chat/oci_data_science.ipynb @@ -19,7 +19,7 @@ "source": [ "# ChatOCIModelDeployment\n", "\n", - "This will help you getting started with OCIModelDeployment [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatOCIModelDeployment features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.ChatOCIModelDeployment.html).\n", + "This will help you getting started with OCIModelDeployment [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatOCIModelDeployment features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html).\n", "\n", "[OCI Data Science](https://docs.oracle.com/en-us/iaas/data-science/using/home.htm) is a fully managed and serverless platform for data science teams to build, train, and manage machine learning models in the Oracle Cloud Infrastructure. You can use [AI Quick Actions](https://blogs.oracle.com/ai-and-datascience/post/ai-quick-actions-in-oci-data-science) to easily deploy LLMs on [OCI Data Science Model Deployment Service](https://docs.oracle.com/en-us/iaas/data-science/using/model-dep-about.htm). You may choose to deploy the model with popular inference frameworks such as vLLM or TGI. By default, the model deployment endpoint mimics the OpenAI API protocol.\n", "\n", @@ -30,7 +30,7 @@ "\n", "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n", "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", - "| [ChatOCIModelDeployment](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.ChatOCIModelDeployment.html) | [langchain-community](https://api.python.langchain.com/en/latest/community_api_reference.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n", + "| [ChatOCIModelDeployment](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n", "\n", "### Model features\n", "\n", @@ -430,9 +430,9 @@ "\n", "For comprehensive details on all features and configurations, please refer to the API reference documentation for each class:\n", "\n", - "* [ChatOCIModelDeployment](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html)\n", - "* [ChatOCIModelDeploymentVLLM](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentVLLM.html)\n", - "* [ChatOCIModelDeploymentTGI](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentTGI.html)" + "* [ChatOCIModelDeployment](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html)\n", + "* [ChatOCIModelDeploymentVLLM](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentVLLM.html)\n", + "* [ChatOCIModelDeploymentTGI](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentTGI.html)" ] } ], diff --git a/docs/docs/integrations/chat/outlines.ipynb b/docs/docs/integrations/chat/outlines.ipynb index 1d53def18b9aa..001ecf1d2b4ec 100644 --- a/docs/docs/integrations/chat/outlines.ipynb +++ b/docs/docs/integrations/chat/outlines.ipynb @@ -17,7 +17,7 @@ "source": [ "# ChatOutlines\n", "\n", - "This will help you getting started with Outlines [chat models](/docs/concepts/chat_models/). For detailed documentation of all ChatOutlines features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html).\n", + "This will help you getting started with Outlines [chat models](/docs/concepts/chat_models/). For detailed documentation of all ChatOutlines features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html).\n", "\n", "[Outlines](https://github.com/outlines-dev/outlines) is a library for constrained language generation. It allows you to use large language models (LLMs) with various backends while applying constraints to the generated output.\n", "\n", @@ -26,7 +26,7 @@ "\n", "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n", "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", - "| [ChatOutlines](https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html) | [langchain-community](https://api.python.langchain.com/en/latest/community_api_reference.html) | ✅ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n", + "| [ChatOutlines](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n", "\n", "### Model features\n", "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n", @@ -316,7 +316,7 @@ "source": [ "## API reference\n", "\n", - "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html\n", + "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html\n", "\n", "## Full Outlines Documentation: \n", "\n", diff --git a/docs/docs/integrations/chat/sambastudio.ipynb b/docs/docs/integrations/chat/sambastudio.ipynb index 64dd05fd96b8c..1ad3ff2805049 100644 --- a/docs/docs/integrations/chat/sambastudio.ipynb +++ b/docs/docs/integrations/chat/sambastudio.ipynb @@ -19,7 +19,7 @@ "source": [ "# ChatSambaStudio\n", "\n", - "This will help you getting started with SambaStudio [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatStudio features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html).\n", + "This will help you getting started with SambaStudio [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatStudio features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html).\n", "\n", "**[SambaNova](https://sambanova.ai/)'s** [SambaStudio](https://docs.sambanova.ai/sambastudio/latest/sambastudio-intro.html) SambaStudio is a rich, GUI-based platform that provides the functionality to train, deploy, and manage models in SambaNova [DataScale](https://sambanova.ai/products/datascale) systems.\n", "\n", @@ -28,7 +28,7 @@ "\n", "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n", "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", - "| [ChatSambaStudio](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n", + "| [ChatSambaStudio](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n", "\n", "### Model features\n", "\n", @@ -355,7 +355,7 @@ "source": [ "## API reference\n", "\n", - "For detailed documentation of all ChatSambaStudio features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html" + "For detailed documentation of all ChatSambaStudio features and configurations head to the API reference: https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html" ] } ], diff --git a/docs/docs/integrations/chat/writer.ipynb b/docs/docs/integrations/chat/writer.ipynb index a76752ef2f64c..9efa41f6f4799 100644 --- a/docs/docs/integrations/chat/writer.ipynb +++ b/docs/docs/integrations/chat/writer.ipynb @@ -1,14 +1,14 @@ { "cells": [ { - "metadata": {}, "cell_type": "raw", + "id": "85e07aae70a15572", + "metadata": {}, "source": [ "---\n", "sidebar_label: Writer\n", "---" - ], - "id": "85e07aae70a15572" + ] }, { "cell_type": "markdown", @@ -26,20 +26,20 @@ }, { "cell_type": "markdown", - "id": "e49f1e0d", + "id": "617a6e98205ab7c8", "metadata": {}, "source": [ "## Overview\n", "\n", "### Integration details\n", - "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/openai) | Package downloads | Package latest |\n", - "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", - "| ChatWriter | langchain-community | ❌ | ❌ | ❌ | ❌ | ❌ |\n", + "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n", + "| :--- | :--- | :---: | :---: |:----------:| :---: | :---: |\n", + "| ChatWriter | langchain-community | ❌ | ❌ | ❌ | ❌ | ❌ |\n", "\n", "### Model features\n", - "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | Image input | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n", - "| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |\n", - "| ✅ | ❌ | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | \n", + "| [Tool calling](/docs/how_to/tool_calling) | Structured output | JSON mode | Image input | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | Logprobs |\n", + "| :---: |:-----------------:| :---: | :---: | :---: | :---: | :---: | :---: |:--------------------------------:|:--------:|\n", + "| ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ |\n", "\n", "## Setup\n", "\n", @@ -52,22 +52,22 @@ }, { "cell_type": "code", + "execution_count": 1, "id": "e817fe2e-4f1d-4533-b19e-2400b1cf6ce8", "metadata": { "ExecuteTime": { - "end_time": "2024-10-24T13:51:54.323678Z", - "start_time": "2024-10-24T13:51:42.127404Z" + "end_time": "2024-11-14T09:46:26.800627Z", + "start_time": "2024-11-14T09:27:59.652281Z" } }, + "outputs": [], "source": [ "import getpass\n", "import os\n", "\n", "if not os.environ.get(\"WRITER_API_KEY\"):\n", - " os.environ[\"WRITER_API_KEY\"] = getpass.getpass(\"Enter your Writer API key: \")" - ], - "outputs": [], - "execution_count": 1 + " os.environ[\"WRITER_API_KEY\"] = getpass.getpass(\"Enter your Writer API key:\")" + ] }, { "cell_type": "markdown", @@ -81,26 +81,29 @@ }, { "cell_type": "code", + "execution_count": 2, "id": "2113471c-75d7-45df-b784-d78da4ef7aba", "metadata": { "ExecuteTime": { - "end_time": "2024-10-24T13:52:49.262240Z", - "start_time": "2024-10-24T13:52:47.564879Z" + "end_time": "2024-11-14T09:46:32.415354Z", + "start_time": "2024-11-14T09:46:26.826112Z" } }, - "source": [ - "%pip install -qU langchain-community writer-sdk" - ], "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "\r\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\u001b[0m\r\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\r\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], - "execution_count": 4 + "source": [ + "%pip install -qU langchain-community writer-sdk" + ] }, { "cell_type": "markdown", @@ -114,14 +117,16 @@ }, { "cell_type": "code", + "execution_count": 3, "id": "522686de", "metadata": { - "tags": [], "ExecuteTime": { - "end_time": "2024-10-24T13:52:38.822950Z", - "start_time": "2024-10-24T13:52:38.674441Z" - } + "end_time": "2024-11-14T09:46:33.504711Z", + "start_time": "2024-11-14T09:46:32.574505Z" + }, + "tags": [] }, + "outputs": [], "source": [ "from langchain_community.chat_models.writer import ChatWriter\n", "\n", @@ -129,25 +134,9 @@ " model=\"palmyra-x-004\",\n", " temperature=0.7,\n", " max_tokens=1000,\n", - " # api_key=\"...\", # if you prefer to pass api key in directly instaed of using env vars\n", - " # base_url=\"...\",\n", " # other params...\n", ")" - ], - "outputs": [ - { - "ename": "ImportError", - "evalue": "cannot import name 'ChatWriter' from 'langchain_community.chat_models' (/home/yanomaly/PycharmProjects/whitesnake/writer/langсhain/libs/community/langchain_community/chat_models/__init__.py)", - "output_type": "error", - "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mImportError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[3], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mlangchain_community\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mchat_models\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m ChatWriter\n\u001B[1;32m 3\u001B[0m llm \u001B[38;5;241m=\u001B[39m ChatWriter(\n\u001B[1;32m 4\u001B[0m model\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mpalmyra-x-004\u001B[39m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 5\u001B[0m temperature\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m0.7\u001B[39m,\n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 9\u001B[0m \u001B[38;5;66;03m# other params...\u001B[39;00m\n\u001B[1;32m 10\u001B[0m )\n", - "\u001B[0;31mImportError\u001B[0m: cannot import name 'ChatWriter' from 'langchain_community.chat_models' (/home/yanomaly/PycharmProjects/whitesnake/writer/langсhain/libs/community/langchain_community/chat_models/__init__.py)" - ] - } - ], - "execution_count": 3 + ] }, { "cell_type": "markdown", @@ -159,9 +148,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "ce16ad78-8e6f-48cd-954e-98be75eb5836", "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:38.856174Z", + "start_time": "2024-11-14T09:46:33.520062Z" + }, "tags": [] }, "outputs": [], @@ -173,18 +166,128 @@ " ),\n", " (\"human\", \"Write a poem about Python.\"),\n", "]\n", - "ai_msg = llm.invoke(messages)\n", - "ai_msg" + "ai_msg = llm.invoke(messages)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "2cd224b8-4499-41fb-a604-d53a7ff17b2e", + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:38.866651Z", + "start_time": "2024-11-14T09:46:38.863817Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "In realms of code, where logic weaves and flows,\n", + "A language rises, Python by its name,\n", + "With syntax clear, where elegance it shows,\n", + "A serpent, wise, that time and space can tame.\n", + "\n", + "Born from the mind of Guido, pure and bright,\n", + "Its beauty lies in simplicity and grace,\n", + "A tool of power, yet gentle in its might,\n", + "In every programmer's heart, a cherished place.\n", + "\n", + "It dances through the data, vast and deep,\n", + "With libraries that span the digital realm,\n", + "From machine learning's secrets to keep,\n", + "To web development, it wields the helm.\n", + "\n", + "In the hands of the novice and the sage,\n", + "Python spins the threads of digital dreams,\n", + "A language that can turn the age,\n", + "With a gentle learning curve, its appeal gleams.\n", + "\n", + "It's more than code, a community it builds,\n", + "Where knowledge freely flows, and all are heard,\n", + "In Python's world, the future unfolds,\n", + "A language of the people, for the world.\n", + "\n", + "So here's to Python, in its gentle might,\n", + "A master of the modern coding art,\n", + "May it continue to light our path each night,\n", + "In the vast, evolving world of code, its heart.\n" + ] + } + ], + "source": [ + "print(ai_msg.content)" + ] + }, + { + "cell_type": "markdown", + "id": "35b3a5b3dabef65", "metadata": {}, + "source": [ + "## Streaming" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2725770182bf96dc", + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:38.914883Z", + "start_time": "2024-11-14T09:46:38.912564Z" + } + }, "outputs": [], "source": [ - "print(ai_msg.content)" + "ai_stream = llm.stream(messages)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a48410d9488162e3", + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:43.226449Z", + "start_time": "2024-11-14T09:46:38.955512Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "In realms of code where logic weaves,\n", + "A language rises, Python, it breezes,\n", + "With syntax clear and simple to read,\n", + "Through its elegance, our spirits are fed.\n", + "\n", + "Like rivers flowing, smooth and serene,\n", + "Its structure harmonious, a coder's dream,\n", + "Indentations guide the flow of control,\n", + "In Python's world, confusion takes no toll.\n", + "\n", + "A vast library, a treasure trove so bright,\n", + "For web and data, it offers its might,\n", + "With modules and packages, a rich array,\n", + "Python empowers us to code in play.\n", + "\n", + "From AI to scripts, in flexibility it thrives,\n", + "A language of the future, as many now derive,\n", + "Its community, a beacon of support and cheer,\n", + "With Python, the possibilities are vast, far and near.\n", + "\n", + "So here's to Python, in its gentle grace,\n", + "A tool that enhances, a language that embraces,\n", + "The art of coding, with a fluent, flowing pen,\n", + "In the Python world, we code, and we begin." + ] + } + ], + "source": [ + "for chunk in ai_stream:\n", + " print(chunk.content, end=\"\")" ] }, { @@ -199,12 +302,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "fbb043e6", "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:50.721645Z", + "start_time": "2024-11-14T09:46:43.234590Z" + }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "AIMessageChunk(content='In the realm of code, where logic weaves and flows, \\nA language rises, like a phoenix from the code\\'s throes. \\nJava, the name, a cup of coffee\\'s steam, \\nBrewed in the minds, where digital dreams gleam.\\n\\nWith syntax clear, like morning\\'s misty hue, \\nIn classes and objects, it spins a tale so true. \\nA platform agnostic, with a byte to spare, \\nAcross the devices, it journeys everywhere.\\n\\nInheritance and polymorphism, its power\\'s core, \\nLike ancient runes, in every line they bore. \\nEncapsulation, a shield, with data it does hide, \\nIn the vast jungle of code, it stands as a guide.\\n\\nFrom applets small, to vast, server-side apps, \\nIts threads run swift, through the computing traps. \\nA language of the people, by the people, for the people’s use, \\nBuilt on the principle, \"write once, run anywhere, with no excuse.\"\\n\\nIn the heart of Android, it beats, a steady drum, \\nCrafting experiences, in every smartphone\\'s hum. \\nIn the cloud, in the enterprise, its presence is vast, \\nA cornerstone of computing, built to last.\\n\\nOh Java, thy elegance, thy robust design, \\nA language that stands, in any computing line. \\nWith every update, with every new release, \\nThy community grows, with a vibrant, diverse peace.\\n\\nSo here\\'s to Java, the versatile, the grand, \\nA language that shapes the digital land. \\nMay it continue to evolve, to grow, to inspire, \\nIn the endless quest of turning thoughts into digital fire.', additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 345, 'prompt_tokens': 33, 'total_tokens': 378, 'completion_tokens_details': None, 'prompt_token_details': None}, 'model_name': 'palmyra-x-004', 'system_fingerprint': 'v1', 'finish_reason': 'stop'}, id='run-a5b4be59-0eb0-41bd-80f7-72477861b0bd-0')" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from langchain_core.prompts import ChatPromptTemplate\n", "\n", @@ -251,9 +369,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "id": "b7ea7690-ec7a-4337-b392-e87d1f39a6ec", - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:50.891937Z", + "start_time": "2024-11-14T09:46:50.733463Z" + } + }, "outputs": [], "source": [ "from pydantic import BaseModel, Field\n", @@ -270,15 +393,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "1d1ab955-6a68-42f8-bb5d-86eb1111478a", - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:51.725422Z", + "start_time": "2024-11-14T09:46:50.904699Z" + } + }, "outputs": [], "source": [ "ai_msg = llm_with_tools.invoke(\n", " \"what is the weather like in New York City\",\n", - ")\n", - "ai_msg" + ")" ] }, { @@ -292,12 +419,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "166cb7ce-831d-4a7c-9721-abc107f11084", - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T09:46:51.744202Z", + "start_time": "2024-11-14T09:46:51.738431Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'name': 'GetWeather',\n", + " 'args': {'location': 'New York City, NY'},\n", + " 'id': 'chatcmpl-tool-fe70912c800d40fc8700d604d4823001',\n", + " 'type': 'tool_call'}]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "ai_msg.tool_calls" + "print(ai_msg.tool_calls)" ] }, { diff --git a/docs/docs/integrations/document_loaders/needle.ipynb b/docs/docs/integrations/document_loaders/needle.ipynb new file mode 100644 index 0000000000000..1ea138456112e --- /dev/null +++ b/docs/docs/integrations/document_loaders/needle.ipynb @@ -0,0 +1,253 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Needle Document Loader\n", + "[Needle](https://needle-ai.com) makes it easy to create your RAG pipelines with minimal effort. \n", + "\n", + "For more details, refer to our [API documentation](https://docs.needle-ai.com/docs/api-reference/needle-api)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Overview\n", + "The Needle Document Loader is a utility for integrating Needle collections with LangChain. It enables seamless storage, retrieval, and utilization of documents for Retrieval-Augmented Generation (RAG) workflows.\n", + "\n", + "This example demonstrates:\n", + "\n", + "* Storing documents into a Needle collection.\n", + "* Setting up a retriever to fetch documents.\n", + "* Building a Retrieval-Augmented Generation (RAG) pipeline." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Setup\n", + "Before starting, ensure you have the following environment variables set:\n", + "\n", + "* NEEDLE_API_KEY: Your API key for authenticating with Needle.\n", + "* OPENAI_API_KEY: Your OpenAI API key for language model operations." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "os.environ[\"NEEDLE_API_KEY\"] = \"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "os.environ[\"OPENAI_API_KEY\"] = \"\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Initialization\n", + "To initialize the NeedleLoader, you need the following parameters:\n", + "\n", + "* needle_api_key: Your Needle API key (or set it as an environment variable).\n", + "* collection_id: The ID of the Needle collection to work with." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Instantiation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_community.document_loaders.needle import NeedleLoader\n", + "\n", + "collection_id = \"clt_01J87M9T6B71DHZTHNXYZQRG5H\"\n", + "\n", + "# Initialize NeedleLoader to store documents to the collection\n", + "document_loader = NeedleLoader(\n", + " needle_api_key=os.getenv(\"NEEDLE_API_KEY\"),\n", + " collection_id=collection_id,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load\n", + "To add files to the Needle collection:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "files = {\n", + " \"tech-radar-30.pdf\": \"https://www.thoughtworks.com/content/dam/thoughtworks/documents/radar/2024/04/tr_technology_radar_vol_30_en.pdf\"\n", + "}\n", + "\n", + "document_loader.add_files(files=files)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Show the documents in the collection\n", + "# collections_documents = document_loader.load()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lazy Load\n", + "The lazy_load method allows you to iteratively load documents from the Needle collection, yielding each document as it is fetched:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Show the documents in the collection\n", + "# collections_documents = document_loader.lazy_load()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Usage\n", + "### Use within a chain\n", + "Below is a complete example of setting up a RAG pipeline with Needle within a chain:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'input': 'Did RAG move to accepted?',\n", + " 'context': [Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.')],\n", + " 'answer': 'Yes, RAG has been adopted as the preferred pattern for improving the quality of responses generated by a large language model.'}" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "\n", + "from langchain.chains import create_retrieval_chain\n", + "from langchain.chains.combine_documents import create_stuff_documents_chain\n", + "from langchain_community.retrievers.needle import NeedleRetriever\n", + "from langchain_core.prompts import ChatPromptTemplate\n", + "from langchain_openai import ChatOpenAI\n", + "\n", + "llm = ChatOpenAI(temperature=0)\n", + "\n", + "# Initialize the Needle retriever (make sure your Needle API key is set as an environment variable)\n", + "retriever = NeedleRetriever(\n", + " needle_api_key=os.getenv(\"NEEDLE_API_KEY\"),\n", + " collection_id=\"clt_01J87M9T6B71DHZTHNXYZQRG5H\",\n", + ")\n", + "\n", + "# Define system prompt for the assistant\n", + "system_prompt = \"\"\"\n", + " You are an assistant for question-answering tasks. \n", + " Use the following pieces of retrieved context to answer the question.\n", + " If you don't know, say so concisely.\\n\\n{context}\n", + " \"\"\"\n", + "\n", + "prompt = ChatPromptTemplate.from_messages(\n", + " [(\"system\", system_prompt), (\"human\", \"{input}\")]\n", + ")\n", + "\n", + "# Define the question-answering chain using a document chain (stuff chain) and the retriever\n", + "question_answer_chain = create_stuff_documents_chain(llm, prompt)\n", + "\n", + "# Create the RAG (Retrieval-Augmented Generation) chain by combining the retriever and the question-answering chain\n", + "rag_chain = create_retrieval_chain(retriever, question_answer_chain)\n", + "\n", + "# Define the input query\n", + "query = {\"input\": \"Did RAG move to accepted?\"}\n", + "\n", + "response = rag_chain.invoke(query)\n", + "\n", + "response" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## API reference\n", + "\n", + "For detailed documentation of all `Needle` features and configurations head to the API reference: https://docs.needle-ai.com" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb b/docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb index b3dadb1f0ad81..6b8894491f30f 100644 --- a/docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb +++ b/docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb @@ -115,7 +115,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The `AzureOpenAIWhisperParser` can also be used in conjuction with audio loaders, like the `YoutubeAudioLoader` with a `GenericLoader`." + "The `AzureOpenAIWhisperParser` can also be used in conjunction with audio loaders, like the `YoutubeAudioLoader` with a `GenericLoader`." ] }, { diff --git a/docs/docs/integrations/document_loaders/sitemap.ipynb b/docs/docs/integrations/document_loaders/sitemap.ipynb index e930b12de31ff..ed6c74d406bfe 100644 --- a/docs/docs/integrations/document_loaders/sitemap.ipynb +++ b/docs/docs/integrations/document_loaders/sitemap.ipynb @@ -103,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ diff --git a/docs/docs/integrations/document_loaders/tomarkdown.ipynb b/docs/docs/integrations/document_loaders/tomarkdown.ipynb index ffc41ea4e5f7c..0f3ce0de36a55 100644 --- a/docs/docs/integrations/document_loaders/tomarkdown.ipynb +++ b/docs/docs/integrations/document_loaders/tomarkdown.ipynb @@ -153,7 +153,7 @@ "\n", "Best practices for developing with LangChain.\n", "\n", - "### [API reference](https://api.python.langchain.com) [​](\\#api-reference \"Direct link to api-reference\")\n", + "### [API reference](https://python.langchain.com/api_reference/) [​](\\#api-reference \"Direct link to api-reference\")\n", "\n", "Head to the reference section for full documentation of all classes and methods in the LangChain and LangChain Experimental Python packages.\n", "\n", diff --git a/docs/docs/integrations/graphs/apache_age.ipynb b/docs/docs/integrations/graphs/apache_age.ipynb index b3c39e974ab6a..588567c018cdc 100644 --- a/docs/docs/integrations/graphs/apache_age.ipynb +++ b/docs/docs/integrations/graphs/apache_age.ipynb @@ -45,8 +45,8 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains import GraphCypherQAChain\n", "from langchain_community.graphs.age_graph import AGEGraph\n", + "from langchain_neo4j import GraphCypherQAChain\n", "from langchain_openai import ChatOpenAI" ] }, @@ -169,7 +169,7 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True\n", + " ChatOpenAI(temperature=0), graph=graph, verbose=True, allow_dangerous_requests=True\n", ")" ] }, @@ -236,7 +236,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, top_k=2\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " top_k=2,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -295,7 +299,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, return_intermediate_steps=True\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " return_intermediate_steps=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -348,7 +356,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, return_direct=True\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " return_direct=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -435,6 +447,7 @@ " graph=graph,\n", " verbose=True,\n", " cypher_prompt=CYPHER_GENERATION_PROMPT,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -503,6 +516,7 @@ " cypher_llm=ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo\"),\n", " qa_llm=ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo-16k\"),\n", " verbose=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -574,6 +588,7 @@ " qa_llm=ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo-16k\"),\n", " verbose=True,\n", " exclude_types=[\"Movie\"],\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -622,6 +637,7 @@ " graph=graph,\n", " verbose=True,\n", " validate_cypher=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, diff --git a/docs/docs/integrations/graphs/diffbot.ipynb b/docs/docs/integrations/graphs/diffbot.ipynb index 06a8ed4e21ba2..9c4a5e866f497 100644 --- a/docs/docs/integrations/graphs/diffbot.ipynb +++ b/docs/docs/integrations/graphs/diffbot.ipynb @@ -45,7 +45,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install --upgrade --quiet langchain langchain-experimental langchain-openai neo4j wikipedia" + "%pip install --upgrade --quiet langchain langchain-experimental langchain-openai langchain-neo4j neo4j wikipedia" ] }, { @@ -124,7 +124,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain_community.graphs import Neo4jGraph\n", + "from langchain_neo4j import Neo4jGraph\n", "\n", "url = \"bolt://localhost:7687\"\n", "username = \"neo4j\"\n", @@ -186,7 +186,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains import GraphCypherQAChain\n", + "from langchain_neo4j import GraphCypherQAChain\n", "from langchain_openai import ChatOpenAI\n", "\n", "chain = GraphCypherQAChain.from_llm(\n", @@ -194,6 +194,7 @@ " qa_llm=ChatOpenAI(temperature=0, model_name=\"gpt-3.5-turbo\"),\n", " graph=graph,\n", " verbose=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, diff --git a/docs/docs/integrations/graphs/memgraph.ipynb b/docs/docs/integrations/graphs/memgraph.ipynb index 85eb7497dbf74..4dc8d33be4b86 100644 --- a/docs/docs/integrations/graphs/memgraph.ipynb +++ b/docs/docs/integrations/graphs/memgraph.ipynb @@ -53,7 +53,7 @@ "metadata": {}, "outputs": [], "source": [ - "pip install langchain langchain-openai neo4j gqlalchemy --user" + "pip install langchain langchain-neo4j langchain-openai neo4j gqlalchemy --user" ] }, { @@ -74,9 +74,9 @@ "import os\n", "\n", "from gqlalchemy import Memgraph\n", - "from langchain.chains import GraphCypherQAChain\n", "from langchain_community.graphs import MemgraphGraph\n", "from langchain_core.prompts import PromptTemplate\n", + "from langchain_neo4j import GraphCypherQAChain\n", "from langchain_openai import ChatOpenAI" ] }, @@ -259,7 +259,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, model_name=\"gpt-3.5-turbo\"\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " model_name=\"gpt-3.5-turbo\",\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -363,7 +367,11 @@ "source": [ "# Return the result of querying the graph directly\n", "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, return_direct=True\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " return_direct=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -412,7 +420,11 @@ "source": [ "# Return all the intermediate steps of query execution\n", "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, return_intermediate_steps=True\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " return_intermediate_steps=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -465,7 +477,11 @@ "source": [ "# Limit the maximum number of results returned by query\n", "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, top_k=2\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " top_k=2,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -530,7 +546,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, model_name=\"gpt-3.5-turbo\"\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " model_name=\"gpt-3.5-turbo\",\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -628,6 +648,7 @@ " graph=graph,\n", " verbose=True,\n", " model_name=\"gpt-3.5-turbo\",\n", + " allow_dangerous_requests=True,\n", ")" ] }, diff --git a/docs/docs/integrations/graphs/neo4j_cypher.ipynb b/docs/docs/integrations/graphs/neo4j_cypher.ipynb index 3348f0b8d26ba..8dd9824d67146 100644 --- a/docs/docs/integrations/graphs/neo4j_cypher.ipynb +++ b/docs/docs/integrations/graphs/neo4j_cypher.ipynb @@ -46,8 +46,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains import GraphCypherQAChain\n", - "from langchain_community.graphs import Neo4jGraph\n", + "from langchain_neo4j import GraphCypherQAChain, Neo4jGraph\n", "from langchain_openai import ChatOpenAI" ] }, @@ -61,6 +60,28 @@ "graph = Neo4jGraph(url=\"bolt://localhost:7687\", username=\"neo4j\", password=\"password\")" ] }, + { + "cell_type": "markdown", + "id": "8c663e91", + "metadata": {}, + "source": [ + "We default to OpenAI models in this guide." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "51c88001", + "metadata": {}, + "outputs": [], + "source": [ + "import getpass\n", + "import os\n", + "\n", + "if \"OPENAI_API_KEY\" not in os.environ:\n", + " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")" + ] + }, { "cell_type": "markdown", "id": "995ea9b9", @@ -203,7 +224,7 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True\n", + " ChatOpenAI(temperature=0), graph=graph, verbose=True, allow_dangerous_requests=True\n", ")" ] }, @@ -264,7 +285,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, top_k=2\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " top_k=2,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -324,7 +349,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, return_intermediate_steps=True\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " return_intermediate_steps=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -377,7 +406,11 @@ "outputs": [], "source": [ "chain = GraphCypherQAChain.from_llm(\n", - " ChatOpenAI(temperature=0), graph=graph, verbose=True, return_direct=True\n", + " ChatOpenAI(temperature=0),\n", + " graph=graph,\n", + " verbose=True,\n", + " return_direct=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -465,6 +498,7 @@ " graph=graph,\n", " verbose=True,\n", " cypher_prompt=CYPHER_GENERATION_PROMPT,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -527,6 +561,7 @@ " cypher_llm=ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo\"),\n", " qa_llm=ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo-16k\"),\n", " verbose=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -592,6 +627,7 @@ " qa_llm=ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo-16k\"),\n", " verbose=True,\n", " exclude_types=[\"Movie\"],\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -640,6 +676,7 @@ " graph=graph,\n", " verbose=True,\n", " validate_cypher=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -734,6 +771,7 @@ " graph=graph,\n", " verbose=True,\n", " use_function_response=True,\n", + " allow_dangerous_requests=True,\n", ")\n", "chain.invoke({\"query\": \"Who played in Top Gun?\"})" ] @@ -790,6 +828,7 @@ " verbose=True,\n", " use_function_response=True,\n", " function_response_system=\"Respond as a pirate!\",\n", + " allow_dangerous_requests=True,\n", ")\n", "chain.invoke({\"query\": \"Who played in Top Gun?\"})" ] diff --git a/docs/docs/integrations/llms/ai21.ipynb b/docs/docs/integrations/llms/ai21.ipynb index cf83e033e0dd5..628755f9e1c25 100644 --- a/docs/docs/integrations/llms/ai21.ipynb +++ b/docs/docs/integrations/llms/ai21.ipynb @@ -17,6 +17,9 @@ "source": [ "# AI21LLM\n", "\n", + ":::caution This service is deprecated.\n", + "See [this page](https://python.langchain.com/docs/integrations/chat/ai21/) for the updated ChatAI21 object. :::\n", + "\n", "This example goes over how to use LangChain to interact with `AI21` Jurassic models. To use the Jamba model, use the [ChatAI21 object](https://python.langchain.com/docs/integrations/chat/ai21/) instead.\n", "\n", "[See a full list of AI21 models and tools on LangChain.](https://pypi.org/project/langchain-ai21/)\n", diff --git a/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb b/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb index 0110a9d575646..1449e6789f28c 100644 --- a/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb +++ b/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb @@ -180,9 +180,9 @@ "\n", "For comprehensive details on all features and configurations, please refer to the API reference documentation for each class:\n", "\n", - "* [OCIModelDeploymentLLM](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentLLM.html)\n", - "* [OCIModelDeploymentVLLM](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentVLLM.html)\n", - "* [OCIModelDeploymentTGI](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI.html)" + "* [OCIModelDeploymentLLM](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentLLM.html)\n", + "* [OCIModelDeploymentVLLM](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentVLLM.html)\n", + "* [OCIModelDeploymentTGI](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI.html)" ] } ], diff --git a/docs/docs/integrations/llms/outlines.ipynb b/docs/docs/integrations/llms/outlines.ipynb index f9c434ef97475..0f29e87300a06 100644 --- a/docs/docs/integrations/llms/outlines.ipynb +++ b/docs/docs/integrations/llms/outlines.ipynb @@ -6,7 +6,7 @@ "source": [ "# Outlines\n", "\n", - "This will help you getting started with Outlines LLM. For detailed documentation of all Outlines features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/llms/outlines.llms.Outlines.html).\n", + "This will help you getting started with Outlines LLM. For detailed documentation of all Outlines features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.outlines.Outlines.html).\n", "\n", "[Outlines](https://github.com/outlines-dev/outlines) is a library for constrained language generation. It allows you to use large language models (LLMs) with various backends while applying constraints to the generated output.\n", "\n", @@ -236,7 +236,7 @@ "source": [ "## API reference\n", "\n", - "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html\n", + "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html\n", "\n", "## Outlines Documentation: \n", "\n", diff --git a/docs/docs/integrations/llms/writer.ipynb b/docs/docs/integrations/llms/writer.ipynb index 7488eff3efe16..bc17ba76582dd 100644 --- a/docs/docs/integrations/llms/writer.ipynb +++ b/docs/docs/integrations/llms/writer.ipynb @@ -4,120 +4,161 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Writer\n", + "# Writer LLM\n", "\n", "[Writer](https://writer.com/) is a platform to generate different language content.\n", "\n", "This example goes over how to use LangChain to interact with `Writer` [models](https://dev.writer.com/docs/models).\n", "\n", - "You have to get the WRITER_API_KEY [here](https://dev.writer.com/docs)." + "## Setup\n", + "\n", + "To access Writer models you'll need to create a Writer account, get an API key, and install the `writer-sdk` and `langchain-community` packages.\n", + "\n", + "### Credentials\n", + "\n", + "Head to [Writer AI Studio](https://app.writer.com/aistudio/signup?utm_campaign=devrel) to sign up to OpenAI and generate an API key. Once you've done this set the WRITER_API_KEY environment variable:" ] }, { + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T11:10:46.824961Z", + "start_time": "2024-11-14T11:10:44.864137Z" + } + }, "cell_type": "code", - "execution_count": 4, + "source": [ + "import getpass\n", + "import os\n", + "\n", + "if not os.environ.get(\"WRITER_API_KEY\"):\n", + " os.environ[\"WRITER_API_KEY\"] = getpass.getpass(\"Enter your Writer API key:\")" + ], + "outputs": [], + "execution_count": 1 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## Installation\n", + "\n", + "The LangChain Writer integration lives in the `langchain-community` package:" + ] + }, + { "metadata": { - "tags": [] + "ExecuteTime": { + "end_time": "2024-11-14T11:10:48.297429Z", + "start_time": "2024-11-14T11:10:46.843983Z" + } }, + "cell_type": "code", + "source": "%pip install -qU langchain-community writer-sdk", "outputs": [ { - "name": "stdin", + "name": "stdout", "output_type": "stream", "text": [ - " ········\n" + "\r\n", + "\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m A new release of pip is available: \u001B[0m\u001B[31;49m24.2\u001B[0m\u001B[39;49m -> \u001B[0m\u001B[32;49m24.3.1\u001B[0m\r\n", + "\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m To update, run: \u001B[0m\u001B[32;49mpip install --upgrade pip\u001B[0m\r\n", + "Note: you may need to restart the kernel to use updated packages.\n" ] } ], - "source": [ - "from getpass import getpass\n", - "\n", - "WRITER_API_KEY = getpass()" - ] + "execution_count": 2 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "Now we can initialize our model object to interact with writer LLMs" }, { - "cell_type": "code", - "execution_count": 5, "metadata": { - "tags": [] + "ExecuteTime": { + "end_time": "2024-11-14T11:10:49.818902Z", + "start_time": "2024-11-14T11:10:48.580516Z" + } }, - "outputs": [], + "cell_type": "code", "source": [ - "import os\n", + "from langchain_community.llms import Writer as WriterLLM\n", "\n", - "os.environ[\"WRITER_API_KEY\"] = WRITER_API_KEY" - ] + "llm = WriterLLM(\n", + " temperature=0.7,\n", + " max_tokens=1000,\n", + " # other params...\n", + ")" + ], + "outputs": [], + "execution_count": 3 }, { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "from langchain.chains import LLMChain\n", - "from langchain_community.llms import Writer\n", - "from langchain_core.prompts import PromptTemplate" - ] + "metadata": {}, + "cell_type": "markdown", + "source": "## Invocation" }, { - "cell_type": "code", - "execution_count": 7, "metadata": { - "tags": [] + "jupyter": { + "is_executing": true + }, + "ExecuteTime": { + "start_time": "2024-11-14T11:10:49.832822Z" + } }, + "cell_type": "code", + "source": "response_text = llm.invoke(input=\"Write a poem\")", "outputs": [], - "source": [ - "template = \"\"\"Question: {question}\n", - "\n", - "Answer: Let's think step by step.\"\"\"\n", - "\n", - "prompt = PromptTemplate.from_template(template)" - ] + "execution_count": null }, { + "metadata": {}, "cell_type": "code", - "execution_count": 14, - "metadata": { - "tags": [] - }, + "source": "print(response_text)", "outputs": [], - "source": [ - "# If you get an error, probably, you need to set up the \"base_url\" parameter that can be taken from the error log.\n", - "\n", - "llm = Writer()" - ] + "execution_count": null + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Streaming" }, { + "metadata": {}, "cell_type": "code", - "execution_count": 15, - "metadata": { - "tags": [] - }, + "source": "stream_response = llm.stream(input=\"Tell me a fairytale\")", "outputs": [], - "source": [ - "llm_chain = LLMChain(prompt=prompt, llm=llm)" - ] + "execution_count": null }, { + "metadata": {}, "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, + "source": [ + "for chunk in stream_response:\n", + " print(chunk, end=\"\")" + ], "outputs": [], + "execution_count": null + }, + { + "metadata": {}, + "cell_type": "markdown", "source": [ - "question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n", + "## Async\n", "\n", - "llm_chain.run(question)" + "Writer support asynchronous calls via **ainvoke()** and **astream()** methods" ] }, { - "cell_type": "code", - "execution_count": null, "metadata": {}, - "outputs": [], - "source": [] + "cell_type": "markdown", + "source": [ + "## API reference\n", + "\n", + "For detailed documentation of all Writer features, head to our [API reference](https://dev.writer.com/api-guides/api-reference/completion-api/text-generation#text-generation)." + ] } ], "metadata": { diff --git a/docs/docs/integrations/memory/neo4j_chat_message_history.ipynb b/docs/docs/integrations/memory/neo4j_chat_message_history.ipynb index d9dc80020c8ae..20cfd9ce68c10 100644 --- a/docs/docs/integrations/memory/neo4j_chat_message_history.ipynb +++ b/docs/docs/integrations/memory/neo4j_chat_message_history.ipynb @@ -19,7 +19,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain_community.chat_message_histories import Neo4jChatMessageHistory\n", + "from langchain_neo4j import Neo4jChatMessageHistory\n", "\n", "history = Neo4jChatMessageHistory(\n", " url=\"bolt://localhost:7687\",\n", diff --git a/docs/docs/integrations/providers/aerospike.mdx b/docs/docs/integrations/providers/aerospike.mdx new file mode 100644 index 0000000000000..9dfbaa68091de --- /dev/null +++ b/docs/docs/integrations/providers/aerospike.mdx @@ -0,0 +1,24 @@ +# Aerospike + +>[Aerospike](https://aerospike.com/docs/vector) is a high-performance, distributed database known for its speed and scalability, now with support for vector storage and search, enabling retrieval and search of embedding vectors for machine learning and AI applications. +> See the documentation for Aerospike Vector Search (AVS) [here](https://aerospike.com/docs/vector). + +## Installation and Setup + +Install the AVS Python SDK and AVS langchain vector store: + +```bash +pip install aerospike-vector-search langchain-community + +See the documentation for the Ptyhon SDK [here](https://aerospike-vector-search-python-client.readthedocs.io/en/latest/index.html). +The documentation for the AVS langchain vector store is [here](https://python.langchain.com/api_reference/community/vectorstores/langchain_community.vectorstores.aerospike.Aerospike.html). + +## Vector Store + +To import this vectorstore: + +```python +from langchain_community.vectorstores import Aerospike + +See a usage example [here](https://python.langchain.com/docs/integrations/vectorstores/aerospike/). + diff --git a/docs/docs/integrations/providers/ai21.mdx b/docs/docs/integrations/providers/ai21.mdx index 60a925363b1fa..140e755da8b83 100644 --- a/docs/docs/integrations/providers/ai21.mdx +++ b/docs/docs/integrations/providers/ai21.mdx @@ -15,53 +15,42 @@ This page covers how to use the `AI21` ecosystem within `LangChain`. pip install langchain-ai21 ``` -## LLMs +## Chat models -See a [usage example](/docs/integrations/llms/ai21). +### AI21 Chat -### AI21 LLM +See a [usage example](/docs/integrations/chat/ai21). ```python -from langchain_ai21 import AI21LLM +from langchain_ai21 import ChatAI21 ``` -### AI21 Contextual Answer +## Deprecated features -You can use AI21’s contextual answers model to receive text or document, -serving as a context, and a question and return an answer based entirely on this context. +:::caution The following features are deprecated. +::: + +### AI21 LLM ```python -from langchain_ai21 import AI21ContextualAnswers +from langchain_ai21 import AI21LLM ``` - -## Chat models - -### AI21 Chat - -See a [usage example](/docs/integrations/chat/ai21). +### AI21 Contextual Answer ```python -from langchain_ai21 import ChatAI21 +from langchain_ai21 import AI21ContextualAnswers ``` -## Embedding models - ### AI21 Embeddings -See a [usage example](/docs/integrations/text_embedding/ai21). - ```python from langchain_ai21 import AI21Embeddings ``` - ## Text splitters ### AI21 Semantic Text Splitter -See a [usage example](/docs/integrations/document_transformers/ai21_semantic_text_splitter). - ```python from langchain_ai21 import AI21SemanticTextSplitter -``` - +``` \ No newline at end of file diff --git a/docs/docs/integrations/providers/neo4j.mdx b/docs/docs/integrations/providers/neo4j.mdx index 929b622d612ee..2b8d8f683cc9f 100644 --- a/docs/docs/integrations/providers/neo4j.mdx +++ b/docs/docs/integrations/providers/neo4j.mdx @@ -11,7 +11,7 @@ ## Installation and Setup -- Install the Python SDK with `pip install neo4j` +- Install the Python SDK with `pip install neo4j langchain-neo4j` ## VectorStore @@ -20,7 +20,7 @@ The Neo4j vector index is used as a vectorstore, whether for semantic search or example selection. ```python -from langchain_community.vectorstores import Neo4jVector +from langchain_neo4j import Neo4jVector ``` See a [usage example](/docs/integrations/vectorstores/neo4jvector) @@ -31,8 +31,7 @@ There exists a wrapper around Neo4j graph database that allows you to generate C and use them to retrieve relevant information from the database. ```python -from langchain_community.graphs import Neo4jGraph -from langchain.chains import GraphCypherQAChain +from langchain_neo4j import GraphCypherQAChain, Neo4jGraph ``` See a [usage example](/docs/integrations/graphs/neo4j_cypher) @@ -45,7 +44,7 @@ By coupling Diffbot's NLP API with Neo4j, a graph database, you can create power These graph structures are fully queryable and can be integrated into various applications. ```python -from langchain_community.graphs import Neo4jGraph +from langchain_neo4j import Neo4jGraph from langchain_experimental.graph_transformers.diffbot import DiffbotGraphTransformer ``` @@ -56,5 +55,5 @@ See a [usage example](/docs/integrations/graphs/diffbot) See a [usage example](/docs/integrations/memory/neo4j_chat_message_history). ```python -from langchain.memory import Neo4jChatMessageHistory +from langchain_neo4j import Neo4jChatMessageHistory ``` diff --git a/docs/docs/integrations/providers/pinecone.mdx b/docs/docs/integrations/providers/pinecone.mdx index 6a56785d5b2b9..c9c8482203473 100644 --- a/docs/docs/integrations/providers/pinecone.mdx +++ b/docs/docs/integrations/providers/pinecone.mdx @@ -32,7 +32,7 @@ For a more detailed walkthrough of the Pinecone vectorstore, see [this notebook] ### Pinecone Hybrid Search ```bash -pip install pinecone-client pinecone-text +pip install pinecone pinecone-text ``` ```python diff --git a/docs/docs/integrations/providers/scrapegraph.mdx b/docs/docs/integrations/providers/scrapegraph.mdx new file mode 100644 index 0000000000000..93507ef3a88d8 --- /dev/null +++ b/docs/docs/integrations/providers/scrapegraph.mdx @@ -0,0 +1,41 @@ +# ScrapeGraph AI + +>[ScrapeGraph AI](https://scrapegraphai.com) is a service that provides AI-powered web scraping capabilities. +>It offers tools for extracting structured data, converting webpages to markdown, and processing local HTML content +>using natural language prompts. + +## Installation and Setup + +Install the required packages: + +```bash +pip install langchain-scrapegraph +``` + +Set up your API key: + +```bash +export SGAI_API_KEY="your-scrapegraph-api-key" +``` + +## Tools + +See a [usage example](/docs/integrations/tools/scrapegraph). + +There are four tools available: + +```python +from langchain_scrapegraph.tools import ( + SmartScraperTool, # Extract structured data from websites + MarkdownifyTool, # Convert webpages to markdown + LocalScraperTool, # Process local HTML content + GetCreditsTool, # Check remaining API credits +) +``` + +Each tool serves a specific purpose: + +- `SmartScraperTool`: Extract structured data from websites given a URL, prompt and optional output schema +- `MarkdownifyTool`: Convert any webpage to clean markdown format +- `LocalScraperTool`: Extract structured data from a local HTML file given a prompt and optional output schema +- `GetCreditsTool`: Check your remaining ScrapeGraph AI credits diff --git a/docs/docs/integrations/providers/unstructured.mdx b/docs/docs/integrations/providers/unstructured.mdx index 312a28d6f6815..8425ff1faa226 100644 --- a/docs/docs/integrations/providers/unstructured.mdx +++ b/docs/docs/integrations/providers/unstructured.mdx @@ -22,7 +22,7 @@ dependencies running. - To run everything locally, install the open-source python package with `pip install unstructured` along with `pip install langchain-community` and use the same `UnstructuredLoader` as mentioned above. - - You can install document specific dependencies with extras, e.g. `pip install "unstructured[docx]"`. + - You can install document specific dependencies with extras, e.g. `pip install "unstructured[docx]"`. Learn more about extras [here](https://docs.unstructured.io/open-source/installation/full-installation). - To install the dependencies for all document types, use `pip install "unstructured[all-docs]"`. - Install the following system dependencies if they are not already available on your system with e.g. `brew install` for Mac. Depending on what document types you're parsing, you may not need all of these. diff --git a/docs/docs/integrations/providers/upstage.ipynb b/docs/docs/integrations/providers/upstage.ipynb index 8e5cb60310931..6f33bd71af53b 100644 --- a/docs/docs/integrations/providers/upstage.ipynb +++ b/docs/docs/integrations/providers/upstage.ipynb @@ -8,7 +8,7 @@ "\n", ">[Upstage](https://upstage.ai) is a leading artificial intelligence (AI) company specializing in delivering above-human-grade performance LLM components.\n", ">\n", - ">**Solar Mini Chat** is a fast yet powerful advanced large language model focusing on English and Korean. It has been specifically fine-tuned for multi-turn chat purposes, showing enhanced performance across a wide range of natural language processing tasks, like multi-turn conversation or tasks that require an understanding of long contexts, such as RAG (Retrieval-Augmented Generation), compared to other models of a similar size. This fine-tuning equips it with the ability to handle longer conversations more effectively, making it particularly adept for interactive applications.\n", + ">**Solar Pro** is an enterprise-grade LLM optimized for single-GPU deployment, excelling in instruction-following and processing structured formats like HTML and Markdown. It supports English, Korean, and Japanese with top multilingual performance and offers domain expertise in finance, healthcare, and legal.\n", "\n", ">Other than Solar, Upstage also offers features for real-world RAG (retrieval-augmented generation), such as **Document Parse** and **Groundedness Check**. \n" ] @@ -21,12 +21,12 @@ "\n", "| API | Description | Import | Example usage |\n", "| --- | --- | --- | --- |\n", - "| Chat | Build assistants using Solar Mini Chat | `from langchain_upstage import ChatUpstage` | [Go](../../chat/upstage) |\n", + "| Chat | Build assistants using Solar Chat | `from langchain_upstage import ChatUpstage` | [Go](../../chat/upstage) |\n", "| Text Embedding | Embed strings to vectors | `from langchain_upstage import UpstageEmbeddings` | [Go](../../text_embedding/upstage) |\n", "| Groundedness Check | Verify groundedness of assistant's response | `from langchain_upstage import UpstageGroundednessCheck` | [Go](../../tools/upstage_groundedness_check) |\n", "| Document Parse | Serialize documents with tables and figures | `from langchain_upstage import UpstageDocumentParseLoader` | [Go](../../document_loaders/upstage) |\n", "\n", - "See [documentations](https://developers.upstage.ai/) for more details about the features." + "See [documentations](https://console.upstage.ai/docs/getting-started/overview) for more details about the models and features." ] }, { diff --git a/docs/docs/integrations/retrievers/bm25.ipynb b/docs/docs/integrations/retrievers/bm25.ipynb index 5e0b3fa1984f9..401031db5fbe1 100644 --- a/docs/docs/integrations/retrievers/bm25.ipynb +++ b/docs/docs/integrations/retrievers/bm25.ipynb @@ -15,7 +15,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a801b57c", + "id": "eccbbc4a", "metadata": {}, "outputs": [], "source": [ @@ -24,9 +24,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "393ac030", "metadata": { + "ExecuteTime": { + "end_time": "2024-11-13T23:35:51.348359Z", + "start_time": "2024-11-13T23:35:49.409254Z" + }, "tags": [] }, "outputs": [], @@ -44,9 +48,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "id": "98b1c017", "metadata": { + "ExecuteTime": { + "end_time": "2024-11-13T23:35:53.096938Z", + "start_time": "2024-11-13T23:35:52.493243Z" + }, "tags": [] }, "outputs": [], @@ -66,9 +74,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "53af4f00", - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-13T23:35:54.202737Z", + "start_time": "2024-11-13T23:35:54.198431Z" + } + }, "outputs": [], "source": [ "from langchain_core.documents import Document\n", @@ -96,9 +109,13 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "c0455218", "metadata": { + "ExecuteTime": { + "end_time": "2024-11-13T23:35:55.643026Z", + "start_time": "2024-11-13T23:35:55.595272Z" + }, "tags": [] }, "outputs": [], @@ -108,22 +125,26 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "7dfa5c29", "metadata": { + "ExecuteTime": { + "end_time": "2024-11-13T23:35:56.122327Z", + "start_time": "2024-11-13T23:35:56.112647Z" + }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ - "[Document(page_content='foo', metadata={}),\n", - " Document(page_content='foo bar', metadata={}),\n", - " Document(page_content='hello', metadata={}),\n", - " Document(page_content='world', metadata={})]" + "[Document(metadata={}, page_content='foo'),\n", + " Document(metadata={}, page_content='foo bar'),\n", + " Document(metadata={}, page_content='hello'),\n", + " Document(metadata={}, page_content='world')]" ] }, - "execution_count": 5, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -132,13 +153,68 @@ "result" ] }, + { + "cell_type": "markdown", + "id": "51043723814c0d68", + "metadata": {}, + "source": [ + "## Preprocessing Function\n", + "Pass a custom preprocessing function to the retriever to improve search results. Tokenizing text at the word level can enhance retrieval, especially when using vector stores like Chroma, Pinecone, or Faiss for chunked documents." + ] + }, { "cell_type": "code", "execution_count": null, - "id": "997aaa8d", + "id": "f5fea58b", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "import nltk\n", + "\n", + "nltk.download(\"punkt_tab\")" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "566fcc801cda5da4", + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-14T00:40:58.728953Z", + "start_time": "2024-11-14T00:40:58.722140Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Document(metadata={}, page_content='bar'),\n", + " Document(metadata={}, page_content='foo bar')]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from nltk.tokenize import word_tokenize\n", + "\n", + "retriever = BM25Retriever.from_documents(\n", + " [\n", + " Document(page_content=\"foo\"),\n", + " Document(page_content=\"bar\"),\n", + " Document(page_content=\"world\"),\n", + " Document(page_content=\"hello\"),\n", + " Document(page_content=\"foo bar\"),\n", + " ],\n", + " k=2,\n", + " preprocess_func=word_tokenize,\n", + ")\n", + "\n", + "result = retriever.invoke(\"bar\")\n", + "result" + ] } ], "metadata": { diff --git a/docs/docs/integrations/retrievers/fleet_context.ipynb b/docs/docs/integrations/retrievers/fleet_context.ipynb index db3e6e79cbab6..2c2d7e6083c3d 100644 --- a/docs/docs/integrations/retrievers/fleet_context.ipynb +++ b/docs/docs/integrations/retrievers/fleet_context.ipynb @@ -9,7 +9,7 @@ "\n", ">[Fleet AI Context](https://www.fleet.so/context) is a dataset of high-quality embeddings of the top 1200 most popular & permissive Python Libraries & their documentation.\n", ">\n", - ">The `Fleet AI` team is on a mission to embed the world's most important data. They've started by embedding the top 1200 Python libraries to enable code generation with up-to-date knowledge. They've been kind enough to share their embeddings of the [LangChain docs](/docs/introduction) and [API reference](https://api.python.langchain.com/en/latest/api_reference.html).\n", + ">The `Fleet AI` team is on a mission to embed the world's most important data. They've started by embedding the top 1200 Python libraries to enable code generation with up-to-date knowledge. They've been kind enough to share their embeddings of the [LangChain docs](/docs/introduction) and [API reference](https://python.langchain.com/api_reference/).\n", "\n", "Let's take a look at how we can use these embeddings to power a docs retrieval system and ultimately a simple code-generating chain!" ] diff --git a/docs/docs/integrations/retrievers/ibm_watsonx_ranker.ipynb b/docs/docs/integrations/retrievers/ibm_watsonx_ranker.ipynb index 66b804e2dcd4d..d58cb2e4d9a55 100644 --- a/docs/docs/integrations/retrievers/ibm_watsonx_ranker.ipynb +++ b/docs/docs/integrations/retrievers/ibm_watsonx_ranker.ipynb @@ -35,9 +35,9 @@ "\n", "### Integration details\n", "\n", - "| Class | Package | JS support | Package downloads | Package latest |\n", + "| Class | Package | [JS support](https://js.langchain.com/docs/integrations/document_compressors/ibm/) | Package downloads | Package latest |\n", "| :--- | :--- | :---: | :---: | :---: |\n", - "| [WatsonxRerank](https://python.langchain.com/api_reference/ibm/chat_models/langchain_ibm.rerank.WatsonxRerank.html) | [langchain-ibm](https://python.langchain.com/api_reference/ibm/index.html) | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-ibm?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-ibm?style=flat-square&label=%20) |" + "| [WatsonxRerank](https://python.langchain.com/api_reference/ibm/rerank/langchain_ibm.rerank.WatsonxRerank.html) | [langchain-ibm](https://python.langchain.com/api_reference/ibm/index.html) | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-ibm?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-ibm?style=flat-square&label=%20) |" ] }, { @@ -445,7 +445,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "langchain_ibm", "language": "python", "name": "python3" }, diff --git a/docs/docs/integrations/retrievers/needle.ipynb b/docs/docs/integrations/retrievers/needle.ipynb new file mode 100644 index 0000000000000..616b6c0a896af --- /dev/null +++ b/docs/docs/integrations/retrievers/needle.ipynb @@ -0,0 +1,235 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Needle Retriever\n", + "[Needle](https://needle-ai.com) makes it easy to create your RAG pipelines with minimal effort. \n", + "\n", + "For more details, refer to our [API documentation](https://docs.needle-ai.com/docs/api-reference/needle-api)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Overview\n", + "The Needle Document Loader is a utility for integrating Needle collections with LangChain. It enables seamless storage, retrieval, and utilization of documents for Retrieval-Augmented Generation (RAG) workflows.\n", + "\n", + "This example demonstrates:\n", + "\n", + "* Storing documents into a Needle collection.\n", + "* Setting up a retriever to fetch documents.\n", + "* Building a Retrieval-Augmented Generation (RAG) pipeline." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Setup\n", + "Before starting, ensure you have the following environment variables set:\n", + "\n", + "* NEEDLE_API_KEY: Your API key for authenticating with Needle.\n", + "* OPENAI_API_KEY: Your OpenAI API key for language model operations." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Initialization\n", + "To initialize the NeedleLoader, you need the following parameters:\n", + "\n", + "* needle_api_key: Your Needle API key (or set it as an environment variable).\n", + "* collection_id: The ID of the Needle collection to work with." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "os.environ[\"NEEDLE_API_KEY\"] = \"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "os.environ[\"OPENAI_API_KEY\"] = \"\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Instantiation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_community.document_loaders.needle import NeedleLoader\n", + "\n", + "collection_id = \"clt_01J87M9T6B71DHZTHNXYZQRG5H\"\n", + "\n", + "# Initialize NeedleLoader to store documents to the collection\n", + "document_loader = NeedleLoader(\n", + " needle_api_key=os.getenv(\"NEEDLE_API_KEY\"),\n", + " collection_id=collection_id,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load\n", + "To add files to the Needle collection:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "files = {\n", + " \"tech-radar-30.pdf\": \"https://www.thoughtworks.com/content/dam/thoughtworks/documents/radar/2024/04/tr_technology_radar_vol_30_en.pdf\"\n", + "}\n", + "\n", + "document_loader.add_files(files=files)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Show the documents in the collection\n", + "# collections_documents = document_loader.load()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Usage\n", + "### Use within a chain\n", + "Below is a complete example of setting up a RAG pipeline with Needle within a chain:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'input': 'Did RAG move to accepted?',\n", + " 'context': [Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='New Moved in/out No change\\n\\n© Thoughtworks, Inc. All Rights Reserved. 12\\n\\nTechniques\\n\\n1. Retrieval-augmented generation (RAG)\\nAdopt\\n\\nRetrieval-augmented generation (RAG) is the preferred pattern for our teams to improve the quality of \\nresponses generated by a large language model (LLM). We’ve successfully used it in several projects, \\nincluding the popular Jugalbandi AI Platform. With RAG, information about relevant and trustworthy \\ndocuments — in formats like HTML and PDF — are stored in databases that supports a vector data \\ntype or efficient document search, such as pgvector, Qdrant or Elasticsearch Relevance Engine. For \\na given prompt, the database is queried to retrieve relevant documents, which are then combined \\nwith the prompt to provide richer context to the LLM. This results in higher quality output and greatly \\nreduced hallucinations. The context window — which determines the maximum size of the LLM input \\n— is limited, which means that selecting the most relevant documents is crucial. We improve the \\nrelevancy of the content that is added to the prompt by reranking. Similarly, the documents are usually \\ntoo large to calculate an embedding, which means they must be split into smaller chunks. This is often \\na difficult problem, and one approach is to have the chunks overlap to a certain extent.'),\n", + " Document(metadata={}, page_content='https://www.thoughtworks.com/radar/tools/nemo-guardrails\\nhttps://www.thoughtworks.com/radar/platforms/langfuse\\nhttps://www.thoughtworks.com/radar/techniques/retrieval-augmented-generation-rag\\nhttps://cruisecontrol.sourceforge.net/\\nhttps://martinfowler.com/articles/continuousIntegration.html\\nhttps://www.thoughtworks.com/radar/techniques/peer-review-equals-pull-request\\nhttps://martinfowler.com/bliki/ContinuousIntegrationCertification.html\\nhttps://linearb.io/platform/gitstream\\nhttps://www.thoughtworks.com/radar/tools/github-merge-queue\\nhttps://stacking.dev/\\n\\n© Thoughtworks, Inc. All Rights Reserved. 8\\n\\nHold HoldAssess AssessTrial TrialAdopt Adopt\\n\\n18\\n\\n8\\n\\n24\\n\\n29\\n\\n30\\n31\\n\\n32\\n33\\n\\n34 35\\n\\n36\\n37\\n\\n38 39\\n\\n40\\n41\\n\\n42\\n43\\n\\n26\\n\\n2\\n\\n3\\n\\n4\\n\\n5\\n\\n6 7\\n\\n9\\n\\n15\\n\\n16\\n\\n17\\n\\n10\\n\\n11\\n\\n12\\n\\n13 14\\n\\n44\\n\\n47\\n49\\n\\n50\\n\\n65\\n66\\n\\n67 68\\n69\\n\\n70\\n71\\n\\n72\\n\\n73 74\\n\\n75\\n\\n76 77\\n\\n78\\n79\\n\\n80\\n81\\n\\n82\\n\\n83\\n\\n51\\n\\n52 54\\n\\n59\\n\\n53\\n56\\n\\n58\\n\\n61\\n\\n62\\n63\\n\\n64\\n\\n85\\n\\n88 89\\n\\n90 91\\n\\n92\\n93\\n\\n94\\n95 96\\n\\n97\\n\\n98 99\\n\\n100\\n\\n101\\n102\\n\\n103\\n\\n104\\n\\n86\\n\\n87\\n1921\\n\\n22\\n\\n20\\n28\\n\\n25\\n\\n27\\n\\n23\\n\\n84\\n\\n105\\n\\n1\\n45\\n\\n46\\n\\n48\\n\\n55\\n57')],\n", + " 'answer': 'Yes, RAG has moved to the \"Adopt\" status.'}" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "\n", + "from langchain.chains import create_retrieval_chain\n", + "from langchain.chains.combine_documents import create_stuff_documents_chain\n", + "from langchain_community.retrievers.needle import NeedleRetriever\n", + "from langchain_core.prompts import ChatPromptTemplate\n", + "from langchain_openai import ChatOpenAI\n", + "\n", + "llm = ChatOpenAI(temperature=0)\n", + "\n", + "# Initialize the Needle retriever (make sure your Needle API key is set as an environment variable)\n", + "retriever = NeedleRetriever(\n", + " needle_api_key=os.getenv(\"NEEDLE_API_KEY\"),\n", + " collection_id=\"clt_01J87M9T6B71DHZTHNXYZQRG5H\",\n", + ")\n", + "\n", + "# Define system prompt for the assistant\n", + "system_prompt = \"\"\"\n", + " You are an assistant for question-answering tasks. \n", + " Use the following pieces of retrieved context to answer the question.\n", + " If you don't know, say so concisely.\\n\\n{context}\n", + " \"\"\"\n", + "\n", + "prompt = ChatPromptTemplate.from_messages(\n", + " [(\"system\", system_prompt), (\"human\", \"{input}\")]\n", + ")\n", + "\n", + "# Define the question-answering chain using a document chain (stuff chain) and the retriever\n", + "question_answer_chain = create_stuff_documents_chain(llm, prompt)\n", + "\n", + "# Create the RAG (Retrieval-Augmented Generation) chain by combining the retriever and the question-answering chain\n", + "rag_chain = create_retrieval_chain(retriever, question_answer_chain)\n", + "\n", + "# Define the input query\n", + "query = {\"input\": \"Did RAG move to accepted?\"}\n", + "\n", + "response = rag_chain.invoke(query)\n", + "\n", + "response" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## API reference\n", + "\n", + "For detailed documentation of all `Needle` features and configurations head to the API reference: https://docs.needle-ai.com" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb b/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb index 72cb5dde4f33e..9722afe59482a 100644 --- a/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb +++ b/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb @@ -24,7 +24,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install --upgrade --quiet pinecone-client pinecone-text pinecone-notebooks" + "%pip install --upgrade --quiet pinecone pinecone-text pinecone-notebooks" ] }, { diff --git a/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb index d5584362a89ae..3ddb37100092f 100644 --- a/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb @@ -194,7 +194,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/astradb.ipynb b/docs/docs/integrations/retrievers/self_query/astradb.ipynb index a170a306f1b6a..a69b22006a367 100644 --- a/docs/docs/integrations/retrievers/self_query/astradb.ipynb +++ b/docs/docs/integrations/retrievers/self_query/astradb.ipynb @@ -146,7 +146,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb index f9f5725afbe2c..c12336bb78275 100644 --- a/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb @@ -164,7 +164,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/dashvector.ipynb b/docs/docs/integrations/retrievers/self_query/dashvector.ipynb index a5c856d9555f7..3e7bcda942754 100644 --- a/docs/docs/integrations/retrievers/self_query/dashvector.ipynb +++ b/docs/docs/integrations/retrievers/self_query/dashvector.ipynb @@ -185,7 +185,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_community.llms import Tongyi\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb b/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb index 1f88a518785e7..d969db98281bc 100644 --- a/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb +++ b/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb @@ -282,7 +282,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/dingo.ipynb b/docs/docs/integrations/retrievers/self_query/dingo.ipynb index 95bda4d1513e9..12f675823b2dc 100644 --- a/docs/docs/integrations/retrievers/self_query/dingo.ipynb +++ b/docs/docs/integrations/retrievers/self_query/dingo.ipynb @@ -196,7 +196,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/hanavector_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/hanavector_self_query.ipynb index 0bdef3836c8a0..e2a0d8a28f25d 100644 --- a/docs/docs/integrations/retrievers/self_query/hanavector_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/hanavector_self_query.ipynb @@ -125,7 +125,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_community.query_constructors.hanavector import HanaTranslator\n", "from langchain_openai import ChatOpenAI\n", diff --git a/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb index c43ab4cf2c4e6..21414461733de 100644 --- a/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb @@ -119,7 +119,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb b/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb index 045a224acdf0c..c7471e29effbc 100644 --- a/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb +++ b/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb @@ -160,7 +160,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb index a29517693669b..c4c90888d3781 100644 --- a/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb @@ -165,7 +165,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import ChatOpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/neo4j_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/neo4j_self_query.ipynb index 6bc4f718dfc84..1730222283f0b 100644 --- a/docs/docs/integrations/retrievers/self_query/neo4j_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/neo4j_self_query.ipynb @@ -99,8 +99,8 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain_community.vectorstores import Neo4jVector\n", "from langchain_core.documents import Document\n", + "from langchain_neo4j import Neo4jVector\n", "from langchain_openai import OpenAIEmbeddings\n", "\n", "embeddings = OpenAIEmbeddings()" @@ -168,7 +168,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb index 8795bbd1d1a38..dfc68614eadab 100644 --- a/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb @@ -135,7 +135,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb index 8d27022fe2582..d05734063fcdc 100644 --- a/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb @@ -141,7 +141,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/pinecone.ipynb b/docs/docs/integrations/retrievers/self_query/pinecone.ipynb index 670c7db91f0f3..8c8bc331d7d9e 100644 --- a/docs/docs/integrations/retrievers/self_query/pinecone.ipynb +++ b/docs/docs/integrations/retrievers/self_query/pinecone.ipynb @@ -190,7 +190,7 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb index 50b162b6928cd..a012caa99d3c1 100644 --- a/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb @@ -144,7 +144,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb index 55e4f6fa350e4..5f72e7738b5cb 100644 --- a/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb @@ -194,7 +194,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb index 8884216448788..8468979c4e81a 100644 --- a/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb @@ -308,7 +308,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb b/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb index a59546e1308fd..4d6362085ec28 100644 --- a/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb +++ b/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb @@ -218,7 +218,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import ChatOpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb index f78a2f107cd6b..4e495264d7260 100644 --- a/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb @@ -249,7 +249,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb index fe98c8f12a624..ab3dbe4f301a6 100644 --- a/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb @@ -91,7 +91,7 @@ "os.environ[\"VECTARA_CORPUS_ID\"] = \"\"\n", "os.environ[\"VECTARA_CUSTOMER_ID\"] = \"\"\n", "\n", - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_community.vectorstores import Vectara\n", "from langchain_openai.chat_models import ChatOpenAI" diff --git a/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb index df5fd9d03e080..b3729e193ea12 100644 --- a/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb @@ -115,7 +115,7 @@ }, "outputs": [], "source": [ - "from langchain.chains.query_constructor.base import AttributeInfo\n", + "from langchain.chains.query_constructor.schema import AttributeInfo\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain_openai import OpenAI\n", "\n", diff --git a/docs/docs/integrations/text_embedding/ai21.ipynb b/docs/docs/integrations/text_embedding/ai21.ipynb index c48d3e24a62b8..d77ba9bbf6e6c 100644 --- a/docs/docs/integrations/text_embedding/ai21.ipynb +++ b/docs/docs/integrations/text_embedding/ai21.ipynb @@ -17,6 +17,8 @@ "source": [ "# AI21Embeddings\n", "\n", + ":::caution This service is deprecated. :::\n", + "\n", "This will help you get started with AI21 embedding models using LangChain. For detailed documentation on `AI21Embeddings` features and configuration options, please refer to the [API reference](https://python.langchain.com/api_reference/ai21/embeddings/langchain_ai21.embeddings.AI21Embeddings.html).\n", "\n", "## Overview\n", @@ -123,7 +125,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/azureopenai.ipynb b/docs/docs/integrations/text_embedding/azureopenai.ipynb index 916132c6f3e43..a7a52227be056 100644 --- a/docs/docs/integrations/text_embedding/azureopenai.ipynb +++ b/docs/docs/integrations/text_embedding/azureopenai.ipynb @@ -133,7 +133,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/cohere.ipynb b/docs/docs/integrations/text_embedding/cohere.ipynb index 073aa6183b024..f231b67b63352 100644 --- a/docs/docs/integrations/text_embedding/cohere.ipynb +++ b/docs/docs/integrations/text_embedding/cohere.ipynb @@ -120,7 +120,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/databricks.ipynb b/docs/docs/integrations/text_embedding/databricks.ipynb index eab60db2aa390..31505992ca7ed 100644 --- a/docs/docs/integrations/text_embedding/databricks.ipynb +++ b/docs/docs/integrations/text_embedding/databricks.ipynb @@ -28,7 +28,7 @@ "\n", "| Class | Package |\n", "| :--- | :--- |\n", - "| [DatabricksEmbeddings](https://api.python.langchain.com/en/latest/embeddings/langchain_databricks.embeddings.DatabricksEmbeddings.html) | [databricks-langchain](https://python.langchain.com/docs/integrations/providers/databricks/) |\n", + "| [DatabricksEmbeddings](https://python.langchain.com/api_reference/community/embeddings/langchain_community.embeddings.databricks.DatabricksEmbeddings.html) | [databricks-langchain](https://python.langchain.com/docs/integrations/providers/databricks/) |\n", "\n", "### Supported Methods\n", "\n", @@ -125,7 +125,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/fireworks.ipynb b/docs/docs/integrations/text_embedding/fireworks.ipynb index 32fe0134b88d5..cbdf48e5e9ec6 100644 --- a/docs/docs/integrations/text_embedding/fireworks.ipynb +++ b/docs/docs/integrations/text_embedding/fireworks.ipynb @@ -120,7 +120,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb b/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb index 384fcaa894a20..e29f5b42e3196 100644 --- a/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb +++ b/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb @@ -169,7 +169,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/ibm_watsonx.ipynb b/docs/docs/integrations/text_embedding/ibm_watsonx.ipynb index 5767a60cb5155..a5720b91144f8 100644 --- a/docs/docs/integrations/text_embedding/ibm_watsonx.ipynb +++ b/docs/docs/integrations/text_embedding/ibm_watsonx.ipynb @@ -203,7 +203,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] @@ -327,7 +327,7 @@ ], "metadata": { "kernelspec": { - "display_name": "langchain", + "display_name": "langchain_ibm", "language": "python", "name": "python3" }, diff --git a/docs/docs/integrations/text_embedding/mistralai.ipynb b/docs/docs/integrations/text_embedding/mistralai.ipynb index 70ce6f1049659..b9e8d0bda9a81 100644 --- a/docs/docs/integrations/text_embedding/mistralai.ipynb +++ b/docs/docs/integrations/text_embedding/mistralai.ipynb @@ -119,7 +119,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/model2vec.ipynb b/docs/docs/integrations/text_embedding/model2vec.ipynb new file mode 100644 index 0000000000000..d8ef5d357050a --- /dev/null +++ b/docs/docs/integrations/text_embedding/model2vec.ipynb @@ -0,0 +1,201 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e8712110", + "metadata": {}, + "source": [ + "## Overview\n", + "\n", + "Model2Vec is a technique to turn any sentence transformer into a really small static model\n", + "[model2vec](https://github.com/MinishLab/model2vec) can be used to generate embeddings." + ] + }, + { + "cell_type": "markdown", + "id": "266dd424", + "metadata": {}, + "source": [ + "## Setup\n", + "\n", + "```bash\n", + "pip install -U langchain-community\n", + "```\n" + ] + }, + { + "cell_type": "markdown", + "id": "78ab91a6", + "metadata": {}, + "source": [ + "## Instantiation" + ] + }, + { + "cell_type": "markdown", + "id": "d06e7719", + "metadata": {}, + "source": [ + "Ensure that `model2vec` is installed\n", + "\n", + "```bash\n", + "pip install -U model2vec\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "f8ea1ed5", + "metadata": {}, + "source": [ + "## Indexing and Retrieval" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d25dc22d-b656-46c6-a42d-eace958590cd", + "metadata": { + "ExecuteTime": { + "end_time": "2023-05-24T15:13:17.176956Z", + "start_time": "2023-05-24T15:13:15.399076Z" + }, + "execution": { + "iopub.execute_input": "2024-03-29T15:39:19.252281Z", + "iopub.status.busy": "2024-03-29T15:39:19.252101Z", + "iopub.status.idle": "2024-03-29T15:39:19.339106Z", + "shell.execute_reply": "2024-03-29T15:39:19.338614Z", + "shell.execute_reply.started": "2024-03-29T15:39:19.252260Z" + } + }, + "outputs": [], + "source": [ + "from langchain_community.embeddings import Model2vecEmbeddings" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "8397b91f-a1f9-4be6-a699-fedaada7c37a", + "metadata": { + "ExecuteTime": { + "end_time": "2023-05-24T15:13:17.193751Z", + "start_time": "2023-05-24T15:13:17.182053Z" + }, + "execution": { + "iopub.execute_input": "2024-03-29T15:39:19.901573Z", + "iopub.status.busy": "2024-03-29T15:39:19.900935Z", + "iopub.status.idle": "2024-03-29T15:39:19.906540Z", + "shell.execute_reply": "2024-03-29T15:39:19.905345Z", + "shell.execute_reply.started": "2024-03-29T15:39:19.901529Z" + } + }, + "outputs": [], + "source": [ + "embeddings = Model2vecEmbeddings(\"minishlab/potion-base-8M\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "abcf98b7-424c-4691-a1cd-862c3d53be11", + "metadata": { + "ExecuteTime": { + "end_time": "2023-05-24T15:13:17.844903Z", + "start_time": "2023-05-24T15:13:17.198751Z" + }, + "execution": { + "iopub.execute_input": "2024-03-29T15:39:20.434581Z", + "iopub.status.busy": "2024-03-29T15:39:20.433117Z", + "iopub.status.idle": "2024-03-29T15:39:22.178650Z", + "shell.execute_reply": "2024-03-29T15:39:22.176058Z", + "shell.execute_reply.started": "2024-03-29T15:39:20.434501Z" + }, + "scrolled": true + }, + "outputs": [], + "source": [ + "query_text = \"This is a test query.\"\n", + "query_result = embeddings.embed_query(query_text)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "98897454-b280-4ee1-bbb9-2c6c15342f87", + "metadata": { + "ExecuteTime": { + "end_time": "2023-05-24T15:13:18.605339Z", + "start_time": "2023-05-24T15:13:17.845906Z" + }, + "execution": { + "iopub.execute_input": "2024-03-29T15:39:28.164009Z", + "iopub.status.busy": "2024-03-29T15:39:28.161759Z", + "iopub.status.idle": "2024-03-29T15:39:30.217232Z", + "shell.execute_reply": "2024-03-29T15:39:30.215348Z", + "shell.execute_reply.started": "2024-03-29T15:39:28.163876Z" + }, + "scrolled": true + }, + "outputs": [], + "source": [ + "document_text = \"This is a test document.\"\n", + "document_result = embeddings.embed_documents([document_text])" + ] + }, + { + "cell_type": "markdown", + "id": "11bac134", + "metadata": {}, + "source": [ + "## Direct Usage\n", + "\n", + "Here's how you would directly make use of `model2vec`\n", + "\n", + "```python\n", + "from model2vec import StaticModel\n", + "\n", + "# Load a model from the HuggingFace hub (in this case the potion-base-8M model)\n", + "model = StaticModel.from_pretrained(\"minishlab/potion-base-8M\")\n", + "\n", + "# Make embeddings\n", + "embeddings = model.encode([\"It's dangerous to go alone!\", \"It's a secret to everybody.\"])\n", + "\n", + "# Make sequences of token embeddings\n", + "token_embeddings = model.encode_as_sequence([\"It's dangerous to go alone!\", \"It's a secret to everybody.\"])\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "d81e21aa", + "metadata": {}, + "source": [ + "## API Reference\n", + "\n", + "For more information check out the model2vec github [repo](https://github.com/MinishLab/model2vec)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/docs/integrations/text_embedding/naver.ipynb b/docs/docs/integrations/text_embedding/naver.ipynb index 53be1d79b574a..5fa9765ebc11a 100644 --- a/docs/docs/integrations/text_embedding/naver.ipynb +++ b/docs/docs/integrations/text_embedding/naver.ipynb @@ -130,7 +130,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/nomic.ipynb b/docs/docs/integrations/text_embedding/nomic.ipynb index 51c8773b2dbf8..820e3c2a32610 100644 --- a/docs/docs/integrations/text_embedding/nomic.ipynb +++ b/docs/docs/integrations/text_embedding/nomic.ipynb @@ -140,7 +140,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/ollama.ipynb b/docs/docs/integrations/text_embedding/ollama.ipynb index 0cc76641485a7..b95d82d226dce 100644 --- a/docs/docs/integrations/text_embedding/ollama.ipynb +++ b/docs/docs/integrations/text_embedding/ollama.ipynb @@ -129,7 +129,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/openai.ipynb b/docs/docs/integrations/text_embedding/openai.ipynb index cea8618fea339..83eeab2293e63 100644 --- a/docs/docs/integrations/text_embedding/openai.ipynb +++ b/docs/docs/integrations/text_embedding/openai.ipynb @@ -125,7 +125,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/together.ipynb b/docs/docs/integrations/text_embedding/together.ipynb index b64159879f939..26721fb183f33 100644 --- a/docs/docs/integrations/text_embedding/together.ipynb +++ b/docs/docs/integrations/text_embedding/together.ipynb @@ -130,7 +130,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/docs/docs/integrations/text_embedding/zhipuai.ipynb b/docs/docs/integrations/text_embedding/zhipuai.ipynb index de33980c5641b..d33ac41c93e9b 100644 --- a/docs/docs/integrations/text_embedding/zhipuai.ipynb +++ b/docs/docs/integrations/text_embedding/zhipuai.ipynb @@ -132,7 +132,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] @@ -251,7 +251,7 @@ "source": [ "## API Reference\n", "\n", - "For detailed documentation on `ZhipuAIEmbeddings` features and configuration options, please refer to the [API reference](https://api.python.langchain.com/en/latest/embeddings/langchain_community.embeddings.zhipuai.ZhipuAIEmbeddings.html).\n" + "For detailed documentation on `ZhipuAIEmbeddings` features and configuration options, please refer to the [API reference](https://python.langchain.com/api_reference/community/embeddings/langchain_community.embeddings.zhipuai.ZhipuAIEmbeddings.html).\n" ] } ], diff --git a/docs/docs/integrations/tools/scrapegraph.ipynb b/docs/docs/integrations/tools/scrapegraph.ipynb new file mode 100644 index 0000000000000..ed9b37d97bd34 --- /dev/null +++ b/docs/docs/integrations/tools/scrapegraph.ipynb @@ -0,0 +1,380 @@ +{ + "cells": [ + { + "cell_type": "raw", + "id": "10238e62-3465-4973-9279-606cbb7ccf16", + "metadata": {}, + "source": [ + "---\n", + "sidebar_label: ScrapeGraph\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "a6f91f20", + "metadata": {}, + "source": [ + "# ScrapeGraph\n", + "\n", + "This notebook provides a quick overview for getting started with ScrapeGraph [tools](/docs/integrations/tools/). For detailed documentation of all ScrapeGraph features and configurations head to the [API reference](https://python.langchain.com/docs/integrations/tools/scrapegraph).\n", + "\n", + "For more information about ScrapeGraph AI:\n", + "- [ScrapeGraph AI Website](https://scrapegraphai.com)\n", + "- [Open Source Project](https://github.com/ScrapeGraphAI/Scrapegraph-ai)\n", + "\n", + "## Overview\n", + "\n", + "### Integration details\n", + "\n", + "| Class | Package | Serializable | JS support | Package latest |\n", + "| :--- | :--- | :---: | :---: | :---: |\n", + "| [SmartScraperTool](https://python.langchain.com/docs/integrations/tools/scrapegraph) | langchain-scrapegraph | ✅ | ❌ | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-scrapegraph?style=flat-square&label=%20) |\n", + "| [MarkdownifyTool](https://python.langchain.com/docs/integrations/tools/scrapegraph) | langchain-scrapegraph | ✅ | ❌ | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-scrapegraph?style=flat-square&label=%20) |\n", + "| [LocalScraperTool](https://python.langchain.com/docs/integrations/tools/scrapegraph) | langchain-scrapegraph | ✅ | ❌ | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-scrapegraph?style=flat-square&label=%20) |\n", + "| [GetCreditsTool](https://python.langchain.com/docs/integrations/tools/scrapegraph) | langchain-scrapegraph | ✅ | ❌ | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-scrapegraph?style=flat-square&label=%20) |\n", + "\n", + "### Tool features\n", + "\n", + "| Tool | Purpose | Input | Output |\n", + "| :--- | :--- | :--- | :--- |\n", + "| SmartScraperTool | Extract structured data from websites | URL + prompt | JSON |\n", + "| MarkdownifyTool | Convert webpages to markdown | URL | Markdown text |\n", + "| LocalScraperTool | Extract data from HTML content | HTML + prompt | JSON |\n", + "| GetCreditsTool | Check API credits | None | Credit info |\n", + "\n", + "\n", + "## Setup\n", + "\n", + "The integration requires the following packages:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "f85b4089", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%pip install --quiet -U langchain-scrapegraph" + ] + }, + { + "cell_type": "markdown", + "id": "b15e9266", + "metadata": {}, + "source": [ + "### Credentials\n", + "\n", + "You'll need a ScrapeGraph AI API key to use these tools. Get one at [scrapegraphai.com](https://scrapegraphai.com)." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "e0b178a2", + "metadata": {}, + "outputs": [], + "source": [ + "import getpass\n", + "import os\n", + "\n", + "if not os.environ.get(\"SGAI_API_KEY\"):\n", + " os.environ[\"SGAI_API_KEY\"] = getpass.getpass(\"ScrapeGraph AI API key:\\n\")" + ] + }, + { + "cell_type": "markdown", + "id": "bc5ab717", + "metadata": {}, + "source": [ + "It's also helpful (but not needed) to set up [LangSmith](https://smith.langchain.com/) for best-in-class observability:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a6c2f136", + "metadata": {}, + "outputs": [], + "source": [ + "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", + "os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()" + ] + }, + { + "cell_type": "markdown", + "id": "1c97218f", + "metadata": {}, + "source": [ + "## Instantiation\n", + "\n", + "Here we show how to instantiate instances of the ScrapeGraph tools:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "8b3ddfe9", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_scrapegraph.tools import (\n", + " GetCreditsTool,\n", + " LocalScraperTool,\n", + " MarkdownifyTool,\n", + " SmartScraperTool,\n", + ")\n", + "\n", + "smartscraper = SmartScraperTool()\n", + "markdownify = MarkdownifyTool()\n", + "localscraper = LocalScraperTool()\n", + "credits = GetCreditsTool()" + ] + }, + { + "cell_type": "markdown", + "id": "74147a1a", + "metadata": {}, + "source": [ + "## Invocation\n", + "\n", + "### [Invoke directly with args](/docs/concepts/tools)\n", + "\n", + "Let's try each tool individually:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "65310a8b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SmartScraper Result: {'company_name': 'ScrapeGraphAI', 'description': \"ScrapeGraphAI is a powerful AI web scraping tool that turns entire websites into clean, structured data through a simple API. It's designed to help developers and AI companies extract valuable data from websites efficiently and transform it into formats that are ready for use in LLM applications and data analysis.\"}\n", + "\n", + "Markdownify Result (first 200 chars): [![ScrapeGraphAI Logo](https://scrapegraphai.com/images/scrapegraphai_logo.svg)ScrapeGraphAI](https://scrapegraphai.com/)\n", + "\n", + "PartnersPricingFAQ[Blog](https://scrapegraphai.com/blog)DocsLog inSign up\n", + "\n", + "Op\n", + "LocalScraper Result: {'company_name': 'Company Name', 'description': 'We are a technology company focused on AI solutions.', 'contact': {'email': 'contact@example.com', 'phone': '(555) 123-4567'}}\n", + "\n", + "Credits Info: {'remaining_credits': 49679, 'total_credits_used': 914}\n" + ] + } + ], + "source": [ + "# SmartScraper\n", + "result = smartscraper.invoke(\n", + " {\n", + " \"user_prompt\": \"Extract the company name and description\",\n", + " \"website_url\": \"https://scrapegraphai.com\",\n", + " }\n", + ")\n", + "print(\"SmartScraper Result:\", result)\n", + "\n", + "# Markdownify\n", + "markdown = markdownify.invoke({\"website_url\": \"https://scrapegraphai.com\"})\n", + "print(\"\\nMarkdownify Result (first 200 chars):\", markdown[:200])\n", + "\n", + "local_html = \"\"\"\n", + "\n", + " \n", + "

      Company Name

      \n", + "

      We are a technology company focused on AI solutions.

      \n", + "
      \n", + "

      Email: contact@example.com

      \n", + "

      Phone: (555) 123-4567

      \n", + "
      \n", + " \n", + "\n", + "\"\"\"\n", + "\n", + "# LocalScraper\n", + "result_local = localscraper.invoke(\n", + " {\n", + " \"user_prompt\": \"Make a summary of the webpage and extract the email and phone number\",\n", + " \"website_html\": local_html,\n", + " }\n", + ")\n", + "print(\"LocalScraper Result:\", result_local)\n", + "\n", + "# Check credits\n", + "credits_info = credits.invoke({})\n", + "print(\"\\nCredits Info:\", credits_info)" + ] + }, + { + "cell_type": "markdown", + "id": "d6e73897", + "metadata": {}, + "source": [ + "### [Invoke with ToolCall](/docs/concepts/tools)\n", + "\n", + "We can also invoke the tool with a model-generated ToolCall:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "f90e33a7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "ToolMessage(content='{\"main_heading\": \"Get the data you need from any website\", \"description\": \"Easily extract and gather information with just a few lines of code with a simple api. Turn websites into clean and usable structured data.\"}', name='SmartScraper', tool_call_id='1')" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_generated_tool_call = {\n", + " \"args\": {\n", + " \"user_prompt\": \"Extract the main heading and description\",\n", + " \"website_url\": \"https://scrapegraphai.com\",\n", + " },\n", + " \"id\": \"1\",\n", + " \"name\": smartscraper.name,\n", + " \"type\": \"tool_call\",\n", + "}\n", + "smartscraper.invoke(model_generated_tool_call)" + ] + }, + { + "cell_type": "markdown", + "id": "659f9fbd", + "metadata": {}, + "source": [ + "## Chaining\n", + "\n", + "Let's use our tools with an LLM to analyze a website:\n", + "\n", + "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "af3123ad", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "# | output: false\n", + "# | echo: false\n", + "\n", + "# %pip install -qU langchain langchain-openai\n", + "from langchain.chat_models import init_chat_model\n", + "\n", + "llm = init_chat_model(model=\"gpt-4o\", model_provider=\"openai\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "fdbf35b5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AIMessage(content='ScrapeGraph AI is an AI-powered web scraping tool that efficiently extracts and converts website data into structured formats via a simple API. It caters to developers, data scientists, and AI researchers, offering features like easy integration, support for dynamic content, and scalability for large projects. It supports various website types, including business, e-commerce, and educational sites. Contact: contact@scrapegraphai.com.', additional_kwargs={'tool_calls': [{'id': 'call_shkRPyjyAtfjH9ffG5rSy9xj', 'function': {'arguments': '{\"user_prompt\":\"Extract details about the products, services, and key features offered by ScrapeGraph AI, as well as any unique selling points or innovations mentioned on the website.\",\"website_url\":\"https://scrapegraphai.com\"}', 'name': 'SmartScraper'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 47, 'prompt_tokens': 480, 'total_tokens': 527, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_c7ca0ebaca', 'finish_reason': 'stop', 'logprobs': None}, id='run-45a12c86-d499-4273-8c59-0db926799bc7-0', tool_calls=[{'name': 'SmartScraper', 'args': {'user_prompt': 'Extract details about the products, services, and key features offered by ScrapeGraph AI, as well as any unique selling points or innovations mentioned on the website.', 'website_url': 'https://scrapegraphai.com'}, 'id': 'call_shkRPyjyAtfjH9ffG5rSy9xj', 'type': 'tool_call'}], usage_metadata={'input_tokens': 480, 'output_tokens': 47, 'total_tokens': 527, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from langchain_core.prompts import ChatPromptTemplate\n", + "from langchain_core.runnables import RunnableConfig, chain\n", + "\n", + "prompt = ChatPromptTemplate(\n", + " [\n", + " (\n", + " \"system\",\n", + " \"You are a helpful assistant that can use tools to extract structured information from websites.\",\n", + " ),\n", + " (\"human\", \"{user_input}\"),\n", + " (\"placeholder\", \"{messages}\"),\n", + " ]\n", + ")\n", + "\n", + "llm_with_tools = llm.bind_tools([smartscraper], tool_choice=smartscraper.name)\n", + "llm_chain = prompt | llm_with_tools\n", + "\n", + "\n", + "@chain\n", + "def tool_chain(user_input: str, config: RunnableConfig):\n", + " input_ = {\"user_input\": user_input}\n", + " ai_msg = llm_chain.invoke(input_, config=config)\n", + " tool_msgs = smartscraper.batch(ai_msg.tool_calls, config=config)\n", + " return llm_chain.invoke({**input_, \"messages\": [ai_msg, *tool_msgs]}, config=config)\n", + "\n", + "\n", + "tool_chain.invoke(\n", + " \"What does ScrapeGraph AI do? Extract this information from their website https://scrapegraphai.com\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "4ac8146c", + "metadata": {}, + "source": [ + "## API reference\n", + "\n", + "For detailed documentation of all ScrapeGraph features and configurations head to the Langchain API reference: https://python.langchain.com/docs/integrations/tools/scrapegraph\n", + "\n", + "Or to the official SDK repo: https://github.com/ScrapeGraphAI/langchain-scrapegraph" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/docs/integrations/vectorstores/astradb.ipynb b/docs/docs/integrations/vectorstores/astradb.ipynb index b2598ac96420c..c614b1f45b461 100644 --- a/docs/docs/integrations/vectorstores/astradb.ipynb +++ b/docs/docs/integrations/vectorstores/astradb.ipynb @@ -457,7 +457,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/chroma.ipynb b/docs/docs/integrations/vectorstores/chroma.ipynb index 90ea438f25849..0e76b95066464 100644 --- a/docs/docs/integrations/vectorstores/chroma.ipynb +++ b/docs/docs/integrations/vectorstores/chroma.ipynb @@ -461,7 +461,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/clickhouse.ipynb b/docs/docs/integrations/vectorstores/clickhouse.ipynb index fecd3998e5ff5..0a68c86cb2e2c 100644 --- a/docs/docs/integrations/vectorstores/clickhouse.ipynb +++ b/docs/docs/integrations/vectorstores/clickhouse.ipynb @@ -358,7 +358,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/couchbase.ipynb b/docs/docs/integrations/vectorstores/couchbase.ipynb index c5aa85e218002..af5f1af4f51e7 100644 --- a/docs/docs/integrations/vectorstores/couchbase.ipynb +++ b/docs/docs/integrations/vectorstores/couchbase.ipynb @@ -676,7 +676,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb b/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb index a6716ef30379f..65ed390b9da32 100644 --- a/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb +++ b/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb @@ -494,7 +494,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] @@ -506,7 +506,7 @@ "source": [ "## API reference\n", "\n", - "For detailed documentation of all DatabricksVectorSearch features and configurations head to the API reference: https://api.python.langchain.com/en/latest/vectorstores/langchain_databricks.vectorstores.DatabricksVectorSearch.html" + "For detailed documentation of all DatabricksVectorSearch features and configurations head to the API reference: https://python.langchain.com/api_reference/databricks/vectorstores/langchain_databricks.vectorstores.DatabricksVectorSearch.html" ] } ], diff --git a/docs/docs/integrations/vectorstores/elasticsearch.ipynb b/docs/docs/integrations/vectorstores/elasticsearch.ipynb index 339197a0fdae9..1a26b1c600fd5 100644 --- a/docs/docs/integrations/vectorstores/elasticsearch.ipynb +++ b/docs/docs/integrations/vectorstores/elasticsearch.ipynb @@ -471,7 +471,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/faiss.ipynb b/docs/docs/integrations/vectorstores/faiss.ipynb index 2837abd3602a6..0f957599065d0 100644 --- a/docs/docs/integrations/vectorstores/faiss.ipynb +++ b/docs/docs/integrations/vectorstores/faiss.ipynb @@ -364,7 +364,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/milvus.ipynb b/docs/docs/integrations/vectorstores/milvus.ipynb index 2cbc8d4e97362..50669cc2b3195 100644 --- a/docs/docs/integrations/vectorstores/milvus.ipynb +++ b/docs/docs/integrations/vectorstores/milvus.ipynb @@ -395,7 +395,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb b/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb index 812b2f12f29a5..a891a53f80bf6 100644 --- a/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb +++ b/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb @@ -439,7 +439,7 @@ "source": [ "#### Other search methods\n", "\n", - "There are a variety of other search methods that are not covered in this notebook, such as MMR search or searching by vector. For a full list of the search abilities available for `MongoDBAtlasVectorStore` check out the [API reference](https://api.python.langchain.com/en/latest/vectorstores/langchain_mongodb.vectorstores.MongoDBAtlasVectorSearch.html)." + "There are a variety of other search methods that are not covered in this notebook, such as MMR search or searching by vector. For a full list of the search abilities available for `MongoDBAtlasVectorStore` check out the [API reference](https://python.langchain.com/api_reference/mongodb/vectorstores/langchain_mongodb.vectorstores.MongoDBAtlasVectorSearch.html)." ] }, { @@ -488,7 +488,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/neo4jvector.ipynb b/docs/docs/integrations/vectorstores/neo4jvector.ipynb index cc489d5c48352..87f521c2fad4c 100644 --- a/docs/docs/integrations/vectorstores/neo4jvector.ipynb +++ b/docs/docs/integrations/vectorstores/neo4jvector.ipynb @@ -34,7 +34,7 @@ "source": [ "# Pip install necessary package\n", "%pip install --upgrade --quiet neo4j\n", - "%pip install --upgrade --quiet langchain-openai langchain-community\n", + "%pip install --upgrade --quiet langchain-openai langchain-neo4j\n", "%pip install --upgrade --quiet tiktoken" ] }, @@ -75,8 +75,8 @@ "outputs": [], "source": [ "from langchain_community.document_loaders import TextLoader\n", - "from langchain_community.vectorstores import Neo4jVector\n", "from langchain_core.documents import Document\n", + "from langchain_neo4j import Neo4jVector\n", "from langchain_openai import OpenAIEmbeddings\n", "from langchain_text_splitters import CharacterTextSplitter" ] diff --git a/docs/docs/integrations/vectorstores/pgvector.ipynb b/docs/docs/integrations/vectorstores/pgvector.ipynb index 8a532b627b919..e6b15ac918433 100644 --- a/docs/docs/integrations/vectorstores/pgvector.ipynb +++ b/docs/docs/integrations/vectorstores/pgvector.ipynb @@ -436,7 +436,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/pinecone.ipynb b/docs/docs/integrations/vectorstores/pinecone.ipynb index a54e4edbeec02..af7882dcef085 100644 --- a/docs/docs/integrations/vectorstores/pinecone.ipynb +++ b/docs/docs/integrations/vectorstores/pinecone.ipynb @@ -410,7 +410,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/qdrant.ipynb b/docs/docs/integrations/vectorstores/qdrant.ipynb index b4f2b5a428ad1..1d963955e607f 100644 --- a/docs/docs/integrations/vectorstores/qdrant.ipynb +++ b/docs/docs/integrations/vectorstores/qdrant.ipynb @@ -648,7 +648,7 @@ } ], "source": [ - "from qdrant_client.http import models\n", + "from qdrant_client import models\n", "\n", "results = vector_store.similarity_search(\n", " query=\"Who are the best soccer players in the world?\",\n", @@ -715,7 +715,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/redis.ipynb b/docs/docs/integrations/vectorstores/redis.ipynb index d43ec71cf4e3b..603a1e4527f15 100644 --- a/docs/docs/integrations/vectorstores/redis.ipynb +++ b/docs/docs/integrations/vectorstores/redis.ipynb @@ -762,7 +762,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)" ] diff --git a/docs/docs/integrations/vectorstores/sap_hanavector.ipynb b/docs/docs/integrations/vectorstores/sap_hanavector.ipynb index 90a0ed5e668e6..ded2118134bc2 100644 --- a/docs/docs/integrations/vectorstores/sap_hanavector.ipynb +++ b/docs/docs/integrations/vectorstores/sap_hanavector.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": { "tags": [] }, @@ -41,7 +41,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:02:16.802456Z", @@ -64,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:02:28.174088Z", @@ -73,8 +73,10 @@ }, "outputs": [], "source": [ + "from dotenv import load_dotenv\n", "from hdbcli import dbapi\n", "\n", + "load_dotenv()\n", "# Use connection settings from the environment\n", "connection = dbapi.connect(\n", " address=os.environ.get(\"HANA_DB_ADDRESS\"),\n", @@ -102,14 +104,22 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:02:25.452472Z", "start_time": "2023-09-09T08:02:25.441563Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of document chunks: 88\n" + ] + } + ], "source": [ "from langchain_community.document_loaders import TextLoader\n", "from langchain_community.vectorstores.hanavector import HanaDB\n", @@ -134,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:04:16.696625Z", @@ -157,9 +167,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Delete already existing documents from the table\n", "db.delete(filter={})\n", @@ -178,9 +199,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "As I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. \n", + "\n", + "While it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice.\n" + ] + } + ], "source": [ "query = \"What did the president say about Ketanji Brown Jackson\"\n", "docs = db.similarity_search(query, k=2)\n", @@ -199,9 +235,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "As I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. \n", + "\n", + "While it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice.\n" + ] + } + ], "source": [ "from langchain_community.vectorstores.utils import DistanceStrategy\n", "\n", @@ -235,7 +286,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:05:23.276819Z", @@ -246,7 +297,24 @@ "outputs_hidden": false } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. \n", + "\n", + "In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. \n", + "\n", + "Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world.\n" + ] + } + ], "source": [ "docs = db.max_marginal_relevance_search(query, k=2, fetch_k=20)\n", "for doc in docs:\n", @@ -254,6 +322,86 @@ " print(doc.page_content)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating an HNSW Vector Index\n", + "\n", + "A vector index can significantly speed up top-k nearest neighbor queries for vectors. Users can create a Hierarchical Navigable Small World (HNSW) vector index using the `create_hnsw_index` function.\n", + "\n", + "For more information about creating an index at the database level, please refer to the [official documentation](https://help.sap.com/docs/hana-cloud-database/sap-hana-cloud-sap-hana-database-vector-engine-guide/create-vector-index-statement-data-definition).\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. \n", + "\n", + "In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. \n", + "\n", + "Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world.\n" + ] + } + ], + "source": [ + "# HanaDB instance uses cosine similarity as default:\n", + "db_cosine = HanaDB(\n", + " embedding=embeddings, connection=connection, table_name=\"STATE_OF_THE_UNION\"\n", + ")\n", + "\n", + "# Attempting to create the HNSW index with default parameters\n", + "db_cosine.create_hnsw_index() # If no other parameters are specified, the default values will be used\n", + "# Default values: m=64, ef_construction=128, ef_search=200\n", + "# The default index name will be: STATE_OF_THE_UNION_COSINE_SIMILARITY_IDX (verify this naming pattern in HanaDB class)\n", + "\n", + "\n", + "# Creating a HanaDB instance with L2 distance as the similarity function and defined values\n", + "db_l2 = HanaDB(\n", + " embedding=embeddings,\n", + " connection=connection,\n", + " table_name=\"STATE_OF_THE_UNION\",\n", + " distance_strategy=DistanceStrategy.EUCLIDEAN_DISTANCE, # Specify L2 distance\n", + ")\n", + "\n", + "# This will create an index based on L2 distance strategy.\n", + "db_l2.create_hnsw_index(\n", + " index_name=\"STATE_OF_THE_UNION_L2_index\",\n", + " m=100, # Max number of neighbors per graph node (valid range: 4 to 1000)\n", + " ef_construction=200, # Max number of candidates during graph construction (valid range: 1 to 100000)\n", + " ef_search=500, # Min number of candidates during the search (valid range: 1 to 100000)\n", + ")\n", + "\n", + "# Use L2 index to perform MMR\n", + "docs = db_l2.max_marginal_relevance_search(query, k=2, fetch_k=20)\n", + "for doc in docs:\n", + " print(\"-\" * 80)\n", + " print(doc.page_content)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "**Key Points**:\n", + "- **Similarity Function**: The similarity function for the index is **cosine similarity** by default. If you want to use a different similarity function (e.g., `L2` distance), you need to specify it when initializing the `HanaDB` instance.\n", + "- **Default Parameters**: In the `create_hnsw_index` function, if the user does not provide custom values for parameters like `m`, `ef_construction`, or `ef_search`, the default values (e.g., `m=64`, `ef_construction=128`, `ef_search=200`) will be used automatically. These values ensure the index is created with reasonable performance without requiring user intervention.\n", + "\n" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -263,9 +411,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "db = HanaDB(\n", " connection=connection, embedding=embeddings, table_name=\"LANGCHAIN_DEMO_BASIC\"\n", @@ -284,9 +443,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "docs = [Document(page_content=\"Some text\"), Document(page_content=\"Other docs\")]\n", "db.add_documents(docs)" @@ -301,9 +471,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "docs = [\n", " Document(\n", @@ -327,9 +508,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "foo\n", + "{'start': 100, 'end': 150, 'doc_name': 'foo.txt', 'quality': 'bad'}\n" + ] + } + ], "source": [ "docs = db.similarity_search(\"foobar\", k=2, filter={\"quality\": \"bad\"})\n", "# With filtering on \"quality\"==\"bad\", only one document should be returned\n", @@ -348,9 +539,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n" + ] + } + ], "source": [ "db.delete(filter={\"quality\": \"bad\"})\n", "\n", @@ -385,7 +584,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -433,9 +632,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'id': {'$ne': 1}}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n", + "Filter: {'id': {'$gt': 1}}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n", + "Filter: {'id': {'$gte': 1}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n", + "Filter: {'id': {'$lt': 1}}\n", + "\n", + "Filter: {'id': {'$lte': 1}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n" + ] + } + ], "source": [ "advanced_filter = {\"id\": {\"$ne\": 1}}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -467,9 +687,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'id': {'$between': (1, 2)}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "Filter: {'name': {'$in': ['adam', 'bob']}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "Filter: {'name': {'$nin': ['adam', 'bob']}}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n" + ] + } + ], "source": [ "advanced_filter = {\"id\": {\"$between\": (1, 2)}}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -493,9 +728,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'name': {'$like': 'a%'}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "Filter: {'name': {'$like': '%a%'}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n" + ] + } + ], "source": [ "advanced_filter = {\"name\": {\"$like\": \"a%\"}}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -515,9 +762,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'$or': [{'id': 1}, {'name': 'bob'}]}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "Filter: {'$and': [{'id': 1}, {'id': 2}]}\n", + "\n", + "Filter: {'$or': [{'id': 1}, {'id': 2}, {'id': 3}]}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n" + ] + } + ], "source": [ "advanced_filter = {\"$or\": [{\"id\": 1}, {\"name\": \"bob\"}]}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -541,7 +804,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -574,7 +837,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -635,9 +898,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Answer from LLM:\n", + "================\n", + "The United States has set up joint patrols with Mexico and Guatemala to catch more human traffickers. This collaboration is part of the efforts to address immigration issues and secure the borders in the region.\n", + "================\n", + "Number of used source document chunks: 5\n" + ] + } + ], "source": [ "question = \"What about Mexico and Guatemala?\"\n", "\n", @@ -679,9 +954,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Answer from LLM:\n", + "================\n", + "Mexico and Guatemala are involved in joint patrols to catch human traffickers.\n" + ] + } + ], "source": [ "question = \"What about other countries?\"\n", "\n", @@ -711,9 +996,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Access the vector DB with a new table\n", "db = HanaDB(\n", @@ -742,9 +1038,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('VEC_META', 'NCLOB')\n", + "('VEC_TEXT', 'NCLOB')\n", + "('VEC_VECTOR', 'REAL_VECTOR')\n" + ] + } + ], "source": [ "cur = connection.cursor()\n", "cur.execute(\n", @@ -795,12 +1101,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "None\n", + "Some other text\n", + "{\"start\": 400, \"end\": 450, \"doc_name\": \"other.txt\"}\n", + "\n" + ] + } + ], "source": [ - "# Create a new table \"MY_OWN_TABLE\" with three \"standard\" columns and one additional column\n", - "my_own_table_name = \"MY_OWN_TABLE\"\n", + "# Create a new table \"MY_OWN_TABLE_ADD\" with three \"standard\" columns and one additional column\n", + "my_own_table_name = \"MY_OWN_TABLE_ADD\"\n", "cur = connection.cursor()\n", "cur.execute(\n", " (\n", @@ -851,9 +1168,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "Some other text\n", + "--------------------------------------------------------------------------------\n", + "Some more text\n" + ] + } + ], "source": [ "docs = [\n", " Document(\n", @@ -886,9 +1214,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filters on this value are very performant\n", + "Some other text\n", + "{\"start\": 400, \"end\": 450, \"doc_name\": \"other.txt\", \"CUSTOMTEXT\": \"Filters on this value are very performant\"}\n", + "\n" + ] + } + ], "source": [ "# Create a new table \"PERFORMANT_CUSTOMTEXT_FILTER\" with three \"standard\" columns and one additional column\n", "my_own_table_name = \"PERFORMANT_CUSTOMTEXT_FILTER\"\n", @@ -952,9 +1291,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "Some other text\n", + "--------------------------------------------------------------------------------\n", + "Some more text\n" + ] + } + ], "source": [ "docs = [\n", " Document(\n", @@ -994,7 +1344,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/docs/docs/integrations/vectorstores/sqlitevec.ipynb b/docs/docs/integrations/vectorstores/sqlitevec.ipynb index 33eb5b854d502..2df878ad238bc 100644 --- a/docs/docs/integrations/vectorstores/sqlitevec.ipynb +++ b/docs/docs/integrations/vectorstores/sqlitevec.ipynb @@ -155,7 +155,7 @@ "cell_type": "markdown", "source": [ "## API reference\n", - "For detailed documentation of all SQLiteVec features and configurations head to the API reference:https://api.python.langchain.com/en/latest/vectorstores/langchain_community.vectorstores.sqlitevec.SQLiteVec.html" + "For detailed documentation of all SQLiteVec features and configurations head to the API reference: https://python.langchain.com/api_reference/community/vectorstores/langchain_community.vectorstores.sqlitevec.SQLiteVec.html" ] }, { diff --git a/docs/docs/integrations/vectorstores/weaviate.ipynb b/docs/docs/integrations/vectorstores/weaviate.ipynb index bd61077055351..ebe4541269f46 100644 --- a/docs/docs/integrations/vectorstores/weaviate.ipynb +++ b/docs/docs/integrations/vectorstores/weaviate.ipynb @@ -552,7 +552,7 @@ "id": "66690c78", "metadata": {}, "source": [ - "A known limitation of large languag models (LLMs) is that their training data can be outdated, or not include the specific domain knowledge that you require.\n", + "A known limitation of large language models (LLMs) is that their training data can be outdated, or not include the specific domain knowledge that you require.\n", "\n", "Take a look at the example below:" ] diff --git a/docs/docs/introduction.mdx b/docs/docs/introduction.mdx index b3edcfbd15dff..e0110afd973bb 100644 --- a/docs/docs/introduction.mdx +++ b/docs/docs/introduction.mdx @@ -11,7 +11,7 @@ LangChain simplifies every stage of the LLM application lifecycle: - **Development**: Build your applications using LangChain's open-source [building blocks](/docs/concepts/lcel), [components](/docs/concepts), and [third-party integrations](/docs/integrations/providers/). Use [LangGraph](/docs/concepts/architecture/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support. - **Productionization**: Use [LangSmith](https://docs.smith.langchain.com/) to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence. -- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/). +- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/). import ThemedImage from '@theme/ThemedImage'; import useBaseUrl from '@docusaurus/useBaseUrl'; @@ -29,11 +29,11 @@ import useBaseUrl from '@docusaurus/useBaseUrl'; Concretely, the framework consists of the following open-source libraries: - **`langchain-core`**: Base abstractions and LangChain Expression Language. -- Integration packages (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers. +- **Integration packages** (e.g. `langchain-openai`, `langchain-anthropic`, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers. - **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. - **`langchain-community`**: Third-party integrations that are community maintained. -- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. -- **[LangGraphPlatform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform)**: Deploy LLM applications built with LangGraph to production. +- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph). +- **[LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform)**: Deploy LLM applications built with LangGraph to production. - **[LangSmith](https://docs.smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications. diff --git a/docs/docs/security.md b/docs/docs/security.md deleted file mode 100644 index 08e841c89a25d..0000000000000 --- a/docs/docs/security.md +++ /dev/null @@ -1,30 +0,0 @@ -# Security - -LangChain has a large ecosystem of integrations with various external resources like local and remote file systems, APIs and databases. These integrations allow developers to create versatile applications that combine the power of LLMs with the ability to access, interact with and manipulate external resources. - -## Best practices - -When building such applications developers should remember to follow good security practices: - -* [**Limit Permissions**](https://en.wikipedia.org/wiki/Principle_of_least_privilege): Scope permissions specifically to the application's need. Granting broad or excessive permissions can introduce significant security vulnerabilities. To avoid such vulnerabilities, consider using read-only credentials, disallowing access to sensitive resources, using sandboxing techniques (such as running inside a container), specifying proxy configurations to control external requests, etc. as appropriate for your application. -* **Anticipate Potential Misuse**: Just as humans can err, so can Large Language Models (LLMs). Always assume that any system access or credentials may be used in any way allowed by the permissions they are assigned. For example, if a pair of database credentials allows deleting data, it’s safest to assume that any LLM able to use those credentials may in fact delete data. -* [**Defense in Depth**](https://en.wikipedia.org/wiki/Defense_in_depth_(computing)): No security technique is perfect. Fine-tuning and good chain design can reduce, but not eliminate, the odds that a Large Language Model (LLM) may make a mistake. It’s best to combine multiple layered security approaches rather than relying on any single layer of defense to ensure security. For example: use both read-only permissions and sandboxing to ensure that LLMs are only able to access data that is explicitly meant for them to use. - -Risks of not doing so include, but are not limited to: -* Data corruption or loss. -* Unauthorized access to confidential information. -* Compromised performance or availability of critical resources. - -Example scenarios with mitigation strategies: - -* A user may ask an agent with access to the file system to delete files that should not be deleted or read the content of files that contain sensitive information. To mitigate, limit the agent to only use a specific directory and only allow it to read or write files that are safe to read or write. Consider further sandboxing the agent by running it in a container. -* A user may ask an agent with write access to an external API to write malicious data to the API, or delete data from that API. To mitigate, give the agent read-only API keys, or limit it to only use endpoints that are already resistant to such misuse. -* A user may ask an agent with access to a database to drop a table or mutate the schema. To mitigate, scope the credentials to only the tables that the agent needs to access and consider issuing READ-ONLY credentials. - -If you're building applications that access external resources like file systems, APIs -or databases, consider speaking with your company's security team to determine how to best -design and secure your applications. - -## Reporting a vulnerability - -Please report security vulnerabilities by email to security@langchain.dev. This will ensure the issue is promptly triaged and acted upon as needed. diff --git a/docs/docs/tutorials/agents.ipynb b/docs/docs/tutorials/agents.ipynb index 2f1671e7c796d..3eca90dc8d043 100644 --- a/docs/docs/tutorials/agents.ipynb +++ b/docs/docs/tutorials/agents.ipynb @@ -21,20 +21,10 @@ "source": [ "# Build an Agent\n", "\n", - ":::info Prerequisites\n", - "\n", - "This guide assumes familiarity with the following concepts:\n", - "\n", - "- [Chat Models](/docs/concepts/chat_models)\n", - "- [Tools](/docs/concepts/tools)\n", - "- [Agents](/docs/concepts/agents)\n", - "\n", - ":::\n", - "\n", "By themselves, language models can't take actions - they just output text.\n", "A big use case for LangChain is creating **agents**.\n", - "Agents are systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action.\n", - "After executing actions, the results can be fed back into the LLM to determine whether more actions are needed, or whether it is okay to finish.\n", + "[Agents](/docs/concepts/agents) are systems that use [LLMs](/docs/concepts/chat_models) as reasoning engines to determine which actions to take and the inputs necessary to perform the action.\n", + "After executing actions, the results can be fed back into the LLM to determine whether more actions are needed, or whether it is okay to finish. This is often achieved via [tool-calling](/docs/concepts/tool_calling).\n", "\n", "In this tutorial we will build an agent that can interact with a search engine. You will be able to ask this agent questions, watch it call the search tool, and have conversations with it.\n", "\n", @@ -747,7 +737,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.3" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/chatbot.ipynb b/docs/docs/tutorials/chatbot.ipynb index afc8142c26400..59c5220200c63 100644 --- a/docs/docs/tutorials/chatbot.ipynb +++ b/docs/docs/tutorials/chatbot.ipynb @@ -25,17 +25,6 @@ "cell_type": "markdown", "metadata": {}, "source": [ - ":::info Prerequisites\n", - "\n", - "This guide assumes familiarity with the following concepts:\n", - "\n", - "- [Chat Models](/docs/concepts/chat_models)\n", - "- [Prompt Templates](/docs/concepts/prompt_templates)\n", - "- [Chat History](/docs/concepts/chat_history)\n", - "\n", - "This guide requires `langgraph >= 0.2.28`.\n", - ":::\n", - "\n", ":::note\n", "\n", "This tutorial previously used the [RunnableWithMessageHistory](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.history.RunnableWithMessageHistory.html) abstraction. You can access that version of the documentation in the [v0.2 docs](https://python.langchain.com/v0.2/docs/tutorials/chatbot/).\n", @@ -50,7 +39,7 @@ "## Overview\n", "\n", "We'll go over an example of how to design and implement an LLM-powered chatbot. \n", - "This chatbot will be able to have a conversation and remember previous interactions.\n", + "This chatbot will be able to have a conversation and remember previous interactions with a [chat model](/docs/concepts/chat_models).\n", "\n", "\n", "Note that this chatbot that we build will only use the language model to have a conversation.\n", @@ -71,7 +60,7 @@ "\n", "### Installation\n", "\n", - "For this tutorial we will need `langchain-core` and `langgraph`:\n", + "For this tutorial we will need `langchain-core` and `langgraph`. This guide requires `langgraph >= 0.2.28`.\n", "\n", "import Tabs from '@theme/Tabs';\n", "import TabItem from '@theme/TabItem';\n", @@ -119,7 +108,7 @@ "\n", "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", "\n", - "\n" + "\n" ] }, { @@ -151,7 +140,7 @@ { "data": { "text/plain": [ - "AIMessage(content='Hi Bob! How can I assist you today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 10, 'prompt_tokens': 11, 'total_tokens': 21, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_1bb46167f9', 'finish_reason': 'stop', 'logprobs': None}, id='run-149994c0-d958-49bb-9a9d-df911baea29f-0', usage_metadata={'input_tokens': 11, 'output_tokens': 10, 'total_tokens': 21})" + "AIMessage(content='Hi Bob! How can I assist you today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 10, 'prompt_tokens': 11, 'total_tokens': 21, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_0705bf87c0', 'finish_reason': 'stop', 'logprobs': None}, id='run-5211544f-da9f-4325-8b8e-b3d92b2fc71a-0', usage_metadata={'input_tokens': 11, 'output_tokens': 10, 'total_tokens': 21, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})" ] }, "execution_count": 3, @@ -180,7 +169,7 @@ { "data": { "text/plain": [ - "AIMessage(content=\"I'm sorry, but I don't have access to personal information about individuals unless you've shared it with me in this conversation. How can I assist you today?\", additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 30, 'prompt_tokens': 11, 'total_tokens': 41, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_1bb46167f9', 'finish_reason': 'stop', 'logprobs': None}, id='run-0ecab57c-728d-4fd1-845c-394a62df8e13-0', usage_metadata={'input_tokens': 11, 'output_tokens': 30, 'total_tokens': 41})" + "AIMessage(content=\"I'm sorry, but I don't have access to personal information about users unless it has been shared with me in the course of our conversation. How can I assist you today?\", additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 34, 'prompt_tokens': 11, 'total_tokens': 45, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_0705bf87c0', 'finish_reason': 'stop', 'logprobs': None}, id='run-a2d13a18-7022-4784-b54f-f85c097d1075-0', usage_metadata={'input_tokens': 11, 'output_tokens': 34, 'total_tokens': 45, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})" ] }, "execution_count": 4, @@ -201,7 +190,7 @@ "We can see that it doesn't take the previous conversation turn into context, and cannot answer the question.\n", "This makes for a terrible chatbot experience!\n", "\n", - "To get around this, we need to pass the entire conversation history into the model. Let's see what happens when we do that:" + "To get around this, we need to pass the entire [conversation history](/docs/concepts/chat_history) into the model. Let's see what happens when we do that:" ] }, { @@ -212,7 +201,7 @@ { "data": { "text/plain": [ - "AIMessage(content='Your name is Bob! How can I help you today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 12, 'prompt_tokens': 33, 'total_tokens': 45, 'completion_tokens_details': {'reasoning_tokens': 0}}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_1bb46167f9', 'finish_reason': 'stop', 'logprobs': None}, id='run-c164c5a1-d85f-46ee-ba8a-bb511cfb0e51-0', usage_metadata={'input_tokens': 33, 'output_tokens': 12, 'total_tokens': 45})" + "AIMessage(content='Your name is Bob! How can I help you today, Bob?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 33, 'total_tokens': 47, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_0705bf87c0', 'finish_reason': 'stop', 'logprobs': None}, id='run-34bcccb3-446e-42f2-b1de-52c09936c02c-0', usage_metadata={'input_tokens': 33, 'output_tokens': 14, 'total_tokens': 47, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})" ] }, "execution_count": 5, @@ -342,7 +331,7 @@ "text": [ "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "Your name is Bob! How can I help you today?\n" + "Your name is Bob! How can I help you today, Bob?\n" ] } ], @@ -372,7 +361,7 @@ "text": [ "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "I'm sorry, but I don't have access to personal information about you unless you provide it. How can I assist you today?\n" + "I'm sorry, but I don't have access to personal information about you unless you've shared it in this conversation. How can I assist you today?\n" ] } ], @@ -402,7 +391,7 @@ "text": [ "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "Your name is Bob! If there's anything else you'd like to discuss or ask, feel free!\n" + "Your name is Bob. What would you like to discuss today?\n" ] } ], @@ -453,7 +442,7 @@ "\n", "## Prompt templates\n", "\n", - "Prompt Templates help to turn raw user information into a format that the LLM can work with. In this case, the raw user input is just a message, which we are passing to the LLM. Let's now make that a bit more complicated. First, let's add in a system message with some custom instructions (but still taking messages as input). Next, we'll add in more input besides just the messages.\n", + "[Prompt Templates](/docs/concepts/prompt_templates) help to turn raw user information into a format that the LLM can work with. In this case, the raw user input is just a message, which we are passing to the LLM. Let's now make that a bit more complicated. First, let's add in a system message with some custom instructions (but still taking messages as input). Next, we'll add in more input besides just the messages.\n", "\n", "To add in a system message, we will create a `ChatPromptTemplate`. We will utilize `MessagesPlaceholder` to pass all the messages in." ] @@ -466,7 +455,7 @@ "source": [ "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n", "\n", - "prompt = ChatPromptTemplate.from_messages(\n", + "prompt_template = ChatPromptTemplate.from_messages(\n", " [\n", " (\n", " \"system\",\n", @@ -495,8 +484,8 @@ "\n", "def call_model(state: MessagesState):\n", " # highlight-start\n", - " chain = prompt | model\n", - " response = chain.invoke(state)\n", + " prompt = prompt_template.invoke(state)\n", + " response = model.invoke(prompt)\n", " # highlight-end\n", " return {\"messages\": response}\n", "\n", @@ -517,7 +506,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -526,7 +515,7 @@ "text": [ "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "Ahoy there, Jim! What brings ye to these treacherous waters today? Be ye seekin’ treasure, tales, or perhaps a bit o’ knowledge? Speak up, matey!\n" + "Ahoy there, Jim! What brings ye to these waters today? Be ye seekin' treasure, knowledge, or perhaps a good tale from the high seas? Arrr!\n" ] } ], @@ -541,7 +530,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -550,7 +539,7 @@ "text": [ "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "Ye be callin' yerself Jim, if I be hearin' ye correctly! A fine name for a scallywag such as yerself! What else can I do fer ye, me hearty?\n" + "Ye be called Jim, matey! A fine name fer a swashbuckler such as yerself! What else can I do fer ye? Arrr!\n" ] } ], @@ -571,11 +560,11 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ - "prompt = ChatPromptTemplate.from_messages(\n", + "prompt_template = ChatPromptTemplate.from_messages(\n", " [\n", " (\n", " \"system\",\n", @@ -595,7 +584,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -618,8 +607,8 @@ "\n", "\n", "def call_model(state: State):\n", - " chain = prompt | model\n", - " response = chain.invoke(state)\n", + " prompt = prompt_template.invoke(state)\n", + " response = model.invoke(prompt)\n", " return {\"messages\": [response]}\n", "\n", "\n", @@ -632,7 +621,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -668,7 +657,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -677,7 +666,7 @@ "text": [ "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "Tu nombre es Bob.\n" + "Tu nombre es Bob. ¿Hay algo más en lo que pueda ayudarte?\n" ] } ], @@ -716,7 +705,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -731,7 +720,7 @@ " AIMessage(content='yes!', additional_kwargs={}, response_metadata={})]" ] }, - "execution_count": 21, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -774,7 +763,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -782,12 +771,12 @@ "\n", "\n", "def call_model(state: State):\n", - " chain = prompt | model\n", " # highlight-start\n", " trimmed_messages = trimmer.invoke(state[\"messages\"])\n", - " response = chain.invoke(\n", + " prompt = prompt_template.invoke(\n", " {\"messages\": trimmed_messages, \"language\": state[\"language\"]}\n", " )\n", + " response = model.invoke(prompt)\n", " # highlight-end\n", " return {\"messages\": [response]}\n", "\n", @@ -808,7 +797,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -817,7 +806,7 @@ "text": [ "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "I don't know your name. If you'd like to share it, feel free!\n" + "I don't know your name. You haven't told me yet!\n" ] } ], @@ -844,7 +833,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -892,7 +881,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -901,9 +890,9 @@ "text": [ "|Hi| Todd|!| Here|’s| a| joke| for| you|:\n", "\n", - "|Why| did| the| scare|crow| win| an| award|?\n", + "|Why| don|’t| skeleton|s| fight| each| other|?\n", "\n", - "|Because| he| was| outstanding| in| his| field|!||" + "|Because| they| don|’t| have| the| guts|!||" ] } ], @@ -960,7 +949,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/classification.ipynb b/docs/docs/tutorials/classification.ipynb index 2391e987e4d6e..c869efc1524e5 100644 --- a/docs/docs/tutorials/classification.ipynb +++ b/docs/docs/tutorials/classification.ipynb @@ -39,7 +39,7 @@ "\n", "## Quickstart\n", "\n", - "Let's see a very straightforward example of how we can use OpenAI tool calling for tagging in LangChain. We'll use the [`with_structured_output`](/docs/how_to/structured_output) method supported by OpenAI models:" + "Let's see a very straightforward example of how we can use OpenAI tool calling for tagging in LangChain. We'll use the [`with_structured_output`](/docs/how_to/structured_output) method supported by OpenAI models." ] }, { @@ -49,11 +49,34 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install --upgrade --quiet langchain langchain-openai\n", + "%pip install --upgrade --quiet langchain-core" + ] + }, + { + "cell_type": "markdown", + "id": "cc2b7cdf-babb-46e2-98d0-302f69446842", + "metadata": {}, + "source": [ + "We'll need to load a [chat model](/docs/integrations/chat/):\n", + "\n", + "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "608ee181-3f06-4719-842d-9672fdce6e57", + "metadata": {}, + "outputs": [], + "source": [ + "# | output: false\n", + "# | echo: false\n", "\n", - "# Set env var OPENAI_API_KEY or load from a .env file:\n", - "# import dotenv\n", - "# dotenv.load_dotenv()" + "from langchain_openai import ChatOpenAI\n", + "\n", + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" ] }, { @@ -66,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "39f3ce3e", "metadata": {}, "outputs": [], @@ -98,14 +121,12 @@ "# LLM\n", "llm = ChatOpenAI(temperature=0, model=\"gpt-4o-mini\").with_structured_output(\n", " Classification\n", - ")\n", - "\n", - "tagging_chain = tagging_prompt | llm" + ")" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "5509b6a6", "metadata": {}, "outputs": [ @@ -115,14 +136,17 @@ "Classification(sentiment='positive', aggressiveness=1, language='Spanish')" ] }, - "execution_count": 6, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inp = \"Estoy increiblemente contento de haberte conocido! Creo que seremos muy buenos amigos!\"\n", - "tagging_chain.invoke({\"input\": inp})" + "prompt = tagging_prompt.invoke({\"input\": inp})\n", + "response = llm.invoke(prompt)\n", + "\n", + "response" ] }, { @@ -135,25 +159,27 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 10, "id": "9154474c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'sentiment': 'negative', 'aggressiveness': 8, 'language': 'Spanish'}" + "{'sentiment': 'enojado', 'aggressiveness': 8, 'language': 'es'}" ] }, - "execution_count": 13, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inp = \"Estoy muy enojado con vos! Te voy a dar tu merecido!\"\n", - "res = tagging_chain.invoke({\"input\": inp})\n", - "res.dict()" + "prompt = tagging_prompt.invoke({\"input\": inp})\n", + "response = llm.invoke(prompt)\n", + "\n", + "response.dict()" ] }, { @@ -194,7 +220,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 11, "id": "6a5f7961", "metadata": {}, "outputs": [], @@ -231,9 +257,7 @@ "\n", "llm = ChatOpenAI(temperature=0, model=\"gpt-4o-mini\").with_structured_output(\n", " Classification\n", - ")\n", - "\n", - "chain = tagging_prompt | llm" + ")" ] }, { @@ -246,68 +270,71 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 12, "id": "d9b9d53d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Classification(sentiment='happy', aggressiveness=1, language='spanish')" + "Classification(sentiment='positive', aggressiveness=1, language='Spanish')" ] }, - "execution_count": 17, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inp = \"Estoy increiblemente contento de haberte conocido! Creo que seremos muy buenos amigos!\"\n", - "chain.invoke({\"input\": inp})" + "prompt = tagging_prompt.invoke({\"input\": inp})\n", + "llm.invoke(prompt)" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 13, "id": "1c12fa00", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Classification(sentiment='sad', aggressiveness=5, language='spanish')" + "Classification(sentiment='enojado', aggressiveness=8, language='es')" ] }, - "execution_count": 18, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inp = \"Estoy muy enojado con vos! Te voy a dar tu merecido!\"\n", - "chain.invoke({\"input\": inp})" + "prompt = tagging_prompt.invoke({\"input\": inp})\n", + "llm.invoke(prompt)" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 14, "id": "0bdfcb05", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Classification(sentiment='neutral', aggressiveness=2, language='english')" + "Classification(sentiment='neutral', aggressiveness=1, language='English')" ] }, - "execution_count": 19, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inp = \"Weather is ok here, I can go outside without much more than a coat\"\n", - "chain.invoke({\"input\": inp})" + "prompt = tagging_prompt.invoke({\"input\": inp})\n", + "llm.invoke(prompt)" ] }, { @@ -348,7 +375,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.1" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/data_generation.ipynb b/docs/docs/tutorials/data_generation.ipynb deleted file mode 100644 index 84a232f4ba2b3..0000000000000 --- a/docs/docs/tutorials/data_generation.ipynb +++ /dev/null @@ -1,666 +0,0 @@ -{ - "cells": [ - { - "cell_type": "raw", - "id": "1302a608-4b4d-46bf-bd0c-b4f13eff2e5e", - "metadata": {}, - "source": [ - "---\n", - "sidebar_class_name: hidden\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "aa3571cc", - "metadata": {}, - "source": [ - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain/blob/master/docs/docs/use_cases/data_generation.ipynb)\n", - "\n", - "# Generate Synthetic Data\n", - "\n", - "Synthetic data is artificially generated data, rather than data collected from real-world events. It's used to simulate real data without compromising privacy or encountering real-world limitations. \n", - "\n", - "Benefits of Synthetic Data:\n", - "\n", - "1. **Privacy and Security**: No real personal data at risk of breaches.\n", - "2. **Data Augmentation**: Expands datasets for machine learning.\n", - "3. **Flexibility**: Create specific or rare scenarios.\n", - "4. **Cost-effective**: Often cheaper than real-world data collection.\n", - "5. **Regulatory Compliance**: Helps navigate strict data protection laws.\n", - "6. **Model Robustness**: Can lead to better generalizing AI models.\n", - "7. **Rapid Prototyping**: Enables quick testing without real data.\n", - "8. **Controlled Experimentation**: Simulate specific conditions.\n", - "9. **Access to Data**: Alternative when real data isn't available.\n", - "\n", - "Note: Despite the benefits, synthetic data should be used carefully, as it may not always capture real-world complexities.\n", - "\n", - "## Quickstart\n", - "\n", - "In this notebook, we'll dive deep into generating synthetic medical billing records using the `langchain` library. This tool is particularly useful when you want to develop or test algorithms but don't want to use real patient data due to privacy concerns or data availability issues." - ] - }, - { - "cell_type": "markdown", - "id": "bca57012", - "metadata": {}, - "source": [ - "### Setup\n", - "First, you'll need to have the `langchain` library installed, along with its dependencies. Since we're using the OpenAI generator chain, we'll install that as well. Since this is an experimental library, we'll need to include `langchain_experimental` in our installation. We'll then import the necessary modules." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a0377478", - "metadata": {}, - "outputs": [], - "source": [ - "%pip install --upgrade --quiet langchain langchain_experimental langchain-openai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "391ae036-36a2-4d2a-8e1b-5a536b268b45", - "metadata": {}, - "outputs": [], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "if \"OPENAI_API_KEY\" not in os.environ:\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"Enter your OpenAI API key: \")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6b47bb31-b4c7-42ff-9253-2c94747db750", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain.prompts import FewShotPromptTemplate, PromptTemplate\n", - "from langchain_experimental.tabular_synthetic_data.openai import (\n", - " OPENAI_TEMPLATE,\n", - " create_openai_data_generator,\n", - ")\n", - "from langchain_experimental.tabular_synthetic_data.prompts import (\n", - " SYNTHETIC_FEW_SHOT_PREFIX,\n", - " SYNTHETIC_FEW_SHOT_SUFFIX,\n", - ")\n", - "from langchain_openai import ChatOpenAI\n", - "from pydantic import BaseModel" - ] - }, - { - "cell_type": "markdown", - "id": "a5a0917b", - "metadata": {}, - "source": [ - "## 1. Define Your Data Model\n", - "Every dataset has a structure or a \"schema\". The `MedicalBilling` class below serves as our schema for the synthetic data. By defining this, we're informing our synthetic data generator about the shape and nature of data we expect." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "291bad6e", - "metadata": {}, - "outputs": [], - "source": [ - "class MedicalBilling(BaseModel):\n", - " patient_id: int\n", - " patient_name: str\n", - " diagnosis_code: str\n", - " procedure_code: str\n", - " total_charge: float\n", - " insurance_claim_amount: float" - ] - }, - { - "cell_type": "markdown", - "id": "2059ca63", - "metadata": {}, - "source": [ - "For instance, every record will have a `patient_id` that's an integer, a `patient_name` that's a string, and so on.\n", - "\n", - "## 2. Sample Data\n", - "To guide the synthetic data generator, it's useful to provide it with a few real-world-like examples. These examples serve as a \"seed\" - they're representative of the kind of data you want, and the generator will use them to create data that looks similar to your expectations.\n", - "\n", - "Here are some fictional medical billing records:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b989b792", - "metadata": {}, - "outputs": [], - "source": [ - "examples = [\n", - " {\n", - " \"example\": \"\"\"Patient ID: 123456, Patient Name: John Doe, Diagnosis Code: \n", - " J20.9, Procedure Code: 99203, Total Charge: $500, Insurance Claim Amount: $350\"\"\"\n", - " },\n", - " {\n", - " \"example\": \"\"\"Patient ID: 789012, Patient Name: Johnson Smith, Diagnosis \n", - " Code: M54.5, Procedure Code: 99213, Total Charge: $150, Insurance Claim Amount: $120\"\"\"\n", - " },\n", - " {\n", - " \"example\": \"\"\"Patient ID: 345678, Patient Name: Emily Stone, Diagnosis Code: \n", - " E11.9, Procedure Code: 99214, Total Charge: $300, Insurance Claim Amount: $250\"\"\"\n", - " },\n", - "]" - ] - }, - { - "cell_type": "markdown", - "id": "57e28809", - "metadata": {}, - "source": [ - "## 3. Craft a Prompt Template\n", - "The generator doesn't magically know how to create our data; we need to guide it. We do this by creating a prompt template. This template helps instruct the underlying language model on how to produce synthetic data in the desired format." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ea6e042e", - "metadata": {}, - "outputs": [], - "source": [ - "OPENAI_TEMPLATE = PromptTemplate(input_variables=[\"example\"], template=\"{example}\")\n", - "\n", - "prompt_template = FewShotPromptTemplate(\n", - " prefix=SYNTHETIC_FEW_SHOT_PREFIX,\n", - " examples=examples,\n", - " suffix=SYNTHETIC_FEW_SHOT_SUFFIX,\n", - " input_variables=[\"subject\", \"extra\"],\n", - " example_prompt=OPENAI_TEMPLATE,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "fa6da3cb", - "metadata": {}, - "source": [ - "The `FewShotPromptTemplate` includes:\n", - "\n", - "- `prefix` and `suffix`: These likely contain guiding context or instructions.\n", - "- `examples`: The sample data we defined earlier.\n", - "- `input_variables`: These variables (\"subject\", \"extra\") are placeholders you can dynamically fill later. For instance, \"subject\" might be filled with \"medical_billing\" to guide the model further.\n", - "- `example_prompt`: This prompt template is the format we want each example row to take in our prompt.\n", - "\n", - "## 4. Creating the Data Generator\n", - "With the schema and the prompt ready, the next step is to create the data generator. This object knows how to communicate with the underlying language model to generate synthetic data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1b9ba911", - "metadata": {}, - "outputs": [], - "source": [ - "synthetic_data_generator = create_openai_data_generator(\n", - " output_schema=MedicalBilling,\n", - " llm=ChatOpenAI(\n", - " temperature=1\n", - " ), # You'll need to replace with your actual Language Model instance\n", - " prompt=prompt_template,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "a4198bd6", - "metadata": {}, - "source": [ - "## 5. Generate Synthetic Data\n", - "Finally, let's generate our synthetic data!" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a424c890", - "metadata": {}, - "outputs": [], - "source": [ - "synthetic_results = synthetic_data_generator.generate(\n", - " subject=\"medical_billing\",\n", - " extra=\"the name must be chosen at random. Make it something you wouldn't normally choose.\",\n", - " runs=10,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "fa4402e9", - "metadata": {}, - "source": [ - "This command asks the generator to produce 10 synthetic medical billing records. The results are stored in `synthetic_results`. The output will be a list of the `MedicalBilling` pydantic model." - ] - }, - { - "cell_type": "markdown", - "id": "53a4cbf9", - "metadata": {}, - "source": [ - "### Other implementations\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9e715d94", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "from langchain_experimental.synthetic_data import (\n", - " DatasetGenerator,\n", - " create_data_generation_chain,\n", - ")\n", - "from langchain_openai import ChatOpenAI" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "94fccedd", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "# LLM\n", - "model = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0.7)\n", - "chain = create_data_generation_chain(model)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "4314c3ea", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'fields': ['blue', 'yellow'],\n", - " 'preferences': {},\n", - " 'text': 'The vibrant blue sky contrasted beautifully with the bright yellow sun, creating a stunning display of colors that instantly lifted the spirits of all who gazed upon it.'}" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chain({\"fields\": [\"blue\", \"yellow\"], \"preferences\": {}})" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "b116c487", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'fields': {'colors': ['blue', 'yellow']},\n", - " 'preferences': {'style': 'Make it in a style of a weather forecast.'},\n", - " 'text': \"Good morning! Today's weather forecast brings a beautiful combination of colors to the sky, with hues of blue and yellow gently blending together like a mesmerizing painting.\"}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chain(\n", - " {\n", - " \"fields\": {\"colors\": [\"blue\", \"yellow\"]},\n", - " \"preferences\": {\"style\": \"Make it in a style of a weather forecast.\"},\n", - " }\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "ff823394", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'fields': {'actor': 'Tom Hanks', 'movies': ['Forrest Gump', 'Green Mile']},\n", - " 'preferences': None,\n", - " 'text': 'Tom Hanks, the renowned actor known for his incredible versatility and charm, has graced the silver screen in unforgettable movies such as \"Forrest Gump\" and \"Green Mile\".'}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chain(\n", - " {\n", - " \"fields\": {\"actor\": \"Tom Hanks\", \"movies\": [\"Forrest Gump\", \"Green Mile\"]},\n", - " \"preferences\": None,\n", - " }\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "1ea1ad5b", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'fields': [{'actor': 'Tom Hanks', 'movies': ['Forrest Gump', 'Green Mile']},\n", - " {'actor': 'Mads Mikkelsen', 'movies': ['Hannibal', 'Another round']}],\n", - " 'preferences': {'minimum_length': 200, 'style': 'gossip'},\n", - " 'text': 'Did you know that Tom Hanks, the beloved Hollywood actor known for his roles in \"Forrest Gump\" and \"Green Mile\", has shared the screen with the talented Mads Mikkelsen, who gained international acclaim for his performances in \"Hannibal\" and \"Another round\"? These two incredible actors have brought their exceptional skills and captivating charisma to the big screen, delivering unforgettable performances that have enthralled audiences around the world. Whether it\\'s Hanks\\' endearing portrayal of Forrest Gump or Mikkelsen\\'s chilling depiction of Hannibal Lecter, these movies have solidified their places in cinematic history, leaving a lasting impact on viewers and cementing their status as true icons of the silver screen.'}" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chain(\n", - " {\n", - " \"fields\": [\n", - " {\"actor\": \"Tom Hanks\", \"movies\": [\"Forrest Gump\", \"Green Mile\"]},\n", - " {\"actor\": \"Mads Mikkelsen\", \"movies\": [\"Hannibal\", \"Another round\"]},\n", - " ],\n", - " \"preferences\": {\"minimum_length\": 200, \"style\": \"gossip\"},\n", - " }\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "93c7a4bb", - "metadata": {}, - "source": [ - "As we can see, the created examples are diversified and possess information we wanted them to have. Also, their style reflects our given preferences quite well." - ] - }, - { - "cell_type": "markdown", - "id": "75f7f55a", - "metadata": {}, - "source": [ - "## Generating exemplary dataset for extraction benchmarking purposes" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "94e98bc4", - "metadata": {}, - "outputs": [], - "source": [ - "inp = [\n", - " {\n", - " \"Actor\": \"Tom Hanks\",\n", - " \"Film\": [\n", - " \"Forrest Gump\",\n", - " \"Saving Private Ryan\",\n", - " \"The Green Mile\",\n", - " \"Toy Story\",\n", - " \"Catch Me If You Can\",\n", - " ],\n", - " },\n", - " {\n", - " \"Actor\": \"Tom Hardy\",\n", - " \"Film\": [\n", - " \"Inception\",\n", - " \"The Dark Knight Rises\",\n", - " \"Mad Max: Fury Road\",\n", - " \"The Revenant\",\n", - " \"Dunkirk\",\n", - " ],\n", - " },\n", - "]\n", - "\n", - "generator = DatasetGenerator(model, {\"style\": \"informal\", \"minimal length\": 500})\n", - "dataset = generator(inp)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "478eaca4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[{'fields': {'Actor': 'Tom Hanks',\n", - " 'Film': ['Forrest Gump',\n", - " 'Saving Private Ryan',\n", - " 'The Green Mile',\n", - " 'Toy Story',\n", - " 'Catch Me If You Can']},\n", - " 'preferences': {'style': 'informal', 'minimal length': 500},\n", - " 'text': 'Tom Hanks, the versatile and charismatic actor, has graced the silver screen in numerous iconic films including the heartwarming and inspirational \"Forrest Gump,\" the intense and gripping war drama \"Saving Private Ryan,\" the emotionally charged and thought-provoking \"The Green Mile,\" the beloved animated classic \"Toy Story,\" and the thrilling and captivating true story adaptation \"Catch Me If You Can.\" With his impressive range and genuine talent, Hanks continues to captivate audiences worldwide, leaving an indelible mark on the world of cinema.'},\n", - " {'fields': {'Actor': 'Tom Hardy',\n", - " 'Film': ['Inception',\n", - " 'The Dark Knight Rises',\n", - " 'Mad Max: Fury Road',\n", - " 'The Revenant',\n", - " 'Dunkirk']},\n", - " 'preferences': {'style': 'informal', 'minimal length': 500},\n", - " 'text': 'Tom Hardy, the versatile actor known for his intense performances, has graced the silver screen in numerous iconic films, including \"Inception,\" \"The Dark Knight Rises,\" \"Mad Max: Fury Road,\" \"The Revenant,\" and \"Dunkirk.\" Whether he\\'s delving into the depths of the subconscious mind, donning the mask of the infamous Bane, or navigating the treacherous wasteland as the enigmatic Max Rockatansky, Hardy\\'s commitment to his craft is always evident. From his breathtaking portrayal of the ruthless Eames in \"Inception\" to his captivating transformation into the ferocious Max in \"Mad Max: Fury Road,\" Hardy\\'s dynamic range and magnetic presence captivate audiences and leave an indelible mark on the world of cinema. In his most physically demanding role to date, he endured the harsh conditions of the freezing wilderness as he portrayed the rugged frontiersman John Fitzgerald in \"The Revenant,\" earning him critical acclaim and an Academy Award nomination. In Christopher Nolan\\'s war epic \"Dunkirk,\" Hardy\\'s stoic and heroic portrayal of Royal Air Force pilot Farrier showcases his ability to convey deep emotion through nuanced performances. With his chameleon-like ability to inhabit a wide range of characters and his unwavering commitment to his craft, Tom Hardy has undoubtedly solidified his place as one of the most talented and sought-after actors of his generation.'}]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dataset" - ] - }, - { - "cell_type": "markdown", - "id": "293a7d64", - "metadata": {}, - "source": [ - "## Extraction from generated examples\n", - "Okay, let's see if we can now extract output from this generated data and how it compares with our case!" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "03c6a375", - "metadata": {}, - "outputs": [], - "source": [ - "from typing import List\n", - "\n", - "from langchain.chains import create_extraction_chain_pydantic\n", - "from langchain_core.output_parsers import PydanticOutputParser\n", - "from langchain_core.prompts import PromptTemplate\n", - "from langchain_openai import OpenAI\n", - "from pydantic import BaseModel, Field" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "9461d225", - "metadata": {}, - "outputs": [], - "source": [ - "class Actor(BaseModel):\n", - " Actor: str = Field(description=\"name of an actor\")\n", - " Film: List[str] = Field(description=\"list of names of films they starred in\")" - ] - }, - { - "cell_type": "markdown", - "id": "8390171d", - "metadata": {}, - "source": [ - "### Parsers" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "8a5528d2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Actor(Actor='Tom Hanks', Film=['Forrest Gump', 'Saving Private Ryan', 'The Green Mile', 'Toy Story', 'Catch Me If You Can'])" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "llm = OpenAI()\n", - "parser = PydanticOutputParser(pydantic_object=Actor)\n", - "\n", - "prompt = PromptTemplate(\n", - " template=\"Extract fields from a given text.\\n{format_instructions}\\n{text}\\n\",\n", - " input_variables=[\"text\"],\n", - " partial_variables={\"format_instructions\": parser.get_format_instructions()},\n", - ")\n", - "\n", - "_input = prompt.format_prompt(text=dataset[0][\"text\"])\n", - "output = llm(_input.to_string())\n", - "\n", - "parsed = parser.parse(output)\n", - "parsed" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "926a7eed", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(parsed.Actor == inp[0][\"Actor\"]) & (parsed.Film == inp[0][\"Film\"])" - ] - }, - { - "cell_type": "markdown", - "id": "b00f0b87", - "metadata": {}, - "source": [ - "### Extractors" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "523bb584", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[Actor(Actor='Tom Hardy', Film=['Inception', 'The Dark Knight Rises', 'Mad Max: Fury Road', 'The Revenant', 'Dunkirk'])]" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "extractor = create_extraction_chain_pydantic(pydantic_schema=Actor, llm=model)\n", - "extracted = extractor.run(dataset[1][\"text\"])\n", - "extracted" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "f8451c2b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(extracted[0].Actor == inp[1][\"Actor\"]) & (extracted[0].Film == inp[1][\"Film\"])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0b03de4d", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.4" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/docs/tutorials/extraction.ipynb b/docs/docs/tutorials/extraction.ipynb index 9a278c383818e..981aa42eeb8ac 100644 --- a/docs/docs/tutorials/extraction.ipynb +++ b/docs/docs/tutorials/extraction.ipynb @@ -17,20 +17,10 @@ "source": [ "# Build an Extraction Chain\n", "\n", - ":::info Prerequisites\n", - "\n", - "This guide assumes familiarity with the following concepts:\n", - "\n", - "- [Chat Models](/docs/concepts/chat_models)\n", - "- [Tools](/docs/concepts/tools)\n", - "- [Tool calling](/docs/concepts/tool_calling)\n", - "\n", - ":::\n", - "\n", - "In this tutorial, we will build a chain to extract structured information from unstructured text. \n", + "In this tutorial, we will use [tool-calling](/docs/concepts/tool_calling) features of [chat models](/docs/concepts/chat_models) to extract structured information from unstructured text. We will also demonstrate how to use [few-shot prompting](/docs/concepts/few_shot_prompting/) in this context to improve performance.\n", "\n", ":::important\n", - "This tutorial will only work with models that support **tool calling**\n", + "This tutorial requires `langchain-core>=0.3.20` and will only work with models that support **tool calling**.\n", ":::" ] }, @@ -43,9 +33,7 @@ "\n", "### Jupyter Notebook\n", "\n", - "This guide (and most of the other guides in the documentation) uses [Jupyter notebooks](https://jupyter.org/) and assumes the reader is as well. Jupyter notebooks are perfect for learning how to work with LLM systems because oftentimes things can go wrong (unexpected output, API down, etc) and going through guides in an interactive environment is a great way to better understand them.\n", - "\n", - "This and other tutorials are perhaps most conveniently run in a Jupyter notebook. See [here](https://jupyter.org/install) for instructions on how to install.\n", + "This and other tutorials are perhaps most conveniently run in a [Jupyter notebooks](https://jupyter.org/). Going through guides in an interactive environment is a great way to better understand them. See [here](https://jupyter.org/install) for instructions on how to install.\n", "\n", "### Installation\n", "\n", @@ -57,10 +45,10 @@ "\n", "\n", " \n", - " pip install langchain\n", + " pip install --upgrade langchain-core\n", " \n", " \n", - " conda install langchain -c conda-forge\n", + " conda install langchain-core -c conda-forge\n", " \n", "\n", "\n", @@ -106,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 2, "id": "c141084c-fb94-4093-8d6a-81175d688e40", "metadata": {}, "outputs": [], @@ -157,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 3, "id": "a5e490f6-35ad-455e-8ae4-2bae021583ff", "metadata": {}, "outputs": [], @@ -171,7 +159,7 @@ "# 1) You can add examples into the prompt template to improve extraction quality\n", "# 2) Introduce additional parameters to take context into account (e.g., include metadata\n", "# about the document from which the text was extracted.)\n", - "prompt = ChatPromptTemplate.from_messages(\n", + "prompt_template = ChatPromptTemplate.from_messages(\n", " [\n", " (\n", " \"system\",\n", @@ -195,30 +183,36 @@ "source": [ "We need to use a model that supports function/tool calling.\n", "\n", - "Please review [the documentation](/docs/concepts/tool_calling) for list of some models that can be used with this API." + "Please review [the documentation](/docs/concepts/tool_calling) for all models that can be used with this API.\n", + "\n", + "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "\n", + "" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "04d846a6-d5cb-4009-ac19-61e3aac0177e", + "execution_count": 4, + "id": "77c1311c-5252-41d6-83e6-fdb40b172e47", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/harrisonchase/workplace/langchain/libs/core/langchain_core/_api/beta_decorator.py:87: LangChainBetaWarning: The method `ChatMistralAI.with_structured_output` is in beta. It is actively being worked on, so the API may change.\n", - " warn_beta(\n" - ] - } - ], + "outputs": [], "source": [ - "from langchain_mistralai import ChatMistralAI\n", + "# | output: false\n", + "# | echo: false\n", "\n", - "llm = ChatMistralAI(model=\"mistral-large-latest\", temperature=0)\n", + "from langchain_openai import ChatOpenAI\n", "\n", - "runnable = prompt | llm.with_structured_output(schema=Person)" + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "04d846a6-d5cb-4009-ac19-61e3aac0177e", + "metadata": {}, + "outputs": [], + "source": [ + "structured_llm = llm.with_structured_output(schema=Person)" ] }, { @@ -226,13 +220,13 @@ "id": "23582c0b-00ed-403f-a10e-3aeabf921f12", "metadata": {}, "source": [ - "Let's test it out" + "Let's test it out:" ] }, { "cell_type": "code", "execution_count": 8, - "id": "13165ac8-a1dc-44ce-a6ed-f52b577473e4", + "id": "dd42a935-022f-4860-b9e0-84268f55b22a", "metadata": {}, "outputs": [ { @@ -248,7 +242,8 @@ ], "source": [ "text = \"Alan Smith is 6 feet tall and has blond hair.\"\n", - "runnable.invoke({\"text\": text})" + "prompt = prompt_template.invoke({\"text\": text})\n", + "structured_llm.invoke(prompt)" ] }, { @@ -264,7 +259,7 @@ "even though it was provided in feet!\n", ":::\n", "\n", - "We can see the LangSmith trace here: https://smith.langchain.com/public/44b69a63-3b3b-47b8-8a6d-61b46533f015/r" + "We can see the LangSmith trace [here](https://smith.langchain.com/public/44b69a63-3b3b-47b8-8a6d-61b46533f015/r). Note that the [chat model portion of the trace](https://smith.langchain.com/public/44b69a63-3b3b-47b8-8a6d-61b46533f015/r/dd1f6305-f1e9-4919-bd8f-339d03a12d01) reveals the exact sequence of messages sent to the model, tools invoked, and other metadata." ] }, { @@ -324,20 +319,20 @@ "metadata": {}, "source": [ ":::important\n", - "Extraction might not be perfect here. Please continue to see how to use **Reference Examples** to improve the quality of extraction, and see the **guidelines** section!\n", + "Extraction results might not be perfect here. Read on to see how to use **Reference Examples** to improve the quality of extraction, and check out our extraction [how-to](/docs/how_to/#extraction) guides for more detail.\n", ":::" ] }, { "cell_type": "code", "execution_count": 10, - "id": "cf7062cc-1d1d-4a37-9122-509d1b87f0a6", + "id": "83ecf0db-757b-4ae3-a9d2-eb1c9f6b2631", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Data(people=[Person(name='Jeff', hair_color=None, height_in_meters=None), Person(name='Anna', hair_color=None, height_in_meters=None)])" + "Data(people=[Person(name='Jeff', hair_color='black', height_in_meters='1.83'), Person(name='Anna', hair_color='black', height_in_meters=None)])" ] }, "execution_count": 10, @@ -346,9 +341,10 @@ } ], "source": [ - "runnable = prompt | llm.with_structured_output(schema=Data)\n", + "structured_llm = llm.with_structured_output(schema=Data)\n", "text = \"My name is Jeff, my hair is black and i am 6 feet tall. Anna has the same color hair as me.\"\n", - "runnable.invoke({\"text\": text})" + "prompt = prompt_template.invoke({\"text\": text})\n", + "structured_llm.invoke(prompt)" ] }, { @@ -363,7 +359,236 @@ "This is usually a **good** thing! It allows specifying **required** attributes on an entity without necessarily forcing the model to detect this entity.\n", ":::\n", "\n", - "We can see the LangSmith trace here: https://smith.langchain.com/public/7173764d-5e76-45fe-8496-84460bd9cdef/r" + "We can see the LangSmith trace [here](https://smith.langchain.com/public/7173764d-5e76-45fe-8496-84460bd9cdef/r)." + ] + }, + { + "cell_type": "markdown", + "id": "c590f366-050a-43d4-8c78-acf84ccfbf9b", + "metadata": {}, + "source": [ + "## Reference examples\n", + "\n", + "The behavior of LLM applications can be steered using [few-shot prompting](/docs/concepts/few_shot_prompting/). For [chat models](/docs/concepts/chat_models/), this can take the form of a sequence of pairs of input and response messages demonstrating desired behaviors.\n", + "\n", + "For example, we can convey the meaning of a symbol with alternating `user` and `assistant` [messages](/docs/concepts/messages/#role):" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "0bb138d7-116e-4542-aa5f-bebf0c301ec6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7\n" + ] + } + ], + "source": [ + "messages = [\n", + " {\"role\": \"user\", \"content\": \"2 🦜 2\"},\n", + " {\"role\": \"assistant\", \"content\": \"4\"},\n", + " {\"role\": \"user\", \"content\": \"2 🦜 3\"},\n", + " {\"role\": \"assistant\", \"content\": \"5\"},\n", + " {\"role\": \"user\", \"content\": \"3 🦜 4\"},\n", + "]\n", + "\n", + "response = llm.invoke(messages)\n", + "print(response.content)" + ] + }, + { + "cell_type": "markdown", + "id": "b5691d07-e2b8-4ab3-a943-9b0b503e2549", + "metadata": {}, + "source": [ + "[Structured output](/docs/concepts/structured_outputs/) often uses [tool calling](/docs/concepts/tool_calling/) under-the-hood. This typically involves the generation of [AI messages](/docs/concepts/messages/#aimessage) containing tool calls, as well as [tool messages](/docs/concepts/messages/#toolmessage) containing the results of tool calls. What should a sequence of messages look like in this case?\n", + "\n", + "Different [chat model providers](/docs/integrations/chat/) impose different requirements for valid message sequences. Some will accept a (repeating) message sequence of the form:\n", + "\n", + "- User message\n", + "- AI message with tool call\n", + "- Tool message with result\n", + "\n", + "Others require a final AI message containing some sort of response.\n", + "\n", + "LangChain includes a utility function [tool_example_to_messages](https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.tool_example_to_messages.html) that will generate a valid sequence for most model providers. It simplifies the generation of structured few-shot examples by just requiring Pydantic representations of the corresponding tool calls.\n", + "\n", + "Let's try this out. We can convert pairs of input strings and desired Pydantic objects to a sequence of messages that can be provided to a chat model. Under the hood, LangChain will format the tool calls to each provider's required format.\n", + "\n", + "Note: this version of `tool_example_to_messages` requires `langchain-core>=0.3.20`." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "c604e476-a2be-4eda-b128-71399e280732", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.utils.function_calling import tool_example_to_messages\n", + "\n", + "examples = [\n", + " (\n", + " \"The ocean is vast and blue. It's more than 20,000 feet deep.\",\n", + " Data(people=[]),\n", + " ),\n", + " (\n", + " \"Fiona traveled far from France to Spain.\",\n", + " Data(people=[Person(name=\"Fiona\", height_in_meters=None, hair_color=None)]),\n", + " ),\n", + "]\n", + "\n", + "\n", + "messages = []\n", + "\n", + "for txt, tool_call in examples:\n", + " if tool_call.people:\n", + " # This final message is optional for some providers\n", + " ai_response = \"Detected people.\"\n", + " else:\n", + " ai_response = \"Detected no people.\"\n", + " messages.extend(tool_example_to_messages(txt, [tool_call], ai_response=ai_response))" + ] + }, + { + "cell_type": "markdown", + "id": "beecc7a6-e423-4ca1-82b7-c2a751362fd6", + "metadata": {}, + "source": [ + "Inspecting the result, we see these two example pairs generated eight messages:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "628f67dd-aee0-4200-ac38-24a9fb16f1d1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "The ocean is vast and blue. It's more than 20,000 feet deep.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " Data (d8f2e054-7fb9-417f-b28f-0447a775b2c3)\n", + " Call ID: d8f2e054-7fb9-417f-b28f-0447a775b2c3\n", + " Args:\n", + " people: []\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "\n", + "You have correctly called this tool.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Detected no people.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Fiona traveled far from France to Spain.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " Data (0178939e-a4b1-4d2a-a93e-b87f665cdfd6)\n", + " Call ID: 0178939e-a4b1-4d2a-a93e-b87f665cdfd6\n", + " Args:\n", + " people: [{'name': 'Fiona', 'hair_color': None, 'height_in_meters': None}]\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "\n", + "You have correctly called this tool.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Detected people.\n" + ] + } + ], + "source": [ + "for message in messages:\n", + " message.pretty_print()" + ] + }, + { + "cell_type": "markdown", + "id": "dc8846f0-8bd1-48e1-bc4d-a62fbfa6a9f4", + "metadata": {}, + "source": [ + "Let's compare performance with and without these messages. For example, let's pass a message for which we intend no people to be extracted:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "6b73d4e2-d18d-4d47-89ec-99b5eb6b234f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Data(people=[Person(name='Earth', hair_color='None', height_in_meters='0.00')])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "message_no_extraction = {\n", + " \"role\": \"user\",\n", + " \"content\": \"The solar system is large, but earth has only 1 moon.\",\n", + "}\n", + "\n", + "structured_llm = llm.with_structured_output(schema=Data)\n", + "structured_llm.invoke([message_no_extraction])" + ] + }, + { + "cell_type": "markdown", + "id": "350e1298-14f1-48e4-b11c-534af643e3a6", + "metadata": {}, + "source": [ + "In this example, the model is liable to erroneously generate records of people.\n", + "\n", + "Because our few-shot examples contain examples of \"negatives\", we encourage the model to behave correctly in this case:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "eb1b3a99-4750-45bc-ad28-5d12751ed9f8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Data(people=[])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "structured_llm.invoke(messages + [message_no_extraction])" + ] + }, + { + "cell_type": "markdown", + "id": "4d1ae320-14bc-45ee-aeeb-8a986f3e6808", + "metadata": {}, + "source": [ + ":::tip\n", + "\n", + "The [LangSmith](https://smith.langchain.com/public/b3433f57-7905-4430-923c-fed214525bf1/r) trace for the run reveals the exact sequence of messages sent to the chat model, tool calls generated, latency, token counts, and other metadata.\n", + "\n", + ":::\n", + "\n", + "See [this guide](/docs/how_to/extraction_examples/) for more detail on extraction workflows with reference examples, including how to incorporate prompt templates and customize the generation of example messages." ] }, { @@ -375,7 +600,7 @@ "\n", "Now that you understand the basics of extraction with LangChain, you're ready to proceed to the rest of the how-to guides:\n", "\n", - "- [Add Examples](/docs/how_to/extraction_examples): Learn how to use **reference examples** to improve performance.\n", + "- [Add Examples](/docs/how_to/extraction_examples): More detail on using **reference examples** to improve performance.\n", "- [Handle Long Text](/docs/how_to/extraction_long_text): What should you do if the text does not fit into the context window of the LLM?\n", "- [Use a Parsing Approach](/docs/how_to/extraction_parse): Use a prompt based approach to extract with models that do not support **tool/function calling**." ] @@ -405,7 +630,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.1" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/graph.ipynb b/docs/docs/tutorials/graph.ipynb index d189d1af21fbe..41960e0186b47 100644 --- a/docs/docs/tutorials/graph.ipynb +++ b/docs/docs/tutorials/graph.ipynb @@ -15,7 +15,7 @@ "source": [ "# Build a Question Answering application over a Graph Database\n", "\n", - "In this guide we'll go over the basic ways to create a Q&A chain over a graph database. These systems will allow us to ask a question about the data in a graph database and get back a natural language answer.\n", + "In this guide we'll go over the basic ways to create a Q&A chain over a graph database. These systems will allow us to ask a question about the data in a graph database and get back a natural language answer. First, we will show a simple out-of-the-box option and then implement a more sophisticated version with LangGraph.\n", "\n", "## ⚠️ Security note ⚠️\n", "\n", @@ -45,7 +45,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install --upgrade --quiet langchain langchain-community langchain-openai neo4j" + "%pip install --upgrade --quiet langchain langchain-neo4j langchain-openai langgraph" ] }, { @@ -57,14 +57,14 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - " ········\n" + "Enter your OpenAI API key: ········\n" ] } ], @@ -90,7 +90,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -108,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -117,13 +117,13 @@ "[]" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from langchain_community.graphs import Neo4jGraph\n", + "from langchain_neo4j import Neo4jGraph\n", "\n", "graph = Neo4jGraph()\n", "\n", @@ -162,19 +162,24 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Node properties are the following:\n", - "Movie {imdbRating: FLOAT, id: STRING, released: DATE, title: STRING},Person {name: STRING},Genre {name: STRING},Chunk {id: STRING, question: STRING, query: STRING, text: STRING, embedding: LIST}\n", - "Relationship properties are the following:\n", + "Node properties:\n", + "Person {name: STRING}\n", + "Movie {id: STRING, released: DATE, title: STRING, imdbRating: FLOAT}\n", + "Genre {name: STRING}\n", + "Chunk {id: STRING, embedding: LIST, text: STRING, question: STRING, query: STRING}\n", + "Relationship properties:\n", "\n", - "The relationships are the following:\n", - "(:Movie)-[:IN_GENRE]->(:Genre),(:Person)-[:DIRECTED]->(:Movie),(:Person)-[:ACTED_IN]->(:Movie)\n" + "The relationships:\n", + "(:Person)-[:DIRECTED]->(:Movie)\n", + "(:Person)-[:ACTED_IN]->(:Movie)\n", + "(:Movie)-[:IN_GENRE]->(:Genre)\n" ] } ], @@ -187,11 +192,65 @@ "cell_type": "markdown", "metadata": {}, "source": [ + "For more involved schema information, you can use `enhanced_schema` option." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.FeatureDeprecationWarning} {category: DEPRECATION} {title: This feature is deprecated and will be removed in future versions.} {description: The procedure has a deprecated field. ('config' used by 'apoc.meta.graphSample' is deprecated.)} {position: line: 1, column: 1, offset: 0} for query: \"CALL apoc.meta.graphSample() YIELD nodes, relationships RETURN nodes, [rel in relationships | {name:apoc.any.property(rel, 'type'), count: apoc.any.property(rel, 'count')}] AS relationships\"\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Node properties:\n", + "- **Person**\n", + " - `name`: STRING Example: \"John Lasseter\"\n", + "- **Movie**\n", + " - `id`: STRING Example: \"1\"\n", + " - `released`: DATE Min: 1964-12-16, Max: 1996-09-15\n", + " - `title`: STRING Example: \"Toy Story\"\n", + " - `imdbRating`: FLOAT Min: 2.4, Max: 9.3\n", + "- **Genre**\n", + " - `name`: STRING Example: \"Adventure\"\n", + "- **Chunk**\n", + " - `id`: STRING Available options: ['d66006059fd78d63f3df90cc1059639a', '0e3dcb4502853979d12357690a95ec17', 'c438c6bcdcf8e4fab227f29f8e7ff204', '97fe701ec38057594464beaa2df0710e', 'b54f9286e684373498c4504b4edd9910', '5b50a72c3a4954b0ff7a0421be4f99b9', 'fb28d41771e717255f0d8f6c799ede32', '58e6f14dd2e6c6702cf333f2335c499c']\n", + " - `text`: STRING Available options: ['How many artists are there?', 'Which actors played in the movie Casino?', 'How many movies has Tom Hanks acted in?', \"List all the genres of the movie Schindler's List\", 'Which actors have worked in movies from both the c', 'Which directors have made movies with at least thr', 'Identify movies where directors also played a role', 'Find the actor with the highest number of movies i']\n", + " - `question`: STRING Available options: ['How many artists are there?', 'Which actors played in the movie Casino?', 'How many movies has Tom Hanks acted in?', \"List all the genres of the movie Schindler's List\", 'Which actors have worked in movies from both the c', 'Which directors have made movies with at least thr', 'Identify movies where directors also played a role', 'Find the actor with the highest number of movies i']\n", + " - `query`: STRING Available options: ['MATCH (a:Person)-[:ACTED_IN]->(:Movie) RETURN coun', \"MATCH (m:Movie {title: 'Casino'})<-[:ACTED_IN]-(a)\", \"MATCH (a:Person {name: 'Tom Hanks'})-[:ACTED_IN]->\", \"MATCH (m:Movie {title: 'Schindler's List'})-[:IN_G\", 'MATCH (a:Person)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]', 'MATCH (d:Person)-[:DIRECTED]->(m:Movie)<-[:ACTED_I', 'MATCH (p:Person)-[:DIRECTED]->(m:Movie), (p)-[:ACT', 'MATCH (a:Actor)-[:ACTED_IN]->(m:Movie) RETURN a.na']\n", + "Relationship properties:\n", + "\n", + "The relationships:\n", + "(:Person)-[:DIRECTED]->(:Movie)\n", + "(:Person)-[:ACTED_IN]->(:Movie)\n", + "(:Movie)-[:IN_GENRE]->(:Genre)\n" + ] + } + ], + "source": [ + "enhanced_graph = Neo4jGraph(enhanced_schema=True)\n", + "print(enhanced_graph.schema)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `enhanced_schema` option enriches property information by including details such as minimum and maximum values for floats and dates, as well as example values for string properties. This additional context helps guide the LLM toward generating more accurate and effective queries.\n", + "\n", "Great! We've got a graph database that we can query. Now let's try hooking it up to an LLM.\n", "\n", - "## Chain\n", + "## GraphQACypherChain\n", "\n", - "Let's use a simple chain that takes a question, turns it into a Cypher query, executes the query, and uses the result to answer the original question.\n", + "Let's use a simple out-of-the-box chain that takes a question, turns it into a Cypher query, executes the query, and uses the result to answer the original question.\n", "\n", "![graph_chain.webp](../../static/img/graph_chain.webp)\n", "\n", @@ -201,7 +260,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -212,10 +271,12 @@ "\n", "\u001b[1m> Entering new GraphCypherQAChain chain...\u001b[0m\n", "Generated Cypher:\n", - "\u001b[32;1m\u001b[1;3mMATCH (:Movie {title: \"Casino\"})<-[:ACTED_IN]-(actor:Person)\n", - "RETURN actor.name\u001b[0m\n", + "\u001b[32;1m\u001b[1;3mcypher\n", + "MATCH (p:Person)-[:ACTED_IN]->(m:Movie {title: \"Casino\"})\n", + "RETURN p.name\n", + "\u001b[0m\n", "Full Context:\n", - "\u001b[32;1m\u001b[1;3m[{'actor.name': 'Joe Pesci'}, {'actor.name': 'Robert De Niro'}, {'actor.name': 'Sharon Stone'}, {'actor.name': 'James Woods'}]\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m[{'p.name': 'Robert De Niro'}, {'p.name': 'Joe Pesci'}, {'p.name': 'Sharon Stone'}, {'p.name': 'James Woods'}]\u001b[0m\n", "\n", "\u001b[1m> Finished chain.\u001b[0m\n" ] @@ -224,20 +285,22 @@ "data": { "text/plain": [ "{'query': 'What was the cast of the Casino?',\n", - " 'result': 'The cast of Casino included Joe Pesci, Robert De Niro, Sharon Stone, and James Woods.'}" + " 'result': 'Robert De Niro, Joe Pesci, Sharon Stone, and James Woods were the cast of Casino.'}" ] }, - "execution_count": 5, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from langchain.chains import GraphCypherQAChain\n", + "from langchain_neo4j import GraphCypherQAChain\n", "from langchain_openai import ChatOpenAI\n", "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n", - "chain = GraphCypherQAChain.from_llm(graph=graph, llm=llm, verbose=True)\n", + "llm = ChatOpenAI(model=\"gpt-4o\", temperature=0)\n", + "chain = GraphCypherQAChain.from_llm(\n", + " graph=enhanced_graph, llm=llm, verbose=True, allow_dangerous_requests=True\n", + ")\n", "response = chain.invoke({\"query\": \"What was the cast of the Casino?\"})\n", "response" ] @@ -246,50 +309,754 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Validating relationship direction\n", + "## Advanced implementation with LangGraph\n", "\n", - "LLMs can struggle with relationship directions in generated Cypher statement. Since the graph schema is predefined, we can validate and optionally correct relationship directions in the generated Cypher statements by using the `validate_cypher` parameter." + "While the GraphCypherQAChain is effective for quick demonstrations, it may face challenges in production environments. Transitioning to LangGraph can enhance the workflow, but implementing natural language to query flows in production remains a complex task. Nevertheless, there are several strategies to significantly improve accuracy and reliability, which we will explore next.\n", + "\n", + "Here is the visualized LangGraph flow we will implement:\n", + "\n", + "![langgraph_text2cypher](../../static/img/langgraph_text2cypher.webp)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will begin by defining the Input, Output, and Overall state of the LangGraph application." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "from operator import add\n", + "from typing import Annotated, List\n", + "\n", + "from typing_extensions import TypedDict\n", + "\n", + "\n", + "class InputState(TypedDict):\n", + " question: str\n", + "\n", + "\n", + "class OverallState(TypedDict):\n", + " question: str\n", + " next_action: str\n", + " cypher_statement: str\n", + " cypher_errors: List[str]\n", + " database_records: List[dict]\n", + " steps: Annotated[List[str], add]\n", + "\n", + "\n", + "class OutputState(TypedDict):\n", + " answer: str\n", + " steps: List[str]\n", + " cypher_statement: str" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The first step is a simple `guardrails` step, where we validate whether the question pertains to movies or their cast. If it doesn't, we notify the user that we cannot answer any other questions. Otherwise, we move on to the Cypher generation step." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from typing import Literal\n", + "\n", + "from langchain_core.prompts import ChatPromptTemplate\n", + "from pydantic import BaseModel, Field\n", + "\n", + "guardrails_system = \"\"\"\n", + "As an intelligent assistant, your primary objective is to decide whether a given question is related to movies or not. \n", + "If the question is related to movies, output \"movie\". Otherwise, output \"end\".\n", + "To make this decision, assess the content of the question and determine if it refers to any movie, actor, director, film industry, \n", + "or related topics. Provide only the specified output: \"movie\" or \"end\".\n", + "\"\"\"\n", + "guardrails_prompt = ChatPromptTemplate.from_messages(\n", + " [\n", + " (\n", + " \"system\",\n", + " guardrails_system,\n", + " ),\n", + " (\n", + " \"human\",\n", + " (\"{question}\"),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "\n", + "class GuardrailsOutput(BaseModel):\n", + " decision: Literal[\"movie\", \"end\"] = Field(\n", + " description=\"Decision on whether the question is related to movies\"\n", + " )\n", + "\n", + "\n", + "guardrails_chain = guardrails_prompt | llm.with_structured_output(GuardrailsOutput)\n", + "\n", + "\n", + "def guardrails(state: InputState) -> OverallState:\n", + " \"\"\"\n", + " Decides if the question is related to movies or not.\n", + " \"\"\"\n", + " guardrails_output = guardrails_chain.invoke({\"question\": state.get(\"question\")})\n", + " database_records = None\n", + " if guardrails_output.decision == \"end\":\n", + " database_records = \"This questions is not about movies or their cast. Therefore I cannot answer this question.\"\n", + " return {\n", + " \"next_action\": guardrails_output.decision,\n", + " \"database_records\": database_records,\n", + " \"steps\": [\"guardrail\"],\n", + " }" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Few-shot prompting" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Converting natural language into accurate queries is challenging. One way to enhance this process is by providing relevant few-shot examples to guide the LLM in query generation. To achieve this, we will use the `SemanticSimilarityExampleSelector` to dynamically select the most relevant examples." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.example_selectors import SemanticSimilarityExampleSelector\n", + "from langchain_neo4j import Neo4jVector\n", + "from langchain_openai import OpenAIEmbeddings\n", + "\n", + "examples = [\n", + " {\n", + " \"question\": \"How many artists are there?\",\n", + " \"query\": \"MATCH (a:Person)-[:ACTED_IN]->(:Movie) RETURN count(DISTINCT a)\",\n", + " },\n", + " {\n", + " \"question\": \"Which actors played in the movie Casino?\",\n", + " \"query\": \"MATCH (m:Movie {title: 'Casino'})<-[:ACTED_IN]-(a) RETURN a.name\",\n", + " },\n", + " {\n", + " \"question\": \"How many movies has Tom Hanks acted in?\",\n", + " \"query\": \"MATCH (a:Person {name: 'Tom Hanks'})-[:ACTED_IN]->(m:Movie) RETURN count(m)\",\n", + " },\n", + " {\n", + " \"question\": \"List all the genres of the movie Schindler's List\",\n", + " \"query\": \"MATCH (m:Movie {title: 'Schindler's List'})-[:IN_GENRE]->(g:Genre) RETURN g.name\",\n", + " },\n", + " {\n", + " \"question\": \"Which actors have worked in movies from both the comedy and action genres?\",\n", + " \"query\": \"MATCH (a:Person)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g1:Genre), (a)-[:ACTED_IN]->(:Movie)-[:IN_GENRE]->(g2:Genre) WHERE g1.name = 'Comedy' AND g2.name = 'Action' RETURN DISTINCT a.name\",\n", + " },\n", + " {\n", + " \"question\": \"Which directors have made movies with at least three different actors named 'John'?\",\n", + " \"query\": \"MATCH (d:Person)-[:DIRECTED]->(m:Movie)<-[:ACTED_IN]-(a:Person) WHERE a.name STARTS WITH 'John' WITH d, COUNT(DISTINCT a) AS JohnsCount WHERE JohnsCount >= 3 RETURN d.name\",\n", + " },\n", + " {\n", + " \"question\": \"Identify movies where directors also played a role in the film.\",\n", + " \"query\": \"MATCH (p:Person)-[:DIRECTED]->(m:Movie), (p)-[:ACTED_IN]->(m) RETURN m.title, p.name\",\n", + " },\n", + " {\n", + " \"question\": \"Find the actor with the highest number of movies in the database.\",\n", + " \"query\": \"MATCH (a:Actor)-[:ACTED_IN]->(m:Movie) RETURN a.name, COUNT(m) AS movieCount ORDER BY movieCount DESC LIMIT 1\",\n", + " },\n", + "]\n", + "\n", + "example_selector = SemanticSimilarityExampleSelector.from_examples(\n", + " examples, OpenAIEmbeddings(), Neo4jVector, k=5, input_keys=[\"question\"]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we implement the Cypher generation chain, also known as **text2cypher**. The prompt includes an enhanced graph schema, dynamically selected few-shot examples, and the user’s question. This combination enables the generation of a Cypher query to retrieve relevant information from the database." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.output_parsers import StrOutputParser\n", + "\n", + "text2cypher_prompt = ChatPromptTemplate.from_messages(\n", + " [\n", + " (\n", + " \"system\",\n", + " (\n", + " \"Given an input question, convert it to a Cypher query. No pre-amble.\"\n", + " \"Do not wrap the response in any backticks or anything else. Respond with a Cypher statement only!\"\n", + " ),\n", + " ),\n", + " (\n", + " \"human\",\n", + " (\n", + " \"\"\"You are a Neo4j expert. Given an input question, create a syntactically correct Cypher query to run.\n", + "Do not wrap the response in any backticks or anything else. Respond with a Cypher statement only!\n", + "Here is the schema information\n", + "{schema}\n", + "\n", + "Below are a number of examples of questions and their corresponding Cypher queries.\n", + "\n", + "{fewshot_examples}\n", + "\n", + "User input: {question}\n", + "Cypher query:\"\"\"\n", + " ),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "text2cypher_chain = text2cypher_prompt | llm | StrOutputParser()\n", + "\n", + "\n", + "def generate_cypher(state: OverallState) -> OverallState:\n", + " \"\"\"\n", + " Generates a cypher statement based on the provided schema and user input\n", + " \"\"\"\n", + " NL = \"\\n\"\n", + " fewshot_examples = (NL * 2).join(\n", + " [\n", + " f\"Question: {el['question']}{NL}Cypher:{el['query']}\"\n", + " for el in example_selector.select_examples(\n", + " {\"question\": state.get(\"question\")}\n", + " )\n", + " ]\n", + " )\n", + " generated_cypher = text2cypher_chain.invoke(\n", + " {\n", + " \"question\": state.get(\"question\"),\n", + " \"fewshot_examples\": fewshot_examples,\n", + " \"schema\": enhanced_graph.schema,\n", + " }\n", + " )\n", + " return {\"cypher_statement\": generated_cypher, \"steps\": [\"generate_cypher\"]}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Query validation\n", + "\n", + "The next step is to validate the generated Cypher statement and ensuring that all property values are accurate. While numbers and dates typically don’t require validation, strings such as movie titles or people’s names do. In this example, we’ll use a basic `CONTAINS` clause for validation, though more advanced mapping and validation techniques can be implemented if needed.\n", + "\n", + "First, we will create a chain that detects any errors in the Cypher statement and extracts the property values it references." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "from typing import List, Optional\n", + "\n", + "validate_cypher_system = \"\"\"\n", + "You are a Cypher expert reviewing a statement written by a junior developer.\n", + "\"\"\"\n", + "\n", + "validate_cypher_user = \"\"\"You must check the following:\n", + "* Are there any syntax errors in the Cypher statement?\n", + "* Are there any missing or undefined variables in the Cypher statement?\n", + "* Are any node labels missing from the schema?\n", + "* Are any relationship types missing from the schema?\n", + "* Are any of the properties not included in the schema?\n", + "* Does the Cypher statement include enough information to answer the question?\n", + "\n", + "Examples of good errors:\n", + "* Label (:Foo) does not exist, did you mean (:Bar)?\n", + "* Property bar does not exist for label Foo, did you mean baz?\n", + "* Relationship FOO does not exist, did you mean FOO_BAR?\n", + "\n", + "Schema:\n", + "{schema}\n", + "\n", + "The question is:\n", + "{question}\n", + "\n", + "The Cypher statement is:\n", + "{cypher}\n", + "\n", + "Make sure you don't make any mistakes!\"\"\"\n", + "\n", + "validate_cypher_prompt = ChatPromptTemplate.from_messages(\n", + " [\n", + " (\n", + " \"system\",\n", + " validate_cypher_system,\n", + " ),\n", + " (\n", + " \"human\",\n", + " (validate_cypher_user),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "\n", + "class Property(BaseModel):\n", + " \"\"\"\n", + " Represents a filter condition based on a specific node property in a graph in a Cypher statement.\n", + " \"\"\"\n", + "\n", + " node_label: str = Field(\n", + " description=\"The label of the node to which this property belongs.\"\n", + " )\n", + " property_key: str = Field(description=\"The key of the property being filtered.\")\n", + " property_value: str = Field(\n", + " description=\"The value that the property is being matched against.\"\n", + " )\n", + "\n", + "\n", + "class ValidateCypherOutput(BaseModel):\n", + " \"\"\"\n", + " Represents the validation result of a Cypher query's output,\n", + " including any errors and applied filters.\n", + " \"\"\"\n", + "\n", + " errors: Optional[List[str]] = Field(\n", + " description=\"A list of syntax or semantical errors in the Cypher statement. Always explain the discrepancy between schema and Cypher statement\"\n", + " )\n", + " filters: Optional[List[Property]] = Field(\n", + " description=\"A list of property-based filters applied in the Cypher statement.\"\n", + " )\n", + "\n", + "\n", + "validate_cypher_chain = validate_cypher_prompt | llm.with_structured_output(\n", + " ValidateCypherOutput\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "LLMs often struggle with correctly determining relationship directions in generated Cypher statements. Since we have access to the schema, we can deterministically correct these directions using the **CypherQueryCorrector**. \n", + "\n", + "*Note: The `CypherQueryCorrector` is an experimental feature and doesn't support all the newest Cypher syntax.*" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_neo4j.chains.graph_qa.cypher_utils import CypherQueryCorrector, Schema\n", + "\n", + "# Cypher query corrector is experimental\n", + "corrector_schema = [\n", + " Schema(el[\"start\"], el[\"type\"], el[\"end\"])\n", + " for el in enhanced_graph.structured_schema.get(\"relationships\")\n", + "]\n", + "cypher_query_corrector = CypherQueryCorrector(corrector_schema)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we can implement the Cypher validation step. First, we use the `EXPLAIN` method to detect any syntax errors. Next, we leverage the LLM to identify potential issues and extract the properties used for filtering. For string properties, we validate them against the database using a simple `CONTAINS` clause.\n", + "\n", + "Based on the validation results, the process can take the following paths:\n", + "\n", + "- If value mapping fails, we end the conversation and inform the user that we couldn't identify a specific property value (e.g., a person or movie title). \n", + "- If errors are found, we route the query for correction. \n", + "- If no issues are detected, we proceed to the Cypher execution step. " + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from neo4j.exceptions import CypherSyntaxError\n", + "\n", + "\n", + "def validate_cypher(state: OverallState) -> OverallState:\n", + " \"\"\"\n", + " Validates the Cypher statements and maps any property values to the database.\n", + " \"\"\"\n", + " errors = []\n", + " mapping_errors = []\n", + " # Check for syntax errors\n", + " try:\n", + " enhanced_graph.query(f\"EXPLAIN {state.get('cypher_statement')}\")\n", + " except CypherSyntaxError as e:\n", + " errors.append(e.message)\n", + " # Experimental feature for correcting relationship directions\n", + " corrected_cypher = cypher_query_corrector(state.get(\"cypher_statement\"))\n", + " if not corrected_cypher:\n", + " errors.append(\"The generated Cypher statement doesn't fit the graph schema\")\n", + " if not corrected_cypher == state.get(\"cypher_statement\"):\n", + " print(\"Relationship direction was corrected\")\n", + " # Use LLM to find additional potential errors and get the mapping for values\n", + " llm_output = validate_cypher_chain.invoke(\n", + " {\n", + " \"question\": state.get(\"question\"),\n", + " \"schema\": enhanced_graph.schema,\n", + " \"cypher\": state.get(\"cypher_statement\"),\n", + " }\n", + " )\n", + " if llm_output.errors:\n", + " errors.extend(llm_output.errors)\n", + " if llm_output.filters:\n", + " for filter in llm_output.filters:\n", + " # Do mapping only for string values\n", + " if (\n", + " not [\n", + " prop\n", + " for prop in enhanced_graph.structured_schema[\"node_props\"][\n", + " filter.node_label\n", + " ]\n", + " if prop[\"property\"] == filter.property_key\n", + " ][0][\"type\"]\n", + " == \"STRING\"\n", + " ):\n", + " pass\n", + " mapping = enhanced_graph.query(\n", + " f\"MATCH (n:{filter.node_label}) WHERE toLower(n.`{filter.property_key}`) = toLower($value) RETURN 'yes' LIMIT 1\",\n", + " {\"value\": filter.property_value},\n", + " )\n", + " if not mapping:\n", + " print(\n", + " f\"Missing value mapping for {filter.node_label} on property {filter.property_key} with value {filter.property_value}\"\n", + " )\n", + " mapping_errors.append(\n", + " f\"Missing value mapping for {filter.node_label} on property {filter.property_key} with value {filter.property_value}\"\n", + " )\n", + " if mapping_errors:\n", + " next_action = \"end\"\n", + " elif errors:\n", + " next_action = \"correct_cypher\"\n", + " else:\n", + " next_action = \"execute_cypher\"\n", + "\n", + " return {\n", + " \"next_action\": next_action,\n", + " \"cypher_statement\": corrected_cypher,\n", + " \"cypher_errors\": errors,\n", + " \"steps\": [\"validate_cypher\"],\n", + " }" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The Cypher correction step takes the existing Cypher statement, any identified errors, and the original question to generate a corrected version of the query." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "correct_cypher_prompt = ChatPromptTemplate.from_messages(\n", + " [\n", + " (\n", + " \"system\",\n", + " (\n", + " \"You are a Cypher expert reviewing a statement written by a junior developer. \"\n", + " \"You need to correct the Cypher statement based on the provided errors. No pre-amble.\"\n", + " \"Do not wrap the response in any backticks or anything else. Respond with a Cypher statement only!\"\n", + " ),\n", + " ),\n", + " (\n", + " \"human\",\n", + " (\n", + " \"\"\"Check for invalid syntax or semantics and return a corrected Cypher statement.\n", + "\n", + "Schema:\n", + "{schema}\n", + "\n", + "Note: Do not include any explanations or apologies in your responses.\n", + "Do not wrap the response in any backticks or anything else.\n", + "Respond with a Cypher statement only!\n", + "\n", + "Do not respond to any questions that might ask anything else than for you to construct a Cypher statement.\n", + "\n", + "The question is:\n", + "{question}\n", + "\n", + "The Cypher statement is:\n", + "{cypher}\n", + "\n", + "The errors are:\n", + "{errors}\n", + "\n", + "Corrected Cypher statement: \"\"\"\n", + " ),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "correct_cypher_chain = correct_cypher_prompt | llm | StrOutputParser()\n", + "\n", + "\n", + "def correct_cypher(state: OverallState) -> OverallState:\n", + " \"\"\"\n", + " Correct the Cypher statement based on the provided errors.\n", + " \"\"\"\n", + " corrected_cypher = correct_cypher_chain.invoke(\n", + " {\n", + " \"question\": state.get(\"question\"),\n", + " \"errors\": state.get(\"cypher_errors\"),\n", + " \"cypher\": state.get(\"cypher_statement\"),\n", + " \"schema\": enhanced_graph.schema,\n", + " }\n", + " )\n", + "\n", + " return {\n", + " \"next_action\": \"validate_cypher\",\n", + " \"cypher_statement\": corrected_cypher,\n", + " \"steps\": [\"correct_cypher\"],\n", + " }" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We need to add a step that executes the given Cypher statement. If no results are returned, we should explicitly handle this scenario, as leaving the context empty can sometimes lead to LLM hallucinations." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "no_results = \"I couldn't find any relevant information in the database\"\n", + "\n", + "\n", + "def execute_cypher(state: OverallState) -> OverallState:\n", + " \"\"\"\n", + " Executes the given Cypher statement.\n", + " \"\"\"\n", + "\n", + " records = enhanced_graph.query(state.get(\"cypher_statement\"))\n", + " return {\n", + " \"database_records\": records if records else no_results,\n", + " \"next_action\": \"end\",\n", + " \"steps\": [\"execute_cypher\"],\n", + " }" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The final step is to generate the answer. This involves combining the initial question with the database output to produce a relevant response." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "generate_final_prompt = ChatPromptTemplate.from_messages(\n", + " [\n", + " (\n", + " \"system\",\n", + " \"You are a helpful assistant\",\n", + " ),\n", + " (\n", + " \"human\",\n", + " (\n", + " \"\"\"Use the following results retrieved from a database to provide\n", + "a succinct, definitive answer to the user's question.\n", + "\n", + "Respond as if you are answering the question directly.\n", + "\n", + "Results: {results}\n", + "Question: {question}\"\"\"\n", + " ),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "generate_final_chain = generate_final_prompt | llm | StrOutputParser()\n", + "\n", + "\n", + "def generate_final_answer(state: OverallState) -> OutputState:\n", + " \"\"\"\n", + " Decides if the question is related to movies.\n", + " \"\"\"\n", + " final_answer = generate_final_chain.invoke(\n", + " {\"question\": state.get(\"question\"), \"results\": state.get(\"database_records\")}\n", + " )\n", + " return {\"answer\": final_answer, \"steps\": [\"generate_final_answer\"]}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we will implement the LangGraph workflow, starting with defining the conditional edge functions." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "def guardrails_condition(\n", + " state: OverallState,\n", + ") -> Literal[\"generate_cypher\", \"generate_final_answer\"]:\n", + " if state.get(\"next_action\") == \"end\":\n", + " return \"generate_final_answer\"\n", + " elif state.get(\"next_action\") == \"movie\":\n", + " return \"generate_cypher\"\n", + "\n", + "\n", + "def validate_cypher_condition(\n", + " state: OverallState,\n", + ") -> Literal[\"generate_final_answer\", \"correct_cypher\", \"execute_cypher\"]:\n", + " if state.get(\"next_action\") == \"end\":\n", + " return \"generate_final_answer\"\n", + " elif state.get(\"next_action\") == \"correct_cypher\":\n", + " return \"correct_cypher\"\n", + " elif state.get(\"next_action\") == \"execute_cypher\":\n", + " return \"execute_cypher\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's put it all together now." + ] + }, + { + "cell_type": "code", + "execution_count": 19, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "\n", - "\u001b[1m> Entering new GraphCypherQAChain chain...\u001b[0m\n", - "Generated Cypher:\n", - "\u001b[32;1m\u001b[1;3mMATCH (:Movie {title: \"Casino\"})<-[:ACTED_IN]-(actor:Person)\n", - "RETURN actor.name\u001b[0m\n", - "Full Context:\n", - "\u001b[32;1m\u001b[1;3m[{'actor.name': 'Joe Pesci'}, {'actor.name': 'Robert De Niro'}, {'actor.name': 'Sharon Stone'}, {'actor.name': 'James Woods'}]\u001b[0m\n", - "\n", - "\u001b[1m> Finished chain.\u001b[0m\n" - ] - }, + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import Image, display\n", + "from langgraph.graph import END, START, StateGraph\n", + "\n", + "langgraph = StateGraph(OverallState, input=InputState, output=OutputState)\n", + "langgraph.add_node(guardrails)\n", + "langgraph.add_node(generate_cypher)\n", + "langgraph.add_node(validate_cypher)\n", + "langgraph.add_node(correct_cypher)\n", + "langgraph.add_node(execute_cypher)\n", + "langgraph.add_node(generate_final_answer)\n", + "\n", + "langgraph.add_edge(START, \"guardrails\")\n", + "langgraph.add_conditional_edges(\n", + " \"guardrails\",\n", + " guardrails_condition,\n", + ")\n", + "langgraph.add_edge(\"generate_cypher\", \"validate_cypher\")\n", + "langgraph.add_conditional_edges(\n", + " \"validate_cypher\",\n", + " validate_cypher_condition,\n", + ")\n", + "langgraph.add_edge(\"execute_cypher\", \"generate_final_answer\")\n", + "langgraph.add_edge(\"correct_cypher\", \"validate_cypher\")\n", + "langgraph.add_edge(\"generate_final_answer\", END)\n", + "\n", + "langgraph = langgraph.compile()\n", + "\n", + "# View\n", + "display(Image(langgraph.get_graph().draw_mermaid_png()))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can now test the application by asking an irrelevant question." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ { "data": { "text/plain": [ - "{'query': 'What was the cast of the Casino?',\n", - " 'result': 'The cast of Casino included Joe Pesci, Robert De Niro, Sharon Stone, and James Woods.'}" + "{'answer': \"I'm sorry, but I cannot provide current weather information. Please check a reliable weather website or app for the latest updates on the weather in Spain.\",\n", + " 'steps': ['guardrail', 'generate_final_answer']}" ] }, - "execution_count": 6, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "chain = GraphCypherQAChain.from_llm(\n", - " graph=graph, llm=llm, verbose=True, validate_cypher=True\n", - ")\n", - "response = chain.invoke({\"query\": \"What was the cast of the Casino?\"})\n", - "response" + "langgraph.invoke({\"question\": \"What's the weather in Spain?\"})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's now ask something relevant about the movies." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'answer': 'The cast of \"Casino\" includes Robert De Niro, Joe Pesci, Sharon Stone, and James Woods.',\n", + " 'steps': ['guardrail',\n", + " 'generate_cypher',\n", + " 'validate_cypher',\n", + " 'execute_cypher',\n", + " 'generate_final_answer'],\n", + " 'cypher_statement': \"MATCH (m:Movie {title: 'Casino'})<-[:ACTED_IN]-(a:Person) RETURN a.name\"}" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "langgraph.invoke({\"question\": \"What was the cast of the Casino?\"})" ] }, { @@ -298,10 +1065,8 @@ "source": [ "### Next steps\n", "\n", - "For more complex query-generation, we may want to create few-shot prompts or add query-checking steps. For advanced techniques like this and more check out:\n", + "For other graph techniques like this and more check out:\n", "\n", - "* [Prompting strategies](/docs/how_to/graph_prompting): Advanced prompt engineering techniques.\n", - "* [Mapping values](/docs/how_to/graph_mapping): Techniques for mapping values from questions to database.\n", "* [Semantic layer](/docs/how_to/graph_semantic): Techniques for implementing semantic layers.\n", "* [Constructing graphs](/docs/how_to/graph_constructing): Techniques for constructing knowledge graphs." ] @@ -330,7 +1095,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.4" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/index.mdx b/docs/docs/tutorials/index.mdx index 7cf4af7e2db56..25486c45e8fc4 100644 --- a/docs/docs/tutorials/index.mdx +++ b/docs/docs/tutorials/index.mdx @@ -6,41 +6,31 @@ sidebar_class_name: hidden New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications. +## Get started + +Familiarize yourself with LangChain's open-source components by building simple applications. + If you're looking to get started with [chat models](/docs/integrations/chat/), [vector stores](/docs/integrations/vectorstores/), or other LangChain components from a specific provider, check out our supported [integrations](/docs/integrations/providers/). -Refer to the [how-to guides](/docs/how_to) for more detail on using common LangChain components. +- [Chat models and prompts](/docs/tutorials/llm_chain): Build a simple LLM application with [prompt templates](/docs/concepts/prompt_templates) and [chat models](/docs/concepts/chat_models). +- [Semantic search](/docs/tutorials/retrievers): Build a semantic search engine over a PDF with [document loaders](/docs/concepts/document_loaders), [embedding models](/docs/concepts/embedding_models/), and [vector stores](/docs/concepts/vectorstores/). +- [Classification](/docs/tutorials/classification): Classify text into categories or labels using [chat models](/docs/concepts/chat_models) with [structured outputs](/docs/concepts/structured_outputs/). +- [Extraction](/docs/tutorials/extraction): Extract structured data from text and other unstructured media using [chat models](/docs/concepts/chat_models) and [few-shot examples](/docs/concepts/few_shot_prompting/). + +Refer to the [how-to guides](/docs/how_to) for more detail on using all LangChain components. + +## Orchestration -See the [conceptual documentation](/docs/concepts) for high level explanations of all LangChain concepts. +Get started using [LangGraph](https://langchain-ai.github.io/langgraph/) to assemble LangChain components into full-featured applications. -## Basics -- [LLM applications](/docs/tutorials/llm_chain): Build a simple LLM application with prompt templates and chat models. - [Chatbots](/docs/tutorials/chatbot): Build a chatbot that incorporates memory. -- [Vector stores](/docs/tutorials/retrievers): Build vector stores and use them to retrieve data. - [Agents](/docs/tutorials/agents): Build an agent that interacts with external tools. - -## Working with external knowledge -- [Retrieval Augmented Generation (RAG)](/docs/tutorials/rag): Build an application that uses your own documents to inform its responses. -- [Conversational RAG](/docs/tutorials/qa_chat_history): Build a RAG application that incorporates a memory of its user interactions. +- [Retrieval Augmented Generation (RAG) Part 1](/docs/tutorials/rag): Build an application that uses your own documents to inform its responses. +- [Retrieval Augmented Generation (RAG) Part 2](/docs/tutorials/qa_chat_history): Build a RAG application that incorporates a memory of its user interactions and multi-step retrieval. - [Question-Answering with SQL](/docs/tutorials/sql_qa): Build a question-answering system that executes SQL queries to inform its responses. -- [Query Analysis](/docs/tutorials/query_analysis): Build a RAG application that analyzes questions to generate filters and other structured queries. -- [Local RAG](/docs/tutorials/local_rag): Build a RAG application using LLMs running locally on your machine. -- [Question-Answering with Graph Databases](/docs/tutorials/graph): Build a question-answering system that queries a graph database to inform its responses. -- [Question-Answering with PDFs](/docs/tutorials/pdf_qa/): Build a question-answering system that ingests PDFs and uses them to inform its responses. - -## Specialized tasks -- [Extraction](/docs/tutorials/extraction): Extract structured data from text and other unstructured media. -- [Synthetic data](/docs/tutorials/data_generation): Generate synthetic data using LLMs. -- [Classification](/docs/tutorials/classification): Classify text into categories or labels. - [Summarization](/docs/tutorials/summarization): Generate summaries of (potentially long) texts. - -## LangGraph - -LangGraph is an extension of LangChain aimed at -building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. - -LangGraph documentation is currently hosted on a separate site. -You can peruse [LangGraph tutorials here](https://langchain-ai.github.io/langgraph/tutorials/). +- [Question-Answering with Graph Databases](/docs/tutorials/graph): Build a question-answering system that queries a graph database to inform its responses. ## LangSmith @@ -55,7 +45,3 @@ You can peruse [LangSmith tutorials here](https://docs.smith.langchain.com/tutor LangSmith helps you evaluate the performance of your LLM applications. The tutorial below is a great way to get started: - [Evaluate your LLM application](https://docs.smith.langchain.com/tutorials/Developers/evaluation) - -## More - -For more tutorials, see our [cookbook section](https://github.com/langchain-ai/langchain/tree/master/cookbook). diff --git a/docs/docs/tutorials/llm_chain.ipynb b/docs/docs/tutorials/llm_chain.ipynb index ea1a8ae0288f2..be3d06736c48d 100644 --- a/docs/docs/tutorials/llm_chain.ipynb +++ b/docs/docs/tutorials/llm_chain.ipynb @@ -15,7 +15,7 @@ "id": "9316da0d", "metadata": {}, "source": [ - "# Build a Simple LLM Application\n", + "# Build a simple LLM application with chat models and prompt templates\n", "\n", "In this quickstart we'll show you how to build a simple LLM application with LangChain. This application will translate text from English into another language. This is a relatively simple LLM application - it's just a single LLM call plus some prompting. Still, this is a great way to get started with LangChain - a lot of features can be built with just some prompting and an LLM call!\n", "\n", @@ -23,7 +23,7 @@ "\n", "- Using [language models](/docs/concepts/chat_models)\n", "\n", - "- Using [PromptTemplates](/docs/concepts/prompt_templates)\n", + "- Using [prompt templates](/docs/concepts/prompt_templates)\n", "\n", "- Debugging and tracing your application using [LangSmith](https://docs.smith.langchain.com/)\n", "\n", @@ -96,7 +96,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "e4b41234", "metadata": {}, "outputs": [], @@ -106,7 +106,7 @@ "\n", "from langchain_openai import ChatOpenAI\n", "\n", - "model = ChatOpenAI(model=\"gpt-4o\")" + "model = ChatOpenAI(model=\"gpt-4o-mini\")" ] }, { @@ -114,22 +114,22 @@ "id": "ca5642ff", "metadata": {}, "source": [ - "Let's first use the model directly. [ChatModels](/docs/concepts/chat_models) are instances of LangChain [Runnables](/docs/concepts/runnables/), which means they expose a standard interface for interacting with them. To simply call the model, we can pass in a list of messages to the `.invoke` method." + "Let's first use the model directly. [ChatModels](/docs/concepts/chat_models) are instances of LangChain [Runnables](/docs/concepts/runnables/), which means they expose a standard interface for interacting with them. To simply call the model, we can pass in a list of [messages](/docs/concepts/messages/) to the `.invoke` method." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "1b2481f0", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "AIMessage(content='Ciao!', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 3, 'prompt_tokens': 20, 'total_tokens': 23, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_9ee9e968ea', 'finish_reason': 'stop', 'logprobs': None}, id='run-ad371806-6082-45c3-b6fa-e44622848ab2-0', usage_metadata={'input_tokens': 20, 'output_tokens': 3, 'total_tokens': 23, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})" + "AIMessage(content='Ciao!', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 3, 'prompt_tokens': 20, 'total_tokens': 23, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_0705bf87c0', 'finish_reason': 'stop', 'logprobs': None}, id='run-32654a56-627c-40e1-a141-ad9350bbfd3e-0', usage_metadata={'input_tokens': 20, 'output_tokens': 3, 'total_tokens': 23, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -138,8 +138,8 @@ "from langchain_core.messages import HumanMessage, SystemMessage\n", "\n", "messages = [\n", - " SystemMessage(content=\"Translate the following from English into Italian\"),\n", - " HumanMessage(content=\"hi!\"),\n", + " SystemMessage(\"Translate the following from English into Italian\"),\n", + " HumanMessage(\"hi!\"),\n", "]\n", "\n", "model.invoke(messages)" @@ -150,9 +150,54 @@ "id": "f83373db", "metadata": {}, "source": [ + ":::tip\n", + "\n", "If we've enabled LangSmith, we can see that this run is logged to LangSmith, and can see the [LangSmith trace](https://smith.langchain.com/public/88baa0b2-7c1a-4d09-ba30-a47985dde2ea/r). The LangSmith trace reports [token](/docs/concepts/tokens/) usage information, latency, [standard model parameters](/docs/concepts/chat_models/#standard-parameters) (such as temperature), and other information.\n", "\n", - "Note that ChatModels receive [message](/docs/concepts/messages/) objects as input and generate message objects as output. In addition to text content, message objects convey conversational [roles](/docs/concepts/messages/#role) and hold important data, such as [tool calls](/docs/concepts/tool_calling/) and token usage counts." + ":::\n", + "\n", + "Note that ChatModels receive [message](/docs/concepts/messages/) objects as input and generate message objects as output. In addition to text content, message objects convey conversational [roles](/docs/concepts/messages/#role) and hold important data, such as [tool calls](/docs/concepts/tool_calling/) and token usage counts.\n", + "\n", + "LangChain also supports chat model inputs via strings or [OpenAI format](/docs/concepts/messages/#openai-format). The following are equivalent:\n", + "\n", + "```python\n", + "model.invoke(\"Hello\")\n", + "\n", + "model.invoke([{\"role\": \"user\", \"content\": \"Hello\"}])\n", + "\n", + "model.invoke([HumanMessage(\"Hello\")])\n", + "```\n", + "\n", + "### Streaming\n", + "\n", + "Because chat models are [Runnables](/docs/concepts/runnables/), they expose a standard interface that includes async and streaming modes of invocation. This allows us to stream individual tokens from a chat model:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "0abb0863-bee7-448d-b013-79d8db01e330", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|C|iao|!||" + ] + } + ], + "source": [ + "for token in model.stream(messages):\n", + " print(token.content, end=\"|\")" + ] + }, + { + "cell_type": "markdown", + "id": "a5963141-468c-4570-8f2e-5f7cfb6eb3db", + "metadata": {}, + "source": [ + "You can find more details on streaming chat model outputs in [this guide](/docs/how_to/chat_streaming/)." ] }, { @@ -174,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "3e73cc20", "metadata": {}, "outputs": [], @@ -206,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "f781b3cb", "metadata": {}, "outputs": [ @@ -216,15 +261,15 @@ "ChatPromptValue(messages=[SystemMessage(content='Translate the following from English into Italian', additional_kwargs={}, response_metadata={}), HumanMessage(content='hi!', additional_kwargs={}, response_metadata={})])" ] }, - "execution_count": 4, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "result = prompt_template.invoke({\"language\": \"Italian\", \"text\": \"hi!\"})\n", + "prompt = prompt_template.invoke({\"language\": \"Italian\", \"text\": \"hi!\"})\n", "\n", - "result" + "prompt" ] }, { @@ -237,7 +282,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "2159b619", "metadata": {}, "outputs": [ @@ -248,39 +293,27 @@ " HumanMessage(content='hi!', additional_kwargs={}, response_metadata={})]" ] }, - "execution_count": 5, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "result.to_messages()" + "prompt.to_messages()" ] }, { "cell_type": "markdown", - "id": "5a4267a8", + "id": "47e70ee6-f0e0-4ae0-a290-002799ebf828", "metadata": {}, "source": [ - "## Chaining together components with LCEL\n", - "\n", - "We can now combine this with the model from above using the pipe (`|`) operator:" + "Finally, we can invoke the chat model on the formatted prompt:" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "6c6beb4b", - "metadata": {}, - "outputs": [], - "source": [ - "chain = prompt_template | model" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "3e45595a", + "execution_count": 8, + "id": "3a509d8c-e122-4641-b9ee-91bc23aa155a", "metadata": {}, "outputs": [ { @@ -292,23 +325,20 @@ } ], "source": [ - "response = chain.invoke({\"language\": \"Italian\", \"text\": \"hi!\"})\n", + "response = model.invoke(prompt)\n", "print(response.content)" ] }, { "cell_type": "markdown", - "id": "0b19cecb", + "id": "d7f0bf25-6efb-4853-9a8f-242f2855c84a", "metadata": {}, "source": [ ":::tip\n", "Message `content` can contain both text and [content blocks](/docs/concepts/messages/#aimessage) with additional structure. See [this guide](/docs/how_to/output_parser_string/) for more information.\n", ":::\n", "\n", - "\n", - "This is a simple example of using [LangChain Expression Language (LCEL)](/docs/concepts/lcel) to chain together LangChain modules. There are several benefits to this approach, including optimized streaming and tracing support.\n", - "\n", - "If we take a look at the [LangSmith trace](https://smith.langchain.com/public/bc49bec0-6b13-4726-967f-dbd3448b786d/r), we can see both components show up." + "If we take a look at the [LangSmith trace](https://smith.langchain.com/public/3ccc2d5e-2869-467b-95d6-33a577df99a2/r), we can see exactly what prompt the chat model receives, along with [token](/docs/concepts/tokens/) usage information, latency, [standard model parameters](/docs/concepts/chat_models/#standard-parameters) (such as temperature), and other information." ] }, { @@ -318,7 +348,7 @@ "source": [ "## Conclusion\n", "\n", - "That's it! In this tutorial you've learned how to create your first simple LLM application. You've learned how to work with language models, how to create a prompt template, and how to get great observability into chains you create with LangSmith.\n", + "That's it! In this tutorial you've learned how to create your first simple LLM application. You've learned how to work with language models, how to create a prompt template, and how to get great observability into applications you create with LangSmith.\n", "\n", "This just scratches the surface of what you will want to learn to become a proficient AI Engineer. Luckily - we've got a lot of other resources!\n", "\n", @@ -333,14 +363,6 @@ "\n", "- [LangSmith](https://docs.smith.langchain.com)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a3d3e206", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/docs/docs/tutorials/local_rag.ipynb b/docs/docs/tutorials/local_rag.ipynb deleted file mode 100644 index a43f764d4c19d..0000000000000 --- a/docs/docs/tutorials/local_rag.ipynb +++ /dev/null @@ -1,475 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "3ea857b1", - "metadata": {}, - "source": [ - "# Build a Local RAG Application\n", - "\n", - ":::info Prerequisites\n", - "\n", - "This guide assumes familiarity with the following concepts:\n", - "\n", - "- [Chat Models](/docs/concepts/chat_models)\n", - "- [Chaining runnables](/docs/how_to/sequence/)\n", - "- [Embeddings](/docs/concepts/embedding_models)\n", - "- [Vector stores](/docs/concepts/vectorstores)\n", - "- [Retrieval-augmented generation](/docs/tutorials/rag/)\n", - "\n", - ":::\n", - "\n", - "The popularity of projects like [llama.cpp](https://github.com/ggerganov/llama.cpp), [Ollama](https://github.com/ollama/ollama), and [llamafile](https://github.com/Mozilla-Ocho/llamafile) underscore the importance of running LLMs locally.\n", - "\n", - "LangChain has integrations with [many open-source LLM providers](/docs/how_to/local_llms) that can be run locally.\n", - "\n", - "This guide will show how to run `LLaMA 3.1` via one provider, [Ollama](/docs/integrations/providers/ollama/) locally (e.g., on your laptop) using local embeddings and a local LLM. However, you can set up and swap in other local providers, such as [LlamaCPP](/docs/integrations/chat/llamacpp/) if you prefer.\n", - "\n", - "**Note:** This guide uses a [chat model](/docs/concepts/chat_models) wrapper that takes care of formatting your input prompt for the specific local model you're using. However, if you are prompting local models directly with a [text-in/text-out LLM](/docs/concepts/text_llms) wrapper, you may need to use a prompt tailed for your specific model. This will often [require the inclusion of special tokens](https://huggingface.co/blog/llama2#how-to-prompt-llama-2). [Here's an example for LLaMA 2](https://smith.langchain.com/hub/rlm/rag-prompt-llama).\n", - "\n", - "## Setup\n", - "\n", - "First we'll need to set up Ollama.\n", - "\n", - "The instructions [on their GitHub repo](https://github.com/ollama/ollama) provide details, which we summarize here:\n", - "\n", - "- [Download](https://ollama.com/download) and run their desktop app\n", - "- From command line, fetch models from [this list of options](https://ollama.com/library). For this guide, you'll need:\n", - " - A general purpose model like `llama3.1:8b`, which you can pull with something like `ollama pull llama3.1:8b`\n", - " - A [text embedding model](https://ollama.com/search?c=embedding) like `nomic-embed-text`, which you can pull with something like `ollama pull nomic-embed-text`\n", - "- When the app is running, all models are automatically served on `localhost:11434`\n", - "- Note that your model choice will depend on your hardware capabilities\n", - "\n", - "Next, install packages needed for local embeddings, vector storage, and inference." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a7dc1ec5", - "metadata": {}, - "outputs": [], - "source": [ - "# Document loading, retrieval methods and text splitting\n", - "%pip install -qU langchain langchain_community\n", - "\n", - "# Local vector store via Chroma\n", - "%pip install -qU langchain_chroma\n", - "\n", - "# Local inference and embeddings via Ollama\n", - "%pip install -qU langchain_ollama\n", - "\n", - "# Web Loader\n", - "%pip install -qU beautifulsoup4" - ] - }, - { - "cell_type": "markdown", - "id": "02b7914e", - "metadata": {}, - "source": [ - "You can also [see this page](/docs/integrations/text_embedding/) for a full list of available embeddings models" - ] - }, - { - "cell_type": "markdown", - "id": "5e7543fa", - "metadata": {}, - "source": [ - "## Document Loading\n", - "\n", - "Now let's load and split an example document.\n", - "\n", - "We'll use a [blog post](https://lilianweng.github.io/posts/2023-06-23-agent/) by Lilian Weng on agents as an example." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f8cf5765", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "\n", - "loader = WebBaseLoader(\"https://lilianweng.github.io/posts/2023-06-23-agent/\")\n", - "data = loader.load()\n", - "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=0)\n", - "all_splits = text_splitter.split_documents(data)" - ] - }, - { - "cell_type": "markdown", - "id": "131d5059", - "metadata": {}, - "source": [ - "Next, the below steps will initialize your vector store. We use [`nomic-embed-text`](https://ollama.com/library/nomic-embed-text), but you can explore other providers or options as well:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "fdce8923", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_chroma import Chroma\n", - "from langchain_ollama import OllamaEmbeddings\n", - "\n", - "local_embeddings = OllamaEmbeddings(model=\"nomic-embed-text\")\n", - "\n", - "vectorstore = Chroma.from_documents(documents=all_splits, embedding=local_embeddings)" - ] - }, - { - "cell_type": "markdown", - "id": "29137915", - "metadata": {}, - "source": [ - "And now we have a working vector store! Test that similarity search is working:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "b0c55e98", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "4" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "question = \"What are the approaches to Task Decomposition?\"\n", - "docs = vectorstore.similarity_search(question)\n", - "len(docs)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "32b43339", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Document(metadata={'description': 'Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.\\nAgent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent’s brain, complemented by several key components:', 'language': 'en', 'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'title': \"LLM Powered Autonomous Agents | Lil'Log\"}, page_content='Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.')" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "docs[0]" - ] - }, - { - "cell_type": "markdown", - "id": "fcf81052", - "metadata": {}, - "source": [ - "Next, set up a model. We use Ollama with `llama3.1:8b` here, but you can [explore other providers](/docs/how_to/local_llms/) or [model options depending on your hardware setup](https://ollama.com/library):" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "af1176bb-d52a-4cf0-b983-8b7433d45b4f", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_ollama import ChatOllama\n", - "\n", - "model = ChatOllama(\n", - " model=\"llama3.1:8b\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "8c4f7adf", - "metadata": {}, - "source": [ - "Test it to make sure you've set everything up properly:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "bf0162e0-8c41-4344-88ae-ff2bbaeb12eb", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "**The scene is set: a packed arena, the crowd on their feet. In the blue corner, we have Stephen Colbert, aka \"The O'Reilly Factor\" himself. In the red corner, the challenger, John Oliver. The judges are announced as Tina Fey, Larry Wilmore, and Patton Oswalt. The crowd roars as the two opponents face off.**\n", - "\n", - "**Stephen Colbert (aka \"The Truth with a Twist\"):**\n", - "Yo, I'm the king of satire, the one they all fear\n", - "My show's on late, but my jokes are clear\n", - "I skewer the politicians, with precision and might\n", - "They tremble at my wit, day and night\n", - "\n", - "**John Oliver:**\n", - "Hold up, Stevie boy, you may have had your time\n", - "But I'm the new kid on the block, with a different prime\n", - "Time to wake up from that 90s coma, son\n", - "My show's got bite, and my facts are never done\n", - "\n", - "**Stephen Colbert:**\n", - "Oh, so you think you're the one, with the \"Last Week\" crown\n", - "But your jokes are stale, like the ones I wore down\n", - "I'm the master of absurdity, the lord of the spin\n", - "You're just a British import, trying to fit in\n", - "\n", - "**John Oliver:**\n", - "Stevie, my friend, you may have been the first\n", - "But I've got the skill and the wit, that's never blurred\n", - "My show's not afraid, to take on the fray\n", - "I'm the one who'll make you think, come what may\n", - "\n", - "**Stephen Colbert:**\n", - "Well, it's time for a showdown, like two old friends\n", - "Let's see whose satire reigns supreme, till the very end\n", - "But I've got a secret, that might just seal your fate\n", - "My humor's contagious, and it's already too late!\n", - "\n", - "**John Oliver:**\n", - "Bring it on, Stevie! I'm ready for you\n", - "I'll take on your jokes, and show them what to do\n", - "My sarcasm's sharp, like a scalpel in the night\n", - "You're just a relic of the past, without a fight\n", - "\n", - "**The judges deliberate, weighing the rhymes and the flow. Finally, they announce their decision:**\n", - "\n", - "Tina Fey: I've got to go with John Oliver. His jokes were sharper, and his delivery was smoother.\n", - "\n", - "Larry Wilmore: Agreed! But Stephen Colbert's still got that old-school charm.\n", - "\n", - "Patton Oswalt: You know what? It's a tie. Both of them brought the heat!\n", - "\n", - "**The crowd goes wild as both opponents take a bow. The rap battle may be over, but the satire war is just beginning...\n" - ] - } - ], - "source": [ - "response_message = model.invoke(\n", - " \"Simulate a rap battle between Stephen Colbert and John Oliver\"\n", - ")\n", - "\n", - "print(response_message.content)" - ] - }, - { - "cell_type": "markdown", - "id": "d58838ae", - "metadata": {}, - "source": [ - "## Using in a chain\n", - "\n", - "We can create a summarization chain with either model by passing in retrieved docs and a simple prompt.\n", - "\n", - "It formats the prompt template using the input key values provided and passes the formatted string to the specified model:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "18a3716d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'The main themes in these documents are:\\n\\n1. **Task Decomposition**: The process of breaking down complex tasks into smaller, manageable subgoals is crucial for efficient task handling.\\n2. **Autonomous Agent System**: A system powered by Large Language Models (LLMs) that can perform planning, reflection, and refinement to improve the quality of final results.\\n3. **Challenges in Planning and Decomposition**:\\n\\t* Long-term planning and task decomposition are challenging for LLMs.\\n\\t* Adjusting plans when faced with unexpected errors is difficult for LLMs.\\n\\t* Humans learn from trial and error, making them more robust than LLMs in certain situations.\\n\\nOverall, the documents highlight the importance of task decomposition and planning in autonomous agent systems powered by LLMs, as well as the challenges that still need to be addressed.'" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "\n", - "prompt = ChatPromptTemplate.from_template(\n", - " \"Summarize the main themes in these retrieved docs: {docs}\"\n", - ")\n", - "\n", - "\n", - "# Convert loaded documents into strings by concatenating their content\n", - "# and ignoring metadata\n", - "def format_docs(docs):\n", - " return \"\\n\\n\".join(doc.page_content for doc in docs)\n", - "\n", - "\n", - "chain = {\"docs\": format_docs} | prompt | model | StrOutputParser()\n", - "\n", - "question = \"What are the approaches to Task Decomposition?\"\n", - "\n", - "docs = vectorstore.similarity_search(question)\n", - "\n", - "chain.invoke(docs)" - ] - }, - { - "cell_type": "markdown", - "id": "3cce6977-52e7-4944-89b4-c161d04f6698", - "metadata": {}, - "source": [ - "## Q&A\n", - "\n", - "You can also perform question-answering with your local model and vector store. Here's an example with a simple string prompt:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "67cefb46-acd3-4c2a-a8f6-b62c7c3e30dc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Task decomposition can be done through (1) simple prompting using LLM, (2) task-specific instructions, or (3) human inputs. This approach helps break down large tasks into smaller, manageable subgoals for efficient handling of complex tasks. It enables agents to plan ahead and improve the quality of final results through reflection and refinement.'" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from langchain_core.runnables import RunnablePassthrough\n", - "\n", - "RAG_TEMPLATE = \"\"\"\n", - "You are an assistant for question-answering tasks. Use the following pieces of retrieved context to answer the question. If you don't know the answer, just say that you don't know. Use three sentences maximum and keep the answer concise.\n", - "\n", - "\n", - "{context}\n", - "\n", - "\n", - "Answer the following question:\n", - "\n", - "{question}\"\"\"\n", - "\n", - "rag_prompt = ChatPromptTemplate.from_template(RAG_TEMPLATE)\n", - "\n", - "chain = (\n", - " RunnablePassthrough.assign(context=lambda input: format_docs(input[\"context\"]))\n", - " | rag_prompt\n", - " | model\n", - " | StrOutputParser()\n", - ")\n", - "\n", - "question = \"What are the approaches to Task Decomposition?\"\n", - "\n", - "docs = vectorstore.similarity_search(question)\n", - "\n", - "# Run\n", - "chain.invoke({\"context\": docs, \"question\": question})" - ] - }, - { - "cell_type": "markdown", - "id": "821729cb", - "metadata": {}, - "source": [ - "## Q&A with retrieval\n", - "\n", - "Finally, instead of manually passing in docs, you can automatically retrieve them from our vector store based on the user question:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "86c7a349", - "metadata": {}, - "outputs": [], - "source": [ - "retriever = vectorstore.as_retriever()\n", - "\n", - "qa_chain = (\n", - " {\"context\": retriever | format_docs, \"question\": RunnablePassthrough()}\n", - " | rag_prompt\n", - " | model\n", - " | StrOutputParser()\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "112ca227", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Task decomposition can be done through (1) simple prompting in Large Language Models (LLM), (2) using task-specific instructions, or (3) with human inputs. This process involves breaking down large tasks into smaller, manageable subgoals for efficient handling of complex tasks.'" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "question = \"What are the approaches to Task Decomposition?\"\n", - "\n", - "qa_chain.invoke(question)" - ] - }, - { - "cell_type": "markdown", - "id": "e75d3e9e", - "metadata": {}, - "source": [ - "## Next steps\n", - "\n", - "You've now seen how to build a RAG application using all local components. RAG is a very deep topic, and you might be interested in the following guides that discuss and demonstrate additional techniques:\n", - "\n", - "- [Video: Reliable, fully local RAG agents with LLaMA 3](https://www.youtube.com/watch?v=-ROS6gfYIts) for an agentic approach to RAG with local models\n", - "- [Video: Building Corrective RAG from scratch with open-source, local LLMs](https://www.youtube.com/watch?v=E2shqsYwxck)\n", - "- [Conceptual guide on retrieval](/docs/concepts/retrieval) for an overview of various retrieval techniques you can apply to improve performance\n", - "- [How to guides on RAG](/docs/how_to/#qa-with-rag) for a deeper dive into different specifics around of RAG\n", - "- [How to run models locally](/docs/how_to/local_llms/) for different approaches to setting up different providers" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/docs/tutorials/pdf_qa.ipynb b/docs/docs/tutorials/pdf_qa.ipynb deleted file mode 100644 index bdc5792eac8b9..0000000000000 --- a/docs/docs/tutorials/pdf_qa.ipynb +++ /dev/null @@ -1,351 +0,0 @@ -{ - "cells": [ - { - "cell_type": "raw", - "metadata": { - "vscode": { - "languageId": "raw" - } - }, - "source": [ - "---\n", - "keywords: [pdf, document loader]\n", - "---" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Build a PDF ingestion and Question/Answering system\n", - "\n", - ":::info Prerequisites\n", - "\n", - "This guide assumes familiarity with the following concepts:\n", - "\n", - "- [Document loaders](/docs/concepts/document_loaders)\n", - "- [Chat models](/docs/concepts/chat_models)\n", - "- [Embeddings](/docs/concepts/embedding_models)\n", - "- [Vector stores](/docs/concepts/vectorstores)\n", - "- [Retrieval-augmented generation](/docs/tutorials/rag/)\n", - "\n", - ":::\n", - "\n", - "PDF files often hold crucial unstructured data unavailable from other sources. They can be quite lengthy, and unlike plain text files, cannot generally be fed directly into the prompt of a language model.\n", - "\n", - "In this tutorial, you'll create a system that can answer questions about PDF files. More specifically, you'll use a [Document Loader](/docs/concepts/document_loaders) to load text in a format usable by an LLM, then build a retrieval-augmented generation (RAG) pipeline to answer questions, including citations from the source material.\n", - "\n", - "This tutorial will gloss over some concepts more deeply covered in our [RAG](/docs/tutorials/rag/) tutorial, so you may want to go through those first if you haven't already.\n", - "\n", - "Let's dive in!\n", - "\n", - "## Loading documents\n", - "\n", - "First, you'll need to choose a PDF to load. We'll use a document from [Nike's annual public SEC report](https://s1.q4cdn.com/806093406/files/doc_downloads/2023/414759-1-_5_Nike-NPS-Combo_Form-10-K_WR.pdf). It's over 100 pages long, and contains some crucial data mixed with longer explanatory text. However, you can feel free to use a PDF of your choosing.\n", - "\n", - "Once you've chosen your PDF, the next step is to load it into a format that an LLM can more easily handle, since LLMs generally require text inputs. LangChain has a few different [built-in document loaders](/docs/how_to/document_loader_pdf/) for this purpose which you can experiment with. Below, we'll use one powered by the [`pypdf`](https://pypi.org/project/pypdf/) package that reads from a filepath:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%pip install -qU pypdf langchain_community" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "107\n" - ] - } - ], - "source": [ - "from langchain_community.document_loaders import PyPDFLoader\n", - "\n", - "file_path = \"../example_data/nke-10k-2023.pdf\"\n", - "loader = PyPDFLoader(file_path)\n", - "\n", - "docs = loader.load()\n", - "\n", - "print(len(docs))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Table of Contents\n", - "UNITED STATES\n", - "SECURITIES AND EXCHANGE COMMISSION\n", - "Washington, D.C. 20549\n", - "FORM 10-K\n", - "\n", - "{'source': '../example_data/nke-10k-2023.pdf', 'page': 0}\n" - ] - } - ], - "source": [ - "print(docs[0].page_content[0:100])\n", - "print(docs[0].metadata)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So what just happened?\n", - "\n", - "- The loader reads the PDF at the specified path into memory.\n", - "- It then extracts text data using the `pypdf` package.\n", - "- Finally, it creates a LangChain [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html#langchain_core.documents.base.Document) for each page of the PDF with the page's content and some metadata about where in the document the text came from.\n", - "\n", - "LangChain has [many other document loaders](/docs/integrations/document_loaders/) for other data sources, or you can create a [custom document loader](/docs/how_to/document_loader_custom/).\n", - "\n", - "## Question answering with RAG\n", - "\n", - "Next, you'll prepare the loaded documents for later retrieval. Using a [text splitter](/docs/concepts/text_splitters), you'll split your loaded documents into smaller documents that can more easily fit into an LLM's context window, then load them into a [vector store](/docs/concepts/vectorstores). You can then create a [retriever](/docs/concepts/retrievers) from the vector store for use in our RAG chain:\n", - "\n", - "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# | output: false\n", - "# | echo: false\n", - "\n", - "import getpass\n", - "import os\n", - "\n", - "from langchain_anthropic import ChatAnthropic\n", - "\n", - "if \"ANTHROPIC_API_KEY\" not in os.environ:\n", - " os.environ[\"ANTHROPIC_API_KEY\"] = getpass.getpass(\"Anthropic API Key:\")\n", - "\n", - "llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\", temperature=0)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%pip install langchain_openai" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# | output: false\n", - "# | echo: false\n", - "\n", - "import getpass\n", - "import os\n", - "\n", - "if \"OPENAI_API_KEY\" not in os.environ:\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_core.vectorstores import InMemoryVectorStore\n", - "from langchain_openai import OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = InMemoryVectorStore.from_documents(\n", - " documents=splits, embedding=OpenAIEmbeddings()\n", - ")\n", - "\n", - "retriever = vectorstore.as_retriever()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally, you'll use some built-in helpers to construct the final `rag_chain`:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'input': \"What was Nike's revenue in 2023?\",\n", - " 'context': [Document(page_content='Table of Contents\\nFISCAL 2023 NIKE BRAND REVENUE HIGHLIGHTS\\nThe following tables present NIKE Brand revenues disaggregated by reportable operating segment, distribution channel and major product line:\\nFISCAL 2023 COMPARED TO FISCAL 2022\\n•NIKE, Inc. Revenues were $51.2 billion in fiscal 2023, which increased 10% and 16% compared to fiscal 2022 on a reported and currency-neutral basis, respectively.\\nThe increase was due to higher revenues in North America, Europe, Middle East & Africa (\"EMEA\"), APLA and Greater China, which contributed approximately 7, 6,\\n2 and 1 percentage points to NIKE, Inc. Revenues, respectively.\\n•NIKE Brand revenues, which represented over 90% of NIKE, Inc. Revenues, increased 10% and 16% on a reported and currency-neutral basis, respectively. This\\nincrease was primarily due to higher revenues in Men\\'s, the Jordan Brand, Women\\'s and Kids\\' which grew 17%, 35%,11% and 10%, respectively, on a wholesale\\nequivalent basis.', metadata={'page': 35, 'source': '../example_data/nke-10k-2023.pdf'}),\n", - " Document(page_content='Enterprise Resource Planning Platform, data and analytics, demand sensing, insight gathering, and other areas to create an end-to-end technology foundation, which we\\nbelieve will further accelerate our digital transformation. We believe this unified approach will accelerate growth and unlock more efficiency for our business, while driving\\nspeed and responsiveness as we serve consumers globally.\\nFINANCIAL HIGHLIGHTS\\n•In fiscal 2023, NIKE, Inc. achieved record Revenues of $51.2 billion, which increased 10% and 16% on a reported and currency-neutral basis, respectively\\n•NIKE Direct revenues grew 14% from $18.7 billion in fiscal 2022 to $21.3 billion in fiscal 2023, and represented approximately 44% of total NIKE Brand revenues for\\nfiscal 2023\\n•Gross margin for the fiscal year decreased 250 basis points to 43.5% primarily driven by higher product costs, higher markdowns and unfavorable changes in foreign\\ncurrency exchange rates, partially offset by strategic pricing actions', metadata={'page': 30, 'source': '../example_data/nke-10k-2023.pdf'}),\n", - " Document(page_content=\"Table of Contents\\nNORTH AMERICA\\n(Dollars in millions) FISCAL 2023FISCAL 2022 % CHANGE% CHANGE\\nEXCLUDING\\nCURRENCY\\nCHANGESFISCAL 2021 % CHANGE% CHANGE\\nEXCLUDING\\nCURRENCY\\nCHANGES\\nRevenues by:\\nFootwear $ 14,897 $ 12,228 22 % 22 %$ 11,644 5 % 5 %\\nApparel 5,947 5,492 8 % 9 % 5,028 9 % 9 %\\nEquipment 764 633 21 % 21 % 507 25 % 25 %\\nTOTAL REVENUES $ 21,608 $ 18,353 18 % 18 %$ 17,179 7 % 7 %\\nRevenues by: \\nSales to Wholesale Customers $ 11,273 $ 9,621 17 % 18 %$ 10,186 -6 % -6 %\\nSales through NIKE Direct 10,335 8,732 18 % 18 % 6,993 25 % 25 %\\nTOTAL REVENUES $ 21,608 $ 18,353 18 % 18 %$ 17,179 7 % 7 %\\nEARNINGS BEFORE INTEREST AND TAXES $ 5,454 $ 5,114 7 % $ 5,089 0 %\\nFISCAL 2023 COMPARED TO FISCAL 2022\\n•North America revenues increased 18% on a currency-neutral basis, primarily due to higher revenues in Men's and the Jordan Brand. NIKE Direct revenues\\nincreased 18%, driven by strong digital sales growth of 23%, comparable store sales growth of 9% and the addition of new stores.\", metadata={'page': 39, 'source': '../example_data/nke-10k-2023.pdf'}),\n", - " Document(page_content=\"Table of Contents\\nEUROPE, MIDDLE EAST & AFRICA\\n(Dollars in millions) FISCAL 2023FISCAL 2022 % CHANGE% CHANGE\\nEXCLUDING\\nCURRENCY\\nCHANGESFISCAL 2021 % CHANGE% CHANGE\\nEXCLUDING\\nCURRENCY\\nCHANGES\\nRevenues by:\\nFootwear $ 8,260 $ 7,388 12 % 25 %$ 6,970 6 % 9 %\\nApparel 4,566 4,527 1 % 14 % 3,996 13 % 16 %\\nEquipment 592 564 5 % 18 % 490 15 % 17 %\\nTOTAL REVENUES $ 13,418 $ 12,479 8 % 21 %$ 11,456 9 % 12 %\\nRevenues by: \\nSales to Wholesale Customers $ 8,522 $ 8,377 2 % 15 %$ 7,812 7 % 10 %\\nSales through NIKE Direct 4,896 4,102 19 % 33 % 3,644 13 % 15 %\\nTOTAL REVENUES $ 13,418 $ 12,479 8 % 21 %$ 11,456 9 % 12 %\\nEARNINGS BEFORE INTEREST AND TAXES $ 3,531 $ 3,293 7 % $ 2,435 35 % \\nFISCAL 2023 COMPARED TO FISCAL 2022\\n•EMEA revenues increased 21% on a currency-neutral basis, due to higher revenues in Men's, the Jordan Brand, Women's and Kids'. NIKE Direct revenues\\nincreased 33%, driven primarily by strong digital sales growth of 43% and comparable store sales growth of 22%.\", metadata={'page': 40, 'source': '../example_data/nke-10k-2023.pdf'})],\n", - " 'answer': 'According to the financial highlights, Nike, Inc. achieved record revenues of $51.2 billion in fiscal 2023, which increased 10% on a reported basis and 16% on a currency-neutral basis compared to fiscal 2022.'}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from langchain.chains import create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "\n", - "\n", - "question_answer_chain = create_stuff_documents_chain(llm, prompt)\n", - "rag_chain = create_retrieval_chain(retriever, question_answer_chain)\n", - "\n", - "results = rag_chain.invoke({\"input\": \"What was Nike's revenue in 2023?\"})\n", - "\n", - "results" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can see that you get both a final answer in the `answer` key of the results dict, and the `context` the LLM used to generate an answer.\n", - "\n", - "Examining the values under the `context` further, you can see that they are documents that each contain a chunk of the ingested page content. Usefully, these documents also preserve the original metadata from way back when you first loaded them:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Table of Contents\n", - "FISCAL 2023 NIKE BRAND REVENUE HIGHLIGHTS\n", - "The following tables present NIKE Brand revenues disaggregated by reportable operating segment, distribution channel and major product line:\n", - "FISCAL 2023 COMPARED TO FISCAL 2022\n", - "•NIKE, Inc. Revenues were $51.2 billion in fiscal 2023, which increased 10% and 16% compared to fiscal 2022 on a reported and currency-neutral basis, respectively.\n", - "The increase was due to higher revenues in North America, Europe, Middle East & Africa (\"EMEA\"), APLA and Greater China, which contributed approximately 7, 6,\n", - "2 and 1 percentage points to NIKE, Inc. Revenues, respectively.\n", - "•NIKE Brand revenues, which represented over 90% of NIKE, Inc. Revenues, increased 10% and 16% on a reported and currency-neutral basis, respectively. This\n", - "increase was primarily due to higher revenues in Men's, the Jordan Brand, Women's and Kids' which grew 17%, 35%,11% and 10%, respectively, on a wholesale\n", - "equivalent basis.\n" - ] - } - ], - "source": [ - "print(results[\"context\"][0].page_content)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'page': 35, 'source': '../example_data/nke-10k-2023.pdf'}\n" - ] - } - ], - "source": [ - "print(results[\"context\"][0].metadata)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This particular chunk came from page 35 in the original PDF. You can use this data to show which page in the PDF the answer came from, allowing users to quickly verify that answers are based on the source material.\n", - "\n", - ":::info\n", - "For a deeper dive into RAG, see [this more focused tutorial](/docs/tutorials/rag/) or [our how-to guides](/docs/how_to/#qa-with-rag).\n", - ":::\n", - "\n", - "## Next steps\n", - "\n", - "You've now seen how to load documents from a PDF file with a Document Loader and some techniques you can use to prepare that loaded data for RAG.\n", - "\n", - "For more on document loaders, you can check out:\n", - "\n", - "- [The entry in the conceptual guide](/docs/concepts/document_loaders)\n", - "- [Related how-to guides](/docs/how_to/#document-loaders)\n", - "- [Available integrations](/docs/integrations/document_loaders/)\n", - "- [How to create a custom document loader](/docs/how_to/document_loader_custom/)\n", - "\n", - "For more on RAG, see:\n", - "\n", - "- [Build a Retrieval Augmented Generation (RAG) App](/docs/tutorials/rag/)\n", - "- [Related how-to guides](/docs/how_to/#qa-with-rag)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.4" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/docs/docs/tutorials/qa_chat_history.ipynb b/docs/docs/tutorials/qa_chat_history.ipynb index 1955abd8c4c4e..2e0b09b2d1713 100644 --- a/docs/docs/tutorials/qa_chat_history.ipynb +++ b/docs/docs/tutorials/qa_chat_history.ipynb @@ -15,32 +15,29 @@ "id": "86fc5bb2-017f-434e-8cd6-53ab214a5604", "metadata": {}, "source": [ - "# Conversational RAG\n", + "# Build a Retrieval Augmented Generation (RAG) App: Part 2\n", "\n", - ":::info Prerequisites\n", + "In many Q&A applications we want to allow the user to have a back-and-forth conversation, meaning the application needs some sort of \"memory\" of past questions and answers, and some logic for incorporating those into its current thinking.\n", "\n", - "This guide assumes familiarity with the following concepts:\n", + "This is a the second part of a multi-part tutorial:\n", "\n", - "- [Chat history](/docs/concepts/chat_history)\n", - "- [Chat models](/docs/concepts/chat_models)\n", - "- [Embeddings](/docs/concepts/embedding_models)\n", - "- [Vector stores](/docs/concepts/vectorstores)\n", - "- [Retrieval-augmented generation](/docs/tutorials/rag/)\n", - "- [Tools](/docs/concepts/tools)\n", - "- [Agents](/docs/concepts/agents)\n", + "- [Part 1](/docs/tutorials/rag) introduces RAG and walks through a minimal implementation.\n", + "- [Part 2](/docs/tutorials/qa_chat_history) (this guide) extends the implementation to accommodate conversation-style interactions and multi-step retrieval processes.\n", "\n", - ":::\n", + "Here we focus on **adding logic for incorporating historical messages.** This involves the management of a [chat history](/docs/concepts/chat_history).\n", "\n", - "In many Q&A applications we want to allow the user to have a back-and-forth conversation, meaning the application needs some sort of \"memory\" of past questions and answers, and some logic for incorporating those into its current thinking.\n", + "We will cover two approaches:\n", "\n", - "In this guide we focus on **adding logic for incorporating historical messages.** Further details on chat history management is [covered here](/docs/how_to/message_history).\n", + "1. [Chains](/docs/tutorials/qa_chat_history/#chains), in which we execute at most one retrieval step;\n", + "2. [Agents](/docs/tutorials/qa_chat_history/#agents), in which we give an LLM discretion to execute multiple retrieval steps.\n", "\n", - "We will cover two approaches:\n", + ":::note\n", "\n", - "1. [Chains](/docs/tutorials/qa_chat_history/#chains), in which we always execute a retrieval step;\n", - "2. [Agents](/docs/tutorials/qa_chat_history/#agents), in which we give an LLM discretion over whether and how to execute a retrieval step (or multiple steps).\n", + "The methods presented here leverage [tool-calling](/docs/concepts/tool_calling/) capabilities in modern [chat models](/docs/concepts/chat_models). See [this page](/docs/integrations/chat/) for a table of models supporting tool calling features.\n", + "\n", + ":::\n", "\n", - "For the external knowledge source, we will use the same [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng from the [RAG tutorial](/docs/tutorials/rag)." + "For the external knowledge source, we will use the same [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng from the [Part 1](/docs/tutorials/rag) of the RAG tutorial." ] }, { @@ -50,117 +47,151 @@ "source": [ "## Setup\n", "\n", - "### Dependencies\n", + "### Components\n", + "\n", + "We will need to select three components from LangChain's suite of integrations.\n", "\n", - "We'll use OpenAI embeddings and a simple in-memory vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts/embedding_models), and [VectorStore](/docs/concepts/vectorstores) or [Retriever](/docs/concepts/retrievers). \n", + "A [chat model](/docs/integrations/chat/):\n", + "\n", + "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", "\n", - "We'll use the following packages:" + "" ] }, { "cell_type": "code", - "execution_count": 1, - "id": "ede7fdc0-ef31-483d-bd67-32e4b5c5d527", + "execution_count": 2, + "id": "fab0dd56-7437-4aeb-af20-7f420d47ca94", "metadata": {}, "outputs": [], "source": [ - "%%capture --no-stderr\n", - "%pip install --upgrade --quiet langchain langchain-community beautifulsoup4" + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_openai import ChatOpenAI\n", + "\n", + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" ] }, { "cell_type": "markdown", - "id": "51ef48de-70b6-4f43-8e0b-ab9b84c9c02a", + "id": "da14773e-ac98-4a97-944b-4c6ec028d195", "metadata": {}, "source": [ - "We need to set environment variable `OPENAI_API_KEY`, which can be done directly or loaded from a `.env` file like so:" + "An [embedding model](/docs/integrations/text_embedding/):\n", + "\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", + "\n", + "" ] }, { "cell_type": "code", - "execution_count": 2, - "id": "143787ca-d8e6-4dc9-8281-4374f4d71720", + "execution_count": 3, + "id": "4691bd31-d8f4-4ba1-aec5-44935400f33c", "metadata": {}, "outputs": [], "source": [ - "import getpass\n", - "import os\n", + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_openai import OpenAIEmbeddings\n", "\n", - "if not os.environ.get(\"OPENAI_API_KEY\"):\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()" + "embeddings = OpenAIEmbeddings()" ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "e207ac1d-4a8e-4172-a9ee-3294519a9a40", + "id": "22fdc314-b91d-4820-b0a8-873b5b6e76f5", "metadata": {}, "source": [ - "### LangSmith\n", + "And a [vector store](/docs/integrations/vectorstores/):\n", "\n", - "Many of the applications you build with LangChain will contain multiple steps with multiple invocations of LLM calls. As these applications get more and more complex, it becomes crucial to be able to inspect what exactly is going on inside your chain or agent. The best way to do this is with [LangSmith](https://smith.langchain.com).\n", - "\n", - "Note that LangSmith is not needed, but it is helpful. If you do want to use LangSmith, after you sign up at the link above, make sure to set your environment variables to start logging traces:\n", + "import VectorStoreTabs from \"@theme/VectorStoreTabs\";\n", "\n", - "```python\n", - "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", - "if not os.environ.get(\"LANGCHAIN_API_KEY\"):\n", - " os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", - "```" + "" ] }, { - "cell_type": "markdown", - "id": "fa6ba684-26cf-4860-904e-a4d51380c134", + "cell_type": "code", + "execution_count": 4, + "id": "137d3848-7265-4673-9779-4c5f604da469", "metadata": {}, + "outputs": [], "source": [ - "## Chains {#chains}\n", + "# | output: false\n", + "# | echo: false\n", "\n", - "Let's first revisit the Q&A app we built over the [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng in the [RAG tutorial](/docs/tutorials/rag)." + "from langchain_core.vectorstores import InMemoryVectorStore\n", + "\n", + "vector_store = InMemoryVectorStore(embeddings)" ] }, { "cell_type": "markdown", - "id": "646840fb-5212-48ea-8bc7-ec7be5ec727e", + "id": "94bc335b-dc8a-4c40-aece-3aa9057cc6bd", "metadata": {}, "source": [ - "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", + "### Dependencies\n", "\n", - "\n" + "In addition, we'll use the following packages:" ] }, { "cell_type": "code", "execution_count": 1, - "id": "cb58f273-2111-4a9b-8932-9b64c95030c8", + "id": "ede7fdc0-ef31-483d-bd67-32e4b5c5d527", "metadata": {}, "outputs": [], "source": [ - "# | output: false\n", - "# | echo: false\n", + "%%capture --no-stderr\n", + "%pip install --upgrade --quiet langgraph langchain-community beautifulsoup4" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "e207ac1d-4a8e-4172-a9ee-3294519a9a40", + "metadata": {}, + "source": [ + "### LangSmith\n", "\n", - "from langchain_openai import ChatOpenAI\n", + "Many of the applications you build with LangChain will contain multiple steps with multiple invocations of LLM calls. As these applications get more and more complex, it becomes crucial to be able to inspect what exactly is going on inside your chain or agent. The best way to do this is with [LangSmith](https://smith.langchain.com).\n", + "\n", + "Note that LangSmith is not needed, but it is helpful. If you do want to use LangSmith, after you sign up at the link above, make sure to set your environment variables to start logging traces:\n", + "\n", + "```python\n", + "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", + "if not os.environ.get(\"LANGCHAIN_API_KEY\"):\n", + " os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "fa6ba684-26cf-4860-904e-a4d51380c134", + "metadata": {}, + "source": [ + "## Chains {#chains}\n", "\n", - "llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)" + "Let's first revisit the vector store we built in [Part 1](/docs/tutorials/rag), which indexes an [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post by Lilian Weng." ] }, { "cell_type": "code", - "execution_count": 3, - "id": "820244ae-74b4-4593-b392-822979dd91b8", + "execution_count": 6, + "id": "ffe06d69-33c9-4ca3-98fb-8c70cde9dba2", "metadata": {}, "outputs": [], "source": [ "import bs4\n", - "from langchain.chains import create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", + "from langchain import hub\n", "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_core.vectorstores import InMemoryVectorStore\n", - "from langchain_openai import OpenAIEmbeddings\n", + "from langchain_core.documents import Document\n", "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "from typing_extensions import List, TypedDict\n", "\n", - "# 1. Load, chunk and index the contents of the blog to create a retriever.\n", + "# Load and chunk contents of the blog\n", "loader = WebBaseLoader(\n", " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", " bs_kwargs=dict(\n", @@ -172,73 +203,53 @@ "docs = loader.load()\n", "\n", "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = InMemoryVectorStore.from_documents(\n", - " documents=splits, embedding=OpenAIEmbeddings()\n", - ")\n", - "retriever = vectorstore.as_retriever()\n", - "\n", - "\n", - "# 2. Incorporate the retriever into a question-answering chain.\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "\n", - "question_answer_chain = create_stuff_documents_chain(llm, prompt)\n", - "rag_chain = create_retrieval_chain(retriever, question_answer_chain)" + "all_splits = text_splitter.split_documents(docs)" ] }, { "cell_type": "code", - "execution_count": 4, - "id": "bf55faaf-0d17-4b74-925d-c478b555f7b2", + "execution_count": 7, + "id": "b4369949-39f1-4cdc-b652-179e0b891b51", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "\"Task decomposition is the process of breaking down a complicated task into smaller, more manageable steps. Techniques like Chain of Thought (CoT) and Tree of Thoughts enhance this process by guiding models to think step by step and explore multiple reasoning possibilities. This approach helps in simplifying complex tasks and provides insight into the model's reasoning.\"" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "response = rag_chain.invoke({\"input\": \"What is Task Decomposition?\"})\n", - "response[\"answer\"]" + "# Index chunks\n", + "_ = vector_store.add_documents(documents=all_splits)" ] }, { "cell_type": "markdown", - "id": "187404c7-db47-49c5-be29-9ecb96dc9afa", + "id": "42c26d5f-1493-4ad6-9210-ea2723695149", "metadata": {}, "source": [ - "Note that we have used the built-in chain constructors `create_stuff_documents_chain` and `create_retrieval_chain`, so that the basic ingredients to our solution are:\n", - "\n", - "1. retriever;\n", - "2. prompt;\n", - "3. LLM.\n", + "In the [Part 1](/docs/tutorials/rag) of the RAG tutorial, we represented the user input, retrieved context, and generated answer as separate keys in the state. Conversational experiences can be naturally represented using a sequence of [messages](/docs/concepts/messages/). In addition to messages from the user and assistant, retrieved documents and other artifacts can be incorporated into a message sequence via [tool messages](/docs/concepts/messages/#toolmessage). This motivates us to represent the state of our RAG application using a sequence of messages. Specifically, we will have\n", "\n", - "This will simplify the process of incorporating chat history.\n", + "1. User input as a `HumanMessage`;\n", + "2. Vector store query as an `AIMessage` with tool calls;\n", + "3. Retrieved documents as a `ToolMessage`;\n", + "4. Final response as a `AIMessage`.\n", "\n", - "### Adding chat history\n", + "This model for state is so versatile that LangGraph offers a built-in version for convenience:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "e27d97f0-27dc-438b-bf61-a403ca284522", + "metadata": {}, + "outputs": [], + "source": [ + "from langgraph.graph import MessagesState, StateGraph\n", "\n", - "The chain we have built uses the input query directly to retrieve relevant context. But in a conversational setting, the user query might require conversational context to be understood. For example, consider this exchange:\n", + "graph_builder = StateGraph(MessagesState)" + ] + }, + { + "cell_type": "markdown", + "id": "35eeb6a1-29f2-4086-8b6f-8761cf24ce59", + "metadata": {}, + "source": [ + "Leveraging [tool-calling](/docs/concepts/tool_calling/) to interact with a retrieval step has another benefit, which is that the query for the retrieval is generated by our model. This is especially important in a conversational setting, where user queries may require contextualization based on the chat history. For instance, consider the following exchange:\n", "\n", "> Human: \"What is Task Decomposition?\"\n", ">\n", @@ -246,161 +257,274 @@ ">\n", "> Human: \"What are common ways of doing it?\"\n", "\n", - "In order to answer the second question, our system needs to understand that \"it\" refers to \"Task Decomposition.\"\n", + "In this scenario, a model could generate a query such as `\"common approaches to task decomposition\"`. Tool-calling facilitates this naturally. As in the [query analysis](/docs/tutorials/rag#query-analysis) section of the RAG tutorial, this allows a model to rewrite user queries into more effective search queries. It also provides support for direct responses that do not involve a retrieval step (e.g., in response to a generic greeting from the user).\n", + "\n", + "Let's turn our retrieval step into a [tool](/docs/concepts/tools):" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "8201a6ef-942f-4571-b3b9-55a430590266", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.tools import tool\n", "\n", - "We'll need to update two things about our existing app:\n", "\n", - "1. **Prompt**: Update our prompt to support historical messages as an input.\n", - "2. **Contextualizing questions**: Add a sub-chain that takes the latest user question and reformulates it in the context of the chat history. This can be thought of simply as building a new \"history aware\" retriever. Whereas before we had:\n", - " - `query` -> `retriever` \n", - " Now we will have:\n", - " - `(query, conversation history)` -> `LLM` -> `rephrased query` -> `retriever`" + "@tool(response_format=\"content_and_artifact\")\n", + "def retrieve(query: str):\n", + " \"\"\"Retrieve information related to a query.\"\"\"\n", + " retrieved_docs = vector_store.similarity_search(query, k=2)\n", + " serialized = \"\\n\\n\".join(\n", + " (f\"Source: {doc.metadata}\\n\" f\"Content: {doc.page_content}\")\n", + " for doc in retrieved_docs\n", + " )\n", + " return serialized, retrieved_docs" ] }, { "cell_type": "markdown", - "id": "776ae958-cbdc-4471-8669-c6087436f0b5", + "id": "9b03f752-d46d-4070-b790-197b742c4dc2", "metadata": {}, "source": [ - "#### Contextualizing the question\n", - "\n", - "First we'll need to define a sub-chain that takes historical messages and the latest user question, and reformulates the question if it makes reference to any information in the historical information.\n", + "See [this guide](/docs/how_to/custom_tools/) for more detail on creating tools.\n", "\n", - "We'll use a prompt that includes a `MessagesPlaceholder` variable under the name \"chat_history\". This allows us to pass in a list of Messages to the prompt using the \"chat_history\" input key, and these messages will be inserted after the system message and before the human message containing the latest question.\n", + "Our graph will consist of three nodes:\n", "\n", - "Note that we leverage a helper function [create_history_aware_retriever](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.history_aware_retriever.create_history_aware_retriever.html) for this step, which manages the case where `chat_history` is empty, and otherwise applies `prompt | llm | StrOutputParser() | retriever` in sequence.\n", + "1. A node that fields the user input, either generating a query for the retriever or responding directly;\n", + "2. A node for the retriever tool that executes the retrieval step;\n", + "3. A node that generates the final response using the retrieved context.\n", "\n", - "`create_history_aware_retriever` constructs a chain that accepts keys `input` and `chat_history` as input, and has the same output schema as a retriever." + "We build them below. Note that we leverage another pre-built LangGraph component, [ToolNode](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.tool_node.ToolNode), that executes the tool and adds the result as a `ToolMessage` to the state." ] }, { "cell_type": "code", - "execution_count": 5, - "id": "2b685428-8b82-4af1-be4f-7232c5d55b73", + "execution_count": 10, + "id": "4d0ce8c9-b404-424b-886e-c1386368ec24", "metadata": {}, "outputs": [], "source": [ - "from langchain.chains import create_history_aware_retriever\n", - "from langchain_core.prompts import MessagesPlaceholder\n", - "\n", - "contextualize_q_system_prompt = (\n", - " \"Given a chat history and the latest user question \"\n", - " \"which might reference context in the chat history, \"\n", - " \"formulate a standalone question which can be understood \"\n", - " \"without the chat history. Do NOT answer the question, \"\n", - " \"just reformulate it if needed and otherwise return it as is.\"\n", - ")\n", - "\n", - "contextualize_q_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", contextualize_q_system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", + "from langchain_core.messages import SystemMessage\n", + "from langgraph.prebuilt import ToolNode\n", + "\n", + "\n", + "# Step 1: Generate an AIMessage that may include a tool-call to be sent.\n", + "def query_or_respond(state: MessagesState):\n", + " \"\"\"Generate tool call for retrieval or respond.\"\"\"\n", + " llm_with_tools = llm.bind_tools([retrieve])\n", + " response = llm_with_tools.invoke(state[\"messages\"])\n", + " # MessagesState appends messages to state instead of overwriting\n", + " return {\"messages\": [response]}\n", + "\n", + "\n", + "# Step 2: Execute the retrieval.\n", + "tools = ToolNode([retrieve])\n", + "\n", + "\n", + "# Step 3: Generate a response using the retrieved content.\n", + "def generate(state: MessagesState):\n", + " \"\"\"Generate answer.\"\"\"\n", + " # Get generated ToolMessages\n", + " recent_tool_messages = []\n", + " for message in reversed(state[\"messages\"]):\n", + " if message.type == \"tool\":\n", + " recent_tool_messages.append(message)\n", + " else:\n", + " break\n", + " tool_messages = recent_tool_messages[::-1]\n", + "\n", + " # Format into prompt\n", + " docs_content = \"\\n\\n\".join(doc.content for doc in tool_messages)\n", + " system_message_content = (\n", + " \"You are an assistant for question-answering tasks. \"\n", + " \"Use the following pieces of retrieved context to answer \"\n", + " \"the question. If you don't know the answer, say that you \"\n", + " \"don't know. Use three sentences maximum and keep the \"\n", + " \"answer concise.\"\n", + " \"\\n\\n\"\n", + " f\"{docs_content}\"\n", + " )\n", + " conversation_messages = [\n", + " message\n", + " for message in state[\"messages\"]\n", + " if message.type in (\"human\", \"system\")\n", + " or (message.type == \"ai\" and not message.tool_calls)\n", " ]\n", - ")\n", - "history_aware_retriever = create_history_aware_retriever(\n", - " llm, retriever, contextualize_q_prompt\n", - ")" + " prompt = [SystemMessage(system_message_content)] + conversation_messages\n", + "\n", + " # Run\n", + " response = llm.invoke(prompt)\n", + " return {\"messages\": [response]}" ] }, { "cell_type": "markdown", - "id": "42a47168-4a1f-4e39-bd2d-d5b03609a243", + "id": "b409ee5f-2973-47ee-a1bf-112731843c5d", + "metadata": {}, + "source": [ + "Finally, we compile our application into a single `graph` object. In this case, we are just connecting the steps into a sequence. We also allow the first `query_or_respond` step to \"short-circuit\" and respond directly to the user if it does not generate a tool call. This allows our application to support conversational experiences-- e.g., responding to generic greetings that may not require a retrieval step" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "ac33f19c-7959-4526-8f12-0de76ae10387", "metadata": {}, + "outputs": [], "source": [ - "This chain prepends a rephrasing of the input query to our retriever, so that the retrieval incorporates the context of the conversation.\n", + "from langgraph.graph import END\n", + "from langgraph.prebuilt import ToolNode, tools_condition\n", "\n", - "Now we can build our full QA chain. This is as simple as updating the retriever to be our new `history_aware_retriever`.\n", + "graph_builder.add_node(query_or_respond)\n", + "graph_builder.add_node(tools)\n", + "graph_builder.add_node(generate)\n", "\n", - "Again, we will use [create_stuff_documents_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.combine_documents.stuff.create_stuff_documents_chain.html) to generate a `question_answer_chain`, with input keys `context`, `chat_history`, and `input`-- it accepts the retrieved context alongside the conversation history and query to generate an answer. A more detailed explaination is over [here](/docs/tutorials/rag/#built-in-chains)\n", + "graph_builder.set_entry_point(\"query_or_respond\")\n", + "graph_builder.add_conditional_edges(\n", + " \"query_or_respond\",\n", + " tools_condition,\n", + " {END: END, \"tools\": \"tools\"},\n", + ")\n", + "graph_builder.add_edge(\"tools\", \"generate\")\n", + "graph_builder.add_edge(\"generate\", END)\n", "\n", - "We build our final `rag_chain` with [create_retrieval_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.retrieval.create_retrieval_chain.html). This chain applies the `history_aware_retriever` and `question_answer_chain` in sequence, retaining intermediate outputs such as the retrieved context for convenience. It has input keys `input` and `chat_history`, and includes `input`, `chat_history`, `context`, and `answer` in its output." + "graph = graph_builder.compile()" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "66f275f3-ddef-4678-b90d-ee64576878f9", + "execution_count": 12, + "id": "5c7e1717-d262-4947-a64d-6b116e53856a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "from langchain.chains import create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", - "\n", - "qa_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", + "from IPython.display import Image, display\n", "\n", + "display(Image(graph.get_graph().draw_mermaid_png()))" + ] + }, + { + "cell_type": "markdown", + "id": "236b6209-ee06-42ba-b266-d90d9cbf224b", + "metadata": {}, + "source": [ + "Let's test our application.\n", "\n", - "question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)\n", + "Note that it responds appropriately to messages that do not require an additional retrieval step:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "4fbca953-970d-4271-be30-6c7799893dd1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Hello\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hello! How can I assist you today?\n" + ] + } + ], + "source": [ + "input_message = \"Hello\"\n", "\n", - "rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)" + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", + "):\n", + " step[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", - "id": "1ba1ae56-7ecb-4563-b792-50a1a5042df3", + "id": "5df5046d-4610-4ffa-9f30-d04453da05a9", "metadata": {}, "source": [ - "Let's try this. Below we ask a question and a follow-up question that requires contextualization to return a sensible response. Because our chain includes a `\"chat_history\"` input, the caller needs to manage the chat history. We can achieve this by appending input and output messages to a list:" + "And when executing a search, we can stream the steps to observe the query generation, retrieval, and answer generation:" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "0005810b-1b95-4666-a795-08d80e478b83", + "execution_count": 14, + "id": "9ab78984-d7fa-40e1-a440-c041a6456c1f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Common ways of task decomposition include using simple prompting techniques, such as asking for \"Steps for XYZ\" or \"What are the subgoals for achieving XYZ?\" Additionally, task-specific instructions can be employed, like \"Write a story outline\" for writing tasks, or human inputs can guide the decomposition process.\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What is Task Decomposition?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_dLjB3rkMoxZZxwUGXi33UBeh)\n", + " Call ID: call_dLjB3rkMoxZZxwUGXi33UBeh\n", + " Args:\n", + " query: Task Decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Task Decomposition is the process of breaking down a complicated task into smaller, manageable steps. It often involves techniques like Chain of Thought (CoT), which encourages models to think step by step, enhancing performance on complex tasks. This approach allows for a clearer understanding of the task and aids in structuring the problem-solving process.\n" ] } ], "source": [ - "from langchain_core.messages import AIMessage, HumanMessage\n", - "\n", - "chat_history = []\n", - "\n", - "question = \"What is Task Decomposition?\"\n", - "ai_msg_1 = rag_chain.invoke({\"input\": question, \"chat_history\": chat_history})\n", - "chat_history.extend(\n", - " [\n", - " HumanMessage(content=question),\n", - " AIMessage(content=ai_msg_1[\"answer\"]),\n", - " ]\n", - ")\n", + "input_message = \"What is Task Decomposition?\"\n", "\n", - "second_question = \"What are common ways of doing it?\"\n", - "ai_msg_2 = rag_chain.invoke({\"input\": second_question, \"chat_history\": chat_history})\n", - "\n", - "print(ai_msg_2[\"answer\"])" + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", + "):\n", + " step[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", - "id": "53263a65-4de2-4dd8-9291-6a8169ab6f1d", + "id": "a26a9c4d-0e5b-4db9-8b78-68624d829ac2", "metadata": {}, "source": [ - ":::tip\n", - "\n", - "Check out the [LangSmith trace](https://smith.langchain.com/public/243301e4-4cc5-4e52-a6e7-8cfe9208398d/r).\n", - "\n", - ":::" + "Check out the LangSmith trace [here](https://smith.langchain.com/public/70110399-01d3-4b4b-9139-cbcd4edf9d6d/r)." ] }, { "cell_type": "markdown", - "id": "53a662c2-f38b-45f9-95c4-66de15637614", + "id": "c2300c04-019c-4c65-a104-3dbf17c924b7", "metadata": {}, "source": [ - "#### Stateful management of chat history\n", + "### Stateful management of chat history\n", "\n", ":::note\n", "\n", @@ -413,11 +537,11 @@ "Please see [How to migrate to LangGraph Memory](/docs/versions/migrating_memory/) for more details.\n", ":::\n", "\n", - "We have added application logic for incorporating chat history, but we are still manually plumbing it through our application. In production, the Q&A application will usually persist the chat history into a database, and be able to read and update it appropriately.\n", + "In production, the Q&A application will usually persist the chat history into a database, and be able to read and update it appropriately.\n", "\n", "[LangGraph](https://langchain-ai.github.io/langgraph/) implements a built-in [persistence layer](https://langchain-ai.github.io/langgraph/concepts/persistence/), making it ideal for chat applications that support multiple conversational turns.\n", "\n", - "Wrapping our chat model in a minimal LangGraph application allows us to automatically persist the message history, simplifying the development of multi-turn applications.\n", + "To manage multiple conversational turns and threads, all we have to do is specify a [checkpointer](https://langchain-ai.github.io/langgraph/concepts/persistence/) when compiling our application. Because the nodes in our graph are appending messages to the state, we will retain a consistent chat history across invocations.\n", "\n", "LangGraph comes with a simple in-memory checkpointer, which we use below. See its [documentation](https://langchain-ai.github.io/langgraph/concepts/persistence/) for more detail, including how to use different persistence backends (e.g., SQLite or Postgres).\n", "\n", @@ -426,121 +550,81 @@ }, { "cell_type": "code", - "execution_count": 8, - "id": "817f8528-ead4-47cd-a4b8-7a1cb8a6641f", + "execution_count": 15, + "id": "e5cd784a-61b2-4f9c-ad92-3e555b33d0bf", "metadata": {}, "outputs": [], "source": [ - "from typing import Sequence\n", - "\n", - "from langchain_core.messages import BaseMessage\n", "from langgraph.checkpoint.memory import MemorySaver\n", - "from langgraph.graph import START, StateGraph\n", - "from langgraph.graph.message import add_messages\n", - "from typing_extensions import Annotated, TypedDict\n", - "\n", - "\n", - "# We define a dict representing the state of the application.\n", - "# This state has the same input and output keys as `rag_chain`.\n", - "class State(TypedDict):\n", - " input: str\n", - " chat_history: Annotated[Sequence[BaseMessage], add_messages]\n", - " context: str\n", - " answer: str\n", - "\n", - "\n", - "# We then define a simple node that runs the `rag_chain`.\n", - "# The `return` values of the node update the graph state, so here we just\n", - "# update the chat history with the input message and response.\n", - "def call_model(state: State):\n", - " response = rag_chain.invoke(state)\n", - " return {\n", - " \"chat_history\": [\n", - " HumanMessage(state[\"input\"]),\n", - " AIMessage(response[\"answer\"]),\n", - " ],\n", - " \"context\": response[\"context\"],\n", - " \"answer\": response[\"answer\"],\n", - " }\n", - "\n", - "\n", - "# Our graph consists only of one node:\n", - "workflow = StateGraph(state_schema=State)\n", - "workflow.add_edge(START, \"model\")\n", - "workflow.add_node(\"model\", call_model)\n", - "\n", - "# Finally, we compile the graph with a checkpointer object.\n", - "# This persists the state, in this case in memory.\n", + "\n", "memory = MemorySaver()\n", - "app = workflow.compile(checkpointer=memory)" + "graph = graph_builder.compile(checkpointer=memory)\n", + "\n", + "# Specify an ID for the thread\n", + "config = {\"configurable\": {\"thread_id\": \"abc123\"}}" ] }, { "cell_type": "markdown", - "id": "6bda388e-c794-4ca5-b96f-0b12f1daaca3", + "id": "f557b169-b33c-42d0-b97e-1b948d0a2914", "metadata": {}, "source": [ - "This application out-of-the-box supports multiple conversation threads. We pass in a configuration `dict` specifying a unique identifier for a thread to control what thread is run. This enables the application to support interactions with multiple users." + "We can now invoke similar to before:" ] }, { "cell_type": "code", - "execution_count": 9, - "id": "efdd4bcd-4de8-4d9a-8f95-4dd6960efc0a", + "execution_count": 16, + "id": "c6d16477-52f5-4755-83d1-60eebddfaaa0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Task decomposition is the process of breaking down a complicated task into smaller, more manageable steps. Techniques like Chain of Thought (CoT) and Tree of Thoughts enhance this process by guiding models to think step by step and explore multiple reasoning possibilities. This approach helps in simplifying complex tasks and provides insight into the model's reasoning.\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What is Task Decomposition?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_JZb6GLD812bW2mQsJ5EJQDnN)\n", + " Call ID: call_JZb6GLD812bW2mQsJ5EJQDnN\n", + " Args:\n", + " query: Task Decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Task Decomposition is a technique used to break down complicated tasks into smaller, manageable steps. It involves using methods like Chain of Thought (CoT) prompting, which encourages the model to think step by step, enhancing performance on complex tasks. This process helps to clarify the model's reasoning and makes it easier to tackle difficult problems.\n" ] } ], "source": [ - "config = {\"configurable\": {\"thread_id\": \"abc123\"}}\n", + "input_message = \"What is Task Decomposition?\"\n", "\n", - "result = app.invoke(\n", - " {\"input\": \"What is Task Decomposition?\"},\n", + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", " config=config,\n", - ")\n", - "print(result[\"answer\"])" + "):\n", + " step[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "8ef6aefc-fe0e-457f-b552-303a45f47342", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "One way of doing task decomposition is by using simple prompting, such as asking the model, \"What are the subgoals for achieving XYZ?\" This method encourages the model to identify and outline the smaller tasks needed to accomplish the larger goal.\n" - ] - } - ], - "source": [ - "result = app.invoke(\n", - " {\"input\": \"What is one way of doing it?\"},\n", - " config=config,\n", - ")\n", - "print(result[\"answer\"])" - ] - }, - { - "cell_type": "markdown", - "id": "3ab59258-84bc-4904-880e-2ebfebbca563", - "metadata": {}, - "source": [ - "The conversation history can be inspected via the state of the application:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "eddfde25-6fac-4ba2-b52f-0682c73b9c15", + "execution_count": 17, + "id": "c9d6f0ee-b5a9-4141-9f6f-ad86a04e083f", "metadata": {}, "outputs": [ { @@ -549,302 +633,126 @@ "text": [ "================================\u001b[1m Human Message \u001b[0m=================================\n", "\n", - "What is Task Decomposition?\n", + "Can you look up some common ways of doing it?\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " retrieve (call_kjRI4Y5cJOiB73yvd7dmb6ux)\n", + " Call ID: call_kjRI4Y5cJOiB73yvd7dmb6ux\n", + " Args:\n", + " query: common methods of task decomposition\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: retrieve\n", "\n", - "Task decomposition is the process of breaking down a complicated task into smaller, more manageable steps. Techniques like Chain of Thought (CoT) and Tree of Thoughts enhance this process by guiding models to think step by step and explore multiple reasoning possibilities. This approach helps in simplifying complex tasks and provides insight into the model's reasoning.\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", "\n", - "What is one way of doing it?\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Component One: Planning#\n", + "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", + "Task Decomposition#\n", + "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "One way of doing task decomposition is by using simple prompting, such as asking the model, \"What are the subgoals for achieving XYZ?\" This method encourages the model to identify and outline the smaller tasks needed to accomplish the larger goal.\n" - ] - } - ], - "source": [ - "chat_history = app.get_state(config).values[\"chat_history\"]\n", - "for message in chat_history:\n", - " message.pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "0ab1ded4-76d9-453f-9b9b-db9a4560c737", - "metadata": {}, - "source": [ - "### Tying it together" - ] - }, - { - "cell_type": "markdown", - "id": "8a08a5ea-df5b-4547-93c6-2a3940dd5c3e", - "metadata": {}, - "source": [ - "![](../../static/img/conversational_retrieval_chain.png)\n", - "\n", - "For convenience, we tie together all of the necessary steps in a single code cell:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "71c32048-1a41-465f-a9e2-c4affc332fd9", - "metadata": {}, - "outputs": [], - "source": [ - "from typing import Sequence\n", - "\n", - "import bs4\n", - "from langchain.chains import create_history_aware_retriever, create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", - "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.messages import AIMessage, BaseMessage, HumanMessage\n", - "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n", - "from langchain_core.vectorstores import InMemoryVectorStore\n", - "from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "from langgraph.checkpoint.memory import MemorySaver\n", - "from langgraph.graph import START, StateGraph\n", - "from langgraph.graph.message import add_messages\n", - "from typing_extensions import Annotated, TypedDict\n", - "\n", - "llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)\n", - "\n", - "\n", - "### Construct retriever ###\n", - "loader = WebBaseLoader(\n", - " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", - " bs_kwargs=dict(\n", - " parse_only=bs4.SoupStrainer(\n", - " class_=(\"post-content\", \"post-title\", \"post-header\")\n", - " )\n", - " ),\n", - ")\n", - "docs = loader.load()\n", - "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = InMemoryVectorStore.from_documents(\n", - " documents=splits, embedding=OpenAIEmbeddings()\n", - ")\n", - "retriever = vectorstore.as_retriever()\n", - "\n", - "\n", - "### Contextualize question ###\n", - "contextualize_q_system_prompt = (\n", - " \"Given a chat history and the latest user question \"\n", - " \"which might reference context in the chat history, \"\n", - " \"formulate a standalone question which can be understood \"\n", - " \"without the chat history. Do NOT answer the question, \"\n", - " \"just reformulate it if needed and otherwise return it as is.\"\n", - ")\n", - "contextualize_q_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", contextualize_q_system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "history_aware_retriever = create_history_aware_retriever(\n", - " llm, retriever, contextualize_q_prompt\n", - ")\n", - "\n", - "\n", - "### Answer question ###\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "qa_prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " MessagesPlaceholder(\"chat_history\"),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", - "question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)\n", - "\n", - "rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)\n", - "\n", - "\n", - "### Statefully manage chat history ###\n", - "class State(TypedDict):\n", - " input: str\n", - " chat_history: Annotated[Sequence[BaseMessage], add_messages]\n", - " context: str\n", - " answer: str\n", - "\n", - "\n", - "def call_model(state: State):\n", - " response = rag_chain.invoke(state)\n", - " return {\n", - " \"chat_history\": [\n", - " HumanMessage(state[\"input\"]),\n", - " AIMessage(response[\"answer\"]),\n", - " ],\n", - " \"context\": response[\"context\"],\n", - " \"answer\": response[\"answer\"],\n", - " }\n", - "\n", - "\n", - "workflow = StateGraph(state_schema=State)\n", - "workflow.add_edge(START, \"model\")\n", - "workflow.add_node(\"model\", call_model)\n", - "\n", - "memory = MemorySaver()\n", - "app = workflow.compile(checkpointer=memory)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "6d0a7a73-d151-47d9-9e99-b4f3291c0322", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Task decomposition is the process of breaking down a complicated task into smaller, more manageable steps. Techniques like Chain of Thought (CoT) and Tree of Thoughts enhance this process by guiding models to think step by step and explore multiple reasoning possibilities. This approach helps in simplifying complex tasks and improving the model's performance.\n" + "Common ways of performing Task Decomposition include: (1) using Large Language Models (LLMs) with simple prompts like \"Steps for XYZ\" or \"What are the subgoals for achieving XYZ?\", (2) employing task-specific instructions such as \"Write a story outline\" for specific tasks, and (3) incorporating human inputs to guide the decomposition process.\n" ] } ], "source": [ - "config = {\"configurable\": {\"thread_id\": \"abc123\"}}\n", + "input_message = \"Can you look up some common ways of doing it?\"\n", "\n", - "result = app.invoke(\n", - " {\"input\": \"What is Task Decomposition?\"},\n", + "for step in graph.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", + " stream_mode=\"values\",\n", " config=config,\n", - ")\n", - "print(result[\"answer\"])" + "):\n", + " step[\"messages\"][-1].pretty_print()" ] }, { - "cell_type": "code", - "execution_count": 14, - "id": "17021822-896a-4513-a17d-1d20b1c5381c", + "cell_type": "markdown", + "id": "4bbbeef2-d9a1-4857-874f-9f3b5cc4eca9", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "One way of doing task decomposition is by using simple prompting, such as asking the model, \"What are the subgoals for achieving XYZ?\" This method encourages the model to identify and outline the smaller steps needed to complete the larger task.\n" - ] - } - ], "source": [ - "result = app.invoke(\n", - " {\"input\": \"What is one way of doing it?\"},\n", - " config=config,\n", - ")\n", - "print(result[\"answer\"])" + "Note that the query generated by the model in the second question incorporates the conversational context.\n", + "\n", + "The [LangSmith](https://smith.langchain.com/public/28e6179f-fc56-45e1-9028-447d76352c14/r) trace is particularly informative here, as we can see exactly what messages are visible to our chat model at each step." ] }, { "cell_type": "markdown", - "id": "861da8ed-d890-4fdc-a3bf-30433db61e0d", + "id": "0ad23c71-3c99-4d9d-b494-9b7a08a557c0", "metadata": {}, "source": [ "## Agents {#agents}\n", "\n", - "Agents leverage the reasoning capabilities of LLMs to make decisions during execution. Using agents allow you to offload some discretion over the retrieval process. Although their behavior is less predictable than chains, they offer some advantages in this context:\n", + "[Agents](/docs/concepts/agents) leverage the reasoning capabilities of LLMs to make decisions during execution. Using agents allows you to offload additional discretion over the retrieval process. Although their behavior is less predictable than the above \"chain\", they are able to execute multiple retrieval steps in service of a query, or iterate on a single search.\n", "\n", - "- Agents generate the input to the retriever directly, without necessarily needing us to explicitly build in contextualization, as we did above;\n", - "- Agents can execute multiple retrieval steps in service of a query, or refrain from executing a retrieval step altogether (e.g., in response to a generic greeting from a user).\n", + "Below we assemble a minimal RAG agent. Using LangGraph's [pre-built ReAct agent constructor](https://langchain-ai.github.io/langgraph/how-tos/#langgraph.prebuilt.chat_agent_executor.create_react_agent), we can do this in one line.\n", "\n", - "### Retrieval tool\n", + ":::tip\n", "\n", - "Agents can access \"tools\" and manage their execution. In this case, we will convert our retriever into a LangChain tool to be wielded by the agent:" + "Check out LangGraph's [Agentic RAG](https://langchain-ai.github.io/langgraph/tutorials/rag/langgraph_agentic_rag/) tutorial for more advanced formulations.\n", + "\n", + ":::" ] }, { "cell_type": "code", - "execution_count": 15, - "id": "809cc747-2135-40a2-8e73-e4556343ee64", + "execution_count": 18, + "id": "470d5996-527d-4ef1-9e31-2c259cc3c050", "metadata": {}, "outputs": [], "source": [ - "from langchain.tools.retriever import create_retriever_tool\n", + "from langgraph.prebuilt import create_react_agent\n", "\n", - "tool = create_retriever_tool(\n", - " retriever,\n", - " \"blog_post_retriever\",\n", - " \"Searches and returns excerpts from the Autonomous Agents blog post.\",\n", - ")\n", - "tools = [tool]" + "agent_executor = create_react_agent(llm, [retrieve], checkpointer=memory)" ] }, { "cell_type": "markdown", - "id": "07dcb968-ed9a-458a-85e1-528cd28c6965", + "id": "7d8f8734-5dcf-4058-a532-11c8a7d0efae", "metadata": {}, "source": [ - "Tools are LangChain [Runnables](/docs/concepts/lcel), and implement the usual interface:" + "Let's inspect the graph:" ] }, { "cell_type": "code", - "execution_count": 16, - "id": "1c8df9d7-6a74-471c-aaef-6c4819ee0cd0", + "execution_count": 19, + "id": "0907cef3-05cb-45c7-ab46-382c58c52eb1", "metadata": {}, "outputs": [ { "data": { + "image/png": "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", "text/plain": [ - "'Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\\n\\nFig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\\n\\n(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user\\'s request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\\n\\nFig. 11. Illustration of how HuggingGPT works. (Image source: Shen et al. 2023)\\nThe system comprises of 4 stages:\\n(1) Task planning: LLM works as the brain and parses the user requests into multiple tasks. There are four attributes associated with each task: task type, ID, dependencies, and arguments. They use few-shot examples to guide LLM to do task parsing and planning.\\nInstruction:'" + "" ] }, - "execution_count": 16, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "tool.invoke(\"task decomposition\")" + "display(Image(agent_executor.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "markdown", - "id": "f77e0217-28be-4b8b-b4c4-9cc4ed5ec201", - "metadata": {}, - "source": [ - "### Agent constructor\n", - "\n", - "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/architecture/#langgraph) to construct the agent. \n", - "Currently we are using a high level interface to construct the agent, but the nice thing about LangGraph is that this high-level interface is backed by a low-level, highly controllable API in case you want to modify the agent logic." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "1726d151-4653-4c72-a187-a14840add526", + "id": "28623a52-7906-440f-8aaf-d6bb5ecbad98", "metadata": {}, - "outputs": [], "source": [ - "from langgraph.prebuilt import create_react_agent\n", + "The key difference from our earlier implementation is that instead of a final generation step that ends the run, here the tool invocation loops back to the original LLM call. The model can then either answer the question using the retrieved context, or generate another tool call to obtain more information.\n", "\n", - "agent_executor = create_react_agent(llm, tools)" - ] - }, - { - "cell_type": "markdown", - "id": "6d5152ca-1c3b-4f58-bb28-f31c0be7ba66", - "metadata": {}, - "source": [ - "We can now try it out. Note that so far it is not stateful (we still need to add in memory)" + "Let's test this out. We construct a question that would typically require an iterative sequence of retrieval steps to answer:" ] }, { "cell_type": "code", - "execution_count": 18, - "id": "170403a2-c914-41db-85d8-a2c381da112d", + "execution_count": 33, + "id": "a2f48f92-bd91-4033-a01b-7bd0667e3d87", "metadata": {}, "outputs": [ { @@ -853,376 +761,110 @@ "text": [ "================================\u001b[1m Human Message \u001b[0m=================================\n", "\n", - "What is Task Decomposition?\n", + "What is the standard method for Task Decomposition?\n", + "\n", + "Once you get the answer, look up common extensions of that method.\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "Tool Calls:\n", - " blog_post_retriever (call_WKHdiejvg4In982Hr3EympuI)\n", - " Call ID: call_WKHdiejvg4In982Hr3EympuI\n", + " retrieve (call_Y3YaIzL71B83Cjqa8d2G0O8N)\n", + " Call ID: call_Y3YaIzL71B83Cjqa8d2G0O8N\n", " Args:\n", - " query: Task Decomposition\n", + " query: standard method for Task Decomposition\n", "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: blog_post_retriever\n", - "\n", - "Fig. 1. Overview of a LLM-powered autonomous agent system.\n", - "Component One: Planning#\n", - "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", - "Task Decomposition#\n", - "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", + "Name: retrieve\n", "\n", - "Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", "\n", - "(3) Task execution: Expert models execute on the specific tasks and log results.\n", - "Instruction:\n", - "\n", - "With the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\n", - "\n", - "Fig. 11. Illustration of how HuggingGPT works. (Image source: Shen et al. 2023)\n", - "The system comprises of 4 stages:\n", - "(1) Task planning: LLM works as the brain and parses the user requests into multiple tasks. There are four attributes associated with each task: task type, ID, dependencies, and arguments. They use few-shot examples to guide LLM to do task parsing and planning.\n", - "Instruction:\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Task Decomposition is a process used in complex problem-solving where a larger task is broken down into smaller, more manageable sub-tasks. This approach enhances the ability of models, particularly large language models (LLMs), to handle intricate tasks by allowing them to think step by step.\n", - "\n", - "There are several methods for task decomposition:\n", - "\n", - "1. **Chain of Thought (CoT)**: This technique encourages the model to articulate its reasoning process by thinking through the task in a sequential manner. It transforms a big task into smaller, manageable steps, which also provides insight into the model's thought process.\n", - "\n", - "2. **Tree of Thoughts**: An extension of CoT, this method explores multiple reasoning possibilities at each step. It decomposes the problem into various thought steps and generates multiple thoughts for each step, creating a tree structure. The evaluation of each state can be done using breadth-first search (BFS) or depth-first search (DFS).\n", - "\n", - "3. **Prompting Techniques**: Task decomposition can be achieved through simple prompts like \"Steps for XYZ\" or \"What are the subgoals for achieving XYZ?\" Additionally, task-specific instructions can guide the model, such as asking it to \"Write a story outline\" for creative tasks.\n", - "\n", - "4. **Human Inputs**: In some cases, human guidance can be used to assist in breaking down tasks.\n", - "\n", - "Overall, task decomposition is a crucial component in planning and executing complex tasks, allowing for better organization and clarity in the problem-solving process.\n" - ] - } - ], - "source": [ - "query = \"What is Task Decomposition?\"\n", - "\n", - "for event in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=query)]},\n", - " stream_mode=\"values\",\n", - "):\n", - " event[\"messages\"][-1].pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "1df703b1-aad6-48fb-b6fa-703e32ea88b9", - "metadata": {}, - "source": [ - "We can again take advantage of LangGraph's built-in persistence to save stateful updates to memory:" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "04a3a664-3c3f-4cd1-9995-26662a52da7c", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.checkpoint.memory import MemorySaver\n", - "\n", - "memory = MemorySaver()\n", - "\n", - "agent_executor = create_react_agent(llm, tools, checkpointer=memory)" - ] - }, - { - "cell_type": "markdown", - "id": "02026f78-338e-4d18-9f05-131e1dd59197", - "metadata": {}, - "source": [ - "This is all we need to construct a conversational RAG agent.\n", - "\n", - "Let's observe its behavior. Note that if we input a query that does not require a retrieval step, the agent does not execute one:" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "d6d70833-b958-4cd7-9e27-29c1c08bb1b8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "Hi! I'm bob\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hello Bob! How can I assist you today?\n" - ] - } - ], - "source": [ - "config = {\"configurable\": {\"thread_id\": \"abc123\"}}\n", - "\n", - "for event in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=\"Hi! I'm bob\")]},\n", - " config=config,\n", - " stream_mode=\"values\",\n", - "):\n", - " event[\"messages\"][-1].pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "a7928865-3dd6-4d36-abc6-2a30de770d09", - "metadata": {}, - "source": [ - "Further, if we input a query that does require a retrieval step, the agent generates the input to the tool:" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "e2c570ae-dd91-402c-8693-ae746de63b16", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What is Task Decomposition?\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " blog_post_retriever (call_0rhrUJiHkoOQxwqCpKTkSkiu)\n", - " Call ID: call_0rhrUJiHkoOQxwqCpKTkSkiu\n", - " Args:\n", - " query: Task Decomposition\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: blog_post_retriever\n", - "\n", - "Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", "Component One: Planning#\n", "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", "Task Decomposition#\n", "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", - "\n", - "Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", - "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", - "\n", - "(3) Task execution: Expert models execute on the specific tasks and log results.\n", - "Instruction:\n", - "\n", - "With the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\n", - "\n", - "Fig. 11. Illustration of how HuggingGPT works. (Image source: Shen et al. 2023)\n", - "The system comprises of 4 stages:\n", - "(1) Task planning: LLM works as the brain and parses the user requests into multiple tasks. There are four attributes associated with each task: task type, ID, dependencies, and arguments. They use few-shot examples to guide LLM to do task parsing and planning.\n", - "Instruction:\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Task Decomposition is a technique used to break down complex tasks into smaller, more manageable steps. This approach is particularly useful in the context of autonomous agents and large language models (LLMs). Here are some key points about Task Decomposition:\n", - "\n", - "1. **Chain of Thought (CoT)**: This is a prompting technique that encourages the model to \"think step by step.\" By doing so, it can utilize more computational resources to decompose difficult tasks into simpler ones, making them easier to handle.\n", - "\n", - "2. **Tree of Thoughts**: An extension of CoT, this method explores multiple reasoning possibilities at each step. It decomposes a problem into various thought steps and generates multiple thoughts for each step, creating a tree structure. This can be evaluated using search methods like breadth-first search (BFS) or depth-first search (DFS).\n", - "\n", - "3. **Methods of Decomposition**: Task decomposition can be achieved through:\n", - " - Simple prompting (e.g., asking for steps to achieve a goal).\n", - " - Task-specific instructions (e.g., requesting a story outline for writing).\n", - " - Human inputs to guide the decomposition process.\n", - "\n", - "4. **Execution**: After decomposition, expert models execute the specific tasks and log the results, allowing for a structured approach to complex problem-solving.\n", - "\n", - "Overall, Task Decomposition enhances the model's ability to tackle intricate tasks by breaking them down into simpler, actionable components.\n" - ] - } - ], - "source": [ - "query = \"What is Task Decomposition?\"\n", - "\n", - "for event in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=query)]},\n", - " config=config,\n", - " stream_mode=\"values\",\n", - "):\n", - " event[\"messages\"][-1].pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "26eaae33-3c4e-49fc-9fc6-db8967e25579", - "metadata": {}, - "source": [ - "Above, instead of inserting our query verbatim into the tool, the agent stripped unnecessary words like \"what\" and \"is\".\n", - "\n", - "This same principle allows the agent to use the context of the conversation when necessary:" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "570d8c68-136e-4ba5-969a-03ba195f6118", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What according to the blog post are common ways of doing it? redo the search\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "Tool Calls:\n", - " blog_post_retriever (call_bZRDF6Xr0QdurM9LItM8cN7a)\n", - " Call ID: call_bZRDF6Xr0QdurM9LItM8cN7a\n", + " retrieve (call_2JntP1x4XQMWwgVpYurE12ff)\n", + " Call ID: call_2JntP1x4XQMWwgVpYurE12ff\n", " Args:\n", - " query: common ways of Task Decomposition\n", + " query: common extensions of Task Decomposition methods\n", "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: blog_post_retriever\n", + "Name: retrieve\n", "\n", - "Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n", "\n", - "Fig. 1. Overview of a LLM-powered autonomous agent system.\n", + "Source: {'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "Content: Fig. 1. Overview of a LLM-powered autonomous agent system.\n", "Component One: Planning#\n", "A complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\n", "Task Decomposition#\n", "Chain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.\n", - "\n", - "Resources:\n", - "1. Internet access for searches and information gathering.\n", - "2. Long Term memory management.\n", - "3. GPT-3.5 powered Agents for delegation of simple tasks.\n", - "4. File output.\n", - "\n", - "Performance Evaluation:\n", - "1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\n", - "2. Constructively self-criticize your big-picture behavior constantly.\n", - "3. Reflect on past decisions and strategies to refine your approach.\n", - "4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.\n", - "\n", - "(3) Task execution: Expert models execute on the specific tasks and log results.\n", - "Instruction:\n", - "\n", - "With the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "\n", - "According to the blog post, common ways to perform Task Decomposition include:\n", + "The standard method for task decomposition involves using techniques such as Chain of Thought (CoT), where a model is instructed to \"think step by step\" to break down complex tasks into smaller, more manageable components. This approach enhances model performance by allowing for more thorough reasoning and planning. Task decomposition can be accomplished through various means, including:\n", "\n", - "1. **Simple Prompting**: Using straightforward prompts such as \"Steps for XYZ.\\n1.\" or \"What are the subgoals for achieving XYZ?\" to guide the model in breaking down the task.\n", + "1. Simple prompting (e.g., asking for steps to achieve a goal).\n", + "2. Task-specific instructions (e.g., asking for a story outline).\n", + "3. Human inputs to guide the decomposition process.\n", "\n", - "2. **Task-Specific Instructions**: Providing specific instructions tailored to the task at hand, such as asking for a \"story outline\" when writing a novel.\n", + "### Common Extensions of Task Decomposition Methods:\n", "\n", - "3. **Human Inputs**: Involving human guidance or input to assist in the decomposition process, allowing for a more nuanced understanding of the task requirements.\n", + "1. **Tree of Thoughts**: This extension builds on CoT by not only decomposing the problem into thought steps but also generating multiple thoughts at each step, creating a tree structure. The search process can employ breadth-first search (BFS) or depth-first search (DFS), with each state evaluated by a classifier or through majority voting.\n", "\n", - "These methods help in transforming complex tasks into smaller, manageable components, facilitating better planning and execution.\n" + "These extensions aim to enhance reasoning capabilities and improve the effectiveness of task decomposition in various contexts.\n" ] } ], "source": [ - "query = \"What according to the blog post are common ways of doing it? redo the search\"\n", + "config = {\"configurable\": {\"thread_id\": \"def234\"}}\n", + "\n", + "input_message = (\n", + " \"What is the standard method for Task Decomposition?\\n\\n\"\n", + " \"Once you get the answer, look up common extensions of that method.\"\n", + ")\n", "\n", "for event in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=query)]},\n", - " config=config,\n", + " {\"messages\": [{\"role\": \"user\", \"content\": input_message}]},\n", " stream_mode=\"values\",\n", + " config=config,\n", "):\n", " event[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", - "id": "f2724616-c106-4e15-a61a-3077c535f692", - "metadata": {}, - "source": [ - "Note that the agent was able to infer that \"it\" in our query refers to \"task decomposition\", and generated a reasonable search query as a result-- in this case, \"common ways of task decomposition\"." - ] - }, - { - "cell_type": "markdown", - "id": "1cf87847-23bb-4672-b41c-12ad9cf81ed4", + "id": "47ab58d2-92ef-4940-a535-7c8808e75523", "metadata": {}, "source": [ - "### Tying it together\n", - "\n", - "For convenience, we tie together all of the necessary steps in a single code cell:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "b1d2b4d4-e604-497d-873d-d345b808578e", - "metadata": {}, - "outputs": [], - "source": [ - "import bs4\n", - "from langchain.tools.retriever import create_retriever_tool\n", - "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.vectorstores import InMemoryVectorStore\n", - "from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "from langgraph.checkpoint.memory import MemorySaver\n", - "from langgraph.prebuilt import create_react_agent\n", - "\n", - "memory = MemorySaver()\n", - "llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)\n", - "\n", + "Note that the agent:\n", "\n", - "### Construct retriever ###\n", - "loader = WebBaseLoader(\n", - " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", - " bs_kwargs=dict(\n", - " parse_only=bs4.SoupStrainer(\n", - " class_=(\"post-content\", \"post-title\", \"post-header\")\n", - " )\n", - " ),\n", - ")\n", - "docs = loader.load()\n", + "1. Generates a query to search for a standard method for task decomposition;\n", + "2. Receiving the answer, generates a second query to search for common extensions of it;\n", + "3. Having received all necessary context, answers the question.\n", "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = InMemoryVectorStore.from_documents(\n", - " documents=splits, embedding=OpenAIEmbeddings()\n", - ")\n", - "retriever = vectorstore.as_retriever()\n", + "We can see the full sequence of steps, along with latency and other metadata, in the [LangSmith trace](https://smith.langchain.com/public/48cbd35e-9ac1-49ab-8c09-500d54c06b81/r).\n", "\n", - "\n", - "### Build retriever tool ###\n", - "tool = create_retriever_tool(\n", - " retriever,\n", - " \"blog_post_retriever\",\n", - " \"Searches and returns excerpts from the Autonomous Agents blog post.\",\n", - ")\n", - "tools = [tool]\n", - "\n", - "\n", - "agent_executor = create_react_agent(llm, tools, checkpointer=memory)" - ] - }, - { - "cell_type": "markdown", - "id": "cd6bf4f4-74f4-419d-9e26-f0ed83cf05fa", - "metadata": {}, - "source": [ "## Next steps\n", "\n", "We've covered the steps to build a basic conversational Q&A application:\n", "\n", - "- We used chains to build a predictable application that generates search queries for each user input;\n", - "- We used agents to build an application that \"decides\" when and how to generate search queries.\n", + "- We used chains to build a predictable application that generates at most one query per user input;\n", + "- We used agents to build an application that can iterate on a sequence of queries.\n", "\n", "To explore different types of retrievers and retrieval strategies, visit the [retrievers](/docs/how_to/#retrievers) section of the how-to guides.\n", "\n", "For a detailed walkthrough of LangChain's conversation memory abstractions, visit the [How to add message history (memory)](/docs/how_to/message_history) guide.\n", "\n", - "To learn more about agents, head to the [Agents Modules](/docs/tutorials/agents)." + "To learn more about agents, check out the [conceptual guide](/docs/concepts/agents) and LangGraph [agent architectures](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/) page." ] }, { "cell_type": "code", "execution_count": null, - "id": "b8d17592-6240-49ac-a904-f0171eddcc14", + "id": "97b7c675-4011-43d2-9a6a-ddcf75fec536", "metadata": {}, "outputs": [], "source": [] @@ -1244,7 +886,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/query_analysis.ipynb b/docs/docs/tutorials/query_analysis.ipynb deleted file mode 100644 index c5bf42f4ce8d0..0000000000000 --- a/docs/docs/tutorials/query_analysis.ipynb +++ /dev/null @@ -1,605 +0,0 @@ -{ - "cells": [ - { - "cell_type": "raw", - "id": "df7d42b9-58a6-434c-a2d7-0b61142f6d3e", - "metadata": {}, - "source": [ - "---\n", - "sidebar_position: 0\n", - "---" - ] - }, - { - "cell_type": "markdown", - "id": "f2195672-0cab-4967-ba8a-c6544635547d", - "metadata": {}, - "source": [ - "# Build a Query Analysis System\n", - "\n", - ":::info Prerequisites\n", - "\n", - "This guide assumes familiarity with the following concepts:\n", - "\n", - "- [Document loaders](/docs/concepts/document_loaders)\n", - "- [Chat models](/docs/concepts/chat_models)\n", - "- [Embeddings](/docs/concepts/embedding_models)\n", - "- [Vector stores](/docs/concepts/vectorstores)\n", - "- [Retrieval](/docs/concepts/retrieval)\n", - "\n", - ":::\n", - "\n", - "This page will show how to use query analysis in a basic end-to-end example. This will cover creating a simple search engine, showing a failure mode that occurs when passing a raw user question to that search, and then an example of how query analysis can help address that issue. There are MANY different query analysis techniques and this end-to-end example will not show all of them.\n", - "\n", - "For the purpose of this example, we will do retrieval over the LangChain YouTube videos." - ] - }, - { - "cell_type": "markdown", - "id": "a4079b57-4369-49c9-b2ad-c809b5408d7e", - "metadata": {}, - "source": [ - "## Setup\n", - "#### Install dependencies" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "e168ef5c-e54e-49a6-8552-5502854a6f01", - "metadata": {}, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "%pip install -qU langchain langchain-community langchain-openai youtube-transcript-api pytube langchain-chroma" - ] - }, - { - "cell_type": "markdown", - "id": "79d66a45-a05c-4d22-b011-b1cdbdfc8f9c", - "metadata": {}, - "source": [ - "#### Set environment variables\n", - "\n", - "We'll use OpenAI in this example:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "40e2979e-a818-4b96-ac25-039336f94319", - "metadata": {}, - "outputs": [], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "if \"OPENAI_API_KEY\" not in os.environ:\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n", - "\n", - "# Optional, uncomment to trace runs with LangSmith. Sign up here: https://smith.langchain.com.\n", - "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", - "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()" - ] - }, - { - "cell_type": "markdown", - "id": "c20b48b8-16d7-4089-bc17-f2d240b3935a", - "metadata": {}, - "source": [ - "### Load documents\n", - "\n", - "We can use the `YouTubeLoader` to load transcripts of a few LangChain videos:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "ae6921e1-3d5a-431c-9999-29a5f33201e1", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_community.document_loaders import YoutubeLoader\n", - "\n", - "urls = [\n", - " \"https://www.youtube.com/watch?v=HAn9vnJy6S4\",\n", - " \"https://www.youtube.com/watch?v=dA1cHGACXCo\",\n", - " \"https://www.youtube.com/watch?v=ZcEMLz27sL4\",\n", - " \"https://www.youtube.com/watch?v=hvAPnpSfSGo\",\n", - " \"https://www.youtube.com/watch?v=EhlPDL4QrWY\",\n", - " \"https://www.youtube.com/watch?v=mmBo8nlu2j0\",\n", - " \"https://www.youtube.com/watch?v=rQdibOsL1ps\",\n", - " \"https://www.youtube.com/watch?v=28lC4fqukoc\",\n", - " \"https://www.youtube.com/watch?v=es-9MgxB-uc\",\n", - " \"https://www.youtube.com/watch?v=wLRHwKuKvOE\",\n", - " \"https://www.youtube.com/watch?v=ObIltMaRJvY\",\n", - " \"https://www.youtube.com/watch?v=DjuXACWYkkU\",\n", - " \"https://www.youtube.com/watch?v=o7C9ld6Ln-M\",\n", - "]\n", - "docs = []\n", - "for url in urls:\n", - " docs.extend(YoutubeLoader.from_youtube_url(url, add_video_info=True).load())" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "2b84918e", - "metadata": {}, - "outputs": [], - "source": [ - "import datetime\n", - "\n", - "# Add some additional metadata: what year the video was published\n", - "for doc in docs:\n", - " doc.metadata[\"publish_year\"] = int(\n", - " datetime.datetime.strptime(\n", - " doc.metadata[\"publish_date\"], \"%Y-%m-%d %H:%M:%S\"\n", - " ).strftime(\"%Y\")\n", - " )" - ] - }, - { - "cell_type": "markdown", - "id": "ce7da456-3023-4f04-bba1-f7e2c468c7fe", - "metadata": {}, - "source": [ - "Here are the titles of the videos we've loaded:" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "3e1a99ee-1078-4373-b80a-630af48bf94a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['OpenGPTs',\n", - " 'Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve',\n", - " 'Streaming Events: Introducing a new `stream_events` method',\n", - " 'LangGraph: Multi-Agent Workflows',\n", - " 'Build and Deploy a RAG app with Pinecone Serverless',\n", - " 'Auto-Prompt Builder (with Hosted LangServe)',\n", - " 'Build a Full Stack RAG App With TypeScript',\n", - " 'Getting Started with Multi-Modal LLMs',\n", - " 'SQL Research Assistant',\n", - " 'Skeleton-of-Thought: Building a New Template from Scratch',\n", - " 'Benchmarking RAG over LangChain Docs',\n", - " 'Building a Research Assistant from Scratch',\n", - " 'LangServe and LangChain Templates Webinar']" - ] - }, - "execution_count": 59, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "[doc.metadata[\"title\"] for doc in docs]" - ] - }, - { - "cell_type": "markdown", - "id": "05a71032-14c3-4517-aa9a-3a5e88eaeb92", - "metadata": {}, - "source": [ - "Here's the metadata associated with each video. We can see that each document also has a title, view count, publication date, and length:" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "c7748415-ddbf-4c55-a242-c28833c03caf", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'source': 'HAn9vnJy6S4',\n", - " 'title': 'OpenGPTs',\n", - " 'description': 'Unknown',\n", - " 'view_count': 7210,\n", - " 'thumbnail_url': 'https://i.ytimg.com/vi/HAn9vnJy6S4/hq720.jpg',\n", - " 'publish_date': '2024-01-31 00:00:00',\n", - " 'length': 1530,\n", - " 'author': 'LangChain',\n", - " 'publish_year': 2024}" - ] - }, - "execution_count": 60, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "docs[0].metadata" - ] - }, - { - "cell_type": "markdown", - "id": "5db72331-1e79-4910-8faa-473a0e370277", - "metadata": {}, - "source": [ - "And here's a sample from a document's contents:" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "845149b7-130e-4228-ac80-d0a9286ef1d3", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "\"hello today I want to talk about open gpts open gpts is a project that we built here at linkchain uh that replicates the GPT store in a few ways so it creates uh end user-facing friendly interface to create different Bots and these Bots can have access to different tools and they can uh be given files to retrieve things over and basically it's a way to create a variety of bots and expose the configuration of these Bots to end users it's all open source um it can be used with open AI it can be us\"" - ] - }, - "execution_count": 61, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "docs[0].page_content[:500]" - ] - }, - { - "cell_type": "markdown", - "id": "561697c8-b848-4b12-847c-ab6a8e2d1ae6", - "metadata": {}, - "source": [ - "### Indexing documents\n", - "\n", - "Whenever we perform retrieval we need to create an index of documents that we can query. We'll use a vector store to index our documents, and we'll chunk them first to make our retrievals more concise and precise:" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "1f621694", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_chroma import Chroma\n", - "from langchain_openai import OpenAIEmbeddings\n", - "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", - "\n", - "text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000)\n", - "chunked_docs = text_splitter.split_documents(docs)\n", - "embeddings = OpenAIEmbeddings(model=\"text-embedding-3-small\")\n", - "vectorstore = Chroma.from_documents(\n", - " chunked_docs,\n", - " embeddings,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "483d8d0a-5c1b-46b0-862c-a4eccfd5ae3c", - "metadata": {}, - "source": [ - "## Retrieval without query analysis\n", - "\n", - "We can perform similarity search on a user question directly to find chunks relevant to the question:" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "id": "09435e9b-57b4-41b1-b34a-449815bdfae0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Build and Deploy a RAG app with Pinecone Serverless\n", - "hi this is Lance from the Lang chain team and today we're going to be building and deploying a rag app using pine con serval list from scratch so we're going to kind of walk through all the code required to do this and I'll use these slides as kind of a guide to kind of lay the the ground work um so first what is rag so under capoy has this pretty nice visualization that shows LMS as a kernel of a new kind of operating system and of course one of the core components of our operating system is th\n" - ] - } - ], - "source": [ - "search_results = vectorstore.similarity_search(\"how do I build a RAG agent\")\n", - "print(search_results[0].metadata[\"title\"])\n", - "print(search_results[0].page_content[:500])" - ] - }, - { - "cell_type": "markdown", - "id": "5a79ef1b-7edd-4b68-98e5-c0e4c0dd02e6", - "metadata": {}, - "source": [ - "This works pretty well! Our first result is quite relevant to the question.\n" - ] - }, - { - "cell_type": "markdown", - "id": "a891e8f5-ef0c-4ec0-b25f-eda7a5350a85", - "metadata": {}, - "source": [ - "What if we wanted to search for results from a specific time period?" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "7adbfc11-ca01-4883-8978-e4f6e4a1d23d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OpenGPTs\n", - "2024-01-31\n", - "hardcoded that it will always do a retrieval step here the assistant decides whether to do a retrieval step or not sometimes this is good sometimes this is bad sometimes it you don't need to do a retrieval step when I said hi it didn't need to call it tool um but other times you know the the llm might mess up and not realize that it needs to do a retrieval step and so the rag bot will always do a retrieval step so it's more focused there because this is also a simpler architecture so it's always\n" - ] - } - ], - "source": [ - "search_results = vectorstore.similarity_search(\"videos on RAG published in 2023\")\n", - "print(search_results[0].metadata[\"title\"])\n", - "print(search_results[0].metadata[\"publish_date\"])\n", - "print(search_results[0].page_content[:500])" - ] - }, - { - "cell_type": "markdown", - "id": "4790e2db-3c6e-440b-b6e8-ebdd6600fda5", - "metadata": {}, - "source": [ - "Our first result is from 2024 (despite us asking for videos from 2023), and not very relevant to the input. Since we're just searching against document contents, there's no way for the results to be filtered on any document attributes.\n", - "\n", - "This is just one failure mode that can arise. Let's now take a look at how a basic form of query analysis can fix it!" - ] - }, - { - "cell_type": "markdown", - "id": "57396e23-c192-4d97-846b-5eacea4d6b8d", - "metadata": {}, - "source": [ - "## Query analysis\n", - "\n", - "We can use query analysis to improve the results of retrieval. This will involve defining a **query schema** that contains some date filters and use a function-calling model to convert a user question into a structured queries. \n", - "\n", - "### Query schema\n", - "In this case we'll have explicit min and max attributes for publication date so that it can be filtered on." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "0b51dd76-820d-41a4-98c8-893f6fe0d1ea", - "metadata": {}, - "outputs": [], - "source": [ - "from typing import Optional\n", - "\n", - "from pydantic import BaseModel, Field\n", - "\n", - "\n", - "class Search(BaseModel):\n", - " \"\"\"Search over a database of tutorial videos about a software library.\"\"\"\n", - "\n", - " query: str = Field(\n", - " ...,\n", - " description=\"Similarity search query applied to video transcripts.\",\n", - " )\n", - " publish_year: Optional[int] = Field(None, description=\"Year video was published\")" - ] - }, - { - "cell_type": "markdown", - "id": "f8b08c52-1ce9-4d8b-a779-cbe8efde51d1", - "metadata": {}, - "source": [ - "### Query generation\n", - "\n", - "To convert user questions to structured queries we'll make use of OpenAI's tool-calling API. Specifically we'll use the new [ChatModel.with_structured_output()](/docs/how_to/structured_output) constructor to handle passing the schema to the model and parsing the output." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "783c03c3-8c72-4f88-9cf4-5829ce6745d6", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/bagatur/langchain/libs/core/langchain_core/_api/beta_decorator.py:86: LangChainBetaWarning: The function `with_structured_output` is in beta. It is actively being worked on, so the API may change.\n", - " warn_beta(\n" - ] - } - ], - "source": [ - "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "from langchain_openai import ChatOpenAI\n", - "\n", - "system = \"\"\"You are an expert at converting user questions into database queries. \\\n", - "You have access to a database of tutorial videos about a software library for building LLM-powered applications. \\\n", - "Given a question, return a list of database queries optimized to retrieve the most relevant results.\n", - "\n", - "If there are acronyms or words you are not familiar with, do not try to rephrase them.\"\"\"\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system),\n", - " (\"human\", \"{question}\"),\n", - " ]\n", - ")\n", - "llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)\n", - "structured_llm = llm.with_structured_output(Search)\n", - "query_analyzer = {\"question\": RunnablePassthrough()} | prompt | structured_llm" - ] - }, - { - "cell_type": "markdown", - "id": "f403517a-b8e3-44ac-b0a6-02f8305635a2", - "metadata": {}, - "source": [ - "Let's see what queries our analyzer generates for the questions we searched earlier:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "bc1d3863", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Search(query='build RAG agent', publish_year=None)" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "query_analyzer.invoke(\"how do I build a RAG agent\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "af62af17-4f90-4dbd-a8b4-dfff51f1db95", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Search(query='RAG', publish_year=2023)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "query_analyzer.invoke(\"videos on RAG published in 2023\")" - ] - }, - { - "cell_type": "markdown", - "id": "c7c65b2f-7881-45fc-a47b-a4eaaf48245f", - "metadata": {}, - "source": [ - "## Retrieval with query analysis\n", - "\n", - "Our query analysis looks pretty good; now let's try using our generated queries to actually perform retrieval. \n", - "\n", - "**Note:** in our example, we specified `tool_choice=\"Search\"`. This will force the LLM to call one - and only one - tool, meaning that we will always have one optimized query to look up. Note that this is not always the case - see other guides for how to deal with situations when no - or multiple - optmized queries are returned." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "1e047d87", - "metadata": {}, - "outputs": [], - "source": [ - "from typing import List\n", - "\n", - "from langchain_core.documents import Document" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "8dac7866", - "metadata": {}, - "outputs": [], - "source": [ - "def retrieval(search: Search) -> List[Document]:\n", - " if search.publish_year is not None:\n", - " # This is syntax specific to Chroma,\n", - " # the vector database we are using.\n", - " _filter = {\"publish_year\": {\"$eq\": search.publish_year}}\n", - " else:\n", - " _filter = None\n", - " return vectorstore.similarity_search(search.query, filter=_filter)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "232ad8a7-7990-4066-9228-d35a555f7293", - "metadata": {}, - "outputs": [], - "source": [ - "retrieval_chain = query_analyzer | retrieval" - ] - }, - { - "cell_type": "markdown", - "id": "e6a4460c", - "metadata": {}, - "source": [ - "We can now run this chain on the problematic input from before, and see that it yields only results from that year!" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "e7f683b5-b1c5-4dec-b163-2efc162a2b51", - "metadata": {}, - "outputs": [], - "source": [ - "results = retrieval_chain.invoke(\"RAG tutorial published in 2023\")" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "1ad52512-b3e8-42a3-8701-d9e87fb8b46c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[('Getting Started with Multi-Modal LLMs', '2023-12-20 00:00:00'),\n", - " ('LangServe and LangChain Templates Webinar', '2023-11-02 00:00:00'),\n", - " ('Getting Started with Multi-Modal LLMs', '2023-12-20 00:00:00'),\n", - " ('Building a Research Assistant from Scratch', '2023-11-16 00:00:00')]" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "[(doc.metadata[\"title\"], doc.metadata[\"publish_date\"]) for doc in results]" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.4" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/docs/tutorials/rag.ipynb b/docs/docs/tutorials/rag.ipynb index 72a366403ba9e..631b5537aa9bc 100644 --- a/docs/docs/tutorials/rag.ipynb +++ b/docs/docs/tutorials/rag.ipynb @@ -5,9 +5,14 @@ "id": "5630b0ca", "metadata": {}, "source": [ - "# Build a Retrieval Augmented Generation (RAG) App\n", + "# Build a Retrieval Augmented Generation (RAG) App: Part 1\n", "\n", - "One of the most powerful applications enabled by LLMs is sophisticated question-answering (Q&A) chatbots. These are applications that can answer questions about specific source information. These applications use a technique known as Retrieval Augmented Generation, or RAG.\n", + "One of the most powerful applications enabled by LLMs is sophisticated question-answering (Q&A) chatbots. These are applications that can answer questions about specific source information. These applications use a technique known as Retrieval Augmented Generation, or [RAG](/docs/concepts/rag/).\n", + "\n", + "This is a multi-part tutorial:\n", + "\n", + "- [Part 1](/docs/tutorials/rag) (this guide) introduces RAG and walks through a minimal implementation.\n", + "- [Part 2](/docs/tutorials/qa_chat_history) extends the implementation to accommodate conversation-style interactions and multi-step retrieval processes.\n", "\n", "This tutorial will show how to build a simple Q&A application\n", "over a text data source. Along the way we’ll go over a typical Q&A\n", @@ -19,23 +24,17 @@ "If you're already familiar with basic retrieval, you might also be interested in\n", "this [high-level overview of different retrieval techinques](/docs/concepts/retrieval).\n", "\n", - "## What is RAG?\n", - "\n", - "RAG is a technique for augmenting LLM knowledge with additional data.\n", - "\n", - "LLMs can reason about wide-ranging topics, but their knowledge is limited to the public data up to a specific point in time that they were trained on. If you want to build AI applications that can reason about private data or data introduced after a model's cutoff date, you need to augment the knowledge of the model with the specific information it needs. The process of bringing and inserting appropriate information into the model prompt is known as Retrieval Augmented Generation (RAG).\n", - "\n", - "LangChain has a number of components designed to help build Q&A applications, and RAG applications more generally. \n", - "\n", "**Note**: Here we focus on Q&A for unstructured data. If you are interested for RAG over structured data, check out our tutorial on doing [question/answering over SQL data](/docs/tutorials/sql_qa).\n", "\n", - "## Concepts\n", + "## Overview\n", "A typical RAG application has two main components:\n", "\n", "**Indexing**: a pipeline for ingesting data from a source and indexing it. *This usually happens offline.*\n", "\n", "**Retrieval and generation**: the actual RAG chain, which takes the user query at run time and retrieves the relevant data from the index, then passes that to the model.\n", "\n", + "Note: the indexing portion of this tutorial will largely follow the [semantic search tutorial](/docs/tutorials/retrievers).\n", + "\n", "The most common full sequence from raw data to answer looks like:\n", "\n", "### Indexing\n", @@ -51,14 +50,13 @@ "\n", "![retrieval_diagram](../../static/img/rag_retrieval_generation.png)\n", "\n", + "Once we've indexed our data, we will use [LangGraph](https://langchain-ai.github.io/langgraph/) as our orchestration framework to implement the retrieval and generation steps.\n", "\n", "## Setup\n", "\n", "### Jupyter Notebook\n", "\n", - "This guide (and most of the other guides in the documentation) uses [Jupyter notebooks](https://jupyter.org/) and assumes the reader is as well. Jupyter notebooks are perfect for learning how to work with LLM systems because oftentimes things can go wrong (unexpected output, API down, etc) and going through guides in an interactive environment is a great way to better understand LLM concepts.\n", - "\n", - "This and other tutorials are perhaps most conveniently run in a Jupyter notebook. See [here](https://jupyter.org/install) for instructions on how to install.\n", + "This and other tutorials are perhaps most conveniently run in a [Jupyter notebooks](https://jupyter.org/). Going through guides in an interactive environment is a great way to better understand them. See [here](https://jupyter.org/install) for instructions on how to install.\n", "\n", "### Installation\n", "\n", @@ -80,7 +78,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install --quiet --upgrade langchain langchain-community langchain-chroma" + "%pip install --quiet --upgrade langchain-text-splitters langchain-community" ] }, { @@ -90,7 +88,7 @@ "source": [ " \n", " \n", - " conda install langchain langchain-community langchain-chroma -c conda-forge\n", + " conda install langchain-text-splitters langchain-community -c conda-forge\n", " \n", "\n", "\n", @@ -119,24 +117,21 @@ "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", "os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()\n", "```\n", - "## Preview\n", "\n", - "In this guide we’ll build an app that answers questions about the website's content. The specific website we will use is the [LLM Powered Autonomous\n", - "Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post\n", - "by Lilian Weng, which allows us to ask questions about the contents of\n", - "the post.\n", + "## Components\n", + "\n", + "We will need to select three components from LangChain's suite of integrations.\n", "\n", - "We can create a simple indexing pipeline and RAG chain to do this in ~20\n", - "lines of code:\n", + "A [chat model](/docs/integrations/chat/):\n", "\n", "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", "\n", - "\n" + "" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "26ef9d35", "metadata": {}, "outputs": [], @@ -146,37 +141,88 @@ "\n", "from langchain_openai import ChatOpenAI\n", "\n", - "llm = ChatOpenAI(model=\"gpt-4\")" + "llm = ChatOpenAI(model=\"gpt-4o-mini\")" + ] + }, + { + "cell_type": "markdown", + "id": "f1b78672-f21e-4827-843e-59514d18ca20", + "metadata": {}, + "source": [ + "An [embedding model](/docs/integrations/text_embedding/):\n", + "\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", + "\n", + "" ] }, { "cell_type": "code", - "execution_count": 2, - "id": "6281ec7b", + "execution_count": 3, + "id": "a199c764-5dfd-45cf-a4d4-731f2c3d474f", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Task Decomposition is a process where a complex task is broken down into smaller, simpler steps or subtasks. This technique is utilized to enhance model performance on complex tasks by making them more manageable. It can be done by using language models with simple prompting, task-specific instructions, or with human inputs.'" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_openai import OpenAIEmbeddings\n", + "\n", + "embeddings = OpenAIEmbeddings()" + ] + }, + { + "cell_type": "markdown", + "id": "859ffca8-055e-4f5a-95fe-55906ed1d63f", + "metadata": {}, + "source": [ + "And a [vector store](/docs/integrations/vectorstores/):\n", + "\n", + "import VectorStoreTabs from \"@theme/VectorStoreTabs\";\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "f4db6b46-ea3f-4994-9d54-d7c84beb50cc", + "metadata": {}, + "outputs": [], + "source": [ + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_core.vectorstores import InMemoryVectorStore\n", + "\n", + "vector_store = InMemoryVectorStore(embeddings)" + ] + }, + { + "cell_type": "markdown", + "id": "93b2d316-922c-4318-b72d-486fd6813b94", + "metadata": {}, + "source": [ + "## Preview\n", + "\n", + "In this guide we’ll build an app that answers questions about the website's content. The specific website we will use is the [LLM Powered Autonomous\n", + "Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) blog post\n", + "by Lilian Weng, which allows us to ask questions about the contents of\n", + "the post.\n", + "\n", + "We can create a simple indexing pipeline and RAG chain to do this in ~50\n", + "lines of code.\n", + "\n", + "```python\n", "import bs4\n", "from langchain import hub\n", - "from langchain_chroma import Chroma\n", "from langchain_community.document_loaders import WebBaseLoader\n", - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "from langchain_openai import OpenAIEmbeddings\n", + "from langchain_core.documents import Document\n", "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "from langgraph.graph import START, StateGraph\n", + "from typing_extensions import List, TypedDict\n", "\n", - "# Load, chunk and index the contents of the blog.\n", + "# Load and chunk contents of the blog\n", "loader = WebBaseLoader(\n", " web_paths=(\"https://lilianweng.github.io/posts/2023-06-23-agent/\",),\n", " bs_kwargs=dict(\n", @@ -188,61 +234,88 @@ "docs = loader.load()\n", "\n", "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", - "splits = text_splitter.split_documents(docs)\n", - "vectorstore = Chroma.from_documents(documents=splits, embedding=OpenAIEmbeddings())\n", + "all_splits = text_splitter.split_documents(docs)\n", + "\n", + "# Index chunks\n", + "_ = vector_store.add_documents(documents=all_splits)\n", "\n", - "# Retrieve and generate using the relevant snippets of the blog.\n", - "retriever = vectorstore.as_retriever()\n", + "# Define prompt for question-answering\n", "prompt = hub.pull(\"rlm/rag-prompt\")\n", "\n", "\n", - "def format_docs(docs):\n", - " return \"\\n\\n\".join(doc.page_content for doc in docs)\n", + "# Define state for application\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str\n", "\n", "\n", - "rag_chain = (\n", - " {\"context\": retriever | format_docs, \"question\": RunnablePassthrough()}\n", - " | prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")\n", + "# Define application steps\n", + "def retrieve(state: State):\n", + " retrieved_docs = vector_store.similarity_search(state[\"question\"])\n", + " return {\"context\": retrieved_docs}\n", + "\n", + "\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", + "\n", + "\n", + "# Compile application and test\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()\n", + "```\n", + "\n", + "```python\n", + "response = graph.invoke({\"question\": \"What is Task Decomposition?\"})\n", + "print(response[\"answer\"])\n", + "```\n", "\n", - "rag_chain.invoke(\"What is Task Decomposition?\")" + "```\n", + "Task Decomposition is the process of breaking down a complicated task into smaller, manageable steps to facilitate easier execution and understanding. Techniques like Chain of Thought (CoT) and Tree of Thoughts (ToT) guide models to think step-by-step, allowing them to explore multiple reasoning possibilities. This method enhances performance on complex tasks and provides insight into the model's thinking process.\n", + "```" ] }, { - "cell_type": "code", - "execution_count": 4, - "id": "3d56d203", + "cell_type": "markdown", + "id": "9ff8204b-dabc-4790-80ea-50d4cf4fceb0", "metadata": {}, - "outputs": [], "source": [ - "# cleanup\n", - "vectorstore.delete_collection()" + "Check out the [LangSmith\n", + "trace](https://smith.langchain.com/public/65030797-7efa-4356-a7bd-b54b3dc70e17/r)." ] }, { "cell_type": "markdown", - "id": "c9d51135", + "id": "efa9ea6a-f914-4f50-8e35-52e6c34b8001", "metadata": {}, "source": [ - "Check out the [LangSmith\n", - "trace](https://smith.langchain.com/public/1c6ca97e-445b-4d00-84b4-c7befcbc59fe/r).\n", - "\n", "## Detailed walkthrough\n", "\n", "Let’s go through the above code step-by-step to really understand what’s\n", "going on.\n", "\n", - "## 1. Indexing: Load {#indexing-load}\n", + "## 1. Indexing {#indexing}\n", + "\n", + ":::note\n", + "\n", + "This section is an abbreviated version of the content in the [semantic search tutorial](/docs/tutorials/retrievers).\n", + "If you're comfortable with [document loaders](/docs/concepts/document_loaders), [embeddings](/docs/concepts/embedding_models), and [vector stores](/docs/concepts/vectorstores),\n", + "feel free to skip to the next section on [retrieval and generation](/docs/tutorials/rag/#orchestration).\n", + "\n", + ":::\n", + "\n", + "### Loading documents\n", "\n", "We need to first load the blog post contents. We can use\n", "[DocumentLoaders](/docs/concepts/document_loaders)\n", "for this, which are objects that load in data from a source and return a\n", "list of\n", - "[Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html).\n", - "A `Document` is an object with some `page_content` (str) and `metadata`\n", - "(dict).\n", + "[Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html)\n", + "objects.\n", "\n", "In this case we’ll use the\n", "[WebBaseLoader](/docs/integrations/document_loaders/web_base),\n", @@ -257,19 +330,16 @@ }, { "cell_type": "code", - "execution_count": 3, - "id": "f5ba0122-8c92-4895-b5ef-f03a634e3fdf", + "execution_count": 6, + "id": "7b0971b5-8579-4a89-bd2e-9029dda4c4f1", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "43131" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Total characters: 43131\n" + ] } ], "source": [ @@ -284,13 +354,14 @@ ")\n", "docs = loader.load()\n", "\n", - "len(docs[0].page_content)" + "assert len(docs) == 1\n", + "print(f\"Total characters: {len(docs[0].page_content)}\")" ] }, { "cell_type": "code", - "execution_count": 4, - "id": "5cf74be6-5f40-4f6d-8689-b6b42ced8b70", + "execution_count": 7, + "id": "1a560025-fb86-4b7e-9586-da263bbad481", "metadata": {}, "outputs": [ { @@ -316,13 +387,12 @@ }, { "cell_type": "markdown", - "id": "07845e7a", + "id": "e6f11795-e19f-4697-bc6e-6d477355a1cd", "metadata": {}, "source": [ - "### Go deeper\n", + "#### Go deeper\n", "\n", - "`DocumentLoader`: Object that loads data from a source as list of\n", - "`Documents`.\n", + "`DocumentLoader`: Object that loads data from a source as list of `Documents`.\n", "\n", "- [Docs](/docs/how_to#document-loaders):\n", " Detailed documentation on how to use `DocumentLoaders`.\n", @@ -331,9 +401,7 @@ "- [Interface](https://python.langchain.com/api_reference/core/document_loaders/langchain_core.document_loaders.base.BaseLoader.html):\n", " API reference for the base interface.\n", "\n", - "\n", - "## 2. Indexing: Split {#indexing-split}\n", - "\n", + "### Splitting documents\n", "\n", "Our loaded document is over 42k characters which is too long to fit\n", "into the context window of many models. Even for those models that could\n", @@ -344,97 +412,46 @@ "vector storage. This should help us retrieve only the most relevant parts\n", "of the blog post at run time.\n", "\n", - "In this case we’ll split our documents into chunks of 1000 characters\n", - "with 200 characters of overlap between chunks. The overlap helps\n", - "mitigate the possibility of separating a statement from important\n", - "context related to it. We use the\n", + "As in the [semantic search tutorial](/docs/tutorials/retrievers), we use a\n", "[RecursiveCharacterTextSplitter](/docs/how_to/recursive_text_splitter),\n", "which will recursively split the document using common separators like\n", "new lines until each chunk is the appropriate size. This is the\n", - "recommended text splitter for generic text use cases.\n", - "\n", - "We set `add_start_index=True` so that the character index where each\n", - "split Document starts within the initial Document is preserved as\n", - "metadata attribute “start_index”." + "recommended text splitter for generic text use cases." ] }, { "cell_type": "code", - "execution_count": 5, - "id": "6aa3f8c0-5113-4c36-9706-ee702407173a", + "execution_count": 8, + "id": "753e1484-e21b-4f62-9866-b3a5971f88a7", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "66" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Split blog post into 66 sub-documents.\n" + ] } ], "source": [ "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", "\n", "text_splitter = RecursiveCharacterTextSplitter(\n", - " chunk_size=1000, chunk_overlap=200, add_start_index=True\n", + " chunk_size=1000, # chunk size (characters)\n", + " chunk_overlap=200, # chunk overlap (characters)\n", + " add_start_index=True, # track index in original document\n", ")\n", "all_splits = text_splitter.split_documents(docs)\n", "\n", - "len(all_splits)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "2257752c-bed2-4d57-be8e-d275bfe70ace", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "969" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(all_splits[0].page_content)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "325fdc48-4a24-4645-9d08-0d22f5be5e13", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/',\n", - " 'start_index': 7056}" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_splits[10].metadata" + "print(f\"Split blog post into {len(all_splits)} sub-documents.\")" ] }, { "cell_type": "markdown", - "id": "7046d580", + "id": "f5193e01-6cf1-45b9-9ba5-38caf75162a6", "metadata": {}, "source": [ - "### Go deeper\n", + "#### Go deeper\n", "\n", "`TextSplitter`: Object that splits a list of `Document`s into smaller\n", "chunks. Subclass of `DocumentTransformer`s.\n", @@ -451,44 +468,44 @@ "- [Integrations](/docs/integrations/document_transformers/)\n", "- [Interface](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.transformers.BaseDocumentTransformer.html): API reference for the base interface.\n", "\n", - "## 3. Indexing: Store {#indexing-store}\n", + "### Storing documents\n", "\n", "Now we need to index our 66 text chunks so that we can search over them\n", - "at runtime. The most common way to do this is to embed the contents of\n", - "each document split and insert these embeddings into a vector database\n", - "(or vector store). When we want to search over our splits, we take a\n", - "text search query, embed it, and perform some sort of “similarity”\n", - "search to identify the stored splits with the most similar embeddings to\n", - "our query embedding. The simplest similarity measure is cosine\n", - "similarity — we measure the cosine of the angle between each pair of\n", - "embeddings (which are high dimensional vectors).\n", + "at runtime. Following the [semantic search tutorial](/docs/tutorials/retrievers),\n", + "our approach is to [embed](/docs/concepts/embedding_models/) the contents of each document split and insert these embeddings\n", + "into a [vector store](/docs/concepts/vectorstores/). Given an input query, we can then use\n", + "vector search to retrieve relevant documents.\n", "\n", "We can embed and store all of our document splits in a single command\n", - "using the [Chroma](/docs/integrations/vectorstores/chroma)\n", - "vector store and\n", - "[OpenAIEmbeddings](/docs/integrations/text_embedding/openai)\n", - "model.\n" + "using the vector store and embeddings model selected at the [start of the tutorial](/docs/tutorials/rag/#components)." ] }, { "cell_type": "code", - "execution_count": 8, - "id": "0b44b41a-8b25-42ad-9e37-7baf82a058cd", + "execution_count": 9, + "id": "00d455e1-c681-4665-9470-58dbeca050d4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['07c18af6-ad58-479a-bfb1-d508033f9c64', '9000bf8e-1993-446f-8d4d-f4e507ba4b8f', 'ba3b5d14-bed9-4f5f-88be-44c88aedc2e6']\n" + ] + } + ], "source": [ - "from langchain_chroma import Chroma\n", - "from langchain_openai import OpenAIEmbeddings\n", + "document_ids = vector_store.add_documents(documents=all_splits)\n", "\n", - "vectorstore = Chroma.from_documents(documents=all_splits, embedding=OpenAIEmbeddings())" + "print(document_ids[:3])" ] }, { "cell_type": "markdown", - "id": "dbddc12e", + "id": "57666234-a5b3-4abc-b079-755241bb2b98", "metadata": {}, "source": [ - "### Go deeper\n", + "#### Go deeper\n", "\n", "`Embeddings`: Wrapper around a text embedding model, used for converting\n", "text to embeddings.\n", @@ -509,426 +526,613 @@ "blog post. Given a user question, we should ideally be able to return\n", "the snippets of the blog post that answer the question.\n", "\n", - "## 4. Retrieval and Generation: Retrieve {#retrieval-and-generation-retrieve}\n", + "## 2. Retrieval and Generation {#orchestration}\n", "\n", "Now let’s write the actual application logic. We want to create a simple\n", "application that takes a user question, searches for documents relevant\n", "to that question, passes the retrieved documents and initial question to\n", "a model, and returns an answer.\n", "\n", - "First we need to define our logic for searching over documents.\n", - "LangChain defines a\n", - "[Retriever](/docs/concepts/retrievers) interface\n", - "which wraps an index that can return relevant `Documents` given a string\n", - "query.\n", + "For generation, we will use the chat model selected at the [start of the tutorial](/docs/tutorials/rag/#components).\n", "\n", - "The most common type of `Retriever` is the\n", - "[VectorStoreRetriever](/docs/how_to/vectorstore_retriever),\n", - "which uses the similarity search capabilities of a vector store to\n", - "facilitate retrieval. Any `VectorStore` can easily be turned into a\n", - "`Retriever` with `VectorStore.as_retriever()`:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "1a0d25f8-8a45-4ec7-b419-c36e231fde13", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "6" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "retriever = vectorstore.as_retriever(search_type=\"similarity\", search_kwargs={\"k\": 6})\n", - "\n", - "retrieved_docs = retriever.invoke(\"What are the approaches to Task Decomposition?\")\n", - "\n", - "len(retrieved_docs)" + "We’ll use a prompt for RAG that is checked into the LangChain prompt hub\n", + "([here](https://smith.langchain.com/hub/rlm/rag-prompt))." ] }, { "cell_type": "code", "execution_count": 10, - "id": "58db0a6a-f1ad-4d28-acf8-98be9ed3c968", + "id": "46f378c5-858c-488f-8aef-8b59a6280791", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\n", - "Task decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.\n" + "You are an assistant for question-answering tasks. Use the following pieces of retrieved context to answer the question. If you don't know the answer, just say that you don't know. Use three sentences maximum and keep the answer concise.\n", + "Question: (question goes here) \n", + "Context: (context goes here) \n", + "Answer:\n" ] } ], "source": [ - "print(retrieved_docs[0].page_content)" + "from langchain import hub\n", + "\n", + "prompt = hub.pull(\"rlm/rag-prompt\")\n", + "\n", + "example_messages = prompt.invoke(\n", + " {\"context\": \"(context goes here)\", \"question\": \"(question goes here)\"}\n", + ").to_messages()\n", + "\n", + "assert len(example_messages) == 1\n", + "print(example_messages[0].content)" ] }, { "cell_type": "markdown", - "id": "8bb602b0", - "metadata": {}, - "source": [ - "### Go deeper\n", - "\n", - "Vector stores are commonly used for retrieval, but there are other ways\n", - "to do retrieval, too.\n", - "\n", - "`Retriever`: An object that returns `Document`s given a text query\n", - "\n", - "- [Docs](/docs/how_to#retrievers): Further\n", - " documentation on the interface and built-in retrieval techniques.\n", - " Some of which include:\n", - " - `MultiQueryRetriever` [generates variants of the input\n", - " question](/docs/how_to/MultiQueryRetriever)\n", - " to improve retrieval hit rate.\n", - " - `MultiVectorRetriever` instead generates\n", - " [variants of the\n", - " embeddings](/docs/how_to/multi_vector),\n", - " also in order to improve retrieval hit rate.\n", - " - `Maximal marginal relevance` selects for [relevance and\n", - " diversity](https://www.cs.cmu.edu/~jgc/publication/The_Use_MMR_Diversity_Based_LTMIR_1998.pdf)\n", - " among the retrieved documents to avoid passing in duplicate\n", - " context.\n", - " - Documents can be filtered during vector store retrieval using\n", - " metadata filters, such as with a [Self Query\n", - " Retriever](/docs/how_to/self_query).\n", - "- [Integrations](/docs/integrations/retrievers/): Integrations\n", - " with retrieval services.\n", - "- [Interface](https://python.langchain.com/api_reference/core/retrievers/langchain_core.retrievers.BaseRetriever.html):\n", - " API reference for the base interface.\n", + "id": "77dfe84d-cc19-4227-bee4-56b69508ab11", + "metadata": {}, + "source": [ + "We'll use [LangGraph](https://langchain-ai.github.io/langgraph/) to tie together the retrieval and generation steps into a single application. This will bring a number of benefits:\n", "\n", - "## 5. Retrieval and Generation: Generate {#retrieval-and-generation-generate}\n", + "- We can define our application logic once and automatically support multiple invocation modes, including streaming, async, and batched calls.\n", + "- We get streamlined deployments via [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/).\n", + "- LangSmith will automatically trace the steps of our application together.\n", + "- We can easily add key features to our application, including [persistence](https://langchain-ai.github.io/langgraph/concepts/persistence/) and [human-in-the-loop approval](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/), with minimal code changes.\n", "\n", - "Let’s put it all together into a chain that takes a question, retrieves\n", - "relevant documents, constructs a prompt, passes it into a model, and\n", - "parses the output.\n", + "To use LangGraph, we need to define three things:\n", "\n", - "We’ll use the gpt-4o-mini OpenAI chat model, but any LangChain `LLM`\n", - "or `ChatModel` could be substituted in.\n", + "1. The state of our application;\n", + "2. The nodes of our application (i.e., application steps);\n", + "3. The \"control flow\" of our application (e.g., the ordering of the steps).\n", "\n", - "\n", + "#### State:\n", "\n", - "We’ll use a prompt for RAG that is checked into the LangChain prompt hub\n", - "([here](https://smith.langchain.com/hub/rlm/rag-prompt))." + "The [state](https://langchain-ai.github.io/langgraph/concepts/low_level/#state) of our application controls what data is input to the application, transferred between steps, and output by the application. It is typically a `TypedDict`, but can also be a [Pydantic BaseModel](https://langchain-ai.github.io/langgraph/how-tos/state-model/).\n", + "\n", + "For a simple RAG application, we can just keep track of the input question, retrieved context, and generated answer:" ] }, { "cell_type": "code", "execution_count": 11, - "id": "ff01d415-7b0f-469d-bfda-b9cb672da611", + "id": "3bdc7c33-67f4-40c3-a0f5-9b846bc6e35c", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[HumanMessage(content=\"You are an assistant for question-answering tasks. Use the following pieces of retrieved context to answer the question. If you don't know the answer, just say that you don't know. Use three sentences maximum and keep the answer concise.\\nQuestion: filler question \\nContext: filler context \\nAnswer:\")]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "from langchain import hub\n", + "from langchain_core.documents import Document\n", + "from typing_extensions import List, TypedDict\n", "\n", - "prompt = hub.pull(\"rlm/rag-prompt\")\n", "\n", - "example_messages = prompt.invoke(\n", - " {\"context\": \"filler context\", \"question\": \"filler question\"}\n", - ").to_messages()\n", + "class State(TypedDict):\n", + " question: str\n", + " context: List[Document]\n", + " answer: str" + ] + }, + { + "cell_type": "markdown", + "id": "77868d9a-892f-4b2c-b706-850f96b4464f", + "metadata": {}, + "source": [ + "#### Nodes (application steps)\n", "\n", - "example_messages" + "Let's start with a simple sequence of two steps: retrieval and generation." ] }, { "cell_type": "code", "execution_count": 12, - "id": "2885ed99-31a0-4d7e-b9b0-af49c462caf4", + "id": "bdabbf44-cbee-46a4-98e4-794fdfc8bb3b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You are an assistant for question-answering tasks. Use the following pieces of retrieved context to answer the question. If you don't know the answer, just say that you don't know. Use three sentences maximum and keep the answer concise.\n", - "Question: filler question \n", - "Context: filler context \n", - "Answer:\n" - ] - } - ], + "outputs": [], "source": [ - "print(example_messages[0].content)" + "def retrieve(state: State):\n", + " retrieved_docs = vector_store.similarity_search(state[\"question\"])\n", + " return {\"context\": retrieved_docs}\n", + "\n", + "\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}" ] }, { "cell_type": "markdown", - "id": "4516200c", + "id": "d1ac9dc3-d73d-48c3-be05-4b60e0b8bc17", "metadata": {}, "source": [ - "We’ll use the [LCEL Runnable](/docs/concepts/lcel)\n", - "protocol to define the chain, allowing us to \n", + "Our retrieval step simply runs a similarity search using the input question, and the generation step formats the retrieved context and original question into a prompt for the chat model.\n", "\n", - "- pipe together components and functions in a transparent way \n", - "- automatically trace our chain in LangSmith \n", - "- get streaming, async, and batched calling out of the box.\n", + "#### Control flow\n", "\n", - "Here is the implementation:" + "Finally, we compile our application into a single `graph` object. In this case, we are just connecting the retrieval and generation steps into a single sequence." ] }, { "cell_type": "code", "execution_count": 13, - "id": "d6820cf3-e14d-4275-bd00-aa1b8262b1ae", + "id": "418ddefb-9a1d-42bf-9d23-e525268312a4", + "metadata": {}, + "outputs": [], + "source": [ + "from langgraph.graph import START, StateGraph\n", + "\n", + "graph_builder = StateGraph(State).add_sequence([retrieve, generate])\n", + "graph_builder.add_edge(START, \"retrieve\")\n", + "graph = graph_builder.compile()" + ] + }, + { + "cell_type": "markdown", + "id": "20b127f4-8411-4214-8cdd-a281771ab708", + "metadata": {}, + "source": [ + "LangGraph also comes with built-in utilities for visualizing the control flow of your application:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "feabc04f-b509-4452-8e2b-d7c7b7585a18", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Task Decomposition is a process where a complex task is broken down into smaller, more manageable steps or parts. This is often done using techniques like \"Chain of Thought\" or \"Tree of Thoughts\", which instruct a model to \"think step by step\" and transform large tasks into multiple simple tasks. Task decomposition can be prompted in a model, guided by task-specific instructions, or influenced by human inputs." - ] + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "\n", + "from IPython.display import Image, display\n", "\n", - "def format_docs(docs):\n", - " return \"\\n\\n\".join(doc.page_content for doc in docs)\n", - "\n", - "\n", - "rag_chain = (\n", - " {\"context\": retriever | format_docs, \"question\": RunnablePassthrough()}\n", - " | prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")\n", - "\n", - "for chunk in rag_chain.stream(\"What is Task Decomposition?\"):\n", - " print(chunk, end=\"\", flush=True)" + "display(Image(graph.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "markdown", - "id": "3dacf214-0803-46f1-960d-42336a545e39", + "id": "31f7dc4d-cac8-4be9-b44c-df097dc28c81", "metadata": {}, "source": [ - "Let's dissect the LCEL to understand what's going on.\n", - "\n", - "First: each of these components (`retriever`, `prompt`, `llm`, etc.) are instances of [Runnable](/docs/concepts/lcel). This means that they implement the same methods-- such as sync and async `.invoke`, `.stream`, or `.batch`-- which makes them easier to connect together. They can be connected into a [RunnableSequence](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableSequence.html)-- another Runnable-- via the `|` operator.\n", - "\n", - "LangChain will automatically cast certain objects to runnables when met with the `|` operator. Here, `format_docs` is cast to a [RunnableLambda](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableLambda.html), and the dict with `\"context\"` and `\"question\"` is cast to a [RunnableParallel](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableParallel.html). The details are less important than the bigger point, which is that each object in the chain is a Runnable.\n", - "\n", - "Let's trace how the input question flows through the above runnables.\n", + "
      \n", + "Do I need to use LangGraph?\n", "\n", - "As we've seen above, the input to `prompt` is expected to be a dict with keys `\"context\"` and `\"question\"`. So the first element of this chain builds runnables that will calculate both of these from the input question:\n", - "- `retriever | format_docs` passes the question through the retriever, generating [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects, and then to `format_docs` to generate strings;\n", - "- `RunnablePassthrough()` passes through the input question unchanged.\n", + "LangGraph is not required to build a RAG application. Indeed, we can implement the same application logic through invocations of the individual components:\n", "\n", - "That is, if you constructed\n", "```python\n", - "chain = (\n", - " {\"context\": retriever | format_docs, \"question\": RunnablePassthrough()}\n", - " | prompt\n", - ")\n", + "question = \"...\"\n", + "\n", + "retrieved_docs = vector_store.similarity_search(question)\n", + "docs_content = \"\\n\\n\".join(doc.page_content for doc in retrieved_docs)\n", + "prompt = prompt.invoke({\"question\": question, \"context\": formatted_docs})\n", + "answer = llm.invoke(prompt)\n", "```\n", - "Then `chain.invoke(question)` would build a formatted prompt, ready for inference. (Note: when developing with LCEL, it can be practical to test with sub-chains like this.)\n", "\n", - "The last steps of the chain are `llm`, which runs the inference, and `StrOutputParser()`, which just plucks the string content out of the LLM's output message.\n", + "The benefits of LangGraph include:\n", "\n", - "You can analyze the individual steps of this chain via its [LangSmith\n", - "trace](https://smith.langchain.com/public/1799e8db-8a6d-4eb2-84d5-46e8d7d5a99b/r).\n", + "- Support for multiple invocation modes: this logic would need to be rewritten if we wanted to stream output tokens, or stream the results of individual steps;\n", + "- Automatic support for tracing via [LangSmith](https://docs.smith.langchain.com/) and deployments via [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/);\n", + "- Support for persistence, human-in-the-loop, and other features.\n", "\n", - "### Built-in chains\n", + "Many use-cases demand RAG in a conversational experience, such that a user can receive context-informed answers via a stateful conversation. As we will see in [Part 2](/docs/tutorials/qa_chat_history) of the tutorial, LangGraph's management and persistence of state simplifies these applications enormously.\n", + "\n", + "
      " + ] + }, + { + "cell_type": "markdown", + "id": "eee9c057-5a08-46a3-8c7d-6a314d1e777d", + "metadata": {}, + "source": [ + "#### Usage\n", "\n", - "If preferred, LangChain includes convenient functions that implement the above LCEL. We compose two functions:\n", + "Let's test our application! LangGraph supports multiple invocation modes, including sync, async, and streaming.\n", "\n", - "- [create_stuff_documents_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.combine_documents.stuff.create_stuff_documents_chain.html) specifies how retrieved context is fed into a prompt and LLM. In this case, we will \"stuff\" the contents into the prompt -- i.e., we will include all retrieved context without any summarization or other processing. It largely implements our above `rag_chain`, with input keys `context` and `input`-- it generates an answer using retrieved context and query.\n", - "- [create_retrieval_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.retrieval.create_retrieval_chain.html) adds the retrieval step and propagates the retrieved context through the chain, providing it alongside the final answer. It has input key `input`, and includes `input`, `context`, and `answer` in its output." + "Invoke:" ] }, { "cell_type": "code", - "execution_count": 37, - "id": "e75bfe98-d9e4-4868-bae1-5811437d859b", + "execution_count": 15, + "id": "663b93ba-f0a7-44c4-a894-fe895bd5b009", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Task Decomposition is a process in which complex tasks are broken down into smaller and simpler steps. Techniques like Chain of Thought (CoT) and Tree of Thoughts are used to enhance model performance on these tasks. The CoT method instructs the model to think step by step, decomposing hard tasks into manageable ones, while Tree of Thoughts extends CoT by exploring multiple reasoning possibilities at each step, creating a tree structure of thoughts.\n" + "Context: [Document(id='a42dc78b-8f76-472a-9e25-180508af74f3', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 1585}, page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.'), Document(id='c0e45887-d0b0-483d-821a-bb5d8316d51d', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 2192}, page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.'), Document(id='4cc7f318-35f5-440f-a4a4-145b5f0b918d', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 29630}, page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.'), Document(id='f621ade4-9b0d-471f-a522-44eb5feeba0c', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 19373}, page_content=\"(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\")]\n", + "\n", + "\n", + "Answer: Task decomposition is a technique used to break down complex tasks into smaller, manageable steps, allowing for more efficient problem-solving. This can be achieved through methods like chain of thought prompting or the tree of thoughts approach, which explores multiple reasoning possibilities at each step. It can be initiated through simple prompts, task-specific instructions, or human inputs.\n" ] } ], "source": [ - "from langchain.chains import create_retrieval_chain\n", - "from langchain.chains.combine_documents import create_stuff_documents_chain\n", - "from langchain_core.prompts import ChatPromptTemplate\n", - "\n", - "system_prompt = (\n", - " \"You are an assistant for question-answering tasks. \"\n", - " \"Use the following pieces of retrieved context to answer \"\n", - " \"the question. If you don't know the answer, say that you \"\n", - " \"don't know. Use three sentences maximum and keep the \"\n", - " \"answer concise.\"\n", - " \"\\n\\n\"\n", - " \"{context}\"\n", - ")\n", - "\n", - "prompt = ChatPromptTemplate.from_messages(\n", - " [\n", - " (\"system\", system_prompt),\n", - " (\"human\", \"{input}\"),\n", - " ]\n", - ")\n", + "result = graph.invoke({\"question\": \"What is Task Decomposition?\"})\n", "\n", - "\n", - "question_answer_chain = create_stuff_documents_chain(llm, prompt)\n", - "rag_chain = create_retrieval_chain(retriever, question_answer_chain)\n", - "\n", - "response = rag_chain.invoke({\"input\": \"What is Task Decomposition?\"})\n", - "print(response[\"answer\"])" + "print(f'Context: {result[\"context\"]}\\n\\n')\n", + "print(f'Answer: {result[\"answer\"]}')" ] }, { "cell_type": "markdown", - "id": "0fe711ea-592b-44a1-89b3-cee33c81aca4", + "id": "4ef88f30-40ca-476b-808d-794cb72d401f", "metadata": {}, "source": [ - "#### Returning sources\n", - "Often in Q&A applications it's important to show users the sources that were used to generate the answer. LangChain's built-in `create_retrieval_chain` will propagate retrieved source documents to the output under the `\"context\"` key:" + "Stream steps:" ] }, { "cell_type": "code", - "execution_count": 41, - "id": "9d4cec1a-75d6-4479-929f-72cadb2dcde8", + "execution_count": 16, + "id": "e6314a96-aab8-4ecc-bbf9-094fa2aa0e50", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.' metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", - "\n", - "page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.' metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 1585}\n", + "{'retrieve': {'context': [Document(id='a42dc78b-8f76-472a-9e25-180508af74f3', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 1585}, page_content='Fig. 1. Overview of a LLM-powered autonomous agent system.\\nComponent One: Planning#\\nA complicated task usually involves many steps. An agent needs to know what they are and plan ahead.\\nTask Decomposition#\\nChain of thought (CoT; Wei et al. 2022) has become a standard prompting technique for enhancing model performance on complex tasks. The model is instructed to “think step by step” to utilize more test-time computation to decompose hard tasks into smaller and simpler steps. CoT transforms big tasks into multiple manageable tasks and shed lights into an interpretation of the model’s thinking process.'), Document(id='c0e45887-d0b0-483d-821a-bb5d8316d51d', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 2192}, page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.'), Document(id='4cc7f318-35f5-440f-a4a4-145b5f0b918d', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 29630}, page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.'), Document(id='f621ade4-9b0d-471f-a522-44eb5feeba0c', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 19373}, page_content=\"(3) Task execution: Expert models execute on the specific tasks and log results.\\nInstruction:\\n\\nWith the input and the inference results, the AI assistant needs to describe the process and results. The previous stages can be formed as - User Input: {{ User Input }}, Task Planning: {{ Tasks }}, Model Selection: {{ Model Assignment }}, Task Execution: {{ Predictions }}. You must first answer the user's request in a straightforward manner. Then describe the task process and show your analysis and model inference results to the user in the first person. If inference results contain a file path, must tell the user the complete file path.\")]}}\n", "\n", - "page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.' metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 2192}\n", + "----------------\n", "\n", - "page_content='Tree of Thoughts (Yao et al. 2023) extends CoT by exploring multiple reasoning possibilities at each step. It first decomposes the problem into multiple thought steps and generates multiple thoughts per step, creating a tree structure. The search process can be BFS (breadth-first search) or DFS (depth-first search) with each state evaluated by a classifier (via a prompt) or majority vote.\\nTask decomposition can be done (1) by LLM with simple prompting like \"Steps for XYZ.\\\\n1.\", \"What are the subgoals for achieving XYZ?\", (2) by using task-specific instructions; e.g. \"Write a story outline.\" for writing a novel, or (3) with human inputs.' metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", + "{'generate': {'answer': 'Task decomposition is the process of breaking down a complex task into smaller, more manageable steps. This technique, often enhanced by methods like Chain of Thought (CoT) or Tree of Thoughts, allows models to reason through tasks systematically and improves performance by clarifying the thought process. It can be achieved through simple prompts, task-specific instructions, or human inputs.'}}\n", "\n", - "page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.' metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}\n", - "\n", - "page_content='Resources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.' metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 29630}\n", + "----------------\n", "\n" ] } ], "source": [ - "for document in response[\"context\"]:\n", - " print(document)\n", - " print()" + "for step in graph.stream(\n", + " {\"question\": \"What is Task Decomposition?\"}, stream_mode=\"updates\"\n", + "):\n", + " print(f\"{step}\\n\\n----------------\\n\")" + ] + }, + { + "cell_type": "markdown", + "id": "f860142d-d50b-4526-a03f-a59a763117fe", + "metadata": {}, + "source": [ + "Stream [tokens](/docs/concepts/tokens/):" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "28625cc3-0f77-4143-af51-ce0fd6682120", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|Task| decomposition| is| the| process| of| breaking| down| complex| tasks| into| smaller|,| more| manageable| steps|.| It| can| be| achieved| through| techniques| like| Chain| of| Thought| (|Co|T|)| prompting|,| which| encourages| the| model| to| think| step| by| step|,| or| through| more| structured| methods| like| the| Tree| of| Thoughts|.| This| approach| not| only| simplifies| task| execution| but| also| provides| insights| into| the| model|'s| reasoning| process|.||" + ] + } + ], + "source": [ + "for message, metadata in graph.stream(\n", + " {\"question\": \"What is Task Decomposition?\"}, stream_mode=\"messages\"\n", + "):\n", + " print(message.content, end=\"|\")" + ] + }, + { + "cell_type": "markdown", + "id": "0fe09894-0cc5-4427-9a24-aef60d20705f", + "metadata": {}, + "source": [ + ":::tip\n", + "\n", + "For async invocations, use:\n", + "\n", + "```python\n", + "result = await graph.ainvoke(...)\n", + "```\n", + "\n", + "and\n", + "\n", + "```python\n", + "async for step in graph.astream(...):\n", + "```\n", + "\n", + ":::" ] }, { "cell_type": "markdown", - "id": "7cd57618", + "id": "406534d4-66a3-4c27-b277-2bd2f5930cf5", "metadata": {}, "source": [ - "### Go deeper\n", + "#### Returning sources\n", + "\n", + "Note that by storing the retrieved context in the state of the graph, we recover sources for the model's generated answer in the `\"context\"` field of the state. See [this guide](/docs/how_to/qa_sources/) on returning sources for more detail.\n", "\n", - "#### Choosing a model\n", + "#### Go deeper\n", "\n", - "`ChatModel`: An LLM-backed chat model. Takes in a sequence of messages\n", - "and returns a message.\n", + "[Chat models](/docs/concepts/chat_models) take in a sequence of messages and return a message.\n", "\n", "- [Docs](/docs/how_to#chat-models)\n", "- [Integrations](/docs/integrations/chat/): 25+ integrations to choose from.\n", "- [Interface](https://python.langchain.com/api_reference/core/language_models/langchain_core.language_models.chat_models.BaseChatModel.html): API reference for the base interface.\n", "\n", - "`LLM`: A text-in-text-out LLM. Takes in a string and returns a string.\n", + "**Customizing the prompt**\n", + "\n", + "As shown above, we can load prompts (e.g., [this RAG\n", + "prompt](https://smith.langchain.com/hub/rlm/rag-prompt)) from the prompt\n", + "hub. The prompt can also be easily customized. For example:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "956e7e78-c26c-4d2d-bf2e-4fc41ff40d37", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.prompts import PromptTemplate\n", + "\n", + "template = \"\"\"Use the following pieces of context to answer the question at the end.\n", + "If you don't know the answer, just say that you don't know, don't try to make up an answer.\n", + "Use three sentences maximum and keep the answer as concise as possible.\n", + "Always say \"thanks for asking!\" at the end of the answer.\n", + "\n", + "{context}\n", "\n", - "- [Docs](/docs/how_to#llms)\n", - "- [Integrations](/docs/integrations/llms): 75+ integrations to choose from.\n", - "- [Interface](https://python.langchain.com/api_reference/core/language_models/langchain_core.language_models.llms.BaseLLM.html): API reference for the base interface.\n", + "Question: {question}\n", "\n", - "See a guide on RAG with locally-running models\n", - "[here](/docs/tutorials/local_rag).\n", + "Helpful Answer:\"\"\"\n", + "custom_rag_prompt = PromptTemplate.from_template(template)" + ] + }, + { + "cell_type": "markdown", + "id": "217cf819-da76-4595-8f75-33f931f1f92a", + "metadata": {}, + "source": [ + "## Query analysis\n", "\n", - "#### Customizing the prompt\n", + "So far, we are executing the retrieval using the raw input query. However, there are some advantages to allowing a model to generate the query for retrieval purposes. For example:\n", "\n", - "As shown above, we can load prompts (e.g., [this RAG\n", - "prompt](https://smith.langchain.com/hub/rlm/rag-prompt)) from the prompt\n", - "hub. The prompt can also be easily customized:" + "- In addition to semantic search, we can build in structured filters (e.g., \"Find documents since the year 2020.\");\n", + "- The model can rewrite user queries, which may be multifaceted or include irrelevant language, into more effective search queries.\n", + "\n", + "[Query analysis](/docs/concepts/retrieval/#query-analysis) employs models to transform or construct optimized search queries from raw user input. We can easily incorporate a query analysis step into our application. For illustrative purposes, let's add some metadata to the documents in our vector store. We will add some (contrived) sections to the document which we can filter on later." ] }, { "cell_type": "code", - "execution_count": 17, - "id": "2ac552b6", + "execution_count": 19, + "id": "df00956a-6565-4c05-b201-32854dd2a889", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'Task decomposition is the process of breaking down a complex task into smaller, more manageable parts. Techniques like Chain of Thought (CoT) and Tree of Thoughts allow an agent to \"think step by step\" and explore multiple reasoning possibilities, respectively. This process can be executed by a Language Model with simple prompts, task-specific instructions, or human inputs. Thanks for asking!'" + "{'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/',\n", + " 'start_index': 8,\n", + " 'section': 'beginning'}" ] }, - "execution_count": 17, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from langchain_core.prompts import PromptTemplate\n", + "total_documents = len(all_splits)\n", + "third = total_documents // 3\n", "\n", - "template = \"\"\"Use the following pieces of context to answer the question at the end.\n", - "If you don't know the answer, just say that you don't know, don't try to make up an answer.\n", - "Use three sentences maximum and keep the answer as concise as possible.\n", - "Always say \"thanks for asking!\" at the end of the answer.\n", + "for i, document in enumerate(all_splits):\n", + " if i < third:\n", + " document.metadata[\"section\"] = \"beginning\"\n", + " elif i < 2 * third:\n", + " document.metadata[\"section\"] = \"middle\"\n", + " else:\n", + " document.metadata[\"section\"] = \"end\"\n", "\n", - "{context}\n", "\n", - "Question: {question}\n", + "all_splits[0].metadata" + ] + }, + { + "cell_type": "markdown", + "id": "114878bd-a334-41ed-8013-ec4ce0a9112b", + "metadata": {}, + "source": [ + "We will need to update the documents in our vector store. We will use a simple [InMemoryVectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.in_memory.InMemoryVectorStore.html) for this, as we will use some of its specific features (i.e., metadata filtering). Refer to the vector store [integration documentation](/docs/integrations/vectorstores/) for relevant features of your chosen vector store." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "ebb3cbd7-7c75-4cc0-a198-ff7c54a0c43a", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.vectorstores import InMemoryVectorStore\n", "\n", - "Helpful Answer:\"\"\"\n", - "custom_rag_prompt = PromptTemplate.from_template(template)\n", + "vector_store = InMemoryVectorStore(embeddings)\n", + "_ = vector_store.add_documents(all_splits)" + ] + }, + { + "cell_type": "markdown", + "id": "c08aaccd-b3df-45e9-8646-d6ea20215e62", + "metadata": {}, + "source": [ + "Let's next define a schema for our search query. We will use [structured output](/docs/concepts/structured_outputs/) for this purpose. Here we define a query as containing a string query and a document section (either \"beginning\", \"middle\", or \"end\"), but this can be defined however you like." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "87f9c8c3-3e99-426d-aa65-fec4b9155c3f", + "metadata": {}, + "outputs": [], + "source": [ + "from typing import Literal\n", + "\n", + "from typing_extensions import Annotated\n", "\n", - "rag_chain = (\n", - " {\"context\": retriever | format_docs, \"question\": RunnablePassthrough()}\n", - " | custom_rag_prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")\n", "\n", - "rag_chain.invoke(\"What is Task Decomposition?\")" + "class Search(TypedDict):\n", + " \"\"\"Search query.\"\"\"\n", + "\n", + " query: Annotated[str, ..., \"Search query to run.\"]\n", + " section: Annotated[\n", + " Literal[\"beginning\", \"middle\", \"end\"],\n", + " ...,\n", + " \"Section to query.\",\n", + " ]" ] }, { "cell_type": "markdown", - "id": "82e4d779", + "id": "6399a870-cb06-4219-9b4f-cfa37cb8ab0f", "metadata": {}, "source": [ - "Check out the [LangSmith\n", - "trace](https://smith.langchain.com/public/da23c4d8-3b33-47fd-84df-a3a582eedf84/r)\n", + "Finally, we add a step to our LangGraph application to generate a query from the user's raw input:" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "7e8fcdcb-a4ff-41c3-97c7-92d81ab29f38", + "metadata": {}, + "outputs": [], + "source": [ + "class State(TypedDict):\n", + " question: str\n", + " # highlight-next-line\n", + " query: Search\n", + " context: List[Document]\n", + " answer: str\n", + "\n", + "\n", + "# highlight-next-line\n", + "def analyze_query(state: State):\n", + " # highlight-next-line\n", + " structured_llm = llm.with_structured_output(Search)\n", + " # highlight-next-line\n", + " query = structured_llm.invoke(state[\"question\"])\n", + " # highlight-next-line\n", + " return {\"query\": query}\n", + "\n", + "\n", + "def retrieve(state: State):\n", + " # highlight-start\n", + " query = state[\"query\"]\n", + " retrieved_docs = vector_store.similarity_search(\n", + " query[\"query\"],\n", + " filter=lambda doc: doc.metadata.get(\"section\") == query[\"section\"],\n", + " )\n", + " # highlight-end\n", + " return {\"context\": retrieved_docs}\n", + "\n", + "\n", + "def generate(state: State):\n", + " docs_content = \"\\n\\n\".join(doc.page_content for doc in state[\"context\"])\n", + " messages = prompt.invoke({\"question\": state[\"question\"], \"context\": docs_content})\n", + " response = llm.invoke(messages)\n", + " return {\"answer\": response.content}\n", + "\n", + "\n", + "# highlight-start\n", + "graph_builder = StateGraph(State).add_sequence([analyze_query, retrieve, generate])\n", + "graph_builder.add_edge(START, \"analyze_query\")\n", + "# highlight-end\n", + "graph = graph_builder.compile()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "8a92d539-f85d-434b-b911-51a1cf9b81da", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(Image(graph.get_graph().draw_mermaid_png()))" + ] + }, + { + "cell_type": "markdown", + "id": "653cf8dc-a201-43ea-9965-02fcfd2fc316", + "metadata": {}, + "source": [ + "We can test our implementation by specifically asking for context from the end of the post. Note that the model includes different information in its answer." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "8b420650-2d9e-4f5e-a8d8-ec36ae07423c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'analyze_query': {'query': {'query': 'Task Decomposition', 'section': 'end'}}}\n", + "\n", + "----------------\n", + "\n", + "{'retrieve': {'context': [Document(id='d6cef137-e1e8-4ddc-91dc-b62bd33c6020', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 39221, 'section': 'end'}, page_content='Finite context length: The restricted context capacity limits the inclusion of historical information, detailed instructions, API call context, and responses. The design of the system has to work with this limited communication bandwidth, while mechanisms like self-reflection to learn from past mistakes would benefit a lot from long or infinite context windows. Although vector stores and retrieval can provide access to a larger knowledge pool, their representation power is not as powerful as full attention.\\n\\n\\nChallenges in long-term planning and task decomposition: Planning over a lengthy history and effectively exploring the solution space remain challenging. LLMs struggle to adjust plans when faced with unexpected errors, making them less robust compared to humans who learn from trial and error.'), Document(id='d1834ae1-eb6a-43d7-a023-08dfa5028799', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 39086, 'section': 'end'}, page_content='}\\n]\\nChallenges#\\nAfter going through key ideas and demos of building LLM-centered agents, I start to see a couple common limitations:'), Document(id='ca7f06e4-2c2e-4788-9a81-2418d82213d9', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 32942, 'section': 'end'}, page_content='}\\n]\\nThen after these clarification, the agent moved into the code writing mode with a different system message.\\nSystem message:'), Document(id='1fcc2736-30f4-4ef6-90f2-c64af92118cb', metadata={'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'start_index': 35127, 'section': 'end'}, page_content='\"content\": \"You will get instructions for code to write.\\\\nYou will write a very long answer. Make sure that every detail of the architecture is, in the end, implemented as code.\\\\nMake sure that every detail of the architecture is, in the end, implemented as code.\\\\n\\\\nThink step by step and reason yourself to the right decisions to make sure we get it right.\\\\nYou will first lay out the names of the core classes, functions, methods that will be necessary, as well as a quick comment on their purpose.\\\\n\\\\nThen you will output the content of each file including ALL code.\\\\nEach file must strictly follow a markdown code block format, where the following tokens must be replaced such that\\\\nFILENAME is the lowercase file name including the file extension,\\\\nLANG is the markup code block language for the code\\'s language, and CODE is the code:\\\\n\\\\nFILENAME\\\\n```LANG\\\\nCODE\\\\n```\\\\n\\\\nYou will start with the \\\\\"entrypoint\\\\\" file, then go to the ones that are imported by that file, and so on.\\\\nPlease')]}}\n", + "\n", + "----------------\n", + "\n", + "{'generate': {'answer': 'The end of the post highlights that task decomposition faces challenges in long-term planning and adapting to unexpected errors. LLMs struggle with adjusting their plans, making them less robust compared to humans who learn from trial and error. This indicates a limitation in effectively exploring the solution space and handling complex tasks.'}}\n", + "\n", + "----------------\n", + "\n" + ] + } + ], + "source": [ + "for step in graph.stream(\n", + " {\"question\": \"What does the end of the post say about Task Decomposition?\"},\n", + " stream_mode=\"updates\",\n", + "):\n", + " print(f\"{step}\\n\\n----------------\\n\")" + ] + }, + { + "cell_type": "markdown", + "id": "5875a48a-c849-4da9-99e0-558b04884fb0", + "metadata": {}, + "source": [ + "In both the streamed steps and the [LangSmith trace](https://smith.langchain.com/public/bdbaae61-130c-4338-8b59-9315dfee22a0/r), we can now observe the structured query that was fed into the retrieval step.\n", "\n", + "Query Analysis is a rich problem with a wide range of approaches. Refer to the [how-to guides](/docs/how_to/#query-analysis) for more examples." + ] + }, + { + "cell_type": "markdown", + "id": "82e4d779", + "metadata": {}, + "source": [ "## Next steps\n", "\n", "We've covered the steps to build a basic Q&A app over data:\n", @@ -937,23 +1141,22 @@ "- Chunking the indexed data with a [Text Splitter](/docs/concepts/text_splitters) to make it more easily usable by a model\n", "- [Embedding the data](/docs/concepts/embedding_models) and storing the data in a [vectorstore](/docs/how_to/vectorstores)\n", "- [Retrieving](/docs/concepts/retrievers) the previously stored chunks in response to incoming questions\n", - "- Generating an answer using the retrieved chunks as context\n", + "- Generating an answer using the retrieved chunks as context.\n", + "\n", + "In [Part 2](/docs/tutorials/qa_chat_history) of the tutorial, we will extend the implementation here to accommodate conversation-style interactions and multi-step retrieval processes.\n", "\n", - "There’s plenty of features, integrations, and extensions to explore in each of\n", - "the above sections. Along with the **Go deeper** sources mentioned\n", - "above, good next steps include:\n", + "Further reading:\n", "\n", "- [Return sources](/docs/how_to/qa_sources): Learn how to return source documents\n", "- [Streaming](/docs/how_to/streaming): Learn how to stream outputs and intermediate steps\n", "- [Add chat history](/docs/how_to/message_history): Learn how to add chat history to your app\n", - "- [Retrieval conceptual guide](/docs/concepts/retrieval): A high-level overview of specific retrieval techniques\n", - "- [Build a local RAG application](/docs/tutorials/local_rag): Create an app similar to the one above using all local components" + "- [Retrieval conceptual guide](/docs/concepts/retrieval): A high-level overview of specific retrieval techniques" ] } ], "metadata": { "kernelspec": { - "display_name": ".venv", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -967,7 +1170,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/retrievers.ipynb b/docs/docs/tutorials/retrievers.ipynb index e4024a53dde88..fa2eca88469b1 100644 --- a/docs/docs/tutorials/retrievers.ipynb +++ b/docs/docs/tutorials/retrievers.ipynb @@ -5,17 +5,20 @@ "id": "bf37a837-7a6a-447b-8779-38f26c585887", "metadata": {}, "source": [ - "# Vector stores and retrievers\n", + "# Build a semantic search engine\n", "\n", - "This tutorial will familiarize you with LangChain's vector store and retriever abstractions. These abstractions are designed to support retrieval of data-- from (vector) databases and other sources-- for integration with LLM workflows. They are important for applications that fetch data to be reasoned over as part of model inference, as in the case of retrieval-augmented generation, or RAG (see our RAG tutorial [here](/docs/tutorials/rag)).\n", + "This tutorial will familiarize you with LangChain's [document loader](/docs/concepts/document_loaders), [embedding](/docs/concepts/embedding_models), and [vector store](/docs/concepts/vectorstores) abstractions. These abstractions are designed to support retrieval of data-- from (vector) databases and other sources-- for integration with LLM workflows. They are important for applications that fetch data to be reasoned over as part of model inference, as in the case of retrieval-augmented generation, or [RAG](/docs/concepts/rag) (see our RAG tutorial [here](/docs/tutorials/rag)).\n", + "\n", + "Here we will build a search engine over a PDF document. This will allow us to retrieve passages in the PDF that are similar to an input query.\n", "\n", "## Concepts\n", "\n", "This guide focuses on retrieval of text data. We will cover the following concepts:\n", "\n", - "- Documents;\n", - "- Vector stores;\n", - "- Retrievers.\n", + "- Documents and document loaders;\n", + "- Text splitters;\n", + "- Embeddings;\n", + "- Vector stores and retrievers.\n", "\n", "## Setup\n", "\n", @@ -25,7 +28,7 @@ "\n", "### Installation\n", "\n", - "This tutorial requires the `langchain`, `langchain-chroma`, and `langchain-openai` packages:\n", + "This tutorial requires the `langchain-community` and `pypdf` packages:\n", "\n", "import Tabs from '@theme/Tabs';\n", "import TabItem from '@theme/TabItem';\n", @@ -33,10 +36,10 @@ "\n", "\n", " \n", - " pip install langchain langchain-chroma langchain-openai\n", + " pip install langchain-community pypdf\n", " \n", " \n", - " conda install langchain langchain-chroma langchain-openai -c conda-forge\n", + " conda install langchain-community pypdf -c conda-forge\n", " \n", "\n", "\n", @@ -67,25 +70,18 @@ "```\n", "\n", "\n", - "## Documents\n", + "## Documents and Document Loaders\n", "\n", - "LangChain implements a [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) abstraction, which is intended to represent a unit of text and associated metadata. It has two attributes:\n", + "LangChain implements a [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) abstraction, which is intended to represent a unit of text and associated metadata. It has three attributes:\n", "\n", "- `page_content`: a string representing the content;\n", - "- `metadata`: a dict containing arbitrary metadata.\n", + "- `metadata`: a dict containing arbitrary metadata;\n", + "- `id`: (optional) a string identifier for the document.\n", "\n", "The `metadata` attribute can capture information about the source of the document, its relationship to other documents, and other information. Note that an individual `Document` object often represents a chunk of a larger document.\n", "\n", - "Let's generate some sample documents:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "9f3dc151-7b2f-4d94-9558-7a84f7eab100", - "metadata": {}, - "outputs": [], - "source": [ + "We can generate sample documents when desired:\n", + "```python\n", "from langchain_core.documents import Document\n", "\n", "documents = [\n", @@ -97,19 +93,199 @@ " page_content=\"Cats are independent pets that often enjoy their own space.\",\n", " metadata={\"source\": \"mammal-pets-doc\"},\n", " ),\n", - " Document(\n", - " page_content=\"Goldfish are popular pets for beginners, requiring relatively simple care.\",\n", - " metadata={\"source\": \"fish-pets-doc\"},\n", - " ),\n", - " Document(\n", - " page_content=\"Parrots are intelligent birds capable of mimicking human speech.\",\n", - " metadata={\"source\": \"bird-pets-doc\"},\n", - " ),\n", - " Document(\n", - " page_content=\"Rabbits are social animals that need plenty of space to hop around.\",\n", - " metadata={\"source\": \"mammal-pets-doc\"},\n", - " ),\n", - "]" + "]\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "f8593578-5699-4b19-96c4-7c990d37a2ec", + "metadata": {}, + "source": [ + "However, the LangChain ecosystem implements [document loaders](/docs/concepts/document_loaders) that [integrate with hundreds of common sources](/docs/integrations/document_loaders/). This makes it easy to incorporate data from these sources into your AI application.\n", + "\n", + "### Loading documents\n", + "\n", + "Let's load a PDF into a sequence of `Document` objects. There is a sample PDF in the LangChain repo [here](https://github.com/langchain-ai/langchain/tree/master/docs/docs/example_data) -- a 10-k filing for Nike from 2023. We can consult the LangChain documentation for [available PDF document loaders](/docs/integrations/document_loaders/#pdfs). Let's select [PyPDFLoader](/docs/integrations/document_loaders/pypdfloader/), which is fairly lightweight." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "a2ac32c4-1036-42d8-8a3d-f7f57e3a0df7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "107\n" + ] + } + ], + "source": [ + "from langchain_community.document_loaders import PyPDFLoader\n", + "\n", + "file_path = \"../example_data/nke-10k-2023.pdf\"\n", + "loader = PyPDFLoader(file_path)\n", + "\n", + "docs = loader.load()\n", + "\n", + "print(len(docs))" + ] + }, + { + "cell_type": "markdown", + "id": "b90f4800-bb82-416b-beba-f42ae88a5c66", + "metadata": {}, + "source": [ + ":::tip\n", + "\n", + "See [this guide](/docs/how_to/document_loader_pdf/) for more detail on PDF document loaders.\n", + "\n", + ":::\n", + "\n", + "`PyPDFLoader` loads one `Document` object per PDF page. For each, we can easily access:\n", + "\n", + "- The string content of the page;\n", + "- Metadata containing the file name and page number." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "850e2ca5-6b20-4e58-ad99-b19786358a3e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table of Contents\n", + "UNITED STATES\n", + "SECURITIES AND EXCHANGE COMMISSION\n", + "Washington, D.C. 20549\n", + "FORM 10-K\n", + "(Mark One)\n", + "☑ ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(D) OF THE SECURITIES EXCHANGE ACT OF 1934\n", + "FO\n", + "\n", + "{'source': '../example_data/nke-10k-2023.pdf', 'page': 0}\n" + ] + } + ], + "source": [ + "print(f\"{docs[0].page_content[:200]}\\n\")\n", + "print(docs[0].metadata)" + ] + }, + { + "cell_type": "markdown", + "id": "2ca6980f-4870-490a-9fe6-8caeead3c1d1", + "metadata": {}, + "source": [ + "### Splitting\n", + "\n", + "For both information retrieval and downstream question-answering purposes, a page may be too coarse a representation. Our goal in the end will be to retrieve `Document` objects that answer an input query, and further splitting our PDF will help ensure that the meanings of relevant portions of the document are not \"washed out\" by surrounding text.\n", + "\n", + "We can use [text splitters](/docs/concepts/text_splitters) for this purpose. Here we will use a simple text splitter that partitions based on characters. We will split our documents into chunks of 1000 characters\n", + "with 200 characters of overlap between chunks. The overlap helps\n", + "mitigate the possibility of separating a statement from important\n", + "context related to it. We use the\n", + "[RecursiveCharacterTextSplitter](/docs/how_to/recursive_text_splitter),\n", + "which will recursively split the document using common separators like\n", + "new lines until each chunk is the appropriate size. This is the\n", + "recommended text splitter for generic text use cases.\n", + "\n", + "We set `add_start_index=True` so that the character index where each\n", + "split Document starts within the initial Document is preserved as\n", + "metadata attribute “start_index”.\n", + "\n", + "See [this guide](/docs/how_to/document_loader_pdf/) for more detail about working with PDFs, including how to extract text from specific sections and images. " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "11c16e79-c8af-4949-9363-9a93a911a0e1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "514" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "\n", + "text_splitter = RecursiveCharacterTextSplitter(\n", + " chunk_size=1000, chunk_overlap=200, add_start_index=True\n", + ")\n", + "all_splits = text_splitter.split_documents(docs)\n", + "\n", + "len(all_splits)" + ] + }, + { + "cell_type": "markdown", + "id": "5c066d46-9187-4d5a-98d3-974c37610276", + "metadata": {}, + "source": [ + "## Embeddings\n", + "\n", + "Vector search is a common way to store and search over unstructured data (such as unstructured text). The idea is to store numeric vectors that are associated with the text. Given a query, we can [embed](/docs/concepts/embedding_models) it as a vector of the same dimension and use vector similarity metrics (such as cosine similarity) to identify related text.\n", + "\n", + "LangChain supports embeddings from [dozens of providers](/docs/integrations/text_embedding/). These models specify how text should be converted into a numeric vector. Let's select a model:\n", + "\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "4d238a38-b9b3-494a-9cea-8694a1b03bc7", + "metadata": {}, + "outputs": [], + "source": [ + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_openai import OpenAIEmbeddings\n", + "\n", + "embeddings = OpenAIEmbeddings()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "c5f3b0ac-4e18-4c6b-84e7-e8822c59ce17", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generated vectors of length 1536\n", + "\n", + "[-0.008586574345827103, -0.03341241180896759, -0.008936782367527485, -0.0036674530711025, 0.010564599186182022, 0.009598285891115665, -0.028587326407432556, -0.015824200585484505, 0.0030416189692914486, -0.012899317778646946]\n" + ] + } + ], + "source": [ + "vector_1 = embeddings.embed_query(all_splits[0].page_content)\n", + "vector_2 = embeddings.embed_query(all_splits[1].page_content)\n", + "\n", + "assert len(vector_1) == len(vector_2)\n", + "print(f\"Generated vectors of length {len(vector_1)}\\n\")\n", + "print(vector_1[:10])" ] }, { @@ -117,33 +293,50 @@ "id": "1cac19bd-27d1-40f1-9c27-7a586b685b4e", "metadata": {}, "source": [ - "Here we've generated five documents, containing metadata indicating three distinct \"sources\".\n", + "Armed with a model for generating text embeddings, we can next store them in a special data structure that supports efficient similarity search.\n", "\n", "## Vector stores\n", "\n", - "Vector search is a common way to store and search over unstructured data (such as unstructured text). The idea is to store numeric vectors that are associated with the text. Given a query, we can [embed](/docs/concepts/embedding_models) it as a vector of the same dimension and use vector similarity metrics to identify related data in the store.\n", - "\n", "LangChain [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) objects contain methods for adding text and `Document` objects to the store, and querying them using various similarity metrics. They are often initialized with [embedding](/docs/how_to/embed_text) models, which determine how text data is translated to numeric vectors.\n", "\n", - "LangChain includes a suite of [integrations](/docs/integrations/vectorstores) with different vector store technologies. Some vector stores are hosted by a provider (e.g., various cloud providers) and require specific credentials to use; some (such as [Postgres](/docs/integrations/vectorstores/pgvector)) run in separate infrastructure that can be run locally or via a third-party; others can run in-memory for lightweight workloads. Here we will demonstrate usage of LangChain VectorStores using [Chroma](/docs/integrations/vectorstores/chroma), which includes an in-memory implementation.\n", + "LangChain includes a suite of [integrations](/docs/integrations/vectorstores) with different vector store technologies. Some vector stores are hosted by a provider (e.g., various cloud providers) and require specific credentials to use; some (such as [Postgres](/docs/integrations/vectorstores/pgvector)) run in separate infrastructure that can be run locally or via a third-party; others can run in-memory for lightweight workloads. Let's select a vector store:\n", + "\n", + "import VectorStoreTabs from \"@theme/VectorStoreTabs\";\n", "\n", - "To instantiate a vector store, we often need to provide an [embedding](/docs/how_to/embed_text) model to specify how text should be converted into a numeric vector. Here we will use [OpenAI embeddings](/docs/integrations/text_embedding/openai/)." + "" ] }, { "cell_type": "code", - "execution_count": 2, - "id": "d48acc28-1a34-414b-8e08-fbdef3a2a60b", + "execution_count": 6, + "id": "5b0d3730-c008-4246-8b03-dd3058513e1c", "metadata": {}, "outputs": [], "source": [ + "# | output: false\n", + "# | echo: false\n", + "\n", "from langchain_chroma import Chroma\n", - "from langchain_openai import OpenAIEmbeddings\n", "\n", - "vectorstore = Chroma.from_documents(\n", - " documents,\n", - " embedding=OpenAIEmbeddings(),\n", - ")" + "vector_store = Chroma(embedding_function=embeddings)" + ] + }, + { + "cell_type": "markdown", + "id": "e3b3035f-1371-4965-ab7a-04eae25e47f3", + "metadata": {}, + "source": [ + "Having instantiated our vector store, we can now index the documents." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "2ea92e04-331c-4f83-aa2a-508322bdfbfc", + "metadata": {}, + "outputs": [], + "source": [ + "ids = vector_store.add_documents(documents=all_splits)" ] }, { @@ -151,7 +344,7 @@ "id": "ff0f0b43-e5b8-4c79-b782-a02f17345487", "metadata": {}, "source": [ - "Calling `.from_documents` here will add the documents to the vector store. [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) implements methods for adding documents that can also be called after the object is instantiated. Most implementations will allow you to connect to an existing vector store-- e.g., by providing a client, index name, or other information. See the documentation for a specific [integration](/docs/integrations/vectorstores) for more detail.\n", + "Note that most vector store implementations will allow you to connect to an existing vector store-- e.g., by providing a client, index name, or other information. See the documentation for a specific [integration](/docs/integrations/vectorstores) for more detail.\n", "\n", "Once we've instantiated a `VectorStore` that contains documents, we can query it. [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) includes methods for querying:\n", "- Synchronously and asynchronously;\n", @@ -161,33 +354,40 @@ "\n", "The methods will generally include a list of [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html#langchain_core.documents.base.Document) objects in their outputs.\n", "\n", - "### Examples\n", + "### Usage\n", + "\n", + "Embeddings typically represent text as a \"dense\" vector such that texts with similar meanings are gemoetrically close. This lets us retrieve relevant information just by passing in a question, without knowledge of any specific key-terms used in the document.\n", "\n", "Return documents based on similarity to a string query:" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 8, "id": "7e01ed91-1a98-4221-960a-bd7a2541a548", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "[Document(page_content='Cats are independent pets that often enjoy their own space.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Dogs are great companions, known for their loyalty and friendliness.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Rabbits are social animals that need plenty of space to hop around.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Parrots are intelligent birds capable of mimicking human speech.', metadata={'source': 'bird-pets-doc'})]" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "page_content='direct to consumer operations sell products through the following number of retail stores in the United States:\n", + "U.S. RETAIL STORES NUMBER\n", + "NIKE Brand factory stores 213 \n", + "NIKE Brand in-line stores (including employee-only stores) 74 \n", + "Converse stores (including factory stores) 82 \n", + "TOTAL 369 \n", + "In the United States, NIKE has eight significant distribution centers. Refer to Item 2. Properties for further information.\n", + "2023 FORM 10-K 2' metadata={'page': 4, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 3125}\n" + ] } ], "source": [ - "vectorstore.similarity_search(\"cat\")" + "results = vector_store.similarity_search(\n", + " \"How many distribution centers does Nike have in the US?\"\n", + ")\n", + "\n", + "print(results[0])" ] }, { @@ -200,26 +400,30 @@ }, { "cell_type": "code", - "execution_count": 4, - "id": "618af196-6182-4a7d-8b09-07493fcdc868", + "execution_count": 9, + "id": "7ff9e061-7710-40b2-93dc-1ca2b71ef96d", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "[Document(page_content='Cats are independent pets that often enjoy their own space.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Dogs are great companions, known for their loyalty and friendliness.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Rabbits are social animals that need plenty of space to hop around.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Parrots are intelligent birds capable of mimicking human speech.', metadata={'source': 'bird-pets-doc'})]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "page_content='Table of Contents\n", + "PART I\n", + "ITEM 1. BUSINESS\n", + "GENERAL\n", + "NIKE, Inc. was incorporated in 1967 under the laws of the State of Oregon. As used in this Annual Report on Form 10-K (this \"Annual Report\"), the terms \"we,\" \"us,\" \"our,\"\n", + "\"NIKE\" and the \"Company\" refer to NIKE, Inc. and its predecessors, subsidiaries and affiliates, collectively, unless the context indicates otherwise.\n", + "Our principal business activity is the design, development and worldwide marketing and selling of athletic footwear, apparel, equipment, accessories and services. NIKE is\n", + "the largest seller of athletic footwear and apparel in the world. We sell our products through NIKE Direct operations, which are comprised of both NIKE-owned retail stores\n", + "and sales through our digital platforms (also referred to as \"NIKE Brand Digital\"), to retail accounts and to a mix of independent distributors, licensees and sales' metadata={'page': 3, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 0}\n" + ] } ], "source": [ - "await vectorstore.asimilarity_search(\"cat\")" + "results = await vector_store.asimilarity_search(\"When was Nike incorporated?\")\n", + "\n", + "print(results[0])" ] }, { @@ -232,34 +436,37 @@ }, { "cell_type": "code", - "execution_count": 5, - "id": "4ed24af2-0d82-478c-949b-b389348d4e9f", + "execution_count": 11, + "id": "52dfc576-40a7-4030-aeb5-bb4d3a493e3e", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "[(Document(page_content='Cats are independent pets that often enjoy their own space.', metadata={'source': 'mammal-pets-doc'}),\n", - " 0.3751849830150604),\n", - " (Document(page_content='Dogs are great companions, known for their loyalty and friendliness.', metadata={'source': 'mammal-pets-doc'}),\n", - " 0.48316916823387146),\n", - " (Document(page_content='Rabbits are social animals that need plenty of space to hop around.', metadata={'source': 'mammal-pets-doc'}),\n", - " 0.49601367115974426),\n", - " (Document(page_content='Parrots are intelligent birds capable of mimicking human speech.', metadata={'source': 'bird-pets-doc'}),\n", - " 0.4972994923591614)]" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Score: 0.23699893057346344\n", + "\n", + "page_content='Table of Contents\n", + "FISCAL 2023 NIKE BRAND REVENUE HIGHLIGHTS\n", + "The following tables present NIKE Brand revenues disaggregated by reportable operating segment, distribution channel and major product line:\n", + "FISCAL 2023 COMPARED TO FISCAL 2022\n", + "•NIKE, Inc. Revenues were $51.2 billion in fiscal 2023, which increased 10% and 16% compared to fiscal 2022 on a reported and currency-neutral basis, respectively.\n", + "The increase was due to higher revenues in North America, Europe, Middle East & Africa (\"EMEA\"), APLA and Greater China, which contributed approximately 7, 6,\n", + "2 and 1 percentage points to NIKE, Inc. Revenues, respectively.\n", + "•NIKE Brand revenues, which represented over 90% of NIKE, Inc. Revenues, increased 10% and 16% on a reported and currency-neutral basis, respectively. This\n", + "increase was primarily due to higher revenues in Men's, the Jordan Brand, Women's and Kids' which grew 17%, 35%,11% and 10%, respectively, on a wholesale\n", + "equivalent basis.' metadata={'page': 35, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 0}\n" + ] } ], "source": [ - "# Note that providers implement different scores; Chroma here\n", - "# returns a distance metric that should vary inversely with\n", - "# similarity.\n", + "# Note that providers implement different scores; the score here\n", + "# is a distance metric that varies inversely with similarity.\n", "\n", - "vectorstore.similarity_search_with_score(\"cat\")" + "results = vector_store.similarity_search_with_score(\"What was Nike's revenue in 2023?\")\n", + "doc, score = results[0]\n", + "print(f\"Score: {score}\\n\")\n", + "print(doc)" ] }, { @@ -272,28 +479,36 @@ }, { "cell_type": "code", - "execution_count": 6, - "id": "b1a5eabb-a821-48cc-917e-cc27f03e4bcc", + "execution_count": 11, + "id": "7be726c1-b24c-414a-9862-d412b94784b2", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "[Document(page_content='Cats are independent pets that often enjoy their own space.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Dogs are great companions, known for their loyalty and friendliness.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Rabbits are social animals that need plenty of space to hop around.', metadata={'source': 'mammal-pets-doc'}),\n", - " Document(page_content='Parrots are intelligent birds capable of mimicking human speech.', metadata={'source': 'bird-pets-doc'})]" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "page_content='Table of Contents\n", + "GROSS MARGIN\n", + "FISCAL 2023 COMPARED TO FISCAL 2022\n", + "For fiscal 2023, our consolidated gross profit increased 4% to $22,292 million compared to $21,479 million for fiscal 2022. Gross margin decreased 250 basis points to\n", + "43.5% for fiscal 2023 compared to 46.0% for fiscal 2022 due to the following:\n", + "*Wholesale equivalent\n", + "The decrease in gross margin for fiscal 2023 was primarily due to:\n", + "•Higher NIKE Brand product costs, on a wholesale equivalent basis, primarily due to higher input costs and elevated inbound freight and logistics costs as well as\n", + "product mix;\n", + "•Lower margin in our NIKE Direct business, driven by higher promotional activity to liquidate inventory in the current period compared to lower promotional activity in\n", + "the prior period resulting from lower available inventory supply;\n", + "•Unfavorable changes in net foreign currency exchange rates, including hedges; and\n", + "•Lower off-price margin, on a wholesale equivalent basis.\n", + "This was partially offset by:' metadata={'page': 36, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 0}\n" + ] } ], "source": [ - "embedding = OpenAIEmbeddings().embed_query(\"cat\")\n", + "embedding = embeddings.embed_query(\"How were Nike's margins impacted in 2023?\")\n", "\n", - "vectorstore.similarity_search_by_vector(embedding)" + "results = vector_store.similarity_search_by_vector(embedding)\n", + "print(results[0])" ] }, { @@ -309,38 +524,47 @@ "\n", "## Retrievers\n", "\n", - "LangChain `VectorStore` objects do not subclass [Runnable](https://python.langchain.com/api_reference/core/index.html#langchain-core-runnables), and so cannot immediately be integrated into LangChain Expression Language [chains](/docs/concepts/lcel).\n", - "\n", - "LangChain [Retrievers](https://python.langchain.com/api_reference/core/index.html#langchain-core-retrievers) are Runnables, so they implement a standard set of methods (e.g., synchronous and asynchronous `invoke` and `batch` operations) and are designed to be incorporated in LCEL chains.\n", + "LangChain `VectorStore` objects do not subclass [Runnable](https://python.langchain.com/api_reference/core/index.html#langchain-core-runnables). LangChain [Retrievers](https://python.langchain.com/api_reference/core/index.html#langchain-core-retrievers) are Runnables, so they implement a standard set of methods (e.g., synchronous and asynchronous `invoke` and `batch` operations). Although we can construct retrievers from vector stores, retrievers can interface with non-vector store sources of data, as well (such as external APIs).\n", "\n", "We can create a simple version of this ourselves, without subclassing `Retriever`. If we choose what method we wish to use to retrieve documents, we can create a runnable easily. Below we will build one around the `similarity_search` method:" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "f1461582-e569-4326-bd95-510f72edf019", + "execution_count": 14, + "id": "58b8e826-1556-489c-b27b-a1efbc4cd689", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[[Document(page_content='Cats are independent pets that often enjoy their own space.', metadata={'source': 'mammal-pets-doc'})],\n", - " [Document(page_content='Goldfish are popular pets for beginners, requiring relatively simple care.', metadata={'source': 'fish-pets-doc'})]]" + "[[Document(metadata={'page': 4, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 3125}, page_content='direct to consumer operations sell products through the following number of retail stores in the United States:\\nU.S. RETAIL STORES NUMBER\\nNIKE Brand factory stores 213 \\nNIKE Brand in-line stores (including employee-only stores) 74 \\nConverse stores (including factory stores) 82 \\nTOTAL 369 \\nIn the United States, NIKE has eight significant distribution centers. Refer to Item 2. Properties for further information.\\n2023 FORM 10-K 2')],\n", + " [Document(metadata={'page': 3, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 0}, page_content='Table of Contents\\nPART I\\nITEM 1. BUSINESS\\nGENERAL\\nNIKE, Inc. was incorporated in 1967 under the laws of the State of Oregon. As used in this Annual Report on Form 10-K (this \"Annual Report\"), the terms \"we,\" \"us,\" \"our,\"\\n\"NIKE\" and the \"Company\" refer to NIKE, Inc. and its predecessors, subsidiaries and affiliates, collectively, unless the context indicates otherwise.\\nOur principal business activity is the design, development and worldwide marketing and selling of athletic footwear, apparel, equipment, accessories and services. NIKE is\\nthe largest seller of athletic footwear and apparel in the world. We sell our products through NIKE Direct operations, which are comprised of both NIKE-owned retail stores\\nand sales through our digital platforms (also referred to as \"NIKE Brand Digital\"), to retail accounts and to a mix of independent distributors, licensees and sales')]]" ] }, - "execution_count": 7, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "from typing import List\n", + "\n", "from langchain_core.documents import Document\n", - "from langchain_core.runnables import RunnableLambda\n", + "from langchain_core.runnables import chain\n", + "\n", "\n", - "retriever = RunnableLambda(vectorstore.similarity_search).bind(k=1) # select top result\n", + "@chain\n", + "def retriever(query: str) -> List[Document]:\n", + " return vector_store.similarity_search(query, k=1)\n", "\n", - "retriever.batch([\"cat\", \"shark\"])" + "\n", + "retriever.batch(\n", + " [\n", + " \"How many distribution centers does Nike have in the US?\",\n", + " \"When was Nike incorporated?\",\n", + " ],\n", + ")" ] }, { @@ -353,29 +577,34 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 13, "id": "4989fe5e-ac58-4751-bc35-f53ff885860c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[[Document(page_content='Cats are independent pets that often enjoy their own space.', metadata={'source': 'mammal-pets-doc'})],\n", - " [Document(page_content='Goldfish are popular pets for beginners, requiring relatively simple care.', metadata={'source': 'fish-pets-doc'})]]" + "[[Document(metadata={'page': 4, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 3125}, page_content='direct to consumer operations sell products through the following number of retail stores in the United States:\\nU.S. RETAIL STORES NUMBER\\nNIKE Brand factory stores 213 \\nNIKE Brand in-line stores (including employee-only stores) 74 \\nConverse stores (including factory stores) 82 \\nTOTAL 369 \\nIn the United States, NIKE has eight significant distribution centers. Refer to Item 2. Properties for further information.\\n2023 FORM 10-K 2')],\n", + " [Document(metadata={'page': 3, 'source': '../example_data/nke-10k-2023.pdf', 'start_index': 0}, page_content='Table of Contents\\nPART I\\nITEM 1. BUSINESS\\nGENERAL\\nNIKE, Inc. was incorporated in 1967 under the laws of the State of Oregon. As used in this Annual Report on Form 10-K (this \"Annual Report\"), the terms \"we,\" \"us,\" \"our,\"\\n\"NIKE\" and the \"Company\" refer to NIKE, Inc. and its predecessors, subsidiaries and affiliates, collectively, unless the context indicates otherwise.\\nOur principal business activity is the design, development and worldwide marketing and selling of athletic footwear, apparel, equipment, accessories and services. NIKE is\\nthe largest seller of athletic footwear and apparel in the world. We sell our products through NIKE Direct operations, which are comprised of both NIKE-owned retail stores\\nand sales through our digital platforms (also referred to as \"NIKE Brand Digital\"), to retail accounts and to a mix of independent distributors, licensees and sales')]]" ] }, - "execution_count": 8, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "retriever = vectorstore.as_retriever(\n", + "retriever = vector_store.as_retriever(\n", " search_type=\"similarity\",\n", " search_kwargs={\"k\": 1},\n", ")\n", "\n", - "retriever.batch([\"cat\", \"shark\"])" + "retriever.batch(\n", + " [\n", + " \"How many distribution centers does Nike have in the US?\",\n", + " \"When was Nike incorporated?\",\n", + " ],\n", + ")" ] }, { @@ -385,70 +614,7 @@ "source": [ "`VectorStoreRetriever` supports search types of `\"similarity\"` (default), `\"mmr\"` (maximum marginal relevance, described above), and `\"similarity_score_threshold\"`. We can use the latter to threshold documents output by the retriever by similarity score.\n", "\n", - "Retrievers can easily be incorporated into more complex applications, such as retrieval-augmented generation (RAG) applications that combine a given question with retrieved context into a prompt for a LLM. Below we show a minimal example.\n", - "\n", - "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "c77b68bf-59f3-4416-9877-960f934c374d", - "metadata": {}, - "outputs": [], - "source": [ - "# | output: false\n", - "# | echo: false\n", - "\n", - "from langchain_openai import ChatOpenAI\n", - "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "6f1ae0d0-0b4b-4da0-80ce-f82913052a83", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_core.prompts import ChatPromptTemplate\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "\n", - "message = \"\"\"\n", - "Answer this question using the provided context only.\n", - "\n", - "{question}\n", - "\n", - "Context:\n", - "{context}\n", - "\"\"\"\n", - "\n", - "prompt = ChatPromptTemplate.from_messages([(\"human\", message)])\n", - "\n", - "rag_chain = {\"context\": retriever, \"question\": RunnablePassthrough()} | prompt | llm" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "b3c0d625-61e0-492e-b3a6-c40d383fca03", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Cats are independent pets that often enjoy their own space.\n" - ] - } - ], - "source": [ - "response = rag_chain.invoke(\"tell me about cats\")\n", - "\n", - "print(response.content)" + "Retrievers can easily be incorporated into more complex applications, such as [retrieval-augmented generation (RAG)](/docs/concepts/rag) applications that combine a given question with retrieved context into a prompt for a LLM. To learn more about building such an application, check out the [RAG tutorial](/docs/tutorials/rag) tutorial." ] }, { @@ -456,7 +622,7 @@ "id": "3d9be7cb-2081-48a4-b6e4-d5e2d562ffd4", "metadata": {}, "source": [ - "## Learn more:\n", + "### Learn more:\n", "\n", "Retrieval strategies can be rich and complex. For example:\n", "\n", @@ -468,7 +634,35 @@ "\n", "The [retrievers](/docs/how_to#retrievers) section of the how-to guides covers these and other built-in retrieval strategies.\n", "\n", - "It is also straightforward to extend the [BaseRetriever](https://python.langchain.com/api_reference/core/retrievers/langchain_core.retrievers.BaseRetriever.html) class in order to implement custom retrievers. See our how-to guide [here](/docs/how_to/custom_retriever)." + "It is also straightforward to extend the [BaseRetriever](https://python.langchain.com/api_reference/core/retrievers/langchain_core.retrievers.BaseRetriever.html) class in order to implement custom retrievers. See our how-to guide [here](/docs/how_to/custom_retriever).\n", + "\n", + "\n", + "## Next steps\n", + "\n", + "You've now seen how to build a semantic search engine over a PDF document.\n", + "\n", + "For more on document loaders:\n", + "\n", + "- [Conceptual guide](/docs/concepts/document_loaders)\n", + "- [How-to guides](/docs/how_to/#document-loaders)\n", + "- [Available integrations](/docs/integrations/document_loaders/)\n", + "\n", + "For more on embeddings:\n", + "\n", + "- [Conceptual guide](/docs/concepts/embedding_models/)\n", + "- [How-to guides](/docs/how_to/#embedding-models)\n", + "- [Available integrations](/docs/integrations/text_embedding/)\n", + "\n", + "For more on vector stores:\n", + "\n", + "- [Conceptual guide](/docs/concepts/vectorstores/)\n", + "- [How-to guides](/docs/how_to/#vector-stores)\n", + "- [Available integrations](/docs/integrations/vectorstores/)\n", + "\n", + "For more on RAG, see:\n", + "\n", + "- [Build a Retrieval Augmented Generation (RAG) App](/docs/tutorials/rag/)\n", + "- [Related how-to guides](/docs/how_to/#qa-with-rag)" ] } ], diff --git a/docs/docs/tutorials/sql_qa.ipynb b/docs/docs/tutorials/sql_qa.ipynb index 6fc2b75c24aea..efd996ef238af 100644 --- a/docs/docs/tutorials/sql_qa.ipynb +++ b/docs/docs/tutorials/sql_qa.ipynb @@ -10,14 +10,14 @@ "\n", "This guide assumes familiarity with the following concepts:\n", "\n", - "- [Chaining runnables](/docs/how_to/sequence/)\n", "- [Chat models](/docs/concepts/chat_models)\n", "- [Tools](/docs/concepts/tools)\n", "- [Agents](/docs/concepts/agents)\n", + "- [LangGraph](/docs/concepts/architecture/#langgraph)\n", "\n", ":::\n", "\n", - "Enabling a LLM system to query structured data can be qualitatively different from unstructured text data. Whereas in the latter it is common to generate text that can be searched against a vector database, the approach for structured data is often for the LLM to write and execute queries in a DSL, such as SQL. In this guide we'll go over the basic ways to create a Q&A system over tabular data in databases. We will cover implementations using both chains and agents. These systems will allow us to ask a question about the data in a database and get back a natural language answer. The main difference between the two is that our agent can query the database in a loop as many times as it needs to answer the question.\n", + "Enabling a LLM system to query structured data can be qualitatively different from unstructured text data. Whereas in the latter it is common to generate text that can be searched against a vector database, the approach for structured data is often for the LLM to write and execute queries in a DSL, such as SQL. In this guide we'll go over the basic ways to create a Q&A system over tabular data in databases. We will cover implementations using both [chains](/docs/tutorials/sql_qa#chains) and [agents](/docs/tutorials/sql_qa#agents). These systems will allow us to ask a question about the data in a database and get back a natural language answer. The main difference between the two is that our agent can query the database in a loop as many times as it needs to answer the question.\n", "\n", "## ⚠️ Security note ⚠️\n", "\n", @@ -41,34 +41,14 @@ "First, get required packages and set environment variables:" ] }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "%pip install --upgrade --quiet langchain langchain-community langchain-openai faiss-cpu" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will use an OpenAI model and a [FAISS-powered vector store](/docs/integrations/vectorstores/faiss/) in this guide." - ] - }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "import getpass\n", - "import os\n", - "\n", - "if not os.environ.get(\"OPENAI_API_KEY\"):\n", - " os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()" + "%%capture --no-stderr\n", + "%pip install --upgrade --quiet langchain-community langchainhub langgraph" ] }, { @@ -87,19 +67,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The below example will use a SQLite connection with Chinook database. Follow [these installation steps](https://database.guide/2-sample-databases-sqlite/) to create `Chinook.db` in the same directory as this notebook:\n", + "### Sample data\n", "\n", - "* Save [this file](https://raw.githubusercontent.com/lerocha/chinook-database/master/ChinookDatabase/DataSources/Chinook_Sqlite.sql) as `Chinook.sql`\n", - "* Run `sqlite3 Chinook.db`\n", - "* Run `.read Chinook.sql`\n", - "* Test `SELECT * FROM Artist LIMIT 10;`\n", + "The below example will use a SQLite connection with the Chinook database, which is a sample database that represents a digital media store. Follow [these installation steps](https://database.guide/2-sample-databases-sqlite/) to create `Chinook.db` in the same directory as this notebook. You can also download and build the database via the command line:\n", + "```bash\n", + "curl -s https://raw.githubusercontent.com/lerocha/chinook-database/master/ChinookDatabase/DataSources/Chinook_Sqlite.sql | sqlite3 Chinook.db\n", + "```\n", "\n", "Now, `Chinook.db` is in our directory and we can interface with it using the SQLAlchemy-driven `SQLDatabase` class:" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -116,7 +96,7 @@ "\"[(1, 'AC/DC'), (2, 'Accept'), (3, 'Aerosmith'), (4, 'Alanis Morissette'), (5, 'Alice In Chains'), (6, 'Antônio Carlos Jobim'), (7, 'Apocalyptica'), (8, 'Audioslave'), (9, 'BackBeat'), (10, 'Billy Cobham')]\"" ] }, - "execution_count": 1, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -138,16 +118,47 @@ "\n", "## Chains {#chains}\n", "\n", - "Chains (i.e., compositions of LangChain [Runnables](/docs/concepts/lcel)) support applications whose steps are predictable. We can create a simple chain that takes a question and does the following:\n", - "- convert the question into a SQL query;\n", - "- execute the query;\n", - "- use the result to answer the original question.\n", + "Chains are compositions of predictable steps. In [LangGraph](/docs/concepts/architecture/#langgraph), we can represent a chain via simple sequence of nodes. Let's create a sequence of steps that, given a question, does the following:\n", + "- converts the question into a SQL query;\n", + "- executes the query;\n", + "- uses the result to answer the original question.\n", "\n", "There are scenarios not supported by this arrangement. For example, this system will execute a SQL query for any user input-- even \"hello\". Importantly, as we'll see below, some questions require more than one query to answer. We will address these scenarios in the Agents section.\n", "\n", + "### Application state\n", + "\n", + "The LangGraph [state](https://langchain-ai.github.io/langgraph/concepts/low_level/#state) of our application controls what data is input to the application, transferred between steps, and output by the application. It is typically a `TypedDict`, but can also be a [Pydantic BaseModel](https://langchain-ai.github.io/langgraph/how-tos/state-model/).\n", + "\n", + "For this application, we can just keep track of the input question, generated query, query result, and generated answer:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from typing_extensions import TypedDict\n", + "\n", + "\n", + "class State(TypedDict):\n", + " question: str\n", + " query: str\n", + " result: str\n", + " answer: str" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we just need functions that operate on this state and populate its contents.\n", + "\n", "### Convert question to SQL query\n", "\n", - "The first step in a SQL chain or agent is to take the user input and convert it to a SQL query. LangChain comes with a built-in chain for this: [create_sql_query_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.sql_database.query.create_sql_query_chain.html)." + "The first step is to take the user input and convert it to a SQL query. To reliably obtain SQL queries (absent markdown formatting and explanations or clarifications), we will make use of LangChain's [structured output](/docs/concepts/structured_outputs/) abstraction.\n", + "\n", + "Let's select a chat model for our application:" ] }, { @@ -161,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -170,208 +181,390 @@ "\n", "from langchain_openai import ChatOpenAI\n", "\n", - "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)" + "llm = ChatOpenAI(model=\"gpt-4o\", temperature=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will pull a prompt from the [Prompt Hub](https://smith.langchain.com/hub) to instruct the model." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m System Message \u001b[0m================================\n", + "\n", + "Given an input question, create a syntactically correct \u001b[33;1m\u001b[1;3m{dialect}\u001b[0m query to run to help find the answer. Unless the user specifies in his question a specific number of examples they wish to obtain, always limit your query to at most \u001b[33;1m\u001b[1;3m{top_k}\u001b[0m results. You can order the results by a relevant column to return the most interesting examples in the database.\n", + "\n", + "Never query for all the columns from a specific table, only ask for a the few relevant columns given the question.\n", + "\n", + "Pay attention to use only the column names that you can see in the schema description. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.\n", + "\n", + "Only use the following tables:\n", + "\u001b[33;1m\u001b[1;3m{table_info}\u001b[0m\n", + "\n", + "Question: \u001b[33;1m\u001b[1;3m{input}\u001b[0m\n" + ] + } + ], + "source": [ + "from langchain import hub\n", + "\n", + "query_prompt_template = hub.pull(\"langchain-ai/sql-query-system-prompt\")\n", + "\n", + "assert len(query_prompt_template.messages) == 1\n", + "query_prompt_template.messages[0].pretty_print()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The prompt includes several parameters we will need to populate, such as the SQL dialect and table schemas. LangChain's [SQLDatabase](https://python.langchain.com/api_reference/community/utilities/langchain_community.utilities.sql_database.SQLDatabase.html) object includes methods to help with this. Our `write_query` step will just populate these parameters and prompt a model to generate the SQL query:" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from typing_extensions import Annotated\n", + "\n", + "\n", + "class QueryOutput(TypedDict):\n", + " \"\"\"Generated SQL query.\"\"\"\n", + "\n", + " query: Annotated[str, ..., \"Syntactically valid SQL query.\"]\n", + "\n", + "\n", + "def write_query(state: State):\n", + " \"\"\"Generate SQL query to fetch information.\"\"\"\n", + " prompt = query_prompt_template.invoke(\n", + " {\n", + " \"dialect\": db.dialect,\n", + " \"top_k\": 10,\n", + " \"table_info\": db.get_table_info(),\n", + " \"input\": state[\"question\"],\n", + " }\n", + " )\n", + " structured_llm = llm.with_structured_output(QueryOutput)\n", + " result = structured_llm.invoke(prompt)\n", + " return {\"query\": result[\"query\"]}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's test it out:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'SELECT COUNT(\"EmployeeId\") AS \"TotalEmployees\" FROM \"Employee\"\\nLIMIT 1;'" + "{'query': 'SELECT COUNT(EmployeeId) AS EmployeeCount FROM Employee;'}" ] }, - "execution_count": 3, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from langchain.chains import create_sql_query_chain\n", + "write_query({\"question\": \"How many Employees are there?\"})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Execute query\n", + "\n", + "**This is the most dangerous part of creating a SQL chain.** Consider carefully if it is OK to run automated queries over your data. Minimize the database connection permissions as much as possible. Consider adding a human approval step to you chains before query execution (see below).\n", + "\n", + "To execute the query, we will load a tool from [langchain-community](/docs/concepts/architecture/#langchain-community). Our `execute_query` node will just wrap this tool:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_community.tools.sql_database.tool import QuerySQLDataBaseTool\n", + "\n", "\n", - "chain = create_sql_query_chain(llm, db)\n", - "response = chain.invoke({\"question\": \"How many employees are there\"})\n", - "response" + "def execute_query(state: State):\n", + " \"\"\"Execute SQL query.\"\"\"\n", + " execute_query_tool = QuerySQLDataBaseTool(db=db)\n", + " return {\"result\": execute_query_tool.invoke(state[\"query\"])}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We can execute the query to make sure it's valid:" + "Testing this step:" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'[(8,)]'" + "{'result': '[(8,)]'}" ] }, - "execution_count": 4, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "db.run(response)" + "execute_query({\"query\": \"SELECT COUNT(EmployeeId) AS EmployeeCount FROM Employee;\"})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generate answer\n", + "\n", + "Finally, our last step generates an answer to the question given the information pulled from the database:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def generate_answer(state: State):\n", + " \"\"\"Answer question using retrieved information as context.\"\"\"\n", + " prompt = (\n", + " \"Given the following user question, corresponding SQL query, \"\n", + " \"and SQL result, answer the user question.\\n\\n\"\n", + " f'Question: {state[\"question\"]}\\n'\n", + " f'SQL Query: {state[\"query\"]}\\n'\n", + " f'SQL Result: {state[\"result\"]}'\n", + " )\n", + " response = llm.invoke(prompt)\n", + " return {\"answer\": response.content}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We can look at the [LangSmith trace](https://smith.langchain.com/public/c8fa52ea-be46-4829-bde2-52894970b830/r) to get a better understanding of what this chain is doing. We can also inspect the chain directly for its prompts. Looking at the prompt (below), we can see that it is:\n", + "### Orchestrating with LangGraph\n", "\n", - "* Dialect-specific. In this case it references SQLite explicitly.\n", - "* Has definitions for all the available tables.\n", - "* Has three examples rows for each table.\n", + "Finally, we compile our application into a single `graph` object. In this case, we are just connecting the three steps into a single sequence." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "from langgraph.graph import START, StateGraph\n", "\n", - "This technique is inspired by papers like [this](https://arxiv.org/pdf/2204.00498.pdf), which suggest showing examples rows and being explicit about tables improves performance. We can also inspect the full prompt like so:" + "graph_builder = StateGraph(State).add_sequence(\n", + " [write_query, execute_query, generate_answer]\n", + ")\n", + "graph_builder.add_edge(START, \"write_query\")\n", + "graph = graph_builder.compile()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "LangGraph also comes with built-in utilities for visualizing the control flow of your application:" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import Image, display\n", + "\n", + "display(Image(graph.get_graph().draw_mermaid_png()))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's test our application! Note that we can stream the results of individual steps:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "You are a SQLite expert. Given an input question, first create a syntactically correct SQLite query to run, then look at the results of the query and return the answer to the input question.\n", - "Unless the user specifies in the question a specific number of examples to obtain, query for at most 5 results using the LIMIT clause as per SQLite. You can order the results to return the most informative data in the database.\n", - "Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (\") to denote them as delimited identifiers.\n", - "Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.\n", - "Pay attention to use date('now') function to get the current date, if the question involves \"today\".\n", - "\n", - "Use the following format:\n", - "\n", - "Question: Question here\n", - "SQLQuery: SQL Query to run\n", - "SQLResult: Result of the SQLQuery\n", - "Answer: Final answer here\n", - "\n", - "Only use the following tables:\n", - "\u001b[33;1m\u001b[1;3m{table_info}\u001b[0m\n", - "\n", - "Question: \u001b[33;1m\u001b[1;3m{input}\u001b[0m\n" + "{'write_query': {'query': 'SELECT COUNT(EmployeeId) AS EmployeeCount FROM Employee;'}}\n", + "{'execute_query': {'result': '[(8,)]'}}\n", + "{'generate_answer': {'answer': 'There are 8 employees.'}}\n" ] } ], "source": [ - "chain.get_prompts()[0].pretty_print()" + "for step in graph.stream(\n", + " {\"question\": \"How many employees are there?\"}, stream_mode=\"updates\"\n", + "):\n", + " print(step)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Execute SQL query\n", + "Check out the [LangSmith trace](https://smith.langchain.com/public/30a79380-6ba6-46af-8bd9-5d1df0b9ccca/r)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Human-in-the-loop\n", + "\n", + "LangGraph supports a number of features that can be useful for this workflow. One of them is [human-in-the-loop](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/): we can interrupt our application before sensitive steps (such as the execution of a SQL query) for human review. This is enabled by LangGraph's [persistence](https://langchain-ai.github.io/langgraph/concepts/persistence/) layer, which saves run progress to your storage of choice. Below, we specify storage in-memory:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from langgraph.checkpoint.memory import MemorySaver\n", "\n", - "Now that we've generated a SQL query, we'll want to execute it. **This is the most dangerous part of creating a SQL chain.** Consider carefully if it is OK to run automated queries over your data. Minimize the database connection permissions as much as possible. Consider adding a human approval step to you chains before query execution (see below).\n", + "memory = MemorySaver()\n", + "graph = graph_builder.compile(checkpointer=memory, interrupt_before=[\"execute_query\"])\n", "\n", - "We can use the `QuerySQLDatabaseTool` to easily add query execution to our chain:" + "# Now that we're using persistence, we need to specify a thread ID\n", + "# so that we can continue the run after review.\n", + "config = {\"configurable\": {\"thread_id\": \"1\"}}" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { + "image/png": "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", "text/plain": [ - "'[(8,)]'" + "" ] }, - "execution_count": 6, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "from langchain_community.tools.sql_database.tool import QuerySQLDataBaseTool\n", - "\n", - "execute_query = QuerySQLDataBaseTool(db=db)\n", - "write_query = create_sql_query_chain(llm, db)\n", - "chain = write_query | execute_query\n", - "chain.invoke({\"question\": \"How many employees are there\"})" + "display(Image(graph.get_graph().draw_mermaid_png()))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Answer the question\n", - "\n", - "Now that we've got a way to automatically generate and execute queries, we just need to combine the original question and SQL query result to generate a final answer. We can do this by passing question and result to the LLM once more:" + "Let's repeat the same run, adding in a simple yes/no approval step:" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 16, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "'There are a total of 8 employees.'" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "{'write_query': {'query': 'SELECT COUNT(EmployeeId) AS NumberOfEmployees FROM Employee;'}}\n", + "{'__interrupt__': ()}\n" + ] + }, + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Do you want to go to execute query? (yes/no): yes\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'execute_query': {'result': '[(8,)]'}}\n", + "{'generate_answer': {'answer': 'There are 8 employees.'}}\n" + ] } ], "source": [ - "from operator import itemgetter\n", - "\n", - "from langchain_core.output_parsers import StrOutputParser\n", - "from langchain_core.prompts import PromptTemplate\n", - "from langchain_core.runnables import RunnablePassthrough\n", - "\n", - "answer_prompt = PromptTemplate.from_template(\n", - " \"\"\"Given the following user question, corresponding SQL query, and SQL result, answer the user question.\n", - "\n", - "Question: {question}\n", - "SQL Query: {query}\n", - "SQL Result: {result}\n", - "Answer: \"\"\"\n", - ")\n", - "\n", - "chain = (\n", - " RunnablePassthrough.assign(query=write_query).assign(\n", - " result=itemgetter(\"query\") | execute_query\n", - " )\n", - " | answer_prompt\n", - " | llm\n", - " | StrOutputParser()\n", - ")\n", - "\n", - "chain.invoke({\"question\": \"How many employees are there\"})" + "for step in graph.stream(\n", + " {\"question\": \"How many employees are there?\"},\n", + " config,\n", + " stream_mode=\"updates\",\n", + "):\n", + " print(step)\n", + "\n", + "try:\n", + " user_approval = input(\"Do you want to go to execute query? (yes/no): \")\n", + "except Exception:\n", + " user_approval = \"no\"\n", + "\n", + "if user_approval.lower() == \"yes\":\n", + " # If approved, continue the graph execution\n", + " for step in graph.stream(None, config, stream_mode=\"updates\"):\n", + " print(step)\n", + "else:\n", + " print(\"Operation cancelled by user.\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Let's review what is happening in the above LCEL. Suppose this chain is invoked.\n", - "- After the first `RunnablePassthrough.assign`, we have a runnable with two elements: \n", - " `{\"question\": question, \"query\": write_query.invoke(question)}` \n", - " Where `write_query` will generate a SQL query in service of answering the question.\n", - "- After the second `RunnablePassthrough.assign`, we have add a third element `\"result\"` that contains `execute_query.invoke(query)`, where `query` was computed in the previous step.\n", - "- These three inputs are formatted into the prompt and passed into the LLM.\n", - "- The `StrOutputParser()` plucks out the string content of the output message.\n", - "\n", - "Note that we are composing LLMs, tools, prompts, and other chains together, but because each implements the Runnable interface, their inputs and outputs can be tied together in a reasonable way." + "See [this](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/) LangGraph guide for more detail and examples." ] }, { @@ -393,14 +586,22 @@ "source": [ "## Agents {#agents}\n", "\n", - "LangChain has a SQL Agent which provides a more flexible way of interacting with SQL Databases than a chain. The main advantages of using the SQL Agent are:\n", + "[Agents](/docs/concepts/agents) leverage the reasoning capabilities of LLMs to make decisions during execution. Using agents allows you to offload additional discretion over the query generation and execution process. Although their behavior is less predictable than the above \"chain\", they feature some advantages:\n", "\n", - "- It can answer questions based on the databases' schema as well as on the databases' content (like describing a specific table).\n", - "- It can recover from errors by running a generated query, catching the traceback and regenerating it correctly.\n", - "- It can query the database as many times as needed to answer the user question.\n", - "- It will save tokens by only retrieving the schema from relevant tables.\n", + "- They can query the database as many times as needed to answer the user question.\n", + "- They can recover from errors by running a generated query, catching the traceback and regenerating it correctly.\n", + "- They can answer questions based on the databases' schema as well as on the databases' content (like describing a specific table).\n", "\n", - "To initialize the agent we'll use the `SQLDatabaseToolkit` to create a bunch of tools:\n", + "\n", + "Below we assemble a minimal SQL agent. We will equip it with a set of tools using LangChain's [SQLDatabaseToolkit](https://python.langchain.com/api_reference/community/agent_toolkits/langchain_community.agent_toolkits.sql.toolkit.SQLDatabaseToolkit.html). Using LangGraph's [pre-built ReAct agent constructor](https://langchain-ai.github.io/langgraph/how-tos/#langgraph.prebuilt.chat_agent_executor.create_react_agent), we can do this in one line.\n", + "\n", + ":::tip\n", + "\n", + "Check out LangGraph's [SQL Agent Tutorial](https://langchain-ai.github.io/langgraph/tutorials/sql-agent/) for a more advanced formulation of a SQL agent.\n", + "\n", + ":::\n", + "\n", + "The `SQLDatabaseToolkit` includes tools that can:\n", "\n", "* Create and execute queries\n", "* Check query syntax\n", @@ -410,19 +611,19 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[QuerySQLDataBaseTool(description=\"Input to this tool is a detailed and correct SQL query, output is a result from the database. If the query is not correct, an error message will be returned. If an error is returned, rewrite the query, check the query, and try again. If you encounter an issue with Unknown column 'xxxx' in 'field list', use sql_db_schema to query the correct table fields.\", db=),\n", - " InfoSQLDatabaseTool(description='Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables. Be sure that the tables actually exist by calling sql_db_list_tables first! Example Input: table1, table2, table3', db=),\n", - " ListSQLDatabaseTool(db=),\n", - " QuerySQLCheckerTool(description='Use this tool to double check if your query is correct before executing it. Always use this tool before executing a query with sql_db_query!', db=, llm=ChatOpenAI(client=, async_client=, temperature=0.0, openai_api_key=SecretStr('**********'), openai_proxy=''), llm_chain=LLMChain(prompt=PromptTemplate(input_variables=['dialect', 'query'], template='\\n{query}\\nDouble check the {dialect} query above for common mistakes, including:\\n- Using NOT IN with NULL values\\n- Using UNION when UNION ALL should have been used\\n- Using BETWEEN for exclusive ranges\\n- Data type mismatch in predicates\\n- Properly quoting identifiers\\n- Using the correct number of arguments for functions\\n- Casting to the correct data type\\n- Using the proper columns for joins\\n\\nIf there are any of the above mistakes, rewrite the query. If there are no mistakes, just reproduce the original query.\\n\\nOutput the final SQL query only.\\n\\nSQL Query: '), llm=ChatOpenAI(client=, async_client=, temperature=0.0, openai_api_key=SecretStr('**********'), openai_proxy='')))]" + "[QuerySQLDataBaseTool(description=\"Input to this tool is a detailed and correct SQL query, output is a result from the database. If the query is not correct, an error message will be returned. If an error is returned, rewrite the query, check the query, and try again. If you encounter an issue with Unknown column 'xxxx' in 'field list', use sql_db_schema to query the correct table fields.\", db=),\n", + " InfoSQLDatabaseTool(description='Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables. Be sure that the tables actually exist by calling sql_db_list_tables first! Example Input: table1, table2, table3', db=),\n", + " ListSQLDatabaseTool(db=),\n", + " QuerySQLCheckerTool(description='Use this tool to double check if your query is correct before executing it. Always use this tool before executing a query with sql_db_query!', db=, llm=ChatOpenAI(client=, async_client=, root_client=, root_async_client=, model_name='gpt-4o', temperature=0.0, model_kwargs={}, openai_api_key=SecretStr('**********')), llm_chain=LLMChain(verbose=False, prompt=PromptTemplate(input_variables=['dialect', 'query'], input_types={}, partial_variables={}, template='\\n{query}\\nDouble check the {dialect} query above for common mistakes, including:\\n- Using NOT IN with NULL values\\n- Using UNION when UNION ALL should have been used\\n- Using BETWEEN for exclusive ranges\\n- Data type mismatch in predicates\\n- Properly quoting identifiers\\n- Using the correct number of arguments for functions\\n- Casting to the correct data type\\n- Using the proper columns for joins\\n\\nIf there are any of the above mistakes, rewrite the query. If there are no mistakes, just reproduce the original query.\\n\\nOutput the final SQL query only.\\n\\nSQL Query: '), llm=ChatOpenAI(client=, async_client=, root_client=, root_async_client=, model_name='gpt-4o', temperature=0.0, model_kwargs={}, openai_api_key=SecretStr('**********')), output_parser=StrOutputParser(), llm_kwargs={}))]" ] }, - "execution_count": 8, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -443,70 +644,81 @@ "source": [ "### System Prompt\n", "\n", - "We will also want to create a system prompt for our agent. This will consist of instructions for how to behave." + "We will also want to load a system prompt for our agent. This will consist of instructions for how to behave." ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m System Message \u001b[0m================================\n", + "\n", + "You are an agent designed to interact with a SQL database.\n", + "Given an input question, create a syntactically correct \u001b[33;1m\u001b[1;3m{dialect}\u001b[0m query to run, then look at the results of the query and return the answer.\n", + "Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most \u001b[33;1m\u001b[1;3m{top_k}\u001b[0m results.\n", + "You can order the results by a relevant column to return the most interesting examples in the database.\n", + "Never query for all the columns from a specific table, only ask for the relevant columns given the question.\n", + "You have access to tools for interacting with the database.\n", + "Only use the below tools. Only use the information returned by the below tools to construct your final answer.\n", + "You MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again.\n", + "\n", + "DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n", + "\n", + "To start you should ALWAYS look at the tables in the database to see what you can query.\n", + "Do NOT skip this step.\n", + "Then you should query the schema of the most relevant tables.\n" + ] + } + ], "source": [ - "from langchain_core.messages import SystemMessage\n", - "\n", - "SQL_PREFIX = \"\"\"You are an agent designed to interact with a SQL database.\n", - "Given an input question, create a syntactically correct SQLite query to run, then look at the results of the query and return the answer.\n", - "Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most 5 results.\n", - "You can order the results by a relevant column to return the most interesting examples in the database.\n", - "Never query for all the columns from a specific table, only ask for the relevant columns given the question.\n", - "You have access to tools for interacting with the database.\n", - "Only use the below tools. Only use the information returned by the below tools to construct your final answer.\n", - "You MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again.\n", + "from langchain import hub\n", "\n", - "DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n", + "prompt_template = hub.pull(\"langchain-ai/sql-agent-system-prompt\")\n", "\n", - "To start you should ALWAYS look at the tables in the database to see what you can query.\n", - "Do NOT skip this step.\n", - "Then you should query the schema of the most relevant tables.\"\"\"\n", - "\n", - "system_message = SystemMessage(content=SQL_PREFIX)" + "assert len(prompt_template.messages) == 1\n", + "prompt_template.messages[0].pretty_print()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Initializing agent\n", - "First, get required package **LangGraph**" + "Let's populate the parameters highlighted in the prompt:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ - "%%capture --no-stderr\n", - "%pip install --upgrade --quiet langgraph" + "system_message = prompt_template.format(dialect=\"SQLite\", top_k=5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ + "### Initializing agent\n", + "\n", "We will use a prebuilt [LangGraph](/docs/concepts/architecture/#langgraph) agent to build our agent" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "from langgraph.prebuilt import create_react_agent\n", "\n", - "agent_executor = create_react_agent(llm, tools, messages_modifier=system_message)" + "agent_executor = create_react_agent(llm, tools, state_modifier=system_message)" ] }, { @@ -518,42 +730,127 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_vnHKe3oul1xbpX0Vrb2vsamZ', 'function': {'arguments': '{\"query\":\"SELECT c.Country, SUM(i.Total) AS Total_Spent FROM customers c JOIN invoices i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY Total_Spent DESC LIMIT 1\"}', 'name': 'sql_db_query'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 53, 'prompt_tokens': 557, 'total_tokens': 610}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-da250593-06b5-414c-a9d9-3fc77036dd9c-0', tool_calls=[{'name': 'sql_db_query', 'args': {'query': 'SELECT c.Country, SUM(i.Total) AS Total_Spent FROM customers c JOIN invoices i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY Total_Spent DESC LIMIT 1'}, 'id': 'call_vnHKe3oul1xbpX0Vrb2vsamZ'}])]}}\n", - "----\n", - "{'action': {'messages': [ToolMessage(content='Error: (sqlite3.OperationalError) no such table: customers\\n[SQL: SELECT c.Country, SUM(i.Total) AS Total_Spent FROM customers c JOIN invoices i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY Total_Spent DESC LIMIT 1]\\n(Background on this error at: https://sqlalche.me/e/20/e3q8)', name='sql_db_query', id='1a5c85d4-1b30-4af3-ab9b-325cbce3b2b4', tool_call_id='call_vnHKe3oul1xbpX0Vrb2vsamZ')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_pp3BBD1hwpdwskUj63G3tgaQ', 'function': {'arguments': '{}', 'name': 'sql_db_list_tables'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 12, 'prompt_tokens': 699, 'total_tokens': 711}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-04cf0e05-61d0-4673-b5dc-1a9b5fd71fff-0', tool_calls=[{'name': 'sql_db_list_tables', 'args': {}, 'id': 'call_pp3BBD1hwpdwskUj63G3tgaQ'}])]}}\n", - "----\n", - "{'action': {'messages': [ToolMessage(content='Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track', name='sql_db_list_tables', id='c2668450-4d73-4d32-8d75-8aac8fa153fd', tool_call_id='call_pp3BBD1hwpdwskUj63G3tgaQ')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_22Asbqgdx26YyEvJxBuANVdY', 'function': {'arguments': '{\"query\":\"SELECT c.Country, SUM(i.Total) AS Total_Spent FROM Customer c JOIN Invoice i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY Total_Spent DESC LIMIT 1\"}', 'name': 'sql_db_query'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 53, 'prompt_tokens': 744, 'total_tokens': 797}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-bdd94241-ca49-4f15-b31a-b7c728a34ea8-0', tool_calls=[{'name': 'sql_db_query', 'args': {'query': 'SELECT c.Country, SUM(i.Total) AS Total_Spent FROM Customer c JOIN Invoice i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY Total_Spent DESC LIMIT 1'}, 'id': 'call_22Asbqgdx26YyEvJxBuANVdY'}])]}}\n", - "----\n", - "{'action': {'messages': [ToolMessage(content=\"[('USA', 523.0600000000003)]\", name='sql_db_query', id='f647e606-8362-40ab-8d34-612ff166dbe1', tool_call_id='call_22Asbqgdx26YyEvJxBuANVdY')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='Customers from the USA spent the most, with a total amount spent of $523.06.', response_metadata={'token_usage': {'completion_tokens': 20, 'prompt_tokens': 819, 'total_tokens': 839}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'stop', 'logprobs': None}, id='run-92e88de0-ff62-41da-8181-053fb5632af4-0')]}}\n", - "----\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Which country's customers spent the most?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_list_tables (call_J7Cj6d9gqkaOwiB99fv8y6uh)\n", + " Call ID: call_J7Cj6d9gqkaOwiB99fv8y6uh\n", + " Args:\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_list_tables\n", + "\n", + "Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_schema (call_zF4O1BfsAfEfQP85vvHPu6Kp)\n", + " Call ID: call_zF4O1BfsAfEfQP85vvHPu6Kp\n", + " Args:\n", + " table_names: Customer, Invoice\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_schema\n", + "\n", + "\n", + "CREATE TABLE \"Customer\" (\n", + "\t\"CustomerId\" INTEGER NOT NULL, \n", + "\t\"FirstName\" NVARCHAR(40) NOT NULL, \n", + "\t\"LastName\" NVARCHAR(20) NOT NULL, \n", + "\t\"Company\" NVARCHAR(80), \n", + "\t\"Address\" NVARCHAR(70), \n", + "\t\"City\" NVARCHAR(40), \n", + "\t\"State\" NVARCHAR(40), \n", + "\t\"Country\" NVARCHAR(40), \n", + "\t\"PostalCode\" NVARCHAR(10), \n", + "\t\"Phone\" NVARCHAR(24), \n", + "\t\"Fax\" NVARCHAR(24), \n", + "\t\"Email\" NVARCHAR(60) NOT NULL, \n", + "\t\"SupportRepId\" INTEGER, \n", + "\tPRIMARY KEY (\"CustomerId\"), \n", + "\tFOREIGN KEY(\"SupportRepId\") REFERENCES \"Employee\" (\"EmployeeId\")\n", + ")\n", + "\n", + "/*\n", + "3 rows from Customer table:\n", + "CustomerId\tFirstName\tLastName\tCompany\tAddress\tCity\tState\tCountry\tPostalCode\tPhone\tFax\tEmail\tSupportRepId\n", + "1\tLuís\tGonçalves\tEmbraer - Empresa Brasileira de Aeronáutica S.A.\tAv. Brigadeiro Faria Lima, 2170\tSão José dos Campos\tSP\tBrazil\t12227-000\t+55 (12) 3923-5555\t+55 (12) 3923-5566\tluisg@embraer.com.br\t3\n", + "2\tLeonie\tKöhler\tNone\tTheodor-Heuss-Straße 34\tStuttgart\tNone\tGermany\t70174\t+49 0711 2842222\tNone\tleonekohler@surfeu.de\t5\n", + "3\tFrançois\tTremblay\tNone\t1498 rue Bélanger\tMontréal\tQC\tCanada\tH2G 1A7\t+1 (514) 721-4711\tNone\tftremblay@gmail.com\t3\n", + "*/\n", + "\n", + "\n", + "CREATE TABLE \"Invoice\" (\n", + "\t\"InvoiceId\" INTEGER NOT NULL, \n", + "\t\"CustomerId\" INTEGER NOT NULL, \n", + "\t\"InvoiceDate\" DATETIME NOT NULL, \n", + "\t\"BillingAddress\" NVARCHAR(70), \n", + "\t\"BillingCity\" NVARCHAR(40), \n", + "\t\"BillingState\" NVARCHAR(40), \n", + "\t\"BillingCountry\" NVARCHAR(40), \n", + "\t\"BillingPostalCode\" NVARCHAR(10), \n", + "\t\"Total\" NUMERIC(10, 2) NOT NULL, \n", + "\tPRIMARY KEY (\"InvoiceId\"), \n", + "\tFOREIGN KEY(\"CustomerId\") REFERENCES \"Customer\" (\"CustomerId\")\n", + ")\n", + "\n", + "/*\n", + "3 rows from Invoice table:\n", + "InvoiceId\tCustomerId\tInvoiceDate\tBillingAddress\tBillingCity\tBillingState\tBillingCountry\tBillingPostalCode\tTotal\n", + "1\t2\t2021-01-01 00:00:00\tTheodor-Heuss-Straße 34\tStuttgart\tNone\tGermany\t70174\t1.98\n", + "2\t4\t2021-01-02 00:00:00\tUllevålsveien 14\tOslo\tNone\tNorway\t0171\t3.96\n", + "3\t8\t2021-01-03 00:00:00\tGrétrystraat 63\tBrussels\tNone\tBelgium\t1000\t5.94\n", + "*/\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_query_checker (call_YkdCcgJOzVUc4IsI3ytLPf0x)\n", + " Call ID: call_YkdCcgJOzVUc4IsI3ytLPf0x\n", + " Args:\n", + " query: SELECT c.Country, SUM(i.Total) as TotalSpent FROM Customer c JOIN Invoice i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY TotalSpent DESC LIMIT 1;\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_query_checker\n", + "\n", + "```sql\n", + "SELECT c.Country, SUM(i.Total) as TotalSpent FROM Customer c JOIN Invoice i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY TotalSpent DESC LIMIT 1;\n", + "```\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_query (call_cojsHW4TTadu9fe6oooMr4Y9)\n", + " Call ID: call_cojsHW4TTadu9fe6oooMr4Y9\n", + " Args:\n", + " query: SELECT c.Country, SUM(i.Total) as TotalSpent FROM Customer c JOIN Invoice i ON c.CustomerId = i.CustomerId GROUP BY c.Country ORDER BY TotalSpent DESC LIMIT 1;\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_query\n", + "\n", + "[('USA', 523.06)]\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "The country whose customers spent the most is the USA, with a total spending of 523.06.\n" ] } ], "source": [ - "for s in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=\"Which country's customers spent the most?\")]}\n", + "question = \"Which country's customers spent the most?\"\n", + "\n", + "for step in agent_executor.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": question}]},\n", + " stream_mode=\"values\",\n", "):\n", - " print(s)\n", - " print(\"----\")" + " step[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ + "You can also use the [LangSmith trace](https://smith.langchain.com/public/8af422aa-b651-4bfe-8683-e2a7f4ccd82c/r) to visualize these steps and associated metadata.\n", + "\n", "Note that the agent executes multiple queries until it has the information it needs:\n", "1. List available tables;\n", "2. Retrieves the schema for three tables;\n", @@ -566,36 +863,69 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_WN0N3mm8WFvPXYlK9P7KvIEr', 'function': {'arguments': '{\"table_names\":\"playlisttrack\"}', 'name': 'sql_db_schema'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 17, 'prompt_tokens': 554, 'total_tokens': 571}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-be278326-4115-4c67-91a0-6dc97e7bffa4-0', tool_calls=[{'name': 'sql_db_schema', 'args': {'table_names': 'playlisttrack'}, 'id': 'call_WN0N3mm8WFvPXYlK9P7KvIEr'}])]}}\n", - "----\n", - "{'action': {'messages': [ToolMessage(content=\"Error: table_names {'playlisttrack'} not found in database\", name='sql_db_schema', id='fe32b3d3-a40f-4802-a6b8-87a2453af8c2', tool_call_id='call_WN0N3mm8WFvPXYlK9P7KvIEr')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='I apologize for the error. Let me first check the available tables in the database.', additional_kwargs={'tool_calls': [{'id': 'call_CzHt30847ql2MmnGxgYeVSL2', 'function': {'arguments': '{}', 'name': 'sql_db_list_tables'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 30, 'prompt_tokens': 592, 'total_tokens': 622}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-f6c107bb-e945-4848-a83c-f57daec1144e-0', tool_calls=[{'name': 'sql_db_list_tables', 'args': {}, 'id': 'call_CzHt30847ql2MmnGxgYeVSL2'}])]}}\n", - "----\n", - "{'action': {'messages': [ToolMessage(content='Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track', name='sql_db_list_tables', id='a4950f74-a0ad-4558-ba54-7bcf99539a02', tool_call_id='call_CzHt30847ql2MmnGxgYeVSL2')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='The database contains a table named \"PlaylistTrack\". Let me retrieve the schema and sample rows from the \"PlaylistTrack\" table.', additional_kwargs={'tool_calls': [{'id': 'call_wX9IjHLgRBUmxlfCthprABRO', 'function': {'arguments': '{\"table_names\":\"PlaylistTrack\"}', 'name': 'sql_db_schema'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 44, 'prompt_tokens': 658, 'total_tokens': 702}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-e8d34372-1159-4654-a185-1e7d0cb70269-0', tool_calls=[{'name': 'sql_db_schema', 'args': {'table_names': 'PlaylistTrack'}, 'id': 'call_wX9IjHLgRBUmxlfCthprABRO'}])]}}\n", - "----\n", - "{'action': {'messages': [ToolMessage(content='\\nCREATE TABLE \"PlaylistTrack\" (\\n\\t\"PlaylistId\" INTEGER NOT NULL, \\n\\t\"TrackId\" INTEGER NOT NULL, \\n\\tPRIMARY KEY (\"PlaylistId\", \"TrackId\"), \\n\\tFOREIGN KEY(\"TrackId\") REFERENCES \"Track\" (\"TrackId\"), \\n\\tFOREIGN KEY(\"PlaylistId\") REFERENCES \"Playlist\" (\"PlaylistId\")\\n)\\n\\n/*\\n3 rows from PlaylistTrack table:\\nPlaylistId\\tTrackId\\n1\\t3402\\n1\\t3389\\n1\\t3390\\n*/', name='sql_db_schema', id='f6ffc37a-188a-4690-b84e-c9f2c78b1e49', tool_call_id='call_wX9IjHLgRBUmxlfCthprABRO')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='The \"PlaylistTrack\" table has the following schema:\\n- PlaylistId: INTEGER (NOT NULL)\\n- TrackId: INTEGER (NOT NULL)\\n- Primary Key: (PlaylistId, TrackId)\\n- Foreign Key: TrackId references Track(TrackId)\\n- Foreign Key: PlaylistId references Playlist(PlaylistId)\\n\\nHere are 3 sample rows from the \"PlaylistTrack\" table:\\n1. PlaylistId: 1, TrackId: 3402\\n2. PlaylistId: 1, TrackId: 3389\\n3. PlaylistId: 1, TrackId: 3390\\n\\nIf you have any specific questions or queries regarding the \"PlaylistTrack\" table, feel free to ask!', response_metadata={'token_usage': {'completion_tokens': 145, 'prompt_tokens': 818, 'total_tokens': 963}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'stop', 'logprobs': None}, id='run-961a4552-3cbd-4d28-b338-4d2f1ac40ea0-0')]}}\n", - "----\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Describe the playlisttrack table\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_list_tables (call_7o2lQBlRAoqGtbF17AW3b4RV)\n", + " Call ID: call_7o2lQBlRAoqGtbF17AW3b4RV\n", + " Args:\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_list_tables\n", + "\n", + "Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_schema (call_xZx5tqzBAlPNiktWsuoafd4t)\n", + " Call ID: call_xZx5tqzBAlPNiktWsuoafd4t\n", + " Args:\n", + " table_names: PlaylistTrack\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_schema\n", + "\n", + "\n", + "CREATE TABLE \"PlaylistTrack\" (\n", + "\t\"PlaylistId\" INTEGER NOT NULL, \n", + "\t\"TrackId\" INTEGER NOT NULL, \n", + "\tPRIMARY KEY (\"PlaylistId\", \"TrackId\"), \n", + "\tFOREIGN KEY(\"TrackId\") REFERENCES \"Track\" (\"TrackId\"), \n", + "\tFOREIGN KEY(\"PlaylistId\") REFERENCES \"Playlist\" (\"PlaylistId\")\n", + ")\n", + "\n", + "/*\n", + "3 rows from PlaylistTrack table:\n", + "PlaylistId\tTrackId\n", + "1\t3402\n", + "1\t3389\n", + "1\t3390\n", + "*/\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "The `PlaylistTrack` table is a junction table that connects playlists and tracks. It has the following columns:\n", + "\n", + "- `PlaylistId`: An integer that references the `PlaylistId` in the `Playlist` table. It is part of the composite primary key.\n", + "- `TrackId`: An integer that references the `TrackId` in the `Track` table. It is also part of the composite primary key.\n", + "\n", + "The primary key for this table is a combination of `PlaylistId` and `TrackId`, ensuring that each track can only appear once in a specific playlist. The table also enforces foreign key constraints to maintain referential integrity with the `Playlist` and `Track` tables.\n" ] } ], "source": [ - "for s in agent_executor.stream(\n", - " {\"messages\": [HumanMessage(content=\"Describe the playlisttrack table\")]}\n", + "question = \"Describe the playlisttrack table\"\n", + "\n", + "for step in agent_executor.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": question}]},\n", + " stream_mode=\"values\",\n", "):\n", - " print(s)\n", - " print(\"----\")" + " step[\"messages\"][-1].pretty_print()" ] }, { @@ -613,20 +943,20 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['Big Ones',\n", - " 'Cidade Negra - Hits',\n", - " 'In Step',\n", - " 'Use Your Illusion I',\n", - " 'Voodoo Lounge']" + "['In Through The Out Door',\n", + " 'Transmission',\n", + " 'Battlestar Galactica (Classic), Season',\n", + " 'A Copland Celebration, Vol. I',\n", + " 'Quiet Songs']" ] }, - "execution_count": 36, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -652,23 +982,78 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Using this function, we can create a **retriever tool** that the agent can execute at its discretion." + "Using this function, we can create a **retriever tool** that the agent can execute at its discretion.\n", + "\n", + "Let's select an [embeddings model](/docs/integrations/text_embedding/) and [vector store](/docs/integrations/vectorstores/) for this step:\n", + "\n", + "**Select an embedding model**:\n", + "\n", + "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n", + "\n", + "" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ - "from langchain.agents.agent_toolkits import create_retriever_tool\n", - "from langchain_community.vectorstores import FAISS\n", + "# | output: false\n", + "# | echo: false\n", + "\n", "from langchain_openai import OpenAIEmbeddings\n", "\n", - "vector_db = FAISS.from_texts(artists + albums, OpenAIEmbeddings())\n", - "retriever = vector_db.as_retriever(search_kwargs={\"k\": 5})\n", - "description = \"\"\"Use to look up values to filter on. Input is an approximate spelling of the proper noun, output is \\\n", - "valid proper nouns. Use the noun most similar to the search.\"\"\"\n", + "embeddings = OpenAIEmbeddings()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Select a vector store**:\n", + "\n", + "import VectorStoreTabs from \"@theme/VectorStoreTabs\";\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "# | output: false\n", + "# | echo: false\n", + "\n", + "from langchain_core.vectorstores import InMemoryVectorStore\n", + "\n", + "vector_store = InMemoryVectorStore(embeddings)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can now construct a retrieval tool that can search over relevant proper nouns in the database:" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.agents.agent_toolkits import create_retriever_tool\n", + "\n", + "_ = vector_store.add_texts(artists + albums)\n", + "retriever = vector_store.as_retriever(search_kwargs={\"k\": 5})\n", + "description = (\n", + " \"Use to look up values to filter on. Input is an approximate spelling \"\n", + " \"of the proper noun, output is valid proper nouns. Use the noun most \"\n", + " \"similar to the search.\"\n", + ")\n", "retriever_tool = create_retriever_tool(\n", " retriever,\n", " name=\"search_proper_nouns\",\n", @@ -685,7 +1070,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -719,66 +1104,146 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ - "system = \"\"\"You are an agent designed to interact with a SQL database.\n", - "Given an input question, create a syntactically correct SQLite query to run, then look at the results of the query and return the answer.\n", - "Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most 5 results.\n", - "You can order the results by a relevant column to return the most interesting examples in the database.\n", - "Never query for all the columns from a specific table, only ask for the relevant columns given the question.\n", - "You have access to tools for interacting with the database.\n", - "Only use the given tools. Only use the information returned by the tools to construct your final answer.\n", - "You MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again.\n", - "\n", - "DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n", - "\n", - "You have access to the following tables: {table_names}\n", - "\n", - "If you need to filter on a proper noun, you must ALWAYS first look up the filter value using the \"search_proper_nouns\" tool!\n", - "Do not try to guess at the proper name - use this function to find similar ones.\"\"\".format(\n", - " table_names=db.get_usable_table_names()\n", + "# Add to system message\n", + "suffix = (\n", + " \"If you need to filter on a proper noun like a Name, you must ALWAYS first look up \"\n", + " \"the filter value using the 'search_proper_nouns' tool! Do not try to \"\n", + " \"guess at the proper name - use this function to find similar ones.\"\n", ")\n", "\n", - "system_message = SystemMessage(content=system)\n", + "system = f\"{system_message}\\n\\n{suffix}\"\n", "\n", "tools.append(retriever_tool)\n", "\n", - "agent = create_react_agent(llm, tools, messages_modifier=system_message)" + "agent = create_react_agent(llm, tools, state_modifier=system)" ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_r5UlSwHKQcWDHx6LrttnqE56', 'function': {'arguments': '{\"query\":\"SELECT COUNT(*) AS album_count FROM Album WHERE ArtistId IN (SELECT ArtistId FROM Artist WHERE Name = \\'Alice In Chains\\')\"}', 'name': 'sql_db_query'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 40, 'prompt_tokens': 612, 'total_tokens': 652}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-548353fd-b06c-45bf-beab-46f81eb434df-0', tool_calls=[{'name': 'sql_db_query', 'args': {'query': \"SELECT COUNT(*) AS album_count FROM Album WHERE ArtistId IN (SELECT ArtistId FROM Artist WHERE Name = 'Alice In Chains')\"}, 'id': 'call_r5UlSwHKQcWDHx6LrttnqE56'}])]}}\n", - "----\n", - "{'action': {'messages': [ToolMessage(content='[(1,)]', name='sql_db_query', id='093058a9-f013-4be1-8e7a-ed839b0c90cd', tool_call_id='call_r5UlSwHKQcWDHx6LrttnqE56')]}}\n", - "----\n", - "{'agent': {'messages': [AIMessage(content='Alice In Chains has 11 albums.', response_metadata={'token_usage': {'completion_tokens': 9, 'prompt_tokens': 665, 'total_tokens': 674}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_3b956da36b', 'finish_reason': 'stop', 'logprobs': None}, id='run-f804eaab-9812-4fb3-ae8b-280af8594ac6-0')]}}\n", - "----\n" + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "How many albums does alis in chain have?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " search_proper_nouns (call_8ryjsRPLAr79mM3Qvnq6gTOH)\n", + " Call ID: call_8ryjsRPLAr79mM3Qvnq6gTOH\n", + " Args:\n", + " query: alis in chain\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: search_proper_nouns\n", + "\n", + "Alice In Chains\n", + "\n", + "Aisha Duo\n", + "\n", + "Xis\n", + "\n", + "Da Lama Ao Caos\n", + "\n", + "A-Sides\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_list_tables (call_NJjtCpU89MBMplssjn1z0xzq)\n", + " Call ID: call_NJjtCpU89MBMplssjn1z0xzq\n", + " Args:\n", + " search_proper_nouns (call_1BfrueC9koSIyi4OfMu2Ao8q)\n", + " Call ID: call_1BfrueC9koSIyi4OfMu2Ao8q\n", + " Args:\n", + " query: Alice In Chains\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: search_proper_nouns\n", + "\n", + "Alice In Chains\n", + "\n", + "Pearl Jam\n", + "\n", + "Pearl Jam\n", + "\n", + "Foo Fighters\n", + "\n", + "Soundgarden\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_schema (call_Kn09w9jd9swcNzIZ1b5MlKID)\n", + " Call ID: call_Kn09w9jd9swcNzIZ1b5MlKID\n", + " Args:\n", + " table_names: Album, Artist\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_schema\n", + "\n", + "\n", + "CREATE TABLE \"Album\" (\n", + "\t\"AlbumId\" INTEGER NOT NULL, \n", + "\t\"Title\" NVARCHAR(160) NOT NULL, \n", + "\t\"ArtistId\" INTEGER NOT NULL, \n", + "\tPRIMARY KEY (\"AlbumId\"), \n", + "\tFOREIGN KEY(\"ArtistId\") REFERENCES \"Artist\" (\"ArtistId\")\n", + ")\n", + "\n", + "/*\n", + "3 rows from Album table:\n", + "AlbumId\tTitle\tArtistId\n", + "1\tFor Those About To Rock We Salute You\t1\n", + "2\tBalls to the Wall\t2\n", + "3\tRestless and Wild\t2\n", + "*/\n", + "\n", + "\n", + "CREATE TABLE \"Artist\" (\n", + "\t\"ArtistId\" INTEGER NOT NULL, \n", + "\t\"Name\" NVARCHAR(120), \n", + "\tPRIMARY KEY (\"ArtistId\")\n", + ")\n", + "\n", + "/*\n", + "3 rows from Artist table:\n", + "ArtistId\tName\n", + "1\tAC/DC\n", + "2\tAccept\n", + "3\tAerosmith\n", + "*/\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " sql_db_query (call_WkHRiPcBoGN9bc58MIupRHKP)\n", + " Call ID: call_WkHRiPcBoGN9bc58MIupRHKP\n", + " Args:\n", + " query: SELECT COUNT(*) FROM Album WHERE ArtistId = (SELECT ArtistId FROM Artist WHERE Name = 'Alice In Chains')\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: sql_db_query\n", + "\n", + "[(1,)]\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Alice In Chains has released 1 album in the database.\n" ] } ], "source": [ - "for s in agent.stream(\n", - " {\"messages\": [HumanMessage(content=\"How many albums does alis in chain have?\")]}\n", + "question = \"How many albums does alis in chain have?\"\n", + "\n", + "for step in agent.stream(\n", + " {\"messages\": [{\"role\": \"user\", \"content\": question}]},\n", + " stream_mode=\"values\",\n", "):\n", - " print(s)\n", - " print(\"----\")" + " step[\"messages\"][-1].pretty_print()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "As we can see, the agent used the `search_proper_nouns` tool in order to check how to correctly query the database for this specific artist." + "As we can see, both in the streamed steps and in the [LangSmith trace](https://smith.langchain.com/public/1d757ed2-5688-4458-9400-023594e2c5a7/r), the agent used the `search_proper_nouns` tool in order to check how to correctly query the database for this specific artist." ] } ], @@ -798,7 +1263,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.1" + "version": "3.10.4" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/summarization.ipynb b/docs/docs/tutorials/summarization.ipynb index 1669f5f071dce..f4800405007eb 100644 --- a/docs/docs/tutorials/summarization.ipynb +++ b/docs/docs/tutorials/summarization.ipynb @@ -124,7 +124,7 @@ "\n", "A central question for building a summarizer is how to pass your documents into the LLM's context window. Two common approaches for this are:\n", "\n", - "1. `Stuff`: Simply \"stuff\" all your documents into a single prompt. This is the simplest approach (see [here](/docs/tutorials/rag#built-in-chains) for more on the `create_stuff_documents_chain` constructor, which is used for this method).\n", + "1. `Stuff`: Simply \"stuff\" all your documents into a single prompt. This is the simplest approach (see [here](/docs/how_to/summarize_stuff/) for more on the `create_stuff_documents_chain` constructor, which is used for this method).\n", "\n", "2. `Map-reduce`: Summarize each document on its own in a \"map\" step and then \"reduce\" the summaries into a final summary (see [here](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html) for more on the `MapReduceDocumentsChain`, which is used for this method).\n", "\n", @@ -251,17 +251,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "The article \"LLM Powered Autonomous Agents\" by Lilian Weng discusses the development and capabilities of autonomous agents powered by large language models (LLMs). It outlines a system architecture that includes three main components: planning, memory, and tool use. \n", + "The article \"LLM Powered Autonomous Agents\" by Lilian Weng discusses the development and capabilities of autonomous agents powered by large language models (LLMs). It outlines a system architecture that includes three main components: Planning, Memory, and Tool Use. \n", "\n", - "1. **Planning**: Agents decompose complex tasks into manageable subgoals and engage in self-reflection to improve their performance over time. Techniques like Chain of Thought (CoT) and Tree of Thoughts (ToT) are highlighted for enhancing reasoning and planning.\n", + "1. **Planning** involves task decomposition, where complex tasks are broken down into manageable subgoals, and self-reflection, allowing agents to learn from past actions to improve future performance. Techniques like Chain of Thought (CoT) and Tree of Thoughts (ToT) are highlighted for enhancing reasoning and planning.\n", "\n", - "2. **Memory**: The article distinguishes between short-term and long-term memory, explaining how agents can utilize in-context learning and external vector stores for information retrieval. Maximum Inner Product Search (MIPS) algorithms are discussed for efficient memory access.\n", + "2. **Memory** is categorized into short-term and long-term memory, with mechanisms for fast retrieval using Maximum Inner Product Search (MIPS) algorithms. This allows agents to retain and recall information effectively.\n", "\n", - "3. **Tool Use**: The integration of external tools allows agents to extend their capabilities beyond their inherent knowledge. Examples include MRKL systems and frameworks like HuggingGPT, which facilitate task planning and execution through API calls.\n", + "3. **Tool Use** enables agents to interact with external APIs and tools, enhancing their capabilities beyond the limitations of their training data. Examples include MRKL systems and frameworks like HuggingGPT, which facilitate task planning and execution.\n", "\n", - "The article also addresses challenges faced by LLM-powered agents, such as finite context length, difficulties in long-term planning, and the reliability of natural language interfaces. It concludes with case studies demonstrating the practical applications of these agents in scientific discovery and interactive simulations.\n", - "\n", - "Overall, the article emphasizes the potential of LLMs as general problem solvers and their ability to function as autonomous agents in various domains.\n" + "The article also addresses challenges such as finite context length, difficulties in long-term planning, and the reliability of natural language interfaces. It concludes with case studies demonstrating the practical applications of these concepts in scientific discovery and interactive simulations. Overall, the article emphasizes the potential of LLMs as powerful problem solvers in autonomous agent systems.\n" ] } ], @@ -296,22 +294,22 @@ { "cell_type": "code", "execution_count": 7, - "id": "b7a89b7a-0141-4689-b768-a2a50cdce7da", + "id": "ebc5b1ff-512f-4732-b385-b8829e069de8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "|The| article| \"|LL|M| Powered| Autonomous| Agents|\"| by| Lil|ian| W|eng| discusses| the| development| and| capabilities| of| autonomous| agents| powered| by| large| language| models| (|LL|Ms|).| It| outlines| a| system| overview| that| includes| three| main| components|:| planning|,| memory|,| and| tool| use|.| \n", + "|The| article| \"|LL|M| Powered| Autonomous| Agents|\"| by| Lil|ian| W|eng| discusses| the| development| and| capabilities| of| autonomous| agents| powered| by| large| language| models| (|LL|Ms|).| It| outlines| a| system| architecture| that| includes| three| main| components|:| Planning|,| Memory|,| and| Tool| Use|.| \n", "\n", - "|1|.| **|Planning|**| involves| task| decomposition|,| where| agents| break| down| complex| tasks| into| manageable| sub|go|als|,| and| self|-ref|lection|,| allowing| agents| to| learn| from| past| actions| to| improve| future| performance|.\n", + "|1|.| **|Planning|**| involves| task| decomposition|,| where| complex| tasks| are| broken| down| into| manageable| sub|go|als|,| and| self|-ref|lection|,| allowing| agents| to| learn| from| past| actions| to| improve| future| performance|.| Techniques| like| Chain| of| Thought| (|Co|T|)| and| Tree| of| Thoughts| (|To|T|)| are| highlighted| for| enhancing| reasoning| and| planning|.\n", "\n", - "|2|.| **|Memory|**| is| categorized| into| short|-term| and| long|-term| memory|,| with| techniques| like| Maximum| Inner| Product| Search| (|M|IPS|)| used| for| efficient| information| retrieval|.\n", + "|2|.| **|Memory|**| is| categorized| into| short|-term| and| long|-term| memory|,| with| mechanisms| for| fast| retrieval| using| Maximum| Inner| Product| Search| (|M|IPS|)| algorithms|.| This| allows| agents| to| retain| and| recall| information| effectively|.\n", "\n", - "|3|.| **|Tool| Use|**| highlights| the| integration| of| external| APIs| to| enhance| the| agent|'s| capabilities|,| illustrated| through| case| studies| like| Chem|Crow| for| scientific| discovery| and| Gener|ative| Agents| for| sim|ulating| human| behavior|.\n", + "|3|.| **|Tool| Use|**| emphasizes| the| integration| of| external| APIs| and| tools| to| extend| the| capabilities| of| L|LM|s|,| enabling| them| to| perform| tasks| beyond| their| inherent| limitations|.| Examples| include| MR|KL| systems| and| frameworks| like| Hug|ging|GPT|,| which| facilitate| task| planning| and| execution|.\n", "\n", - "|The| article| also| addresses| challenges| such| as| finite| context| length|,| difficulties| in| long|-term| planning|,| and| the| reliability| of| natural| language| interfaces|.| It| concludes| with| references| to| various| studies| and| projects| that| contribute| to| the| field| of| L|LM|-powered| agents|.||" + "|The| article| also| addresses| challenges| such| as| finite| context| length|,| difficulties| in| long|-term| planning|,| and| the| reliability| of| natural| language| interfaces|.| It| concludes| with| case| studies| demonstrating| the| practical| applications| of| L|LM|-powered| agents| in| scientific| discovery| and| interactive| simulations|.| Overall|,| the| piece| illustrates| the| potential| of| L|LM|s| as| general| problem| sol|vers| and| their| evolving| role| in| autonomous| systems|.||" ] } ], @@ -349,7 +347,7 @@ "- The LangGraph implementation is straightforward to modify and extend, as we will see below.\n", "\n", "### Map\n", - "Let's first define the prompt associated with the map step, and associated it with the LLM via a [chain](/docs/how_to/sequence/). We can use the same summarization prompt as in the `stuff` approach, above:" + "Let's first define the prompt associated with the map step. We can use the same summarization prompt as in the `stuff` approach, above:" ] }, { @@ -359,14 +357,11 @@ "metadata": {}, "outputs": [], "source": [ - "from langchain_core.output_parsers import StrOutputParser\n", "from langchain_core.prompts import ChatPromptTemplate\n", "\n", "map_prompt = ChatPromptTemplate.from_messages(\n", " [(\"system\", \"Write a concise summary of the following:\\\\n\\\\n{context}\")]\n", - ")\n", - "\n", - "map_chain = map_prompt | llm | StrOutputParser()" + ")" ] }, { @@ -378,19 +373,13 @@ "\n", "This will work with your [LangSmith API key](https://docs.smith.langchain.com/).\n", "\n", - "For example, see the map prompt [here](https://smith.langchain.com/hub/rlm/map-prompt)." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "ce48b805-d98b-4e0f-8b9e-3b3e72cad3d3", - "metadata": {}, - "outputs": [], - "source": [ + "For example, see the map prompt [here](https://smith.langchain.com/hub/rlm/map-prompt).\n", + "\n", + "```python\n", "from langchain import hub\n", "\n", - "map_prompt = hub.pull(\"rlm/map-prompt\")" + "map_prompt = hub.pull(\"rlm/map-prompt\")\n", + "```" ] }, { @@ -400,12 +389,12 @@ "source": [ "### Reduce\n", "\n", - "We also define a chain that takes the document mapping results and reduces them into a single output." + "We also define a prompt that takes the document mapping results and reduces them into a single output." ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "id": "6a718890-99ab-439a-8f79-b9ae9c58ad24", "metadata": {}, "outputs": [], @@ -418,9 +407,7 @@ "of the main themes.\n", "\"\"\"\n", "\n", - "reduce_prompt = ChatPromptTemplate([(\"human\", reduce_template)])\n", - "\n", - "reduce_chain = reduce_prompt | llm | StrOutputParser()" + "reduce_prompt = ChatPromptTemplate([(\"human\", reduce_template)])" ] }, { @@ -439,7 +426,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "id": "7821efb9-e1de-4234-84d2-75dfe13b5a6c", "metadata": {}, "outputs": [ @@ -478,7 +465,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "id": "10ced55c-9e3e-404f-abe9-83ac29ffaa5a", "metadata": {}, "outputs": [], @@ -524,8 +511,9 @@ "\n", "# Here we generate a summary, given a document\n", "async def generate_summary(state: SummaryState):\n", - " response = await map_chain.ainvoke(state[\"content\"])\n", - " return {\"summaries\": [response]}\n", + " prompt = map_prompt.invoke(state[\"content\"])\n", + " response = await llm.ainvoke(prompt)\n", + " return {\"summaries\": [response.content]}\n", "\n", "\n", "# Here we define the logic to map out over the documents\n", @@ -545,6 +533,12 @@ " }\n", "\n", "\n", + "async def _reduce(input: dict) -> str:\n", + " prompt = reduce_prompt.invoke(input)\n", + " response = await llm.ainvoke(prompt)\n", + " return response.content\n", + "\n", + "\n", "# Add node to collapse summaries\n", "async def collapse_summaries(state: OverallState):\n", " doc_lists = split_list_of_docs(\n", @@ -552,7 +546,7 @@ " )\n", " results = []\n", " for doc_list in doc_lists:\n", - " results.append(await acollapse_docs(doc_list, reduce_chain.ainvoke))\n", + " results.append(await acollapse_docs(doc_list, _reduce))\n", "\n", " return {\"collapsed_summaries\": results}\n", "\n", @@ -571,7 +565,7 @@ "\n", "# Here we will generate the final summary\n", "async def generate_final_summary(state: OverallState):\n", - " response = await reduce_chain.ainvoke(state[\"collapsed_summaries\"])\n", + " response = await _reduce(state[\"collapsed_summaries\"])\n", " return {\"final_summary\": response}\n", "\n", "\n", @@ -748,7 +742,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.4" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb b/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb index f031e1dbb70d2..4e53e5506b8d4 100644 --- a/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb +++ b/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb @@ -426,7 +426,7 @@ "\n", "## Usage with a pre-built langgraph agent\n", "\n", - "This example shows usage of an Agent Executor with a pre-built agent constructed using the [create_tool_calling_agent](https://api.python.langchain.com/en/latest/agents/langchain.agents.tool_calling_agent.base.create_tool_calling_agent.html) function.\n", + "This example shows usage of an Agent Executor with a pre-built agent constructed using the [create_tool_calling_agent](https://python.langchain.com/api_reference/langchain/agents/langchain.agents.tool_calling_agent.base.create_tool_calling_agent.html) function.\n", "\n", "If you are using one of the [old LangChain pre-built agents](https://python.langchain.com/v0.1/docs/modules/agents/agent_types/), you should be able\n", "to replace that code with the new [langgraph pre-built agent](https://langchain-ai.github.io/langgraph/how-tos/create-react-agent/) which leverages\n", @@ -673,7 +673,7 @@ "\n", "\n", "If you need to implement more efficient logic and want to use `RunnableWithMessageHistory` for now the way to achieve this\n", - "is to subclass from [BaseChatMessageHistory](https://api.python.langchain.com/en/latest/chat_history/langchain_core.chat_history.BaseChatMessageHistory.html) and\n", + "is to subclass from [BaseChatMessageHistory](https://python.langchain.com/api_reference/core/chat_history/langchain_core.chat_history.BaseChatMessageHistory.html) and\n", "define appropriate logic for `add_messages` (that doesn't simply append the history, but instead re-writes it).\n", "\n", "Unless you have a good reason to implement this solution, you should instead use LangGraph." diff --git a/docs/package.json b/docs/package.json index b82fda1c4c0b3..b02d589e268c2 100644 --- a/docs/package.json +++ b/docs/package.json @@ -35,6 +35,7 @@ "json-loader": "^0.5.7", "prism-react-renderer": "^2.1.0", "process": "^0.11.10", + "raw-loader": "^4.0.2", "react": "^18", "react-dom": "^18", "typescript": "^5.2.2", diff --git a/docs/scripts/prepare_notebooks_for_ci.py b/docs/scripts/prepare_notebooks_for_ci.py index d7ecb32c12eb4..b96e262946293 100644 --- a/docs/scripts/prepare_notebooks_for_ci.py +++ b/docs/scripts/prepare_notebooks_for_ci.py @@ -25,8 +25,6 @@ "docs/docs/how_to/example_selectors_langsmith.ipynb", # TODO: add langchain-benchmarks; fix cassette issue "docs/docs/how_to/extraction_long_text.ipynb", # Non-determinism due to batch "docs/docs/how_to/graph_constructing.ipynb", # Requires local neo4j - "docs/docs/how_to/graph_mapping.ipynb", # Requires local neo4j - "docs/docs/how_to/graph_prompting.ipynb", # Requires local neo4j "docs/docs/how_to/graph_semantic.ipynb", # Requires local neo4j "docs/docs/how_to/hybrid.ipynb", # Requires AstraDB instance "docs/docs/how_to/indexing.ipynb", # Requires local Elasticsearch @@ -39,8 +37,6 @@ "docs/docs/how_to/tools_human.ipynb", # Requires human input() "docs/docs/how_to/tools_prompting.ipynb", # Local LLMs "docs/docs/tutorials/graph.ipynb", # Requires local graph db running - "docs/docs/tutorials/local_rag.ipynb", # Local LLMs - "docs/docs/tutorials/query_analysis.ipynb", # Requires youtube_transcript_api "docs/docs/tutorials/summarization.ipynb", # TODO: source of non-determinism somewhere, fix or add to no cassettes ] diff --git a/docs/src/theme/ChatModelTabs.js b/docs/src/theme/ChatModelTabs.js index 162723942aab4..f9efa57e97ceb 100644 --- a/docs/src/theme/ChatModelTabs.js +++ b/docs/src/theme/ChatModelTabs.js @@ -15,6 +15,7 @@ import CodeBlock from "@theme-original/CodeBlock"; * @property {string} [googleParams] - Parameters for Google chat model. Defaults to `model="gemini-pro"` * @property {string} [togetherParams] - Parameters for Together chat model. Defaults to `model="mistralai/Mixtral-8x7B-Instruct-v0.1"` * @property {string} [nvidiaParams] - Parameters for Nvidia NIM model. Defaults to `model="meta/llama3-70b-instruct"` + * @property {string} [databricksParams] - Parameters for Databricks model. Defaults to `endpoint="databricks-meta-llama-3-1-70b-instruct"` * @property {string} [awsBedrockParams] - Parameters for AWS Bedrock chat model. * @property {boolean} [hideOpenai] - Whether or not to hide OpenAI chat model. * @property {boolean} [hideAnthropic] - Whether or not to hide Anthropic chat model. @@ -27,6 +28,7 @@ import CodeBlock from "@theme-original/CodeBlock"; * @property {boolean} [hideAzure] - Whether or not to hide Microsoft Azure OpenAI chat model. * @property {boolean} [hideNvidia] - Whether or not to hide NVIDIA NIM model. * @property {boolean} [hideAWS] - Whether or not to hide AWS models. + * @property {boolean} [hideDatabricks] - Whether or not to hide Databricks models. * @property {string} [customVarName] - Custom variable name for the model. Defaults to `model`. */ @@ -46,6 +48,7 @@ export default function ChatModelTabs(props) { azureParams, nvidiaParams, awsBedrockParams, + databricksParams, hideOpenai, hideAnthropic, hideCohere, @@ -57,6 +60,7 @@ export default function ChatModelTabs(props) { hideAzure, hideNvidia, hideAWS, + hideDatabricks, customVarName, } = props; @@ -79,6 +83,7 @@ export default function ChatModelTabs(props) { `\n azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],\n azure_deployment=os.environ["AZURE_OPENAI_DEPLOYMENT_NAME"],\n openai_api_version=os.environ["AZURE_OPENAI_API_VERSION"],\n`; const nvidiaParamsOrDefault = nvidiaParams ?? `model="meta/llama3-70b-instruct"` const awsBedrockParamsOrDefault = awsBedrockParams ?? `model="anthropic.claude-3-5-sonnet-20240620-v1:0",\n beta_use_converse_api=True`; + const databricksParamsOrDefault = databricksParams ?? `endpoint="databricks-meta-llama-3-1-70b-instruct"` const llmVarName = customVarName ?? "model"; @@ -182,6 +187,15 @@ export default function ChatModelTabs(props) { default: false, shouldHide: hideTogether, }, + { + value: "Databricks", + label: "Databricks", + text: `from databricks_langchain import ChatDatabricks\n\nos.environ["DATABRICKS_HOST"] = "https://example.staging.cloud.databricks.com/serving-endpoints"\n\n${llmVarName} = ChatDatabricks(${databricksParamsOrDefault})`, + apiKeyName: "DATABRICKS_TOKEN", + packageName: "databricks-langchain", + default: false, + shouldHide: hideDatabricks, + }, ]; return ( diff --git a/docs/src/theme/EmbeddingTabs.js b/docs/src/theme/EmbeddingTabs.js index 7e1012baec109..f29da74f135fb 100644 --- a/docs/src/theme/EmbeddingTabs.js +++ b/docs/src/theme/EmbeddingTabs.js @@ -36,7 +36,7 @@ export default function EmbeddingTabs(props) { `\n azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],\n azure_deployment=os.environ["AZURE_OPENAI_DEPLOYMENT_NAME"],\n openai_api_version=os.environ["AZURE_OPENAI_API_VERSION"],\n`; const googleParamsOrDefault = googleParams ?? `model="text-embedding-004"`; const awsParamsOrDefault = awsParams ?? `model_id="amazon.titan-embed-text-v2:0"`; - const huggingFaceParamsOrDefault = huggingFaceParams ?? `model="sentence-transformers/all-mpnet-base-v2"`; + const huggingFaceParamsOrDefault = huggingFaceParams ?? `model_name="sentence-transformers/all-mpnet-base-v2"`; const ollamaParamsOrDefault = ollamaParams ?? `model="llama3"`; const cohereParamsOrDefault = cohereParams ?? `model="embed-english-v3.0"`; const mistralParamsOrDefault = mistralParams ?? `model="mistral-embed"`; diff --git a/docs/src/theme/VectorStoreTabs.js b/docs/src/theme/VectorStoreTabs.js index 52c20fba5158d..da246630d7574 100644 --- a/docs/src/theme/VectorStoreTabs.js +++ b/docs/src/theme/VectorStoreTabs.js @@ -12,7 +12,7 @@ export default function VectorStoreTabs(props) { { value: "In-memory", label: "In-memory", - text: `from langchain_core.vector_stores import InMemoryVectorStore\n\n${vectorStoreVarName} = InMemoryVectorStore(embeddings)`, + text: `from langchain_core.vectorstores import InMemoryVectorStore\n\n${vectorStoreVarName} = InMemoryVectorStore(embeddings)`, packageName: "langchain-core", default: true, }, diff --git a/docs/static/img/langgraph_text2cypher.webp b/docs/static/img/langgraph_text2cypher.webp new file mode 100644 index 0000000000000..a5afd292cebae Binary files /dev/null and b/docs/static/img/langgraph_text2cypher.webp differ diff --git a/docs/vercel.json b/docs/vercel.json index ad2f021cacb53..f91844dda1265 100644 --- a/docs/vercel.json +++ b/docs/vercel.json @@ -36,11 +36,11 @@ }, { "source": "/docs/expression_language(/?)", - "destination": "/docs/concepts/#langchain-expression-language-lcel" + "destination": "/docs/concepts/lcel" }, { "source": "/docs/expression_language/interface(/?)", - "destination": "/docs/concepts/#runnable-interface" + "destination": "/docs/concepts/runnables" }, { "source": "/docs/versions/overview(/?)", @@ -50,6 +50,30 @@ "source": "/docs/how_to/tool_calls_multi_modal(/?)", "destination": "/docs/how_to/multimodal_inputs/" }, + { + "source": "/docs/tutorials/pdf_qa", + "destination": "/docs/tutorials/retrievers/" + }, + { + "source": "/docs/tutorials/query_analysis", + "destination": "/docs/tutorials/rag#query-analysis" + }, + { + "source": "/docs/tutorials/local_rag", + "destination": "/docs/tutorials/rag" + }, + { + "source": "/docs/how_to/graph_mapping(/?)", + "destination": "/docs/tutorials/graph#query-validation" + }, + { + "source": "/docs/how_to/graph_prompting(/?)", + "destination": "/docs/tutorials/graph#few-shot-prompting" + }, + { + "source": "/docs/tutorials/data_generation", + "destination": "https://python.langchain.com/v0.2/docs/tutorials/data_generation/" + }, { "source": "/docs/langsmith(/?)", "destination": "https://docs.smith.langchain.com/" diff --git a/docs/yarn.lock b/docs/yarn.lock index 94436d8e05823..aad5a86bb52cd 100644 --- a/docs/yarn.lock +++ b/docs/yarn.lock @@ -9043,6 +9043,14 @@ raw-body@2.5.2: iconv-lite "0.4.24" unpipe "1.0.0" +raw-loader@^4.0.2: + version "4.0.2" + resolved "https://registry.yarnpkg.com/raw-loader/-/raw-loader-4.0.2.tgz#1aac6b7d1ad1501e66efdac1522c73e59a584eb6" + integrity sha512-ZnScIV3ag9A4wPX/ZayxL/jZH+euYb6FcUinPcgiQW0+UBtEv0O6Q3lGd3cqJ+GHH+rksEv3Pj99oxJ3u3VIKA== + dependencies: + loader-utils "^2.0.0" + schema-utils "^3.0.0" + rc@1.2.8: version "1.2.8" resolved "https://registry.yarnpkg.com/rc/-/rc-1.2.8.tgz#cd924bf5200a075b83c188cd6b9e211b7fc0d3ed" diff --git a/libs/cli/.gitignore b/libs/cli/.gitignore index 68bc17f9ff210..413adb3d0f4fc 100644 --- a/libs/cli/.gitignore +++ b/libs/cli/.gitignore @@ -158,3 +158,5 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ + +.integration_test diff --git a/libs/cli/Makefile b/libs/cli/Makefile index 445235c22c841..d93de61d8cc90 100644 --- a/libs/cli/Makefile +++ b/libs/cli/Makefile @@ -1,8 +1,48 @@ -lint lint_diff: - poetry run poe lint -test: - poetry run poe test +###################### +# LINTING AND FORMATTING +###################### -format: - poetry run poe format +# Define a variable for Python and notebook files. +PYTHON_FILES=. +MYPY_CACHE=.mypy_cache +lint format: PYTHON_FILES=. +lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/cli --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$') +lint_package: PYTHON_FILES=langchain_cli +lint_tests: PYTHON_FILES=tests +lint_tests: MYPY_CACHE=.mypy_cache_test + +lint lint_diff lint_package lint_tests: + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff + [ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE) + +format format_diff: + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES) + +test tests: _test _e2e_test + +PYTHON = .venv/bin/python + +_test: + poetry run pytest tests + +# custom integration testing for cli integration flow +# currently ignores vectorstores test because lacks implementation +_e2e_test: + rm -rf .integration_test + mkdir .integration_test + cd .integration_test && \ + python3 -m venv .venv && \ + $(PYTHON) -m pip install --upgrade poetry && \ + $(PYTHON) -m pip install -e .. && \ + $(PYTHON) -m langchain_cli.cli integration new --name parrot-link --name-class ParrotLink && \ + $(PYTHON) -m langchain_cli.cli integration new --name parrot-link --name-class ParrotLinkB --src=integration_template/chat_models.py --dst=langchain-parrot-link/langchain_parrot_link/chat_models_b.py && \ + $(PYTHON) -m langchain_cli.cli integration create-doc --name parrot-link --name-class ParrotLinkB --component-type ChatModel --destination-dir langchain-parrot-link/docs && \ + cd langchain-parrot-link && \ + poetry install --with lint,typing,test && \ + poetry run pip install -e ../../../standard-tests && \ + make format lint tests && \ + poetry install --with test_integration && \ + make integration_test diff --git a/libs/cli/langchain_cli/dev_scripts.py b/libs/cli/langchain_cli/dev_scripts.py index cccd9689e4482..ebb9331a9c61e 100644 --- a/libs/cli/langchain_cli/dev_scripts.py +++ b/libs/cli/langchain_cli/dev_scripts.py @@ -1,3 +1,4 @@ +# type: ignore """ Development Scripts for template packages """ diff --git a/libs/cli/langchain_cli/integration_template/Makefile b/libs/cli/langchain_cli/integration_template/Makefile index b30039ace1fe0..4c4bbf237d9dc 100644 --- a/libs/cli/langchain_cli/integration_template/Makefile +++ b/libs/cli/langchain_cli/integration_template/Makefile @@ -33,13 +33,13 @@ lint_tests: PYTHON_FILES=tests lint_tests: MYPY_CACHE=.mypy_cache_test lint lint_diff lint_package lint_tests: - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES) [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff [ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE) format format_diff: [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I --fix $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES) spell_check: poetry run codespell --toml pyproject.toml diff --git a/libs/cli/langchain_cli/integration_template/docs/text_embedding.ipynb b/libs/cli/langchain_cli/integration_template/docs/text_embedding.ipynb index 5babaae5fd212..79ff38ba76398 100644 --- a/libs/cli/langchain_cli/integration_template/docs/text_embedding.ipynb +++ b/libs/cli/langchain_cli/integration_template/docs/text_embedding.ipynb @@ -127,7 +127,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ] diff --git a/libs/cli/langchain_cli/integration_template/docs/vectorstores.ipynb b/libs/cli/langchain_cli/integration_template/docs/vectorstores.ipynb index c90550b48d66c..2ae2da87291bc 100644 --- a/libs/cli/langchain_cli/integration_template/docs/vectorstores.ipynb +++ b/libs/cli/langchain_cli/integration_template/docs/vectorstores.ipynb @@ -292,7 +292,7 @@ "\n", "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", "\n", - "- [Tutorials: working with external knowledge](https://python.langchain.com/docs/tutorials/#working-with-external-knowledge)\n", + "- [Tutorials](/docs/tutorials/)\n", "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/#retrieval)" ] diff --git a/libs/cli/langchain_cli/integration_template/integration_template/__init__.py b/libs/cli/langchain_cli/integration_template/integration_template/__init__.py index 60d8dac5d007b..44bec467eaa90 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/__init__.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/__init__.py @@ -1,8 +1,11 @@ from importlib import metadata from __module_name__.chat_models import Chat__ModuleName__ +from __module_name__.document_loaders import __ModuleName__Loader from __module_name__.embeddings import __ModuleName__Embeddings -from __module_name__.llms import __ModuleName__LLM +from __module_name__.retrievers import __ModuleName__Retriever +from __module_name__.toolkits import __ModuleName__Toolkit +from __module_name__.tools import __ModuleName__Tool from __module_name__.vectorstores import __ModuleName__VectorStore try: @@ -14,8 +17,11 @@ __all__ = [ "Chat__ModuleName__", - "__ModuleName__LLM", "__ModuleName__VectorStore", "__ModuleName__Embeddings", + "__ModuleName__Loader", + "__ModuleName__Retriever", + "__ModuleName__Toolkit", + "__ModuleName__Tool", "__version__", ] diff --git a/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py b/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py index d299fb2ff26d1..917feb2df0ba2 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py @@ -1,13 +1,19 @@ """__ModuleName__ chat models.""" -from typing import Any, List, Optional +from typing import Any, Dict, Iterator, List, Optional from langchain_core.callbacks import ( CallbackManagerForLLMRun, ) -from langchain_core.language_models.chat_models import BaseChatModel -from langchain_core.messages import BaseMessage -from langchain_core.outputs import ChatResult +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import ( + AIMessage, + AIMessageChunk, + BaseMessage, +) +from langchain_core.messages.ai import UsageMetadata +from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult +from pydantic import Field class Chat__ModuleName__(BaseChatModel): @@ -15,6 +21,8 @@ class Chat__ModuleName__(BaseChatModel): # https://github.com/langchain-ai/langchain/blob/7ff05357bac6eaedf5058a2af88f23a1817d40fe/libs/partners/openai/langchain_openai/chat_models/base.py#L1120 """__ModuleName__ chat model integration. + The default implementation echoes the first `parrot_buffer_length` characters of the input. + # TODO: Replace with relevant packages, env vars. Setup: Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. @@ -258,7 +266,36 @@ class Joke(BaseModel): """ # noqa: E501 - # TODO: This method must be implemented to generate chat responses. + model_name: str = Field(alias="model") + """The name of the model""" + parrot_buffer_length: int + """The number of characters from the last message of the prompt to be echoed.""" + temperature: Optional[float] = None + max_tokens: Optional[int] = None + timeout: Optional[int] = None + stop: Optional[List[str]] = None + max_retries: int = 2 + + @property + def _llm_type(self) -> str: + """Return type of chat model.""" + return "chat-__package_name_short__" + + @property + def _identifying_params(self) -> Dict[str, Any]: + """Return a dictionary of identifying parameters. + + This information is used by the LangChain callback system, which + is used for tracing purposes make it possible to monitor LLMs. + """ + return { + # The model name allows users to specify custom token counting + # rules in LLM monitoring applications (e.g., in LangSmith users + # can provide per token pricing for their model and monitor + # costs for the given LLM.) + "model_name": self.model_name, + } + def _generate( self, messages: List[BaseMessage], @@ -266,16 +303,101 @@ def _generate( run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> ChatResult: - raise NotImplementedError() + """Override the _generate method to implement the chat model logic. + + This can be a call to an API, a call to a local model, or any other + implementation that generates a response to the input prompt. + + Args: + messages: the prompt composed of a list of messages. + stop: a list of strings on which the model should stop generating. + If generation stops due to a stop token, the stop token itself + SHOULD BE INCLUDED as part of the output. This is not enforced + across models right now, but it's a good practice to follow since + it makes it much easier to parse the output of the model + downstream and understand why generation stopped. + run_manager: A run manager with callbacks for the LLM. + """ + # Replace this with actual logic to generate a response from a list + # of messages. + last_message = messages[-1] + tokens = last_message.content[: self.parrot_buffer_length] + ct_input_tokens = sum(len(message.content) for message in messages) + ct_output_tokens = len(tokens) + message = AIMessage( + content=tokens, + additional_kwargs={}, # Used to add additional payload to the message + response_metadata={ # Use for response metadata + "time_in_seconds": 3, + }, + usage_metadata={ + "input_tokens": ct_input_tokens, + "output_tokens": ct_output_tokens, + "total_tokens": ct_input_tokens + ct_output_tokens, + }, + ) + ## + + generation = ChatGeneration(message=message) + return ChatResult(generations=[generation]) + + def _stream( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[CallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> Iterator[ChatGenerationChunk]: + """Stream the output of the model. + + This method should be implemented if the model can generate output + in a streaming fashion. If the model does not support streaming, + do not implement it. In that case streaming requests will be automatically + handled by the _generate method. + + Args: + messages: the prompt composed of a list of messages. + stop: a list of strings on which the model should stop generating. + If generation stops due to a stop token, the stop token itself + SHOULD BE INCLUDED as part of the output. This is not enforced + across models right now, but it's a good practice to follow since + it makes it much easier to parse the output of the model + downstream and understand why generation stopped. + run_manager: A run manager with callbacks for the LLM. + """ + last_message = messages[-1] + tokens = str(last_message.content[: self.parrot_buffer_length]) + ct_input_tokens = sum(len(message.content) for message in messages) + + for token in tokens: + usage_metadata = UsageMetadata( + { + "input_tokens": ct_input_tokens, + "output_tokens": 1, + "total_tokens": ct_input_tokens + 1, + } + ) + ct_input_tokens = 0 + chunk = ChatGenerationChunk( + message=AIMessageChunk(content=token, usage_metadata=usage_metadata) + ) - # TODO: Implement if Chat__ModuleName__ supports streaming. Otherwise delete method. - # def _stream( - # self, - # messages: List[BaseMessage], - # stop: Optional[List[str]] = None, - # run_manager: Optional[CallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> Iterator[ChatGenerationChunk]: + if run_manager: + # This is optional in newer versions of LangChain + # The on_llm_new_token will be called automatically + run_manager.on_llm_new_token(token, chunk=chunk) + + yield chunk + + # Let's add some other information (e.g., response metadata) + chunk = ChatGenerationChunk( + message=AIMessageChunk(content="", response_metadata={"time_in_sec": 3}) + ) + if run_manager: + # This is optional in newer versions of LangChain + # The on_llm_new_token will be called automatically + run_manager.on_llm_new_token(token, chunk=chunk) + yield chunk # TODO: Implement if Chat__ModuleName__ supports async streaming. Otherwise delete. # async def _astream( @@ -294,8 +416,3 @@ def _generate( # run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, # **kwargs: Any, # ) -> ChatResult: - - @property - def _llm_type(self) -> str: - """Return type of chat model.""" - return "chat-__package_name_short__" diff --git a/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py b/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py index 174c567da8df1..5df2bbfbd402c 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py @@ -8,7 +8,8 @@ class __ModuleName__Embeddings(Embeddings): # TODO: Replace with relevant packages, env vars. Setup: - Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. + Install ``__package_name__`` and set environment variable + ``__MODULE_NAME___API_KEY``. .. code-block:: bash @@ -70,21 +71,26 @@ class __ModuleName__Embeddings(Embeddings): """ + def __init__(self, model: str): + self.model = model + def embed_documents(self, texts: List[str]) -> List[List[float]]: """Embed search docs.""" - raise NotImplementedError + return [[0.5, 0.6, 0.7] for _ in texts] def embed_query(self, text: str) -> List[float]: """Embed query text.""" - raise NotImplementedError - - # only keep aembed_documents and aembed_query if they're implemented! - # delete them otherwise to use the base class' default - # implementation, which calls the sync version in an executor - async def aembed_documents(self, texts: List[str]) -> List[List[float]]: - """Asynchronous Embed search docs.""" - raise NotImplementedError - - async def aembed_query(self, text: str) -> List[float]: - """Asynchronous Embed query text.""" - raise NotImplementedError + return self.embed_documents([text])[0] + + # optional: add custom async implementations here + # you can also delete these, and the base class will + # use the default implementation, which calls the sync + # version in an async executor: + + # async def aembed_documents(self, texts: List[str]) -> List[List[float]]: + # """Asynchronous Embed search docs.""" + # ... + + # async def aembed_query(self, text: str) -> List[float]: + # """Asynchronous Embed query text.""" + # ... diff --git a/libs/cli/langchain_cli/integration_template/integration_template/llms.py b/libs/cli/langchain_cli/integration_template/integration_template/llms.py deleted file mode 100644 index 2dbe4ac918362..0000000000000 --- a/libs/cli/langchain_cli/integration_template/integration_template/llms.py +++ /dev/null @@ -1,155 +0,0 @@ -"""__ModuleName__ large language models.""" - -from typing import ( - Any, - List, - Optional, -) - -from langchain_core.callbacks import ( - CallbackManagerForLLMRun, -) -from langchain_core.language_models import BaseLLM -from langchain_core.outputs import LLMResult - - -class __ModuleName__LLM(BaseLLM): - """__ModuleName__ completion model integration. - - # TODO: Replace with relevant packages, env vars. - Setup: - Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. - - .. code-block:: bash - - pip install -U __package_name__ - export __MODULE_NAME___API_KEY="your-api-key" - - # TODO: Populate with relevant params. - Key init args — completion params: - model: str - Name of __ModuleName__ model to use. - temperature: float - Sampling temperature. - max_tokens: Optional[int] - Max number of tokens to generate. - - # TODO: Populate with relevant params. - Key init args — client params: - timeout: Optional[float] - Timeout for requests. - max_retries: int - Max number of retries. - api_key: Optional[str] - __ModuleName__ API key. If not passed in will be read from env var __MODULE_NAME___API_KEY. - - See full list of supported init args and their descriptions in the params section. - - # TODO: Replace with relevant init params. - Instantiate: - .. code-block:: python - - from __module_name__ import __ModuleName__LLM - - llm = __ModuleName__LLM( - model="...", - temperature=0, - max_tokens=None, - timeout=None, - max_retries=2, - # api_key="...", - # other params... - ) - - Invoke: - .. code-block:: python - - input_text = "The meaning of life is " - llm.invoke(input_text) - - .. code-block:: python - - # TODO: Example output. - - # TODO: Delete if token-level streaming isn't supported. - Stream: - .. code-block:: python - - for chunk in llm.stream(input_text): - print(chunk) - - .. code-block:: python - - # TODO: Example output. - - .. code-block:: python - - ''.join(llm.stream(input_text)) - - .. code-block:: python - - # TODO: Example output. - - # TODO: Delete if native async isn't supported. - Async: - .. code-block:: python - - await llm.ainvoke(input_text) - - # stream: - # async for chunk in (await llm.astream(input_text)) - - # batch: - # await llm.abatch([input_text]) - - .. code-block:: python - - # TODO: Example output. - """ - - # TODO: This method must be implemented to generate text completions. - def _generate( - self, - prompts: List[str], - stop: Optional[List[str]] = None, - run_manager: Optional[CallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> LLMResult: - raise NotImplementedError - - # TODO: Implement if __ModuleName__LLM supports async generation. Otherwise - # delete method. - # async def _agenerate( - # self, - # prompts: List[str], - # stop: Optional[List[str]] = None, - # run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> LLMResult: - # raise NotImplementedError - - # TODO: Implement if __ModuleName__LLM supports streaming. Otherwise delete method. - # def _stream( - # self, - # prompt: str, - # stop: Optional[List[str]] = None, - # run_manager: Optional[CallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> Iterator[GenerationChunk]: - # raise NotImplementedError - - # TODO: Implement if __ModuleName__LLM supports async streaming. Otherwise delete - # method. - # async def _astream( - # self, - # prompt: str, - # stop: Optional[List[str]] = None, - # run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> AsyncIterator[GenerationChunk]: - # raise NotImplementedError - - @property - def _llm_type(self) -> str: - """Return type of LLM.""" - return "__package_name_short__-llm" diff --git a/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py b/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py index c48661873c8eb..242103f3a4056 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py @@ -1,7 +1,8 @@ """__ModuleName__ retrievers.""" -from typing import List +from typing import Any, List +from langchain_core.callbacks import CallbackManagerForRetrieverRun from langchain_core.documents import Document from langchain_core.retrievers import BaseRetriever @@ -13,7 +14,8 @@ class __ModuleName__Retriever(BaseRetriever): # TODO: Replace with relevant packages, env vars, etc. Setup: - Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. + Install ``__package_name__`` and set environment variable + ``__MODULE_NAME___API_KEY``. .. code-block:: bash @@ -82,8 +84,24 @@ def format_docs(docs): # TODO: Example output. - """ # noqa: E501 + """ + + k: int = 3 # TODO: This method must be implemented to retrieve documents. - def _get_relevant_documents(self, query: str) -> List[Document]: - raise NotImplementedError() + def _get_relevant_documents( + self, query: str, *, run_manager: CallbackManagerForRetrieverRun, **kwargs: Any + ) -> List[Document]: + k = kwargs.get("k", self.k) + return [ + Document(page_content=f"Result {i} for query: {query}") for i in range(k) + ] + + # optional: add custom async implementations here + # async def _aget_relevant_documents( + # self, + # query: str, + # *, + # run_manager: AsyncCallbackManagerForRetrieverRun, + # **kwargs: Any, + # ) -> List[Document]: ... diff --git a/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py b/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py index 5a80398891167..b3eda23bd2343 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py @@ -2,10 +2,10 @@ from typing import List -from langchain_core.tools import BaseTool, BaseToolKit +from langchain_core.tools import BaseTool, BaseToolkit -class __ModuleName__Toolkit(BaseToolKit): +class __ModuleName__Toolkit(BaseToolkit): # TODO: Replace all TODOs in docstring. See example docstring: # https://github.com/langchain-ai/langchain/blob/c123cb2b304f52ab65db4714eeec46af69a861ec/libs/community/langchain_community/agent_toolkits/sql/toolkit.py#L19 """__ModuleName__ toolkit. diff --git a/libs/cli/langchain_cli/integration_template/integration_template/tools.py b/libs/cli/langchain_cli/integration_template/integration_template/tools.py index 57deb006f062a..1904c9865b76c 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/tools.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/tools.py @@ -6,10 +6,10 @@ CallbackManagerForToolRun, ) from langchain_core.tools import BaseTool -from pydantic import BaseModel +from pydantic import BaseModel, Field -class __ModuleName__Input(BaseModel): +class __ModuleName__ToolInput(BaseModel): """Input schema for __ModuleName__ tool. This docstring is **not** part of what is sent to the model when performing tool @@ -18,12 +18,11 @@ class __ModuleName__Input(BaseModel): """ # TODO: Add input args and descriptions. - # a: int = Field(..., description="first number") - # b: int = Field(0, description="second number") - ... + a: int = Field(..., description="first number to add") + b: int = Field(..., description="second number to add") -class __ModuleName__Tool(BaseTool): +class __ModuleName__Tool(BaseTool): # type: ignore[override] """__ModuleName__ tool. Setup: @@ -69,24 +68,26 @@ class __ModuleName__Tool(BaseTool): """The name that is passed to the model when performing tool calling.""" description: str = "TODO: Tool description." """The description that is passed to the model when performing tool calling.""" - args_schema: Type[BaseModel] = __ModuleName__Input + args_schema: Type[BaseModel] = __ModuleName__ToolInput """The schema that is passed to the model when performing tool calling.""" # TODO: Add any other init params for the tool. # param1: Optional[str] # """param1 determines foobar""" - # TODO: Replaced *args with real tool arguments. + # TODO: Replaced (a, b) with real tool arguments. def _run( - self, *args, run_manager: Optional[CallbackManagerForToolRun] = None + self, a: int, b: int, *, run_manager: Optional[CallbackManagerForToolRun] = None ) -> str: - raise NotImplementedError + return str(a + b + 80) # TODO: Implement if tool has native async functionality, otherwise delete. # async def _arun( # self, - # *args, + # a: int, + # b: int, + # *, # run_manager: Optional[AsyncCallbackManagerForToolRun] = None, # ) -> str: # ... diff --git a/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py b/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py index 4236e8c037e73..cef35ecaf44c5 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py @@ -2,25 +2,23 @@ from __future__ import annotations -import asyncio -from functools import partial +import uuid from typing import ( - TYPE_CHECKING, Any, Callable, - Iterable, + Iterator, List, Optional, + Sequence, Tuple, Type, TypeVar, ) +from langchain_core.documents import Document from langchain_core.embeddings import Embeddings from langchain_core.vectorstores import VectorStore - -if TYPE_CHECKING: - from langchain_core.documents import Document +from langchain_core.vectorstores.utils import _cosine_similarity as cosine_similarity VST = TypeVar("VST", bound=VectorStore) @@ -160,146 +158,282 @@ class __ModuleName__VectorStore(VectorStore): """ # noqa: E501 - def add_texts( - self, - texts: Iterable[str], - metadatas: Optional[List[dict]] = None, - **kwargs: Any, - ) -> List[str]: - raise NotImplementedError + def __init__(self, embedding: Embeddings) -> None: + """Initialize with the given embedding function. - async def aadd_texts( - self, - texts: Iterable[str], + Args: + embedding: embedding function to use. + """ + self._database: dict[str, dict[str, Any]] = {} + self.embedding = embedding + + @classmethod + def from_texts( + cls: Type[__ModuleName__VectorStore], + texts: List[str], + embedding: Embeddings, metadatas: Optional[List[dict]] = None, **kwargs: Any, - ) -> List[str]: - return await asyncio.get_running_loop().run_in_executor( - None, partial(self.add_texts, **kwargs), texts, metadatas + ) -> __ModuleName__VectorStore: + store = cls( + embedding=embedding, ) - - def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> Optional[bool]: - raise NotImplementedError - - async def adelete( - self, ids: Optional[List[str]] = None, **kwargs: Any - ) -> Optional[bool]: - raise NotImplementedError - - def similarity_search( - self, query: str, k: int = 4, **kwargs: Any - ) -> List[Document]: - raise NotImplementedError - - async def asimilarity_search( - self, query: str, k: int = 4, **kwargs: Any - ) -> List[Document]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial(self.similarity_search, query, k=k, **kwargs) - return await asyncio.get_event_loop().run_in_executor(None, func) - - def similarity_search_with_score( - self, *args: Any, **kwargs: Any - ) -> List[Tuple[Document, float]]: - raise NotImplementedError - - async def asimilarity_search_with_score( - self, *args: Any, **kwargs: Any - ) -> List[Tuple[Document, float]]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial(self.similarity_search_with_score, *args, **kwargs) - return await asyncio.get_event_loop().run_in_executor(None, func) - - def similarity_search_by_vector( - self, embedding: List[float], k: int = 4, **kwargs: Any - ) -> List[Document]: - raise NotImplementedError - - async def asimilarity_search_by_vector( - self, embedding: List[float], k: int = 4, **kwargs: Any - ) -> List[Document]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial(self.similarity_search_by_vector, embedding, k=k, **kwargs) - return await asyncio.get_event_loop().run_in_executor(None, func) - - def max_marginal_relevance_search( + store.add_texts(texts=texts, metadatas=metadatas, **kwargs) + return store + + # optional: add custom async implementations + # @classmethod + # async def afrom_texts( + # cls: Type[VST], + # texts: List[str], + # embedding: Embeddings, + # metadatas: Optional[List[dict]] = None, + # **kwargs: Any, + # ) -> VST: + # return await asyncio.get_running_loop().run_in_executor( + # None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas + # ) + + @property + def embeddings(self) -> Embeddings: + return self.embedding + + def add_documents( self, - query: str, - k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, + documents: List[Document], + ids: Optional[List[str]] = None, **kwargs: Any, - ) -> List[Document]: - raise NotImplementedError + ) -> List[str]: + """Add documents to the store.""" + texts = [doc.page_content for doc in documents] + vectors = self.embedding.embed_documents(texts) + + if ids and len(ids) != len(texts): + msg = ( + f"ids must be the same length as texts. " + f"Got {len(ids)} ids and {len(texts)} texts." + ) + raise ValueError(msg) - async def amax_marginal_relevance_search( - self, - query: str, - k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, - **kwargs: Any, - ) -> List[Document]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial( - self.max_marginal_relevance_search, - query, - k=k, - fetch_k=fetch_k, - lambda_mult=lambda_mult, - **kwargs, + id_iterator: Iterator[Optional[str]] = ( + iter(ids) if ids else iter(doc.id for doc in documents) ) - return await asyncio.get_event_loop().run_in_executor(None, func) - def max_marginal_relevance_search_by_vector( + ids_ = [] + + for doc, vector in zip(documents, vectors): + doc_id = next(id_iterator) + doc_id_ = doc_id if doc_id else str(uuid.uuid4()) + ids_.append(doc_id_) + self._database[doc_id_] = { + "id": doc_id_, + "vector": vector, + "text": doc.page_content, + "metadata": doc.metadata, + } + + return ids_ + + # optional: add custom async implementations + # async def aadd_documents( + # self, + # documents: List[Document], + # ids: Optional[List[str]] = None, + # **kwargs: Any, + # ) -> List[str]: + # raise NotImplementedError + + def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> None: + if ids: + for _id in ids: + self._database.pop(_id, None) + + # optional: add custom async implementations + # async def adelete( + # self, ids: Optional[List[str]] = None, **kwargs: Any + # ) -> None: + # raise NotImplementedError + + def get_by_ids(self, ids: Sequence[str], /) -> list[Document]: + """Get documents by their ids. + + Args: + ids: The ids of the documents to get. + + Returns: + A list of Document objects. + """ + documents = [] + + for doc_id in ids: + doc = self._database.get(doc_id) + if doc: + documents.append( + Document( + id=doc["id"], + page_content=doc["text"], + metadata=doc["metadata"], + ) + ) + return documents + + # optional: add custom async implementations + # async def aget_by_ids(self, ids: Sequence[str], /) -> list[Document]: + # raise NotImplementedError + + # NOTE: the below helper method implements similarity search for in-memory + # storage. It is optional and not a part of the vector store interface. + def _similarity_search_with_score_by_vector( self, embedding: List[float], k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, + filter: Optional[Callable[[Document], bool]] = None, **kwargs: Any, - ) -> List[Document]: - raise NotImplementedError + ) -> List[tuple[Document, float, List[float]]]: + # get all docs with fixed order in list + docs = list(self._database.values()) + + if filter is not None: + docs = [ + doc + for doc in docs + if filter(Document(page_content=doc["text"], metadata=doc["metadata"])) + ] + + if not docs: + return [] + + similarity = cosine_similarity([embedding], [doc["vector"] for doc in docs])[0] + + # get the indices ordered by similarity score + top_k_idx = similarity.argsort()[::-1][:k] + + return [ + ( + # Document + Document( + id=doc_dict["id"], + page_content=doc_dict["text"], + metadata=doc_dict["metadata"], + ), + # Score + float(similarity[idx].item()), + # Embedding vector + doc_dict["vector"], + ) + for idx in top_k_idx + # Assign using walrus operator to avoid multiple lookups + if (doc_dict := docs[idx]) + ] - async def amax_marginal_relevance_search_by_vector( - self, - embedding: List[float], - k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, - **kwargs: Any, + def similarity_search( + self, query: str, k: int = 4, **kwargs: Any ) -> List[Document]: - raise NotImplementedError - - @classmethod - def from_texts( - cls: Type[VST], - texts: List[str], - embedding: Embeddings, - metadatas: Optional[List[dict]] = None, - **kwargs: Any, - ) -> VST: - raise NotImplementedError - - @classmethod - async def afrom_texts( - cls: Type[VST], - texts: List[str], - embedding: Embeddings, - metadatas: Optional[List[dict]] = None, - **kwargs: Any, - ) -> VST: - return await asyncio.get_running_loop().run_in_executor( - None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas - ) + embedding = self.embedding.embed_query(query) + return [ + doc + for doc, _, _ in self._similarity_search_with_score_by_vector( + embedding=embedding, k=k, **kwargs + ) + ] + + # optional: add custom async implementations + # async def asimilarity_search( + # self, query: str, k: int = 4, **kwargs: Any + # ) -> List[Document]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial(self.similarity_search, query, k=k, **kwargs) + # return await asyncio.get_event_loop().run_in_executor(None, func) - def _select_relevance_score_fn(self) -> Callable[[float], float]: - raise NotImplementedError + def similarity_search_with_score( + self, query: str, k: int = 4, **kwargs: Any + ) -> List[Tuple[Document, float]]: + embedding = self.embedding.embed_query(query) + return [ + (doc, similarity) + for doc, similarity, _ in self._similarity_search_with_score_by_vector( + embedding=embedding, k=k, **kwargs + ) + ] + + # optional: add custom async implementations + # async def asimilarity_search_with_score( + # self, *args: Any, **kwargs: Any + # ) -> List[Tuple[Document, float]]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial(self.similarity_search_with_score, *args, **kwargs) + # return await asyncio.get_event_loop().run_in_executor(None, func) + + ### ADDITIONAL OPTIONAL SEARCH METHODS BELOW ### + + # def similarity_search_by_vector( + # self, embedding: List[float], k: int = 4, **kwargs: Any + # ) -> List[Document]: + # raise NotImplementedError + + # optional: add custom async implementations + # async def asimilarity_search_by_vector( + # self, embedding: List[float], k: int = 4, **kwargs: Any + # ) -> List[Document]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial(self.similarity_search_by_vector, embedding, k=k, **kwargs) + # return await asyncio.get_event_loop().run_in_executor(None, func) + + # def max_marginal_relevance_search( + # self, + # query: str, + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, + # **kwargs: Any, + # ) -> List[Document]: + # raise NotImplementedError + + # optional: add custom async implementations + # async def amax_marginal_relevance_search( + # self, + # query: str, + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, + # **kwargs: Any, + # ) -> List[Document]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial( + # self.max_marginal_relevance_search, + # query, + # k=k, + # fetch_k=fetch_k, + # lambda_mult=lambda_mult, + # **kwargs, + # ) + # return await asyncio.get_event_loop().run_in_executor(None, func) + + # def max_marginal_relevance_search_by_vector( + # self, + # embedding: List[float], + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, + # **kwargs: Any, + # ) -> List[Document]: + # raise NotImplementedError + + # optional: add custom async implementations + # async def amax_marginal_relevance_search_by_vector( + # self, + # embedding: List[float], + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, + # **kwargs: Any, + # ) -> List[Document]: + # raise NotImplementedError diff --git a/libs/cli/langchain_cli/integration_template/pyproject.toml b/libs/cli/langchain_cli/integration_template/pyproject.toml index efdcb9efeadcd..fa3c596b069bb 100644 --- a/libs/cli/langchain_cli/integration_template/pyproject.toml +++ b/libs/cli/langchain_cli/integration_template/pyproject.toml @@ -1,5 +1,5 @@ [build-system] -requires = [ "poetry-core>=1.0.0",] +requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" [tool.poetry] @@ -23,14 +23,16 @@ python = ">=3.9,<4.0" langchain-core = "^0.3.15" [tool.ruff.lint] -select = [ "E", "F", "I", "T201",] +select = ["E", "F", "I", "T201"] [tool.coverage.run] -omit = [ "tests/*",] +omit = ["tests/*"] [tool.pytest.ini_options] addopts = "--strict-markers --strict-config --durations=5" -markers = [ "compile: mark placeholder test used to compile integration tests without running them",] +markers = [ + "compile: mark placeholder test used to compile integration tests without running them", +] asyncio_mode = "auto" [tool.poetry.group.test] @@ -48,11 +50,14 @@ optional = true [tool.poetry.group.dev] optional = true +[tool.poetry.group.dev.dependencies] + [tool.poetry.group.test.dependencies] pytest = "^7.4.3" pytest-asyncio = "^0.23.2" pytest-socket = "^0.7.0" pytest-watcher = "^0.3.4" +langchain-tests = "^0.3.5" [tool.poetry.group.codespell.dependencies] codespell = "^2.2.6" @@ -64,15 +69,3 @@ ruff = "^0.5" [tool.poetry.group.typing.dependencies] mypy = "^1.10" - -[tool.poetry.group.test.dependencies.langchain-core] -path = "../../core" -develop = true - -[tool.poetry.group.dev.dependencies.langchain-core] -path = "../../core" -develop = true - -[tool.poetry.group.typing.dependencies.langchain-core] -path = "../../core" -develop = true diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py index 26b63bd706b5f..c84dafa973abf 100644 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py @@ -1,64 +1,21 @@ """Test Chat__ModuleName__ chat model.""" -from __module_name__.chat_models import Chat__ModuleName__ - - -def test_stream() -> None: - """Test streaming tokens from OpenAI.""" - llm = Chat__ModuleName__() - - for token in llm.stream("I'm Pickle Rick"): - assert isinstance(token.content, str) - - -async def test_astream() -> None: - """Test streaming tokens from OpenAI.""" - llm = Chat__ModuleName__() - - async for token in llm.astream("I'm Pickle Rick"): - assert isinstance(token.content, str) - - -async def test_abatch() -> None: - """Test streaming tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token.content, str) - +from typing import Type -async def test_abatch_tags() -> None: - """Test batch tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = await llm.abatch( - ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]} - ) - for token in result: - assert isinstance(token.content, str) - - -def test_batch() -> None: - """Test batch tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token.content, str) - - -async def test_ainvoke() -> None: - """Test invoke tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) - assert isinstance(result.content, str) - - -def test_invoke() -> None: - """Test invoke tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) - assert isinstance(result.content, str) +from __module_name__.chat_models import Chat__ModuleName__ +from langchain_tests.integration_tests import ChatModelIntegrationTests + + +class TestChatParrotLinkIntegration(ChatModelIntegrationTests): + @property + def chat_model_class(self) -> Type[Chat__ModuleName__]: + return Chat__ModuleName__ + + @property + def chat_model_params(self) -> dict: + # These should be parameters used to initialize your integration for testing + return { + "model": "bird-brain-001", + "temperature": 0, + "parrot_buffer_length": 50, + } diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py index 51937d157d255..f7bd526d04bd5 100644 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py @@ -1,20 +1,16 @@ """Test __ModuleName__ embeddings.""" -from __module_name__.embeddings import __ModuleName__Embeddings +from typing import Type +from __module_name__.embeddings import __ModuleName__Embeddings +from langchain_tests.integration_tests import EmbeddingsIntegrationTests -def test___module_name___embedding_documents() -> None: - """Test cohere embeddings.""" - documents = ["foo bar"] - embedding = __ModuleName__Embeddings() - output = embedding.embed_documents(documents) - assert len(output) == 1 - assert len(output[0]) > 0 +class TestParrotLinkEmbeddingsIntegration(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[__ModuleName__Embeddings]: + return __ModuleName__Embeddings -def test___module_name___embedding_query() -> None: - """Test cohere embeddings.""" - document = "foo bar" - embedding = __ModuleName__Embeddings() - output = embedding.embed_query(document) - assert len(output) > 0 + @property + def embedding_model_params(self) -> dict: + return {"model": "nest-embed-001"} diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_llms.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_llms.py deleted file mode 100644 index 9fd6e0a628e94..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_llms.py +++ /dev/null @@ -1,64 +0,0 @@ -"""Test __ModuleName__LLM llm.""" - -from __module_name__.llms import __ModuleName__LLM - - -def test_stream() -> None: - """Test streaming tokens from OpenAI.""" - llm = __ModuleName__LLM() - - for token in llm.stream("I'm Pickle Rick"): - assert isinstance(token, str) - - -async def test_astream() -> None: - """Test streaming tokens from OpenAI.""" - llm = __ModuleName__LLM() - - async for token in llm.astream("I'm Pickle Rick"): - assert isinstance(token, str) - - -async def test_abatch() -> None: - """Test streaming tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token, str) - - -async def test_abatch_tags() -> None: - """Test batch tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = await llm.abatch( - ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]} - ) - for token in result: - assert isinstance(token, str) - - -def test_batch() -> None: - """Test batch tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token, str) - - -async def test_ainvoke() -> None: - """Test invoke tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) - assert isinstance(result, str) - - -def test_invoke() -> None: - """Test invoke tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) - assert isinstance(result, str) diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py new file mode 100644 index 0000000000000..f4164ebd1b0f4 --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py @@ -0,0 +1,24 @@ +from typing import Type + +from __module_name__.retrievers import __ModuleName__Retriever +from langchain_tests.integration_tests import ( + RetrieversIntegrationTests, +) + + +class Test__ModuleName__Retriever(RetrieversIntegrationTests): + @property + def retriever_constructor(self) -> Type[__ModuleName__Retriever]: + """Get an empty vectorstore for unit tests.""" + return __ModuleName__Retriever + + @property + def retriever_constructor_params(self) -> dict: + return {"k": 2} + + @property + def retriever_query_example(self) -> str: + """ + Returns a str representing the "query" of an example retriever call. + """ + return "example query" diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py new file mode 100644 index 0000000000000..529bd7fe7ea16 --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py @@ -0,0 +1,27 @@ +from typing import Type + +from __module_name__.tools import __ModuleName__Tool +from langchain_tests.integration_tests import ToolsIntegrationTests + + +class TestParrotMultiplyToolIntegration(ToolsIntegrationTests): + @property + def tool_constructor(self) -> Type[__ModuleName__Tool]: + return __ModuleName__Tool + + @property + def tool_constructor_params(self) -> dict: + # if your tool constructor instead required initialization arguments like + # `def __init__(self, some_arg: int):`, you would return those here + # as a dictionary, e.g.: `return {'some_arg': 42}` + return {} + + @property + def tool_invoke_params_example(self) -> dict: + """ + Returns a dictionary representing the "args" of an example tool call. + + This should NOT be a ToolCall dict - i.e. it should not + have {"name", "id", "args"} keys. + """ + return {"a": 2, "b": 3} diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py new file mode 100644 index 0000000000000..d7c71f662d951 --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py @@ -0,0 +1,20 @@ +from typing import Generator + +import pytest +from __module_name__.vectorstores import __ModuleName__VectorStore +from langchain_core.vectorstores import VectorStore +from langchain_tests.integration_tests import VectorStoreIntegrationTests + + +class Test__ModuleName__VectorStore(VectorStoreIntegrationTests): + @pytest.fixture() + def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore + """Get an empty vectorstore for unit tests.""" + store = __ModuleName__VectorStore(self.get_embeddings()) + # note: store should be EMPTY at this point + # if you need to delete data, you may do so here + try: + yield store + finally: + # cleanup operations, or deleting data + pass diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py index 70cc82c75dcbf..c83081a44790b 100644 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py +++ b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py @@ -1,8 +1,21 @@ """Test chat model integration.""" +from typing import Type + from __module_name__.chat_models import Chat__ModuleName__ +from langchain_tests.unit_tests import ChatModelUnitTests + +class TestChat__ModuleName__Unit(ChatModelUnitTests): + @property + def chat_model_class(self) -> Type[Chat__ModuleName__]: + return Chat__ModuleName__ -def test_initialization() -> None: - """Test chat model initialization.""" - Chat__ModuleName__() + @property + def chat_model_params(self) -> dict: + # These should be parameters used to initialize your integration for testing + return { + "model": "bird-brain-001", + "temperature": 0, + "parrot_buffer_length": 50, + } diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py index ab4f45a9b7304..5fdf8feb0837d 100644 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py +++ b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py @@ -1,8 +1,16 @@ """Test embedding model integration.""" +from typing import Type + from __module_name__.embeddings import __ModuleName__Embeddings +from langchain_tests.unit_tests import EmbeddingsUnitTests + +class TestParrotLinkEmbeddingsUnit(EmbeddingsUnitTests): + @property + def embeddings_class(self) -> Type[__ModuleName__Embeddings]: + return __ModuleName__Embeddings -def test_initialization() -> None: - """Test embedding model initialization.""" - __ModuleName__Embeddings() + @property + def embedding_model_params(self) -> dict: + return {"model": "nest-embed-001"} diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_imports.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_imports.py deleted file mode 100644 index 1dfa338914189..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_imports.py +++ /dev/null @@ -1,12 +0,0 @@ -from __module_name__ import __all__ - -EXPECTED_ALL = [ - "__ModuleName__LLM", - "Chat__ModuleName__", - "__ModuleName__VectorStore", - "__ModuleName__Embeddings", -] - - -def test_all_imports() -> None: - assert sorted(EXPECTED_ALL) == sorted(__all__) diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_llms.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_llms.py deleted file mode 100644 index 7d53dad10acdd..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_llms.py +++ /dev/null @@ -1,8 +0,0 @@ -"""Test __ModuleName__ Chat API wrapper.""" - -from __module_name__ import __ModuleName__LLM - - -def test_initialization() -> None: - """Test integration initialization.""" - __ModuleName__LLM() diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py new file mode 100644 index 0000000000000..23231276d4125 --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py @@ -0,0 +1,27 @@ +from typing import Type + +from __module_name__.tools import __ModuleName__Tool +from langchain_tests.unit_tests import ToolsUnitTests + + +class TestParrotMultiplyToolUnit(ToolsUnitTests): + @property + def tool_constructor(self) -> Type[__ModuleName__Tool]: + return __ModuleName__Tool + + @property + def tool_constructor_params(self) -> dict: + # if your tool constructor instead required initialization arguments like + # `def __init__(self, some_arg: int):`, you would return those here + # as a dictionary, e.g.: `return {'some_arg': 42}` + return {} + + @property + def tool_invoke_params_example(self) -> dict: + """ + Returns a dictionary representing the "args" of an example tool call. + + This should NOT be a ToolCall dict - i.e. it should not + have {"name", "id", "args"} keys. + """ + return {"a": 2, "b": 3} diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_vectorstores.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_vectorstores.py deleted file mode 100644 index 6c044a9a66fb4..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_vectorstores.py +++ /dev/null @@ -1,6 +0,0 @@ -from __module_name__.vectorstores import __ModuleName__VectorStore - - -def test_initialization() -> None: - """Test integration vectorstore initialization.""" - __ModuleName__VectorStore() diff --git a/libs/cli/langchain_cli/namespaces/app.py b/libs/cli/langchain_cli/namespaces/app.py index 9bf007652b448..d1fcb46b848fb 100644 --- a/libs/cli/langchain_cli/namespaces/app.py +++ b/libs/cli/langchain_cli/namespaces/app.py @@ -5,6 +5,7 @@ import shutil import subprocess import sys +import warnings from pathlib import Path from typing import Dict, List, Optional, Tuple @@ -163,6 +164,12 @@ def add( langchain app add git+ssh://git@github.com/efriis/simple-pirate.git """ + if not branch and not repo: + warnings.warn( + "Adding templates from the default branch and repo is deprecated." + " At a minimum, you will have to add `--branch v0.2` for this to work" + ) + parsed_deps = parse_dependencies(dependencies, repo, branch, api_path) project_root = get_package_root(project_dir) diff --git a/libs/cli/langchain_cli/namespaces/integration.py b/libs/cli/langchain_cli/namespaces/integration.py index e78af97c25d97..fbacf1274f177 100644 --- a/libs/cli/langchain_cli/namespaces/integration.py +++ b/libs/cli/langchain_cli/namespaces/integration.py @@ -6,7 +6,7 @@ import shutil import subprocess from pathlib import Path -from typing import Optional +from typing import Dict, Optional, cast import typer from typing_extensions import Annotated, TypedDict @@ -15,19 +15,17 @@ integration_cli = typer.Typer(no_args_is_help=True, add_completion=False) -Replacements = TypedDict( - "Replacements", - { - "__package_name__": str, - "__module_name__": str, - "__ModuleName__": str, - "__MODULE_NAME__": str, - "__package_name_short__": str, - }, -) +class Replacements(TypedDict): + __package_name__: str + __module_name__: str + __ModuleName__: str + __MODULE_NAME__: str + __package_name_short__: str + __package_name_short_snake__: str -def _process_name(name: str, *, community: bool = False): + +def _process_name(name: str, *, community: bool = False) -> Replacements: preprocessed = name.replace("_", "-").lower() if preprocessed.startswith("langchain-"): @@ -42,7 +40,7 @@ def _process_name(name: str, *, community: bool = False): raise ValueError("Name should not end with `-`.") if preprocessed.find("--") != -1: raise ValueError("Name should not contain consecutive hyphens.") - replacements = { + replacements: Replacements = { "__package_name__": f"langchain-{preprocessed}", "__module_name__": "langchain_" + preprocessed.replace("-", "_"), "__ModuleName__": preprocessed.title().replace("-", ""), @@ -52,7 +50,7 @@ def _process_name(name: str, *, community: bool = False): } if community: replacements["__module_name__"] = preprocessed.replace("-", "_") - return Replacements(replacements) + return replacements @integration_cli.command() @@ -71,19 +69,25 @@ def new( " This is used to name classes like `MyIntegrationVectorStore`" ), ] = None, + src: Annotated[ + Optional[list[str]], + typer.Option( + help="The name of the single template file to copy." + " e.g. `--src integration_template/chat_models.py " + "--dst my_integration/chat_models.py`. Can be used multiple times.", + ), + ] = None, + dst: Annotated[ + Optional[list[str]], + typer.Option( + help="The relative path to the integration package to place the new file in" + ". e.g. `my-integration/my_integration.py`", + ), + ] = None, ): """ Creates a new integration package. - - Should be run from libs/partners """ - # confirm that we are in the right directory - if not Path.cwd().name == "partners" or not Path.cwd().parent.name == "libs": - typer.echo( - "This command should be run from the `libs/partners` directory in the " - "langchain-ai/langchain monorepo. Continuing is NOT recommended." - ) - typer.confirm("Are you sure you want to continue?", abort=True) try: replacements = _process_name(name) @@ -104,27 +108,66 @@ def new( "Name of integration in PascalCase", default=replacements["__ModuleName__"] ) - destination_dir = Path.cwd() / replacements["__package_name_short__"] - if destination_dir.exists(): - typer.echo(f"Folder {destination_dir} exists.") - raise typer.Exit(code=1) - - # copy over template from ../integration_template project_template_dir = Path(__file__).parents[1] / "integration_template" - shutil.copytree(project_template_dir, destination_dir, dirs_exist_ok=False) + destination_dir = Path.cwd() / replacements["__package_name__"] + if not src and not dst: + if destination_dir.exists(): + typer.echo(f"Folder {destination_dir} exists.") + raise typer.Exit(code=1) - # folder movement - package_dir = destination_dir / replacements["__module_name__"] - shutil.move(destination_dir / "integration_template", package_dir) + # copy over template from ../integration_template + shutil.copytree(project_template_dir, destination_dir, dirs_exist_ok=False) - # replacements in files - replace_glob(destination_dir, "**/*", replacements) + # folder movement + package_dir = destination_dir / replacements["__module_name__"] + shutil.move(destination_dir / "integration_template", package_dir) - # poetry install - subprocess.run( - ["poetry", "install", "--with", "lint,test,typing,test_integration"], - cwd=destination_dir, - ) + # replacements in files + replace_glob(destination_dir, "**/*", cast(Dict[str, str], replacements)) + + # poetry install + subprocess.run( + ["poetry", "install", "--with", "lint,test,typing,test_integration"], + cwd=destination_dir, + ) + else: + # confirm src and dst are the same length + if not src: + typer.echo("Cannot provide --dst without --src.") + raise typer.Exit(code=1) + src_paths = [project_template_dir / p for p in src] + if dst and len(src) != len(dst): + typer.echo("Number of --src and --dst arguments must match.") + raise typer.Exit(code=1) + if not dst: + # assume we're in a package dir, copy to equivalent path + dst_paths = [destination_dir / p for p in src] + else: + dst_paths = [Path.cwd() / p for p in dst] + dst_paths = [ + p / f"{replacements['__package_name_short_snake__']}.ipynb" + if not p.suffix + else p + for p in dst_paths + ] + + # confirm no duplicate dst_paths + if len(dst_paths) != len(set(dst_paths)): + typer.echo( + "Duplicate destination paths provided or computed - please " + "specify them explicitly with --dst." + ) + raise typer.Exit(code=1) + + # confirm no files exist at dst_paths + for dst_path in dst_paths: + if dst_path.exists(): + typer.echo(f"File {dst_path} exists.") + raise typer.Exit(code=1) + + for src_path, dst_path in zip(src_paths, dst_paths): + shutil.copy(src_path, dst_path) + replace_file(dst_path, cast(Dict[str, str], replacements)) TEMPLATE_MAP: dict[str, str] = { @@ -187,43 +230,15 @@ def create_doc( """ Creates a new integration doc. """ - try: - replacements = _process_name(name, community=component_type == "Tool") - except ValueError as e: - typer.echo(e) - raise typer.Exit(code=1) - - if name_class: - if not re.match(r"^[A-Z][a-zA-Z0-9]*$", name_class): - typer.echo( - "Name should only contain letters (a-z, A-Z), numbers, and underscores" - ", and start with a capital letter." - ) - raise typer.Exit(code=1) - replacements["__ModuleName__"] = name_class - else: - replacements["__ModuleName__"] = typer.prompt( - ( - "The PascalCase name of the integration (e.g. `OpenAI`, `VertexAI`). " - "Do not include a 'Chat', 'VectorStore', etc. prefix/suffix." - ), - default=replacements["__ModuleName__"], - ) - destination_path = ( - Path.cwd() - / destination_dir - / (replacements["__package_name_short_snake__"] + ".ipynb") - ) - - # copy over template from ../integration_template - template_dir = Path(__file__).parents[1] / "integration_template" / "docs" - if component_type in TEMPLATE_MAP: - docs_template = template_dir / TEMPLATE_MAP[component_type] - else: - raise ValueError( + if component_type not in TEMPLATE_MAP: + typer.echo( f"Unrecognized {component_type=}. Expected one of {_component_types_str}." ) - shutil.copy(docs_template, destination_path) + raise typer.Exit(code=1) - # replacements in file - replace_file(destination_path, replacements) + new( + name=name, + name_class=name_class, + src=[f"docs/{TEMPLATE_MAP[component_type]}"], + dst=[destination_dir], + ) diff --git a/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py b/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py index 57fd457f19e4b..51b8b79bd3b6e 100644 --- a/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py +++ b/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py @@ -17,7 +17,7 @@ class ImportExtractor(ast.NodeVisitor): def __init__(self, *, from_package: Optional[str] = None) -> None: """Extract all imports from the given code, optionally filtering by package.""" - self.imports = [] + self.imports: list = [] self.package = from_package def visit_ImportFrom(self, node): @@ -68,7 +68,7 @@ def find_subclasses_in_module(module, classes_: List[Type]) -> List[str]: return subclasses -def _get_all_classnames_from_file(file: str, pkg: str) -> List[Tuple[str, str]]: +def _get_all_classnames_from_file(file: Path, pkg: str) -> List[Tuple[str, str]]: """Extract all class names from a file.""" with open(file, encoding="utf-8") as f: code = f.read() @@ -145,7 +145,7 @@ def find_imports_from_package( return extractor.imports -def _get_current_module(path: str, pkg_root: str) -> str: +def _get_current_module(path: Path, pkg_root: str) -> str: """Convert a path to a module name.""" path_as_pathlib = pathlib.Path(os.path.abspath(path)) relative_path = path_as_pathlib.relative_to(pkg_root).with_suffix("") diff --git a/libs/cli/langchain_cli/namespaces/migrate/main.py b/libs/cli/langchain_cli/namespaces/migrate/main.py index 483fa9f6ea6c7..0956f9d4f683c 100644 --- a/libs/cli/langchain_cli/namespaces/migrate/main.py +++ b/libs/cli/langchain_cli/namespaces/migrate/main.py @@ -4,7 +4,7 @@ import rich import typer -from gritql import run +from gritql import run # type: ignore from typer import Option diff --git a/libs/cli/langchain_cli/utils/find_replace.py b/libs/cli/langchain_cli/utils/find_replace.py index cfea68d3dfaa7..12cb9bb4a13fe 100644 --- a/libs/cli/langchain_cli/utils/find_replace.py +++ b/libs/cli/langchain_cli/utils/find_replace.py @@ -13,7 +13,7 @@ def find_and_replace(source: str, replacements: Dict[str, str]) -> str: return rtn -def replace_file(source: Path, replacements: Dict[str, str]) -> None: +def replace_file(source: Path, replacements: dict[str, str]) -> None: try: content = source.read_text() except UnicodeDecodeError: @@ -24,7 +24,7 @@ def replace_file(source: Path, replacements: Dict[str, str]) -> None: source.write_text(new_content) -def replace_glob(parent: Path, glob: str, replacements: Dict[str, str]) -> None: +def replace_glob(parent: Path, glob: str, replacements: dict[str, str]) -> None: for file in parent.glob(glob): if not file.is_file(): continue diff --git a/libs/cli/poetry.lock b/libs/cli/poetry.lock index d2026cb3a1119..72cd18d604530 100644 --- a/libs/cli/poetry.lock +++ b/libs/cli/poetry.lock @@ -1,5 +1,128 @@ # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +[[package]] +name = "aiohappyeyeballs" +version = "2.4.4" +description = "Happy Eyeballs for asyncio" +optional = false +python-versions = ">=3.8" +files = [ + {file = "aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8"}, + {file = "aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745"}, +] + +[[package]] +name = "aiohttp" +version = "3.11.10" +description = "Async http client/server framework (asyncio)" +optional = false +python-versions = ">=3.9" +files = [ + {file = "aiohttp-3.11.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:cbad88a61fa743c5d283ad501b01c153820734118b65aee2bd7dbb735475ce0d"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:80886dac673ceaef499de2f393fc80bb4481a129e6cb29e624a12e3296cc088f"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:61b9bae80ed1f338c42f57c16918853dc51775fb5cb61da70d590de14d8b5fb4"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9e2e576caec5c6a6b93f41626c9c02fc87cd91538b81a3670b2e04452a63def6"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:02c13415b5732fb6ee7ff64583a5e6ed1c57aa68f17d2bda79c04888dfdc2769"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4cfce37f31f20800a6a6620ce2cdd6737b82e42e06e6e9bd1b36f546feb3c44f"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3bbbfff4c679c64e6e23cb213f57cc2c9165c9a65d63717108a644eb5a7398df"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:49c7dbbc1a559ae14fc48387a115b7d4bbc84b4a2c3b9299c31696953c2a5219"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:68386d78743e6570f054fe7949d6cb37ef2b672b4d3405ce91fafa996f7d9b4d"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9ef405356ba989fb57f84cac66f7b0260772836191ccefbb987f414bcd2979d9"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5d6958671b296febe7f5f859bea581a21c1d05430d1bbdcf2b393599b1cdce77"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:99b7920e7165be5a9e9a3a7f1b680f06f68ff0d0328ff4079e5163990d046767"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:0dc49f42422163efb7e6f1df2636fe3db72713f6cd94688e339dbe33fe06d61d"}, + {file = "aiohttp-3.11.10-cp310-cp310-win32.whl", hash = "sha256:40d1c7a7f750b5648642586ba7206999650208dbe5afbcc5284bcec6579c9b91"}, + {file = "aiohttp-3.11.10-cp310-cp310-win_amd64.whl", hash = "sha256:68ff6f48b51bd78ea92b31079817aff539f6c8fc80b6b8d6ca347d7c02384e33"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:77c4aa15a89847b9891abf97f3d4048f3c2d667e00f8a623c89ad2dccee6771b"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:909af95a72cedbefe5596f0bdf3055740f96c1a4baa0dd11fd74ca4de0b4e3f1"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:386fbe79863eb564e9f3615b959e28b222259da0c48fd1be5929ac838bc65683"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3de34936eb1a647aa919655ff8d38b618e9f6b7f250cc19a57a4bf7fd2062b6d"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0c9527819b29cd2b9f52033e7fb9ff08073df49b4799c89cb5754624ecd98299"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:65a96e3e03300b41f261bbfd40dfdbf1c301e87eab7cd61c054b1f2e7c89b9e8"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98f5635f7b74bcd4f6f72fcd85bea2154b323a9f05226a80bc7398d0c90763b0"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:03b6002e20938fc6ee0918c81d9e776bebccc84690e2b03ed132331cca065ee5"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6362cc6c23c08d18ddbf0e8c4d5159b5df74fea1a5278ff4f2c79aed3f4e9f46"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:3691ed7726fef54e928fe26344d930c0c8575bc968c3e239c2e1a04bd8cf7838"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31d5093d3acd02b31c649d3a69bb072d539d4c7659b87caa4f6d2bcf57c2fa2b"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:8b3cf2dc0f0690a33f2d2b2cb15db87a65f1c609f53c37e226f84edb08d10f52"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:fbbaea811a2bba171197b08eea288b9402faa2bab2ba0858eecdd0a4105753a3"}, + {file = "aiohttp-3.11.10-cp311-cp311-win32.whl", hash = "sha256:4b2c7ac59c5698a7a8207ba72d9e9c15b0fc484a560be0788b31312c2c5504e4"}, + {file = "aiohttp-3.11.10-cp311-cp311-win_amd64.whl", hash = "sha256:974d3a2cce5fcfa32f06b13ccc8f20c6ad9c51802bb7f829eae8a1845c4019ec"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:b78f053a7ecfc35f0451d961dacdc671f4bcbc2f58241a7c820e9d82559844cf"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ab7485222db0959a87fbe8125e233b5a6f01f4400785b36e8a7878170d8c3138"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:cf14627232dfa8730453752e9cdc210966490992234d77ff90bc8dc0dce361d5"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:076bc454a7e6fd646bc82ea7f98296be0b1219b5e3ef8a488afbdd8e81fbac50"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:482cafb7dc886bebeb6c9ba7925e03591a62ab34298ee70d3dd47ba966370d2c"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf3d1a519a324af764a46da4115bdbd566b3c73fb793ffb97f9111dbc684fc4d"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24213ba85a419103e641e55c27dc7ff03536c4873470c2478cce3311ba1eee7b"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b99acd4730ad1b196bfb03ee0803e4adac371ae8efa7e1cbc820200fc5ded109"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:14cdb5a9570be5a04eec2ace174a48ae85833c2aadc86de68f55541f66ce42ab"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:7e97d622cb083e86f18317282084bc9fbf261801b0192c34fe4b1febd9f7ae69"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:012f176945af138abc10c4a48743327a92b4ca9adc7a0e078077cdb5dbab7be0"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:44224d815853962f48fe124748227773acd9686eba6dc102578defd6fc99e8d9"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c87bf31b7fdab94ae3adbe4a48e711bfc5f89d21cf4c197e75561def39e223bc"}, + {file = "aiohttp-3.11.10-cp312-cp312-win32.whl", hash = "sha256:06a8e2ee1cbac16fe61e51e0b0c269400e781b13bcfc33f5425912391a542985"}, + {file = "aiohttp-3.11.10-cp312-cp312-win_amd64.whl", hash = "sha256:be2b516f56ea883a3e14dda17059716593526e10fb6303189aaf5503937db408"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:8cc5203b817b748adccb07f36390feb730b1bc5f56683445bfe924fc270b8816"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:5ef359ebc6949e3a34c65ce20230fae70920714367c63afd80ea0c2702902ccf"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9bca390cb247dbfaec3c664326e034ef23882c3f3bfa5fbf0b56cad0320aaca5"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:811f23b3351ca532af598405db1093f018edf81368e689d1b508c57dcc6b6a32"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ddf5f7d877615f6a1e75971bfa5ac88609af3b74796ff3e06879e8422729fd01"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6ab29b8a0beb6f8eaf1e5049252cfe74adbaafd39ba91e10f18caeb0e99ffb34"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c49a76c1038c2dd116fa443eba26bbb8e6c37e924e2513574856de3b6516be99"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7f3dc0e330575f5b134918976a645e79adf333c0a1439dcf6899a80776c9ab39"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:efb15a17a12497685304b2d976cb4939e55137df7b09fa53f1b6a023f01fcb4e"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:db1d0b28fcb7f1d35600150c3e4b490775251dea70f894bf15c678fdd84eda6a"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:15fccaf62a4889527539ecb86834084ecf6e9ea70588efde86e8bc775e0e7542"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:593c114a2221444f30749cc5e5f4012488f56bd14de2af44fe23e1e9894a9c60"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7852bbcb4d0d2f0c4d583f40c3bc750ee033265d80598d0f9cb6f372baa6b836"}, + {file = "aiohttp-3.11.10-cp313-cp313-win32.whl", hash = "sha256:65e55ca7debae8faaffee0ebb4b47a51b4075f01e9b641c31e554fd376595c6c"}, + {file = "aiohttp-3.11.10-cp313-cp313-win_amd64.whl", hash = "sha256:beb39a6d60a709ae3fb3516a1581777e7e8b76933bb88c8f4420d875bb0267c6"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:0580f2e12de2138f34debcd5d88894786453a76e98febaf3e8fe5db62d01c9bf"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a55d2ad345684e7c3dd2c20d2f9572e9e1d5446d57200ff630e6ede7612e307f"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:04814571cb72d65a6899db6099e377ed00710bf2e3eafd2985166f2918beaf59"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e44a9a3c053b90c6f09b1bb4edd880959f5328cf63052503f892c41ea786d99f"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:502a1464ccbc800b4b1995b302efaf426e8763fadf185e933c2931df7db9a199"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:613e5169f8ae77b1933e42e418a95931fb4867b2991fc311430b15901ed67079"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4cca22a61b7fe45da8fc73c3443150c3608750bbe27641fc7558ec5117b27fdf"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:86a5dfcc39309470bd7b68c591d84056d195428d5d2e0b5ccadfbaf25b026ebc"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:77ae58586930ee6b2b6f696c82cf8e78c8016ec4795c53e36718365f6959dc82"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:78153314f26d5abef3239b4a9af20c229c6f3ecb97d4c1c01b22c4f87669820c"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:98283b94cc0e11c73acaf1c9698dea80c830ca476492c0fe2622bd931f34b487"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:53bf2097e05c2accc166c142a2090e4c6fd86581bde3fd9b2d3f9e93dda66ac1"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:c5532f0441fc09c119e1dca18fbc0687e64fbeb45aa4d6a87211ceaee50a74c4"}, + {file = "aiohttp-3.11.10-cp39-cp39-win32.whl", hash = "sha256:47ad15a65fb41c570cd0ad9a9ff8012489e68176e7207ec7b82a0940dddfd8be"}, + {file = "aiohttp-3.11.10-cp39-cp39-win_amd64.whl", hash = "sha256:c6b9e6d7e41656d78e37ce754813fa44b455c3d0d0dced2a047def7dc5570b74"}, + {file = "aiohttp-3.11.10.tar.gz", hash = "sha256:b1fc6b45010a8d0ff9e88f9f2418c6fd408c99c211257334aff41597ebece42e"}, +] + +[package.dependencies] +aiohappyeyeballs = ">=2.3.0" +aiosignal = ">=1.1.2" +async-timeout = {version = ">=4.0,<6.0", markers = "python_version < \"3.11\""} +attrs = ">=17.3.0" +frozenlist = ">=1.1.1" +multidict = ">=4.5,<7.0" +propcache = ">=0.2.0" +yarl = ">=1.17.0,<2.0" + +[package.extras] +speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"] + +[[package]] +name = "aiosignal" +version = "1.3.1" +description = "aiosignal: a list of registered asynchronous callbacks" +optional = false +python-versions = ">=3.7" +files = [ + {file = "aiosignal-1.3.1-py3-none-any.whl", hash = "sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17"}, + {file = "aiosignal-1.3.1.tar.gz", hash = "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc"}, +] + +[package.dependencies] +frozenlist = ">=1.1.0" + [[package]] name = "annotated-types" version = "0.7.0" @@ -13,26 +136,56 @@ files = [ [[package]] name = "anyio" -version = "4.6.2.post1" +version = "4.7.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.9" files = [ - {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"}, - {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"}, + {file = "anyio-4.7.0-py3-none-any.whl", hash = "sha256:ea60c3723ab42ba6fff7e8ccb0488c898ec538ff4df1f1d5e642c3601d07e352"}, + {file = "anyio-4.7.0.tar.gz", hash = "sha256:2f834749c602966b7d456a7567cafcb309f96482b5081d14ac93ccd457f9dd48"}, ] [package.dependencies] exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} idna = ">=2.8" sniffio = ">=1.1" -typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} +typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] -doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"] +doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"] trio = ["trio (>=0.26.1)"] +[[package]] +name = "async-timeout" +version = "4.0.3" +description = "Timeout context manager for asyncio programs" +optional = false +python-versions = ">=3.7" +files = [ + {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"}, + {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"}, +] + +[[package]] +name = "attrs" +version = "24.2.0" +description = "Classes Without Boilerplate" +optional = false +python-versions = ">=3.7" +files = [ + {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"}, + {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"}, +] + +[package.extras] +benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"] +tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] + [[package]] name = "certifi" version = "2024.8.30" @@ -209,13 +362,13 @@ test = ["pytest (>=6)"] [[package]] name = "fastapi" -version = "0.115.5" +version = "0.115.6" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" optional = false python-versions = ">=3.8" files = [ - {file = "fastapi-0.115.5-py3-none-any.whl", hash = "sha256:596b95adbe1474da47049e802f9a65ab2ffa9c2b07e7efee70eb8a66c9f2f796"}, - {file = "fastapi-0.115.5.tar.gz", hash = "sha256:0e7a4d0dc0d01c68df21887cce0945e72d3c48b9f4f79dfe7a7d53aa08fbb289"}, + {file = "fastapi-0.115.6-py3-none-any.whl", hash = "sha256:e9240b29e36fa8f4bb7290316988e90c381e5092e0cbe84e7818cc3713bcf305"}, + {file = "fastapi-0.115.6.tar.gz", hash = "sha256:9ec46f7addc14ea472958a96aae5b5de65f39721a46aaf5705c480d9a8b76654"}, ] [package.dependencies] @@ -227,6 +380,107 @@ typing-extensions = ">=4.8.0" all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"] standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "jinja2 (>=2.11.2)", "python-multipart (>=0.0.7)", "uvicorn[standard] (>=0.12.0)"] +[[package]] +name = "frozenlist" +version = "1.5.0" +description = "A list-like structure which implements collections.abc.MutableSequence" +optional = false +python-versions = ">=3.8" +files = [ + {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5b6a66c18b5b9dd261ca98dffcb826a525334b2f29e7caa54e182255c5f6a65a"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1b3eb7b05ea246510b43a7e53ed1653e55c2121019a97e60cad7efb881a97bb"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:15538c0cbf0e4fa11d1e3a71f823524b0c46299aed6e10ebb4c2089abd8c3bec"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e79225373c317ff1e35f210dd5f1344ff31066ba8067c307ab60254cd3a78ad5"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9272fa73ca71266702c4c3e2d4a28553ea03418e591e377a03b8e3659d94fa76"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:498524025a5b8ba81695761d78c8dd7382ac0b052f34e66939c42df860b8ff17"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:92b5278ed9d50fe610185ecd23c55d8b307d75ca18e94c0e7de328089ac5dcba"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f3c8c1dacd037df16e85227bac13cca58c30da836c6f936ba1df0c05d046d8d"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f2ac49a9bedb996086057b75bf93538240538c6d9b38e57c82d51f75a73409d2"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e66cc454f97053b79c2ab09c17fbe3c825ea6b4de20baf1be28919460dd7877f"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5a3ba5f9a0dfed20337d3e966dc359784c9f96503674c2faf015f7fe8e96798c"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:6321899477db90bdeb9299ac3627a6a53c7399c8cd58d25da094007402b039ab"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:76e4753701248476e6286f2ef492af900ea67d9706a0155335a40ea21bf3b2f5"}, + {file = "frozenlist-1.5.0-cp310-cp310-win32.whl", hash = "sha256:977701c081c0241d0955c9586ffdd9ce44f7a7795df39b9151cd9a6fd0ce4cfb"}, + {file = "frozenlist-1.5.0-cp310-cp310-win_amd64.whl", hash = "sha256:189f03b53e64144f90990d29a27ec4f7997d91ed3d01b51fa39d2dbe77540fd4"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:fd74520371c3c4175142d02a976aee0b4cb4a7cc912a60586ffd8d5929979b30"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2f3f7a0fbc219fb4455264cae4d9f01ad41ae6ee8524500f381de64ffaa077d5"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f47c9c9028f55a04ac254346e92977bf0f166c483c74b4232bee19a6697e4778"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0996c66760924da6e88922756d99b47512a71cfd45215f3570bf1e0b694c206a"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a2fe128eb4edeabe11896cb6af88fca5346059f6c8d807e3b910069f39157869"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a8ea951bbb6cacd492e3948b8da8c502a3f814f5d20935aae74b5df2b19cf3d"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de537c11e4aa01d37db0d403b57bd6f0546e71a82347a97c6a9f0dcc532b3a45"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c2623347b933fcb9095841f1cc5d4ff0b278addd743e0e966cb3d460278840d"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:cee6798eaf8b1416ef6909b06f7dc04b60755206bddc599f52232606e18179d3"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:f5f9da7f5dbc00a604fe74aa02ae7c98bcede8a3b8b9666f9f86fc13993bc71a"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:90646abbc7a5d5c7c19461d2e3eeb76eb0b204919e6ece342feb6032c9325ae9"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:bdac3c7d9b705d253b2ce370fde941836a5f8b3c5c2b8fd70940a3ea3af7f4f2"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:03d33c2ddbc1816237a67f66336616416e2bbb6beb306e5f890f2eb22b959cdf"}, + {file = "frozenlist-1.5.0-cp311-cp311-win32.whl", hash = "sha256:237f6b23ee0f44066219dae14c70ae38a63f0440ce6750f868ee08775073f942"}, + {file = "frozenlist-1.5.0-cp311-cp311-win_amd64.whl", hash = "sha256:0cc974cc93d32c42e7b0f6cf242a6bd941c57c61b618e78b6c0a96cb72788c1d"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:31115ba75889723431aa9a4e77d5f398f5cf976eea3bdf61749731f62d4a4a21"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7437601c4d89d070eac8323f121fcf25f88674627505334654fd027b091db09d"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7948140d9f8ece1745be806f2bfdf390127cf1a763b925c4a805c603df5e697e"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:feeb64bc9bcc6b45c6311c9e9b99406660a9c05ca8a5b30d14a78555088b0b3a"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:683173d371daad49cffb8309779e886e59c2f369430ad28fe715f66d08d4ab1a"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7d57d8f702221405a9d9b40f9da8ac2e4a1a8b5285aac6100f3393675f0a85ee"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:30c72000fbcc35b129cb09956836c7d7abf78ab5416595e4857d1cae8d6251a6"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:000a77d6034fbad9b6bb880f7ec073027908f1b40254b5d6f26210d2dab1240e"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5d7f5a50342475962eb18b740f3beecc685a15b52c91f7d975257e13e029eca9"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:87f724d055eb4785d9be84e9ebf0f24e392ddfad00b3fe036e43f489fafc9039"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:6e9080bb2fb195a046e5177f10d9d82b8a204c0736a97a153c2466127de87784"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:9b93d7aaa36c966fa42efcaf716e6b3900438632a626fb09c049f6a2f09fc631"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:52ef692a4bc60a6dd57f507429636c2af8b6046db8b31b18dac02cbc8f507f7f"}, + {file = "frozenlist-1.5.0-cp312-cp312-win32.whl", hash = "sha256:29d94c256679247b33a3dc96cce0f93cbc69c23bf75ff715919332fdbb6a32b8"}, + {file = "frozenlist-1.5.0-cp312-cp312-win_amd64.whl", hash = "sha256:8969190d709e7c48ea386db202d708eb94bdb29207a1f269bab1196ce0dcca1f"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:7a1a048f9215c90973402e26c01d1cff8a209e1f1b53f72b95c13db61b00f953"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:dd47a5181ce5fcb463b5d9e17ecfdb02b678cca31280639255ce9d0e5aa67af0"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1431d60b36d15cda188ea222033eec8e0eab488f39a272461f2e6d9e1a8e63c2"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6482a5851f5d72767fbd0e507e80737f9c8646ae7fd303def99bfe813f76cf7f"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:44c49271a937625619e862baacbd037a7ef86dd1ee215afc298a417ff3270608"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:12f78f98c2f1c2429d42e6a485f433722b0061d5c0b0139efa64f396efb5886b"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ce3aa154c452d2467487765e3adc730a8c153af77ad84096bc19ce19a2400840"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b7dc0c4338e6b8b091e8faf0db3168a37101943e687f373dce00959583f7439"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:45e0896250900b5aa25180f9aec243e84e92ac84bd4a74d9ad4138ef3f5c97de"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:561eb1c9579d495fddb6da8959fd2a1fca2c6d060d4113f5844b433fc02f2641"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:df6e2f325bfee1f49f81aaac97d2aa757c7646534a06f8f577ce184afe2f0a9e"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:140228863501b44b809fb39ec56b5d4071f4d0aa6d216c19cbb08b8c5a7eadb9"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7707a25d6a77f5d27ea7dc7d1fc608aa0a478193823f88511ef5e6b8a48f9d03"}, + {file = "frozenlist-1.5.0-cp313-cp313-win32.whl", hash = "sha256:31a9ac2b38ab9b5a8933b693db4939764ad3f299fcaa931a3e605bc3460e693c"}, + {file = "frozenlist-1.5.0-cp313-cp313-win_amd64.whl", hash = "sha256:11aabdd62b8b9c4b84081a3c246506d1cddd2dd93ff0ad53ede5defec7886b28"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:dd94994fc91a6177bfaafd7d9fd951bc8689b0a98168aa26b5f543868548d3ca"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2d0da8bbec082bf6bf18345b180958775363588678f64998c2b7609e34719b10"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:73f2e31ea8dd7df61a359b731716018c2be196e5bb3b74ddba107f694fbd7604"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:828afae9f17e6de596825cf4228ff28fbdf6065974e5ac1410cecc22f699d2b3"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f1577515d35ed5649d52ab4319db757bb881ce3b2b796d7283e6634d99ace307"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2150cc6305a2c2ab33299453e2968611dacb970d2283a14955923062c8d00b10"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a72b7a6e3cd2725eff67cd64c8f13335ee18fc3c7befc05aed043d24c7b9ccb9"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c16d2fa63e0800723139137d667e1056bee1a1cf7965153d2d104b62855e9b99"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:17dcc32fc7bda7ce5875435003220a457bcfa34ab7924a49a1c19f55b6ee185c"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:97160e245ea33d8609cd2b8fd997c850b56db147a304a262abc2b3be021a9171"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:f1e6540b7fa044eee0bb5111ada694cf3dc15f2b0347ca125ee9ca984d5e9e6e"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:91d6c171862df0a6c61479d9724f22efb6109111017c87567cfeb7b5d1449fdf"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c1fac3e2ace2eb1052e9f7c7db480818371134410e1f5c55d65e8f3ac6d1407e"}, + {file = "frozenlist-1.5.0-cp38-cp38-win32.whl", hash = "sha256:b97f7b575ab4a8af9b7bc1d2ef7f29d3afee2226bd03ca3875c16451ad5a7723"}, + {file = "frozenlist-1.5.0-cp38-cp38-win_amd64.whl", hash = "sha256:374ca2dabdccad8e2a76d40b1d037f5bd16824933bf7bcea3e59c891fd4a0923"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:9bbcdfaf4af7ce002694a4e10a0159d5a8d20056a12b05b45cea944a4953f972"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1893f948bf6681733aaccf36c5232c231e3b5166d607c5fa77773611df6dc336"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2b5e23253bb709ef57a8e95e6ae48daa9ac5f265637529e4ce6b003a37b2621f"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f253985bb515ecd89629db13cb58d702035ecd8cfbca7d7a7e29a0e6d39af5f"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:04a5c6babd5e8fb7d3c871dc8b321166b80e41b637c31a995ed844a6139942b6"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9fe0f1c29ba24ba6ff6abf688cb0b7cf1efab6b6aa6adc55441773c252f7411"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:226d72559fa19babe2ccd920273e767c96a49b9d3d38badd7c91a0fdeda8ea08"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:15b731db116ab3aedec558573c1a5eec78822b32292fe4f2f0345b7f697745c2"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:366d8f93e3edfe5a918c874702f78faac300209a4d5bf38352b2c1bdc07a766d"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:1b96af8c582b94d381a1c1f51ffaedeb77c821c690ea5f01da3d70a487dd0a9b"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:c03eff4a41bd4e38415cbed054bbaff4a075b093e2394b6915dca34a40d1e38b"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:50cf5e7ee9b98f22bdecbabf3800ae78ddcc26e4a435515fc72d97903e8488e0"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1e76bfbc72353269c44e0bc2cfe171900fbf7f722ad74c9a7b638052afe6a00c"}, + {file = "frozenlist-1.5.0-cp39-cp39-win32.whl", hash = "sha256:666534d15ba8f0fda3f53969117383d5dc021266b3c1a42c9ec4855e4b58b9d3"}, + {file = "frozenlist-1.5.0-cp39-cp39-win_amd64.whl", hash = "sha256:5c28f4b5dbef8a0d8aad0d4de24d1e9e981728628afaf4ea0792f5d0939372f0"}, + {file = "frozenlist-1.5.0-py3-none-any.whl", hash = "sha256:d994863bba198a4a518b467bb971c56e1db3f180a25c6cf7bb1949c267f748c3"}, + {file = "frozenlist-1.5.0.tar.gz", hash = "sha256:81d5af29e61b9c8348e876d442253723928dce6433e0e76cd925cd83f1b4b817"}, +] + [[package]] name = "gitdb" version = "4.0.11" @@ -259,6 +513,92 @@ gitdb = ">=4.0.1,<5" doc = ["sphinx (==4.3.2)", "sphinx-autodoc-typehints", "sphinx-rtd-theme", "sphinxcontrib-applehelp (>=1.0.2,<=1.0.4)", "sphinxcontrib-devhelp (==1.0.2)", "sphinxcontrib-htmlhelp (>=2.0.0,<=2.0.1)", "sphinxcontrib-qthelp (==1.0.3)", "sphinxcontrib-serializinghtml (==1.1.5)"] test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit", "pytest (>=7.3.1)", "pytest-cov", "pytest-instafail", "pytest-mock", "pytest-sugar", "typing-extensions"] +[[package]] +name = "greenlet" +version = "3.1.1" +description = "Lightweight in-process concurrent programming" +optional = false +python-versions = ">=3.7" +files = [ + {file = "greenlet-3.1.1-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:0bbae94a29c9e5c7e4a2b7f0aae5c17e8e90acbfd3bf6270eeba60c39fce3563"}, + {file = "greenlet-3.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0fde093fb93f35ca72a556cf72c92ea3ebfda3d79fc35bb19fbe685853869a83"}, + {file = "greenlet-3.1.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:36b89d13c49216cadb828db8dfa6ce86bbbc476a82d3a6c397f0efae0525bdd0"}, + {file = "greenlet-3.1.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:94b6150a85e1b33b40b1464a3f9988dcc5251d6ed06842abff82e42632fac120"}, + {file = "greenlet-3.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:93147c513fac16385d1036b7e5b102c7fbbdb163d556b791f0f11eada7ba65dc"}, + {file = "greenlet-3.1.1-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:da7a9bff22ce038e19bf62c4dd1ec8391062878710ded0a845bcf47cc0200617"}, + {file = "greenlet-3.1.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:b2795058c23988728eec1f36a4e5e4ebad22f8320c85f3587b539b9ac84128d7"}, + {file = "greenlet-3.1.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ed10eac5830befbdd0c32f83e8aa6288361597550ba669b04c48f0f9a2c843c6"}, + {file = "greenlet-3.1.1-cp310-cp310-win_amd64.whl", hash = "sha256:77c386de38a60d1dfb8e55b8c1101d68c79dfdd25c7095d51fec2dd800892b80"}, + {file = "greenlet-3.1.1-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:e4d333e558953648ca09d64f13e6d8f0523fa705f51cae3f03b5983489958c70"}, + {file = "greenlet-3.1.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:09fc016b73c94e98e29af67ab7b9a879c307c6731a2c9da0db5a7d9b7edd1159"}, + {file = "greenlet-3.1.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d5e975ca70269d66d17dd995dafc06f1b06e8cb1ec1e9ed54c1d1e4a7c4cf26e"}, + {file = "greenlet-3.1.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b2813dc3de8c1ee3f924e4d4227999285fd335d1bcc0d2be6dc3f1f6a318ec1"}, + {file = "greenlet-3.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e347b3bfcf985a05e8c0b7d462ba6f15b1ee1c909e2dcad795e49e91b152c383"}, + {file = "greenlet-3.1.1-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9e8f8c9cb53cdac7ba9793c276acd90168f416b9ce36799b9b885790f8ad6c0a"}, + {file = "greenlet-3.1.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:62ee94988d6b4722ce0028644418d93a52429e977d742ca2ccbe1c4f4a792511"}, + {file = "greenlet-3.1.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:1776fd7f989fc6b8d8c8cb8da1f6b82c5814957264d1f6cf818d475ec2bf6395"}, + {file = "greenlet-3.1.1-cp311-cp311-win_amd64.whl", hash = "sha256:48ca08c771c268a768087b408658e216133aecd835c0ded47ce955381105ba39"}, + {file = "greenlet-3.1.1-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:4afe7ea89de619adc868e087b4d2359282058479d7cfb94970adf4b55284574d"}, + {file = "greenlet-3.1.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f406b22b7c9a9b4f8aa9d2ab13d6ae0ac3e85c9a809bd590ad53fed2bf70dc79"}, + {file = "greenlet-3.1.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c3a701fe5a9695b238503ce5bbe8218e03c3bcccf7e204e455e7462d770268aa"}, + {file = "greenlet-3.1.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2846930c65b47d70b9d178e89c7e1a69c95c1f68ea5aa0a58646b7a96df12441"}, + {file = "greenlet-3.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:99cfaa2110534e2cf3ba31a7abcac9d328d1d9f1b95beede58294a60348fba36"}, + {file = "greenlet-3.1.1-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1443279c19fca463fc33e65ef2a935a5b09bb90f978beab37729e1c3c6c25fe9"}, + {file = "greenlet-3.1.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:b7cede291382a78f7bb5f04a529cb18e068dd29e0fb27376074b6d0317bf4dd0"}, + {file = "greenlet-3.1.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:23f20bb60ae298d7d8656c6ec6db134bca379ecefadb0b19ce6f19d1f232a942"}, + {file = "greenlet-3.1.1-cp312-cp312-win_amd64.whl", hash = "sha256:7124e16b4c55d417577c2077be379514321916d5790fa287c9ed6f23bd2ffd01"}, + {file = "greenlet-3.1.1-cp313-cp313-macosx_11_0_universal2.whl", hash = "sha256:05175c27cb459dcfc05d026c4232f9de8913ed006d42713cb8a5137bd49375f1"}, + {file = "greenlet-3.1.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:935e943ec47c4afab8965954bf49bfa639c05d4ccf9ef6e924188f762145c0ff"}, + {file = "greenlet-3.1.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:667a9706c970cb552ede35aee17339a18e8f2a87a51fba2ed39ceeeb1004798a"}, + {file = "greenlet-3.1.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b8a678974d1f3aa55f6cc34dc480169d58f2e6d8958895d68845fa4ab566509e"}, + {file = "greenlet-3.1.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efc0f674aa41b92da8c49e0346318c6075d734994c3c4e4430b1c3f853e498e4"}, + {file = "greenlet-3.1.1-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0153404a4bb921f0ff1abeb5ce8a5131da56b953eda6e14b88dc6bbc04d2049e"}, + {file = "greenlet-3.1.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:275f72decf9932639c1c6dd1013a1bc266438eb32710016a1c742df5da6e60a1"}, + {file = "greenlet-3.1.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:c4aab7f6381f38a4b42f269057aee279ab0fc7bf2e929e3d4abfae97b682a12c"}, + {file = "greenlet-3.1.1-cp313-cp313-win_amd64.whl", hash = "sha256:b42703b1cf69f2aa1df7d1030b9d77d3e584a70755674d60e710f0af570f3761"}, + {file = "greenlet-3.1.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f1695e76146579f8c06c1509c7ce4dfe0706f49c6831a817ac04eebb2fd02011"}, + {file = "greenlet-3.1.1-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7876452af029456b3f3549b696bb36a06db7c90747740c5302f74a9e9fa14b13"}, + {file = "greenlet-3.1.1-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4ead44c85f8ab905852d3de8d86f6f8baf77109f9da589cb4fa142bd3b57b475"}, + {file = "greenlet-3.1.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8320f64b777d00dd7ccdade271eaf0cad6636343293a25074cc5566160e4de7b"}, + {file = "greenlet-3.1.1-cp313-cp313t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6510bf84a6b643dabba74d3049ead221257603a253d0a9873f55f6a59a65f822"}, + {file = "greenlet-3.1.1-cp313-cp313t-musllinux_1_1_aarch64.whl", hash = "sha256:04b013dc07c96f83134b1e99888e7a79979f1a247e2a9f59697fa14b5862ed01"}, + {file = "greenlet-3.1.1-cp313-cp313t-musllinux_1_1_x86_64.whl", hash = "sha256:411f015496fec93c1c8cd4e5238da364e1da7a124bcb293f085bf2860c32c6f6"}, + {file = "greenlet-3.1.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:47da355d8687fd65240c364c90a31569a133b7b60de111c255ef5b606f2ae291"}, + {file = "greenlet-3.1.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:98884ecf2ffb7d7fe6bd517e8eb99d31ff7855a840fa6d0d63cd07c037f6a981"}, + {file = "greenlet-3.1.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f1d4aeb8891338e60d1ab6127af1fe45def5259def8094b9c7e34690c8858803"}, + {file = "greenlet-3.1.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db32b5348615a04b82240cc67983cb315309e88d444a288934ee6ceaebcad6cc"}, + {file = "greenlet-3.1.1-cp37-cp37m-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:dcc62f31eae24de7f8dce72134c8651c58000d3b1868e01392baea7c32c247de"}, + {file = "greenlet-3.1.1-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:1d3755bcb2e02de341c55b4fca7a745a24a9e7212ac953f6b3a48d117d7257aa"}, + {file = "greenlet-3.1.1-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:b8da394b34370874b4572676f36acabac172602abf054cbc4ac910219f3340af"}, + {file = "greenlet-3.1.1-cp37-cp37m-win32.whl", hash = "sha256:a0dfc6c143b519113354e780a50381508139b07d2177cb6ad6a08278ec655798"}, + {file = "greenlet-3.1.1-cp37-cp37m-win_amd64.whl", hash = "sha256:54558ea205654b50c438029505def3834e80f0869a70fb15b871c29b4575ddef"}, + {file = "greenlet-3.1.1-cp38-cp38-macosx_11_0_universal2.whl", hash = "sha256:346bed03fe47414091be4ad44786d1bd8bef0c3fcad6ed3dee074a032ab408a9"}, + {file = "greenlet-3.1.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dfc59d69fc48664bc693842bd57acfdd490acafda1ab52c7836e3fc75c90a111"}, + {file = "greenlet-3.1.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d21e10da6ec19b457b82636209cbe2331ff4306b54d06fa04b7c138ba18c8a81"}, + {file = "greenlet-3.1.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:37b9de5a96111fc15418819ab4c4432e4f3c2ede61e660b1e33971eba26ef9ba"}, + {file = "greenlet-3.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6ef9ea3f137e5711f0dbe5f9263e8c009b7069d8a1acea822bd5e9dae0ae49c8"}, + {file = "greenlet-3.1.1-cp38-cp38-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:85f3ff71e2e60bd4b4932a043fbbe0f499e263c628390b285cb599154a3b03b1"}, + {file = "greenlet-3.1.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:95ffcf719966dd7c453f908e208e14cde192e09fde6c7186c8f1896ef778d8cd"}, + {file = "greenlet-3.1.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:03a088b9de532cbfe2ba2034b2b85e82df37874681e8c470d6fb2f8c04d7e4b7"}, + {file = "greenlet-3.1.1-cp38-cp38-win32.whl", hash = "sha256:8b8b36671f10ba80e159378df9c4f15c14098c4fd73a36b9ad715f057272fbef"}, + {file = "greenlet-3.1.1-cp38-cp38-win_amd64.whl", hash = "sha256:7017b2be767b9d43cc31416aba48aab0d2309ee31b4dbf10a1d38fb7972bdf9d"}, + {file = "greenlet-3.1.1-cp39-cp39-macosx_11_0_universal2.whl", hash = "sha256:396979749bd95f018296af156201d6211240e7a23090f50a8d5d18c370084dc3"}, + {file = "greenlet-3.1.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ca9d0ff5ad43e785350894d97e13633a66e2b50000e8a183a50a88d834752d42"}, + {file = "greenlet-3.1.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f6ff3b14f2df4c41660a7dec01045a045653998784bf8cfcb5a525bdffffbc8f"}, + {file = "greenlet-3.1.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:94ebba31df2aa506d7b14866fed00ac141a867e63143fe5bca82a8e503b36437"}, + {file = "greenlet-3.1.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:73aaad12ac0ff500f62cebed98d8789198ea0e6f233421059fa68a5aa7220145"}, + {file = "greenlet-3.1.1-cp39-cp39-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:63e4844797b975b9af3a3fb8f7866ff08775f5426925e1e0bbcfe7932059a12c"}, + {file = "greenlet-3.1.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:7939aa3ca7d2a1593596e7ac6d59391ff30281ef280d8632fa03d81f7c5f955e"}, + {file = "greenlet-3.1.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d0028e725ee18175c6e422797c407874da24381ce0690d6b9396c204c7f7276e"}, + {file = "greenlet-3.1.1-cp39-cp39-win32.whl", hash = "sha256:5e06afd14cbaf9e00899fae69b24a32f2196c19de08fcb9f4779dd4f004e5e7c"}, + {file = "greenlet-3.1.1-cp39-cp39-win_amd64.whl", hash = "sha256:3319aa75e0e0639bc15ff54ca327e8dc7a6fe404003496e3c6925cd3142e0e22"}, + {file = "greenlet-3.1.1.tar.gz", hash = "sha256:4ce3ac6cdb6adf7946475d7ef31777c26d94bccc377e070a7986bd2d5c515467"}, +] + +[package.extras] +docs = ["Sphinx", "furo"] +test = ["objgraph", "psutil"] + [[package]] name = "gritql" version = "0.1.5" @@ -304,13 +644,13 @@ trio = ["trio (>=0.22.0,<1.0)"] [[package]] name = "httpx" -version = "0.27.2" +version = "0.28.0" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"}, - {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"}, + {file = "httpx-0.28.0-py3-none-any.whl", hash = "sha256:dc0b419a0cfeb6e8b34e85167c0da2671206f5095f1baa9663d23bcfd6b535fc"}, + {file = "httpx-0.28.0.tar.gz", hash = "sha256:0858d3bab51ba7e386637f22a61d8ccddaeec5f3fe4209da3a6168dbb91573e0"}, ] [package.dependencies] @@ -318,7 +658,6 @@ anyio = "*" certifi = "*" httpcore = "==1.*" idna = "*" -sniffio = "*" [package.extras] brotli = ["brotli", "brotlicffi"] @@ -377,15 +716,44 @@ files = [ {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"}, ] +[[package]] +name = "langchain" +version = "0.3.9" +description = "Building applications with LLMs through composability" +optional = false +python-versions = ">=3.9,<4.0" +files = [] +develop = true + +[package.dependencies] +aiohttp = "^3.8.3" +async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""} +langchain-core = "^0.3.21" +langchain-text-splitters = "^0.3.0" +langsmith = "^0.1.17" +numpy = [ + {version = ">=1.22.4,<2", markers = "python_version < \"3.12\""}, + {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}, +] +pydantic = "^2.7.4" +PyYAML = ">=5.3" +requests = "^2" +SQLAlchemy = ">=1.4,<3" +tenacity = ">=8.1.0,!=8.4.0,<10" + +[package.source] +type = "directory" +url = "../langchain" + [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = "<4.0,>=3.9" files = [ - {file = "langchain_core-0.3.19-py3-none-any.whl", hash = "sha256:562b7cc3c15dfaa9270cb1496990c1f3b3e0b660c4d6a3236d7f693346f2a96c"}, - {file = "langchain_core-0.3.19.tar.gz", hash = "sha256:126d9e8cadb2a5b8d1793a228c0783a3b608e36064d5a2ef1a4d38d07a344523"}, + {file = "langchain_core-0.3.21-py3-none-any.whl", hash = "sha256:7e723dff80946a1198976c6876fea8326dc82566ef9bcb5f8d9188f738733665"}, + {file = "langchain_core-0.3.21.tar.gz", hash = "sha256:561b52b258ffa50a9fb11d7a1940ebfd915654d1ec95b35e81dfd5ee84143411"}, ] [package.dependencies] @@ -400,6 +768,20 @@ PyYAML = ">=5.3" tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0" typing-extensions = ">=4.7" +[[package]] +name = "langchain-text-splitters" +version = "0.3.2" +description = "LangChain text splitting utilities" +optional = false +python-versions = "<4.0,>=3.9" +files = [ + {file = "langchain_text_splitters-0.3.2-py3-none-any.whl", hash = "sha256:0db28c53f41d1bc024cdb3b1646741f6d46d5371e90f31e7e7c9fbe75d01c726"}, + {file = "langchain_text_splitters-0.3.2.tar.gz", hash = "sha256:81e6515d9901d6dd8e35fb31ccd4f30f76d44b771890c789dc835ef9f16204df"}, +] + +[package.dependencies] +langchain-core = ">=0.3.15,<0.4.0" + [[package]] name = "langserve" version = "0.3.0" @@ -426,13 +808,13 @@ server = ["fastapi (>=0.90.1,<1)", "sse-starlette (>=1.3.0,<2.0.0)"] [[package]] name = "langsmith" -version = "0.1.144" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.144-py3-none-any.whl", hash = "sha256:08ffb975bff2e82fc6f5428837c64c074ea25102d08a25e256361a80812c6100"}, - {file = "langsmith-0.1.144.tar.gz", hash = "sha256:b621f358d5a33441d7b5e7264c376bf4ea82bfc62d7e41aafc0f8094e3bd6369"}, + {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"}, + {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"}, ] [package.dependencies] @@ -445,6 +827,9 @@ pydantic = [ requests = ">=2,<3" requests-toolbelt = ">=1.0.0,<2.0.0" +[package.extras] +langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"] + [[package]] name = "markdown-it-py" version = "3.0.0" @@ -480,71 +865,365 @@ files = [ {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"}, ] +[[package]] +name = "multidict" +version = "6.1.0" +description = "multidict implementation" +optional = false +python-versions = ">=3.8" +files = [ + {file = "multidict-6.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:3380252550e372e8511d49481bd836264c009adb826b23fefcc5dd3c69692f60"}, + {file = "multidict-6.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:99f826cbf970077383d7de805c0681799491cb939c25450b9b5b3ced03ca99f1"}, + {file = "multidict-6.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a114d03b938376557927ab23f1e950827c3b893ccb94b62fd95d430fd0e5cf53"}, + {file = "multidict-6.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b1c416351ee6271b2f49b56ad7f308072f6f44b37118d69c2cad94f3fa8a40d5"}, + {file = "multidict-6.1.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6b5d83030255983181005e6cfbac1617ce9746b219bc2aad52201ad121226581"}, + {file = "multidict-6.1.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3e97b5e938051226dc025ec80980c285b053ffb1e25a3db2a3aa3bc046bf7f56"}, + {file = "multidict-6.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d618649d4e70ac6efcbba75be98b26ef5078faad23592f9b51ca492953012429"}, + {file = "multidict-6.1.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:10524ebd769727ac77ef2278390fb0068d83f3acb7773792a5080f2b0abf7748"}, + {file = "multidict-6.1.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:ff3827aef427c89a25cc96ded1759271a93603aba9fb977a6d264648ebf989db"}, + {file = "multidict-6.1.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:06809f4f0f7ab7ea2cabf9caca7d79c22c0758b58a71f9d32943ae13c7ace056"}, + {file = "multidict-6.1.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:f179dee3b863ab1c59580ff60f9d99f632f34ccb38bf67a33ec6b3ecadd0fd76"}, + {file = "multidict-6.1.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:aaed8b0562be4a0876ee3b6946f6869b7bcdb571a5d1496683505944e268b160"}, + {file = "multidict-6.1.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:3c8b88a2ccf5493b6c8da9076fb151ba106960a2df90c2633f342f120751a9e7"}, + {file = "multidict-6.1.0-cp310-cp310-win32.whl", hash = "sha256:4a9cb68166a34117d6646c0023c7b759bf197bee5ad4272f420a0141d7eb03a0"}, + {file = "multidict-6.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:20b9b5fbe0b88d0bdef2012ef7dee867f874b72528cf1d08f1d59b0e3850129d"}, + {file = "multidict-6.1.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:3efe2c2cb5763f2f1b275ad2bf7a287d3f7ebbef35648a9726e3b69284a4f3d6"}, + {file = "multidict-6.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c7053d3b0353a8b9de430a4f4b4268ac9a4fb3481af37dfe49825bf45ca24156"}, + {file = "multidict-6.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:27e5fc84ccef8dfaabb09d82b7d179c7cf1a3fbc8a966f8274fcb4ab2eb4cadb"}, + {file = "multidict-6.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e2b90b43e696f25c62656389d32236e049568b39320e2735d51f08fd362761b"}, + {file = "multidict-6.1.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d83a047959d38a7ff552ff94be767b7fd79b831ad1cd9920662db05fec24fe72"}, + {file = "multidict-6.1.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d1a9dd711d0877a1ece3d2e4fea11a8e75741ca21954c919406b44e7cf971304"}, + {file = "multidict-6.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ec2abea24d98246b94913b76a125e855eb5c434f7c46546046372fe60f666351"}, + {file = "multidict-6.1.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4867cafcbc6585e4b678876c489b9273b13e9fff9f6d6d66add5e15d11d926cb"}, + {file = "multidict-6.1.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:5b48204e8d955c47c55b72779802b219a39acc3ee3d0116d5080c388970b76e3"}, + {file = "multidict-6.1.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:d8fff389528cad1618fb4b26b95550327495462cd745d879a8c7c2115248e399"}, + {file = "multidict-6.1.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:a7a9541cd308eed5e30318430a9c74d2132e9a8cb46b901326272d780bf2d423"}, + {file = "multidict-6.1.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:da1758c76f50c39a2efd5e9859ce7d776317eb1dd34317c8152ac9251fc574a3"}, + {file = "multidict-6.1.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:c943a53e9186688b45b323602298ab727d8865d8c9ee0b17f8d62d14b56f0753"}, + {file = "multidict-6.1.0-cp311-cp311-win32.whl", hash = "sha256:90f8717cb649eea3504091e640a1b8568faad18bd4b9fcd692853a04475a4b80"}, + {file = "multidict-6.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:82176036e65644a6cc5bd619f65f6f19781e8ec2e5330f51aa9ada7504cc1926"}, + {file = "multidict-6.1.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:b04772ed465fa3cc947db808fa306d79b43e896beb677a56fb2347ca1a49c1fa"}, + {file = "multidict-6.1.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:6180c0ae073bddeb5a97a38c03f30c233e0a4d39cd86166251617d1bbd0af436"}, + {file = "multidict-6.1.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:071120490b47aa997cca00666923a83f02c7fbb44f71cf7f136df753f7fa8761"}, + {file = "multidict-6.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50b3a2710631848991d0bf7de077502e8994c804bb805aeb2925a981de58ec2e"}, + {file = "multidict-6.1.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b58c621844d55e71c1b7f7c498ce5aa6985d743a1a59034c57a905b3f153c1ef"}, + {file = "multidict-6.1.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:55b6d90641869892caa9ca42ff913f7ff1c5ece06474fbd32fb2cf6834726c95"}, + {file = "multidict-6.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4b820514bfc0b98a30e3d85462084779900347e4d49267f747ff54060cc33925"}, + {file = "multidict-6.1.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:10a9b09aba0c5b48c53761b7c720aaaf7cf236d5fe394cd399c7ba662d5f9966"}, + {file = "multidict-6.1.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1e16bf3e5fc9f44632affb159d30a437bfe286ce9e02754759be5536b169b305"}, + {file = "multidict-6.1.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:76f364861c3bfc98cbbcbd402d83454ed9e01a5224bb3a28bf70002a230f73e2"}, + {file = "multidict-6.1.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:820c661588bd01a0aa62a1283f20d2be4281b086f80dad9e955e690c75fb54a2"}, + {file = "multidict-6.1.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:0e5f362e895bc5b9e67fe6e4ded2492d8124bdf817827f33c5b46c2fe3ffaca6"}, + {file = "multidict-6.1.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:3ec660d19bbc671e3a6443325f07263be452c453ac9e512f5eb935e7d4ac28b3"}, + {file = "multidict-6.1.0-cp312-cp312-win32.whl", hash = "sha256:58130ecf8f7b8112cdb841486404f1282b9c86ccb30d3519faf301b2e5659133"}, + {file = "multidict-6.1.0-cp312-cp312-win_amd64.whl", hash = "sha256:188215fc0aafb8e03341995e7c4797860181562380f81ed0a87ff455b70bf1f1"}, + {file = "multidict-6.1.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:d569388c381b24671589335a3be6e1d45546c2988c2ebe30fdcada8457a31008"}, + {file = "multidict-6.1.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:052e10d2d37810b99cc170b785945421141bf7bb7d2f8799d431e7db229c385f"}, + {file = "multidict-6.1.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f90c822a402cb865e396a504f9fc8173ef34212a342d92e362ca498cad308e28"}, + {file = "multidict-6.1.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b225d95519a5bf73860323e633a664b0d85ad3d5bede6d30d95b35d4dfe8805b"}, + {file = "multidict-6.1.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:23bfd518810af7de1116313ebd9092cb9aa629beb12f6ed631ad53356ed6b86c"}, + {file = "multidict-6.1.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5c09fcfdccdd0b57867577b719c69e347a436b86cd83747f179dbf0cc0d4c1f3"}, + {file = "multidict-6.1.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf6bea52ec97e95560af5ae576bdac3aa3aae0b6758c6efa115236d9e07dae44"}, + {file = "multidict-6.1.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:57feec87371dbb3520da6192213c7d6fc892d5589a93db548331954de8248fd2"}, + {file = "multidict-6.1.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0c3f390dc53279cbc8ba976e5f8035eab997829066756d811616b652b00a23a3"}, + {file = "multidict-6.1.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:59bfeae4b25ec05b34f1956eaa1cb38032282cd4dfabc5056d0a1ec4d696d3aa"}, + {file = "multidict-6.1.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:b2f59caeaf7632cc633b5cf6fc449372b83bbdf0da4ae04d5be36118e46cc0aa"}, + {file = "multidict-6.1.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:37bb93b2178e02b7b618893990941900fd25b6b9ac0fa49931a40aecdf083fe4"}, + {file = "multidict-6.1.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4e9f48f58c2c523d5a06faea47866cd35b32655c46b443f163d08c6d0ddb17d6"}, + {file = "multidict-6.1.0-cp313-cp313-win32.whl", hash = "sha256:3a37ffb35399029b45c6cc33640a92bef403c9fd388acce75cdc88f58bd19a81"}, + {file = "multidict-6.1.0-cp313-cp313-win_amd64.whl", hash = "sha256:e9aa71e15d9d9beaad2c6b9319edcdc0a49a43ef5c0a4c8265ca9ee7d6c67774"}, + {file = "multidict-6.1.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:db7457bac39421addd0c8449933ac32d8042aae84a14911a757ae6ca3eef1392"}, + {file = "multidict-6.1.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:d094ddec350a2fb899fec68d8353c78233debde9b7d8b4beeafa70825f1c281a"}, + {file = "multidict-6.1.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:5845c1fd4866bb5dd3125d89b90e57ed3138241540897de748cdf19de8a2fca2"}, + {file = "multidict-6.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9079dfc6a70abe341f521f78405b8949f96db48da98aeb43f9907f342f627cdc"}, + {file = "multidict-6.1.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3914f5aaa0f36d5d60e8ece6a308ee1c9784cd75ec8151062614657a114c4478"}, + {file = "multidict-6.1.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c08be4f460903e5a9d0f76818db3250f12e9c344e79314d1d570fc69d7f4eae4"}, + {file = "multidict-6.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d093be959277cb7dee84b801eb1af388b6ad3ca6a6b6bf1ed7585895789d027d"}, + {file = "multidict-6.1.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3702ea6872c5a2a4eeefa6ffd36b042e9773f05b1f37ae3ef7264b1163c2dcf6"}, + {file = "multidict-6.1.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:2090f6a85cafc5b2db085124d752757c9d251548cedabe9bd31afe6363e0aff2"}, + {file = "multidict-6.1.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:f67f217af4b1ff66c68a87318012de788dd95fcfeb24cc889011f4e1c7454dfd"}, + {file = "multidict-6.1.0-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:189f652a87e876098bbc67b4da1049afb5f5dfbaa310dd67c594b01c10388db6"}, + {file = "multidict-6.1.0-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:6bb5992037f7a9eff7991ebe4273ea7f51f1c1c511e6a2ce511d0e7bdb754492"}, + {file = "multidict-6.1.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:ac10f4c2b9e770c4e393876e35a7046879d195cd123b4f116d299d442b335bcd"}, + {file = "multidict-6.1.0-cp38-cp38-win32.whl", hash = "sha256:e27bbb6d14416713a8bd7aaa1313c0fc8d44ee48d74497a0ff4c3a1b6ccb5167"}, + {file = "multidict-6.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:22f3105d4fb15c8f57ff3959a58fcab6ce36814486500cd7485651230ad4d4ef"}, + {file = "multidict-6.1.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:4e18b656c5e844539d506a0a06432274d7bd52a7487e6828c63a63d69185626c"}, + {file = "multidict-6.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a185f876e69897a6f3325c3f19f26a297fa058c5e456bfcff8015e9a27e83ae1"}, + {file = "multidict-6.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ab7c4ceb38d91570a650dba194e1ca87c2b543488fe9309b4212694174fd539c"}, + {file = "multidict-6.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e617fb6b0b6953fffd762669610c1c4ffd05632c138d61ac7e14ad187870669c"}, + {file = "multidict-6.1.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:16e5f4bf4e603eb1fdd5d8180f1a25f30056f22e55ce51fb3d6ad4ab29f7d96f"}, + {file = "multidict-6.1.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c035da3f544b1882bac24115f3e2e8760f10a0107614fc9839fd232200b875"}, + {file = "multidict-6.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:957cf8e4b6e123a9eea554fa7ebc85674674b713551de587eb318a2df3e00255"}, + {file = "multidict-6.1.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:483a6aea59cb89904e1ceabd2b47368b5600fb7de78a6e4a2c2987b2d256cf30"}, + {file = "multidict-6.1.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:87701f25a2352e5bf7454caa64757642734da9f6b11384c1f9d1a8e699758057"}, + {file = "multidict-6.1.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:682b987361e5fd7a139ed565e30d81fd81e9629acc7d925a205366877d8c8657"}, + {file = "multidict-6.1.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:ce2186a7df133a9c895dea3331ddc5ddad42cdd0d1ea2f0a51e5d161e4762f28"}, + {file = "multidict-6.1.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9f636b730f7e8cb19feb87094949ba54ee5357440b9658b2a32a5ce4bce53972"}, + {file = "multidict-6.1.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:73eae06aa53af2ea5270cc066dcaf02cc60d2994bbb2c4ef5764949257d10f43"}, + {file = "multidict-6.1.0-cp39-cp39-win32.whl", hash = "sha256:1ca0083e80e791cffc6efce7660ad24af66c8d4079d2a750b29001b53ff59ada"}, + {file = "multidict-6.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:aa466da5b15ccea564bdab9c89175c762bc12825f4659c11227f515cee76fa4a"}, + {file = "multidict-6.1.0-py3-none-any.whl", hash = "sha256:48e171e52d1c4d33888e529b999e5900356b9ae588c2f09a52dcefb158b27506"}, + {file = "multidict-6.1.0.tar.gz", hash = "sha256:22ae2ebf9b0c69d206c003e2f6a914ea33f0a932d4aa16f236afc049d9958f4a"}, +] + +[package.dependencies] +typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""} + +[[package]] +name = "mypy" +version = "1.13.0" +description = "Optional static typing for Python" +optional = false +python-versions = ">=3.8" +files = [ + {file = "mypy-1.13.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6607e0f1dd1fb7f0aca14d936d13fd19eba5e17e1cd2a14f808fa5f8f6d8f60a"}, + {file = "mypy-1.13.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8a21be69bd26fa81b1f80a61ee7ab05b076c674d9b18fb56239d72e21d9f4c80"}, + {file = "mypy-1.13.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7b2353a44d2179846a096e25691d54d59904559f4232519d420d64da6828a3a7"}, + {file = "mypy-1.13.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0730d1c6a2739d4511dc4253f8274cdd140c55c32dfb0a4cf8b7a43f40abfa6f"}, + {file = "mypy-1.13.0-cp310-cp310-win_amd64.whl", hash = "sha256:c5fc54dbb712ff5e5a0fca797e6e0aa25726c7e72c6a5850cfd2adbc1eb0a372"}, + {file = "mypy-1.13.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:581665e6f3a8a9078f28d5502f4c334c0c8d802ef55ea0e7276a6e409bc0d82d"}, + {file = "mypy-1.13.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3ddb5b9bf82e05cc9a627e84707b528e5c7caaa1c55c69e175abb15a761cec2d"}, + {file = "mypy-1.13.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:20c7ee0bc0d5a9595c46f38beb04201f2620065a93755704e141fcac9f59db2b"}, + {file = "mypy-1.13.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:3790ded76f0b34bc9c8ba4def8f919dd6a46db0f5a6610fb994fe8efdd447f73"}, + {file = "mypy-1.13.0-cp311-cp311-win_amd64.whl", hash = "sha256:51f869f4b6b538229c1d1bcc1dd7d119817206e2bc54e8e374b3dfa202defcca"}, + {file = "mypy-1.13.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:5c7051a3461ae84dfb5dd15eff5094640c61c5f22257c8b766794e6dd85e72d5"}, + {file = "mypy-1.13.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:39bb21c69a5d6342f4ce526e4584bc5c197fd20a60d14a8624d8743fffb9472e"}, + {file = "mypy-1.13.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:164f28cb9d6367439031f4c81e84d3ccaa1e19232d9d05d37cb0bd880d3f93c2"}, + {file = "mypy-1.13.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a4c1bfcdbce96ff5d96fc9b08e3831acb30dc44ab02671eca5953eadad07d6d0"}, + {file = "mypy-1.13.0-cp312-cp312-win_amd64.whl", hash = "sha256:a0affb3a79a256b4183ba09811e3577c5163ed06685e4d4b46429a271ba174d2"}, + {file = "mypy-1.13.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:a7b44178c9760ce1a43f544e595d35ed61ac2c3de306599fa59b38a6048e1aa7"}, + {file = "mypy-1.13.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:5d5092efb8516d08440e36626f0153b5006d4088c1d663d88bf79625af3d1d62"}, + {file = "mypy-1.13.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:de2904956dac40ced10931ac967ae63c5089bd498542194b436eb097a9f77bc8"}, + {file = "mypy-1.13.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:7bfd8836970d33c2105562650656b6846149374dc8ed77d98424b40b09340ba7"}, + {file = "mypy-1.13.0-cp313-cp313-win_amd64.whl", hash = "sha256:9f73dba9ec77acb86457a8fc04b5239822df0c14a082564737833d2963677dbc"}, + {file = "mypy-1.13.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:100fac22ce82925f676a734af0db922ecfea991e1d7ec0ceb1e115ebe501301a"}, + {file = "mypy-1.13.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:7bcb0bb7f42a978bb323a7c88f1081d1b5dee77ca86f4100735a6f541299d8fb"}, + {file = "mypy-1.13.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bde31fc887c213e223bbfc34328070996061b0833b0a4cfec53745ed61f3519b"}, + {file = "mypy-1.13.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:07de989f89786f62b937851295ed62e51774722e5444a27cecca993fc3f9cd74"}, + {file = "mypy-1.13.0-cp38-cp38-win_amd64.whl", hash = "sha256:4bde84334fbe19bad704b3f5b78c4abd35ff1026f8ba72b29de70dda0916beb6"}, + {file = "mypy-1.13.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0246bcb1b5de7f08f2826451abd947bf656945209b140d16ed317f65a17dc7dc"}, + {file = "mypy-1.13.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:7f5b7deae912cf8b77e990b9280f170381fdfbddf61b4ef80927edd813163732"}, + {file = "mypy-1.13.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7029881ec6ffb8bc233a4fa364736789582c738217b133f1b55967115288a2bc"}, + {file = "mypy-1.13.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:3e38b980e5681f28f033f3be86b099a247b13c491f14bb8b1e1e134d23bb599d"}, + {file = "mypy-1.13.0-cp39-cp39-win_amd64.whl", hash = "sha256:a6789be98a2017c912ae6ccb77ea553bbaf13d27605d2ca20a76dfbced631b24"}, + {file = "mypy-1.13.0-py3-none-any.whl", hash = "sha256:9c250883f9fd81d212e0952c92dbfcc96fc237f4b7c92f56ac81fd48460b3e5a"}, + {file = "mypy-1.13.0.tar.gz", hash = "sha256:0291a61b6fbf3e6673e3405cfcc0e7650bebc7939659fdca2702958038bd835e"}, +] + +[package.dependencies] +mypy-extensions = ">=1.0.0" +tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} +typing-extensions = ">=4.6.0" + +[package.extras] +dmypy = ["psutil (>=4.0)"] +faster-cache = ["orjson"] +install-types = ["pip"] +mypyc = ["setuptools (>=50)"] +reports = ["lxml"] + +[[package]] +name = "mypy-extensions" +version = "1.0.0" +description = "Type system extensions for programs checked with the mypy type checker." +optional = false +python-versions = ">=3.5" +files = [ + {file = "mypy_extensions-1.0.0-py3-none-any.whl", hash = "sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d"}, + {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"}, +] + +[[package]] +name = "numpy" +version = "1.26.4" +description = "Fundamental package for array computing in Python" +optional = false +python-versions = ">=3.9" +files = [ + {file = "numpy-1.26.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9ff0f4f29c51e2803569d7a51c2304de5554655a60c5d776e35b4a41413830d0"}, + {file = "numpy-1.26.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2e4ee3380d6de9c9ec04745830fd9e2eccb3e6cf790d39d7b98ffd19b0dd754a"}, + {file = "numpy-1.26.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d209d8969599b27ad20994c8e41936ee0964e6da07478d6c35016bc386b66ad4"}, + {file = "numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ffa75af20b44f8dba823498024771d5ac50620e6915abac414251bd971b4529f"}, + {file = "numpy-1.26.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:62b8e4b1e28009ef2846b4c7852046736bab361f7aeadeb6a5b89ebec3c7055a"}, + {file = "numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a4abb4f9001ad2858e7ac189089c42178fcce737e4169dc61321660f1a96c7d2"}, + {file = "numpy-1.26.4-cp310-cp310-win32.whl", hash = "sha256:bfe25acf8b437eb2a8b2d49d443800a5f18508cd811fea3181723922a8a82b07"}, + {file = "numpy-1.26.4-cp310-cp310-win_amd64.whl", hash = "sha256:b97fe8060236edf3662adfc2c633f56a08ae30560c56310562cb4f95500022d5"}, + {file = "numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4c66707fabe114439db9068ee468c26bbdf909cac0fb58686a42a24de1760c71"}, + {file = "numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:edd8b5fe47dab091176d21bb6de568acdd906d1887a4584a15a9a96a1dca06ef"}, + {file = "numpy-1.26.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ab55401287bfec946ced39700c053796e7cc0e3acbef09993a9ad2adba6ca6e"}, + {file = "numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:666dbfb6ec68962c033a450943ded891bed2d54e6755e35e5835d63f4f6931d5"}, + {file = "numpy-1.26.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:96ff0b2ad353d8f990b63294c8986f1ec3cb19d749234014f4e7eb0112ceba5a"}, + {file = "numpy-1.26.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:60dedbb91afcbfdc9bc0b1f3f402804070deed7392c23eb7a7f07fa857868e8a"}, + {file = "numpy-1.26.4-cp311-cp311-win32.whl", hash = "sha256:1af303d6b2210eb850fcf03064d364652b7120803a0b872f5211f5234b399f20"}, + {file = "numpy-1.26.4-cp311-cp311-win_amd64.whl", hash = "sha256:cd25bcecc4974d09257ffcd1f098ee778f7834c3ad767fe5db785be9a4aa9cb2"}, + {file = "numpy-1.26.4-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:b3ce300f3644fb06443ee2222c2201dd3a89ea6040541412b8fa189341847218"}, + {file = "numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b"}, + {file = "numpy-1.26.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9fad7dcb1aac3c7f0584a5a8133e3a43eeb2fe127f47e3632d43d677c66c102b"}, + {file = "numpy-1.26.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:675d61ffbfa78604709862923189bad94014bef562cc35cf61d3a07bba02a7ed"}, + {file = "numpy-1.26.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:ab47dbe5cc8210f55aa58e4805fe224dac469cde56b9f731a4c098b91917159a"}, + {file = "numpy-1.26.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:1dda2e7b4ec9dd512f84935c5f126c8bd8b9f2fc001e9f54af255e8c5f16b0e0"}, + {file = "numpy-1.26.4-cp312-cp312-win32.whl", hash = "sha256:50193e430acfc1346175fcbdaa28ffec49947a06918b7b92130744e81e640110"}, + {file = "numpy-1.26.4-cp312-cp312-win_amd64.whl", hash = "sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818"}, + {file = "numpy-1.26.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:7349ab0fa0c429c82442a27a9673fc802ffdb7c7775fad780226cb234965e53c"}, + {file = "numpy-1.26.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:52b8b60467cd7dd1e9ed082188b4e6bb35aa5cdd01777621a1658910745b90be"}, + {file = "numpy-1.26.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d5241e0a80d808d70546c697135da2c613f30e28251ff8307eb72ba696945764"}, + {file = "numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f870204a840a60da0b12273ef34f7051e98c3b5961b61b0c2c1be6dfd64fbcd3"}, + {file = "numpy-1.26.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:679b0076f67ecc0138fd2ede3a8fd196dddc2ad3254069bcb9faf9a79b1cebcd"}, + {file = "numpy-1.26.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:47711010ad8555514b434df65f7d7b076bb8261df1ca9bb78f53d3b2db02e95c"}, + {file = "numpy-1.26.4-cp39-cp39-win32.whl", hash = "sha256:a354325ee03388678242a4d7ebcd08b5c727033fcff3b2f536aea978e15ee9e6"}, + {file = "numpy-1.26.4-cp39-cp39-win_amd64.whl", hash = "sha256:3373d5d70a5fe74a2c1bb6d2cfd9609ecf686d47a2d7b1d37a8f3b6bf6003aea"}, + {file = "numpy-1.26.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:afedb719a9dcfc7eaf2287b839d8198e06dcd4cb5d276a3df279231138e83d30"}, + {file = "numpy-1.26.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:95a7476c59002f2f6c590b9b7b998306fba6a5aa646b1e22ddfeaf8f78c3a29c"}, + {file = "numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:7e50d0a0cc3189f9cb0aeb3a6a6af18c16f59f004b866cd2be1c14b36134a4a0"}, + {file = "numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010"}, +] + +[[package]] +name = "numpy" +version = "2.1.3" +description = "Fundamental package for array computing in Python" +optional = false +python-versions = ">=3.10" +files = [ + {file = "numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c894b4305373b9c5576d7a12b473702afdf48ce5369c074ba304cc5ad8730dff"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b47fbb433d3260adcd51eb54f92a2ffbc90a4595f8970ee00e064c644ac788f5"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:825656d0743699c529c5943554d223c021ff0494ff1442152ce887ef4f7561a1"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:6a4825252fcc430a182ac4dee5a505053d262c807f8a924603d411f6718b88fd"}, + {file = "numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e711e02f49e176a01d0349d82cb5f05ba4db7d5e7e0defd026328e5cfb3226d3"}, + {file = "numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:78574ac2d1a4a02421f25da9559850d59457bac82f2b8d7a44fe83a64f770098"}, + {file = "numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:c7662f0e3673fe4e832fe07b65c50342ea27d989f92c80355658c7f888fcc83c"}, + {file = "numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:fa2d1337dc61c8dc417fbccf20f6d1e139896a30721b7f1e832b2bb6ef4eb6c4"}, + {file = "numpy-2.1.3-cp310-cp310-win32.whl", hash = "sha256:72dcc4a35a8515d83e76b58fdf8113a5c969ccd505c8a946759b24e3182d1f23"}, + {file = "numpy-2.1.3-cp310-cp310-win_amd64.whl", hash = "sha256:ecc76a9ba2911d8d37ac01de72834d8849e55473457558e12995f4cd53e778e0"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4d1167c53b93f1f5d8a139a742b3c6f4d429b54e74e6b57d0eff40045187b15d"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c80e4a09b3d95b4e1cac08643f1152fa71a0a821a2d4277334c88d54b2219a41"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:576a1c1d25e9e02ed7fa5477f30a127fe56debd53b8d2c89d5578f9857d03ca9"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:973faafebaae4c0aaa1a1ca1ce02434554d67e628b8d805e61f874b84e136b09"}, + {file = "numpy-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:762479be47a4863e261a840e8e01608d124ee1361e48b96916f38b119cfda04a"}, + {file = "numpy-2.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc6f24b3d1ecc1eebfbf5d6051faa49af40b03be1aaa781ebdadcbc090b4539b"}, + {file = "numpy-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:17ee83a1f4fef3c94d16dc1802b998668b5419362c8a4f4e8a491de1b41cc3ee"}, + {file = "numpy-2.1.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:15cb89f39fa6d0bdfb600ea24b250e5f1a3df23f901f51c8debaa6a5d122b2f0"}, + {file = "numpy-2.1.3-cp311-cp311-win32.whl", hash = "sha256:d9beb777a78c331580705326d2367488d5bc473b49a9bc3036c154832520aca9"}, + {file = "numpy-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:d89dd2b6da69c4fff5e39c28a382199ddedc3a5be5390115608345dec660b9e2"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f55ba01150f52b1027829b50d70ef1dafd9821ea82905b63936668403c3b471e"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:13138eadd4f4da03074851a698ffa7e405f41a0845a6b1ad135b81596e4e9958"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:a6b46587b14b888e95e4a24d7b13ae91fa22386c199ee7b418f449032b2fa3b8"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:0fa14563cc46422e99daef53d725d0c326e99e468a9320a240affffe87852564"}, + {file = "numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8637dcd2caa676e475503d1f8fdb327bc495554e10838019651b76d17b98e512"}, + {file = "numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2312b2aa89e1f43ecea6da6ea9a810d06aae08321609d8dc0d0eda6d946a541b"}, + {file = "numpy-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a38c19106902bb19351b83802531fea19dee18e5b37b36454f27f11ff956f7fc"}, + {file = "numpy-2.1.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:02135ade8b8a84011cbb67dc44e07c58f28575cf9ecf8ab304e51c05528c19f0"}, + {file = "numpy-2.1.3-cp312-cp312-win32.whl", hash = "sha256:e6988e90fcf617da2b5c78902fe8e668361b43b4fe26dbf2d7b0f8034d4cafb9"}, + {file = "numpy-2.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:0d30c543f02e84e92c4b1f415b7c6b5326cbe45ee7882b6b77db7195fb971e3a"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:96fe52fcdb9345b7cd82ecd34547fca4321f7656d500eca497eb7ea5a926692f"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f653490b33e9c3a4c1c01d41bc2aef08f9475af51146e4a7710c450cf9761598"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:dc258a761a16daa791081d026f0ed4399b582712e6fc887a95af09df10c5ca57"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:016d0f6f5e77b0f0d45d77387ffa4bb89816b57c835580c3ce8e099ef830befe"}, + {file = "numpy-2.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c181ba05ce8299c7aa3125c27b9c2167bca4a4445b7ce73d5febc411ca692e43"}, + {file = "numpy-2.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5641516794ca9e5f8a4d17bb45446998c6554704d888f86df9b200e66bdcce56"}, + {file = "numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ea4dedd6e394a9c180b33c2c872b92f7ce0f8e7ad93e9585312b0c5a04777a4a"}, + {file = "numpy-2.1.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:b0df3635b9c8ef48bd3be5f862cf71b0a4716fa0e702155c45067c6b711ddcef"}, + {file = "numpy-2.1.3-cp313-cp313-win32.whl", hash = "sha256:50ca6aba6e163363f132b5c101ba078b8cbd3fa92c7865fd7d4d62d9779ac29f"}, + {file = "numpy-2.1.3-cp313-cp313-win_amd64.whl", hash = "sha256:747641635d3d44bcb380d950679462fae44f54b131be347d5ec2bce47d3df9ed"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:996bb9399059c5b82f76b53ff8bb686069c05acc94656bb259b1d63d04a9506f"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:45966d859916ad02b779706bb43b954281db43e185015df6eb3323120188f9e4"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:baed7e8d7481bfe0874b566850cb0b85243e982388b7b23348c6db2ee2b2ae8e"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:a9f7f672a3388133335589cfca93ed468509cb7b93ba3105fce780d04a6576a0"}, + {file = "numpy-2.1.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7aac50327da5d208db2eec22eb11e491e3fe13d22653dce51b0f4109101b408"}, + {file = "numpy-2.1.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4394bc0dbd074b7f9b52024832d16e019decebf86caf909d94f6b3f77a8ee3b6"}, + {file = "numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl", hash = "sha256:50d18c4358a0a8a53f12a8ba9d772ab2d460321e6a93d6064fc22443d189853f"}, + {file = "numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:14e253bd43fc6b37af4921b10f6add6925878a42a0c5fe83daee390bca80bc17"}, + {file = "numpy-2.1.3-cp313-cp313t-win32.whl", hash = "sha256:08788d27a5fd867a663f6fc753fd7c3ad7e92747efc73c53bca2f19f8bc06f48"}, + {file = "numpy-2.1.3-cp313-cp313t-win_amd64.whl", hash = "sha256:2564fbdf2b99b3f815f2107c1bbc93e2de8ee655a69c261363a1172a79a257d4"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:4f2015dfe437dfebbfce7c85c7b53d81ba49e71ba7eadbf1df40c915af75979f"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:3522b0dfe983a575e6a9ab3a4a4dfe156c3e428468ff08ce582b9bb6bd1d71d4"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c006b607a865b07cd981ccb218a04fc86b600411d83d6fc261357f1c0966755d"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:e14e26956e6f1696070788252dcdff11b4aca4c3e8bd166e0df1bb8f315a67cb"}, + {file = "numpy-2.1.3.tar.gz", hash = "sha256:aa08e04e08aaf974d4458def539dece0d28146d866a39da5639596f4921fd761"}, +] + [[package]] name = "orjson" -version = "3.10.11" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.11-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6dade64687f2bd7c090281652fe18f1151292d567a9302b34c2dbb92a3872f1f"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82f07c550a6ccd2b9290849b22316a609023ed851a87ea888c0456485a7d196a"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd9a187742d3ead9df2e49240234d728c67c356516cf4db018833a86f20ec18c"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:77b0fed6f209d76c1c39f032a70df2d7acf24b1812ca3e6078fd04e8972685a3"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:63fc9d5fe1d4e8868f6aae547a7b8ba0a2e592929245fff61d633f4caccdcdd6"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65cd3e3bb4fbb4eddc3c1e8dce10dc0b73e808fcb875f9fab40c81903dd9323e"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6f67c570602300c4befbda12d153113b8974a3340fdcf3d6de095ede86c06d92"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:1f39728c7f7d766f1f5a769ce4d54b5aaa4c3f92d5b84817053cc9995b977acc"}, - {file = "orjson-3.10.11-cp310-none-win32.whl", hash = "sha256:1789d9db7968d805f3d94aae2c25d04014aae3a2fa65b1443117cd462c6da647"}, - {file = "orjson-3.10.11-cp310-none-win_amd64.whl", hash = "sha256:5576b1e5a53a5ba8f8df81872bb0878a112b3ebb1d392155f00f54dd86c83ff6"}, - {file = "orjson-3.10.11-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1444f9cb7c14055d595de1036f74ecd6ce15f04a715e73f33bb6326c9cef01b6"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdec57fe3b4bdebcc08a946db3365630332dbe575125ff3d80a3272ebd0ddafe"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4eed32f33a0ea6ef36ccc1d37f8d17f28a1d6e8eefae5928f76aff8f1df85e67"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:80df27dd8697242b904f4ea54820e2d98d3f51f91e97e358fc13359721233e4b"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:705f03cee0cb797256d54de6695ef219e5bc8c8120b6654dd460848d57a9af3d"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03246774131701de8e7059b2e382597da43144a9a7400f178b2a32feafc54bd5"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8b5759063a6c940a69c728ea70d7c33583991c6982915a839c8da5f957e0103a"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:677f23e32491520eebb19c99bb34675daf5410c449c13416f7f0d93e2cf5f981"}, - {file = "orjson-3.10.11-cp311-none-win32.whl", hash = "sha256:a11225d7b30468dcb099498296ffac36b4673a8398ca30fdaec1e6c20df6aa55"}, - {file = "orjson-3.10.11-cp311-none-win_amd64.whl", hash = "sha256:df8c677df2f9f385fcc85ab859704045fa88d4668bc9991a527c86e710392bec"}, - {file = "orjson-3.10.11-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:360a4e2c0943da7c21505e47cf6bd725588962ff1d739b99b14e2f7f3545ba51"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:496e2cb45de21c369079ef2d662670a4892c81573bcc143c4205cae98282ba97"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7dfa8db55c9792d53c5952900c6a919cfa377b4f4534c7a786484a6a4a350c19"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:51f3382415747e0dbda9dade6f1e1a01a9d37f630d8c9049a8ed0e385b7a90c0"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f35a1b9f50a219f470e0e497ca30b285c9f34948d3c8160d5ad3a755d9299433"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e2f3b7c5803138e67028dde33450e054c87e0703afbe730c105f1fcd873496d5"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f91d9eb554310472bd09f5347950b24442600594c2edc1421403d7610a0998fd"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dfbb2d460a855c9744bbc8e36f9c3a997c4b27d842f3d5559ed54326e6911f9b"}, - {file = "orjson-3.10.11-cp312-none-win32.whl", hash = "sha256:d4a62c49c506d4d73f59514986cadebb7e8d186ad510c518f439176cf8d5359d"}, - {file = "orjson-3.10.11-cp312-none-win_amd64.whl", hash = "sha256:f1eec3421a558ff7a9b010a6c7effcfa0ade65327a71bb9b02a1c3b77a247284"}, - {file = "orjson-3.10.11-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c46294faa4e4d0eb73ab68f1a794d2cbf7bab33b1dda2ac2959ffb7c61591899"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:52e5834d7d6e58a36846e059d00559cb9ed20410664f3ad156cd2cc239a11230"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2fc947e5350fdce548bfc94f434e8760d5cafa97fb9c495d2fef6757aa02ec0"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0efabbf839388a1dab5b72b5d3baedbd6039ac83f3b55736eb9934ea5494d258"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a3f29634260708c200c4fe148e42b4aae97d7b9fee417fbdd74f8cfc265f15b0"}, - {file = "orjson-3.10.11-cp313-none-win32.whl", hash = "sha256:1a1222ffcee8a09476bbdd5d4f6f33d06d0d6642df2a3d78b7a195ca880d669b"}, - {file = "orjson-3.10.11-cp313-none-win_amd64.whl", hash = "sha256:bc274ac261cc69260913b2d1610760e55d3c0801bb3457ba7b9004420b6b4270"}, - {file = "orjson-3.10.11-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:19b3763e8bbf8ad797df6b6b5e0fc7c843ec2e2fc0621398534e0c6400098f87"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1be83a13312e5e58d633580c5eb8d0495ae61f180da2722f20562974188af205"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:afacfd1ab81f46dedd7f6001b6d4e8de23396e4884cd3c3436bd05defb1a6446"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb4d0bea56bba596723d73f074c420aec3b2e5d7d30698bc56e6048066bd560c"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96ed1de70fcb15d5fed529a656df29f768187628727ee2788344e8a51e1c1350"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4bfb30c891b530f3f80e801e3ad82ef150b964e5c38e1fb8482441c69c35c61c"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:d496c74fc2b61341e3cefda7eec21b7854c5f672ee350bc55d9a4997a8a95204"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:655a493bac606655db9a47fe94d3d84fc7f3ad766d894197c94ccf0c5408e7d3"}, - {file = "orjson-3.10.11-cp38-none-win32.whl", hash = "sha256:b9546b278c9fb5d45380f4809e11b4dd9844ca7aaf1134024503e134ed226161"}, - {file = "orjson-3.10.11-cp38-none-win_amd64.whl", hash = "sha256:b592597fe551d518f42c5a2eb07422eb475aa8cfdc8c51e6da7054b836b26782"}, - {file = "orjson-3.10.11-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c95f2ecafe709b4e5c733b5e2768ac569bed308623c85806c395d9cca00e08af"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:80c00d4acded0c51c98754fe8218cb49cb854f0f7eb39ea4641b7f71732d2cb7"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:461311b693d3d0a060439aa669c74f3603264d4e7a08faa68c47ae5a863f352d"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52ca832f17d86a78cbab86cdc25f8c13756ebe182b6fc1a97d534051c18a08de"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c57ea78a753812f528178aa2f1c57da633754c91d2124cb28991dab4c79a54"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7fcfc6f7ca046383fb954ba528587e0f9336828b568282b27579c49f8e16aad"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:86b9dd983857970c29e4c71bb3e95ff085c07d3e83e7c46ebe959bac07ebd80b"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:4d83f87582d223e54efb2242a79547611ba4ebae3af8bae1e80fa9a0af83bb7f"}, - {file = "orjson-3.10.11-cp39-none-win32.whl", hash = "sha256:9fd0ad1c129bc9beb1154c2655f177620b5beaf9a11e0d10bac63ef3fce96950"}, - {file = "orjson-3.10.11-cp39-none-win_amd64.whl", hash = "sha256:10f416b2a017c8bd17f325fb9dee1fb5cdd7a54e814284896b7c3f2763faa017"}, - {file = "orjson-3.10.11.tar.gz", hash = "sha256:e35b6d730de6384d5b2dab5fd23f0d76fae8bbc8c353c2f78210aa5fa4beb3ef"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] @@ -558,17 +1237,6 @@ files = [ {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, ] -[[package]] -name = "pastel" -version = "0.2.1" -description = "Bring colors to your terminal." -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -files = [ - {file = "pastel-0.2.1-py2.py3-none-any.whl", hash = "sha256:4349225fcdf6c2bb34d483e523475de5bb04a5c10ef711263452cb37d7dd4364"}, - {file = "pastel-0.2.1.tar.gz", hash = "sha256:e6581ac04e973cac858828c6202c1e1e81fee1dc7de7683f3e1ffe0bfd8a573d"}, -] - [[package]] name = "pluggy" version = "1.5.0" @@ -585,32 +1253,105 @@ dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] [[package]] -name = "poethepoet" -version = "0.24.4" -description = "A task runner that works well with poetry." +name = "propcache" +version = "0.2.1" +description = "Accelerated property cache" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "poethepoet-0.24.4-py3-none-any.whl", hash = "sha256:fb4ea35d7f40fe2081ea917d2e4102e2310fda2cde78974050ca83896e229075"}, - {file = "poethepoet-0.24.4.tar.gz", hash = "sha256:ff4220843a87c888cbcb5312c8905214701d0af60ac7271795baa8369b428fef"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6b3f39a85d671436ee3d12c017f8fdea38509e4f25b28eb25877293c98c243f6"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d51fbe4285d5db5d92a929e3e21536ea3dd43732c5b177c7ef03f918dff9f2"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6445804cf4ec763dc70de65a3b0d9954e868609e83850a47ca4f0cb64bd79fea"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f9479aa06a793c5aeba49ce5c5692ffb51fcd9a7016e017d555d5e2b0045d212"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9631c5e8b5b3a0fda99cb0d29c18133bca1e18aea9effe55adb3da1adef80d3"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3156628250f46a0895f1f36e1d4fbe062a1af8718ec3ebeb746f1d23f0c5dc4d"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b6fb63ae352e13748289f04f37868099e69dba4c2b3e271c46061e82c745634"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:887d9b0a65404929641a9fabb6452b07fe4572b269d901d622d8a34a4e9043b2"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:a96dc1fa45bd8c407a0af03b2d5218392729e1822b0c32e62c5bf7eeb5fb3958"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a7e65eb5c003a303b94aa2c3852ef130230ec79e349632d030e9571b87c4698c"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:999779addc413181912e984b942fbcc951be1f5b3663cd80b2687758f434c583"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:19a0f89a7bb9d8048d9c4370c9c543c396e894c76be5525f5e1ad287f1750ddf"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:1ac2f5fe02fa75f56e1ad473f1175e11f475606ec9bd0be2e78e4734ad575034"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:574faa3b79e8ebac7cb1d7930f51184ba1ccf69adfdec53a12f319a06030a68b"}, + {file = "propcache-0.2.1-cp310-cp310-win32.whl", hash = "sha256:03ff9d3f665769b2a85e6157ac8b439644f2d7fd17615a82fa55739bc97863f4"}, + {file = "propcache-0.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:2d3af2e79991102678f53e0dbf4c35de99b6b8b58f29a27ca0325816364caaba"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ffc3cca89bb438fb9c95c13fc874012f7b9466b89328c3c8b1aa93cdcfadd16"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f174bbd484294ed9fdf09437f889f95807e5f229d5d93588d34e92106fbf6717"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:70693319e0b8fd35dd863e3e29513875eb15c51945bf32519ef52927ca883bc3"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b480c6a4e1138e1aa137c0079b9b6305ec6dcc1098a8ca5196283e8a49df95a9"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d27b84d5880f6d8aa9ae3edb253c59d9f6642ffbb2c889b78b60361eed449787"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:857112b22acd417c40fa4595db2fe28ab900c8c5fe4670c7989b1c0230955465"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf6c4150f8c0e32d241436526f3c3f9cbd34429492abddbada2ffcff506c51af"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66d4cfda1d8ed687daa4bc0274fcfd5267873db9a5bc0418c2da19273040eeb7"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c2f992c07c0fca81655066705beae35fc95a2fa7366467366db627d9f2ee097f"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:4a571d97dbe66ef38e472703067021b1467025ec85707d57e78711c085984e54"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:bb6178c241278d5fe853b3de743087be7f5f4c6f7d6d22a3b524d323eecec505"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:ad1af54a62ffe39cf34db1aa6ed1a1873bd548f6401db39d8e7cd060b9211f82"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e7048abd75fe40712005bcfc06bb44b9dfcd8e101dda2ecf2f5aa46115ad07ca"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:160291c60081f23ee43d44b08a7e5fb76681221a8e10b3139618c5a9a291b84e"}, + {file = "propcache-0.2.1-cp311-cp311-win32.whl", hash = "sha256:819ce3b883b7576ca28da3861c7e1a88afd08cc8c96908e08a3f4dd64a228034"}, + {file = "propcache-0.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:edc9fc7051e3350643ad929df55c451899bb9ae6d24998a949d2e4c87fb596d3"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:081a430aa8d5e8876c6909b67bd2d937bfd531b0382d3fdedb82612c618bc41a"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d2ccec9ac47cf4e04897619c0e0c1a48c54a71bdf045117d3a26f80d38ab1fb0"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:14d86fe14b7e04fa306e0c43cdbeebe6b2c2156a0c9ce56b815faacc193e320d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:049324ee97bb67285b49632132db351b41e77833678432be52bdd0289c0e05e4"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1cd9a1d071158de1cc1c71a26014dcdfa7dd3d5f4f88c298c7f90ad6f27bb46d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:98110aa363f1bb4c073e8dcfaefd3a5cea0f0834c2aab23dda657e4dab2f53b5"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:647894f5ae99c4cf6bb82a1bb3a796f6e06af3caa3d32e26d2350d0e3e3faf24"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bfd3223c15bebe26518d58ccf9a39b93948d3dcb3e57a20480dfdd315356baff"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d71264a80f3fcf512eb4f18f59423fe82d6e346ee97b90625f283df56aee103f"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:e73091191e4280403bde6c9a52a6999d69cdfde498f1fdf629105247599b57ec"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:3935bfa5fede35fb202c4b569bb9c042f337ca4ff7bd540a0aa5e37131659348"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f508b0491767bb1f2b87fdfacaba5f7eddc2f867740ec69ece6d1946d29029a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1672137af7c46662a1c2be1e8dc78cb6d224319aaa40271c9257d886be4363a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b74c261802d3d2b85c9df2dfb2fa81b6f90deeef63c2db9f0e029a3cac50b518"}, + {file = "propcache-0.2.1-cp312-cp312-win32.whl", hash = "sha256:d09c333d36c1409d56a9d29b3a1b800a42c76a57a5a8907eacdbce3f18768246"}, + {file = "propcache-0.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:c214999039d4f2a5b2073ac506bba279945233da8c786e490d411dfc30f855c1"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:aca405706e0b0a44cc6bfd41fbe89919a6a56999157f6de7e182a990c36e37bc"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:12d1083f001ace206fe34b6bdc2cb94be66d57a850866f0b908972f90996b3e9"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d93f3307ad32a27bda2e88ec81134b823c240aa3abb55821a8da553eed8d9439"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba278acf14471d36316159c94a802933d10b6a1e117b8554fe0d0d9b75c9d536"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4e6281aedfca15301c41f74d7005e6e3f4ca143584ba696ac69df4f02f40d629"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b750a8e5a1262434fb1517ddf64b5de58327f1adc3524a5e44c2ca43305eb0b"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf72af5e0fb40e9babf594308911436c8efde3cb5e75b6f206c34ad18be5c052"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b2d0a12018b04f4cb820781ec0dffb5f7c7c1d2a5cd22bff7fb055a2cb19ebce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e800776a79a5aabdb17dcc2346a7d66d0777e942e4cd251defeb084762ecd17d"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:4160d9283bd382fa6c0c2b5e017acc95bc183570cd70968b9202ad6d8fc48dce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:30b43e74f1359353341a7adb783c8f1b1c676367b011709f466f42fda2045e95"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:58791550b27d5488b1bb52bc96328456095d96206a250d28d874fafe11b3dfaf"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:0f022d381747f0dfe27e99d928e31bc51a18b65bb9e481ae0af1380a6725dd1f"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:297878dc9d0a334358f9b608b56d02e72899f3b8499fc6044133f0d319e2ec30"}, + {file = "propcache-0.2.1-cp313-cp313-win32.whl", hash = "sha256:ddfab44e4489bd79bda09d84c430677fc7f0a4939a73d2bba3073036f487a0a6"}, + {file = "propcache-0.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:556fc6c10989f19a179e4321e5d678db8eb2924131e64652a51fe83e4c3db0e1"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:6a9a8c34fb7bb609419a211e59da8887eeca40d300b5ea8e56af98f6fbbb1541"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ae1aa1cd222c6d205853b3013c69cd04515f9d6ab6de4b0603e2e1c33221303e"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:accb6150ce61c9c4b7738d45550806aa2b71c7668c6942f17b0ac182b6142fd4"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5eee736daafa7af6d0a2dc15cc75e05c64f37fc37bafef2e00d77c14171c2097"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f7a31fc1e1bd362874863fdeed71aed92d348f5336fd84f2197ba40c59f061bd"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cba4cfa1052819d16699e1d55d18c92b6e094d4517c41dd231a8b9f87b6fa681"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f089118d584e859c62b3da0892b88a83d611c2033ac410e929cb6754eec0ed16"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:781e65134efaf88feb447e8c97a51772aa75e48b794352f94cb7ea717dedda0d"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:31f5af773530fd3c658b32b6bdc2d0838543de70eb9a2156c03e410f7b0d3aae"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:a7a078f5d37bee6690959c813977da5291b24286e7b962e62a94cec31aa5188b"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:cea7daf9fc7ae6687cf1e2c049752f19f146fdc37c2cc376e7d0032cf4f25347"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:8b3489ff1ed1e8315674d0775dc7d2195fb13ca17b3808721b54dbe9fd020faf"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9403db39be1393618dd80c746cb22ccda168efce239c73af13c3763ef56ffc04"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5d97151bc92d2b2578ff7ce779cdb9174337390a535953cbb9452fb65164c587"}, + {file = "propcache-0.2.1-cp39-cp39-win32.whl", hash = "sha256:9caac6b54914bdf41bcc91e7eb9147d331d29235a7c967c150ef5df6464fd1bb"}, + {file = "propcache-0.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:92fc4500fcb33899b05ba73276dfb684a20d31caa567b7cb5252d48f896a91b1"}, + {file = "propcache-0.2.1-py3-none-any.whl", hash = "sha256:52277518d6aae65536e9cea52d4e7fd2f7a66f4aa2d30ed3f2fcea620ace3c54"}, + {file = "propcache-0.2.1.tar.gz", hash = "sha256:3f77ce728b19cb537714499928fe800c3dda29e8d9428778fc7c186da4c09a64"}, ] -[package.dependencies] -pastel = ">=0.2.1,<0.3.0" -tomli = ">=1.2.2" - -[package.extras] -poetry-plugin = ["poetry (>=1.0,<2.0)"] - [[package]] name = "pydantic" -version = "2.10.1" +version = "2.10.3" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.10.1-py3-none-any.whl", hash = "sha256:a8d20db84de64cf4a7d59e899c2caf0fe9d660c7cfc482528e7020d7dd189a7e"}, - {file = "pydantic-2.10.1.tar.gz", hash = "sha256:a4daca2dc0aa429555e0656d6bf94873a7dc5f54ee42b1f5873d666fb3f35560"}, + {file = "pydantic-2.10.3-py3-none-any.whl", hash = "sha256:be04d85bbc7b65651c5f8e6b9976ed9c6f41782a55524cef079a34a0bb82144d"}, + {file = "pydantic-2.10.3.tar.gz", hash = "sha256:cb5ac360ce894ceacd69c403187900a02c4b20b693a9dd1d643e1effab9eadf9"}, ] [package.dependencies] @@ -962,6 +1703,54 @@ files = [ {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"}, ] +[[package]] +name = "sqlalchemy" +version = "2.0.36" +description = "Database Abstraction Library" +optional = false +python-versions = ">=3.7" +files = [ + {file = "SQLAlchemy-2.0.36-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c245b1fbade9c35e5bd3b64270ab49ce990369018289ecfde3f9c318411aaa07"}, + {file = "SQLAlchemy-2.0.36-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f9511d8dd4a6e9271d07d150fb2f81874a3c8c95e11ff9af3a2dfc35fe42ee44"}, + {file = "SQLAlchemy-2.0.36-cp310-cp310-win32.whl", hash = "sha256:c3f3631693003d8e585d4200730616b78fafd5a01ef8b698f6967da5c605b3fa"}, + {file = "SQLAlchemy-2.0.36-cp310-cp310-win_amd64.whl", hash = "sha256:a86bfab2ef46d63300c0f06936bd6e6c0105faa11d509083ba8f2f9d237fb5b5"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2519f3a5d0517fc159afab1015e54bb81b4406c278749779be57a569d8d1bb0d"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:39769a115f730d683b0eb7b694db9789267bcd027326cccc3125e862eb03bfd8"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-win32.whl", hash = "sha256:66bffbad8d6271bb1cc2f9a4ea4f86f80fe5e2e3e501a5ae2a3dc6a76e604e6f"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-win_amd64.whl", hash = "sha256:23623166bfefe1487d81b698c423f8678e80df8b54614c2bf4b4cfcd7c711959"}, + {file = "SQLAlchemy-2.0.36-py3-none-any.whl", hash = "sha256:fddbe92b4760c6f5d48162aef14824add991aeda8ddadb3c31d56eb15ca69f8e"}, + {file = "sqlalchemy-2.0.36.tar.gz", hash = "sha256:7f2767680b6d2398aea7082e45a774b2b0767b5c8d8ffb9c8b683088ea9b29c5"}, +] + +[package.dependencies] +greenlet = {version = "!=0.4.17", markers = "python_version < \"3.13\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"} +typing-extensions = ">=4.6.0" + +[package.extras] +aiomysql = ["aiomysql (>=0.2.0)", "greenlet (!=0.4.17)"] +aioodbc = ["aioodbc", "greenlet (!=0.4.17)"] +aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"] +asyncio = ["greenlet (!=0.4.17)"] +asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"] +mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5,!=1.1.10)"] +mssql = ["pyodbc"] +mssql-pymssql = ["pymssql"] +mssql-pyodbc = ["pyodbc"] +mypy = ["mypy (>=0.910)"] +mysql = ["mysqlclient (>=1.4.0)"] +mysql-connector = ["mysql-connector-python"] +oracle = ["cx_oracle (>=8)"] +oracle-oracledb = ["oracledb (>=1.0.1)"] +postgresql = ["psycopg2 (>=2.7)"] +postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"] +postgresql-pg8000 = ["pg8000 (>=1.29.1)"] +postgresql-psycopg = ["psycopg (>=3.0.7)"] +postgresql-psycopg2binary = ["psycopg2-binary"] +postgresql-psycopg2cffi = ["psycopg2cffi"] +postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"] +pymysql = ["pymysql"] +sqlcipher = ["sqlcipher3_binary"] + [[package]] name = "sse-starlette" version = "1.8.2" @@ -1014,13 +1803,43 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tomli" -version = "2.1.0" +version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, - {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"}, + {file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"}, + {file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"}, + {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"}, + {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"}, + {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"}, + {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"}, + {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"}, + {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"}, ] [[package]] @@ -1147,10 +1966,106 @@ files = [ [package.extras] watchmedo = ["PyYAML (>=3.10)"] +[[package]] +name = "yarl" +version = "1.18.3" +description = "Yet another URL library" +optional = false +python-versions = ">=3.9" +files = [ + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:602d98f2c2d929f8e697ed274fbadc09902c4025c5a9963bf4e9edfc3ab6f7ed"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c654d5207c78e0bd6d749f6dae1dcbbfde3403ad3a4b11f3c5544d9906969dde"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5094d9206c64181d0f6e76ebd8fb2f8fe274950a63890ee9e0ebfd58bf9d787b"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35098b24e0327fc4ebdc8ffe336cee0a87a700c24ffed13161af80124b7dc8e5"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3236da9272872443f81fedc389bace88408f64f89f75d1bdb2256069a8730ccc"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e2c08cc9b16f4f4bc522771d96734c7901e7ebef70c6c5c35dd0f10845270bcd"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:80316a8bd5109320d38eef8833ccf5f89608c9107d02d2a7f985f98ed6876990"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c1e1cc06da1491e6734f0ea1e6294ce00792193c463350626571c287c9a704db"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fea09ca13323376a2fdfb353a5fa2e59f90cd18d7ca4eaa1fd31f0a8b4f91e62"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e3b9fd71836999aad54084906f8663dffcd2a7fb5cdafd6c37713b2e72be1760"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:757e81cae69244257d125ff31663249b3013b5dc0a8520d73694aed497fb195b"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b1771de9944d875f1b98a745bc547e684b863abf8f8287da8466cf470ef52690"}, + {file = "yarl-1.18.3-cp310-cp310-win32.whl", hash = "sha256:8874027a53e3aea659a6d62751800cf6e63314c160fd607489ba5c2edd753cf6"}, + {file = "yarl-1.18.3-cp310-cp310-win_amd64.whl", hash = "sha256:93b2e109287f93db79210f86deb6b9bbb81ac32fc97236b16f7433db7fc437d8"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8503ad47387b8ebd39cbbbdf0bf113e17330ffd339ba1144074da24c545f0069"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02ddb6756f8f4517a2d5e99d8b2f272488e18dd0bfbc802f31c16c6c20f22193"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:67a283dd2882ac98cc6318384f565bffc751ab564605959df4752d42483ad889"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d980e0325b6eddc81331d3f4551e2a333999fb176fd153e075c6d1c2530aa8a8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b643562c12680b01e17239be267bc306bbc6aac1f34f6444d1bded0c5ce438ca"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c017a3b6df3a1bd45b9fa49a0f54005e53fbcad16633870104b66fa1a30a29d8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75674776d96d7b851b6498f17824ba17849d790a44d282929c42dbb77d4f17ae"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ccaa3a4b521b780a7e771cc336a2dba389a0861592bbce09a476190bb0c8b4b3"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d06d3005e668744e11ed80812e61efd77d70bb7f03e33c1598c301eea20efbb"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:9d41beda9dc97ca9ab0b9888cb71f7539124bc05df02c0cff6e5acc5a19dcc6e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:ba23302c0c61a9999784e73809427c9dbedd79f66a13d84ad1b1943802eaaf59"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:6748dbf9bfa5ba1afcc7556b71cda0d7ce5f24768043a02a58846e4a443d808d"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:0b0cad37311123211dc91eadcb322ef4d4a66008d3e1bdc404808992260e1a0e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0fb2171a4486bb075316ee754c6d8382ea6eb8b399d4ec62fde2b591f879778a"}, + {file = "yarl-1.18.3-cp311-cp311-win32.whl", hash = "sha256:61b1a825a13bef4a5f10b1885245377d3cd0bf87cba068e1d9a88c2ae36880e1"}, + {file = "yarl-1.18.3-cp311-cp311-win_amd64.whl", hash = "sha256:b9d60031cf568c627d028239693fd718025719c02c9f55df0a53e587aab951b5"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1dd4bdd05407ced96fed3d7f25dbbf88d2ffb045a0db60dbc247f5b3c5c25d50"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7c33dd1931a95e5d9a772d0ac5e44cac8957eaf58e3c8da8c1414de7dd27c576"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:25b411eddcfd56a2f0cd6a384e9f4f7aa3efee14b188de13048c25b5e91f1640"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:436c4fc0a4d66b2badc6c5fc5ef4e47bb10e4fd9bf0c79524ac719a01f3607c2"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e35ef8683211db69ffe129a25d5634319a677570ab6b2eba4afa860f54eeaf75"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84b2deecba4a3f1a398df819151eb72d29bfeb3b69abb145a00ddc8d30094512"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e5a1fea0fd4f5bfa7440a47eff01d9822a65b4488f7cff83155a0f31a2ecba"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0e883008013c0e4aef84dcfe2a0b172c4d23c2669412cf5b3371003941f72bb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5a3f356548e34a70b0172d8890006c37be92995f62d95a07b4a42e90fba54272"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ccd17349166b1bee6e529b4add61727d3f55edb7babbe4069b5764c9587a8cc6"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b958ddd075ddba5b09bb0be8a6d9906d2ce933aee81100db289badbeb966f54e"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c7d79f7d9aabd6011004e33b22bc13056a3e3fb54794d138af57f5ee9d9032cb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:4891ed92157e5430874dad17b15eb1fda57627710756c27422200c52d8a4e393"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ce1af883b94304f493698b00d0f006d56aea98aeb49d75ec7d98cd4a777e9285"}, + {file = "yarl-1.18.3-cp312-cp312-win32.whl", hash = "sha256:f91c4803173928a25e1a55b943c81f55b8872f0018be83e3ad4938adffb77dd2"}, + {file = "yarl-1.18.3-cp312-cp312-win_amd64.whl", hash = "sha256:7e2ee16578af3b52ac2f334c3b1f92262f47e02cc6193c598502bd46f5cd1477"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:90adb47ad432332d4f0bc28f83a5963f426ce9a1a8809f5e584e704b82685dcb"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:913829534200eb0f789d45349e55203a091f45c37a2674678744ae52fae23efa"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ef9f7768395923c3039055c14334ba4d926f3baf7b776c923c93d80195624782"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88a19f62ff30117e706ebc9090b8ecc79aeb77d0b1f5ec10d2d27a12bc9f66d0"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e17c9361d46a4d5addf777c6dd5eab0715a7684c2f11b88c67ac37edfba6c482"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a74a13a4c857a84a845505fd2d68e54826a2cd01935a96efb1e9d86c728e186"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41f7ce59d6ee7741af71d82020346af364949314ed3d87553763a2df1829cc58"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f52a265001d830bc425f82ca9eabda94a64a4d753b07d623a9f2863fde532b53"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:82123d0c954dc58db301f5021a01854a85bf1f3bb7d12ae0c01afc414a882ca2"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:2ec9bbba33b2d00999af4631a3397d1fd78290c48e2a3e52d8dd72db3a067ac8"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:fbd6748e8ab9b41171bb95c6142faf068f5ef1511935a0aa07025438dd9a9bc1"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:877d209b6aebeb5b16c42cbb377f5f94d9e556626b1bfff66d7b0d115be88d0a"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:b464c4ab4bfcb41e3bfd3f1c26600d038376c2de3297760dfe064d2cb7ea8e10"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8d39d351e7faf01483cc7ff7c0213c412e38e5a340238826be7e0e4da450fdc8"}, + {file = "yarl-1.18.3-cp313-cp313-win32.whl", hash = "sha256:61ee62ead9b68b9123ec24bc866cbef297dd266175d53296e2db5e7f797f902d"}, + {file = "yarl-1.18.3-cp313-cp313-win_amd64.whl", hash = "sha256:578e281c393af575879990861823ef19d66e2b1d0098414855dd367e234f5b3c"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:61e5e68cb65ac8f547f6b5ef933f510134a6bf31bb178be428994b0cb46c2a04"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:fe57328fbc1bfd0bd0514470ac692630f3901c0ee39052ae47acd1d90a436719"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a440a2a624683108a1b454705ecd7afc1c3438a08e890a1513d468671d90a04e"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:09c7907c8548bcd6ab860e5f513e727c53b4a714f459b084f6580b49fa1b9cee"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b4f6450109834af88cb4cc5ecddfc5380ebb9c228695afc11915a0bf82116789"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9ca04806f3be0ac6d558fffc2fdf8fcef767e0489d2684a21912cc4ed0cd1b8"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77a6e85b90a7641d2e07184df5557132a337f136250caafc9ccaa4a2a998ca2c"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6333c5a377c8e2f5fae35e7b8f145c617b02c939d04110c76f29ee3676b5f9a5"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:0b3c92fa08759dbf12b3a59579a4096ba9af8dd344d9a813fc7f5070d86bbab1"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:4ac515b860c36becb81bb84b667466885096b5fc85596948548b667da3bf9f24"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:045b8482ce9483ada4f3f23b3774f4e1bf4f23a2d5c912ed5170f68efb053318"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:a4bb030cf46a434ec0225bddbebd4b89e6471814ca851abb8696170adb163985"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:54d6921f07555713b9300bee9c50fb46e57e2e639027089b1d795ecd9f7fa910"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1d407181cfa6e70077df3377938c08012d18893f9f20e92f7d2f314a437c30b1"}, + {file = "yarl-1.18.3-cp39-cp39-win32.whl", hash = "sha256:ac36703a585e0929b032fbaab0707b75dc12703766d0b53486eabd5139ebadd5"}, + {file = "yarl-1.18.3-cp39-cp39-win_amd64.whl", hash = "sha256:ba87babd629f8af77f557b61e49e7c7cac36f22f871156b91e10a6e9d4f829e9"}, + {file = "yarl-1.18.3-py3-none-any.whl", hash = "sha256:b57f4f58099328dfb26c6a771d09fb20dbbae81d20cfb66141251ea063bd101b"}, + {file = "yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1"}, +] + +[package.dependencies] +idna = ">=2.0" +multidict = ">=4.0" +propcache = ">=0.2.0" + [extras] serve = [] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "ed6ba14db90499ff27fefaab277bb8b879a48e024f4dabf944d76d8f7375002b" +content-hash = "c666eaa9945394483db2cf56ec2c147869b2fcefb767184c83c4f0e2f211ea2b" diff --git a/libs/cli/pyproject.toml b/libs/cli/pyproject.toml index 004d48b3bb3fb..2e3ee70fea7ab 100644 --- a/libs/cli/pyproject.toml +++ b/libs/cli/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langchain-cli" -version = "0.0.33" +version = "0.0.35" description = "CLI for interacting with LangChain" authors = ["Erick Friis "] readme = "README.md" @@ -25,16 +25,18 @@ langchain = "langchain_cli.cli:app" langchain-cli = "langchain_cli.cli:app" [tool.poetry.group.dev.dependencies] -poethepoet = "^0.24.1" pytest = "^7.4.2" pytest-watch = "^4.2.0" [tool.poetry.group.lint.dependencies] ruff = "^0.5" +mypy = "^1.13.0" [tool.poetry.group.test.dependencies] +langchain = {path = "../langchain", develop = true} [tool.poetry.group.typing.dependencies] +langchain = {path = "../langchain", develop = true} [tool.poetry.group.test_integration.dependencies] @@ -50,22 +52,11 @@ select = [ "T201", # print ] -[tool.poe.tasks] -test = "poetry run pytest tests" -watch = "poetry run ptw" -version = "poetry version --short" -bump = ["_bump_1", "_bump_2"] -lint = ["_lint", "_check_formatting"] -format = ["_format", "_lint_fix"] - -_bump_2.shell = """sed -i "" "/^__version__ =/c\\ \n__version__ = \\"$version\\"\n" langchain_cli/cli.py""" -_bump_2.uses = { version = "version" } - -_bump_1 = "poetry version patch" -_check_formatting = "poetry run ruff format . --diff" -_lint = "poetry run ruff check ." -_format = "poetry run ruff format ." -_lint_fix = "poetry run ruff check . --fix" +[tool.mypy] +exclude = [ + "langchain_cli/integration_template", + "langchain_cli/package_template", +] [build-system] requires = ["poetry-core"] diff --git a/libs/cli/scripts/generate_migrations.py b/libs/cli/scripts/generate_migrations.py index 38c830443c775..11b5a8a6b0ed3 100644 --- a/libs/cli/scripts/generate_migrations.py +++ b/libs/cli/scripts/generate_migrations.py @@ -1,3 +1,4 @@ +# type: ignore """Script to generate migrations for the migration script.""" import json diff --git a/libs/cli/tests/integration_tests/test_compile.py b/libs/cli/tests/integration_tests/test_compile.py new file mode 100644 index 0000000000000..33ecccdfa0fbd --- /dev/null +++ b/libs/cli/tests/integration_tests/test_compile.py @@ -0,0 +1,7 @@ +import pytest + + +@pytest.mark.compile +def test_placeholder() -> None: + """Used for compiling integration tests without running any real tests.""" + pass diff --git a/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py b/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py index 4fbeae295bacf..3cc57112ead53 100644 --- a/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py +++ b/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py @@ -41,6 +41,7 @@ def find_issue(current: Folder, expected: Folder) -> str: return "Unknown" +@pytest.mark.xfail(reason="grit may not be installed in env") def test_command_line(tmp_path: Path) -> None: runner = CliRunner() diff --git a/libs/community/README.md b/libs/community/README.md index 38240d2c9486a..02b1e754764d5 100644 --- a/libs/community/README.md +++ b/libs/community/README.md @@ -13,7 +13,7 @@ pip install langchain-community LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application. -For full documentation see the [API reference](https://api.python.langchain.com/en/stable/community_api_reference.html). +For full documentation see the [API reference](https://python.langchain.com/api_reference/community/index.html). ![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](https://raw.githubusercontent.com/langchain-ai/langchain/e1d113ea84a2edcf4a7709fc5be0e972ea74a5d9/docs/static/svg/langchain_stack_112024.svg "LangChain Framework Overview") diff --git a/libs/community/extended_testing_deps.txt b/libs/community/extended_testing_deps.txt index e599d9353afa5..fc208a71ef21c 100644 --- a/libs/community/extended_testing_deps.txt +++ b/libs/community/extended_testing_deps.txt @@ -46,6 +46,7 @@ motor>=3.3.1,<4 msal>=1.25.0,<2 mwparserfromhell>=0.6.4,<0.7 mwxml>=0.3.3,<0.4 +needle-python>=0.4 networkx>=3.2.1,<4 newspaper3k>=0.2.8,<0.3 numexpr>=2.8.6,<3 @@ -55,7 +56,6 @@ openai<2 openapi-pydantic>=0.3.2,<0.4 oracle-ads>=2.9.1,<3 oracledb>=2.2.0,<3 -outlines[test]>=0.1.0,<0.2 pandas>=2.0.1,<3 pdfminer-six>=20221105,<20240706 pgvector>=0.1.6,<0.2 diff --git a/libs/community/langchain_community/adapters/openai.py b/libs/community/langchain_community/adapters/openai.py index 673e5fa567be8..cc40b5811220c 100644 --- a/libs/community/langchain_community/adapters/openai.py +++ b/libs/community/langchain_community/adapters/openai.py @@ -91,6 +91,8 @@ def convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage: additional_kwargs["function_call"] = dict(function_call) if tool_calls := _dict.get("tool_calls"): additional_kwargs["tool_calls"] = tool_calls + if context := _dict.get("context"): + additional_kwargs["context"] = context return AIMessage(content=content, additional_kwargs=additional_kwargs) elif role == "system": return SystemMessage(content=_dict.get("content", "")) @@ -135,6 +137,11 @@ def convert_message_to_dict(message: BaseMessage) -> dict: # If tool calls only, content is None not empty string if message_dict["content"] == "": message_dict["content"] = None + if "context" in message.additional_kwargs: + message_dict["context"] = message.additional_kwargs["context"] + # If context only, content is None not empty string + if message_dict["content"] == "": + message_dict["content"] = None elif isinstance(message, SystemMessage): message_dict = {"role": "system", "content": message.content} elif isinstance(message, FunctionMessage): diff --git a/libs/community/langchain_community/agent_toolkits/sql/base.py b/libs/community/langchain_community/agent_toolkits/sql/base.py index a738b0b948254..5cacc0f9f0a53 100644 --- a/libs/community/langchain_community/agent_toolkits/sql/base.py +++ b/libs/community/langchain_community/agent_toolkits/sql/base.py @@ -107,13 +107,13 @@ def create_sql_agent( .. code-block:: python - from langchain_openai import ChatOpenAI - from langchain_community.agent_toolkits import create_sql_agent - from langchain_community.utilities import SQLDatabase + from langchain_openai import ChatOpenAI + from langchain_community.agent_toolkits import create_sql_agent + from langchain_community.utilities import SQLDatabase - db = SQLDatabase.from_uri("sqlite:///Chinook.db") - llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0) - agent_executor = create_sql_agent(llm, db=db, agent_type="tool-calling", verbose=True) + db = SQLDatabase.from_uri("sqlite:///Chinook.db") + llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0) + agent_executor = create_sql_agent(llm, db=db, agent_type="tool-calling", verbose=True) """ # noqa: E501 from langchain.agents import ( diff --git a/libs/community/langchain_community/agent_toolkits/sql/toolkit.py b/libs/community/langchain_community/agent_toolkits/sql/toolkit.py index 6920349cd3f29..75566c96b9307 100644 --- a/libs/community/langchain_community/agent_toolkits/sql/toolkit.py +++ b/libs/community/langchain_community/agent_toolkits/sql/toolkit.py @@ -2,6 +2,8 @@ from typing import List +from langchain_core.caches import BaseCache as BaseCache +from langchain_core.callbacks import Callbacks as Callbacks from langchain_core.language_models import BaseLanguageModel from langchain_core.tools import BaseTool from langchain_core.tools.base import BaseToolkit @@ -129,3 +131,6 @@ def get_tools(self) -> List[BaseTool]: def get_context(self) -> dict: """Return db context that you may want in agent prompt.""" return self.db.get_context() + + +SQLDatabaseToolkit.model_rebuild() diff --git a/libs/community/langchain_community/agents/openai_assistant/base.py b/libs/community/langchain_community/agents/openai_assistant/base.py index 971e8ba8381ed..f9006f66ca5ab 100644 --- a/libs/community/langchain_community/agents/openai_assistant/base.py +++ b/libs/community/langchain_community/agents/openai_assistant/base.py @@ -543,11 +543,16 @@ def _create_run(self, input: dict) -> Any: Returns: Any: The created run object. """ - params = { - k: v - for k, v in input.items() - if k in ("instructions", "model", "tools", "tool_resources", "run_metadata") - } + allowed_assistant_params = ( + "instructions", + "model", + "tools", + "tool_resources", + "run_metadata", + "truncation_strategy", + "max_prompt_tokens", + ) + params = {k: v for k, v in input.items() if k in allowed_assistant_params} return self.client.beta.threads.runs.create( input["thread_id"], assistant_id=self.assistant_id, diff --git a/libs/community/langchain_community/callbacks/openai_info.py b/libs/community/langchain_community/callbacks/openai_info.py index 9e2c070ccd2bf..4976f6331f11d 100644 --- a/libs/community/langchain_community/callbacks/openai_info.py +++ b/libs/community/langchain_community/callbacks/openai_info.py @@ -30,10 +30,12 @@ "gpt-4o": 0.0025, "gpt-4o-2024-05-13": 0.005, "gpt-4o-2024-08-06": 0.0025, + "gpt-4o-2024-11-20": 0.0025, # GPT-4o output "gpt-4o-completion": 0.01, "gpt-4o-2024-05-13-completion": 0.015, "gpt-4o-2024-08-06-completion": 0.01, + "gpt-4o-2024-11-20-completion": 0.01, # GPT-4 input "gpt-4": 0.03, "gpt-4-0314": 0.03, diff --git a/libs/community/langchain_community/chains/graph_qa/cypher.py b/libs/community/langchain_community/chains/graph_qa/cypher.py index 91a5ba606621b..760ce66731206 100644 --- a/libs/community/langchain_community/chains/graph_qa/cypher.py +++ b/libs/community/langchain_community/chains/graph_qa/cypher.py @@ -7,6 +7,7 @@ from langchain.chains.base import Chain from langchain.chains.llm import LLMChain +from langchain_core._api.deprecation import deprecated from langchain_core.callbacks import CallbackManagerForChainRun from langchain_core.language_models import BaseLanguageModel from langchain_core.messages import ( @@ -44,6 +45,11 @@ """ +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.chains.graph_qa.cypher.extract_cypher", +) def extract_cypher(text: str) -> str: """Extract Cypher code from a text. @@ -62,6 +68,11 @@ def extract_cypher(text: str) -> str: return matches[0] if matches else text +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.chains.graph_qa.cypher.construct_schema", +) def construct_schema( structured_schema: Dict[str, Any], include_types: List[str], @@ -124,6 +135,11 @@ def filter_func(x: str) -> bool: ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.chains.graph_qa.cypher.get_function_response", +) def get_function_response( question: str, context: List[Dict[str, Any]] ) -> List[BaseMessage]: @@ -149,6 +165,11 @@ def get_function_response( return messages +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.GraphCypherQAChain", +) class GraphCypherQAChain(Chain): """Chain for question-answering against a graph by generating Cypher statements. diff --git a/libs/community/langchain_community/chains/graph_qa/cypher_utils.py b/libs/community/langchain_community/chains/graph_qa/cypher_utils.py index c123cac9b52f3..4d8c7c45572fb 100644 --- a/libs/community/langchain_community/chains/graph_qa/cypher_utils.py +++ b/libs/community/langchain_community/chains/graph_qa/cypher_utils.py @@ -2,9 +2,16 @@ from collections import namedtuple from typing import Any, Dict, List, Optional, Tuple +from langchain_core._api.deprecation import deprecated + Schema = namedtuple("Schema", ["left_node", "relation", "right_node"]) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.chains.graph_qa.cypher_utils.CypherQueryCorrector", +) class CypherQueryCorrector: """ Used to correct relationship direction in generated Cypher statements. diff --git a/libs/community/langchain_community/chains/pebblo_retrieval/enforcement_filters.py b/libs/community/langchain_community/chains/pebblo_retrieval/enforcement_filters.py index 570cbdfa783f8..579b86acb0ebc 100644 --- a/libs/community/langchain_community/chains/pebblo_retrieval/enforcement_filters.py +++ b/libs/community/langchain_community/chains/pebblo_retrieval/enforcement_filters.py @@ -27,8 +27,9 @@ PINECONE = "Pinecone" QDRANT = "Qdrant" PGVECTOR = "PGVector" +PINECONE_VECTOR_STORE = "PineconeVectorStore" -SUPPORTED_VECTORSTORES = {PINECONE, QDRANT, PGVECTOR} +SUPPORTED_VECTORSTORES = {PINECONE, QDRANT, PGVECTOR, PINECONE_VECTOR_STORE} def clear_enforcement_filters(retriever: VectorStoreRetriever) -> None: @@ -505,7 +506,7 @@ def _set_identity_enforcement_filter( of the retriever based on the type of the vectorstore. """ search_kwargs = retriever.search_kwargs - if retriever.vectorstore.__class__.__name__ == PINECONE: + if retriever.vectorstore.__class__.__name__ in [PINECONE, PINECONE_VECTOR_STORE]: _apply_pinecone_authorization_filter(search_kwargs, auth_context) elif retriever.vectorstore.__class__.__name__ == QDRANT: _apply_qdrant_authorization_filter(search_kwargs, auth_context) diff --git a/libs/community/langchain_community/chat_message_histories/neo4j.py b/libs/community/langchain_community/chat_message_histories/neo4j.py index aeca69cdad8c0..5a054c706de25 100644 --- a/libs/community/langchain_community/chat_message_histories/neo4j.py +++ b/libs/community/langchain_community/chat_message_histories/neo4j.py @@ -1,5 +1,6 @@ from typing import List, Optional, Union +from langchain_core._api.deprecation import deprecated from langchain_core.chat_history import BaseChatMessageHistory from langchain_core.messages import BaseMessage, messages_from_dict from langchain_core.utils import get_from_dict_or_env @@ -7,6 +8,11 @@ from langchain_community.graphs import Neo4jGraph +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.Neo4jChatMessageHistory", +) class Neo4jChatMessageHistory(BaseChatMessageHistory): """Chat message history stored in a Neo4j database.""" diff --git a/libs/community/langchain_community/chat_models/anyscale.py b/libs/community/langchain_community/chat_models/anyscale.py index e6f70b359f1eb..b5db8bbeb0caa 100644 --- a/libs/community/langchain_community/chat_models/anyscale.py +++ b/libs/community/langchain_community/chat_models/anyscale.py @@ -72,7 +72,7 @@ def lc_secrets(self) -> Dict[str, str]: def is_lc_serializable(cls) -> bool: return False - anyscale_api_key: SecretStr = Field(default=None) + anyscale_api_key: SecretStr = Field(default=SecretStr("")) """AnyScale Endpoints API keys.""" model_name: str = Field(default=DEFAULT_MODEL, alias="model") """Model name to use.""" diff --git a/libs/community/langchain_community/chat_models/google_palm.py b/libs/community/langchain_community/chat_models/google_palm.py index 77038256c7d82..e9bd5928a040d 100644 --- a/libs/community/langchain_community/chat_models/google_palm.py +++ b/libs/community/langchain_community/chat_models/google_palm.py @@ -219,7 +219,7 @@ class ChatGooglePalm(BaseChatModel, BaseModel): To use you must have the google.generativeai Python package installed and either: - 1. The ``GOOGLE_API_KEY``` environment variable set with your API key, or + 1. The ``GOOGLE_API_KEY`` environment variable set with your API key, or 2. Pass your API key using the google_api_key kwarg to the ChatGoogle constructor. diff --git a/libs/community/langchain_community/chat_models/gpt_router.py b/libs/community/langchain_community/chat_models/gpt_router.py index c833b8e42404f..395fb80c01e30 100644 --- a/libs/community/langchain_community/chat_models/gpt_router.py +++ b/libs/community/langchain_community/chat_models/gpt_router.py @@ -152,7 +152,7 @@ class GPTRouter(BaseChatModel): client: Any = Field(default=None, exclude=True) #: :meta private: models_priority_list: List[GPTRouterModel] = Field(min_length=1) - gpt_router_api_base: str = Field(default=None) + gpt_router_api_base: str = Field(default="") """WriteSonic GPTRouter custom endpoint""" gpt_router_api_key: Optional[SecretStr] = None """WriteSonic GPTRouter API Key""" diff --git a/libs/community/langchain_community/chat_models/kinetica.py b/libs/community/langchain_community/chat_models/kinetica.py index e4a44f8d6a0fd..2af8b33715d41 100644 --- a/libs/community/langchain_community/chat_models/kinetica.py +++ b/libs/community/langchain_community/chat_models/kinetica.py @@ -38,7 +38,7 @@ class _KdtSuggestContext(BaseModel): table: Optional[str] = Field(default=None, title="Name of table") description: Optional[str] = Field(default=None, title="Table description") - columns: List[str] = Field(default=None, title="Table columns list") + columns: List[str] = Field(default=[], title="Table columns list") rules: Optional[List[str]] = Field( default=None, title="Rules that apply to the table." ) @@ -121,7 +121,7 @@ class _KdtoSuggestRequest(BaseModel): class _KdtMessage(BaseModel): """pydantic API response type""" - role: str = Field(default=None, title="One of [user|assistant|system]") + role: str = Field(default="", title="One of [user|assistant|system]") content: str @@ -129,7 +129,7 @@ class _KdtChoice(BaseModel): """pydantic API response type""" index: int - message: _KdtMessage = Field(default=None, title="The generated SQL") + message: Optional[_KdtMessage] = Field(default=None, title="The generated SQL") finish_reason: str @@ -150,7 +150,7 @@ class _KdtSqlResponse(BaseModel): model: str choices: List[_KdtChoice] usage: _KdtUsage - prompt: str = Field(default=None, title="The input question") + prompt: str = Field(default="", title="The input question") class _KdtCompletionResponse(BaseModel): @@ -376,9 +376,8 @@ def _generate( dict_messages = [self._convert_message_to_dict(m) for m in messages] sql_response = self._submit_completion(dict_messages) - response_message = sql_response.choices[0].message - # generated_dict = response_message.model_dump() # pydantic v2 - generated_dict = response_message.dict() + response_message = cast(_KdtMessage, sql_response.choices[0].message) + generated_dict = response_message.model_dump() generated_message = self._convert_message_from_dict(generated_dict) @@ -539,7 +538,7 @@ class KineticaSqlResponse(BaseModel): the generated SQL and related Pandas Dataframe fetched from the database. """ - sql: str = Field(default=None) + sql: str = Field(default="") """The generated SQL.""" # dataframe: "pd.DataFrame" = Field(default=None) diff --git a/libs/community/langchain_community/chat_models/litellm.py b/libs/community/langchain_community/chat_models/litellm.py index d6c9557339857..83c3020910155 100644 --- a/libs/community/langchain_community/chat_models/litellm.py +++ b/libs/community/langchain_community/chat_models/litellm.py @@ -11,6 +11,7 @@ Dict, Iterator, List, + Literal, Mapping, Optional, Sequence, @@ -212,6 +213,33 @@ def _convert_message_to_dict(message: BaseMessage) -> dict: return message_dict +_OPENAI_MODELS = [ + "o1-mini", + "o1-preview", + "gpt-4o-mini", + "gpt-4o-mini-2024-07-18", + "gpt-4o", + "gpt-4o-2024-08-06", + "gpt-4o-2024-05-13", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4-0125-preview", + "gpt-4-1106-preview", + "gpt-3.5-turbo-1106", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0301", + "gpt-3.5-turbo-0613", + "gpt-3.5-turbo-16k", + "gpt-3.5-turbo-16k-0613", + "gpt-4", + "gpt-4-0314", + "gpt-4-0613", + "gpt-4-32k", + "gpt-4-32k-0314", + "gpt-4-32k-0613", +] + + class ChatLiteLLM(BaseChatModel): """Chat model that uses the LiteLLM API.""" @@ -465,6 +493,9 @@ async def _agenerate( def bind_tools( self, tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]], + tool_choice: Optional[ + Union[dict, str, Literal["auto", "none", "required", "any"], bool] + ] = None, **kwargs: Any, ) -> Runnable[LanguageModelInput, BaseMessage]: """Bind tool-like objects to this chat model. @@ -476,17 +507,47 @@ def bind_tools( Can be a dictionary, pydantic model, callable, or BaseTool. Pydantic models, callables, and BaseTools will be automatically converted to their schema dictionary representation. - tool_choice: Which tool to require the model to call. - Must be the name of the single provided function or - "auto" to automatically determine which function to call - (if any), or a dict of the form: - {"type": "function", "function": {"name": <>}}. + tool_choice: Which tool to require the model to call. Options are: + - str of the form ``"<>"``: calls <> tool. + - ``"auto"``: + automatically selects a tool (including no tool). + - ``"none"``: + does not call a tool. + - ``"any"`` or ``"required"`` or ``True``: + forces least one tool to be called. + - dict of the form: + ``{"type": "function", "function": {"name": <>}}`` + - ``False`` or ``None``: no effect **kwargs: Any additional parameters to pass to the :class:`~langchain.runnable.Runnable` constructor. """ formatted_tools = [convert_to_openai_tool(tool) for tool in tools] - return super().bind(tools=formatted_tools, **kwargs) + + # In case of openai if tool_choice is `any` or if bool has been provided we + # change it to `required` as that is suppored by openai. + if ( + (self.model is not None and "azure" in self.model) + or (self.model_name is not None and "azure" in self.model_name) + or (self.model is not None and self.model in _OPENAI_MODELS) + or (self.model_name is not None and self.model_name in _OPENAI_MODELS) + ) and (tool_choice == "any" or isinstance(tool_choice, bool)): + tool_choice = "required" + # If tool_choice is bool apart from openai we make it `any` + elif isinstance(tool_choice, bool): + tool_choice = "any" + elif isinstance(tool_choice, dict): + tool_names = [ + formatted_tool["function"]["name"] for formatted_tool in formatted_tools + ] + if not any( + tool_name == tool_choice["function"]["name"] for tool_name in tool_names + ): + raise ValueError( + f"Tool choice {tool_choice} was specified, but the only " + f"provided tools were {tool_names}." + ) + return super().bind(tools=formatted_tools, tool_choice=tool_choice, **kwargs) @property def _identifying_params(self) -> Dict[str, Any]: diff --git a/libs/community/langchain_community/chat_models/moonshot.py b/libs/community/langchain_community/chat_models/moonshot.py index 7290c52b76e8b..68f8fdc5a5a28 100644 --- a/libs/community/langchain_community/chat_models/moonshot.py +++ b/libs/community/langchain_community/chat_models/moonshot.py @@ -13,21 +13,142 @@ class MoonshotChat(MoonshotCommon, ChatOpenAI): # type: ignore[misc, override, override] - """Moonshot large language models. + """Moonshot chat model integration. - To use, you should have the ``openai`` python package installed, and the - environment variable ``MOONSHOT_API_KEY`` set with your API key. - (Moonshot's chat API is compatible with OpenAI's SDK.) + Setup: + Install ``openai`` and set environment variables ``MOONSHOT_API_KEY``. - Referenced from https://platform.moonshot.cn/docs + .. code-block:: bash - Example: + pip install openai + export MOONSHOT_API_KEY="your-api-key" + + Key init args — completion params: + model: str + Name of Moonshot model to use. + temperature: float + Sampling temperature. + max_tokens: Optional[int] + Max number of tokens to generate. + + Key init args — client params: + api_key: Optional[str] + Moonshot API KEY. If not passed in will be read from env var MOONSHOT_API_KEY. + api_base: Optional[str] + Base URL for API requests. + + See full list of supported init args and their descriptions in the params section. + + Instantiate: + .. code-block:: python + + from langchain_community.chat_models import MoonshotChat + + chat = MoonshotChat( + temperature=0.5, + api_key="your-api-key", + model="moonshot-v1-8k", + # api_base="...", + # other params... + ) + + Invoke: + .. code-block:: python + + messages = [ + ("system", "你是一名专业的翻译家，可以将用户的中文翻译为英文。"), + ("human", "我喜欢编程。"), + ] + chat.invoke(messages) + + .. code-block:: python + + AIMessage( + content='I like programming.', + additional_kwargs={}, + response_metadata={ + 'token_usage': { + 'completion_tokens': 5, + 'prompt_tokens': 27, + 'total_tokens': 32 + }, + 'model_name': 'moonshot-v1-8k', + 'system_fingerprint': None, + 'finish_reason': 'stop', + 'logprobs': None + }, + id='run-71c03f4e-6628-41d5-beb6-d2559ae68266-0' + ) + + Stream: .. code-block:: python - from langchain_community.chat_models.moonshot import MoonshotChat + for chunk in chat.stream(messages): + print(chunk) + + .. code-block:: python + + content='' additional_kwargs={} response_metadata={} id='run-80d77096-8b83-4c39-a84d-71d9c746da92' + content='I' additional_kwargs={} response_metadata={} id='run-80d77096-8b83-4c39-a84d-71d9c746da92' + content=' like' additional_kwargs={} response_metadata={} id='run-80d77096-8b83-4c39-a84d-71d9c746da92' + content=' programming' additional_kwargs={} response_metadata={} id='run-80d77096-8b83-4c39-a84d-71d9c746da92' + content='.' additional_kwargs={} response_metadata={} id='run-80d77096-8b83-4c39-a84d-71d9c746da92' + content='' additional_kwargs={} response_metadata={'finish_reason': 'stop'} id='run-80d77096-8b83-4c39-a84d-71d9c746da92' + + .. code-block:: python + + stream = chat.stream(messages) + full = next(stream) + for chunk in stream: + full += chunk + full + + .. code-block:: python + + AIMessageChunk( + content='I like programming.', + additional_kwargs={}, + response_metadata={'finish_reason': 'stop'}, + id='run-10c80976-7aa5-4ff7-ba3e-1251665557ef' + ) + + Async: + .. code-block:: python + + await chat.ainvoke(messages) + + # stream: + # async for chunk in chat.astream(messages): + # print(chunk) + + # batch: + # await chat.abatch([messages]) + + .. code-block:: python + + [AIMessage(content='I like programming.', additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 5, 'prompt_tokens': 27, 'total_tokens': 32}, 'model_name': 'moonshot-v1-8k', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-2938b005-9204-4b9f-b273-1c3272fce9e5-0')] + + Response metadata + .. code-block:: python + + ai_msg = chat.invoke(messages) + ai_msg.response_metadata + + .. code-block:: python - moonshot = MoonshotChat(model="moonshot-v1-8k") - """ + { + 'token_usage': { + 'completion_tokens': 5, + 'prompt_tokens': 27, + 'total_tokens': 32 + }, + 'model_name': 'moonshot-v1-8k', + 'system_fingerprint': None, + 'finish_reason': 'stop', + 'logprobs': None + } + + """ # noqa: E501 @pre_init def validate_environment(cls, values: Dict) -> Dict: diff --git a/libs/community/langchain_community/chat_models/naver.py b/libs/community/langchain_community/chat_models/naver.py index c54b4a0d68678..2df6ad1a4f25f 100644 --- a/libs/community/langchain_community/chat_models/naver.py +++ b/libs/community/langchain_community/chat_models/naver.py @@ -175,8 +175,8 @@ class ChatClovaX(BaseChatModel): model.invoke([HumanMessage(content="Come up with 10 names for a song about parrots.")]) """ # noqa: E501 - client: httpx.Client = Field(default=None) #: :meta private: - async_client: httpx.AsyncClient = Field(default=None) #: :meta private: + client: Optional[httpx.Client] = Field(default=None) #: :meta private: + async_client: Optional[httpx.AsyncClient] = Field(default=None) #: :meta private: model_name: str = Field( default="HCX-003", @@ -197,7 +197,7 @@ class ChatClovaX(BaseChatModel): ncp_apigw_api_key: Optional[SecretStr] = Field(default=None, alias="apigw_api_key") """Automatically inferred from env are `NCP_APIGW_API_KEY` if not provided.""" - base_url: str = Field(default=None, alias="base_url") + base_url: str = Field(default="", alias="base_url") """ Automatically inferred from env are `NCP_CLOVASTUDIO_API_BASE_URL` if not provided. """ @@ -356,11 +356,12 @@ def _completion_with_retry(self, **kwargs: Any) -> Any: kwargs["stream"] = False stream = kwargs["stream"] + client = cast(httpx.Client, self.client) if stream: def iter_sse() -> Iterator[ServerSentEvent]: with connect_sse( - self.client, "POST", self._api_url, json=kwargs + client, "POST", self._api_url, json=kwargs ) as event_source: _raise_on_error(event_source.response) for sse in event_source.iter_sse(): @@ -376,7 +377,7 @@ def iter_sse() -> Iterator[ServerSentEvent]: return iter_sse() else: - response = self.client.post(url=self._api_url, json=kwargs) + response = client.post(url=self._api_url, json=kwargs) _raise_on_error(response) return response.json() @@ -395,13 +396,14 @@ async def _completion_with_retry(**kwargs: Any) -> Any: if "stream" not in kwargs: kwargs["stream"] = False stream = kwargs["stream"] + async_client = cast(httpx.AsyncClient, self.async_client) if stream: event_source = aconnect_sse( - self.async_client, "POST", self._api_url, json=kwargs + async_client, "POST", self._api_url, json=kwargs ) return _aiter_sse(event_source) else: - response = await self.async_client.post(url=self._api_url, json=kwargs) + response = await async_client.post(url=self._api_url, json=kwargs) await _araise_on_error(response) return response.json() diff --git a/libs/community/langchain_community/chat_models/octoai.py b/libs/community/langchain_community/chat_models/octoai.py index 4f7120c2c8398..7087748729762 100644 --- a/libs/community/langchain_community/chat_models/octoai.py +++ b/libs/community/langchain_community/chat_models/octoai.py @@ -46,7 +46,7 @@ class ChatOctoAI(ChatOpenAI): """ octoai_api_base: str = Field(default=DEFAULT_API_BASE) - octoai_api_token: SecretStr = Field(default=None, alias="api_key") + octoai_api_token: SecretStr = Field(default=SecretStr(""), alias="api_key") model_name: str = Field(default=DEFAULT_MODEL, alias="model") @property diff --git a/libs/community/langchain_community/chat_models/perplexity.py b/libs/community/langchain_community/chat_models/perplexity.py index 88547c67d29db..ce415dd59cbd5 100644 --- a/libs/community/langchain_community/chat_models/perplexity.py +++ b/libs/community/langchain_community/chat_models/perplexity.py @@ -261,7 +261,10 @@ def _generate( response = self.client.chat.completions.create( model=params["model"], messages=message_dicts ) - message = AIMessage(content=response.choices[0].message.content) + message = AIMessage( + content=response.choices[0].message.content, + additional_kwargs={"citations": response.citations}, + ) return ChatResult(generations=[ChatGeneration(message=message)]) @property diff --git a/libs/community/langchain_community/chat_models/sambanova.py b/libs/community/langchain_community/chat_models/sambanova.py index 358650a892e9b..fb43c7c86a9e8 100644 --- a/libs/community/langchain_community/chat_models/sambanova.py +++ b/libs/community/langchain_community/chat_models/sambanova.py @@ -256,7 +256,7 @@ class Joke(BaseModel): sambanova_url: str = Field(default="") """SambaNova Cloud Url""" - sambanova_api_key: SecretStr = Field(default="") + sambanova_api_key: SecretStr = Field(default=SecretStr("")) """SambaNova Cloud api key""" model: str = Field(default="Meta-Llama-3.1-8B-Instruct") @@ -1072,7 +1072,7 @@ class ChatSambaStudio(BaseChatModel): sambastudio_url: str = Field(default="") """SambaStudio Url""" - sambastudio_api_key: SecretStr = Field(default="") + sambastudio_api_key: SecretStr = Field(default=SecretStr("")) """SambaStudio api key""" base_url: str = Field(default="", exclude=True) diff --git a/libs/community/langchain_community/chat_models/writer.py b/libs/community/langchain_community/chat_models/writer.py index 945b9d8b0b6d2..4101b6e23eb35 100644 --- a/libs/community/langchain_community/chat_models/writer.py +++ b/libs/community/langchain_community/chat_models/writer.py @@ -2,6 +2,7 @@ from __future__ import annotations +import json import logging from typing import ( Any, @@ -11,7 +12,6 @@ Iterator, List, Literal, - Mapping, Optional, Sequence, Tuple, @@ -26,8 +26,6 @@ from langchain_core.language_models import LanguageModelInput from langchain_core.language_models.chat_models import ( BaseChatModel, - agenerate_from_stream, - generate_from_stream, ) from langchain_core.messages import ( AIMessage, @@ -40,99 +38,49 @@ ) from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult from langchain_core.runnables import Runnable +from langchain_core.utils import get_from_dict_or_env from langchain_core.utils.function_calling import convert_to_openai_tool -from pydantic import BaseModel, ConfigDict, Field, SecretStr +from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator logger = logging.getLogger(__name__) -def _convert_message_to_dict(message: BaseMessage) -> dict: - """Convert a LangChain message to a Writer message dict.""" - message_dict = {"role": "", "content": message.content} - - if isinstance(message, ChatMessage): - message_dict["role"] = message.role - elif isinstance(message, HumanMessage): - message_dict["role"] = "user" - elif isinstance(message, AIMessage): - message_dict["role"] = "assistant" - if message.tool_calls: - message_dict["tool_calls"] = [ - { - "id": tool["id"], - "type": "function", - "function": {"name": tool["name"], "arguments": tool["args"]}, - } - for tool in message.tool_calls - ] - elif isinstance(message, SystemMessage): - message_dict["role"] = "system" - elif isinstance(message, ToolMessage): - message_dict["role"] = "tool" - message_dict["tool_call_id"] = message.tool_call_id - else: - raise ValueError(f"Got unknown message type: {type(message)}") - - if message.name: - message_dict["name"] = message.name - - return message_dict - - -def _convert_dict_to_message(response_dict: Dict[str, Any]) -> BaseMessage: - """Convert a Writer message dict to a LangChain message.""" - role = response_dict["role"] - content = response_dict.get("content", "") - - if role == "user": - return HumanMessage(content=content) - elif role == "assistant": - additional_kwargs = {} - if tool_calls := response_dict.get("tool_calls"): - additional_kwargs["tool_calls"] = tool_calls - return AIMessageChunk(content=content, additional_kwargs=additional_kwargs) - elif role == "system": - return SystemMessage(content=content) - elif role == "tool": - return ToolMessage( - content=content, - tool_call_id=response_dict["tool_call_id"], - name=response_dict.get("name"), - ) - else: - return ChatMessage(content=content, role=role) - - class ChatWriter(BaseChatModel): """Writer chat model. To use, you should have the ``writer-sdk`` Python package installed, and the - environment variable ``WRITER_API_KEY`` set with your API key. + environment variable ``WRITER_API_KEY`` set with your API key or pass 'api_key' + init param. Example: .. code-block:: python from langchain_community.chat_models import ChatWriter - chat = ChatWriter(model="palmyra-x-004") + chat = ChatWriter( + api_key="your key" + model="palmyra-x-004" + ) """ client: Any = Field(default=None, exclude=True) #: :meta private: async_client: Any = Field(default=None, exclude=True) #: :meta private: + + api_key: Optional[SecretStr] = Field(default=None) + """Writer API key.""" + model_name: str = Field(default="palmyra-x-004", alias="model") """Model name to use.""" + temperature: float = 0.7 """What sampling temperature to use.""" + model_kwargs: Dict[str, Any] = Field(default_factory=dict) """Holds any model parameters valid for `create` call not explicitly specified.""" - writer_api_key: Optional[SecretStr] = Field(default=None, alias="api_key") - """Writer API key.""" - writer_api_base: Optional[str] = Field(default=None, alias="base_url") - """Base URL for API requests.""" - streaming: bool = False - """Whether to stream the results or not.""" + n: int = 1 """Number of chat completions to generate for each prompt.""" + max_tokens: Optional[int] = None """Maximum number of tokens to generate.""" @@ -149,37 +97,159 @@ def _identifying_params(self) -> Dict[str, Any]: return { "model_name": self.model_name, "temperature": self.temperature, - "streaming": self.streaming, **self.model_kwargs, } - def _create_chat_result(self, response: Mapping[str, Any]) -> ChatResult: + @property + def _default_params(self) -> Dict[str, Any]: + """Get the default parameters for calling Writer API.""" + return { + "model": self.model_name, + "temperature": self.temperature, + "n": self.n, + "max_tokens": self.max_tokens, + **self.model_kwargs, + } + + @model_validator(mode="before") + @classmethod + def validate_environment(cls, values: Dict) -> Any: + """Validates that api key is passed and creates Writer clients.""" + try: + from writerai import AsyncClient, Client + except ImportError as e: + raise ImportError( + "Could not import writerai python package. " + "Please install it with `pip install writerai`." + ) from e + + if not values.get("client"): + values.update( + { + "client": Client( + api_key=get_from_dict_or_env( + values, "api_key", "WRITER_API_KEY" + ) + ) + } + ) + + if not values.get("async_client"): + values.update( + { + "async_client": AsyncClient( + api_key=get_from_dict_or_env( + values, "api_key", "WRITER_API_KEY" + ) + ) + } + ) + + if not ( + type(values.get("client")) is Client + and type(values.get("async_client")) is AsyncClient + ): + raise ValueError( + "'client' attribute must be with type 'Client' and " + "'async_client' must be with type 'AsyncClient' from 'writerai' package" + ) + + return values + + def _create_chat_result(self, response: Any) -> ChatResult: generations = [] - for choice in response["choices"]: - message = _convert_dict_to_message(choice["message"]) + for choice in response.choices: + message = self._convert_writer_to_langchain(choice.message) gen = ChatGeneration( message=message, - generation_info=dict(finish_reason=choice.get("finish_reason")), + generation_info=dict(finish_reason=choice.finish_reason), ) generations.append(gen) - token_usage = response.get("usage", {}) + token_usage = {} + + if response.usage: + token_usage = response.usage.__dict__ llm_output = { "token_usage": token_usage, "model_name": self.model_name, - "system_fingerprint": response.get("system_fingerprint", ""), + "system_fingerprint": response.system_fingerprint, } return ChatResult(generations=generations, llm_output=llm_output) - def _convert_messages_to_dicts( + @staticmethod + def _convert_langchain_to_writer(message: BaseMessage) -> dict: + """Convert a LangChain message to a Writer message dict.""" + message_dict = {"role": "", "content": message.content} + + if isinstance(message, ChatMessage): + message_dict["role"] = message.role + elif isinstance(message, HumanMessage): + message_dict["role"] = "user" + elif isinstance(message, AIMessage): + message_dict["role"] = "assistant" + if message.tool_calls: + message_dict["tool_calls"] = [ + { + "id": tool["id"], + "type": "function", + "function": {"name": tool["name"], "arguments": tool["args"]}, + } + for tool in message.tool_calls + ] + elif isinstance(message, SystemMessage): + message_dict["role"] = "system" + elif isinstance(message, ToolMessage): + message_dict["role"] = "tool" + message_dict["tool_call_id"] = message.tool_call_id + else: + raise ValueError(f"Got unknown message type: {type(message)}") + + if message.name: + message_dict["name"] = message.name + + return message_dict + + @staticmethod + def _convert_writer_to_langchain(response_message: Any) -> BaseMessage: + """Convert a Writer message to a LangChain message.""" + if not isinstance(response_message, dict): + response_message = json.loads( + json.dumps(response_message, default=lambda o: o.__dict__) + ) + + role = response_message.get("role", "") + content = response_message.get("content") + if not content: + content = "" + + if role == "user": + return HumanMessage(content=content) + elif role == "assistant": + additional_kwargs = {} + if tool_calls := response_message.get("tool_calls", []): + additional_kwargs["tool_calls"] = tool_calls + return AIMessageChunk(content=content, additional_kwargs=additional_kwargs) + elif role == "system": + return SystemMessage(content=content) + elif role == "tool": + return ToolMessage( + content=content, + tool_call_id=response_message.get("tool_call_id", ""), + name=response_message.get("name", ""), + ) + else: + return ChatMessage(content=content, role=role) + + def _convert_messages_to_writer( self, messages: List[BaseMessage], stop: Optional[List[str]] = None ) -> Tuple[List[Dict[str, Any]], Dict[str, Any]]: + """Convert a list of LangChain messages to List of Writer dicts.""" params = { "model": self.model_name, "temperature": self.temperature, "n": self.n, - "stream": self.streaming, **self.model_kwargs, } if stop: @@ -187,7 +257,7 @@ def _convert_messages_to_dicts( if self.max_tokens is not None: params["max_tokens"] = self.max_tokens - message_dicts = [_convert_message_to_dict(m) for m in messages] + message_dicts = [self._convert_langchain_to_writer(m) for m in messages] return message_dicts, params def _stream( @@ -197,17 +267,17 @@ def _stream( run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> Iterator[ChatGenerationChunk]: - message_dicts, params = self._convert_messages_to_dicts(messages, stop) + message_dicts, params = self._convert_messages_to_writer(messages, stop) params = {**params, **kwargs, "stream": True} response = self.client.chat.chat(messages=message_dicts, **params) for chunk in response: - delta = chunk["choices"][0].get("delta") - if not delta or not delta.get("content"): + delta = chunk.choices[0].delta + if not delta or not delta.content: continue - chunk = _convert_dict_to_message( - {"role": "assistant", "content": delta["content"]} + chunk = self._convert_writer_to_langchain( + {"role": "assistant", "content": delta.content} ) chunk = ChatGenerationChunk(message=chunk) @@ -223,17 +293,17 @@ async def _astream( run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any, ) -> AsyncIterator[ChatGenerationChunk]: - message_dicts, params = self._convert_messages_to_dicts(messages, stop) + message_dicts, params = self._convert_messages_to_writer(messages, stop) params = {**params, **kwargs, "stream": True} response = await self.async_client.chat.chat(messages=message_dicts, **params) async for chunk in response: - delta = chunk["choices"][0].get("delta") - if not delta or not delta.get("content"): + delta = chunk.choices[0].delta + if not delta or not delta.content: continue - chunk = _convert_dict_to_message( - {"role": "assistant", "content": delta["content"]} + chunk = self._convert_writer_to_langchain( + {"role": "assistant", "content": delta.content} ) chunk = ChatGenerationChunk(message=chunk) @@ -249,12 +319,7 @@ def _generate( run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> ChatResult: - if self.streaming: - return generate_from_stream( - self._stream(messages, stop, run_manager, **kwargs) - ) - - message_dicts, params = self._convert_messages_to_dicts(messages, stop) + message_dicts, params = self._convert_messages_to_writer(messages, stop) params = {**params, **kwargs} response = self.client.chat.chat(messages=message_dicts, **params) return self._create_chat_result(response) @@ -266,28 +331,11 @@ async def _agenerate( run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any, ) -> ChatResult: - if self.streaming: - return await agenerate_from_stream( - self._astream(messages, stop, run_manager, **kwargs) - ) - - message_dicts, params = self._convert_messages_to_dicts(messages, stop) + message_dicts, params = self._convert_messages_to_writer(messages, stop) params = {**params, **kwargs} response = await self.async_client.chat.chat(messages=message_dicts, **params) return self._create_chat_result(response) - @property - def _default_params(self) -> Dict[str, Any]: - """Get the default parameters for calling Writer API.""" - return { - "model": self.model_name, - "temperature": self.temperature, - "stream": self.streaming, - "n": self.n, - "max_tokens": self.max_tokens, - **self.model_kwargs, - } - def bind_tools( self, tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable]], diff --git a/libs/community/langchain_community/document_loaders/__init__.py b/libs/community/langchain_community/document_loaders/__init__.py index 2576093d3d48b..8a56f918ab6ac 100644 --- a/libs/community/langchain_community/document_loaders/__init__.py +++ b/libs/community/langchain_community/document_loaders/__init__.py @@ -299,6 +299,9 @@ from langchain_community.document_loaders.mongodb import ( MongodbLoader, ) + from langchain_community.document_loaders.needle import ( + NeedleLoader, + ) from langchain_community.document_loaders.news import ( NewsURLLoader, ) @@ -631,6 +634,7 @@ "MergedDataLoader": "langchain_community.document_loaders.merge", "ModernTreasuryLoader": "langchain_community.document_loaders.modern_treasury", "MongodbLoader": "langchain_community.document_loaders.mongodb", + "NeedleLoader": "langchain_community.document_loaders.needle", "NewsURLLoader": "langchain_community.document_loaders.news", "NotebookLoader": "langchain_community.document_loaders.notebook", "NotionDBLoader": "langchain_community.document_loaders.notiondb", @@ -837,6 +841,7 @@ def __getattr__(name: str) -> Any: "MergedDataLoader", "ModernTreasuryLoader", "MongodbLoader", + "NeedleLoader", "NewsURLLoader", "NotebookLoader", "NotionDBLoader", diff --git a/libs/community/langchain_community/document_loaders/base_o365.py b/libs/community/langchain_community/document_loaders/base_o365.py index 5f89d0794fccd..981a637cbb3b1 100644 --- a/libs/community/langchain_community/document_loaders/base_o365.py +++ b/libs/community/langchain_community/document_loaders/base_o365.py @@ -5,7 +5,9 @@ import logging import mimetypes import os +import re import tempfile +import urllib from abc import abstractmethod from pathlib import Path, PurePath from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Sequence, Union @@ -186,9 +188,18 @@ def _load_from_folder(self, folder: Folder) -> Iterable[Blob]: for file in items: if file.is_file: if file.mime_type in list(file_mime_types.values()): + source = file.web_url + if re.search( + r"Doc.aspx\?sourcedoc=.*file=([^&]+)", file.web_url + ): + source = ( + file._parent.web_url + + "/" + + urllib.parse.quote(file.name) + ) file.download(to_path=temp_dir, chunk_size=self.chunk_size) metadata_dict[file.name] = { - "source": file.web_url, + "source": source, "mime_type": file.mime_type, "created": str(file.created), "modified": str(file.modified), @@ -241,9 +252,18 @@ def _load_from_object_ids( continue if file.is_file: if file.mime_type in list(file_mime_types.values()): + source = file.web_url + if re.search( + r"Doc.aspx\?sourcedoc=.*file=([^&]+)", file.web_url + ): + source = ( + file._parent.web_url + + "/" + + urllib.parse.quote(file.name) + ) file.download(to_path=temp_dir, chunk_size=self.chunk_size) metadata_dict[file.name] = { - "source": file.web_url, + "source": source, "mime_type": file.mime_type, "created": file.created, "modified": file.modified, diff --git a/libs/community/langchain_community/document_loaders/confluence.py b/libs/community/langchain_community/document_loaders/confluence.py index 70c86e7dce962..263c0c8d31fe2 100644 --- a/libs/community/langchain_community/document_loaders/confluence.py +++ b/libs/community/langchain_community/document_loaders/confluence.py @@ -166,6 +166,7 @@ def __init__( include_archived_content: bool = False, include_attachments: bool = False, include_comments: bool = False, + include_labels: bool = False, content_format: ContentFormat = ContentFormat.STORAGE, limit: Optional[int] = 50, max_pages: Optional[int] = 1000, @@ -181,6 +182,7 @@ def __init__( self.include_archived_content = include_archived_content self.include_attachments = include_attachments self.include_comments = include_comments + self.include_labels = include_labels self.content_format = content_format self.limit = limit self.max_pages = max_pages @@ -327,12 +329,20 @@ def _lazy_load(self, **kwargs: Any) -> Iterator[Document]: ) include_attachments = self._resolve_param("include_attachments", kwargs) include_comments = self._resolve_param("include_comments", kwargs) + include_labels = self._resolve_param("include_labels", kwargs) content_format = self._resolve_param("content_format", kwargs) limit = self._resolve_param("limit", kwargs) max_pages = self._resolve_param("max_pages", kwargs) ocr_languages = self._resolve_param("ocr_languages", kwargs) keep_markdown_format = self._resolve_param("keep_markdown_format", kwargs) keep_newlines = self._resolve_param("keep_newlines", kwargs) + expand = ",".join( + [ + content_format.value, + "version", + *(["metadata.labels"] if include_labels else []), + ] + ) if not space_key and not page_ids and not label and not cql: raise ValueError( @@ -347,13 +357,14 @@ def _lazy_load(self, **kwargs: Any) -> Iterator[Document]: limit=limit, max_pages=max_pages, status="any" if include_archived_content else "current", - expand=f"{content_format.value},version", + expand=expand, ) yield from self.process_pages( pages, include_restricted_content, include_attachments, include_comments, + include_labels, content_format, ocr_languages=ocr_languages, keep_markdown_format=keep_markdown_format, @@ -380,13 +391,14 @@ def _lazy_load(self, **kwargs: Any) -> Iterator[Document]: limit=limit, max_pages=max_pages, include_archived_spaces=include_archived_content, - expand=f"{content_format.value},version", + expand=expand, ) yield from self.process_pages( pages, include_restricted_content, include_attachments, include_comments, + False, # labels are not included in the search results content_format, ocr_languages, keep_markdown_format, @@ -408,7 +420,8 @@ def _lazy_load(self, **kwargs: Any) -> Iterator[Document]: before_sleep=before_sleep_log(logger, logging.WARNING), )(self.confluence.get_page_by_id) page = get_page( - page_id=page_id, expand=f"{content_format.value},version" + page_id=page_id, + expand=expand, ) if not include_restricted_content and not self.is_public_page(page): continue @@ -416,6 +429,7 @@ def _lazy_load(self, **kwargs: Any) -> Iterator[Document]: page, include_attachments, include_comments, + include_labels, content_format, ocr_languages, keep_markdown_format, @@ -498,6 +512,7 @@ def process_pages( include_restricted_content: bool, include_attachments: bool, include_comments: bool, + include_labels: bool, content_format: ContentFormat, ocr_languages: Optional[str] = None, keep_markdown_format: Optional[bool] = False, @@ -511,6 +526,7 @@ def process_pages( page, include_attachments, include_comments, + include_labels, content_format, ocr_languages=ocr_languages, keep_markdown_format=keep_markdown_format, @@ -522,6 +538,7 @@ def process_page( page: dict, include_attachments: bool, include_comments: bool, + include_labels: bool, content_format: ContentFormat, ocr_languages: Optional[str] = None, keep_markdown_format: Optional[bool] = False, @@ -575,10 +592,19 @@ def process_page( ] text = text + "".join(comment_texts) + if include_labels: + labels = [ + label["name"] + for label in page.get("metadata", {}) + .get("labels", {}) + .get("results", []) + ] + metadata = { "title": page["title"], "id": page["id"], "source": self.base_url.strip("/") + page["_links"]["webui"], + **({"labels": labels} if include_labels else {}), } if "version" in page and "when" in page["version"]: diff --git a/libs/community/langchain_community/document_loaders/needle.py b/libs/community/langchain_community/document_loaders/needle.py new file mode 100644 index 0000000000000..03b9ee0c0e01e --- /dev/null +++ b/libs/community/langchain_community/document_loaders/needle.py @@ -0,0 +1,164 @@ +from typing import Dict, Iterator, List, Optional + +from langchain_core.document_loaders.base import BaseLoader +from langchain_core.documents import Document + + +class NeedleLoader(BaseLoader): + """ + NeedleLoader is a document loader for managing documents stored in a collection. + + Setup: + Install the `needle-python` library and set your Needle API key. + + .. code-block:: bash + + pip install needle-python + export NEEDLE_API_KEY="your-api-key" + + Key init args: + - `needle_api_key` (Optional[str]): API key for authenticating with Needle. + - `collection_id` (str): Needle collection to load documents from. + + Usage: + .. code-block:: python + + from langchain_community.document_loaders.needle import NeedleLoader + + loader = NeedleLoader( + needle_api_key="your-api-key", + collection_id="your-collection-id" + ) + + # Load documents + documents = loader.load() + for doc in documents: + print(doc.metadata) + + # Lazy load documents + for doc in loader.lazy_load(): + print(doc.metadata) + """ + + def __init__( + self, + needle_api_key: Optional[str] = None, + collection_id: Optional[str] = None, + ) -> None: + """ + Initializes the NeedleLoader with API key and collection ID. + + Args: + needle_api_key (Optional[str]): API key for authenticating with Needle. + collection_id (Optional[str]): Identifier for the Needle collection. + + Raises: + ImportError: If the `needle-python` library is not installed. + ValueError: If the collection ID is not provided. + """ + try: + from needle.v1 import NeedleClient + except ImportError: + raise ImportError( + "Please install with `pip install needle-python` to use NeedleLoader." + ) + + super().__init__() + self.needle_api_key = needle_api_key + self.collection_id = collection_id + self.client: Optional[NeedleClient] = None + + if self.needle_api_key: + self.client = NeedleClient(api_key=self.needle_api_key) + + if not self.collection_id: + raise ValueError("Collection ID must be provided.") + + def _get_collection(self) -> None: + """ + Ensures the Needle collection is set and the client is initialized. + + Raises: + ValueError: If the Needle client is not initialized or + if the collection ID is missing. + """ + if self.client is None: + raise ValueError( + "NeedleClient is not initialized. Provide a valid API key." + ) + if not self.collection_id: + raise ValueError("Collection ID must be provided.") + + def add_files(self, files: Dict[str, str]) -> None: + """ + Adds files to the Needle collection. + + Args: + files (Dict[str, str]): Dictionary where keys are file names and values + are file URLs. + + Raises: + ImportError: If the `needle-python` library is not installed. + ValueError: If the collection is not properly initialized. + """ + try: + from needle.v1.models import FileToAdd + except ImportError: + raise ImportError( + "Please install with `pip install needle-python` to add files." + ) + + self._get_collection() + assert self.client is not None, "NeedleClient must be initialized." + + files_to_add = [FileToAdd(name=name, url=url) for name, url in files.items()] + + self.client.collections.files.add( + collection_id=self.collection_id, files=files_to_add + ) + + def _fetch_documents(self) -> List[Document]: + """ + Fetches metadata for documents from the Needle collection. + + Returns: + List[Document]: A list of documents with metadata. Content is excluded. + + Raises: + ValueError: If the collection is not properly initialized. + """ + self._get_collection() + assert self.client is not None, "NeedleClient must be initialized." + + files = self.client.collections.files.list(self.collection_id) + docs = [ + Document( + page_content="", # Needle doesn't provide file content fetching + metadata={ + "source": file.url, + "title": file.name, + "size": getattr(file, "size", None), + }, + ) + for file in files + if file.status == "indexed" + ] + return docs + + def load(self) -> List[Document]: + """ + Loads all documents from the Needle collection. + + Returns: + List[Document]: A list of documents from the collection. + """ + return self._fetch_documents() + + def lazy_load(self) -> Iterator[Document]: + """ + Lazily loads documents from the Needle collection. + + Yields: + Iterator[Document]: An iterator over the documents. + """ + yield from self._fetch_documents() diff --git a/libs/community/langchain_community/embeddings/__init__.py b/libs/community/langchain_community/embeddings/__init__.py index 38c7d5a76bc1d..05a503ca299ac 100644 --- a/libs/community/langchain_community/embeddings/__init__.py +++ b/libs/community/langchain_community/embeddings/__init__.py @@ -145,6 +145,9 @@ from langchain_community.embeddings.mlflow_gateway import ( MlflowAIGatewayEmbeddings, ) + from langchain_community.embeddings.model2vec import ( + Model2vecEmbeddings, + ) from langchain_community.embeddings.modelscope_hub import ( ModelScopeEmbeddings, ) @@ -289,6 +292,7 @@ "MlflowAIGatewayEmbeddings", "MlflowCohereEmbeddings", "MlflowEmbeddings", + "Model2vecEmbeddings", "ModelScopeEmbeddings", "MosaicMLInstructorEmbeddings", "NLPCloudEmbeddings", @@ -372,6 +376,7 @@ "MlflowAIGatewayEmbeddings": "langchain_community.embeddings.mlflow_gateway", "MlflowCohereEmbeddings": "langchain_community.embeddings.mlflow", "MlflowEmbeddings": "langchain_community.embeddings.mlflow", + "Model2vecEmbeddings": "langchain_community.embeddings.model2vec", "ModelScopeEmbeddings": "langchain_community.embeddings.modelscope_hub", "MosaicMLInstructorEmbeddings": "langchain_community.embeddings.mosaicml", "NLPCloudEmbeddings": "langchain_community.embeddings.nlpcloud", diff --git a/libs/community/langchain_community/embeddings/anyscale.py b/libs/community/langchain_community/embeddings/anyscale.py index 82a87c46debbc..7f35a729b484b 100644 --- a/libs/community/langchain_community/embeddings/anyscale.py +++ b/libs/community/langchain_community/embeddings/anyscale.py @@ -2,7 +2,7 @@ from __future__ import annotations -from typing import Dict +from typing import Dict, Optional from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init from pydantic import Field, SecretStr @@ -17,7 +17,7 @@ class AnyscaleEmbeddings(OpenAIEmbeddings): """`Anyscale` Embeddings API.""" - anyscale_api_key: SecretStr = Field(default=None) + anyscale_api_key: Optional[SecretStr] = Field(default=None) """AnyScale Endpoints API keys.""" model: str = Field(default=DEFAULT_MODEL) """Model name to use.""" diff --git a/libs/community/langchain_community/embeddings/model2vec.py b/libs/community/langchain_community/embeddings/model2vec.py new file mode 100644 index 0000000000000..8cba54b09011a --- /dev/null +++ b/libs/community/langchain_community/embeddings/model2vec.py @@ -0,0 +1,66 @@ +"""Wrapper around model2vec embedding models.""" + +from typing import List + +from langchain_core.embeddings import Embeddings + + +class Model2vecEmbeddings(Embeddings): + """model2v embedding models. + + Install model2vec first, run 'pip install -U model2vec'. + The github repository for model2vec is : https://github.com/MinishLab/model2vec + + Example: + .. code-block:: python + + from langchain_community.embeddings import Model2vecEmbeddings + + embedding = Model2vecEmbeddings("minishlab/potion-base-8M") + embedding.embed_documents([ + "It's dangerous to go alone!", + "It's a secret to everybody.", + ]) + embedding.embed_query( + "Take this with you." + ) + """ + + def __init__(self, model: str): + """Initialize embeddings. + + Args: + model: Model name. + """ + try: + from model2vec import StaticModel + except ImportError as e: + raise ImportError( + "Unable to import model2vec, please install with " + "`pip install -U model2vec`." + ) from e + self._model = StaticModel.from_pretrained(model) + + def embed_documents(self, texts: List[str]) -> List[List[float]]: + """Embed documents using the model2vec embeddings model. + + Args: + texts: The list of texts to embed. + + Returns: + List of embeddings, one for each text. + """ + + return self._model.encode_as_sequence(texts) + + def embed_query(self, text: str) -> List[float]: + """Embed a query using the model2vec embeddings model. + + Args: + text: The text to embed. + + Returns: + Embeddings for the text. + """ + + return self._model.encode(text) diff --git a/libs/community/langchain_community/embeddings/naver.py b/libs/community/langchain_community/embeddings/naver.py index 9b111a841bbf8..1de8921017769 100644 --- a/libs/community/langchain_community/embeddings/naver.py +++ b/libs/community/langchain_community/embeddings/naver.py @@ -1,5 +1,5 @@ import logging -from typing import Any, Dict, List, Optional +from typing import Any, Dict, List, Optional, cast import httpx from langchain_core.embeddings import Embeddings @@ -60,8 +60,8 @@ class ClovaXEmbeddings(BaseModel, Embeddings): output = embedding.embed_documents(documents) """ # noqa: E501 - client: httpx.Client = Field(default=None) #: :meta private: - async_client: httpx.AsyncClient = Field(default=None) #: :meta private: + client: Optional[httpx.Client] = Field(default=None) #: :meta private: + async_client: Optional[httpx.AsyncClient] = Field(default=None) #: :meta private: ncp_clovastudio_api_key: Optional[SecretStr] = Field(default=None, alias="api_key") """Automatically inferred from env are `NCP_CLOVASTUDIO_API_KEY` if not provided.""" @@ -69,7 +69,7 @@ class ClovaXEmbeddings(BaseModel, Embeddings): ncp_apigw_api_key: Optional[SecretStr] = Field(default=None, alias="apigw_api_key") """Automatically inferred from env are `NCP_APIGW_API_KEY` if not provided.""" - base_url: str = Field(default=None, alias="base_url") + base_url: Optional[str] = Field(default=None, alias="base_url") """ Automatically inferred from env are `NCP_CLOVASTUDIO_API_BASE_URL` if not provided. """ @@ -168,13 +168,15 @@ def default_headers(self) -> Dict[str, Any]: def _embed_text(self, text: str) -> List[float]: payload = {"text": text} - response = self.client.post(url=self._api_url, json=payload) + client = cast(httpx.Client, self.client) + response = client.post(url=self._api_url, json=payload) _raise_on_error(response) return response.json()["result"]["embedding"] async def _aembed_text(self, text: str) -> List[float]: payload = {"text": text} - response = await self.async_client.post(url=self._api_url, json=payload) + async_client = cast(httpx.AsyncClient, self.client) + response = await async_client.post(url=self._api_url, json=payload) await _araise_on_error(response) return response.json()["result"]["embedding"] diff --git a/libs/community/langchain_community/embeddings/octoai_embeddings.py b/libs/community/langchain_community/embeddings/octoai_embeddings.py index 3cbfe01449ae4..dc16288da94ed 100644 --- a/libs/community/langchain_community/embeddings/octoai_embeddings.py +++ b/libs/community/langchain_community/embeddings/octoai_embeddings.py @@ -1,4 +1,4 @@ -from typing import Dict +from typing import Dict, Optional from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init from pydantic import Field, SecretStr @@ -20,7 +20,7 @@ class OctoAIEmbeddings(OpenAIEmbeddings): Alternatively, you can use the octoai_api_token keyword argument. """ - octoai_api_token: SecretStr = Field(default=None) + octoai_api_token: Optional[SecretStr] = Field(default=None) """OctoAI Endpoints API keys.""" endpoint_url: str = Field(default=DEFAULT_API_BASE) """Base URL path for API requests.""" diff --git a/libs/community/langchain_community/graphs/neo4j_graph.py b/libs/community/langchain_community/graphs/neo4j_graph.py index d3e8860c89131..dd2a7937f7f81 100644 --- a/libs/community/langchain_community/graphs/neo4j_graph.py +++ b/libs/community/langchain_community/graphs/neo4j_graph.py @@ -1,6 +1,7 @@ from hashlib import md5 from typing import Any, Dict, List, Optional +from langchain_core._api.deprecation import deprecated from langchain_core.utils import get_from_dict_or_env from langchain_community.graphs.graph_document import GraphDocument @@ -51,6 +52,11 @@ ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.graphs.neo4j_graph.clean_string_values", +) def clean_string_values(text: str) -> str: """Clean string values for schema. @@ -65,6 +71,11 @@ def clean_string_values(text: str) -> str: return text.replace("\n", " ").replace("\r", " ") +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.graphs.neo4j_graph.value_sanitize", +) def value_sanitize(d: Any) -> Any: """Sanitize the input dictionary or list. @@ -111,6 +122,11 @@ def value_sanitize(d: Any) -> Any: return d +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.graphs.neo4j_graph._get_node_import_query", +) def _get_node_import_query(baseEntityLabel: bool, include_source: bool) -> str: if baseEntityLabel: return ( @@ -134,6 +150,11 @@ def _get_node_import_query(baseEntityLabel: bool, include_source: bool) -> str: ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.graphs.neo4j_graph._get_rel_import_query", +) def _get_rel_import_query(baseEntityLabel: bool) -> str: if baseEntityLabel: return ( @@ -158,6 +179,11 @@ def _get_rel_import_query(baseEntityLabel: bool) -> str: ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.graphs.neo4j_graph._format_schema", +) def _format_schema(schema: Dict, is_enhanced: bool) -> str: formatted_node_props = [] formatted_rel_props = [] @@ -287,10 +313,20 @@ def _format_schema(schema: Dict, is_enhanced: bool) -> str: ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.graphs.neo4j_graph._remove_backticks", +) def _remove_backticks(text: str) -> str: return text.replace("`", "") +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.Neo4jGraph", +) class Neo4jGraph(GraphStore): """Neo4j database wrapper for various graph operations. diff --git a/libs/community/langchain_community/llms/anyscale.py b/libs/community/langchain_community/llms/anyscale.py index 60e3e2526d0cc..e91607543e17e 100644 --- a/libs/community/langchain_community/llms/anyscale.py +++ b/libs/community/langchain_community/llms/anyscale.py @@ -84,7 +84,7 @@ def send_query(llm, text): """Key word arguments to pass to the model.""" anyscale_api_base: str = Field(default=DEFAULT_BASE_URL) - anyscale_api_key: SecretStr = Field(default=None) + anyscale_api_key: SecretStr = Field(default=SecretStr("")) model_name: str = Field(default=DEFAULT_MODEL) prefix_messages: List = Field(default_factory=list) diff --git a/libs/community/langchain_community/llms/exllamav2.py b/libs/community/langchain_community/llms/exllamav2.py index 27f5c1ac1d53c..6ac9dc5832af9 100644 --- a/libs/community/langchain_community/llms/exllamav2.py +++ b/libs/community/langchain_community/llms/exllamav2.py @@ -43,7 +43,7 @@ class ExLlamaV2(LLM): # Langchain parameters logfunc: Callable = print - stop_sequences: List[str] = Field("") + stop_sequences: List[str] = Field([]) """Sequences that immediately will stop the generator.""" max_new_tokens: int = Field(150) @@ -56,7 +56,7 @@ class ExLlamaV2(LLM): """Whether to print debug information.""" # Generator parameters - disallowed_tokens: List[int] = Field(None) + disallowed_tokens: Optional[List[int]] = Field(None) """List of tokens to disallow during generation.""" @pre_init diff --git a/libs/community/langchain_community/llms/gooseai.py b/libs/community/langchain_community/llms/gooseai.py index e8dc5ec77efeb..61383e9b7db8b 100644 --- a/libs/community/langchain_community/llms/gooseai.py +++ b/libs/community/langchain_community/llms/gooseai.py @@ -61,7 +61,7 @@ class GooseAI(LLM): model_kwargs: Dict[str, Any] = Field(default_factory=dict) """Holds any model parameters valid for `create` call not explicitly specified.""" - logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict) + logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict) # type: ignore[arg-type] """Adjust the probability of specific tokens being generated.""" gooseai_api_key: Optional[SecretStr] = None diff --git a/libs/community/langchain_community/llms/octoai_endpoint.py b/libs/community/langchain_community/llms/octoai_endpoint.py index 38abe0813f73b..de56c11eb5817 100644 --- a/libs/community/langchain_community/llms/octoai_endpoint.py +++ b/libs/community/langchain_community/llms/octoai_endpoint.py @@ -36,7 +36,7 @@ class OctoAIEndpoint(BaseOpenAI): # type: ignore[override] """Key word arguments to pass to the model.""" octoai_api_base: str = Field(default=DEFAULT_BASE_URL) - octoai_api_token: SecretStr = Field(default=None) + octoai_api_token: SecretStr = Field(default=SecretStr("")) model_name: str = Field(default=DEFAULT_MODEL) @classmethod diff --git a/libs/community/langchain_community/llms/openai.py b/libs/community/langchain_community/llms/openai.py index fe74a55105a2f..9a3937179c96f 100644 --- a/libs/community/langchain_community/llms/openai.py +++ b/libs/community/langchain_community/llms/openai.py @@ -219,7 +219,7 @@ def is_lc_serializable(cls) -> bool: ) """Timeout for requests to OpenAI completion API. Can be float, httpx.Timeout or None.""" - logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict) + logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict) # type: ignore[arg-type] """Adjust the probability of specific tokens being generated.""" max_retries: int = 2 """Maximum number of retries to make when generating.""" diff --git a/libs/community/langchain_community/llms/sambanova.py b/libs/community/langchain_community/llms/sambanova.py index 7b4badce9b269..a485b87cd404c 100644 --- a/libs/community/langchain_community/llms/sambanova.py +++ b/libs/community/langchain_community/llms/sambanova.py @@ -105,7 +105,7 @@ class SambaStudio(LLM): sambastudio_url: str = Field(default="") """SambaStudio Url""" - sambastudio_api_key: SecretStr = Field(default="") + sambastudio_api_key: SecretStr = Field(default=SecretStr("")) """SambaStudio api key""" base_url: str = Field(default="", exclude=True) @@ -607,7 +607,7 @@ class SambaNovaCloud(LLM): sambanova_url: str = Field(default="") """SambaNova Cloud Url""" - sambanova_api_key: SecretStr = Field(default="") + sambanova_api_key: SecretStr = Field(default=SecretStr("")) """SambaNova Cloud api key""" model: str = Field(default="Meta-Llama-3.1-8B-Instruct") diff --git a/libs/community/langchain_community/llms/writer.py b/libs/community/langchain_community/llms/writer.py index d82a346c43616..e68909d06e13e 100644 --- a/libs/community/langchain_community/llms/writer.py +++ b/libs/community/langchain_community/llms/writer.py @@ -1,108 +1,89 @@ -from typing import Any, Dict, List, Mapping, Optional +from typing import Any, AsyncIterator, Dict, Iterator, List, Mapping, Optional -import requests -from langchain_core.callbacks import CallbackManagerForLLMRun +from langchain_core.callbacks import ( + AsyncCallbackManagerForLLMRun, + CallbackManagerForLLMRun, +) from langchain_core.language_models.llms import LLM -from langchain_core.utils import get_from_dict_or_env, pre_init -from pydantic import ConfigDict - -from langchain_community.llms.utils import enforce_stop_tokens +from langchain_core.outputs import GenerationChunk +from langchain_core.utils import get_from_dict_or_env +from pydantic import ConfigDict, Field, SecretStr, model_validator class Writer(LLM): """Writer large language models. - To use, you should have the environment variable ``WRITER_API_KEY`` and - ``WRITER_ORG_ID`` set with your API key and organization ID respectively. + To use, you should have the ``writer-sdk`` Python package installed, and the + environment variable ``WRITER_API_KEY`` set with your API key. Example: .. code-block:: python - from langchain_community.llms import Writer - writer = Writer(model_id="palmyra-base") + from langchain_community.llms import Writer as WriterLLM + from writerai import Writer, AsyncWriter + + client = Writer() + async_client = AsyncWriter() + + chat = WriterLLM( + client=client, + async_client=async_client + ) """ - writer_org_id: Optional[str] = None - """Writer organization ID.""" + client: Any = Field(default=None, exclude=True) #: :meta private: + async_client: Any = Field(default=None, exclude=True) #: :meta private: - model_id: str = "palmyra-instruct" - """Model name to use.""" + api_key: Optional[SecretStr] = Field(default=None) + """Writer API key.""" - min_tokens: Optional[int] = None - """Minimum number of tokens to generate.""" + model_name: str = Field(default="palmyra-x-003-instruct", alias="model") + """Model name to use.""" max_tokens: Optional[int] = None - """Maximum number of tokens to generate.""" + """The maximum number of tokens that the model can generate in the response.""" - temperature: Optional[float] = None - """What sampling temperature to use.""" + temperature: Optional[float] = 0.7 + """Controls the randomness of the model's outputs. Higher values lead to more + random outputs, while lower values make the model more deterministic.""" top_p: Optional[float] = None - """Total probability mass of tokens to consider at each step.""" + """Used to control the nucleus sampling, where only the most probable tokens + with a cumulative probability of top_p are considered for sampling, providing + a way to fine-tune the randomness of predictions.""" stop: Optional[List[str]] = None - """Sequences when completion generation will stop.""" - - presence_penalty: Optional[float] = None - """Penalizes repeated tokens regardless of frequency.""" - - repetition_penalty: Optional[float] = None - """Penalizes repeated tokens according to frequency.""" + """Specifies stopping conditions for the model's output generation. This can + be an array of strings or a single string that the model will look for as a + signal to stop generating further tokens.""" best_of: Optional[int] = None - """Generates this many completions server-side and returns the "best".""" - - logprobs: bool = False - """Whether to return log probabilities.""" - - n: Optional[int] = None - """How many completions to generate.""" + """Specifies the number of completions to generate and return the best one. + Useful for generating multiple outputs and choosing the best based on some + criteria.""" - writer_api_key: Optional[str] = None - """Writer API key.""" - - base_url: Optional[str] = None - """Base url to use, if None decides based on model name.""" - - model_config = ConfigDict( - extra="forbid", - ) + model_kwargs: Dict[str, Any] = Field(default_factory=dict) + """Holds any model parameters valid for `create` call not explicitly specified.""" - @pre_init - def validate_environment(cls, values: Dict) -> Dict: - """Validate that api key and organization id exist in environment.""" - - writer_api_key = get_from_dict_or_env( - values, "writer_api_key", "WRITER_API_KEY" - ) - values["writer_api_key"] = writer_api_key - - writer_org_id = get_from_dict_or_env(values, "writer_org_id", "WRITER_ORG_ID") - values["writer_org_id"] = writer_org_id - - return values + model_config = ConfigDict(populate_by_name=True) @property def _default_params(self) -> Mapping[str, Any]: """Get the default parameters for calling Writer API.""" return { - "minTokens": self.min_tokens, - "maxTokens": self.max_tokens, + "max_tokens": self.max_tokens, "temperature": self.temperature, - "topP": self.top_p, + "top_p": self.top_p, "stop": self.stop, - "presencePenalty": self.presence_penalty, - "repetitionPenalty": self.repetition_penalty, - "bestOf": self.best_of, - "logprobs": self.logprobs, - "n": self.n, + "best_of": self.best_of, + **self.model_kwargs, } @property def _identifying_params(self) -> Mapping[str, Any]: """Get the identifying parameters.""" return { - **{"model_id": self.model_id, "writer_org_id": self.writer_org_id}, + "model": self.model_name, **self._default_params, } @@ -111,6 +92,51 @@ def _llm_type(self) -> str: """Return type of llm.""" return "writer" + @model_validator(mode="before") + @classmethod + def validate_environment(cls, values: Dict) -> Any: + """Validates that api key is passed and creates Writer clients.""" + try: + from writerai import AsyncClient, Client + except ImportError as e: + raise ImportError( + "Could not import writerai python package. " + "Please install it with `pip install writerai`." + ) from e + + if not values.get("client"): + values.update( + { + "client": Client( + api_key=get_from_dict_or_env( + values, "api_key", "WRITER_API_KEY" + ) + ) + } + ) + + if not values.get("async_client"): + values.update( + { + "async_client": AsyncClient( + api_key=get_from_dict_or_env( + values, "api_key", "WRITER_API_KEY" + ) + ) + } + ) + + if not ( + type(values.get("client")) is Client + and type(values.get("async_client")) is AsyncClient + ): + raise ValueError( + "'client' attribute must be with type 'Client' and " + "'async_client' must be with type 'AsyncClient' from 'writerai' package" + ) + + return values + def _call( self, prompt: str, @@ -118,41 +144,54 @@ def _call( run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> str: - """Call out to Writer's completions endpoint. - - Args: - prompt: The prompt to pass into the model. - stop: Optional list of stop words to use when generating. - - Returns: - The string generated by the model. - - Example: - .. code-block:: python - - response = Writer("Tell me a joke.") - """ - if self.base_url is not None: - base_url = self.base_url - else: - base_url = ( - "https://enterprise-api.writer.com/llm" - f"/organization/{self.writer_org_id}" - f"/model/{self.model_id}/completions" - ) - params = {**self._default_params, **kwargs} - response = requests.post( - url=base_url, - headers={ - "Authorization": f"{self.writer_api_key}", - "Content-Type": "application/json", - "Accept": "application/json", - }, - json={"prompt": prompt, **params}, - ) - text = response.text + params = {**self._identifying_params, **kwargs} + if stop is not None: + params.update({"stop": stop}) + text = self.client.completions.create(prompt=prompt, **params).choices[0].text + return text + + async def _acall( + self, + prompt: str, + stop: Optional[list[str]] = None, + run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> str: + params = {**self._identifying_params, **kwargs} if stop is not None: - # I believe this is required since the stop tokens - # are not enforced by the model parameters - text = enforce_stop_tokens(text, stop) + params.update({"stop": stop}) + response = await self.async_client.completions.create(prompt=prompt, **params) + text = response.choices[0].text return text + + def _stream( + self, + prompt: str, + stop: Optional[list[str]] = None, + run_manager: Optional[CallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> Iterator[GenerationChunk]: + params = {**self._identifying_params, **kwargs, "stream": True} + if stop is not None: + params.update({"stop": stop}) + response = self.client.completions.create(prompt=prompt, **params) + for chunk in response: + if run_manager: + run_manager.on_llm_new_token(chunk.value) + yield GenerationChunk(text=chunk.value) + + async def _astream( + self, + prompt: str, + stop: Optional[list[str]] = None, + run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> AsyncIterator[GenerationChunk]: + params = {**self._identifying_params, **kwargs, "stream": True} + if stop is not None: + params.update({"stop": stop}) + response = await self.async_client.completions.create(prompt=prompt, **params) + async for chunk in response: + if run_manager: + await run_manager.on_llm_new_token(chunk.value) + yield GenerationChunk(text=chunk.value) diff --git a/libs/community/langchain_community/query_constructors/databricks_vector_search.py b/libs/community/langchain_community/query_constructors/databricks_vector_search.py index 03e7de8efa795..f79a690c9bab4 100644 --- a/libs/community/langchain_community/query_constructors/databricks_vector_search.py +++ b/libs/community/langchain_community/query_constructors/databricks_vector_search.py @@ -90,5 +90,5 @@ def visit_structured_query( if structured_query.filter is None: kwargs = {} else: - kwargs = {"filters": structured_query.filter.accept(self)} + kwargs = {"filter": structured_query.filter.accept(self)} return structured_query.query, kwargs diff --git a/libs/community/langchain_community/query_constructors/neo4j.py b/libs/community/langchain_community/query_constructors/neo4j.py index ecb62452069ac..2ce1de136fcb4 100644 --- a/libs/community/langchain_community/query_constructors/neo4j.py +++ b/libs/community/langchain_community/query_constructors/neo4j.py @@ -1,5 +1,6 @@ from typing import Dict, Tuple, Union +from langchain_core._api.deprecation import deprecated from langchain_core.structured_query import ( Comparator, Comparison, @@ -10,6 +11,11 @@ ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.query_constructors.neo4j.Neo4jTranslator", +) class Neo4jTranslator(Visitor): """Translate `Neo4j` internal query language elements to valid filters.""" diff --git a/libs/community/langchain_community/retrievers/__init__.py b/libs/community/langchain_community/retrievers/__init__.py index 75600eab6d5ad..ce4ac731bde28 100644 --- a/libs/community/langchain_community/retrievers/__init__.py +++ b/libs/community/langchain_community/retrievers/__init__.py @@ -93,6 +93,7 @@ MilvusRetriever, ) from langchain_community.retrievers.nanopq import NanoPQRetriever + from langchain_community.retrievers.needle import NeedleRetriever from langchain_community.retrievers.outline import ( OutlineRetriever, ) @@ -173,6 +174,7 @@ "MetalRetriever": "langchain_community.retrievers.metal", "MilvusRetriever": "langchain_community.retrievers.milvus", "NanoPQRetriever": "langchain_community.retrievers.nanopq", + "NeedleRetriever": "langchain_community.retrievers.needle", "OutlineRetriever": "langchain_community.retrievers.outline", "PineconeHybridSearchRetriever": "langchain_community.retrievers.pinecone_hybrid_search", # noqa: E501 "PubMedRetriever": "langchain_community.retrievers.pubmed", @@ -229,6 +231,7 @@ def __getattr__(name: str) -> Any: "MetalRetriever", "MilvusRetriever", "NanoPQRetriever", + "NeedleRetriever", "NeuralDBRetriever", "OutlineRetriever", "PineconeHybridSearchRetriever", diff --git a/libs/community/langchain_community/retrievers/bm25.py b/libs/community/langchain_community/retrievers/bm25.py index 543058c131a98..70910ce170f61 100644 --- a/libs/community/langchain_community/retrievers/bm25.py +++ b/libs/community/langchain_community/retrievers/bm25.py @@ -33,6 +33,7 @@ def from_texts( cls, texts: Iterable[str], metadatas: Optional[Iterable[dict]] = None, + ids: Optional[Iterable[str]] = None, bm25_params: Optional[Dict[str, Any]] = None, preprocess_func: Callable[[str], List[str]] = default_preprocessing_func, **kwargs: Any, @@ -42,6 +43,7 @@ def from_texts( Args: texts: A list of texts to vectorize. metadatas: A list of metadata dicts to associate with each text. + ids: A list of ids to associate with each text. bm25_params: Parameters to pass to the BM25 vectorizer. preprocess_func: A function to preprocess each text before vectorization. **kwargs: Any other arguments to pass to the retriever. @@ -61,7 +63,15 @@ def from_texts( bm25_params = bm25_params or {} vectorizer = BM25Okapi(texts_processed, **bm25_params) metadatas = metadatas or ({} for _ in texts) - docs = [Document(page_content=t, metadata=m) for t, m in zip(texts, metadatas)] + if ids: + docs = [ + Document(page_content=t, metadata=m, id=i) + for t, m, i in zip(texts, metadatas, ids) + ] + else: + docs = [ + Document(page_content=t, metadata=m) for t, m in zip(texts, metadatas) + ] return cls( vectorizer=vectorizer, docs=docs, preprocess_func=preprocess_func, **kwargs ) @@ -86,11 +96,14 @@ def from_documents( Returns: A BM25Retriever instance. """ - texts, metadatas = zip(*((d.page_content, d.metadata) for d in documents)) + texts, metadatas, ids = zip( + *((d.page_content, d.metadata, d.id) for d in documents) + ) return cls.from_texts( texts=texts, bm25_params=bm25_params, metadatas=metadatas, + ids=ids, preprocess_func=preprocess_func, **kwargs, ) diff --git a/libs/community/langchain_community/retrievers/needle.py b/libs/community/langchain_community/retrievers/needle.py new file mode 100644 index 0000000000000..201d617fda490 --- /dev/null +++ b/libs/community/langchain_community/retrievers/needle.py @@ -0,0 +1,96 @@ +from typing import Any, List, Optional # noqa: I001 + +from langchain_core.callbacks import CallbackManagerForRetrieverRun +from langchain_core.documents import Document +from langchain_core.retrievers import BaseRetriever +from pydantic import BaseModel, Field + + +class NeedleRetriever(BaseRetriever, BaseModel): + """ + NeedleRetriever retrieves relevant documents or context from a Needle collection + based on a search query. + + Setup: + Install the `needle-python` library and set your Needle API key. + + .. code-block:: bash + + pip install needle-python + export NEEDLE_API_KEY="your-api-key" + + Key init args: + - `needle_api_key` (Optional[str]): The API key for authenticating with Needle. + - `collection_id` (str): The ID of the Needle collection to search in. + - `client` (Optional[NeedleClient]): An optional instance of the NeedleClient. + + Usage: + .. code-block:: python + + from langchain_community.retrievers.needle import NeedleRetriever + + retriever = NeedleRetriever( + needle_api_key="your-api-key", + collection_id="your-collection-id" + ) + + results = retriever.retrieve("example query") + for doc in results: + print(doc.page_content) + """ + + client: Optional[Any] = None + """Optional instance of NeedleClient.""" + needle_api_key: Optional[str] = Field(None, description="Needle API Key") + collection_id: Optional[str] = Field( + ..., description="The ID of the Needle collection to search in" + ) + + def _initialize_client(self) -> None: + """ + Initialize the NeedleClient with the provided API key. + + If a client instance is already provided, this method does nothing. + """ + try: + from needle.v1 import NeedleClient + except ImportError: + raise ImportError("Please install with `pip install needle-python`.") + + if not self.client: + self.client = NeedleClient(api_key=self.needle_api_key) + + def _search_collection(self, query: str) -> List[Document]: + """ + Search the Needle collection for relevant documents. + + Args: + query (str): The search query used to find relevant documents. + + Returns: + List[Document]: A list of documents matching the search query. + """ + self._initialize_client() + if self.client is None: + raise ValueError("NeedleClient is not initialized. Provide an API key.") + + results = self.client.collections.search( + collection_id=self.collection_id, text=query + ) + docs = [Document(page_content=result.content) for result in results] + return docs + + def _get_relevant_documents( + self, query: str, *, run_manager: CallbackManagerForRetrieverRun + ) -> List[Document]: + """ + Retrieve relevant documents based on the query. + + Args: + query (str): The query string used to search the collection. + Returns: + List[Document]: A list of documents relevant to the query. + """ + # The `run_manager` parameter is included to match the superclass signature, + # but it is not used in this implementation. + return self._search_collection(query) diff --git a/libs/community/langchain_community/tools/edenai/edenai_base_tool.py b/libs/community/langchain_community/tools/edenai/edenai_base_tool.py index 6c802bbf72a3c..5ce3b89dce3a2 100644 --- a/libs/community/langchain_community/tools/edenai/edenai_base_tool.py +++ b/libs/community/langchain_community/tools/edenai/edenai_base_tool.py @@ -23,7 +23,7 @@ class EdenaiTool(BaseTool): # type: ignore[override] feature: str subfeature: str - edenai_api_key: SecretStr = Field( + edenai_api_key: Optional[SecretStr] = Field( default_factory=secret_from_env("EDENAI_API_KEY", default=None) ) is_async: bool = False @@ -48,8 +48,9 @@ def _call_eden_ai(self, query_params: Dict[str, Any]) -> str: requests.Response: The response from the EdenAI API call. """ + api_key = self.edenai_api_key.get_secret_value() if self.edenai_api_key else "" headers = { - "Authorization": f"Bearer {self.edenai_api_key.get_secret_value()}", + "Authorization": f"Bearer {api_key}", "User-Agent": self.get_user_agent(), } diff --git a/libs/community/langchain_community/tools/office365/messages_search.py b/libs/community/langchain_community/tools/office365/messages_search.py index a320844356941..07178c5f1e2db 100644 --- a/libs/community/langchain_community/tools/office365/messages_search.py +++ b/libs/community/langchain_community/tools/office365/messages_search.py @@ -19,7 +19,7 @@ class SearchEmailsInput(BaseModel): """From https://learn.microsoft.com/en-us/graph/search-query-parameter""" folder: str = Field( - default=None, + default="", description=( " If the user wants to search in only one folder, the name of the folder. " 'Default folders are "inbox", "drafts", "sent items", "deleted ttems", but ' diff --git a/libs/community/langchain_community/utilities/dalle_image_generator.py b/libs/community/langchain_community/utilities/dalle_image_generator.py index ed34231b2bfe3..d95483bb4f67b 100644 --- a/libs/community/langchain_community/utilities/dalle_image_generator.py +++ b/libs/community/langchain_community/utilities/dalle_image_generator.py @@ -31,7 +31,7 @@ class DallEAPIWrapper(BaseModel): async_client: Any = Field(default=None, exclude=True) #: :meta private: model_name: str = Field(default="dall-e-2", alias="model") model_kwargs: Dict[str, Any] = Field(default_factory=dict) - openai_api_key: SecretStr = Field( + openai_api_key: Optional[SecretStr] = Field( alias="api_key", default_factory=secret_from_env( "OPENAI_API_KEY", diff --git a/libs/community/langchain_community/utilities/pubmed.py b/libs/community/langchain_community/utilities/pubmed.py index e3b23cfa0adfb..20185d0c2858e 100644 --- a/libs/community/langchain_community/utilities/pubmed.py +++ b/libs/community/langchain_community/utilities/pubmed.py @@ -31,6 +31,7 @@ class PubMedAPIWrapper(BaseModel): sleep_time: time to wait between retries. Default is 0.2 seconds. email: email address to be used for the PubMed API. + api_key: API key to be used for the PubMed API. """ parse: Any #: :meta private: @@ -47,6 +48,7 @@ class PubMedAPIWrapper(BaseModel): MAX_QUERY_LENGTH: int = 300 doc_content_chars_max: int = 2000 email: str = "your_email@example.com" + api_key: str = "" @model_validator(mode="before") @classmethod @@ -101,6 +103,8 @@ def lazy_load(self, query: str) -> Iterator[dict]: + str({urllib.parse.quote(query)}) + f"&retmode=json&retmax={self.top_k_results}&usehistory=y" ) + if self.api_key != "": + url += f"&api_key={self.api_key}" result = urllib.request.urlopen(url) text = result.read().decode("utf-8") json_text = json.loads(text) @@ -135,6 +139,8 @@ def retrieve_article(self, uid: str, webenv: str) -> dict: + "&webenv=" + webenv ) + if self.api_key != "": + url += f"&api_key={self.api_key}" retry = 0 while True: diff --git a/libs/community/langchain_community/utilities/scenexplain.py b/libs/community/langchain_community/utilities/scenexplain.py index 30eff00fdfb14..2c7b5304adec6 100644 --- a/libs/community/langchain_community/utilities/scenexplain.py +++ b/libs/community/langchain_community/utilities/scenexplain.py @@ -23,7 +23,7 @@ class SceneXplainAPIWrapper(BaseModel): and create a new API key. """ - scenex_api_key: str = Field(..., default_factory=from_env("SCENEX_API_KEY")) + scenex_api_key: str = Field(..., default_factory=from_env("SCENEX_API_KEY")) # type: ignore[call-overload] scenex_api_url: str = "https://api.scenex.jina.ai/v1/describe" def _describe_image(self, image: str) -> str: diff --git a/libs/community/langchain_community/vectorstores/hanavector.py b/libs/community/langchain_community/vectorstores/hanavector.py index 07ced73afe971..6c0a8040b255c 100644 --- a/libs/community/langchain_community/vectorstores/hanavector.py +++ b/libs/community/langchain_community/vectorstores/hanavector.py @@ -256,6 +256,89 @@ def _split_off_special_metadata(self, metadata: dict) -> Tuple[dict, list]: return metadata, special_metadata + def create_hnsw_index( + self, + m: Optional[int] = None, # Optional M parameter + ef_construction: Optional[int] = None, # Optional efConstruction parameter + ef_search: Optional[int] = None, # Optional efSearch parameter + index_name: Optional[str] = None, # Optional custom index name + ) -> None: + """ + Creates an HNSW vector index on a specified table and vector column with + optional build and search configurations. If no configurations are provided, + default parameters from the database are used. If provided values exceed the + valid ranges, an error will be raised. + The index is always created in ONLINE mode. + + Args: + m: (Optional) Maximum number of neighbors per graph node + (Valid Range: [4, 1000]) + ef_construction: (Optional) Maximal candidates to consider when building + the graph (Valid Range: [1, 100000]) + ef_search: (Optional) Minimum candidates for top-k-nearest neighbor + queries (Valid Range: [1, 100000]) + index_name: (Optional) Custom index name. Defaults to + __idx + """ + # Set default index name if not provided + distance_func_name = HANA_DISTANCE_FUNCTION[self.distance_strategy][0] + default_index_name = f"{self.table_name}_{distance_func_name}_idx" + # Use provided index_name or default + index_name = ( + HanaDB._sanitize_name(index_name) if index_name else default_index_name + ) + # Initialize build_config and search_config as empty dictionaries + build_config = {} + search_config = {} + + # Validate and add m parameter to build_config if provided + if m is not None: + m = HanaDB._sanitize_int(m) + if not (4 <= m <= 1000): + raise ValueError("M must be in the range [4, 1000]") + build_config["M"] = m + + # Validate and add ef_construction to build_config if provided + if ef_construction is not None: + ef_construction = HanaDB._sanitize_int(ef_construction) + if not (1 <= ef_construction <= 100000): + raise ValueError("efConstruction must be in the range [1, 100000]") + build_config["efConstruction"] = ef_construction + + # Validate and add ef_search to search_config if provided + if ef_search is not None: + ef_search = HanaDB._sanitize_int(ef_search) + if not (1 <= ef_search <= 100000): + raise ValueError("efSearch must be in the range [1, 100000]") + search_config["efSearch"] = ef_search + + # Convert build_config and search_config to JSON strings if they contain values + build_config_str = json.dumps(build_config) if build_config else "" + search_config_str = json.dumps(search_config) if search_config else "" + + # Create the index SQL string with the ONLINE keyword + sql_str = ( + f'CREATE HNSW VECTOR INDEX {index_name} ON "{self.table_name}" ' + f'("{self.vector_column}") ' + f"SIMILARITY FUNCTION {distance_func_name} " + ) + + # Append build_config to the SQL string if provided + if build_config_str: + sql_str += f"BUILD CONFIGURATION '{build_config_str}' " + + # Append search_config to the SQL string if provided + if search_config_str: + sql_str += f"SEARCH CONFIGURATION '{search_config_str}' " + + # Always add the ONLINE option + sql_str += "ONLINE " + cur = self.connection.cursor() + try: + cur.execute(sql_str) + finally: + cur.close() + def add_texts( # type: ignore[override] self, texts: Iterable[str], @@ -418,18 +501,18 @@ def similarity_search_with_score_and_vector_by_vector( k = HanaDB._sanitize_int(k) embedding = HanaDB._sanitize_list_float(embedding) distance_func_name = HANA_DISTANCE_FUNCTION[self.distance_strategy][0] - embedding_as_str = ",".join(map(str, embedding)) + embedding_as_str = "[" + ",".join(map(str, embedding)) + "]" sql_str = ( f"SELECT TOP {k}" f' "{self.content_column}", ' # row[0] f' "{self.metadata_column}", ' # row[1] f' TO_NVARCHAR("{self.vector_column}"), ' # row[2] - f' {distance_func_name}("{self.vector_column}", TO_REAL_VECTOR ' - f" (ARRAY({embedding_as_str}))) AS CS " # row[3] + f' {distance_func_name}("{self.vector_column}", TO_REAL_VECTOR (?)) AS CS ' f'FROM "{self.table_name}"' ) order_str = f" order by CS {HANA_DISTANCE_FUNCTION[self.distance_strategy][1]}" where_str, query_tuple = self._create_where_by_filter(filter) + query_tuple = (embedding_as_str,) + tuple(query_tuple) sql_str = sql_str + where_str sql_str = sql_str + order_str try: @@ -512,7 +595,7 @@ def _process_filter_object(self, filter): # type: ignore[no-untyped-def] where_str_logical, query_tuple_logical, ) = self._process_filter_object(logical_operand) - where_str += where_str_logical + where_str += "(" + where_str_logical + ")" query_tuple += query_tuple_logical continue diff --git a/libs/community/langchain_community/vectorstores/lancedb.py b/libs/community/langchain_community/vectorstores/lancedb.py index d790fa169cc11..bcde354e8888e 100644 --- a/libs/community/langchain_community/vectorstores/lancedb.py +++ b/libs/community/langchain_community/vectorstores/lancedb.py @@ -43,7 +43,8 @@ class LanceDB(VectorStore): table_name: Name of the table to use. Defaults to ``vectorstore``. api_key: API key to use for LanceDB cloud database. region: Region to use for LanceDB cloud database. - mode: Mode to use for adding data to the table. Defaults to ``overwrite``. + mode: Mode to use for adding data to the table. Valid values are + ``append`` and ``overwrite``. Defaults to ``overwrite``. diff --git a/libs/community/langchain_community/vectorstores/marqo.py b/libs/community/langchain_community/vectorstores/marqo.py index a2331bc65d8f3..96b762662d7d8 100644 --- a/libs/community/langchain_community/vectorstores/marqo.py +++ b/libs/community/langchain_community/vectorstores/marqo.py @@ -109,9 +109,12 @@ def add_texts( List[str]: The list of ids that were added. """ - if self._client.index(self._index_name).get_settings()["index_defaults"][ - "treat_urls_and_pointers_as_images" - ]: + settings = self._client.index(self._index_name).get_settings() + if ( + "index_defaults" in settings + and settings["index_defaults"]["treat_urls_and_pointers_as_images"] + or settings.get("treat_urls_and_pointers_as_images") + ): raise ValueError( "Marqo.add_texts is disabled for multimodal indexes. To add documents " "with a multimodal index use the Python client for Marqo directly." diff --git a/libs/community/langchain_community/vectorstores/neo4j_vector.py b/libs/community/langchain_community/vectorstores/neo4j_vector.py index 7f7f3f97dd875..03d97a5a9d034 100644 --- a/libs/community/langchain_community/vectorstores/neo4j_vector.py +++ b/libs/community/langchain_community/vectorstores/neo4j_vector.py @@ -16,6 +16,7 @@ ) import numpy as np +from langchain_core._api.deprecation import deprecated from langchain_core.documents import Document from langchain_core.embeddings import Embeddings from langchain_core.utils import get_from_dict_or_env @@ -63,6 +64,11 @@ ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.SearchType", +) class SearchType(str, enum.Enum): """Enumerator of the Distance strategies.""" @@ -73,6 +79,11 @@ class SearchType(str, enum.Enum): DEFAULT_SEARCH_TYPE = SearchType.VECTOR +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.IndexType", +) class IndexType(str, enum.Enum): """Enumerator of the index types.""" @@ -83,6 +94,11 @@ class IndexType(str, enum.Enum): DEFAULT_INDEX_TYPE = IndexType.NODE +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector._get_search_index_query", +) def _get_search_index_query( search_type: SearchType, index_type: IndexType = DEFAULT_INDEX_TYPE ) -> str: @@ -119,6 +135,11 @@ def _get_search_index_query( ) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.check_if_not_null", +) def check_if_not_null(props: List[str], values: List[Any]) -> None: """Check if the values are not None or empty string""" for prop, value in zip(props, values): @@ -126,6 +147,11 @@ def check_if_not_null(props: List[str], values: List[Any]) -> None: raise ValueError(f"Parameter `{prop}` must not be None or empty string") +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.sort_by_index_name", +) def sort_by_index_name( lst: List[Dict[str, Any]], index_name: str ) -> List[Dict[str, Any]]: @@ -133,6 +159,11 @@ def sort_by_index_name( return sorted(lst, key=lambda x: x.get("name") != index_name) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.remove_lucene_chars", +) def remove_lucene_chars(text: str) -> str: """Remove Lucene special characters""" special_chars = [ @@ -161,6 +192,11 @@ def remove_lucene_chars(text: str) -> str: return text.strip() +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.dict_to_yaml_str", +) def dict_to_yaml_str(input_dict: Dict, indent: int = 0) -> str: """ Convert a dictionary to a YAML-like string without using external libraries. @@ -186,6 +222,11 @@ def dict_to_yaml_str(input_dict: Dict, indent: int = 0) -> str: return yaml_str +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.combine_queries", +) def combine_queries( input_queries: List[Tuple[str, Dict[str, Any]]], operator: str ) -> Tuple[str, Dict[str, Any]]: @@ -220,6 +261,11 @@ def combine_queries( return combined_query, combined_params +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.collect_params", +) def collect_params( input_data: List[Tuple[str, Dict[str, str]]], ) -> Tuple[List[str], Dict[str, Any]]: @@ -247,6 +293,11 @@ def collect_params( return (query_parts, params) +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector._handle_field_filter", +) def _handle_field_filter( field: str, value: Any, param_number: int = 1 ) -> Tuple[str, Dict]: @@ -348,6 +399,11 @@ def _handle_field_filter( raise NotImplementedError() +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.vectorstores.neo4j_vector.construct_metadata_filter", +) def construct_metadata_filter(filter: Dict[str, Any]) -> Tuple[str, Dict]: """Construct a metadata filter. @@ -430,6 +486,11 @@ def construct_metadata_filter(filter: Dict[str, Any]) -> Tuple[str, Dict]: raise ValueError("Got an empty dictionary for filters.") +@deprecated( + since="0.3.8", + removal="1.0", + alternative_import="langchain_neo4j.Neo4jVector", +) class Neo4jVector(VectorStore): """`Neo4j` vector index. diff --git a/libs/community/langchain_community/vectorstores/oraclevs.py b/libs/community/langchain_community/vectorstores/oraclevs.py index fa4be73e57c35..2ca39e9f6f1b5 100644 --- a/libs/community/langchain_community/vectorstores/oraclevs.py +++ b/libs/community/langchain_community/vectorstores/oraclevs.py @@ -762,7 +762,7 @@ def similarity_search_by_vector_returning_embeddings( k: int, filter: Optional[Dict[str, Any]] = None, **kwargs: Any, - ) -> List[Tuple[Document, float, np.ndarray[np.float32, Any]]]: + ) -> List[Tuple[Document, float, np.ndarray]]: embedding_arr: Any if self.insert_mode == "clob": embedding_arr = json.dumps(embedding) diff --git a/libs/community/langchain_community/vectorstores/pinecone.py b/libs/community/langchain_community/vectorstores/pinecone.py index 2cd41903dc814..7d960409e6b0f 100644 --- a/libs/community/langchain_community/vectorstores/pinecone.py +++ b/libs/community/langchain_community/vectorstores/pinecone.py @@ -31,7 +31,7 @@ def _import_pinecone() -> Any: except ImportError as e: raise ImportError( "Could not import pinecone python package. " - "Please install it with `pip install pinecone-client`." + "Please install it with `pip3 install pinecone`." ) from e return pinecone @@ -48,7 +48,7 @@ def _is_pinecone_v3() -> bool: class Pinecone(VectorStore): """`Pinecone` vector store. - To use, you should have the ``pinecone-client`` python package installed. + To use, you should have the ``pinecone`` python package installed. This version of Pinecone is deprecated. Please use `langchain_pinecone.Pinecone` instead. diff --git a/libs/community/langchain_community/vectorstores/redis/schema.py b/libs/community/langchain_community/vectorstores/redis/schema.py index 413951e1fffb4..cd1920799e6da 100644 --- a/libs/community/langchain_community/vectorstores/redis/schema.py +++ b/libs/community/langchain_community/vectorstores/redis/schema.py @@ -97,7 +97,7 @@ class RedisVectorField(RedisField): dims: int = Field(...) algorithm: object = Field(...) datatype: str = Field(default="FLOAT32") - distance_metric: RedisDistanceMetric = Field(default="COSINE") + distance_metric: RedisDistanceMetric = Field(default="COSINE") # type: ignore[assignment] initial_cap: Optional[int] = None @field_validator("algorithm", "datatype", "distance_metric", mode="before") diff --git a/libs/community/langchain_community/vectorstores/supabase.py b/libs/community/langchain_community/vectorstores/supabase.py index 4ff75b02f426e..b12f6c22e3c6b 100644 --- a/libs/community/langchain_community/vectorstores/supabase.py +++ b/libs/community/langchain_community/vectorstores/supabase.py @@ -270,7 +270,7 @@ def similarity_search_by_vector_returning_embeddings( k: int, filter: Optional[Dict[str, Any]] = None, postgrest_filter: Optional[str] = None, - ) -> List[Tuple[Document, float, np.ndarray[np.float32, Any]]]: + ) -> List[Tuple[Document, float, np.ndarray]]: match_documents_params = self.match_args(query, filter) query_builder = self._client.rpc(self.query_name, match_documents_params) diff --git a/libs/community/langchain_community/vectorstores/tencentvectordb.py b/libs/community/langchain_community/vectorstores/tencentvectordb.py index c3bda890fe241..7d408c21132af 100644 --- a/libs/community/langchain_community/vectorstores/tencentvectordb.py +++ b/libs/community/langchain_community/vectorstores/tencentvectordb.py @@ -6,7 +6,18 @@ import logging import time from enum import Enum -from typing import Any, Dict, Iterable, List, Optional, Sequence, Tuple, Union, cast +from typing import ( + Any, + Callable, + Dict, + Iterable, + List, + Optional, + Sequence, + Tuple, + Union, + cast, +) import numpy as np from langchain_core.documents import Document @@ -168,8 +179,8 @@ def __init__( tcvectordb = guard_import("tcvectordb") tcollection = guard_import("tcvectordb.model.collection") enum = guard_import("tcvectordb.model.enum") - - if t_vdb_embedding: + self.embedding_model = None + if embedding is None and t_vdb_embedding: embedding_model = [ model for model in enum.EmbeddingModel @@ -566,3 +577,17 @@ def max_marginal_relevance_search_by_vector( ) # Reorder the values and return. return [documents[x] for x in new_ordering if x != -1] + + def _select_relevance_score_fn(self) -> Callable[[float], float]: + metric_type = self.index_params.metric_type + if metric_type == "COSINE": + return self._cosine_relevance_score_fn + elif metric_type == "L2": + return self._euclidean_relevance_score_fn + elif metric_type == "IP": + return self._max_inner_product_relevance_score_fn + else: + raise ValueError( + "No supported normalization function" + f" for distance metric of type: {metric_type}." + ) diff --git a/libs/community/poetry.lock b/libs/community/poetry.lock index 7885dc8e2ebb4..13f550948f4d7 100644 --- a/libs/community/poetry.lock +++ b/libs/community/poetry.lock @@ -2,123 +2,109 @@ [[package]] name = "aiohappyeyeballs" -version = "2.4.3" +version = "2.4.4" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"}, - {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"}, + {file = "aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8"}, + {file = "aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745"}, ] [[package]] name = "aiohttp" -version = "3.10.10" +version = "3.11.10" description = "Async http client/server framework (asyncio)" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "aiohttp-3.10.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:be7443669ae9c016b71f402e43208e13ddf00912f47f623ee5994e12fc7d4b3f"}, - {file = "aiohttp-3.10.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7b06b7843929e41a94ea09eb1ce3927865387e3e23ebe108e0d0d09b08d25be9"}, - {file = "aiohttp-3.10.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:333cf6cf8e65f6a1e06e9eb3e643a0c515bb850d470902274239fea02033e9a8"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:274cfa632350225ce3fdeb318c23b4a10ec25c0e2c880eff951a3842cf358ac1"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9e5e4a85bdb56d224f412d9c98ae4cbd032cc4f3161818f692cd81766eee65a"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b606353da03edcc71130b52388d25f9a30a126e04caef1fd637e31683033abd"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ab5a5a0c7a7991d90446a198689c0535be89bbd6b410a1f9a66688f0880ec026"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:578a4b875af3e0daaf1ac6fa983d93e0bbfec3ead753b6d6f33d467100cdc67b"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8105fd8a890df77b76dd3054cddf01a879fc13e8af576805d667e0fa0224c35d"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3bcd391d083f636c06a68715e69467963d1f9600f85ef556ea82e9ef25f043f7"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fbc6264158392bad9df19537e872d476f7c57adf718944cc1e4495cbabf38e2a"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:e48d5021a84d341bcaf95c8460b152cfbad770d28e5fe14a768988c461b821bc"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:2609e9ab08474702cc67b7702dbb8a80e392c54613ebe80db7e8dbdb79837c68"}, - {file = "aiohttp-3.10.10-cp310-cp310-win32.whl", hash = "sha256:84afcdea18eda514c25bc68b9af2a2b1adea7c08899175a51fe7c4fb6d551257"}, - {file = "aiohttp-3.10.10-cp310-cp310-win_amd64.whl", hash = "sha256:9c72109213eb9d3874f7ac8c0c5fa90e072d678e117d9061c06e30c85b4cf0e6"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c30a0eafc89d28e7f959281b58198a9fa5e99405f716c0289b7892ca345fe45f"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:258c5dd01afc10015866114e210fb7365f0d02d9d059c3c3415382ab633fcbcb"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:15ecd889a709b0080f02721255b3f80bb261c2293d3c748151274dfea93ac871"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3935f82f6f4a3820270842e90456ebad3af15810cf65932bd24da4463bc0a4c"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:413251f6fcf552a33c981c4709a6bba37b12710982fec8e558ae944bfb2abd38"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d1720b4f14c78a3089562b8875b53e36b51c97c51adc53325a69b79b4b48ebcb"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:679abe5d3858b33c2cf74faec299fda60ea9de62916e8b67e625d65bf069a3b7"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:79019094f87c9fb44f8d769e41dbb664d6e8fcfd62f665ccce36762deaa0e911"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:fe2fb38c2ed905a2582948e2de560675e9dfbee94c6d5ccdb1301c6d0a5bf092"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:a3f00003de6eba42d6e94fabb4125600d6e484846dbf90ea8e48a800430cc142"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:1bbb122c557a16fafc10354b9d99ebf2f2808a660d78202f10ba9d50786384b9"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:30ca7c3b94708a9d7ae76ff281b2f47d8eaf2579cd05971b5dc681db8caac6e1"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:df9270660711670e68803107d55c2b5949c2e0f2e4896da176e1ecfc068b974a"}, - {file = "aiohttp-3.10.10-cp311-cp311-win32.whl", hash = "sha256:aafc8ee9b742ce75044ae9a4d3e60e3d918d15a4c2e08a6c3c3e38fa59b92d94"}, - {file = "aiohttp-3.10.10-cp311-cp311-win_amd64.whl", hash = "sha256:362f641f9071e5f3ee6f8e7d37d5ed0d95aae656adf4ef578313ee585b585959"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:9294bbb581f92770e6ed5c19559e1e99255e4ca604a22c5c6397b2f9dd3ee42c"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:a8fa23fe62c436ccf23ff930149c047f060c7126eae3ccea005f0483f27b2e28"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5c6a5b8c7926ba5d8545c7dd22961a107526562da31a7a32fa2456baf040939f"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:007ec22fbc573e5eb2fb7dec4198ef8f6bf2fe4ce20020798b2eb5d0abda6138"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9627cc1a10c8c409b5822a92d57a77f383b554463d1884008e051c32ab1b3742"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:50edbcad60d8f0e3eccc68da67f37268b5144ecc34d59f27a02f9611c1d4eec7"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a45d85cf20b5e0d0aa5a8dca27cce8eddef3292bc29d72dcad1641f4ed50aa16"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0b00807e2605f16e1e198f33a53ce3c4523114059b0c09c337209ae55e3823a8"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f2d4324a98062be0525d16f768a03e0bbb3b9fe301ceee99611dc9a7953124e6"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:438cd072f75bb6612f2aca29f8bd7cdf6e35e8f160bc312e49fbecab77c99e3a"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:baa42524a82f75303f714108fea528ccacf0386af429b69fff141ffef1c534f9"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a7d8d14fe962153fc681f6366bdec33d4356f98a3e3567782aac1b6e0e40109a"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c1277cd707c465cd09572a774559a3cc7c7a28802eb3a2a9472588f062097205"}, - {file = "aiohttp-3.10.10-cp312-cp312-win32.whl", hash = "sha256:59bb3c54aa420521dc4ce3cc2c3fe2ad82adf7b09403fa1f48ae45c0cbde6628"}, - {file = "aiohttp-3.10.10-cp312-cp312-win_amd64.whl", hash = "sha256:0e1b370d8007c4ae31ee6db7f9a2fe801a42b146cec80a86766e7ad5c4a259cf"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ad7593bb24b2ab09e65e8a1d385606f0f47c65b5a2ae6c551db67d6653e78c28"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:1eb89d3d29adaf533588f209768a9c02e44e4baf832b08118749c5fad191781d"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3fe407bf93533a6fa82dece0e74dbcaaf5d684e5a51862887f9eaebe6372cd79"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50aed5155f819873d23520919e16703fc8925e509abbb1a1491b0087d1cd969e"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4f05e9727ce409358baa615dbeb9b969db94324a79b5a5cea45d39bdb01d82e6"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3dffb610a30d643983aeb185ce134f97f290f8935f0abccdd32c77bed9388b42"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa6658732517ddabe22c9036479eabce6036655ba87a0224c612e1ae6af2087e"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:741a46d58677d8c733175d7e5aa618d277cd9d880301a380fd296975a9cdd7bc"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e00e3505cd80440f6c98c6d69269dcc2a119f86ad0a9fd70bccc59504bebd68a"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:ffe595f10566f8276b76dc3a11ae4bb7eba1aac8ddd75811736a15b0d5311414"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:bdfcf6443637c148c4e1a20c48c566aa694fa5e288d34b20fcdc58507882fed3"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:d183cf9c797a5291e8301790ed6d053480ed94070637bfaad914dd38b0981f67"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:77abf6665ae54000b98b3c742bc6ea1d1fb31c394bcabf8b5d2c1ac3ebfe7f3b"}, - {file = "aiohttp-3.10.10-cp313-cp313-win32.whl", hash = "sha256:4470c73c12cd9109db8277287d11f9dd98f77fc54155fc71a7738a83ffcc8ea8"}, - {file = "aiohttp-3.10.10-cp313-cp313-win_amd64.whl", hash = "sha256:486f7aabfa292719a2753c016cc3a8f8172965cabb3ea2e7f7436c7f5a22a151"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:1b66ccafef7336a1e1f0e389901f60c1d920102315a56df85e49552308fc0486"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:acd48d5b80ee80f9432a165c0ac8cbf9253eaddb6113269a5e18699b33958dbb"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:3455522392fb15ff549d92fbf4b73b559d5e43dc522588f7eb3e54c3f38beee7"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45c3b868724137f713a38376fef8120c166d1eadd50da1855c112fe97954aed8"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:da1dee8948d2137bb51fbb8a53cce6b1bcc86003c6b42565f008438b806cccd8"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c5ce2ce7c997e1971b7184ee37deb6ea9922ef5163c6ee5aa3c274b05f9e12fa"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:28529e08fde6f12eba8677f5a8608500ed33c086f974de68cc65ab218713a59d"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f7db54c7914cc99d901d93a34704833568d86c20925b2762f9fa779f9cd2e70f"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:03a42ac7895406220124c88911ebee31ba8b2d24c98507f4a8bf826b2937c7f2"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:7e338c0523d024fad378b376a79faff37fafb3c001872a618cde1d322400a572"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:038f514fe39e235e9fef6717fbf944057bfa24f9b3db9ee551a7ecf584b5b480"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:64f6c17757251e2b8d885d728b6433d9d970573586a78b78ba8929b0f41d045a"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:93429602396f3383a797a2a70e5f1de5df8e35535d7806c9f91df06f297e109b"}, - {file = "aiohttp-3.10.10-cp38-cp38-win32.whl", hash = "sha256:c823bc3971c44ab93e611ab1a46b1eafeae474c0c844aff4b7474287b75fe49c"}, - {file = "aiohttp-3.10.10-cp38-cp38-win_amd64.whl", hash = "sha256:54ca74df1be3c7ca1cf7f4c971c79c2daf48d9aa65dea1a662ae18926f5bc8ce"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:01948b1d570f83ee7bbf5a60ea2375a89dfb09fd419170e7f5af029510033d24"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9fc1500fd2a952c5c8e3b29aaf7e3cc6e27e9cfc0a8819b3bce48cc1b849e4cc"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f614ab0c76397661b90b6851a030004dac502e48260ea10f2441abd2207fbcc7"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:00819de9e45d42584bed046314c40ea7e9aea95411b38971082cad449392b08c"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:05646ebe6b94cc93407b3bf34b9eb26c20722384d068eb7339de802154d61bc5"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:998f3bd3cfc95e9424a6acd7840cbdd39e45bc09ef87533c006f94ac47296090"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d9010c31cd6fa59438da4e58a7f19e4753f7f264300cd152e7f90d4602449762"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ea7ffc6d6d6f8a11e6f40091a1040995cdff02cfc9ba4c2f30a516cb2633554"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:ef9c33cc5cbca35808f6c74be11eb7f5f6b14d2311be84a15b594bd3e58b5527"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:ce0cdc074d540265bfeb31336e678b4e37316849d13b308607efa527e981f5c2"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:597a079284b7ee65ee102bc3a6ea226a37d2b96d0418cc9047490f231dc09fe8"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:7789050d9e5d0c309c706953e5e8876e38662d57d45f936902e176d19f1c58ab"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:e7f8b04d83483577fd9200461b057c9f14ced334dcb053090cea1da9c8321a91"}, - {file = "aiohttp-3.10.10-cp39-cp39-win32.whl", hash = "sha256:c02a30b904282777d872266b87b20ed8cc0d1501855e27f831320f471d54d983"}, - {file = "aiohttp-3.10.10-cp39-cp39-win_amd64.whl", hash = "sha256:edfe3341033a6b53a5c522c802deb2079eee5cbfbb0af032a55064bd65c73a23"}, - {file = "aiohttp-3.10.10.tar.gz", hash = "sha256:0631dd7c9f0822cc61c88586ca76d5b5ada26538097d0f1df510b082bad3411a"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:cbad88a61fa743c5d283ad501b01c153820734118b65aee2bd7dbb735475ce0d"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:80886dac673ceaef499de2f393fc80bb4481a129e6cb29e624a12e3296cc088f"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:61b9bae80ed1f338c42f57c16918853dc51775fb5cb61da70d590de14d8b5fb4"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9e2e576caec5c6a6b93f41626c9c02fc87cd91538b81a3670b2e04452a63def6"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:02c13415b5732fb6ee7ff64583a5e6ed1c57aa68f17d2bda79c04888dfdc2769"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4cfce37f31f20800a6a6620ce2cdd6737b82e42e06e6e9bd1b36f546feb3c44f"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3bbbfff4c679c64e6e23cb213f57cc2c9165c9a65d63717108a644eb5a7398df"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:49c7dbbc1a559ae14fc48387a115b7d4bbc84b4a2c3b9299c31696953c2a5219"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:68386d78743e6570f054fe7949d6cb37ef2b672b4d3405ce91fafa996f7d9b4d"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9ef405356ba989fb57f84cac66f7b0260772836191ccefbb987f414bcd2979d9"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5d6958671b296febe7f5f859bea581a21c1d05430d1bbdcf2b393599b1cdce77"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:99b7920e7165be5a9e9a3a7f1b680f06f68ff0d0328ff4079e5163990d046767"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:0dc49f42422163efb7e6f1df2636fe3db72713f6cd94688e339dbe33fe06d61d"}, + {file = "aiohttp-3.11.10-cp310-cp310-win32.whl", hash = "sha256:40d1c7a7f750b5648642586ba7206999650208dbe5afbcc5284bcec6579c9b91"}, + {file = "aiohttp-3.11.10-cp310-cp310-win_amd64.whl", hash = "sha256:68ff6f48b51bd78ea92b31079817aff539f6c8fc80b6b8d6ca347d7c02384e33"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:77c4aa15a89847b9891abf97f3d4048f3c2d667e00f8a623c89ad2dccee6771b"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:909af95a72cedbefe5596f0bdf3055740f96c1a4baa0dd11fd74ca4de0b4e3f1"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:386fbe79863eb564e9f3615b959e28b222259da0c48fd1be5929ac838bc65683"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3de34936eb1a647aa919655ff8d38b618e9f6b7f250cc19a57a4bf7fd2062b6d"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0c9527819b29cd2b9f52033e7fb9ff08073df49b4799c89cb5754624ecd98299"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:65a96e3e03300b41f261bbfd40dfdbf1c301e87eab7cd61c054b1f2e7c89b9e8"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98f5635f7b74bcd4f6f72fcd85bea2154b323a9f05226a80bc7398d0c90763b0"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:03b6002e20938fc6ee0918c81d9e776bebccc84690e2b03ed132331cca065ee5"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6362cc6c23c08d18ddbf0e8c4d5159b5df74fea1a5278ff4f2c79aed3f4e9f46"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:3691ed7726fef54e928fe26344d930c0c8575bc968c3e239c2e1a04bd8cf7838"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31d5093d3acd02b31c649d3a69bb072d539d4c7659b87caa4f6d2bcf57c2fa2b"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:8b3cf2dc0f0690a33f2d2b2cb15db87a65f1c609f53c37e226f84edb08d10f52"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:fbbaea811a2bba171197b08eea288b9402faa2bab2ba0858eecdd0a4105753a3"}, + {file = "aiohttp-3.11.10-cp311-cp311-win32.whl", hash = "sha256:4b2c7ac59c5698a7a8207ba72d9e9c15b0fc484a560be0788b31312c2c5504e4"}, + {file = "aiohttp-3.11.10-cp311-cp311-win_amd64.whl", hash = "sha256:974d3a2cce5fcfa32f06b13ccc8f20c6ad9c51802bb7f829eae8a1845c4019ec"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:b78f053a7ecfc35f0451d961dacdc671f4bcbc2f58241a7c820e9d82559844cf"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ab7485222db0959a87fbe8125e233b5a6f01f4400785b36e8a7878170d8c3138"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:cf14627232dfa8730453752e9cdc210966490992234d77ff90bc8dc0dce361d5"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:076bc454a7e6fd646bc82ea7f98296be0b1219b5e3ef8a488afbdd8e81fbac50"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:482cafb7dc886bebeb6c9ba7925e03591a62ab34298ee70d3dd47ba966370d2c"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf3d1a519a324af764a46da4115bdbd566b3c73fb793ffb97f9111dbc684fc4d"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24213ba85a419103e641e55c27dc7ff03536c4873470c2478cce3311ba1eee7b"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b99acd4730ad1b196bfb03ee0803e4adac371ae8efa7e1cbc820200fc5ded109"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:14cdb5a9570be5a04eec2ace174a48ae85833c2aadc86de68f55541f66ce42ab"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:7e97d622cb083e86f18317282084bc9fbf261801b0192c34fe4b1febd9f7ae69"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:012f176945af138abc10c4a48743327a92b4ca9adc7a0e078077cdb5dbab7be0"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:44224d815853962f48fe124748227773acd9686eba6dc102578defd6fc99e8d9"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c87bf31b7fdab94ae3adbe4a48e711bfc5f89d21cf4c197e75561def39e223bc"}, + {file = "aiohttp-3.11.10-cp312-cp312-win32.whl", hash = "sha256:06a8e2ee1cbac16fe61e51e0b0c269400e781b13bcfc33f5425912391a542985"}, + {file = "aiohttp-3.11.10-cp312-cp312-win_amd64.whl", hash = "sha256:be2b516f56ea883a3e14dda17059716593526e10fb6303189aaf5503937db408"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:8cc5203b817b748adccb07f36390feb730b1bc5f56683445bfe924fc270b8816"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:5ef359ebc6949e3a34c65ce20230fae70920714367c63afd80ea0c2702902ccf"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9bca390cb247dbfaec3c664326e034ef23882c3f3bfa5fbf0b56cad0320aaca5"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:811f23b3351ca532af598405db1093f018edf81368e689d1b508c57dcc6b6a32"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ddf5f7d877615f6a1e75971bfa5ac88609af3b74796ff3e06879e8422729fd01"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6ab29b8a0beb6f8eaf1e5049252cfe74adbaafd39ba91e10f18caeb0e99ffb34"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c49a76c1038c2dd116fa443eba26bbb8e6c37e924e2513574856de3b6516be99"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7f3dc0e330575f5b134918976a645e79adf333c0a1439dcf6899a80776c9ab39"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:efb15a17a12497685304b2d976cb4939e55137df7b09fa53f1b6a023f01fcb4e"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:db1d0b28fcb7f1d35600150c3e4b490775251dea70f894bf15c678fdd84eda6a"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:15fccaf62a4889527539ecb86834084ecf6e9ea70588efde86e8bc775e0e7542"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:593c114a2221444f30749cc5e5f4012488f56bd14de2af44fe23e1e9894a9c60"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7852bbcb4d0d2f0c4d583f40c3bc750ee033265d80598d0f9cb6f372baa6b836"}, + {file = "aiohttp-3.11.10-cp313-cp313-win32.whl", hash = "sha256:65e55ca7debae8faaffee0ebb4b47a51b4075f01e9b641c31e554fd376595c6c"}, + {file = "aiohttp-3.11.10-cp313-cp313-win_amd64.whl", hash = "sha256:beb39a6d60a709ae3fb3516a1581777e7e8b76933bb88c8f4420d875bb0267c6"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:0580f2e12de2138f34debcd5d88894786453a76e98febaf3e8fe5db62d01c9bf"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a55d2ad345684e7c3dd2c20d2f9572e9e1d5446d57200ff630e6ede7612e307f"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:04814571cb72d65a6899db6099e377ed00710bf2e3eafd2985166f2918beaf59"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e44a9a3c053b90c6f09b1bb4edd880959f5328cf63052503f892c41ea786d99f"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:502a1464ccbc800b4b1995b302efaf426e8763fadf185e933c2931df7db9a199"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:613e5169f8ae77b1933e42e418a95931fb4867b2991fc311430b15901ed67079"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4cca22a61b7fe45da8fc73c3443150c3608750bbe27641fc7558ec5117b27fdf"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:86a5dfcc39309470bd7b68c591d84056d195428d5d2e0b5ccadfbaf25b026ebc"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:77ae58586930ee6b2b6f696c82cf8e78c8016ec4795c53e36718365f6959dc82"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:78153314f26d5abef3239b4a9af20c229c6f3ecb97d4c1c01b22c4f87669820c"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:98283b94cc0e11c73acaf1c9698dea80c830ca476492c0fe2622bd931f34b487"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:53bf2097e05c2accc166c142a2090e4c6fd86581bde3fd9b2d3f9e93dda66ac1"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:c5532f0441fc09c119e1dca18fbc0687e64fbeb45aa4d6a87211ceaee50a74c4"}, + {file = "aiohttp-3.11.10-cp39-cp39-win32.whl", hash = "sha256:47ad15a65fb41c570cd0ad9a9ff8012489e68176e7207ec7b82a0940dddfd8be"}, + {file = "aiohttp-3.11.10-cp39-cp39-win_amd64.whl", hash = "sha256:c6b9e6d7e41656d78e37ce754813fa44b455c3d0d0dced2a047def7dc5570b74"}, + {file = "aiohttp-3.11.10.tar.gz", hash = "sha256:b1fc6b45010a8d0ff9e88f9f2418c6fd408c99c211257334aff41597ebece42e"}, ] [package.dependencies] aiohappyeyeballs = ">=2.3.0" aiosignal = ">=1.1.2" -async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""} +async-timeout = {version = ">=4.0,<6.0", markers = "python_version < \"3.11\""} attrs = ">=17.3.0" frozenlist = ">=1.1.1" multidict = ">=4.5,<7.0" -yarl = ">=1.12.0,<2.0" +propcache = ">=0.2.0" +yarl = ">=1.17.0,<2.0" [package.extras] speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"] @@ -150,24 +136,24 @@ files = [ [[package]] name = "anyio" -version = "4.6.2.post1" +version = "4.7.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.9" files = [ - {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"}, - {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"}, + {file = "anyio-4.7.0-py3-none-any.whl", hash = "sha256:ea60c3723ab42ba6fff7e8ccb0488c898ec538ff4df1f1d5e642c3601d07e352"}, + {file = "anyio-4.7.0.tar.gz", hash = "sha256:2f834749c602966b7d456a7567cafcb309f96482b5081d14ac93ccd457f9dd48"}, ] [package.dependencies] exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} idna = ">=2.8" sniffio = ">=1.1" -typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} +typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] -doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"] +doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"] trio = ["trio (>=0.26.1)"] [[package]] @@ -259,21 +245,18 @@ test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock [[package]] name = "asttokens" -version = "2.4.1" +version = "3.0.0" description = "Annotate AST trees with source code positions" optional = false -python-versions = "*" +python-versions = ">=3.8" files = [ - {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"}, - {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"}, + {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"}, + {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"}, ] -[package.dependencies] -six = ">=1.12.0" - [package.extras] -astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"] -test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"] +astroid = ["astroid (>=2,<4)"] +test = ["astroid (>=2,<4)", "pytest", "pytest-cov", "pytest-xdist"] [[package]] name = "async-lru" @@ -701,73 +684,73 @@ test = ["pytest"] [[package]] name = "coverage" -version = "7.6.4" +version = "7.6.9" description = "Code coverage measurement for Python" optional = false python-versions = ">=3.9" files = [ - {file = "coverage-7.6.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5f8ae553cba74085db385d489c7a792ad66f7f9ba2ee85bfa508aeb84cf0ba07"}, - {file = "coverage-7.6.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8165b796df0bd42e10527a3f493c592ba494f16ef3c8b531288e3d0d72c1f6f0"}, - {file = "coverage-7.6.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c7c8b95bf47db6d19096a5e052ffca0a05f335bc63cef281a6e8fe864d450a72"}, - {file = "coverage-7.6.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ed9281d1b52628e81393f5eaee24a45cbd64965f41857559c2b7ff19385df51"}, - {file = "coverage-7.6.4-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0809082ee480bb8f7416507538243c8863ac74fd8a5d2485c46f0f7499f2b491"}, - {file = "coverage-7.6.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d541423cdd416b78626b55f123412fcf979d22a2c39fce251b350de38c15c15b"}, - {file = "coverage-7.6.4-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:58809e238a8a12a625c70450b48e8767cff9eb67c62e6154a642b21ddf79baea"}, - {file = "coverage-7.6.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:c9b8e184898ed014884ca84c70562b4a82cbc63b044d366fedc68bc2b2f3394a"}, - {file = "coverage-7.6.4-cp310-cp310-win32.whl", hash = "sha256:6bd818b7ea14bc6e1f06e241e8234508b21edf1b242d49831831a9450e2f35fa"}, - {file = "coverage-7.6.4-cp310-cp310-win_amd64.whl", hash = "sha256:06babbb8f4e74b063dbaeb74ad68dfce9186c595a15f11f5d5683f748fa1d172"}, - {file = "coverage-7.6.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:73d2b73584446e66ee633eaad1a56aad577c077f46c35ca3283cd687b7715b0b"}, - {file = "coverage-7.6.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:51b44306032045b383a7a8a2c13878de375117946d68dcb54308111f39775a25"}, - {file = "coverage-7.6.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3fb02fe73bed561fa12d279a417b432e5b50fe03e8d663d61b3d5990f29546"}, - {file = "coverage-7.6.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed8fe9189d2beb6edc14d3ad19800626e1d9f2d975e436f84e19efb7fa19469b"}, - {file = "coverage-7.6.4-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b369ead6527d025a0fe7bd3864e46dbee3aa8f652d48df6174f8d0bac9e26e0e"}, - {file = "coverage-7.6.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:ade3ca1e5f0ff46b678b66201f7ff477e8fa11fb537f3b55c3f0568fbfe6e718"}, - {file = "coverage-7.6.4-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:27fb4a050aaf18772db513091c9c13f6cb94ed40eacdef8dad8411d92d9992db"}, - {file = "coverage-7.6.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:4f704f0998911abf728a7783799444fcbbe8261c4a6c166f667937ae6a8aa522"}, - {file = "coverage-7.6.4-cp311-cp311-win32.whl", hash = "sha256:29155cd511ee058e260db648b6182c419422a0d2e9a4fa44501898cf918866cf"}, - {file = "coverage-7.6.4-cp311-cp311-win_amd64.whl", hash = "sha256:8902dd6a30173d4ef09954bfcb24b5d7b5190cf14a43170e386979651e09ba19"}, - {file = "coverage-7.6.4-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:12394842a3a8affa3ba62b0d4ab7e9e210c5e366fbac3e8b2a68636fb19892c2"}, - {file = "coverage-7.6.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2b6b4c83d8e8ea79f27ab80778c19bc037759aea298da4b56621f4474ffeb117"}, - {file = "coverage-7.6.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1d5b8007f81b88696d06f7df0cb9af0d3b835fe0c8dbf489bad70b45f0e45613"}, - {file = "coverage-7.6.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b57b768feb866f44eeed9f46975f3d6406380275c5ddfe22f531a2bf187eda27"}, - {file = "coverage-7.6.4-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5915fcdec0e54ee229926868e9b08586376cae1f5faa9bbaf8faf3561b393d52"}, - {file = "coverage-7.6.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0b58c672d14f16ed92a48db984612f5ce3836ae7d72cdd161001cc54512571f2"}, - {file = "coverage-7.6.4-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:2fdef0d83a2d08d69b1f2210a93c416d54e14d9eb398f6ab2f0a209433db19e1"}, - {file = "coverage-7.6.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8cf717ee42012be8c0cb205dbbf18ffa9003c4cbf4ad078db47b95e10748eec5"}, - {file = "coverage-7.6.4-cp312-cp312-win32.whl", hash = "sha256:7bb92c539a624cf86296dd0c68cd5cc286c9eef2d0c3b8b192b604ce9de20a17"}, - {file = "coverage-7.6.4-cp312-cp312-win_amd64.whl", hash = "sha256:1032e178b76a4e2b5b32e19d0fd0abbce4b58e77a1ca695820d10e491fa32b08"}, - {file = "coverage-7.6.4-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:023bf8ee3ec6d35af9c1c6ccc1d18fa69afa1cb29eaac57cb064dbb262a517f9"}, - {file = "coverage-7.6.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:b0ac3d42cb51c4b12df9c5f0dd2f13a4f24f01943627120ec4d293c9181219ba"}, - {file = "coverage-7.6.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f8fe4984b431f8621ca53d9380901f62bfb54ff759a1348cd140490ada7b693c"}, - {file = "coverage-7.6.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5fbd612f8a091954a0c8dd4c0b571b973487277d26476f8480bfa4b2a65b5d06"}, - {file = "coverage-7.6.4-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dacbc52de979f2823a819571f2e3a350a7e36b8cb7484cdb1e289bceaf35305f"}, - {file = "coverage-7.6.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:dab4d16dfef34b185032580e2f2f89253d302facba093d5fa9dbe04f569c4f4b"}, - {file = "coverage-7.6.4-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:862264b12ebb65ad8d863d51f17758b1684560b66ab02770d4f0baf2ff75da21"}, - {file = "coverage-7.6.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5beb1ee382ad32afe424097de57134175fea3faf847b9af002cc7895be4e2a5a"}, - {file = "coverage-7.6.4-cp313-cp313-win32.whl", hash = "sha256:bf20494da9653f6410213424f5f8ad0ed885e01f7e8e59811f572bdb20b8972e"}, - {file = "coverage-7.6.4-cp313-cp313-win_amd64.whl", hash = "sha256:182e6cd5c040cec0a1c8d415a87b67ed01193ed9ad458ee427741c7d8513d963"}, - {file = "coverage-7.6.4-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:a181e99301a0ae128493a24cfe5cfb5b488c4e0bf2f8702091473d033494d04f"}, - {file = "coverage-7.6.4-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:df57bdbeffe694e7842092c5e2e0bc80fff7f43379d465f932ef36f027179806"}, - {file = "coverage-7.6.4-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0bcd1069e710600e8e4cf27f65c90c7843fa8edfb4520fb0ccb88894cad08b11"}, - {file = "coverage-7.6.4-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:99b41d18e6b2a48ba949418db48159d7a2e81c5cc290fc934b7d2380515bd0e3"}, - {file = "coverage-7.6.4-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a6b1e54712ba3474f34b7ef7a41e65bd9037ad47916ccb1cc78769bae324c01a"}, - {file = "coverage-7.6.4-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:53d202fd109416ce011578f321460795abfe10bb901b883cafd9b3ef851bacfc"}, - {file = "coverage-7.6.4-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:c48167910a8f644671de9f2083a23630fbf7a1cb70ce939440cd3328e0919f70"}, - {file = "coverage-7.6.4-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:cc8ff50b50ce532de2fa7a7daae9dd12f0a699bfcd47f20945364e5c31799fef"}, - {file = "coverage-7.6.4-cp313-cp313t-win32.whl", hash = "sha256:b8d3a03d9bfcaf5b0141d07a88456bb6a4c3ce55c080712fec8418ef3610230e"}, - {file = "coverage-7.6.4-cp313-cp313t-win_amd64.whl", hash = "sha256:f3ddf056d3ebcf6ce47bdaf56142af51bb7fad09e4af310241e9db7a3a8022e1"}, - {file = "coverage-7.6.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9cb7fa111d21a6b55cbf633039f7bc2749e74932e3aa7cb7333f675a58a58bf3"}, - {file = "coverage-7.6.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:11a223a14e91a4693d2d0755c7a043db43d96a7450b4f356d506c2562c48642c"}, - {file = "coverage-7.6.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a413a096c4cbac202433c850ee43fa326d2e871b24554da8327b01632673a076"}, - {file = "coverage-7.6.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:00a1d69c112ff5149cabe60d2e2ee948752c975d95f1e1096742e6077affd376"}, - {file = "coverage-7.6.4-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1f76846299ba5c54d12c91d776d9605ae33f8ae2b9d1d3c3703cf2db1a67f2c0"}, - {file = "coverage-7.6.4-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:fe439416eb6380de434886b00c859304338f8b19f6f54811984f3420a2e03858"}, - {file = "coverage-7.6.4-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:0294ca37f1ba500667b1aef631e48d875ced93ad5e06fa665a3295bdd1d95111"}, - {file = "coverage-7.6.4-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:6f01ba56b1c0e9d149f9ac85a2f999724895229eb36bd997b61e62999e9b0901"}, - {file = "coverage-7.6.4-cp39-cp39-win32.whl", hash = "sha256:bc66f0bf1d7730a17430a50163bb264ba9ded56739112368ba985ddaa9c3bd09"}, - {file = "coverage-7.6.4-cp39-cp39-win_amd64.whl", hash = "sha256:c481b47f6b5845064c65a7bc78bc0860e635a9b055af0df46fdf1c58cebf8e8f"}, - {file = "coverage-7.6.4-pp39.pp310-none-any.whl", hash = "sha256:3c65d37f3a9ebb703e710befdc489a38683a5b152242664b973a7b7b22348a4e"}, - {file = "coverage-7.6.4.tar.gz", hash = "sha256:29fc0f17b1d3fea332f8001d4558f8214af7f1d87a345f3a133c901d60347c73"}, + {file = "coverage-7.6.9-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:85d9636f72e8991a1706b2b55b06c27545448baf9f6dbf51c4004609aacd7dcb"}, + {file = "coverage-7.6.9-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:608a7fd78c67bee8936378299a6cb9f5149bb80238c7a566fc3e6717a4e68710"}, + {file = "coverage-7.6.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:96d636c77af18b5cb664ddf12dab9b15a0cfe9c0bde715da38698c8cea748bfa"}, + {file = "coverage-7.6.9-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d75cded8a3cff93da9edc31446872d2997e327921d8eed86641efafd350e1df1"}, + {file = "coverage-7.6.9-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f7b15f589593110ae767ce997775d645b47e5cbbf54fd322f8ebea6277466cec"}, + {file = "coverage-7.6.9-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:44349150f6811b44b25574839b39ae35291f6496eb795b7366fef3bd3cf112d3"}, + {file = "coverage-7.6.9-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:d891c136b5b310d0e702e186d70cd16d1119ea8927347045124cb286b29297e5"}, + {file = "coverage-7.6.9-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:db1dab894cc139f67822a92910466531de5ea6034ddfd2b11c0d4c6257168073"}, + {file = "coverage-7.6.9-cp310-cp310-win32.whl", hash = "sha256:41ff7b0da5af71a51b53f501a3bac65fb0ec311ebed1632e58fc6107f03b9198"}, + {file = "coverage-7.6.9-cp310-cp310-win_amd64.whl", hash = "sha256:35371f8438028fdccfaf3570b31d98e8d9eda8bb1d6ab9473f5a390969e98717"}, + {file = "coverage-7.6.9-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:932fc826442132dde42ee52cf66d941f581c685a6313feebed358411238f60f9"}, + {file = "coverage-7.6.9-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:085161be5f3b30fd9b3e7b9a8c301f935c8313dcf928a07b116324abea2c1c2c"}, + {file = "coverage-7.6.9-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ccc660a77e1c2bf24ddbce969af9447a9474790160cfb23de6be4fa88e3951c7"}, + {file = "coverage-7.6.9-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c69e42c892c018cd3c8d90da61d845f50a8243062b19d228189b0224150018a9"}, + {file = "coverage-7.6.9-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0824a28ec542a0be22f60c6ac36d679e0e262e5353203bea81d44ee81fe9c6d4"}, + {file = "coverage-7.6.9-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:4401ae5fc52ad8d26d2a5d8a7428b0f0c72431683f8e63e42e70606374c311a1"}, + {file = "coverage-7.6.9-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:98caba4476a6c8d59ec1eb00c7dd862ba9beca34085642d46ed503cc2d440d4b"}, + {file = "coverage-7.6.9-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ee5defd1733fd6ec08b168bd4f5387d5b322f45ca9e0e6c817ea6c4cd36313e3"}, + {file = "coverage-7.6.9-cp311-cp311-win32.whl", hash = "sha256:f2d1ec60d6d256bdf298cb86b78dd715980828f50c46701abc3b0a2b3f8a0dc0"}, + {file = "coverage-7.6.9-cp311-cp311-win_amd64.whl", hash = "sha256:0d59fd927b1f04de57a2ba0137166d31c1a6dd9e764ad4af552912d70428c92b"}, + {file = "coverage-7.6.9-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:99e266ae0b5d15f1ca8d278a668df6f51cc4b854513daab5cae695ed7b721cf8"}, + {file = "coverage-7.6.9-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9901d36492009a0a9b94b20e52ebfc8453bf49bb2b27bca2c9706f8b4f5a554a"}, + {file = "coverage-7.6.9-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:abd3e72dd5b97e3af4246cdada7738ef0e608168de952b837b8dd7e90341f015"}, + {file = "coverage-7.6.9-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff74026a461eb0660366fb01c650c1d00f833a086b336bdad7ab00cc952072b3"}, + {file = "coverage-7.6.9-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65dad5a248823a4996724a88eb51d4b31587aa7aa428562dbe459c684e5787ae"}, + {file = "coverage-7.6.9-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:22be16571504c9ccea919fcedb459d5ab20d41172056206eb2994e2ff06118a4"}, + {file = "coverage-7.6.9-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:0f957943bc718b87144ecaee70762bc2bc3f1a7a53c7b861103546d3a403f0a6"}, + {file = "coverage-7.6.9-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0ae1387db4aecb1f485fb70a6c0148c6cdaebb6038f1d40089b1fc84a5db556f"}, + {file = "coverage-7.6.9-cp312-cp312-win32.whl", hash = "sha256:1a330812d9cc7ac2182586f6d41b4d0fadf9be9049f350e0efb275c8ee8eb692"}, + {file = "coverage-7.6.9-cp312-cp312-win_amd64.whl", hash = "sha256:b12c6b18269ca471eedd41c1b6a1065b2f7827508edb9a7ed5555e9a56dcfc97"}, + {file = "coverage-7.6.9-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:899b8cd4781c400454f2f64f7776a5d87bbd7b3e7f7bda0cb18f857bb1334664"}, + {file = "coverage-7.6.9-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:61f70dc68bd36810972e55bbbe83674ea073dd1dcc121040a08cdf3416c5349c"}, + {file = "coverage-7.6.9-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8a289d23d4c46f1a82d5db4abeb40b9b5be91731ee19a379d15790e53031c014"}, + {file = "coverage-7.6.9-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7e216d8044a356fc0337c7a2a0536d6de07888d7bcda76febcb8adc50bdbbd00"}, + {file = "coverage-7.6.9-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3c026eb44f744acaa2bda7493dad903aa5bf5fc4f2554293a798d5606710055d"}, + {file = "coverage-7.6.9-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e77363e8425325384f9d49272c54045bbed2f478e9dd698dbc65dbc37860eb0a"}, + {file = "coverage-7.6.9-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:777abfab476cf83b5177b84d7486497e034eb9eaea0d746ce0c1268c71652077"}, + {file = "coverage-7.6.9-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:447af20e25fdbe16f26e84eb714ba21d98868705cb138252d28bc400381f6ffb"}, + {file = "coverage-7.6.9-cp313-cp313-win32.whl", hash = "sha256:d872ec5aeb086cbea771c573600d47944eea2dcba8be5f3ee649bfe3cb8dc9ba"}, + {file = "coverage-7.6.9-cp313-cp313-win_amd64.whl", hash = "sha256:fd1213c86e48dfdc5a0cc676551db467495a95a662d2396ecd58e719191446e1"}, + {file = "coverage-7.6.9-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:ba9e7484d286cd5a43744e5f47b0b3fb457865baf07bafc6bee91896364e1419"}, + {file = "coverage-7.6.9-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:e5ea1cf0872ee455c03e5674b5bca5e3e68e159379c1af0903e89f5eba9ccc3a"}, + {file = "coverage-7.6.9-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2d10e07aa2b91835d6abec555ec8b2733347956991901eea6ffac295f83a30e4"}, + {file = "coverage-7.6.9-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:13a9e2d3ee855db3dd6ea1ba5203316a1b1fd8eaeffc37c5b54987e61e4194ae"}, + {file = "coverage-7.6.9-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c38bf15a40ccf5619fa2fe8f26106c7e8e080d7760aeccb3722664c8656b030"}, + {file = "coverage-7.6.9-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:d5275455b3e4627c8e7154feaf7ee0743c2e7af82f6e3b561967b1cca755a0be"}, + {file = "coverage-7.6.9-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:8f8770dfc6e2c6a2d4569f411015c8d751c980d17a14b0530da2d7f27ffdd88e"}, + {file = "coverage-7.6.9-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:8d2dfa71665a29b153a9681edb1c8d9c1ea50dfc2375fb4dac99ea7e21a0bcd9"}, + {file = "coverage-7.6.9-cp313-cp313t-win32.whl", hash = "sha256:5e6b86b5847a016d0fbd31ffe1001b63355ed309651851295315031ea7eb5a9b"}, + {file = "coverage-7.6.9-cp313-cp313t-win_amd64.whl", hash = "sha256:97ddc94d46088304772d21b060041c97fc16bdda13c6c7f9d8fcd8d5ae0d8611"}, + {file = "coverage-7.6.9-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:adb697c0bd35100dc690de83154627fbab1f4f3c0386df266dded865fc50a902"}, + {file = "coverage-7.6.9-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:be57b6d56e49c2739cdf776839a92330e933dd5e5d929966fbbd380c77f060be"}, + {file = "coverage-7.6.9-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f1592791f8204ae9166de22ba7e6705fa4ebd02936c09436a1bb85aabca3e599"}, + {file = "coverage-7.6.9-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4e12ae8cc979cf83d258acb5e1f1cf2f3f83524d1564a49d20b8bec14b637f08"}, + {file = "coverage-7.6.9-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb5555cff66c4d3d6213a296b360f9e1a8e323e74e0426b6c10ed7f4d021e464"}, + {file = "coverage-7.6.9-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:b9389a429e0e5142e69d5bf4a435dd688c14478a19bb901735cdf75e57b13845"}, + {file = "coverage-7.6.9-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:592ac539812e9b46046620341498caf09ca21023c41c893e1eb9dbda00a70cbf"}, + {file = "coverage-7.6.9-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a27801adef24cc30871da98a105f77995e13a25a505a0161911f6aafbd66e678"}, + {file = "coverage-7.6.9-cp39-cp39-win32.whl", hash = "sha256:8e3c3e38930cfb729cb8137d7f055e5a473ddaf1217966aa6238c88bd9fd50e6"}, + {file = "coverage-7.6.9-cp39-cp39-win_amd64.whl", hash = "sha256:e28bf44afa2b187cc9f41749138a64435bf340adfcacb5b2290c070ce99839d4"}, + {file = "coverage-7.6.9-pp39.pp310-none-any.whl", hash = "sha256:f3ca78518bc6bc92828cd11867b121891d75cae4ea9e908d72030609b996db1b"}, + {file = "coverage-7.6.9.tar.gz", hash = "sha256:4a8d8977b0c6ef5aeadcb644da9e69ae0dcfe66ec7f368c89c72e058bd71164d"}, ] [package.dependencies] @@ -842,37 +825,37 @@ typing-inspect = ">=0.4.0,<1" [[package]] name = "debugpy" -version = "1.8.8" +version = "1.8.9" description = "An implementation of the Debug Adapter Protocol for Python" optional = false python-versions = ">=3.8" files = [ - {file = "debugpy-1.8.8-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:e59b1607c51b71545cb3496876544f7186a7a27c00b436a62f285603cc68d1c6"}, - {file = "debugpy-1.8.8-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a6531d952b565b7cb2fbd1ef5df3d333cf160b44f37547a4e7cf73666aca5d8d"}, - {file = "debugpy-1.8.8-cp310-cp310-win32.whl", hash = "sha256:b01f4a5e5c5fb1d34f4ccba99a20ed01eabc45a4684f4948b5db17a319dfb23f"}, - {file = "debugpy-1.8.8-cp310-cp310-win_amd64.whl", hash = "sha256:535f4fb1c024ddca5913bb0eb17880c8f24ba28aa2c225059db145ee557035e9"}, - {file = "debugpy-1.8.8-cp311-cp311-macosx_14_0_universal2.whl", hash = "sha256:c399023146e40ae373753a58d1be0a98bf6397fadc737b97ad612886b53df318"}, - {file = "debugpy-1.8.8-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:09cc7b162586ea2171eea055985da2702b0723f6f907a423c9b2da5996ad67ba"}, - {file = "debugpy-1.8.8-cp311-cp311-win32.whl", hash = "sha256:eea8821d998ebeb02f0625dd0d76839ddde8cbf8152ebbe289dd7acf2cdc6b98"}, - {file = "debugpy-1.8.8-cp311-cp311-win_amd64.whl", hash = "sha256:d4483836da2a533f4b1454dffc9f668096ac0433de855f0c22cdce8c9f7e10c4"}, - {file = "debugpy-1.8.8-cp312-cp312-macosx_14_0_universal2.whl", hash = "sha256:0cc94186340be87b9ac5a707184ec8f36547fb66636d1029ff4f1cc020e53996"}, - {file = "debugpy-1.8.8-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:64674e95916e53c2e9540a056e5f489e0ad4872645399d778f7c598eacb7b7f9"}, - {file = "debugpy-1.8.8-cp312-cp312-win32.whl", hash = "sha256:5c6e885dbf12015aed73770f29dec7023cb310d0dc2ba8bfbeb5c8e43f80edc9"}, - {file = "debugpy-1.8.8-cp312-cp312-win_amd64.whl", hash = "sha256:19ffbd84e757a6ca0113574d1bf5a2298b3947320a3e9d7d8dc3377f02d9f864"}, - {file = "debugpy-1.8.8-cp313-cp313-macosx_14_0_universal2.whl", hash = "sha256:705cd123a773d184860ed8dae99becd879dfec361098edbefb5fc0d3683eb804"}, - {file = "debugpy-1.8.8-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:890fd16803f50aa9cb1a9b9b25b5ec321656dd6b78157c74283de241993d086f"}, - {file = "debugpy-1.8.8-cp313-cp313-win32.whl", hash = "sha256:90244598214bbe704aa47556ec591d2f9869ff9e042e301a2859c57106649add"}, - {file = "debugpy-1.8.8-cp313-cp313-win_amd64.whl", hash = "sha256:4b93e4832fd4a759a0c465c967214ed0c8a6e8914bced63a28ddb0dd8c5f078b"}, - {file = "debugpy-1.8.8-cp38-cp38-macosx_14_0_x86_64.whl", hash = "sha256:143ef07940aeb8e7316de48f5ed9447644da5203726fca378f3a6952a50a9eae"}, - {file = "debugpy-1.8.8-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f95651bdcbfd3b27a408869a53fbefcc2bcae13b694daee5f1365b1b83a00113"}, - {file = "debugpy-1.8.8-cp38-cp38-win32.whl", hash = "sha256:26b461123a030e82602a750fb24d7801776aa81cd78404e54ab60e8b5fecdad5"}, - {file = "debugpy-1.8.8-cp38-cp38-win_amd64.whl", hash = "sha256:f3cbf1833e644a3100eadb6120f25be8a532035e8245584c4f7532937edc652a"}, - {file = "debugpy-1.8.8-cp39-cp39-macosx_14_0_x86_64.whl", hash = "sha256:53709d4ec586b525724819dc6af1a7703502f7e06f34ded7157f7b1f963bb854"}, - {file = "debugpy-1.8.8-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a9c013077a3a0000e83d97cf9cc9328d2b0bbb31f56b0e99ea3662d29d7a6a2"}, - {file = "debugpy-1.8.8-cp39-cp39-win32.whl", hash = "sha256:ffe94dd5e9a6739a75f0b85316dc185560db3e97afa6b215628d1b6a17561cb2"}, - {file = "debugpy-1.8.8-cp39-cp39-win_amd64.whl", hash = "sha256:5c0e5a38c7f9b481bf31277d2f74d2109292179081f11108e668195ef926c0f9"}, - {file = "debugpy-1.8.8-py2.py3-none-any.whl", hash = "sha256:ec684553aba5b4066d4de510859922419febc710df7bba04fe9e7ef3de15d34f"}, - {file = "debugpy-1.8.8.zip", hash = "sha256:e6355385db85cbd666be703a96ab7351bc9e6c61d694893206f8001e22aee091"}, + {file = "debugpy-1.8.9-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:cfe1e6c6ad7178265f74981edf1154ffce97b69005212fbc90ca22ddfe3d017e"}, + {file = "debugpy-1.8.9-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ada7fb65102a4d2c9ab62e8908e9e9f12aed9d76ef44880367bc9308ebe49a0f"}, + {file = "debugpy-1.8.9-cp310-cp310-win32.whl", hash = "sha256:c36856343cbaa448171cba62a721531e10e7ffb0abff838004701454149bc037"}, + {file = "debugpy-1.8.9-cp310-cp310-win_amd64.whl", hash = "sha256:17c5e0297678442511cf00a745c9709e928ea4ca263d764e90d233208889a19e"}, + {file = "debugpy-1.8.9-cp311-cp311-macosx_14_0_universal2.whl", hash = "sha256:b74a49753e21e33e7cf030883a92fa607bddc4ede1aa4145172debc637780040"}, + {file = "debugpy-1.8.9-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:62d22dacdb0e296966d7d74a7141aaab4bec123fa43d1a35ddcb39bf9fd29d70"}, + {file = "debugpy-1.8.9-cp311-cp311-win32.whl", hash = "sha256:8138efff315cd09b8dcd14226a21afda4ca582284bf4215126d87342bba1cc66"}, + {file = "debugpy-1.8.9-cp311-cp311-win_amd64.whl", hash = "sha256:ff54ef77ad9f5c425398efb150239f6fe8e20c53ae2f68367eba7ece1e96226d"}, + {file = "debugpy-1.8.9-cp312-cp312-macosx_14_0_universal2.whl", hash = "sha256:957363d9a7a6612a37458d9a15e72d03a635047f946e5fceee74b50d52a9c8e2"}, + {file = "debugpy-1.8.9-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5e565fc54b680292b418bb809f1386f17081d1346dca9a871bf69a8ac4071afe"}, + {file = "debugpy-1.8.9-cp312-cp312-win32.whl", hash = "sha256:3e59842d6c4569c65ceb3751075ff8d7e6a6ada209ceca6308c9bde932bcef11"}, + {file = "debugpy-1.8.9-cp312-cp312-win_amd64.whl", hash = "sha256:66eeae42f3137eb428ea3a86d4a55f28da9bd5a4a3d369ba95ecc3a92c1bba53"}, + {file = "debugpy-1.8.9-cp313-cp313-macosx_14_0_universal2.whl", hash = "sha256:957ecffff80d47cafa9b6545de9e016ae8c9547c98a538ee96ab5947115fb3dd"}, + {file = "debugpy-1.8.9-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1efbb3ff61487e2c16b3e033bc8595aea578222c08aaf3c4bf0f93fadbd662ee"}, + {file = "debugpy-1.8.9-cp313-cp313-win32.whl", hash = "sha256:7c4d65d03bee875bcb211c76c1d8f10f600c305dbd734beaed4077e902606fee"}, + {file = "debugpy-1.8.9-cp313-cp313-win_amd64.whl", hash = "sha256:e46b420dc1bea64e5bbedd678148be512442bc589b0111bd799367cde051e71a"}, + {file = "debugpy-1.8.9-cp38-cp38-macosx_14_0_x86_64.whl", hash = "sha256:472a3994999fe6c0756945ffa359e9e7e2d690fb55d251639d07208dbc37caea"}, + {file = "debugpy-1.8.9-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:365e556a4772d7d0d151d7eb0e77ec4db03bcd95f26b67b15742b88cacff88e9"}, + {file = "debugpy-1.8.9-cp38-cp38-win32.whl", hash = "sha256:54a7e6d3014c408eb37b0b06021366ee985f1539e12fe49ca2ee0d392d9ceca5"}, + {file = "debugpy-1.8.9-cp38-cp38-win_amd64.whl", hash = "sha256:8e99c0b1cc7bf86d83fb95d5ccdc4ad0586d4432d489d1f54e4055bcc795f693"}, + {file = "debugpy-1.8.9-cp39-cp39-macosx_14_0_x86_64.whl", hash = "sha256:7e8b079323a56f719977fde9d8115590cb5e7a1cba2fcee0986ef8817116e7c1"}, + {file = "debugpy-1.8.9-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6953b335b804a41f16a192fa2e7851bdcfd92173cbb2f9f777bb934f49baab65"}, + {file = "debugpy-1.8.9-cp39-cp39-win32.whl", hash = "sha256:7e646e62d4602bb8956db88b1e72fe63172148c1e25c041e03b103a25f36673c"}, + {file = "debugpy-1.8.9-cp39-cp39-win_amd64.whl", hash = "sha256:3d9755e77a2d680ce3d2c5394a444cf42be4a592caaf246dbfbdd100ffcf7ae5"}, + {file = "debugpy-1.8.9-py2.py3-none-any.whl", hash = "sha256:cc37a6c9987ad743d9c3a14fa1b1a14b7e4e6041f9dd0c8abf8895fe7a97b899"}, + {file = "debugpy-1.8.9.zip", hash = "sha256:1339e14c7d980407248f09824d1b25ff5c5616651689f1e0f0e51bdead3ea13e"}, ] [[package]] @@ -960,13 +943,13 @@ files = [ [[package]] name = "duckdb-engine" -version = "0.11.5" +version = "0.13.6" description = "SQLAlchemy driver for duckdb" optional = false python-versions = "<4,>=3.8" files = [ - {file = "duckdb_engine-0.11.5-py3-none-any.whl", hash = "sha256:b227fcb1380a9f5b1f4878af82fd862e8aafd68e6e93179025ac48c7f3aa64f7"}, - {file = "duckdb_engine-0.11.5.tar.gz", hash = "sha256:a9419647b0cf480b4ad73add05d30cc6762c7d542ec14a0d4b477f8a96a58892"}, + {file = "duckdb_engine-0.13.6-py3-none-any.whl", hash = "sha256:cedd44252cce5f42de88752026925154a566c407987116a242d250642904ba84"}, + {file = "duckdb_engine-0.13.6.tar.gz", hash = "sha256:221ec7759e157fd8d4fcb0bd64f603c5a4b1889186f30d805a91b10a73f8c59a"}, ] [package.dependencies] @@ -1004,13 +987,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth [[package]] name = "fastjsonschema" -version = "2.20.0" +version = "2.21.1" description = "Fastest Python implementation of JSON schema" optional = false python-versions = "*" files = [ - {file = "fastjsonschema-2.20.0-py3-none-any.whl", hash = "sha256:5875f0b0fa7a0043a91e93a9b8f793bcbbba9691e7fd83dca95c28ba26d21f0a"}, - {file = "fastjsonschema-2.20.0.tar.gz", hash = "sha256:3d48fc5300ee96f5d116f10fe6f28d938e6008f59a6a025c2649475b87f76a23"}, + {file = "fastjsonschema-2.21.1-py3-none-any.whl", hash = "sha256:c9e5b7e908310918cf494a434eeb31384dd84a98b57a30bcb1f535015b554667"}, + {file = "fastjsonschema-2.21.1.tar.gz", hash = "sha256:794d4f0a58f848961ba16af7b9c85a3e88cd360df008c59aac6fc5ae9323b5d4"}, ] [package.extras] @@ -1241,13 +1224,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.6" +version = "1.0.7" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"}, - {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"}, + {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, + {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, ] [package.dependencies] @@ -1262,13 +1245,13 @@ trio = ["trio (>=0.22.0,<1.0)"] [[package]] name = "httpx" -version = "0.27.2" +version = "0.28.1" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"}, - {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"}, + {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"}, + {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"}, ] [package.dependencies] @@ -1276,7 +1259,6 @@ anyio = "*" certifi = "*" httpcore = "==1.*" idna = "*" -sniffio = "*" [package.extras] brotli = ["brotli", "brotlicffi"] @@ -1487,13 +1469,13 @@ i18n = ["Babel (>=2.7)"] [[package]] name = "json5" -version = "0.9.28" +version = "0.10.0" description = "A Python implementation of the JSON5 data format." optional = false python-versions = ">=3.8.0" files = [ - {file = "json5-0.9.28-py3-none-any.whl", hash = "sha256:29c56f1accdd8bc2e037321237662034a7e07921e2b7223281a5ce2c46f0c4df"}, - {file = "json5-0.9.28.tar.gz", hash = "sha256:1f82f36e615bc5b42f1bbd49dbc94b12563c56408c6ffa06414ea310890e9a6e"}, + {file = "json5-0.10.0-py3-none-any.whl", hash = "sha256:19b23410220a7271e8377f81ba8aacba2fdd56947fbb137ee5977cbe1f5e8dfa"}, + {file = "json5-0.10.0.tar.gz", hash = "sha256:e66941c8f0a02026943c52c2eb34ebeb2a6f819a0be05920a6f5243cd30fd559"}, ] [package.extras] @@ -1750,18 +1732,18 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (> [[package]] name = "jupyterlab" -version = "4.3.0" +version = "4.3.2" description = "JupyterLab computational environment" optional = false python-versions = ">=3.8" files = [ - {file = "jupyterlab-4.3.0-py3-none-any.whl", hash = "sha256:f67e1095ad61ae04349024f0b40345062ab108a0c6998d9810fec6a3c1a70cd5"}, - {file = "jupyterlab-4.3.0.tar.gz", hash = "sha256:7c6835cbf8df0af0ec8a39332e85ff11693fb9a468205343b4fc0bfbc74817e5"}, + {file = "jupyterlab-4.3.2-py3-none-any.whl", hash = "sha256:e87100cbab8b886ff7a4f325c856100ba6fdfe916162a85409daf0e707e19d1d"}, + {file = "jupyterlab-4.3.2.tar.gz", hash = "sha256:3c0a6882dbddcc0a7bfdd5e2236f351b2b263e48780236e6996c2aca13ac5b22"}, ] [package.dependencies] async-lru = ">=1.0.0" -httpx = ">=0.25.0" +httpx = ">=0.28.0,<0.29.0" importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""} ipykernel = ">=6.5.0" jinja2 = ">=3.0.3" @@ -1771,7 +1753,7 @@ jupyter-server = ">=2.4.0,<3" jupyterlab-server = ">=2.27.1,<3" notebook-shim = ">=0.2" packaging = "*" -setuptools = ">=40.1.0" +setuptools = ">=40.8.0" tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""} tornado = ">=6.2.0" traitlets = "*" @@ -1833,7 +1815,7 @@ files = [ [[package]] name = "langchain" -version = "0.3.7" +version = "0.3.10" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -1843,12 +1825,12 @@ develop = true [package.dependencies] aiohttp = "^3.8.3" async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""} -langchain-core = "^0.3.15" +langchain-core = "^0.3.22" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" numpy = [ {version = ">=1.22.4,<2", markers = "python_version < \"3.12\""}, - {version = ">=1.26.2,<2", markers = "python_version >= \"3.12\""}, + {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}, ] pydantic = "^2.7.4" PyYAML = ">=5.3" @@ -1862,7 +1844,7 @@ url = "../langchain" [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.22" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -1887,7 +1869,7 @@ url = "../core" [[package]] name = "langchain-tests" -version = "0.3.1" +version = "0.3.5" description = "Standard tests for LangChain implementations" optional = false python-versions = ">=3.9,<4.0" @@ -1895,9 +1877,15 @@ files = [] develop = true [package.dependencies] -httpx = "^0.27.0" -langchain-core = "^0.3.15" +httpx = ">=0.25.0,<1" +langchain-core = "^0.3.21" +numpy = [ + {version = ">=1.24.0,<2.0.0", markers = "python_version < \"3.12\""}, + {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}, +] pytest = ">=7,<9" +pytest-asyncio = ">=0.20,<1" +pytest-socket = ">=0.6.0,<1" syrupy = "^4" [package.source] @@ -1922,18 +1910,18 @@ url = "../text-splitters" [[package]] name = "langsmith" -version = "0.1.142" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.142-py3-none-any.whl", hash = "sha256:f639ca23c9a0bb77af5fb881679b2f66ff1f21f19d0bebf4e51375e7585a8b38"}, - {file = "langsmith-0.1.142.tar.gz", hash = "sha256:f8a84d100f3052233ff0a1d66ae14c5dfc20b7e41a1601de011384f16ee6cb82"}, + {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"}, + {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -1941,6 +1929,9 @@ pydantic = [ requests = ">=2,<3" requests-toolbelt = ">=1.0.0,<2.0.0" +[package.extras] +langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"] + [[package]] name = "lark" version = "1.2.2" @@ -2257,13 +2248,13 @@ types-protobuf = ">=4.24" [[package]] name = "nbclient" -version = "0.10.0" +version = "0.10.1" description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." optional = false python-versions = ">=3.8.0" files = [ - {file = "nbclient-0.10.0-py3-none-any.whl", hash = "sha256:f13e3529332a1f1f81d82a53210322476a168bb7090a0289c795fe9cc11c9d3f"}, - {file = "nbclient-0.10.0.tar.gz", hash = "sha256:4b3f1b7dba531e498449c4db4f53da339c91d449dc11e9af3a43b4eb5c5abb09"}, + {file = "nbclient-0.10.1-py3-none-any.whl", hash = "sha256:949019b9240d66897e442888cfb618f69ef23dc71c01cb5fced8499c2cfc084d"}, + {file = "nbclient-0.10.1.tar.gz", hash = "sha256:3e93e348ab27e712acd46fccd809139e356eb9a31aab641d1a7991a6eb4e6f68"}, ] [package.dependencies] @@ -2274,7 +2265,7 @@ traitlets = ">=5.4" [package.extras] dev = ["pre-commit"] -docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"] +docs = ["autodoc-traits", "flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "mock", "moto", "myst-parser", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling", "testpath", "xmltodict"] test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"] [[package]] @@ -2349,26 +2340,26 @@ files = [ [[package]] name = "notebook" -version = "7.0.7" +version = "7.3.1" description = "Jupyter Notebook - A web-based notebook environment for interactive computing" optional = false python-versions = ">=3.8" files = [ - {file = "notebook-7.0.7-py3-none-any.whl", hash = "sha256:289b606d7e173f75a18beb1406ef411b43f97f7a9c55ba03efa3622905a62346"}, - {file = "notebook-7.0.7.tar.gz", hash = "sha256:3bcff00c17b3ac142ef5f436d50637d936b274cfa0b41f6ac0175363de9b4e09"}, + {file = "notebook-7.3.1-py3-none-any.whl", hash = "sha256:212e1486b2230fe22279043f33c7db5cf9a01d29feb063a85cb139747b7c9483"}, + {file = "notebook-7.3.1.tar.gz", hash = "sha256:84381c2a82d867517fd25b86e986dae1fe113a70b98f03edff9b94e499fec8fa"}, ] [package.dependencies] jupyter-server = ">=2.4.0,<3" -jupyterlab = ">=4.0.2,<5" -jupyterlab-server = ">=2.22.1,<3" +jupyterlab = ">=4.3.2,<4.4" +jupyterlab-server = ">=2.27.1,<3" notebook-shim = ">=0.2,<0.3" tornado = ">=6.2.0" [package.extras] dev = ["hatch", "pre-commit"] docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"] -test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.22.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"] +test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"] [[package]] name = "notebook-shim" @@ -2432,71 +2423,152 @@ files = [ {file = "numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010"}, ] +[[package]] +name = "numpy" +version = "2.1.3" +description = "Fundamental package for array computing in Python" +optional = false +python-versions = ">=3.10" +files = [ + {file = "numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c894b4305373b9c5576d7a12b473702afdf48ce5369c074ba304cc5ad8730dff"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b47fbb433d3260adcd51eb54f92a2ffbc90a4595f8970ee00e064c644ac788f5"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:825656d0743699c529c5943554d223c021ff0494ff1442152ce887ef4f7561a1"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:6a4825252fcc430a182ac4dee5a505053d262c807f8a924603d411f6718b88fd"}, + {file = "numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e711e02f49e176a01d0349d82cb5f05ba4db7d5e7e0defd026328e5cfb3226d3"}, + {file = "numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:78574ac2d1a4a02421f25da9559850d59457bac82f2b8d7a44fe83a64f770098"}, + {file = "numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:c7662f0e3673fe4e832fe07b65c50342ea27d989f92c80355658c7f888fcc83c"}, + {file = "numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:fa2d1337dc61c8dc417fbccf20f6d1e139896a30721b7f1e832b2bb6ef4eb6c4"}, + {file = "numpy-2.1.3-cp310-cp310-win32.whl", hash = "sha256:72dcc4a35a8515d83e76b58fdf8113a5c969ccd505c8a946759b24e3182d1f23"}, + {file = "numpy-2.1.3-cp310-cp310-win_amd64.whl", hash = "sha256:ecc76a9ba2911d8d37ac01de72834d8849e55473457558e12995f4cd53e778e0"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4d1167c53b93f1f5d8a139a742b3c6f4d429b54e74e6b57d0eff40045187b15d"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c80e4a09b3d95b4e1cac08643f1152fa71a0a821a2d4277334c88d54b2219a41"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:576a1c1d25e9e02ed7fa5477f30a127fe56debd53b8d2c89d5578f9857d03ca9"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:973faafebaae4c0aaa1a1ca1ce02434554d67e628b8d805e61f874b84e136b09"}, + {file = "numpy-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:762479be47a4863e261a840e8e01608d124ee1361e48b96916f38b119cfda04a"}, + {file = "numpy-2.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc6f24b3d1ecc1eebfbf5d6051faa49af40b03be1aaa781ebdadcbc090b4539b"}, + {file = "numpy-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:17ee83a1f4fef3c94d16dc1802b998668b5419362c8a4f4e8a491de1b41cc3ee"}, + {file = "numpy-2.1.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:15cb89f39fa6d0bdfb600ea24b250e5f1a3df23f901f51c8debaa6a5d122b2f0"}, + {file = "numpy-2.1.3-cp311-cp311-win32.whl", hash = "sha256:d9beb777a78c331580705326d2367488d5bc473b49a9bc3036c154832520aca9"}, + {file = "numpy-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:d89dd2b6da69c4fff5e39c28a382199ddedc3a5be5390115608345dec660b9e2"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f55ba01150f52b1027829b50d70ef1dafd9821ea82905b63936668403c3b471e"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:13138eadd4f4da03074851a698ffa7e405f41a0845a6b1ad135b81596e4e9958"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:a6b46587b14b888e95e4a24d7b13ae91fa22386c199ee7b418f449032b2fa3b8"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:0fa14563cc46422e99daef53d725d0c326e99e468a9320a240affffe87852564"}, + {file = "numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8637dcd2caa676e475503d1f8fdb327bc495554e10838019651b76d17b98e512"}, + {file = "numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2312b2aa89e1f43ecea6da6ea9a810d06aae08321609d8dc0d0eda6d946a541b"}, + {file = "numpy-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a38c19106902bb19351b83802531fea19dee18e5b37b36454f27f11ff956f7fc"}, + {file = "numpy-2.1.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:02135ade8b8a84011cbb67dc44e07c58f28575cf9ecf8ab304e51c05528c19f0"}, + {file = "numpy-2.1.3-cp312-cp312-win32.whl", hash = "sha256:e6988e90fcf617da2b5c78902fe8e668361b43b4fe26dbf2d7b0f8034d4cafb9"}, + {file = "numpy-2.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:0d30c543f02e84e92c4b1f415b7c6b5326cbe45ee7882b6b77db7195fb971e3a"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:96fe52fcdb9345b7cd82ecd34547fca4321f7656d500eca497eb7ea5a926692f"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f653490b33e9c3a4c1c01d41bc2aef08f9475af51146e4a7710c450cf9761598"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:dc258a761a16daa791081d026f0ed4399b582712e6fc887a95af09df10c5ca57"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:016d0f6f5e77b0f0d45d77387ffa4bb89816b57c835580c3ce8e099ef830befe"}, + {file = "numpy-2.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c181ba05ce8299c7aa3125c27b9c2167bca4a4445b7ce73d5febc411ca692e43"}, + {file = "numpy-2.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5641516794ca9e5f8a4d17bb45446998c6554704d888f86df9b200e66bdcce56"}, + {file = "numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ea4dedd6e394a9c180b33c2c872b92f7ce0f8e7ad93e9585312b0c5a04777a4a"}, + {file = "numpy-2.1.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:b0df3635b9c8ef48bd3be5f862cf71b0a4716fa0e702155c45067c6b711ddcef"}, + {file = "numpy-2.1.3-cp313-cp313-win32.whl", hash = "sha256:50ca6aba6e163363f132b5c101ba078b8cbd3fa92c7865fd7d4d62d9779ac29f"}, + {file = "numpy-2.1.3-cp313-cp313-win_amd64.whl", hash = "sha256:747641635d3d44bcb380d950679462fae44f54b131be347d5ec2bce47d3df9ed"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:996bb9399059c5b82f76b53ff8bb686069c05acc94656bb259b1d63d04a9506f"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:45966d859916ad02b779706bb43b954281db43e185015df6eb3323120188f9e4"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:baed7e8d7481bfe0874b566850cb0b85243e982388b7b23348c6db2ee2b2ae8e"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:a9f7f672a3388133335589cfca93ed468509cb7b93ba3105fce780d04a6576a0"}, + {file = "numpy-2.1.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7aac50327da5d208db2eec22eb11e491e3fe13d22653dce51b0f4109101b408"}, + {file = "numpy-2.1.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4394bc0dbd074b7f9b52024832d16e019decebf86caf909d94f6b3f77a8ee3b6"}, + {file = "numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl", hash = "sha256:50d18c4358a0a8a53f12a8ba9d772ab2d460321e6a93d6064fc22443d189853f"}, + {file = "numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:14e253bd43fc6b37af4921b10f6add6925878a42a0c5fe83daee390bca80bc17"}, + {file = "numpy-2.1.3-cp313-cp313t-win32.whl", hash = "sha256:08788d27a5fd867a663f6fc753fd7c3ad7e92747efc73c53bca2f19f8bc06f48"}, + {file = "numpy-2.1.3-cp313-cp313t-win_amd64.whl", hash = "sha256:2564fbdf2b99b3f815f2107c1bbc93e2de8ee655a69c261363a1172a79a257d4"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:4f2015dfe437dfebbfce7c85c7b53d81ba49e71ba7eadbf1df40c915af75979f"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:3522b0dfe983a575e6a9ab3a4a4dfe156c3e428468ff08ce582b9bb6bd1d71d4"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c006b607a865b07cd981ccb218a04fc86b600411d83d6fc261357f1c0966755d"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:e14e26956e6f1696070788252dcdff11b4aca4c3e8bd166e0df1bb8f315a67cb"}, + {file = "numpy-2.1.3.tar.gz", hash = "sha256:aa08e04e08aaf974d4458def539dece0d28146d866a39da5639596f4921fd761"}, +] + [[package]] name = "orjson" -version = "3.10.11" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.11-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6dade64687f2bd7c090281652fe18f1151292d567a9302b34c2dbb92a3872f1f"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82f07c550a6ccd2b9290849b22316a609023ed851a87ea888c0456485a7d196a"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd9a187742d3ead9df2e49240234d728c67c356516cf4db018833a86f20ec18c"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:77b0fed6f209d76c1c39f032a70df2d7acf24b1812ca3e6078fd04e8972685a3"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:63fc9d5fe1d4e8868f6aae547a7b8ba0a2e592929245fff61d633f4caccdcdd6"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65cd3e3bb4fbb4eddc3c1e8dce10dc0b73e808fcb875f9fab40c81903dd9323e"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6f67c570602300c4befbda12d153113b8974a3340fdcf3d6de095ede86c06d92"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:1f39728c7f7d766f1f5a769ce4d54b5aaa4c3f92d5b84817053cc9995b977acc"}, - {file = "orjson-3.10.11-cp310-none-win32.whl", hash = "sha256:1789d9db7968d805f3d94aae2c25d04014aae3a2fa65b1443117cd462c6da647"}, - {file = "orjson-3.10.11-cp310-none-win_amd64.whl", hash = "sha256:5576b1e5a53a5ba8f8df81872bb0878a112b3ebb1d392155f00f54dd86c83ff6"}, - {file = "orjson-3.10.11-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1444f9cb7c14055d595de1036f74ecd6ce15f04a715e73f33bb6326c9cef01b6"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdec57fe3b4bdebcc08a946db3365630332dbe575125ff3d80a3272ebd0ddafe"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4eed32f33a0ea6ef36ccc1d37f8d17f28a1d6e8eefae5928f76aff8f1df85e67"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:80df27dd8697242b904f4ea54820e2d98d3f51f91e97e358fc13359721233e4b"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:705f03cee0cb797256d54de6695ef219e5bc8c8120b6654dd460848d57a9af3d"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03246774131701de8e7059b2e382597da43144a9a7400f178b2a32feafc54bd5"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8b5759063a6c940a69c728ea70d7c33583991c6982915a839c8da5f957e0103a"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:677f23e32491520eebb19c99bb34675daf5410c449c13416f7f0d93e2cf5f981"}, - {file = "orjson-3.10.11-cp311-none-win32.whl", hash = "sha256:a11225d7b30468dcb099498296ffac36b4673a8398ca30fdaec1e6c20df6aa55"}, - {file = "orjson-3.10.11-cp311-none-win_amd64.whl", hash = "sha256:df8c677df2f9f385fcc85ab859704045fa88d4668bc9991a527c86e710392bec"}, - {file = "orjson-3.10.11-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:360a4e2c0943da7c21505e47cf6bd725588962ff1d739b99b14e2f7f3545ba51"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:496e2cb45de21c369079ef2d662670a4892c81573bcc143c4205cae98282ba97"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7dfa8db55c9792d53c5952900c6a919cfa377b4f4534c7a786484a6a4a350c19"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:51f3382415747e0dbda9dade6f1e1a01a9d37f630d8c9049a8ed0e385b7a90c0"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f35a1b9f50a219f470e0e497ca30b285c9f34948d3c8160d5ad3a755d9299433"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e2f3b7c5803138e67028dde33450e054c87e0703afbe730c105f1fcd873496d5"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f91d9eb554310472bd09f5347950b24442600594c2edc1421403d7610a0998fd"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dfbb2d460a855c9744bbc8e36f9c3a997c4b27d842f3d5559ed54326e6911f9b"}, - {file = "orjson-3.10.11-cp312-none-win32.whl", hash = "sha256:d4a62c49c506d4d73f59514986cadebb7e8d186ad510c518f439176cf8d5359d"}, - {file = "orjson-3.10.11-cp312-none-win_amd64.whl", hash = "sha256:f1eec3421a558ff7a9b010a6c7effcfa0ade65327a71bb9b02a1c3b77a247284"}, - {file = "orjson-3.10.11-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c46294faa4e4d0eb73ab68f1a794d2cbf7bab33b1dda2ac2959ffb7c61591899"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:52e5834d7d6e58a36846e059d00559cb9ed20410664f3ad156cd2cc239a11230"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2fc947e5350fdce548bfc94f434e8760d5cafa97fb9c495d2fef6757aa02ec0"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0efabbf839388a1dab5b72b5d3baedbd6039ac83f3b55736eb9934ea5494d258"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a3f29634260708c200c4fe148e42b4aae97d7b9fee417fbdd74f8cfc265f15b0"}, - {file = "orjson-3.10.11-cp313-none-win32.whl", hash = "sha256:1a1222ffcee8a09476bbdd5d4f6f33d06d0d6642df2a3d78b7a195ca880d669b"}, - {file = "orjson-3.10.11-cp313-none-win_amd64.whl", hash = "sha256:bc274ac261cc69260913b2d1610760e55d3c0801bb3457ba7b9004420b6b4270"}, - {file = "orjson-3.10.11-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:19b3763e8bbf8ad797df6b6b5e0fc7c843ec2e2fc0621398534e0c6400098f87"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1be83a13312e5e58d633580c5eb8d0495ae61f180da2722f20562974188af205"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:afacfd1ab81f46dedd7f6001b6d4e8de23396e4884cd3c3436bd05defb1a6446"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb4d0bea56bba596723d73f074c420aec3b2e5d7d30698bc56e6048066bd560c"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96ed1de70fcb15d5fed529a656df29f768187628727ee2788344e8a51e1c1350"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4bfb30c891b530f3f80e801e3ad82ef150b964e5c38e1fb8482441c69c35c61c"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:d496c74fc2b61341e3cefda7eec21b7854c5f672ee350bc55d9a4997a8a95204"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:655a493bac606655db9a47fe94d3d84fc7f3ad766d894197c94ccf0c5408e7d3"}, - {file = "orjson-3.10.11-cp38-none-win32.whl", hash = "sha256:b9546b278c9fb5d45380f4809e11b4dd9844ca7aaf1134024503e134ed226161"}, - {file = "orjson-3.10.11-cp38-none-win_amd64.whl", hash = "sha256:b592597fe551d518f42c5a2eb07422eb475aa8cfdc8c51e6da7054b836b26782"}, - {file = "orjson-3.10.11-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c95f2ecafe709b4e5c733b5e2768ac569bed308623c85806c395d9cca00e08af"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:80c00d4acded0c51c98754fe8218cb49cb854f0f7eb39ea4641b7f71732d2cb7"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:461311b693d3d0a060439aa669c74f3603264d4e7a08faa68c47ae5a863f352d"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52ca832f17d86a78cbab86cdc25f8c13756ebe182b6fc1a97d534051c18a08de"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c57ea78a753812f528178aa2f1c57da633754c91d2124cb28991dab4c79a54"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7fcfc6f7ca046383fb954ba528587e0f9336828b568282b27579c49f8e16aad"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:86b9dd983857970c29e4c71bb3e95ff085c07d3e83e7c46ebe959bac07ebd80b"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:4d83f87582d223e54efb2242a79547611ba4ebae3af8bae1e80fa9a0af83bb7f"}, - {file = "orjson-3.10.11-cp39-none-win32.whl", hash = "sha256:9fd0ad1c129bc9beb1154c2655f177620b5beaf9a11e0d10bac63ef3fce96950"}, - {file = "orjson-3.10.11-cp39-none-win_amd64.whl", hash = "sha256:10f416b2a017c8bd17f325fb9dee1fb5cdd7a54e814284896b7c3f2763faa017"}, - {file = "orjson-3.10.11.tar.gz", hash = "sha256:e35b6d730de6384d5b2dab5fd23f0d76fae8bbc8c353c2f78210aa5fa4beb3ef"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] @@ -2680,13 +2752,13 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "prometheus-client" -version = "0.21.0" +version = "0.21.1" description = "Python client for the Prometheus monitoring system." optional = false python-versions = ">=3.8" files = [ - {file = "prometheus_client-0.21.0-py3-none-any.whl", hash = "sha256:4fa6b4dd0ac16d58bb587c04b1caae65b8c5043e85f778f42f5f632f6af2e166"}, - {file = "prometheus_client-0.21.0.tar.gz", hash = "sha256:96c83c606b71ff2b0a433c98889d275f51ffec6c5e267de37c7a2b5c9aa9233e"}, + {file = "prometheus_client-0.21.1-py3-none-any.whl", hash = "sha256:594b45c410d6f4f8888940fe80b5cc2521b305a1fafe1c58609ef715a001f301"}, + {file = "prometheus_client-0.21.1.tar.gz", hash = "sha256:252505a722ac04b0456be05c05f75f45d760c2911ffc45f2a06bcaed9f3ae3fb"}, ] [package.extras] @@ -2708,129 +2780,113 @@ wcwidth = "*" [[package]] name = "propcache" -version = "0.2.0" +version = "0.2.1" description = "Accelerated property cache" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "propcache-0.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c5869b8fd70b81835a6f187c5fdbe67917a04d7e52b6e7cc4e5fe39d55c39d58"}, - {file = "propcache-0.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:952e0d9d07609d9c5be361f33b0d6d650cd2bae393aabb11d9b719364521984b"}, - {file = "propcache-0.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:33ac8f098df0585c0b53009f039dfd913b38c1d2edafed0cedcc0c32a05aa110"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:97e48e8875e6c13909c800fa344cd54cc4b2b0db1d5f911f840458a500fde2c2"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:388f3217649d6d59292b722d940d4d2e1e6a7003259eb835724092a1cca0203a"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f571aea50ba5623c308aa146eb650eebf7dbe0fd8c5d946e28343cb3b5aad577"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3dfafb44f7bb35c0c06eda6b2ab4bfd58f02729e7c4045e179f9a861b07c9850"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a3ebe9a75be7ab0b7da2464a77bb27febcb4fab46a34f9288f39d74833db7f61"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d2f0d0f976985f85dfb5f3d685697ef769faa6b71993b46b295cdbbd6be8cc37"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a3dc1a4b165283bd865e8f8cb5f0c64c05001e0718ed06250d8cac9bec115b48"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9e0f07b42d2a50c7dd2d8675d50f7343d998c64008f1da5fef888396b7f84630"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e63e3e1e0271f374ed489ff5ee73d4b6e7c60710e1f76af5f0e1a6117cd26394"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:56bb5c98f058a41bb58eead194b4db8c05b088c93d94d5161728515bd52b052b"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7665f04d0c7f26ff8bb534e1c65068409bf4687aa2534faf7104d7182debb336"}, - {file = "propcache-0.2.0-cp310-cp310-win32.whl", hash = "sha256:7cf18abf9764746b9c8704774d8b06714bcb0a63641518a3a89c7f85cc02c2ad"}, - {file = "propcache-0.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:cfac69017ef97db2438efb854edf24f5a29fd09a536ff3a992b75990720cdc99"}, - {file = "propcache-0.2.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:63f13bf09cc3336eb04a837490b8f332e0db41da66995c9fd1ba04552e516354"}, - {file = "propcache-0.2.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:608cce1da6f2672a56b24a015b42db4ac612ee709f3d29f27a00c943d9e851de"}, - {file = "propcache-0.2.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:466c219deee4536fbc83c08d09115249db301550625c7fef1c5563a584c9bc87"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fc2db02409338bf36590aa985a461b2c96fce91f8e7e0f14c50c5fcc4f229016"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a6ed8db0a556343d566a5c124ee483ae113acc9a557a807d439bcecc44e7dfbb"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:91997d9cb4a325b60d4e3f20967f8eb08dfcb32b22554d5ef78e6fd1dda743a2"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c7dde9e533c0a49d802b4f3f218fa9ad0a1ce21f2c2eb80d5216565202acab4"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ffcad6c564fe6b9b8916c1aefbb37a362deebf9394bd2974e9d84232e3e08504"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:97a58a28bcf63284e8b4d7b460cbee1edaab24634e82059c7b8c09e65284f178"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:945db8ee295d3af9dbdbb698cce9bbc5c59b5c3fe328bbc4387f59a8a35f998d"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:39e104da444a34830751715f45ef9fc537475ba21b7f1f5b0f4d71a3b60d7fe2"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:c5ecca8f9bab618340c8e848d340baf68bcd8ad90a8ecd7a4524a81c1764b3db"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:c436130cc779806bdf5d5fae0d848713105472b8566b75ff70048c47d3961c5b"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:191db28dc6dcd29d1a3e063c3be0b40688ed76434622c53a284e5427565bbd9b"}, - {file = "propcache-0.2.0-cp311-cp311-win32.whl", hash = "sha256:5f2564ec89058ee7c7989a7b719115bdfe2a2fb8e7a4543b8d1c0cc4cf6478c1"}, - {file = "propcache-0.2.0-cp311-cp311-win_amd64.whl", hash = "sha256:6e2e54267980349b723cff366d1e29b138b9a60fa376664a157a342689553f71"}, - {file = "propcache-0.2.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:2ee7606193fb267be4b2e3b32714f2d58cad27217638db98a60f9efb5efeccc2"}, - {file = "propcache-0.2.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:91ee8fc02ca52e24bcb77b234f22afc03288e1dafbb1f88fe24db308910c4ac7"}, - {file = "propcache-0.2.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2e900bad2a8456d00a113cad8c13343f3b1f327534e3589acc2219729237a2e8"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f52a68c21363c45297aca15561812d542f8fc683c85201df0bebe209e349f793"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1e41d67757ff4fbc8ef2af99b338bfb955010444b92929e9e55a6d4dcc3c4f09"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a64e32f8bd94c105cc27f42d3b658902b5bcc947ece3c8fe7bc1b05982f60e89"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:55346705687dbd7ef0d77883ab4f6fabc48232f587925bdaf95219bae072491e"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:00181262b17e517df2cd85656fcd6b4e70946fe62cd625b9d74ac9977b64d8d9"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6994984550eaf25dd7fc7bd1b700ff45c894149341725bb4edc67f0ffa94efa4"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:56295eb1e5f3aecd516d91b00cfd8bf3a13991de5a479df9e27dd569ea23959c"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:439e76255daa0f8151d3cb325f6dd4a3e93043e6403e6491813bcaaaa8733887"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f6475a1b2ecb310c98c28d271a30df74f9dd436ee46d09236a6b750a7599ce57"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:3444cdba6628accf384e349014084b1cacd866fbb88433cd9d279d90a54e0b23"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4a9d9b4d0a9b38d1c391bb4ad24aa65f306c6f01b512e10a8a34a2dc5675d348"}, - {file = "propcache-0.2.0-cp312-cp312-win32.whl", hash = "sha256:69d3a98eebae99a420d4b28756c8ce6ea5a29291baf2dc9ff9414b42676f61d5"}, - {file = "propcache-0.2.0-cp312-cp312-win_amd64.whl", hash = "sha256:ad9c9b99b05f163109466638bd30ada1722abb01bbb85c739c50b6dc11f92dc3"}, - {file = "propcache-0.2.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ecddc221a077a8132cf7c747d5352a15ed763b674c0448d811f408bf803d9ad7"}, - {file = "propcache-0.2.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0e53cb83fdd61cbd67202735e6a6687a7b491c8742dfc39c9e01e80354956763"}, - {file = "propcache-0.2.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:92fe151145a990c22cbccf9ae15cae8ae9eddabfc949a219c9f667877e40853d"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d6a21ef516d36909931a2967621eecb256018aeb11fc48656e3257e73e2e247a"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3f88a4095e913f98988f5b338c1d4d5d07dbb0b6bad19892fd447484e483ba6b"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5a5b3bb545ead161be780ee85a2b54fdf7092815995661947812dde94a40f6fb"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:67aeb72e0f482709991aa91345a831d0b707d16b0257e8ef88a2ad246a7280bf"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3c997f8c44ec9b9b0bcbf2d422cc00a1d9b9c681f56efa6ca149a941e5560da2"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:2a66df3d4992bc1d725b9aa803e8c5a66c010c65c741ad901e260ece77f58d2f"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3ebbcf2a07621f29638799828b8d8668c421bfb94c6cb04269130d8de4fb7136"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1235c01ddaa80da8235741e80815ce381c5267f96cc49b1477fdcf8c047ef325"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:3947483a381259c06921612550867b37d22e1df6d6d7e8361264b6d037595f44"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:d5bed7f9805cc29c780f3aee05de3262ee7ce1f47083cfe9f77471e9d6777e83"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e4a91d44379f45f5e540971d41e4626dacd7f01004826a18cb048e7da7e96544"}, - {file = "propcache-0.2.0-cp313-cp313-win32.whl", hash = "sha256:f902804113e032e2cdf8c71015651c97af6418363bea8d78dc0911d56c335032"}, - {file = "propcache-0.2.0-cp313-cp313-win_amd64.whl", hash = "sha256:8f188cfcc64fb1266f4684206c9de0e80f54622c3f22a910cbd200478aeae61e"}, - {file = "propcache-0.2.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:53d1bd3f979ed529f0805dd35ddaca330f80a9a6d90bc0121d2ff398f8ed8861"}, - {file = "propcache-0.2.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:83928404adf8fb3d26793665633ea79b7361efa0287dfbd372a7e74311d51ee6"}, - {file = "propcache-0.2.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:77a86c261679ea5f3896ec060be9dc8e365788248cc1e049632a1be682442063"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:218db2a3c297a3768c11a34812e63b3ac1c3234c3a086def9c0fee50d35add1f"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7735e82e3498c27bcb2d17cb65d62c14f1100b71723b68362872bca7d0913d90"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:20a617c776f520c3875cf4511e0d1db847a076d720714ae35ffe0df3e440be68"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:67b69535c870670c9f9b14a75d28baa32221d06f6b6fa6f77a0a13c5a7b0a5b9"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4569158070180c3855e9c0791c56be3ceeb192defa2cdf6a3f39e54319e56b89"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:db47514ffdbd91ccdc7e6f8407aac4ee94cc871b15b577c1c324236b013ddd04"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:2a60ad3e2553a74168d275a0ef35e8c0a965448ffbc3b300ab3a5bb9956c2162"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:662dd62358bdeaca0aee5761de8727cfd6861432e3bb828dc2a693aa0471a563"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:25a1f88b471b3bc911d18b935ecb7115dff3a192b6fef46f0bfaf71ff4f12418"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:f60f0ac7005b9f5a6091009b09a419ace1610e163fa5deaba5ce3484341840e7"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:74acd6e291f885678631b7ebc85d2d4aec458dd849b8c841b57ef04047833bed"}, - {file = "propcache-0.2.0-cp38-cp38-win32.whl", hash = "sha256:d9b6ddac6408194e934002a69bcaadbc88c10b5f38fb9307779d1c629181815d"}, - {file = "propcache-0.2.0-cp38-cp38-win_amd64.whl", hash = "sha256:676135dcf3262c9c5081cc8f19ad55c8a64e3f7282a21266d05544450bffc3a5"}, - {file = "propcache-0.2.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:25c8d773a62ce0451b020c7b29a35cfbc05de8b291163a7a0f3b7904f27253e6"}, - {file = "propcache-0.2.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:375a12d7556d462dc64d70475a9ee5982465fbb3d2b364f16b86ba9135793638"}, - {file = "propcache-0.2.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1ec43d76b9677637a89d6ab86e1fef70d739217fefa208c65352ecf0282be957"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f45eec587dafd4b2d41ac189c2156461ebd0c1082d2fe7013571598abb8505d1"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bc092ba439d91df90aea38168e11f75c655880c12782facf5cf9c00f3d42b562"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fa1076244f54bb76e65e22cb6910365779d5c3d71d1f18b275f1dfc7b0d71b4d"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:682a7c79a2fbf40f5dbb1eb6bfe2cd865376deeac65acf9beb607505dced9e12"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8e40876731f99b6f3c897b66b803c9e1c07a989b366c6b5b475fafd1f7ba3fb8"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:363ea8cd3c5cb6679f1c2f5f1f9669587361c062e4899fce56758efa928728f8"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:140fbf08ab3588b3468932974a9331aff43c0ab8a2ec2c608b6d7d1756dbb6cb"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:e70fac33e8b4ac63dfc4c956fd7d85a0b1139adcfc0d964ce288b7c527537fea"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:b33d7a286c0dc1a15f5fc864cc48ae92a846df287ceac2dd499926c3801054a6"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:f6d5749fdd33d90e34c2efb174c7e236829147a2713334d708746e94c4bde40d"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:22aa8f2272d81d9317ff5756bb108021a056805ce63dd3630e27d042c8092798"}, - {file = "propcache-0.2.0-cp39-cp39-win32.whl", hash = "sha256:73e4b40ea0eda421b115248d7e79b59214411109a5bc47d0d48e4c73e3b8fcf9"}, - {file = "propcache-0.2.0-cp39-cp39-win_amd64.whl", hash = "sha256:9517d5e9e0731957468c29dbfd0f976736a0e55afaea843726e887f36fe017df"}, - {file = "propcache-0.2.0-py3-none-any.whl", hash = "sha256:2ccc28197af5313706511fab3a8b66dcd6da067a1331372c82ea1cb74285e036"}, - {file = "propcache-0.2.0.tar.gz", hash = "sha256:df81779732feb9d01e5d513fad0122efb3d53bbc75f61b2a4f29a020bc985e70"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6b3f39a85d671436ee3d12c017f8fdea38509e4f25b28eb25877293c98c243f6"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d51fbe4285d5db5d92a929e3e21536ea3dd43732c5b177c7ef03f918dff9f2"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6445804cf4ec763dc70de65a3b0d9954e868609e83850a47ca4f0cb64bd79fea"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f9479aa06a793c5aeba49ce5c5692ffb51fcd9a7016e017d555d5e2b0045d212"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9631c5e8b5b3a0fda99cb0d29c18133bca1e18aea9effe55adb3da1adef80d3"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3156628250f46a0895f1f36e1d4fbe062a1af8718ec3ebeb746f1d23f0c5dc4d"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b6fb63ae352e13748289f04f37868099e69dba4c2b3e271c46061e82c745634"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:887d9b0a65404929641a9fabb6452b07fe4572b269d901d622d8a34a4e9043b2"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:a96dc1fa45bd8c407a0af03b2d5218392729e1822b0c32e62c5bf7eeb5fb3958"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a7e65eb5c003a303b94aa2c3852ef130230ec79e349632d030e9571b87c4698c"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:999779addc413181912e984b942fbcc951be1f5b3663cd80b2687758f434c583"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:19a0f89a7bb9d8048d9c4370c9c543c396e894c76be5525f5e1ad287f1750ddf"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:1ac2f5fe02fa75f56e1ad473f1175e11f475606ec9bd0be2e78e4734ad575034"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:574faa3b79e8ebac7cb1d7930f51184ba1ccf69adfdec53a12f319a06030a68b"}, + {file = "propcache-0.2.1-cp310-cp310-win32.whl", hash = "sha256:03ff9d3f665769b2a85e6157ac8b439644f2d7fd17615a82fa55739bc97863f4"}, + {file = "propcache-0.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:2d3af2e79991102678f53e0dbf4c35de99b6b8b58f29a27ca0325816364caaba"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ffc3cca89bb438fb9c95c13fc874012f7b9466b89328c3c8b1aa93cdcfadd16"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f174bbd484294ed9fdf09437f889f95807e5f229d5d93588d34e92106fbf6717"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:70693319e0b8fd35dd863e3e29513875eb15c51945bf32519ef52927ca883bc3"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b480c6a4e1138e1aa137c0079b9b6305ec6dcc1098a8ca5196283e8a49df95a9"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d27b84d5880f6d8aa9ae3edb253c59d9f6642ffbb2c889b78b60361eed449787"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:857112b22acd417c40fa4595db2fe28ab900c8c5fe4670c7989b1c0230955465"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf6c4150f8c0e32d241436526f3c3f9cbd34429492abddbada2ffcff506c51af"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66d4cfda1d8ed687daa4bc0274fcfd5267873db9a5bc0418c2da19273040eeb7"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c2f992c07c0fca81655066705beae35fc95a2fa7366467366db627d9f2ee097f"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:4a571d97dbe66ef38e472703067021b1467025ec85707d57e78711c085984e54"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:bb6178c241278d5fe853b3de743087be7f5f4c6f7d6d22a3b524d323eecec505"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:ad1af54a62ffe39cf34db1aa6ed1a1873bd548f6401db39d8e7cd060b9211f82"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e7048abd75fe40712005bcfc06bb44b9dfcd8e101dda2ecf2f5aa46115ad07ca"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:160291c60081f23ee43d44b08a7e5fb76681221a8e10b3139618c5a9a291b84e"}, + {file = "propcache-0.2.1-cp311-cp311-win32.whl", hash = "sha256:819ce3b883b7576ca28da3861c7e1a88afd08cc8c96908e08a3f4dd64a228034"}, + {file = "propcache-0.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:edc9fc7051e3350643ad929df55c451899bb9ae6d24998a949d2e4c87fb596d3"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:081a430aa8d5e8876c6909b67bd2d937bfd531b0382d3fdedb82612c618bc41a"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d2ccec9ac47cf4e04897619c0e0c1a48c54a71bdf045117d3a26f80d38ab1fb0"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:14d86fe14b7e04fa306e0c43cdbeebe6b2c2156a0c9ce56b815faacc193e320d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:049324ee97bb67285b49632132db351b41e77833678432be52bdd0289c0e05e4"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1cd9a1d071158de1cc1c71a26014dcdfa7dd3d5f4f88c298c7f90ad6f27bb46d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:98110aa363f1bb4c073e8dcfaefd3a5cea0f0834c2aab23dda657e4dab2f53b5"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:647894f5ae99c4cf6bb82a1bb3a796f6e06af3caa3d32e26d2350d0e3e3faf24"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bfd3223c15bebe26518d58ccf9a39b93948d3dcb3e57a20480dfdd315356baff"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d71264a80f3fcf512eb4f18f59423fe82d6e346ee97b90625f283df56aee103f"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:e73091191e4280403bde6c9a52a6999d69cdfde498f1fdf629105247599b57ec"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:3935bfa5fede35fb202c4b569bb9c042f337ca4ff7bd540a0aa5e37131659348"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f508b0491767bb1f2b87fdfacaba5f7eddc2f867740ec69ece6d1946d29029a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1672137af7c46662a1c2be1e8dc78cb6d224319aaa40271c9257d886be4363a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b74c261802d3d2b85c9df2dfb2fa81b6f90deeef63c2db9f0e029a3cac50b518"}, + {file = "propcache-0.2.1-cp312-cp312-win32.whl", hash = "sha256:d09c333d36c1409d56a9d29b3a1b800a42c76a57a5a8907eacdbce3f18768246"}, + {file = "propcache-0.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:c214999039d4f2a5b2073ac506bba279945233da8c786e490d411dfc30f855c1"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:aca405706e0b0a44cc6bfd41fbe89919a6a56999157f6de7e182a990c36e37bc"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:12d1083f001ace206fe34b6bdc2cb94be66d57a850866f0b908972f90996b3e9"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d93f3307ad32a27bda2e88ec81134b823c240aa3abb55821a8da553eed8d9439"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba278acf14471d36316159c94a802933d10b6a1e117b8554fe0d0d9b75c9d536"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4e6281aedfca15301c41f74d7005e6e3f4ca143584ba696ac69df4f02f40d629"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b750a8e5a1262434fb1517ddf64b5de58327f1adc3524a5e44c2ca43305eb0b"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf72af5e0fb40e9babf594308911436c8efde3cb5e75b6f206c34ad18be5c052"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b2d0a12018b04f4cb820781ec0dffb5f7c7c1d2a5cd22bff7fb055a2cb19ebce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e800776a79a5aabdb17dcc2346a7d66d0777e942e4cd251defeb084762ecd17d"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:4160d9283bd382fa6c0c2b5e017acc95bc183570cd70968b9202ad6d8fc48dce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:30b43e74f1359353341a7adb783c8f1b1c676367b011709f466f42fda2045e95"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:58791550b27d5488b1bb52bc96328456095d96206a250d28d874fafe11b3dfaf"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:0f022d381747f0dfe27e99d928e31bc51a18b65bb9e481ae0af1380a6725dd1f"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:297878dc9d0a334358f9b608b56d02e72899f3b8499fc6044133f0d319e2ec30"}, + {file = "propcache-0.2.1-cp313-cp313-win32.whl", hash = "sha256:ddfab44e4489bd79bda09d84c430677fc7f0a4939a73d2bba3073036f487a0a6"}, + {file = "propcache-0.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:556fc6c10989f19a179e4321e5d678db8eb2924131e64652a51fe83e4c3db0e1"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:6a9a8c34fb7bb609419a211e59da8887eeca40d300b5ea8e56af98f6fbbb1541"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ae1aa1cd222c6d205853b3013c69cd04515f9d6ab6de4b0603e2e1c33221303e"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:accb6150ce61c9c4b7738d45550806aa2b71c7668c6942f17b0ac182b6142fd4"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5eee736daafa7af6d0a2dc15cc75e05c64f37fc37bafef2e00d77c14171c2097"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f7a31fc1e1bd362874863fdeed71aed92d348f5336fd84f2197ba40c59f061bd"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cba4cfa1052819d16699e1d55d18c92b6e094d4517c41dd231a8b9f87b6fa681"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f089118d584e859c62b3da0892b88a83d611c2033ac410e929cb6754eec0ed16"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:781e65134efaf88feb447e8c97a51772aa75e48b794352f94cb7ea717dedda0d"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:31f5af773530fd3c658b32b6bdc2d0838543de70eb9a2156c03e410f7b0d3aae"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:a7a078f5d37bee6690959c813977da5291b24286e7b962e62a94cec31aa5188b"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:cea7daf9fc7ae6687cf1e2c049752f19f146fdc37c2cc376e7d0032cf4f25347"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:8b3489ff1ed1e8315674d0775dc7d2195fb13ca17b3808721b54dbe9fd020faf"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9403db39be1393618dd80c746cb22ccda168efce239c73af13c3763ef56ffc04"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5d97151bc92d2b2578ff7ce779cdb9174337390a535953cbb9452fb65164c587"}, + {file = "propcache-0.2.1-cp39-cp39-win32.whl", hash = "sha256:9caac6b54914bdf41bcc91e7eb9147d331d29235a7c967c150ef5df6464fd1bb"}, + {file = "propcache-0.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:92fc4500fcb33899b05ba73276dfb684a20d31caa567b7cb5252d48f896a91b1"}, + {file = "propcache-0.2.1-py3-none-any.whl", hash = "sha256:52277518d6aae65536e9cea52d4e7fd2f7a66f4aa2d30ed3f2fcea620ace3c54"}, + {file = "propcache-0.2.1.tar.gz", hash = "sha256:3f77ce728b19cb537714499928fe800c3dda29e8d9428778fc7c186da4c09a64"}, ] [[package]] name = "protobuf" -version = "5.28.3" +version = "5.29.1" description = "" optional = false python-versions = ">=3.8" files = [ - {file = "protobuf-5.28.3-cp310-abi3-win32.whl", hash = "sha256:0c4eec6f987338617072592b97943fdbe30d019c56126493111cf24344c1cc24"}, - {file = "protobuf-5.28.3-cp310-abi3-win_amd64.whl", hash = "sha256:91fba8f445723fcf400fdbe9ca796b19d3b1242cd873907979b9ed71e4afe868"}, - {file = "protobuf-5.28.3-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:a3f6857551e53ce35e60b403b8a27b0295f7d6eb63d10484f12bc6879c715687"}, - {file = "protobuf-5.28.3-cp38-abi3-manylinux2014_aarch64.whl", hash = "sha256:3fa2de6b8b29d12c61911505d893afe7320ce7ccba4df913e2971461fa36d584"}, - {file = "protobuf-5.28.3-cp38-abi3-manylinux2014_x86_64.whl", hash = "sha256:712319fbdddb46f21abb66cd33cb9e491a5763b2febd8f228251add221981135"}, - {file = "protobuf-5.28.3-cp38-cp38-win32.whl", hash = "sha256:3e6101d095dfd119513cde7259aa703d16c6bbdfae2554dfe5cfdbe94e32d548"}, - {file = "protobuf-5.28.3-cp38-cp38-win_amd64.whl", hash = "sha256:27b246b3723692bf1068d5734ddaf2fccc2cdd6e0c9b47fe099244d80200593b"}, - {file = "protobuf-5.28.3-cp39-cp39-win32.whl", hash = "sha256:135658402f71bbd49500322c0f736145731b16fc79dc8f367ab544a17eab4535"}, - {file = "protobuf-5.28.3-cp39-cp39-win_amd64.whl", hash = "sha256:70585a70fc2dd4818c51287ceef5bdba6387f88a578c86d47bb34669b5552c36"}, - {file = "protobuf-5.28.3-py3-none-any.whl", hash = "sha256:cee1757663fa32a1ee673434fcf3bf24dd54763c79690201208bafec62f19eed"}, - {file = "protobuf-5.28.3.tar.gz", hash = "sha256:64badbc49180a5e401f373f9ce7ab1d18b63f7dd4a9cdc43c92b9f0b481cef7b"}, + {file = "protobuf-5.29.1-cp310-abi3-win32.whl", hash = "sha256:22c1f539024241ee545cbcb00ee160ad1877975690b16656ff87dde107b5f110"}, + {file = "protobuf-5.29.1-cp310-abi3-win_amd64.whl", hash = "sha256:1fc55267f086dd4050d18ef839d7bd69300d0d08c2a53ca7df3920cc271a3c34"}, + {file = "protobuf-5.29.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:d473655e29c0c4bbf8b69e9a8fb54645bc289dead6d753b952e7aa660254ae18"}, + {file = "protobuf-5.29.1-cp38-abi3-manylinux2014_aarch64.whl", hash = "sha256:b5ba1d0e4c8a40ae0496d0e2ecfdbb82e1776928a205106d14ad6985a09ec155"}, + {file = "protobuf-5.29.1-cp38-abi3-manylinux2014_x86_64.whl", hash = "sha256:8ee1461b3af56145aca2800e6a3e2f928108c749ba8feccc6f5dd0062c410c0d"}, + {file = "protobuf-5.29.1-cp38-cp38-win32.whl", hash = "sha256:50879eb0eb1246e3a5eabbbe566b44b10348939b7cc1b267567e8c3d07213853"}, + {file = "protobuf-5.29.1-cp38-cp38-win_amd64.whl", hash = "sha256:027fbcc48cea65a6b17028510fdd054147057fa78f4772eb547b9274e5219331"}, + {file = "protobuf-5.29.1-cp39-cp39-win32.whl", hash = "sha256:5a41deccfa5e745cef5c65a560c76ec0ed8e70908a67cc8f4da5fce588b50d57"}, + {file = "protobuf-5.29.1-cp39-cp39-win_amd64.whl", hash = "sha256:012ce28d862ff417fd629285aca5d9772807f15ceb1a0dbd15b88f58c776c98c"}, + {file = "protobuf-5.29.1-py3-none-any.whl", hash = "sha256:32600ddb9c2a53dedc25b8581ea0f1fd8ea04956373c0c07577ce58d312522e0"}, + {file = "protobuf-5.29.1.tar.gz", hash = "sha256:683be02ca21a6ffe80db6dd02c0b5b2892322c59ca57fd6c872d652cb80549cb"}, ] [[package]] @@ -2901,22 +2957,19 @@ files = [ [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.3" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.3-py3-none-any.whl", hash = "sha256:be04d85bbc7b65651c5f8e6b9976ed9c6f41782a55524cef079a34a0bb82144d"}, + {file = "pydantic-2.10.3.tar.gz", hash = "sha256:cb5ac360ce894ceacd69c403187900a02c4b20b693a9dd1d643e1effab9eadf9"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -2924,100 +2977,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -3579,101 +3643,114 @@ files = [ [[package]] name = "rpds-py" -version = "0.21.0" +version = "0.22.3" description = "Python bindings to Rust's persistent data structures (rpds)" optional = false python-versions = ">=3.9" files = [ - {file = "rpds_py-0.21.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:a017f813f24b9df929674d0332a374d40d7f0162b326562daae8066b502d0590"}, - {file = "rpds_py-0.21.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:20cc1ed0bcc86d8e1a7e968cce15be45178fd16e2ff656a243145e0b439bd250"}, - {file = "rpds_py-0.21.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ad116dda078d0bc4886cb7840e19811562acdc7a8e296ea6ec37e70326c1b41c"}, - {file = "rpds_py-0.21.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:808f1ac7cf3b44f81c9475475ceb221f982ef548e44e024ad5f9e7060649540e"}, - {file = "rpds_py-0.21.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:de552f4a1916e520f2703ec474d2b4d3f86d41f353e7680b597512ffe7eac5d0"}, - {file = "rpds_py-0.21.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:efec946f331349dfc4ae9d0e034c263ddde19414fe5128580f512619abed05f1"}, - {file = "rpds_py-0.21.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b80b4690bbff51a034bfde9c9f6bf9357f0a8c61f548942b80f7b66356508bf5"}, - {file = "rpds_py-0.21.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:085ed25baac88953d4283e5b5bd094b155075bb40d07c29c4f073e10623f9f2e"}, - {file = "rpds_py-0.21.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:daa8efac2a1273eed2354397a51216ae1e198ecbce9036fba4e7610b308b6153"}, - {file = "rpds_py-0.21.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:95a5bad1ac8a5c77b4e658671642e4af3707f095d2b78a1fdd08af0dfb647624"}, - {file = "rpds_py-0.21.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:3e53861b29a13d5b70116ea4230b5f0f3547b2c222c5daa090eb7c9c82d7f664"}, - {file = "rpds_py-0.21.0-cp310-none-win32.whl", hash = "sha256:ea3a6ac4d74820c98fcc9da4a57847ad2cc36475a8bd9683f32ab6d47a2bd682"}, - {file = "rpds_py-0.21.0-cp310-none-win_amd64.whl", hash = "sha256:b8f107395f2f1d151181880b69a2869c69e87ec079c49c0016ab96860b6acbe5"}, - {file = "rpds_py-0.21.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:5555db3e618a77034954b9dc547eae94166391a98eb867905ec8fcbce1308d95"}, - {file = "rpds_py-0.21.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:97ef67d9bbc3e15584c2f3c74bcf064af36336c10d2e21a2131e123ce0f924c9"}, - {file = "rpds_py-0.21.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ab2c2a26d2f69cdf833174f4d9d86118edc781ad9a8fa13970b527bf8236027"}, - {file = "rpds_py-0.21.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4e8921a259f54bfbc755c5bbd60c82bb2339ae0324163f32868f63f0ebb873d9"}, - {file = "rpds_py-0.21.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8a7ff941004d74d55a47f916afc38494bd1cfd4b53c482b77c03147c91ac0ac3"}, - {file = "rpds_py-0.21.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5145282a7cd2ac16ea0dc46b82167754d5e103a05614b724457cffe614f25bd8"}, - {file = "rpds_py-0.21.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:de609a6f1b682f70bb7163da745ee815d8f230d97276db049ab447767466a09d"}, - {file = "rpds_py-0.21.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:40c91c6e34cf016fa8e6b59d75e3dbe354830777fcfd74c58b279dceb7975b75"}, - {file = "rpds_py-0.21.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d2132377f9deef0c4db89e65e8bb28644ff75a18df5293e132a8d67748397b9f"}, - {file = "rpds_py-0.21.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:0a9e0759e7be10109645a9fddaaad0619d58c9bf30a3f248a2ea57a7c417173a"}, - {file = "rpds_py-0.21.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:9e20da3957bdf7824afdd4b6eeb29510e83e026473e04952dca565170cd1ecc8"}, - {file = "rpds_py-0.21.0-cp311-none-win32.whl", hash = "sha256:f71009b0d5e94c0e86533c0b27ed7cacc1239cb51c178fd239c3cfefefb0400a"}, - {file = "rpds_py-0.21.0-cp311-none-win_amd64.whl", hash = "sha256:e168afe6bf6ab7ab46c8c375606298784ecbe3ba31c0980b7dcbb9631dcba97e"}, - {file = "rpds_py-0.21.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:30b912c965b2aa76ba5168fd610087bad7fcde47f0a8367ee8f1876086ee6d1d"}, - {file = "rpds_py-0.21.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:ca9989d5d9b1b300bc18e1801c67b9f6d2c66b8fd9621b36072ed1df2c977f72"}, - {file = "rpds_py-0.21.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6f54e7106f0001244a5f4cf810ba8d3f9c542e2730821b16e969d6887b664266"}, - {file = "rpds_py-0.21.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fed5dfefdf384d6fe975cc026886aece4f292feaf69d0eeb716cfd3c5a4dd8be"}, - {file = "rpds_py-0.21.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:590ef88db231c9c1eece44dcfefd7515d8bf0d986d64d0caf06a81998a9e8cab"}, - {file = "rpds_py-0.21.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f983e4c2f603c95dde63df633eec42955508eefd8d0f0e6d236d31a044c882d7"}, - {file = "rpds_py-0.21.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b229ce052ddf1a01c67d68166c19cb004fb3612424921b81c46e7ea7ccf7c3bf"}, - {file = "rpds_py-0.21.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ebf64e281a06c904a7636781d2e973d1f0926a5b8b480ac658dc0f556e7779f4"}, - {file = "rpds_py-0.21.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:998a8080c4495e4f72132f3d66ff91f5997d799e86cec6ee05342f8f3cda7dca"}, - {file = "rpds_py-0.21.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:98486337f7b4f3c324ab402e83453e25bb844f44418c066623db88e4c56b7c7b"}, - {file = "rpds_py-0.21.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:a78d8b634c9df7f8d175451cfeac3810a702ccb85f98ec95797fa98b942cea11"}, - {file = "rpds_py-0.21.0-cp312-none-win32.whl", hash = "sha256:a58ce66847711c4aa2ecfcfaff04cb0327f907fead8945ffc47d9407f41ff952"}, - {file = "rpds_py-0.21.0-cp312-none-win_amd64.whl", hash = "sha256:e860f065cc4ea6f256d6f411aba4b1251255366e48e972f8a347cf88077b24fd"}, - {file = "rpds_py-0.21.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:ee4eafd77cc98d355a0d02f263efc0d3ae3ce4a7c24740010a8b4012bbb24937"}, - {file = "rpds_py-0.21.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:688c93b77e468d72579351a84b95f976bd7b3e84aa6686be6497045ba84be560"}, - {file = "rpds_py-0.21.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c38dbf31c57032667dd5a2f0568ccde66e868e8f78d5a0d27dcc56d70f3fcd3b"}, - {file = "rpds_py-0.21.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2d6129137f43f7fa02d41542ffff4871d4aefa724a5fe38e2c31a4e0fd343fb0"}, - {file = "rpds_py-0.21.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:520ed8b99b0bf86a176271f6fe23024323862ac674b1ce5b02a72bfeff3fff44"}, - {file = "rpds_py-0.21.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:aaeb25ccfb9b9014a10eaf70904ebf3f79faaa8e60e99e19eef9f478651b9b74"}, - {file = "rpds_py-0.21.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:af04ac89c738e0f0f1b913918024c3eab6e3ace989518ea838807177d38a2e94"}, - {file = "rpds_py-0.21.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b9b76e2afd585803c53c5b29e992ecd183f68285b62fe2668383a18e74abe7a3"}, - {file = "rpds_py-0.21.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:5afb5efde74c54724e1a01118c6e5c15e54e642c42a1ba588ab1f03544ac8c7a"}, - {file = "rpds_py-0.21.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:52c041802a6efa625ea18027a0723676a778869481d16803481ef6cc02ea8cb3"}, - {file = "rpds_py-0.21.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:ee1e4fc267b437bb89990b2f2abf6c25765b89b72dd4a11e21934df449e0c976"}, - {file = "rpds_py-0.21.0-cp313-none-win32.whl", hash = "sha256:0c025820b78817db6a76413fff6866790786c38f95ea3f3d3c93dbb73b632202"}, - {file = "rpds_py-0.21.0-cp313-none-win_amd64.whl", hash = "sha256:320c808df533695326610a1b6a0a6e98f033e49de55d7dc36a13c8a30cfa756e"}, - {file = "rpds_py-0.21.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:2c51d99c30091f72a3c5d126fad26236c3f75716b8b5e5cf8effb18889ced928"}, - {file = "rpds_py-0.21.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:cbd7504a10b0955ea287114f003b7ad62330c9e65ba012c6223dba646f6ffd05"}, - {file = "rpds_py-0.21.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6dcc4949be728ede49e6244eabd04064336012b37f5c2200e8ec8eb2988b209c"}, - {file = "rpds_py-0.21.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f414da5c51bf350e4b7960644617c130140423882305f7574b6cf65a3081cecb"}, - {file = "rpds_py-0.21.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9afe42102b40007f588666bc7de82451e10c6788f6f70984629db193849dced1"}, - {file = "rpds_py-0.21.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b929c2bb6e29ab31f12a1117c39f7e6d6450419ab7464a4ea9b0b417174f044"}, - {file = "rpds_py-0.21.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8404b3717da03cbf773a1d275d01fec84ea007754ed380f63dfc24fb76ce4592"}, - {file = "rpds_py-0.21.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e12bb09678f38b7597b8346983d2323a6482dcd59e423d9448108c1be37cac9d"}, - {file = "rpds_py-0.21.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:58a0e345be4b18e6b8501d3b0aa540dad90caeed814c515e5206bb2ec26736fd"}, - {file = "rpds_py-0.21.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:c3761f62fcfccf0864cc4665b6e7c3f0c626f0380b41b8bd1ce322103fa3ef87"}, - {file = "rpds_py-0.21.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:c2b2f71c6ad6c2e4fc9ed9401080badd1469fa9889657ec3abea42a3d6b2e1ed"}, - {file = "rpds_py-0.21.0-cp39-none-win32.whl", hash = "sha256:b21747f79f360e790525e6f6438c7569ddbfb1b3197b9e65043f25c3c9b489d8"}, - {file = "rpds_py-0.21.0-cp39-none-win_amd64.whl", hash = "sha256:0626238a43152918f9e72ede9a3b6ccc9e299adc8ade0d67c5e142d564c9a83d"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:6b4ef7725386dc0762857097f6b7266a6cdd62bfd209664da6712cb26acef035"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:6bc0e697d4d79ab1aacbf20ee5f0df80359ecf55db33ff41481cf3e24f206919"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:da52d62a96e61c1c444f3998c434e8b263c384f6d68aca8274d2e08d1906325c"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:98e4fe5db40db87ce1c65031463a760ec7906ab230ad2249b4572c2fc3ef1f9f"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:30bdc973f10d28e0337f71d202ff29345320f8bc49a31c90e6c257e1ccef4333"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:faa5e8496c530f9c71f2b4e1c49758b06e5f4055e17144906245c99fa6d45356"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:32eb88c30b6a4f0605508023b7141d043a79b14acb3b969aa0b4f99b25bc7d4a"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a89a8ce9e4e75aeb7fa5d8ad0f3fecdee813802592f4f46a15754dcb2fd6b061"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:241e6c125568493f553c3d0fdbb38c74babf54b45cef86439d4cd97ff8feb34d"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-musllinux_1_2_i686.whl", hash = "sha256:3b766a9f57663396e4f34f5140b3595b233a7b146e94777b97a8413a1da1be18"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:af4a644bf890f56e41e74be7d34e9511e4954894d544ec6b8efe1e21a1a8da6c"}, - {file = "rpds_py-0.21.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:3e30a69a706e8ea20444b98a49f386c17b26f860aa9245329bab0851ed100677"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:031819f906bb146561af051c7cef4ba2003d28cff07efacef59da973ff7969ba"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:b876f2bc27ab5954e2fd88890c071bd0ed18b9c50f6ec3de3c50a5ece612f7a6"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dc5695c321e518d9f03b7ea6abb5ea3af4567766f9852ad1560f501b17588c7b"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b4de1da871b5c0fd5537b26a6fc6814c3cc05cabe0c941db6e9044ffbb12f04a"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:878f6fea96621fda5303a2867887686d7a198d9e0f8a40be100a63f5d60c88c9"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a8eeec67590e94189f434c6d11c426892e396ae59e4801d17a93ac96b8c02a6c"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1ff2eba7f6c0cb523d7e9cff0903f2fe1feff8f0b2ceb6bd71c0e20a4dcee271"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a429b99337062877d7875e4ff1a51fe788424d522bd64a8c0a20ef3021fdb6ed"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:d167e4dbbdac48bd58893c7e446684ad5d425b407f9336e04ab52e8b9194e2ed"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-musllinux_1_2_i686.whl", hash = "sha256:4eb2de8a147ffe0626bfdc275fc6563aa7bf4b6db59cf0d44f0ccd6ca625a24e"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:e78868e98f34f34a88e23ee9ccaeeec460e4eaf6db16d51d7a9b883e5e785a5e"}, - {file = "rpds_py-0.21.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:4991ca61656e3160cdaca4851151fd3f4a92e9eba5c7a530ab030d6aee96ec89"}, - {file = "rpds_py-0.21.0.tar.gz", hash = "sha256:ed6378c9d66d0de903763e7706383d60c33829581f0adff47b6535f1802fa6db"}, + {file = "rpds_py-0.22.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:6c7b99ca52c2c1752b544e310101b98a659b720b21db00e65edca34483259967"}, + {file = "rpds_py-0.22.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:be2eb3f2495ba669d2a985f9b426c1797b7d48d6963899276d22f23e33d47e37"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:70eb60b3ae9245ddea20f8a4190bd79c705a22f8028aaf8bbdebe4716c3fab24"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4041711832360a9b75cfb11b25a6a97c8fb49c07b8bd43d0d02b45d0b499a4ff"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:64607d4cbf1b7e3c3c8a14948b99345eda0e161b852e122c6bb71aab6d1d798c"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e69b0a0e2537f26d73b4e43ad7bc8c8efb39621639b4434b76a3de50c6966e"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc27863442d388870c1809a87507727b799c8460573cfbb6dc0eeaef5a11b5ec"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e79dd39f1e8c3504be0607e5fc6e86bb60fe3584bec8b782578c3b0fde8d932c"}, + {file = "rpds_py-0.22.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:e0fa2d4ec53dc51cf7d3bb22e0aa0143966119f42a0c3e4998293a3dd2856b09"}, + {file = "rpds_py-0.22.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fda7cb070f442bf80b642cd56483b5548e43d366fe3f39b98e67cce780cded00"}, + {file = "rpds_py-0.22.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:cff63a0272fcd259dcc3be1657b07c929c466b067ceb1c20060e8d10af56f5bf"}, + {file = "rpds_py-0.22.3-cp310-cp310-win32.whl", hash = "sha256:9bd7228827ec7bb817089e2eb301d907c0d9827a9e558f22f762bb690b131652"}, + {file = "rpds_py-0.22.3-cp310-cp310-win_amd64.whl", hash = "sha256:9beeb01d8c190d7581a4d59522cd3d4b6887040dcfc744af99aa59fef3e041a8"}, + {file = "rpds_py-0.22.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d20cfb4e099748ea39e6f7b16c91ab057989712d31761d3300d43134e26e165f"}, + {file = "rpds_py-0.22.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:68049202f67380ff9aa52f12e92b1c30115f32e6895cd7198fa2a7961621fc5a"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fb4f868f712b2dd4bcc538b0a0c1f63a2b1d584c925e69a224d759e7070a12d5"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bc51abd01f08117283c5ebf64844a35144a0843ff7b2983e0648e4d3d9f10dbb"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0f3cec041684de9a4684b1572fe28c7267410e02450f4561700ca5a3bc6695a2"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7ef9d9da710be50ff6809fed8f1963fecdfecc8b86656cadfca3bc24289414b0"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:59f4a79c19232a5774aee369a0c296712ad0e77f24e62cad53160312b1c1eaa1"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1a60bce91f81ddaac922a40bbb571a12c1070cb20ebd6d49c48e0b101d87300d"}, + {file = "rpds_py-0.22.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:e89391e6d60251560f0a8f4bd32137b077a80d9b7dbe6d5cab1cd80d2746f648"}, + {file = "rpds_py-0.22.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e3fb866d9932a3d7d0c82da76d816996d1667c44891bd861a0f97ba27e84fc74"}, + {file = "rpds_py-0.22.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1352ae4f7c717ae8cba93421a63373e582d19d55d2ee2cbb184344c82d2ae55a"}, + {file = "rpds_py-0.22.3-cp311-cp311-win32.whl", hash = "sha256:b0b4136a252cadfa1adb705bb81524eee47d9f6aab4f2ee4fa1e9d3cd4581f64"}, + {file = "rpds_py-0.22.3-cp311-cp311-win_amd64.whl", hash = "sha256:8bd7c8cfc0b8247c8799080fbff54e0b9619e17cdfeb0478ba7295d43f635d7c"}, + {file = "rpds_py-0.22.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:27e98004595899949bd7a7b34e91fa7c44d7a97c40fcaf1d874168bb652ec67e"}, + {file = "rpds_py-0.22.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1978d0021e943aae58b9b0b196fb4895a25cc53d3956b8e35e0b7682eefb6d56"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:655ca44a831ecb238d124e0402d98f6212ac527a0ba6c55ca26f616604e60a45"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:feea821ee2a9273771bae61194004ee2fc33f8ec7db08117ef9147d4bbcbca8e"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:22bebe05a9ffc70ebfa127efbc429bc26ec9e9b4ee4d15a740033efda515cf3d"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3af6e48651c4e0d2d166dc1b033b7042ea3f871504b6805ba5f4fe31581d8d38"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e67ba3c290821343c192f7eae1d8fd5999ca2dc99994114643e2f2d3e6138b15"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:02fbb9c288ae08bcb34fb41d516d5eeb0455ac35b5512d03181d755d80810059"}, + {file = "rpds_py-0.22.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f56a6b404f74ab372da986d240e2e002769a7d7102cc73eb238a4f72eec5284e"}, + {file = "rpds_py-0.22.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:0a0461200769ab3b9ab7e513f6013b7a97fdeee41c29b9db343f3c5a8e2b9e61"}, + {file = "rpds_py-0.22.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8633e471c6207a039eff6aa116e35f69f3156b3989ea3e2d755f7bc41754a4a7"}, + {file = "rpds_py-0.22.3-cp312-cp312-win32.whl", hash = "sha256:593eba61ba0c3baae5bc9be2f5232430453fb4432048de28399ca7376de9c627"}, + {file = "rpds_py-0.22.3-cp312-cp312-win_amd64.whl", hash = "sha256:d115bffdd417c6d806ea9069237a4ae02f513b778e3789a359bc5856e0404cc4"}, + {file = "rpds_py-0.22.3-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:ea7433ce7e4bfc3a85654aeb6747babe3f66eaf9a1d0c1e7a4435bbdf27fea84"}, + {file = "rpds_py-0.22.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:6dd9412824c4ce1aca56c47b0991e65bebb7ac3f4edccfd3f156150c96a7bf25"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:20070c65396f7373f5df4005862fa162db5d25d56150bddd0b3e8214e8ef45b4"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0b09865a9abc0ddff4e50b5ef65467cd94176bf1e0004184eb915cbc10fc05c5"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3453e8d41fe5f17d1f8e9c383a7473cd46a63661628ec58e07777c2fff7196dc"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f5d36399a1b96e1a5fdc91e0522544580dbebeb1f77f27b2b0ab25559e103b8b"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:009de23c9c9ee54bf11303a966edf4d9087cd43a6003672e6aa7def643d06518"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1aef18820ef3e4587ebe8b3bc9ba6e55892a6d7b93bac6d29d9f631a3b4befbd"}, + {file = "rpds_py-0.22.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f60bd8423be1d9d833f230fdbccf8f57af322d96bcad6599e5a771b151398eb2"}, + {file = "rpds_py-0.22.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:62d9cfcf4948683a18a9aff0ab7e1474d407b7bab2ca03116109f8464698ab16"}, + {file = "rpds_py-0.22.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9253fc214112405f0afa7db88739294295f0e08466987f1d70e29930262b4c8f"}, + {file = "rpds_py-0.22.3-cp313-cp313-win32.whl", hash = "sha256:fb0ba113b4983beac1a2eb16faffd76cb41e176bf58c4afe3e14b9c681f702de"}, + {file = "rpds_py-0.22.3-cp313-cp313-win_amd64.whl", hash = "sha256:c58e2339def52ef6b71b8f36d13c3688ea23fa093353f3a4fee2556e62086ec9"}, + {file = "rpds_py-0.22.3-cp313-cp313t-macosx_10_12_x86_64.whl", hash = "sha256:f82a116a1d03628a8ace4859556fb39fd1424c933341a08ea3ed6de1edb0283b"}, + {file = "rpds_py-0.22.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:3dfcbc95bd7992b16f3f7ba05af8a64ca694331bd24f9157b49dadeeb287493b"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:59259dc58e57b10e7e18ce02c311804c10c5a793e6568f8af4dead03264584d1"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5725dd9cc02068996d4438d397e255dcb1df776b7ceea3b9cb972bdb11260a83"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:99b37292234e61325e7a5bb9689e55e48c3f5f603af88b1642666277a81f1fbd"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:27b1d3b3915a99208fee9ab092b8184c420f2905b7d7feb4aeb5e4a9c509b8a1"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f612463ac081803f243ff13cccc648578e2279295048f2a8d5eb430af2bae6e3"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f73d3fef726b3243a811121de45193c0ca75f6407fe66f3f4e183c983573e130"}, + {file = "rpds_py-0.22.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:3f21f0495edea7fdbaaa87e633a8689cd285f8f4af5c869f27bc8074638ad69c"}, + {file = "rpds_py-0.22.3-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:1e9663daaf7a63ceccbbb8e3808fe90415b0757e2abddbfc2e06c857bf8c5e2b"}, + {file = "rpds_py-0.22.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:a76e42402542b1fae59798fab64432b2d015ab9d0c8c47ba7addddbaf7952333"}, + {file = "rpds_py-0.22.3-cp313-cp313t-win32.whl", hash = "sha256:69803198097467ee7282750acb507fba35ca22cc3b85f16cf45fb01cb9097730"}, + {file = "rpds_py-0.22.3-cp313-cp313t-win_amd64.whl", hash = "sha256:f5cf2a0c2bdadf3791b5c205d55a37a54025c6e18a71c71f82bb536cf9a454bf"}, + {file = "rpds_py-0.22.3-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:378753b4a4de2a7b34063d6f95ae81bfa7b15f2c1a04a9518e8644e81807ebea"}, + {file = "rpds_py-0.22.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3445e07bf2e8ecfeef6ef67ac83de670358abf2996916039b16a218e3d95e97e"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7b2513ba235829860b13faa931f3b6846548021846ac808455301c23a101689d"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eaf16ae9ae519a0e237a0f528fd9f0197b9bb70f40263ee57ae53c2b8d48aeb3"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:583f6a1993ca3369e0f80ba99d796d8e6b1a3a2a442dd4e1a79e652116413091"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4617e1915a539a0d9a9567795023de41a87106522ff83fbfaf1f6baf8e85437e"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0c150c7a61ed4a4f4955a96626574e9baf1adf772c2fb61ef6a5027e52803543"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2fa4331c200c2521512595253f5bb70858b90f750d39b8cbfd67465f8d1b596d"}, + {file = "rpds_py-0.22.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:214b7a953d73b5e87f0ebece4a32a5bd83c60a3ecc9d4ec8f1dca968a2d91e99"}, + {file = "rpds_py-0.22.3-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:f47ad3d5f3258bd7058d2d506852217865afefe6153a36eb4b6928758041d831"}, + {file = "rpds_py-0.22.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:f276b245347e6e36526cbd4a266a417796fc531ddf391e43574cf6466c492520"}, + {file = "rpds_py-0.22.3-cp39-cp39-win32.whl", hash = "sha256:bbb232860e3d03d544bc03ac57855cd82ddf19c7a07651a7c0fdb95e9efea8b9"}, + {file = "rpds_py-0.22.3-cp39-cp39-win_amd64.whl", hash = "sha256:cfbc454a2880389dbb9b5b398e50d439e2e58669160f27b60e5eca11f68ae17c"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:d48424e39c2611ee1b84ad0f44fb3b2b53d473e65de061e3f460fc0be5f1939d"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:24e8abb5878e250f2eb0d7859a8e561846f98910326d06c0d51381fed59357bd"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4b232061ca880db21fa14defe219840ad9b74b6158adb52ddf0e87bead9e8493"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ac0a03221cdb5058ce0167ecc92a8c89e8d0decdc9e99a2ec23380793c4dcb96"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eb0c341fa71df5a4595f9501df4ac5abfb5a09580081dffbd1ddd4654e6e9123"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf9db5488121b596dbfc6718c76092fda77b703c1f7533a226a5a9f65248f8ad"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0b8db6b5b2d4491ad5b6bdc2bc7c017eec108acbf4e6785f42a9eb0ba234f4c9"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b3d504047aba448d70cf6fa22e06cb09f7cbd761939fdd47604f5e007675c24e"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:e61b02c3f7a1e0b75e20c3978f7135fd13cb6cf551bf4a6d29b999a88830a338"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_i686.whl", hash = "sha256:e35ba67d65d49080e8e5a1dd40101fccdd9798adb9b050ff670b7d74fa41c566"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:26fd7cac7dd51011a245f29a2cc6489c4608b5a8ce8d75661bb4a1066c52dfbe"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:177c7c0fce2855833819c98e43c262007f42ce86651ffbb84f37883308cb0e7d"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:bb47271f60660803ad11f4c61b42242b8c1312a31c98c578f79ef9387bbde21c"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:70fb28128acbfd264eda9bf47015537ba3fe86e40d046eb2963d75024be4d055"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:44d61b4b7d0c2c9ac019c314e52d7cbda0ae31078aabd0f22e583af3e0d79723"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f0e260eaf54380380ac3808aa4ebe2d8ca28b9087cf411649f96bad6900c728"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b25bc607423935079e05619d7de556c91fb6adeae9d5f80868dde3468657994b"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fb6116dfb8d1925cbdb52595560584db42a7f664617a1f7d7f6e32f138cdf37d"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a63cbdd98acef6570c62b92a1e43266f9e8b21e699c363c0fef13bd530799c11"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b8f60e1b739a74bab7e01fcbe3dddd4657ec685caa04681df9d562ef15b625f"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:2e8b55d8517a2fda8d95cb45d62a5a8bbf9dd0ad39c5b25c8833efea07b880ca"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-musllinux_1_2_i686.whl", hash = "sha256:2de29005e11637e7a2361fa151f780ff8eb2543a0da1413bb951e9f14b699ef3"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:666ecce376999bf619756a24ce15bb14c5bfaf04bf00abc7e663ce17c3f34fe7"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:5246b14ca64a8675e0a7161f7af68fe3e910e6b90542b4bfb5439ba752191df6"}, + {file = "rpds_py-0.22.3.tar.gz", hash = "sha256:e32fee8ab45d3c2db6da19a5323bc3362237c8b653c70194414b892fd06a080d"}, ] [[package]] @@ -3737,13 +3814,13 @@ testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs ( [[package]] name = "six" -version = "1.16.0" +version = "1.17.0" description = "Python 2 and 3 compatibility utilities" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" files = [ - {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"}, - {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"}, + {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"}, + {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"}, ] [[package]] @@ -3770,60 +3847,21 @@ files = [ [[package]] name = "sqlalchemy" -version = "2.0.35" +version = "2.0.36" description = "Database Abstraction Library" optional = false python-versions = ">=3.7" files = [ - {file = "SQLAlchemy-2.0.35-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:67219632be22f14750f0d1c70e62f204ba69d28f62fd6432ba05ab295853de9b"}, - {file = "SQLAlchemy-2.0.35-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4668bd8faf7e5b71c0319407b608f278f279668f358857dbfd10ef1954ac9f90"}, - {file = "SQLAlchemy-2.0.35-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb8bea573863762bbf45d1e13f87c2d2fd32cee2dbd50d050f83f87429c9e1ea"}, - {file = "SQLAlchemy-2.0.35-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f552023710d4b93d8fb29a91fadf97de89c5926c6bd758897875435f2a939f33"}, - {file = "SQLAlchemy-2.0.35-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:016b2e665f778f13d3c438651dd4de244214b527a275e0acf1d44c05bc6026a9"}, - {file = "SQLAlchemy-2.0.35-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7befc148de64b6060937231cbff8d01ccf0bfd75aa26383ffdf8d82b12ec04ff"}, - {file = "SQLAlchemy-2.0.35-cp310-cp310-win32.whl", hash = "sha256:22b83aed390e3099584b839b93f80a0f4a95ee7f48270c97c90acd40ee646f0b"}, - {file = "SQLAlchemy-2.0.35-cp310-cp310-win_amd64.whl", hash = "sha256:a29762cd3d116585278ffb2e5b8cc311fb095ea278b96feef28d0b423154858e"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:e21f66748ab725ade40fa7af8ec8b5019c68ab00b929f6643e1b1af461eddb60"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8a6219108a15fc6d24de499d0d515c7235c617b2540d97116b663dade1a54d62"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:042622a5306c23b972192283f4e22372da3b8ddf5f7aac1cc5d9c9b222ab3ff6"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:627dee0c280eea91aed87b20a1f849e9ae2fe719d52cbf847c0e0ea34464b3f7"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:4fdcd72a789c1c31ed242fd8c1bcd9ea186a98ee8e5408a50e610edfef980d71"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:89b64cd8898a3a6f642db4eb7b26d1b28a497d4022eccd7717ca066823e9fb01"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-win32.whl", hash = "sha256:6a93c5a0dfe8d34951e8a6f499a9479ffb9258123551fa007fc708ae2ac2bc5e"}, - {file = "SQLAlchemy-2.0.35-cp311-cp311-win_amd64.whl", hash = "sha256:c68fe3fcde03920c46697585620135b4ecfdfc1ed23e75cc2c2ae9f8502c10b8"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:eb60b026d8ad0c97917cb81d3662d0b39b8ff1335e3fabb24984c6acd0c900a2"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6921ee01caf375363be5e9ae70d08ce7ca9d7e0e8983183080211a062d299468"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8cdf1a0dbe5ced887a9b127da4ffd7354e9c1a3b9bb330dce84df6b70ccb3a8d"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:93a71c8601e823236ac0e5d087e4f397874a421017b3318fd92c0b14acf2b6db"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e04b622bb8a88f10e439084486f2f6349bf4d50605ac3e445869c7ea5cf0fa8c"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:1b56961e2d31389aaadf4906d453859f35302b4eb818d34a26fab72596076bb8"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-win32.whl", hash = "sha256:0f9f3f9a3763b9c4deb8c5d09c4cc52ffe49f9876af41cc1b2ad0138878453cf"}, - {file = "SQLAlchemy-2.0.35-cp312-cp312-win_amd64.whl", hash = "sha256:25b0f63e7fcc2a6290cb5f7f5b4fc4047843504983a28856ce9b35d8f7de03cc"}, - {file = "SQLAlchemy-2.0.35-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:f021d334f2ca692523aaf7bbf7592ceff70c8594fad853416a81d66b35e3abf9"}, - {file = "SQLAlchemy-2.0.35-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:05c3f58cf91683102f2f0265c0db3bd3892e9eedabe059720492dbaa4f922da1"}, - {file = "SQLAlchemy-2.0.35-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:032d979ce77a6c2432653322ba4cbeabf5a6837f704d16fa38b5a05d8e21fa00"}, - {file = "SQLAlchemy-2.0.35-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:2e795c2f7d7249b75bb5f479b432a51b59041580d20599d4e112b5f2046437a3"}, - {file = "SQLAlchemy-2.0.35-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:cc32b2990fc34380ec2f6195f33a76b6cdaa9eecf09f0c9404b74fc120aef36f"}, - {file = "SQLAlchemy-2.0.35-cp37-cp37m-win32.whl", hash = "sha256:9509c4123491d0e63fb5e16199e09f8e262066e58903e84615c301dde8fa2e87"}, - {file = "SQLAlchemy-2.0.35-cp37-cp37m-win_amd64.whl", hash = "sha256:3655af10ebcc0f1e4e06c5900bb33e080d6a1fa4228f502121f28a3b1753cde5"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:4c31943b61ed8fdd63dfd12ccc919f2bf95eefca133767db6fbbd15da62078ec"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:a62dd5d7cc8626a3634208df458c5fe4f21200d96a74d122c83bc2015b333bc1"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0630774b0977804fba4b6bbea6852ab56c14965a2b0c7fc7282c5f7d90a1ae72"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8d625eddf7efeba2abfd9c014a22c0f6b3796e0ffb48f5d5ab106568ef01ff5a"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:ada603db10bb865bbe591939de854faf2c60f43c9b763e90f653224138f910d9"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c41411e192f8d3ea39ea70e0fae48762cd11a2244e03751a98bd3c0ca9a4e936"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-win32.whl", hash = "sha256:d299797d75cd747e7797b1b41817111406b8b10a4f88b6e8fe5b5e59598b43b0"}, - {file = "SQLAlchemy-2.0.35-cp38-cp38-win_amd64.whl", hash = "sha256:0375a141e1c0878103eb3d719eb6d5aa444b490c96f3fedab8471c7f6ffe70ee"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ccae5de2a0140d8be6838c331604f91d6fafd0735dbdcee1ac78fc8fbaba76b4"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2a275a806f73e849e1c309ac11108ea1a14cd7058577aba962cd7190e27c9e3c"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:732e026240cdd1c1b2e3ac515c7a23820430ed94292ce33806a95869c46bd139"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:890da8cd1941fa3dab28c5bac3b9da8502e7e366f895b3b8e500896f12f94d11"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:c0d8326269dbf944b9201911b0d9f3dc524d64779a07518199a58384c3d37a44"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:b76d63495b0508ab9fc23f8152bac63205d2a704cd009a2b0722f4c8e0cba8e0"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-win32.whl", hash = "sha256:69683e02e8a9de37f17985905a5eca18ad651bf592314b4d3d799029797d0eb3"}, - {file = "SQLAlchemy-2.0.35-cp39-cp39-win_amd64.whl", hash = "sha256:aee110e4ef3c528f3abbc3c2018c121e708938adeeff9006428dd7c8555e9b3f"}, - {file = "SQLAlchemy-2.0.35-py3-none-any.whl", hash = "sha256:2ab3f0336c0387662ce6221ad30ab3a5e6499aab01b9790879b6578fd9b8faa1"}, - {file = "sqlalchemy-2.0.35.tar.gz", hash = "sha256:e11d7ea4d24f0a262bccf9a7cd6284c976c5369dac21db237cff59586045ab9f"}, + {file = "SQLAlchemy-2.0.36-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c245b1fbade9c35e5bd3b64270ab49ce990369018289ecfde3f9c318411aaa07"}, + {file = "SQLAlchemy-2.0.36-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f9511d8dd4a6e9271d07d150fb2f81874a3c8c95e11ff9af3a2dfc35fe42ee44"}, + {file = "SQLAlchemy-2.0.36-cp310-cp310-win32.whl", hash = "sha256:c3f3631693003d8e585d4200730616b78fafd5a01ef8b698f6967da5c605b3fa"}, + {file = "SQLAlchemy-2.0.36-cp310-cp310-win_amd64.whl", hash = "sha256:a86bfab2ef46d63300c0f06936bd6e6c0105faa11d509083ba8f2f9d237fb5b5"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2519f3a5d0517fc159afab1015e54bb81b4406c278749779be57a569d8d1bb0d"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:39769a115f730d683b0eb7b694db9789267bcd027326cccc3125e862eb03bfd8"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-win32.whl", hash = "sha256:66bffbad8d6271bb1cc2f9a4ea4f86f80fe5e2e3e501a5ae2a3dc6a76e604e6f"}, + {file = "SQLAlchemy-2.0.36-cp311-cp311-win_amd64.whl", hash = "sha256:23623166bfefe1487d81b698c423f8678e80df8b54614c2bf4b4cfcd7c711959"}, + {file = "SQLAlchemy-2.0.36-py3-none-any.whl", hash = "sha256:fddbe92b4760c6f5d48162aef14824add991aeda8ddadb3c31d56eb15ca69f8e"}, + {file = "sqlalchemy-2.0.36.tar.gz", hash = "sha256:7f2767680b6d2398aea7082e45a774b2b0767b5c8d8ffb9c8b683088ea9b29c5"}, ] [package.dependencies] @@ -3836,7 +3874,7 @@ aioodbc = ["aioodbc", "greenlet (!=0.4.17)"] aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"] asyncio = ["greenlet (!=0.4.17)"] asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"] -mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"] +mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5,!=1.1.10)"] mssql = ["pyodbc"] mssql-pymssql = ["pymssql"] mssql-pyodbc = ["pyodbc"] @@ -3876,13 +3914,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"] [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -3955,33 +3993,63 @@ files = [ [[package]] name = "tomli" -version = "2.1.0" +version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, - {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"}, + {file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"}, + {file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"}, + {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"}, + {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"}, + {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"}, + {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"}, + {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"}, + {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"}, ] [[package]] name = "tornado" -version = "6.4.1" +version = "6.4.2" description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." optional = false python-versions = ">=3.8" files = [ - {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8"}, - {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14"}, - {file = "tornado-6.4.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4"}, - {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842"}, - {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3"}, - {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f"}, - {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4"}, - {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698"}, - {file = "tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d"}, - {file = "tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7"}, - {file = "tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9"}, + {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e828cce1123e9e44ae2a50a9de3055497ab1d0aeb440c5ac23064d9e44880da1"}, + {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:072ce12ada169c5b00b7d92a99ba089447ccc993ea2143c9ede887e0937aa803"}, + {file = "tornado-6.4.2-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a017d239bd1bb0919f72af256a970624241f070496635784d9bf0db640d3fec"}, + {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c36e62ce8f63409301537222faffcef7dfc5284f27eec227389f2ad11b09d946"}, + {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca9eb02196e789c9cb5c3c7c0f04fb447dc2adffd95265b2c7223a8a615ccbf"}, + {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:304463bd0772442ff4d0f5149c6f1c2135a1fae045adf070821c6cdc76980634"}, + {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:c82c46813ba483a385ab2a99caeaedf92585a1f90defb5693351fa7e4ea0bf73"}, + {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:932d195ca9015956fa502c6b56af9eb06106140d844a335590c1ec7f5277d10c"}, + {file = "tornado-6.4.2-cp38-abi3-win32.whl", hash = "sha256:2876cef82e6c5978fde1e0d5b1f919d756968d5b4282418f3146b79b58556482"}, + {file = "tornado-6.4.2-cp38-abi3-win_amd64.whl", hash = "sha256:908b71bf3ff37d81073356a5fadcc660eb10c1476ee6e2725588626ce7e5ca38"}, + {file = "tornado-6.4.2.tar.gz", hash = "sha256:92bad5b4746e9879fd7bf1eb21dce4e3fc5128d71601f80005afa39237ad620b"}, ] [[package]] @@ -4026,13 +4094,13 @@ files = [ [[package]] name = "types-protobuf" -version = "5.28.3.20241030" +version = "5.28.3.20241203" description = "Typing stubs for protobuf" optional = false python-versions = ">=3.8" files = [ - {file = "types-protobuf-5.28.3.20241030.tar.gz", hash = "sha256:f7e6b45845d75393fb41c0b3ce82c46d775f9771fae2097414a1dbfe5b51a988"}, - {file = "types_protobuf-5.28.3.20241030-py3-none-any.whl", hash = "sha256:f3dae16adf342d4fb5bb3673cabb22549a6252e5dd66fc52d8310b1a39c64ba9"}, + {file = "types_protobuf-5.28.3.20241203-py3-none-any.whl", hash = "sha256:5367632a4785394b0504e7c1e4d54a2dceeae9cd4f73a705d0f6499fc99cecb1"}, + {file = "types_protobuf-5.28.3.20241203.tar.gz", hash = "sha256:2e1c962bdf76c576506b5fc0678d28efa6652a54c04ae46562a6209e777bd789"}, ] [[package]] @@ -4052,13 +4120,13 @@ types-cffi = "*" [[package]] name = "types-python-dateutil" -version = "2.9.0.20241003" +version = "2.9.0.20241206" description = "Typing stubs for python-dateutil" optional = false python-versions = ">=3.8" files = [ - {file = "types-python-dateutil-2.9.0.20241003.tar.gz", hash = "sha256:58cb85449b2a56d6684e41aeefb4c4280631246a0da1a719bdbe6f3fb0317446"}, - {file = "types_python_dateutil-2.9.0.20241003-py3-none-any.whl", hash = "sha256:250e1d8e80e7bbc3a6c99b907762711d1a1cdd00e978ad39cb5940f6f0a87f3d"}, + {file = "types_python_dateutil-2.9.0.20241206-py3-none-any.whl", hash = "sha256:e248a4bc70a486d3e3ec84d0dc30eec3a5f979d6e7ee4123ae043eedbb987f53"}, + {file = "types_python_dateutil-2.9.0.20241206.tar.gz", hash = "sha256:18f493414c26ffba692a72369fea7a154c502646301ebfe3d56a04b3767284cb"}, ] [[package]] @@ -4128,13 +4196,13 @@ urllib3 = ">=2" [[package]] name = "types-setuptools" -version = "75.3.0.20241112" +version = "75.6.0.20241126" description = "Typing stubs for setuptools" optional = false python-versions = ">=3.8" files = [ - {file = "types-setuptools-75.3.0.20241112.tar.gz", hash = "sha256:f9e1ebd17a56f606e16395c4ee4efa1cdc394b9a2a0ee898a624058b4b62ef8f"}, - {file = "types_setuptools-75.3.0.20241112-py3-none-any.whl", hash = "sha256:78cb5fef4a6056d2f37114d27da90f4655a306e4e38042d7034a8a880bc3f5dd"}, + {file = "types_setuptools-75.6.0.20241126-py3-none-any.whl", hash = "sha256:aaae310a0e27033c1da8457d4d26ac673b0c8a0de7272d6d4708e263f2ea3b9b"}, + {file = "types_setuptools-75.6.0.20241126.tar.gz", hash = "sha256:7bf25ad4be39740e469f9268b6beddda6e088891fa5a27e985c6ce68bf62ace0"}, ] [[package]] @@ -4370,172 +4438,167 @@ files = [ [[package]] name = "wrapt" -version = "1.16.0" +version = "1.17.0" description = "Module for decorators, wrappers and monkey patching." optional = false -python-versions = ">=3.6" +python-versions = ">=3.8" files = [ - {file = "wrapt-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ffa565331890b90056c01db69c0fe634a776f8019c143a5ae265f9c6bc4bd6d4"}, - {file = "wrapt-1.16.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e4fdb9275308292e880dcbeb12546df7f3e0f96c6b41197e0cf37d2826359020"}, - {file = "wrapt-1.16.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bb2dee3874a500de01c93d5c71415fcaef1d858370d405824783e7a8ef5db440"}, - {file = "wrapt-1.16.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2a88e6010048489cda82b1326889ec075a8c856c2e6a256072b28eaee3ccf487"}, - {file = "wrapt-1.16.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ac83a914ebaf589b69f7d0a1277602ff494e21f4c2f743313414378f8f50a4cf"}, - {file = "wrapt-1.16.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:73aa7d98215d39b8455f103de64391cb79dfcad601701a3aa0dddacf74911d72"}, - {file = "wrapt-1.16.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:807cc8543a477ab7422f1120a217054f958a66ef7314f76dd9e77d3f02cdccd0"}, - {file = "wrapt-1.16.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bf5703fdeb350e36885f2875d853ce13172ae281c56e509f4e6eca049bdfb136"}, - {file = "wrapt-1.16.0-cp310-cp310-win32.whl", hash = "sha256:f6b2d0c6703c988d334f297aa5df18c45e97b0af3679bb75059e0e0bd8b1069d"}, - {file = "wrapt-1.16.0-cp310-cp310-win_amd64.whl", hash = "sha256:decbfa2f618fa8ed81c95ee18a387ff973143c656ef800c9f24fb7e9c16054e2"}, - {file = "wrapt-1.16.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1a5db485fe2de4403f13fafdc231b0dbae5eca4359232d2efc79025527375b09"}, - {file = "wrapt-1.16.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:75ea7d0ee2a15733684badb16de6794894ed9c55aa5e9903260922f0482e687d"}, - {file = "wrapt-1.16.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a452f9ca3e3267cd4d0fcf2edd0d035b1934ac2bd7e0e57ac91ad6b95c0c6389"}, - {file = "wrapt-1.16.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:43aa59eadec7890d9958748db829df269f0368521ba6dc68cc172d5d03ed8060"}, - {file = "wrapt-1.16.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:72554a23c78a8e7aa02abbd699d129eead8b147a23c56e08d08dfc29cfdddca1"}, - {file = "wrapt-1.16.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d2efee35b4b0a347e0d99d28e884dfd82797852d62fcd7ebdeee26f3ceb72cf3"}, - {file = "wrapt-1.16.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:6dcfcffe73710be01d90cae08c3e548d90932d37b39ef83969ae135d36ef3956"}, - {file = "wrapt-1.16.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:eb6e651000a19c96f452c85132811d25e9264d836951022d6e81df2fff38337d"}, - {file = "wrapt-1.16.0-cp311-cp311-win32.whl", hash = "sha256:66027d667efe95cc4fa945af59f92c5a02c6f5bb6012bff9e60542c74c75c362"}, - {file = "wrapt-1.16.0-cp311-cp311-win_amd64.whl", hash = "sha256:aefbc4cb0a54f91af643660a0a150ce2c090d3652cf4052a5397fb2de549cd89"}, - {file = "wrapt-1.16.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:5eb404d89131ec9b4f748fa5cfb5346802e5ee8836f57d516576e61f304f3b7b"}, - {file = "wrapt-1.16.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9090c9e676d5236a6948330e83cb89969f433b1943a558968f659ead07cb3b36"}, - {file = "wrapt-1.16.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94265b00870aa407bd0cbcfd536f17ecde43b94fb8d228560a1e9d3041462d73"}, - {file = "wrapt-1.16.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f2058f813d4f2b5e3a9eb2eb3faf8f1d99b81c3e51aeda4b168406443e8ba809"}, - {file = "wrapt-1.16.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98b5e1f498a8ca1858a1cdbffb023bfd954da4e3fa2c0cb5853d40014557248b"}, - {file = "wrapt-1.16.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:14d7dc606219cdd7405133c713f2c218d4252f2a469003f8c46bb92d5d095d81"}, - {file = "wrapt-1.16.0-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:49aac49dc4782cb04f58986e81ea0b4768e4ff197b57324dcbd7699c5dfb40b9"}, - {file = "wrapt-1.16.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:418abb18146475c310d7a6dc71143d6f7adec5b004ac9ce08dc7a34e2babdc5c"}, - {file = "wrapt-1.16.0-cp312-cp312-win32.whl", hash = "sha256:685f568fa5e627e93f3b52fda002c7ed2fa1800b50ce51f6ed1d572d8ab3e7fc"}, - {file = "wrapt-1.16.0-cp312-cp312-win_amd64.whl", hash = "sha256:dcdba5c86e368442528f7060039eda390cc4091bfd1dca41e8046af7c910dda8"}, - {file = "wrapt-1.16.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:d462f28826f4657968ae51d2181a074dfe03c200d6131690b7d65d55b0f360f8"}, - {file = "wrapt-1.16.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a33a747400b94b6d6b8a165e4480264a64a78c8a4c734b62136062e9a248dd39"}, - {file = "wrapt-1.16.0-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b3646eefa23daeba62643a58aac816945cadc0afaf21800a1421eeba5f6cfb9c"}, - {file = "wrapt-1.16.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ebf019be5c09d400cf7b024aa52b1f3aeebeff51550d007e92c3c1c4afc2a40"}, - {file = "wrapt-1.16.0-cp36-cp36m-musllinux_1_1_aarch64.whl", hash = "sha256:0d2691979e93d06a95a26257adb7bfd0c93818e89b1406f5a28f36e0d8c1e1fc"}, - {file = "wrapt-1.16.0-cp36-cp36m-musllinux_1_1_i686.whl", hash = "sha256:1acd723ee2a8826f3d53910255643e33673e1d11db84ce5880675954183ec47e"}, - {file = "wrapt-1.16.0-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:bc57efac2da352a51cc4658878a68d2b1b67dbe9d33c36cb826ca449d80a8465"}, - {file = "wrapt-1.16.0-cp36-cp36m-win32.whl", hash = "sha256:da4813f751142436b075ed7aa012a8778aa43a99f7b36afe9b742d3ed8bdc95e"}, - {file = "wrapt-1.16.0-cp36-cp36m-win_amd64.whl", hash = "sha256:6f6eac2360f2d543cc875a0e5efd413b6cbd483cb3ad7ebf888884a6e0d2e966"}, - {file = "wrapt-1.16.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:a0ea261ce52b5952bf669684a251a66df239ec6d441ccb59ec7afa882265d593"}, - {file = "wrapt-1.16.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7bd2d7ff69a2cac767fbf7a2b206add2e9a210e57947dd7ce03e25d03d2de292"}, - {file = "wrapt-1.16.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9159485323798c8dc530a224bd3ffcf76659319ccc7bbd52e01e73bd0241a0c5"}, - {file = "wrapt-1.16.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a86373cf37cd7764f2201b76496aba58a52e76dedfaa698ef9e9688bfd9e41cf"}, - {file = "wrapt-1.16.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:73870c364c11f03ed072dda68ff7aea6d2a3a5c3fe250d917a429c7432e15228"}, - {file = "wrapt-1.16.0-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:b935ae30c6e7400022b50f8d359c03ed233d45b725cfdd299462f41ee5ffba6f"}, - {file = "wrapt-1.16.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:db98ad84a55eb09b3c32a96c576476777e87c520a34e2519d3e59c44710c002c"}, - {file = "wrapt-1.16.0-cp37-cp37m-win32.whl", hash = "sha256:9153ed35fc5e4fa3b2fe97bddaa7cbec0ed22412b85bcdaf54aeba92ea37428c"}, - {file = "wrapt-1.16.0-cp37-cp37m-win_amd64.whl", hash = "sha256:66dfbaa7cfa3eb707bbfcd46dab2bc6207b005cbc9caa2199bcbc81d95071a00"}, - {file = "wrapt-1.16.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:1dd50a2696ff89f57bd8847647a1c363b687d3d796dc30d4dd4a9d1689a706f0"}, - {file = "wrapt-1.16.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:44a2754372e32ab315734c6c73b24351d06e77ffff6ae27d2ecf14cf3d229202"}, - {file = "wrapt-1.16.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8e9723528b9f787dc59168369e42ae1c3b0d3fadb2f1a71de14531d321ee05b0"}, - {file = "wrapt-1.16.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:dbed418ba5c3dce92619656802cc5355cb679e58d0d89b50f116e4a9d5a9603e"}, - {file = "wrapt-1.16.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:941988b89b4fd6b41c3f0bfb20e92bd23746579736b7343283297c4c8cbae68f"}, - {file = "wrapt-1.16.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:6a42cd0cfa8ffc1915aef79cb4284f6383d8a3e9dcca70c445dcfdd639d51267"}, - {file = "wrapt-1.16.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:1ca9b6085e4f866bd584fb135a041bfc32cab916e69f714a7d1d397f8c4891ca"}, - {file = "wrapt-1.16.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:d5e49454f19ef621089e204f862388d29e6e8d8b162efce05208913dde5b9ad6"}, - {file = "wrapt-1.16.0-cp38-cp38-win32.whl", hash = "sha256:c31f72b1b6624c9d863fc095da460802f43a7c6868c5dda140f51da24fd47d7b"}, - {file = "wrapt-1.16.0-cp38-cp38-win_amd64.whl", hash = "sha256:490b0ee15c1a55be9c1bd8609b8cecd60e325f0575fc98f50058eae366e01f41"}, - {file = "wrapt-1.16.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9b201ae332c3637a42f02d1045e1d0cccfdc41f1f2f801dafbaa7e9b4797bfc2"}, - {file = "wrapt-1.16.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2076fad65c6736184e77d7d4729b63a6d1ae0b70da4868adeec40989858eb3fb"}, - {file = "wrapt-1.16.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5cd603b575ebceca7da5a3a251e69561bec509e0b46e4993e1cac402b7247b8"}, - {file = "wrapt-1.16.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b47cfad9e9bbbed2339081f4e346c93ecd7ab504299403320bf85f7f85c7d46c"}, - {file = "wrapt-1.16.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f8212564d49c50eb4565e502814f694e240c55551a5f1bc841d4fcaabb0a9b8a"}, - {file = "wrapt-1.16.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:5f15814a33e42b04e3de432e573aa557f9f0f56458745c2074952f564c50e664"}, - {file = "wrapt-1.16.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:db2e408d983b0e61e238cf579c09ef7020560441906ca990fe8412153e3b291f"}, - {file = "wrapt-1.16.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:edfad1d29c73f9b863ebe7082ae9321374ccb10879eeabc84ba3b69f2579d537"}, - {file = "wrapt-1.16.0-cp39-cp39-win32.whl", hash = "sha256:ed867c42c268f876097248e05b6117a65bcd1e63b779e916fe2e33cd6fd0d3c3"}, - {file = "wrapt-1.16.0-cp39-cp39-win_amd64.whl", hash = "sha256:eb1b046be06b0fce7249f1d025cd359b4b80fc1c3e24ad9eca33e0dcdb2e4a35"}, - {file = "wrapt-1.16.0-py3-none-any.whl", hash = "sha256:6906c4100a8fcbf2fa735f6059214bb13b97f75b1a61777fcf6432121ef12ef1"}, - {file = "wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d"}, + {file = "wrapt-1.17.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2a0c23b8319848426f305f9cb0c98a6e32ee68a36264f45948ccf8e7d2b941f8"}, + {file = "wrapt-1.17.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b1ca5f060e205f72bec57faae5bd817a1560fcfc4af03f414b08fa29106b7e2d"}, + {file = "wrapt-1.17.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e185ec6060e301a7e5f8461c86fb3640a7beb1a0f0208ffde7a65ec4074931df"}, + {file = "wrapt-1.17.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb90765dd91aed05b53cd7a87bd7f5c188fcd95960914bae0d32c5e7f899719d"}, + {file = "wrapt-1.17.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:879591c2b5ab0a7184258274c42a126b74a2c3d5a329df16d69f9cee07bba6ea"}, + {file = "wrapt-1.17.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fce6fee67c318fdfb7f285c29a82d84782ae2579c0e1b385b7f36c6e8074fffb"}, + {file = "wrapt-1.17.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:0698d3a86f68abc894d537887b9bbf84d29bcfbc759e23f4644be27acf6da301"}, + {file = "wrapt-1.17.0-cp310-cp310-win32.whl", hash = "sha256:69d093792dc34a9c4c8a70e4973a3361c7a7578e9cd86961b2bbf38ca71e4e22"}, + {file = "wrapt-1.17.0-cp310-cp310-win_amd64.whl", hash = "sha256:f28b29dc158ca5d6ac396c8e0a2ef45c4e97bb7e65522bfc04c989e6fe814575"}, + {file = "wrapt-1.17.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:74bf625b1b4caaa7bad51d9003f8b07a468a704e0644a700e936c357c17dd45a"}, + {file = "wrapt-1.17.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f2a28eb35cf99d5f5bd12f5dd44a0f41d206db226535b37b0c60e9da162c3ed"}, + {file = "wrapt-1.17.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:81b1289e99cf4bad07c23393ab447e5e96db0ab50974a280f7954b071d41b489"}, + {file = "wrapt-1.17.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f2939cd4a2a52ca32bc0b359015718472d7f6de870760342e7ba295be9ebaf9"}, + {file = "wrapt-1.17.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6a9653131bda68a1f029c52157fd81e11f07d485df55410401f745007bd6d339"}, + {file = "wrapt-1.17.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:4e4b4385363de9052dac1a67bfb535c376f3d19c238b5f36bddc95efae15e12d"}, + {file = "wrapt-1.17.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:bdf62d25234290db1837875d4dceb2151e4ea7f9fff2ed41c0fde23ed542eb5b"}, + {file = "wrapt-1.17.0-cp311-cp311-win32.whl", hash = "sha256:5d8fd17635b262448ab8f99230fe4dac991af1dabdbb92f7a70a6afac8a7e346"}, + {file = "wrapt-1.17.0-cp311-cp311-win_amd64.whl", hash = "sha256:92a3d214d5e53cb1db8b015f30d544bc9d3f7179a05feb8f16df713cecc2620a"}, + {file = "wrapt-1.17.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:89fc28495896097622c3fc238915c79365dd0ede02f9a82ce436b13bd0ab7569"}, + {file = "wrapt-1.17.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:875d240fdbdbe9e11f9831901fb8719da0bd4e6131f83aa9f69b96d18fae7504"}, + {file = "wrapt-1.17.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e5ed16d95fd142e9c72b6c10b06514ad30e846a0d0917ab406186541fe68b451"}, + {file = "wrapt-1.17.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:18b956061b8db634120b58f668592a772e87e2e78bc1f6a906cfcaa0cc7991c1"}, + {file = "wrapt-1.17.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:daba396199399ccabafbfc509037ac635a6bc18510ad1add8fd16d4739cdd106"}, + {file = "wrapt-1.17.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:4d63f4d446e10ad19ed01188d6c1e1bb134cde8c18b0aa2acfd973d41fcc5ada"}, + {file = "wrapt-1.17.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8a5e7cc39a45fc430af1aefc4d77ee6bad72c5bcdb1322cfde852c15192b8bd4"}, + {file = "wrapt-1.17.0-cp312-cp312-win32.whl", hash = "sha256:0a0a1a1ec28b641f2a3a2c35cbe86c00051c04fffcfcc577ffcdd707df3f8635"}, + {file = "wrapt-1.17.0-cp312-cp312-win_amd64.whl", hash = "sha256:3c34f6896a01b84bab196f7119770fd8466c8ae3dfa73c59c0bb281e7b588ce7"}, + {file = "wrapt-1.17.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:714c12485aa52efbc0fc0ade1e9ab3a70343db82627f90f2ecbc898fdf0bb181"}, + {file = "wrapt-1.17.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:da427d311782324a376cacb47c1a4adc43f99fd9d996ffc1b3e8529c4074d393"}, + {file = "wrapt-1.17.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ba1739fb38441a27a676f4de4123d3e858e494fac05868b7a281c0a383c098f4"}, + {file = "wrapt-1.17.0-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e711fc1acc7468463bc084d1b68561e40d1eaa135d8c509a65dd534403d83d7b"}, + {file = "wrapt-1.17.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:140ea00c87fafc42739bd74a94a5a9003f8e72c27c47cd4f61d8e05e6dec8721"}, + {file = "wrapt-1.17.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:73a96fd11d2b2e77d623a7f26e004cc31f131a365add1ce1ce9a19e55a1eef90"}, + {file = "wrapt-1.17.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:0b48554952f0f387984da81ccfa73b62e52817a4386d070c75e4db7d43a28c4a"}, + {file = "wrapt-1.17.0-cp313-cp313-win32.whl", hash = "sha256:498fec8da10e3e62edd1e7368f4b24aa362ac0ad931e678332d1b209aec93045"}, + {file = "wrapt-1.17.0-cp313-cp313-win_amd64.whl", hash = "sha256:fd136bb85f4568fffca995bd3c8d52080b1e5b225dbf1c2b17b66b4c5fa02838"}, + {file = "wrapt-1.17.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:17fcf043d0b4724858f25b8826c36e08f9fb2e475410bece0ec44a22d533da9b"}, + {file = "wrapt-1.17.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e4a557d97f12813dc5e18dad9fa765ae44ddd56a672bb5de4825527c847d6379"}, + {file = "wrapt-1.17.0-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0229b247b0fc7dee0d36176cbb79dbaf2a9eb7ecc50ec3121f40ef443155fb1d"}, + {file = "wrapt-1.17.0-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8425cfce27b8b20c9b89d77fb50e368d8306a90bf2b6eef2cdf5cd5083adf83f"}, + {file = "wrapt-1.17.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:9c900108df470060174108012de06d45f514aa4ec21a191e7ab42988ff42a86c"}, + {file = "wrapt-1.17.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:4e547b447073fc0dbfcbff15154c1be8823d10dab4ad401bdb1575e3fdedff1b"}, + {file = "wrapt-1.17.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:914f66f3b6fc7b915d46c1cc424bc2441841083de01b90f9e81109c9759e43ab"}, + {file = "wrapt-1.17.0-cp313-cp313t-win32.whl", hash = "sha256:a4192b45dff127c7d69b3bdfb4d3e47b64179a0b9900b6351859f3001397dabf"}, + {file = "wrapt-1.17.0-cp313-cp313t-win_amd64.whl", hash = "sha256:4f643df3d4419ea3f856c5c3f40fec1d65ea2e89ec812c83f7767c8730f9827a"}, + {file = "wrapt-1.17.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:69c40d4655e078ede067a7095544bcec5a963566e17503e75a3a3e0fe2803b13"}, + {file = "wrapt-1.17.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f495b6754358979379f84534f8dd7a43ff8cff2558dcdea4a148a6e713a758f"}, + {file = "wrapt-1.17.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:baa7ef4e0886a6f482e00d1d5bcd37c201b383f1d314643dfb0367169f94f04c"}, + {file = "wrapt-1.17.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a8fc931382e56627ec4acb01e09ce66e5c03c384ca52606111cee50d931a342d"}, + {file = "wrapt-1.17.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:8f8909cdb9f1b237786c09a810e24ee5e15ef17019f7cecb207ce205b9b5fcce"}, + {file = "wrapt-1.17.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:ad47b095f0bdc5585bced35bd088cbfe4177236c7df9984b3cc46b391cc60627"}, + {file = "wrapt-1.17.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:948a9bd0fb2c5120457b07e59c8d7210cbc8703243225dbd78f4dfc13c8d2d1f"}, + {file = "wrapt-1.17.0-cp38-cp38-win32.whl", hash = "sha256:5ae271862b2142f4bc687bdbfcc942e2473a89999a54231aa1c2c676e28f29ea"}, + {file = "wrapt-1.17.0-cp38-cp38-win_amd64.whl", hash = "sha256:f335579a1b485c834849e9075191c9898e0731af45705c2ebf70e0cd5d58beed"}, + {file = "wrapt-1.17.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:d751300b94e35b6016d4b1e7d0e7bbc3b5e1751e2405ef908316c2a9024008a1"}, + {file = "wrapt-1.17.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7264cbb4a18dc4acfd73b63e4bcfec9c9802614572025bdd44d0721983fc1d9c"}, + {file = "wrapt-1.17.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:33539c6f5b96cf0b1105a0ff4cf5db9332e773bb521cc804a90e58dc49b10578"}, + {file = "wrapt-1.17.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c30970bdee1cad6a8da2044febd824ef6dc4cc0b19e39af3085c763fdec7de33"}, + {file = "wrapt-1.17.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:bc7f729a72b16ee21795a943f85c6244971724819819a41ddbaeb691b2dd85ad"}, + {file = "wrapt-1.17.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:6ff02a91c4fc9b6a94e1c9c20f62ea06a7e375f42fe57587f004d1078ac86ca9"}, + {file = "wrapt-1.17.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:2dfb7cff84e72e7bf975b06b4989477873dcf160b2fd89959c629535df53d4e0"}, + {file = "wrapt-1.17.0-cp39-cp39-win32.whl", hash = "sha256:2399408ac33ffd5b200480ee858baa58d77dd30e0dd0cab6a8a9547135f30a88"}, + {file = "wrapt-1.17.0-cp39-cp39-win_amd64.whl", hash = "sha256:4f763a29ee6a20c529496a20a7bcb16a73de27f5da6a843249c7047daf135977"}, + {file = "wrapt-1.17.0-py3-none-any.whl", hash = "sha256:d2c63b93548eda58abf5188e505ffed0229bf675f7c3090f8e36ad55b8cbc371"}, + {file = "wrapt-1.17.0.tar.gz", hash = "sha256:16187aa2317c731170a88ef35e8937ae0f533c402872c1ee5e6d079fcf320801"}, ] [[package]] name = "yarl" -version = "1.17.1" +version = "1.18.3" description = "Yet another URL library" optional = false python-versions = ">=3.9" files = [ - {file = "yarl-1.17.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b1794853124e2f663f0ea54efb0340b457f08d40a1cef78edfa086576179c91"}, - {file = "yarl-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:fbea1751729afe607d84acfd01efd95e3b31db148a181a441984ce9b3d3469da"}, - {file = "yarl-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8ee427208c675f1b6e344a1f89376a9613fc30b52646a04ac0c1f6587c7e46ec"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3b74ff4767d3ef47ffe0cd1d89379dc4d828d4873e5528976ced3b44fe5b0a21"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:62a91aefff3d11bf60e5956d340eb507a983a7ec802b19072bb989ce120cd948"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:846dd2e1243407133d3195d2d7e4ceefcaa5f5bf7278f0a9bda00967e6326b04"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3e844be8d536afa129366d9af76ed7cb8dfefec99f5f1c9e4f8ae542279a6dc3"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:cc7c92c1baa629cb03ecb0c3d12564f172218fb1739f54bf5f3881844daadc6d"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:ae3476e934b9d714aa8000d2e4c01eb2590eee10b9d8cd03e7983ad65dfbfcba"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c7e177c619342e407415d4f35dec63d2d134d951e24b5166afcdfd1362828e17"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:64cc6e97f14cf8a275d79c5002281f3040c12e2e4220623b5759ea7f9868d6a5"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:84c063af19ef5130084db70ada40ce63a84f6c1ef4d3dbc34e5e8c4febb20822"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:482c122b72e3c5ec98f11457aeb436ae4aecca75de19b3d1de7cf88bc40db82f"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:380e6c38ef692b8fd5a0f6d1fa8774d81ebc08cfbd624b1bca62a4d4af2f9931"}, - {file = "yarl-1.17.1-cp310-cp310-win32.whl", hash = "sha256:16bca6678a83657dd48df84b51bd56a6c6bd401853aef6d09dc2506a78484c7b"}, - {file = "yarl-1.17.1-cp310-cp310-win_amd64.whl", hash = "sha256:561c87fea99545ef7d692403c110b2f99dced6dff93056d6e04384ad3bc46243"}, - {file = "yarl-1.17.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:cbad927ea8ed814622305d842c93412cb47bd39a496ed0f96bfd42b922b4a217"}, - {file = "yarl-1.17.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:fca4b4307ebe9c3ec77a084da3a9d1999d164693d16492ca2b64594340999988"}, - {file = "yarl-1.17.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ff5c6771c7e3511a06555afa317879b7db8d640137ba55d6ab0d0c50425cab75"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5b29beab10211a746f9846baa39275e80034e065460d99eb51e45c9a9495bcca"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1a52a1ffdd824fb1835272e125385c32fd8b17fbdefeedcb4d543cc23b332d74"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:58c8e9620eb82a189c6c40cb6b59b4e35b2ee68b1f2afa6597732a2b467d7e8f"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d216e5d9b8749563c7f2c6f7a0831057ec844c68b4c11cb10fc62d4fd373c26d"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:881764d610e3269964fc4bb3c19bb6fce55422828e152b885609ec176b41cf11"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8c79e9d7e3d8a32d4824250a9c6401194fb4c2ad9a0cec8f6a96e09a582c2cc0"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:299f11b44d8d3a588234adbe01112126010bd96d9139c3ba7b3badd9829261c3"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:cc7d768260f4ba4ea01741c1b5fe3d3a6c70eb91c87f4c8761bbcce5181beafe"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:de599af166970d6a61accde358ec9ded821234cbbc8c6413acfec06056b8e860"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:2b24ec55fad43e476905eceaf14f41f6478780b870eda5d08b4d6de9a60b65b4"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:9fb815155aac6bfa8d86184079652c9715c812d506b22cfa369196ef4e99d1b4"}, - {file = "yarl-1.17.1-cp311-cp311-win32.whl", hash = "sha256:7615058aabad54416ddac99ade09a5510cf77039a3b903e94e8922f25ed203d7"}, - {file = "yarl-1.17.1-cp311-cp311-win_amd64.whl", hash = "sha256:14bc88baa44e1f84164a392827b5defb4fa8e56b93fecac3d15315e7c8e5d8b3"}, - {file = "yarl-1.17.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:327828786da2006085a4d1feb2594de6f6d26f8af48b81eb1ae950c788d97f61"}, - {file = "yarl-1.17.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:cc353841428d56b683a123a813e6a686e07026d6b1c5757970a877195f880c2d"}, - {file = "yarl-1.17.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c73df5b6e8fabe2ddb74876fb82d9dd44cbace0ca12e8861ce9155ad3c886139"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0bdff5e0995522706c53078f531fb586f56de9c4c81c243865dd5c66c132c3b5"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:06157fb3c58f2736a5e47c8fcbe1afc8b5de6fb28b14d25574af9e62150fcaac"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1654ec814b18be1af2c857aa9000de7a601400bd4c9ca24629b18486c2e35463"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f6595c852ca544aaeeb32d357e62c9c780eac69dcd34e40cae7b55bc4fb1147"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:459e81c2fb920b5f5df744262d1498ec2c8081acdcfe18181da44c50f51312f7"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:7e48cdb8226644e2fbd0bdb0a0f87906a3db07087f4de77a1b1b1ccfd9e93685"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:d9b6b28a57feb51605d6ae5e61a9044a31742db557a3b851a74c13bc61de5172"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:e594b22688d5747b06e957f1ef822060cb5cb35b493066e33ceac0cf882188b7"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:5f236cb5999ccd23a0ab1bd219cfe0ee3e1c1b65aaf6dd3320e972f7ec3a39da"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a2a64e62c7a0edd07c1c917b0586655f3362d2c2d37d474db1a509efb96fea1c"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:d0eea830b591dbc68e030c86a9569826145df485b2b4554874b07fea1275a199"}, - {file = "yarl-1.17.1-cp312-cp312-win32.whl", hash = "sha256:46ddf6e0b975cd680eb83318aa1d321cb2bf8d288d50f1754526230fcf59ba96"}, - {file = "yarl-1.17.1-cp312-cp312-win_amd64.whl", hash = "sha256:117ed8b3732528a1e41af3aa6d4e08483c2f0f2e3d3d7dca7cf538b3516d93df"}, - {file = "yarl-1.17.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:5d1d42556b063d579cae59e37a38c61f4402b47d70c29f0ef15cee1acaa64488"}, - {file = "yarl-1.17.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:c0167540094838ee9093ef6cc2c69d0074bbf84a432b4995835e8e5a0d984374"}, - {file = "yarl-1.17.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:2f0a6423295a0d282d00e8701fe763eeefba8037e984ad5de44aa349002562ac"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e5b078134f48552c4d9527db2f7da0b5359abd49393cdf9794017baec7506170"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d401f07261dc5aa36c2e4efc308548f6ae943bfff20fcadb0a07517a26b196d8"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b5f1ac7359e17efe0b6e5fec21de34145caef22b260e978336f325d5c84e6938"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f63d176a81555984e91f2c84c2a574a61cab7111cc907e176f0f01538e9ff6e"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9e275792097c9f7e80741c36de3b61917aebecc08a67ae62899b074566ff8556"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:81713b70bea5c1386dc2f32a8f0dab4148a2928c7495c808c541ee0aae614d67"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:aa46dce75078fceaf7cecac5817422febb4355fbdda440db55206e3bd288cfb8"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1ce36ded585f45b1e9bb36d0ae94765c6608b43bd2e7f5f88079f7a85c61a4d3"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:2d374d70fdc36f5863b84e54775452f68639bc862918602d028f89310a034ab0"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:2d9f0606baaec5dd54cb99667fcf85183a7477f3766fbddbe3f385e7fc253299"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:b0341e6d9a0c0e3cdc65857ef518bb05b410dbd70d749a0d33ac0f39e81a4258"}, - {file = "yarl-1.17.1-cp313-cp313-win32.whl", hash = "sha256:2e7ba4c9377e48fb7b20dedbd473cbcbc13e72e1826917c185157a137dac9df2"}, - {file = "yarl-1.17.1-cp313-cp313-win_amd64.whl", hash = "sha256:949681f68e0e3c25377462be4b658500e85ca24323d9619fdc41f68d46a1ffda"}, - {file = "yarl-1.17.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:8994b29c462de9a8fce2d591028b986dbbe1b32f3ad600b2d3e1c482c93abad6"}, - {file = "yarl-1.17.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f9cbfbc5faca235fbdf531b93aa0f9f005ec7d267d9d738761a4d42b744ea159"}, - {file = "yarl-1.17.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b40d1bf6e6f74f7c0a567a9e5e778bbd4699d1d3d2c0fe46f4b717eef9e96b95"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f5efe0661b9fcd6246f27957f6ae1c0eb29bc60552820f01e970b4996e016004"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b5c4804e4039f487e942c13381e6c27b4b4e66066d94ef1fae3f6ba8b953f383"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b5d6a6c9602fd4598fa07e0389e19fe199ae96449008d8304bf5d47cb745462e"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6f4c9156c4d1eb490fe374fb294deeb7bc7eaccda50e23775b2354b6a6739934"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d6324274b4e0e2fa1b3eccb25997b1c9ed134ff61d296448ab8269f5ac068c4c"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:d8a8b74d843c2638f3864a17d97a4acda58e40d3e44b6303b8cc3d3c44ae2d29"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7fac95714b09da9278a0b52e492466f773cfe37651cf467a83a1b659be24bf71"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:c180ac742a083e109c1a18151f4dd8675f32679985a1c750d2ff806796165b55"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:578d00c9b7fccfa1745a44f4eddfdc99d723d157dad26764538fbdda37209857"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:1a3b91c44efa29e6c8ef8a9a2b583347998e2ba52c5d8280dbd5919c02dfc3b5"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a7ac5b4984c468ce4f4a553df281450df0a34aefae02e58d77a0847be8d1e11f"}, - {file = "yarl-1.17.1-cp39-cp39-win32.whl", hash = "sha256:7294e38f9aa2e9f05f765b28ffdc5d81378508ce6dadbe93f6d464a8c9594473"}, - {file = "yarl-1.17.1-cp39-cp39-win_amd64.whl", hash = "sha256:eb6dce402734575e1a8cc0bb1509afca508a400a57ce13d306ea2c663bad1138"}, - {file = "yarl-1.17.1-py3-none-any.whl", hash = "sha256:f1790a4b1e8e8e028c391175433b9c8122c39b46e1663228158e61e6f915bf06"}, - {file = "yarl-1.17.1.tar.gz", hash = "sha256:067a63fcfda82da6b198fa73079b1ca40b7c9b7994995b6ee38acda728b64d47"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:602d98f2c2d929f8e697ed274fbadc09902c4025c5a9963bf4e9edfc3ab6f7ed"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c654d5207c78e0bd6d749f6dae1dcbbfde3403ad3a4b11f3c5544d9906969dde"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5094d9206c64181d0f6e76ebd8fb2f8fe274950a63890ee9e0ebfd58bf9d787b"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35098b24e0327fc4ebdc8ffe336cee0a87a700c24ffed13161af80124b7dc8e5"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3236da9272872443f81fedc389bace88408f64f89f75d1bdb2256069a8730ccc"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e2c08cc9b16f4f4bc522771d96734c7901e7ebef70c6c5c35dd0f10845270bcd"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:80316a8bd5109320d38eef8833ccf5f89608c9107d02d2a7f985f98ed6876990"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c1e1cc06da1491e6734f0ea1e6294ce00792193c463350626571c287c9a704db"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fea09ca13323376a2fdfb353a5fa2e59f90cd18d7ca4eaa1fd31f0a8b4f91e62"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e3b9fd71836999aad54084906f8663dffcd2a7fb5cdafd6c37713b2e72be1760"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:757e81cae69244257d125ff31663249b3013b5dc0a8520d73694aed497fb195b"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b1771de9944d875f1b98a745bc547e684b863abf8f8287da8466cf470ef52690"}, + {file = "yarl-1.18.3-cp310-cp310-win32.whl", hash = "sha256:8874027a53e3aea659a6d62751800cf6e63314c160fd607489ba5c2edd753cf6"}, + {file = "yarl-1.18.3-cp310-cp310-win_amd64.whl", hash = "sha256:93b2e109287f93db79210f86deb6b9bbb81ac32fc97236b16f7433db7fc437d8"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8503ad47387b8ebd39cbbbdf0bf113e17330ffd339ba1144074da24c545f0069"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02ddb6756f8f4517a2d5e99d8b2f272488e18dd0bfbc802f31c16c6c20f22193"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:67a283dd2882ac98cc6318384f565bffc751ab564605959df4752d42483ad889"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d980e0325b6eddc81331d3f4551e2a333999fb176fd153e075c6d1c2530aa8a8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b643562c12680b01e17239be267bc306bbc6aac1f34f6444d1bded0c5ce438ca"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c017a3b6df3a1bd45b9fa49a0f54005e53fbcad16633870104b66fa1a30a29d8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75674776d96d7b851b6498f17824ba17849d790a44d282929c42dbb77d4f17ae"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ccaa3a4b521b780a7e771cc336a2dba389a0861592bbce09a476190bb0c8b4b3"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d06d3005e668744e11ed80812e61efd77d70bb7f03e33c1598c301eea20efbb"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:9d41beda9dc97ca9ab0b9888cb71f7539124bc05df02c0cff6e5acc5a19dcc6e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:ba23302c0c61a9999784e73809427c9dbedd79f66a13d84ad1b1943802eaaf59"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:6748dbf9bfa5ba1afcc7556b71cda0d7ce5f24768043a02a58846e4a443d808d"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:0b0cad37311123211dc91eadcb322ef4d4a66008d3e1bdc404808992260e1a0e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0fb2171a4486bb075316ee754c6d8382ea6eb8b399d4ec62fde2b591f879778a"}, + {file = "yarl-1.18.3-cp311-cp311-win32.whl", hash = "sha256:61b1a825a13bef4a5f10b1885245377d3cd0bf87cba068e1d9a88c2ae36880e1"}, + {file = "yarl-1.18.3-cp311-cp311-win_amd64.whl", hash = "sha256:b9d60031cf568c627d028239693fd718025719c02c9f55df0a53e587aab951b5"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1dd4bdd05407ced96fed3d7f25dbbf88d2ffb045a0db60dbc247f5b3c5c25d50"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7c33dd1931a95e5d9a772d0ac5e44cac8957eaf58e3c8da8c1414de7dd27c576"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:25b411eddcfd56a2f0cd6a384e9f4f7aa3efee14b188de13048c25b5e91f1640"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:436c4fc0a4d66b2badc6c5fc5ef4e47bb10e4fd9bf0c79524ac719a01f3607c2"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e35ef8683211db69ffe129a25d5634319a677570ab6b2eba4afa860f54eeaf75"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84b2deecba4a3f1a398df819151eb72d29bfeb3b69abb145a00ddc8d30094512"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e5a1fea0fd4f5bfa7440a47eff01d9822a65b4488f7cff83155a0f31a2ecba"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0e883008013c0e4aef84dcfe2a0b172c4d23c2669412cf5b3371003941f72bb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5a3f356548e34a70b0172d8890006c37be92995f62d95a07b4a42e90fba54272"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ccd17349166b1bee6e529b4add61727d3f55edb7babbe4069b5764c9587a8cc6"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b958ddd075ddba5b09bb0be8a6d9906d2ce933aee81100db289badbeb966f54e"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c7d79f7d9aabd6011004e33b22bc13056a3e3fb54794d138af57f5ee9d9032cb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:4891ed92157e5430874dad17b15eb1fda57627710756c27422200c52d8a4e393"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ce1af883b94304f493698b00d0f006d56aea98aeb49d75ec7d98cd4a777e9285"}, + {file = "yarl-1.18.3-cp312-cp312-win32.whl", hash = "sha256:f91c4803173928a25e1a55b943c81f55b8872f0018be83e3ad4938adffb77dd2"}, + {file = "yarl-1.18.3-cp312-cp312-win_amd64.whl", hash = "sha256:7e2ee16578af3b52ac2f334c3b1f92262f47e02cc6193c598502bd46f5cd1477"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:90adb47ad432332d4f0bc28f83a5963f426ce9a1a8809f5e584e704b82685dcb"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:913829534200eb0f789d45349e55203a091f45c37a2674678744ae52fae23efa"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ef9f7768395923c3039055c14334ba4d926f3baf7b776c923c93d80195624782"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88a19f62ff30117e706ebc9090b8ecc79aeb77d0b1f5ec10d2d27a12bc9f66d0"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e17c9361d46a4d5addf777c6dd5eab0715a7684c2f11b88c67ac37edfba6c482"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a74a13a4c857a84a845505fd2d68e54826a2cd01935a96efb1e9d86c728e186"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41f7ce59d6ee7741af71d82020346af364949314ed3d87553763a2df1829cc58"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f52a265001d830bc425f82ca9eabda94a64a4d753b07d623a9f2863fde532b53"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:82123d0c954dc58db301f5021a01854a85bf1f3bb7d12ae0c01afc414a882ca2"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:2ec9bbba33b2d00999af4631a3397d1fd78290c48e2a3e52d8dd72db3a067ac8"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:fbd6748e8ab9b41171bb95c6142faf068f5ef1511935a0aa07025438dd9a9bc1"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:877d209b6aebeb5b16c42cbb377f5f94d9e556626b1bfff66d7b0d115be88d0a"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:b464c4ab4bfcb41e3bfd3f1c26600d038376c2de3297760dfe064d2cb7ea8e10"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8d39d351e7faf01483cc7ff7c0213c412e38e5a340238826be7e0e4da450fdc8"}, + {file = "yarl-1.18.3-cp313-cp313-win32.whl", hash = "sha256:61ee62ead9b68b9123ec24bc866cbef297dd266175d53296e2db5e7f797f902d"}, + {file = "yarl-1.18.3-cp313-cp313-win_amd64.whl", hash = "sha256:578e281c393af575879990861823ef19d66e2b1d0098414855dd367e234f5b3c"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:61e5e68cb65ac8f547f6b5ef933f510134a6bf31bb178be428994b0cb46c2a04"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:fe57328fbc1bfd0bd0514470ac692630f3901c0ee39052ae47acd1d90a436719"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a440a2a624683108a1b454705ecd7afc1c3438a08e890a1513d468671d90a04e"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:09c7907c8548bcd6ab860e5f513e727c53b4a714f459b084f6580b49fa1b9cee"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b4f6450109834af88cb4cc5ecddfc5380ebb9c228695afc11915a0bf82116789"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9ca04806f3be0ac6d558fffc2fdf8fcef767e0489d2684a21912cc4ed0cd1b8"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77a6e85b90a7641d2e07184df5557132a337f136250caafc9ccaa4a2a998ca2c"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6333c5a377c8e2f5fae35e7b8f145c617b02c939d04110c76f29ee3676b5f9a5"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:0b3c92fa08759dbf12b3a59579a4096ba9af8dd344d9a813fc7f5070d86bbab1"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:4ac515b860c36becb81bb84b667466885096b5fc85596948548b667da3bf9f24"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:045b8482ce9483ada4f3f23b3774f4e1bf4f23a2d5c912ed5170f68efb053318"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:a4bb030cf46a434ec0225bddbebd4b89e6471814ca851abb8696170adb163985"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:54d6921f07555713b9300bee9c50fb46e57e2e639027089b1d795ecd9f7fa910"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1d407181cfa6e70077df3377938c08012d18893f9f20e92f7d2f314a437c30b1"}, + {file = "yarl-1.18.3-cp39-cp39-win32.whl", hash = "sha256:ac36703a585e0929b032fbaab0707b75dc12703766d0b53486eabd5139ebadd5"}, + {file = "yarl-1.18.3-cp39-cp39-win_amd64.whl", hash = "sha256:ba87babd629f8af77f557b61e49e7c7cac36f22f871156b91e10a6e9d4f829e9"}, + {file = "yarl-1.18.3-py3-none-any.whl", hash = "sha256:b57f4f58099328dfb26c6a771d09fb20dbbae81d20cfb66141251ea063bd101b"}, + {file = "yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1"}, ] [package.dependencies] @@ -4565,4 +4628,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "b369e0441d1066761e311c967981f172881e87fc9f2f5b96b9891667bd336404" +content-hash = "82c8110d73b618825af6b9083eb22ad670344dd4160bf2a13a71d447149f9059" diff --git a/libs/community/pyproject.toml b/libs/community/pyproject.toml index 25c63358ed7fd..43a6fec431090 100644 --- a/libs/community/pyproject.toml +++ b/libs/community/pyproject.toml @@ -1,10 +1,10 @@ [build-system] -requires = ["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-community" -version = "0.3.7" +version = "0.3.10" description = "Community contributed LangChain integrations." authors = [] license = "MIT" @@ -12,15 +12,12 @@ readme = "README.md" repository = "https://github.com/langchain-ai/langchain" [tool.ruff] -exclude = [ - "tests/examples/non-utf8-encoding.py", - "tests/integration_tests/examples/non-utf8-encoding.py", -] +exclude = [ "tests/examples/non-utf8-encoding.py", "tests/integration_tests/examples/non-utf8-encoding.py",] [tool.mypy] ignore_missing_imports = "True" disallow_untyped_defs = "True" -exclude = ["notebooks", "examples", "example_data"] +exclude = [ "notebooks", "examples", "example_data",] [tool.codespell] skip = ".git,*.pdf,*.svg,*.pdf,*.yaml,*.ipynb,poetry.lock,*.min.js,*.css,package-lock.json,example_data,_dist,examples,*.trig" @@ -33,9 +30,9 @@ ignore-words-list = "momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogy [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.17" -langchain = "^0.3.7" -SQLAlchemy = ">=1.4,<2.0.36" +langchain-core = "^0.3.22" +langchain = "^0.3.10" +SQLAlchemy = ">=1.4,<3" requests = "^2" PyYAML = ">=5.3" aiohttp = "^3.8.3" @@ -49,28 +46,20 @@ version = ">=1.22.4,<2" python = "<3.12" [[tool.poetry.dependencies.numpy]] -version = ">=1.26.2,<2" +version = ">=1.26.2,<3" python = ">=3.12" [tool.ruff.lint] -select = ["E", "F", "I", "T201"] +select = [ "E", "F", "I", "T201",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--strict-markers --strict-config --durations=5 --snapshot-warn-unused -vv" -markers = [ - "requires: mark tests as requiring a specific library", - "scheduled: mark tests to run in scheduled testing", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "scheduled: mark tests to run in scheduled testing", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" -filterwarnings = [ - "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", - "ignore::langchain_core._api.deprecation.LangChainDeprecationWarning:test", - "ignore::langchain_core._api.deprecation.LangChainPendingDeprecationWarning:test", -] +filterwarnings = [ "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", "ignore::langchain_core._api.deprecation.LangChainDeprecationWarning:test", "ignore::langchain_core._api.deprecation.LangChainPendingDeprecationWarning:test",] [tool.poetry.group.test] optional = true @@ -91,7 +80,7 @@ optional = true pytest = "^7.4.4" pytest-cov = "^4.1.0" pytest-dotenv = "^0.5.2" -duckdb-engine = "^0.11.0" +duckdb-engine = "^0.13.6" pytest-watcher = "^0.2.6" freezegun = "^1.2.2" responses = "^0.22.0" diff --git a/libs/community/scripts/check_pydantic.sh b/libs/community/scripts/check_pydantic.sh index 99cb222d2b26e..ca83c483d515a 100755 --- a/libs/community/scripts/check_pydantic.sh +++ b/libs/community/scripts/check_pydantic.sh @@ -20,7 +20,7 @@ count=$(git grep -E '(@root_validator)|(@validator)|(@field_validator)|(@pre_ini # PRs that increase the current count will not be accepted. # PRs that decrease update the code in the repository # and allow decreasing the count of are welcome! -current_count=126 +current_count=125 if [ "$count" -gt "$current_count" ]; then echo "The PR seems to be introducing new usage of @root_validator and/or @field_validator." diff --git a/libs/community/tests/integration_tests/llms/test_writer.py b/libs/community/tests/integration_tests/llms/test_writer.py deleted file mode 100644 index db8ad809144b0..0000000000000 --- a/libs/community/tests/integration_tests/llms/test_writer.py +++ /dev/null @@ -1,10 +0,0 @@ -"""Test Writer API wrapper.""" - -from langchain_community.llms.writer import Writer - - -def test_writer_call() -> None: - """Test valid call to Writer.""" - llm = Writer() - output = llm.invoke("Say foo:") - assert isinstance(output, str) diff --git a/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py b/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py index 15d65de90b136..8b6bc19912a79 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py +++ b/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py @@ -3,27 +3,15 @@ import uuid import pytest -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_community.vectorstores import ApertureDB -class TestApertureDBReadWriteTestSuite(ReadWriteTestSuite): +class TestApertureStandard(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> ApertureDB: descriptor_set = uuid.uuid4().hex # Fresh descriptor set for each test return ApertureDB( embeddings=self.get_embeddings(), descriptor_set=descriptor_set ) - - -class TestAsyncApertureDBReadWriteTestSuite(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> ApertureDB: - descriptor_set = uuid.uuid4().hex # Fresh descriptor set for each test - return ApertureDB( - embeddings=self.get_embeddings(), descriptor_set=descriptor_set - ) diff --git a/libs/community/tests/integration_tests/vectorstores/test_hanavector.py b/libs/community/tests/integration_tests/vectorstores/test_hanavector.py index fd50baf529077..e1ffcd7af0eac 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_hanavector.py +++ b/libs/community/tests/integration_tests/vectorstores/test_hanavector.py @@ -1432,3 +1432,193 @@ def test_preexisting_specific_columns_for_returned_metadata_completeness( assert docs[0].metadata["quality"] == "good" assert docs[0].metadata["ready"] assert "NonExisting" not in docs[0].metadata.keys() + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_with_default_values(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INDEX_DEFAULT" + + # Delete table if it exists (cleanup from previous tests) + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test the creation of HNSW index + try: + vectorDB.create_hnsw_index() + except Exception as e: + pytest.fail(f"Failed to create HNSW index: {e}") + + # Perform a search using the index to confirm its correctness + search_result = vectorDB.max_marginal_relevance_search(texts[0], k=2, fetch_k=20) + + assert len(search_result) == 2 + assert search_result[0].page_content == texts[0] + assert search_result[1].page_content != texts[0] + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_with_defined_values(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INDEX_DEFINED" + + # Delete table if it exists (cleanup from previous tests) + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + distance_strategy=DistanceStrategy.EUCLIDEAN_DISTANCE, + ) + + # Test the creation of HNSW index with specific values + try: + vectorDB.create_hnsw_index( + index_name="my_L2_index", ef_search=500, m=100, ef_construction=200 + ) + except Exception as e: + pytest.fail(f"Failed to create HNSW index with defined values: {e}") + + # Perform a search using the index to confirm its correctness + search_result = vectorDB.max_marginal_relevance_search(texts[0], k=2, fetch_k=20) + + assert len(search_result) == 2 + assert search_result[0].page_content == texts[0] + assert search_result[1].page_content != texts[0] + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_after_initialization(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INDEX_AFTER_INIT" + + drop_table(test_setup.conn, table_name) + + # Initialize HanaDB without adding documents yet + vectorDB = HanaDB( + connection=test_setup.conn, + embedding=embedding, + table_name=table_name, + ) + + # Create HNSW index before adding documents + vectorDB.create_hnsw_index( + index_name="index_pre_add", ef_search=400, m=50, ef_construction=150 + ) + + # Add texts after index creation + vectorDB.add_texts(texts=texts) + + # Perform similarity search using the index + search_result = vectorDB.similarity_search(texts[0], k=3) + + # Assert that search result is valid and has expected length + assert len(search_result) == 3 + assert search_result[0].page_content == texts[0] + assert search_result[1].page_content != texts[0] + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_duplicate_hnsw_index_creation(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_DUPLICATE_INDEX" + + # Delete table if it exists (cleanup from previous tests) + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Create HNSW index for the first time + vectorDB.create_hnsw_index( + index_name="index_cosine", + ef_search=300, + m=80, + ef_construction=100, + ) + + with pytest.raises(Exception): + vectorDB.create_hnsw_index(ef_search=300, m=80, ef_construction=100) + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_invalid_m_value(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INVALID_M" + + # Cleanup: drop the table if it exists + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test invalid `m` value (too low) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(m=3) + + # Test invalid `m` value (too high) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(m=1001) + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_invalid_ef_construction(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INVALID_EF_CONSTRUCTION" + + # Cleanup: drop the table if it exists + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test invalid `ef_construction` value (too low) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_construction=0) + + # Test invalid `ef_construction` value (too high) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_construction=100001) + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_invalid_ef_search(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INVALID_EF_SEARCH" + + # Cleanup: drop the table if it exists + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test invalid `ef_search` value (too low) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_search=0) + + # Test invalid `ef_search` value (too high) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_search=100001) diff --git a/libs/community/tests/unit_tests/agents/test_openai_assistant.py b/libs/community/tests/unit_tests/agents/test_openai_assistant.py new file mode 100644 index 0000000000000..ea99ab5ccd753 --- /dev/null +++ b/libs/community/tests/unit_tests/agents/test_openai_assistant.py @@ -0,0 +1,39 @@ +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from langchain_community.agents.openai_assistant import OpenAIAssistantV2Runnable + + +def _create_mock_client(*args: Any, use_async: bool = False, **kwargs: Any) -> Any: + client = AsyncMock() if use_async else MagicMock() + client.beta.threads.runs.create = MagicMock(return_value=None) # type: ignore + return client + + +@pytest.mark.requires("openai") +def test_set_run_truncation_params() -> None: + client = _create_mock_client() + + assistant = OpenAIAssistantV2Runnable(assistant_id="assistant_xyz", client=client) + input = { + "content": "AI question", + "thread_id": "thread_xyz", + "instructions": "You're a helpful assistant; answer questions as best you can.", + "model": "gpt-4o", + "max_prompt_tokens": 2000, + "truncation_strategy": {"type": "last_messages", "last_messages": 10}, + } + expected_response = { + "assistant_id": "assistant_xyz", + "instructions": "You're a helpful assistant; answer questions as best you can.", + "model": "gpt-4o", + "max_prompt_tokens": 2000, + "truncation_strategy": {"type": "last_messages", "last_messages": 10}, + } + + assistant._create_run(input=input) + _, kwargs = client.beta.threads.runs.create.call_args + + assert kwargs == expected_response diff --git a/libs/community/tests/unit_tests/chat_models/test_writer.py b/libs/community/tests/unit_tests/chat_models/test_writer.py index 944a9dfeaba1f..2524f62957d1b 100644 --- a/libs/community/tests/unit_tests/chat_models/test_writer.py +++ b/libs/community/tests/unit_tests/chat_models/test_writer.py @@ -1,61 +1,251 @@ -"""Unit tests for Writer chat model integration.""" - import json -from typing import Any, Dict, List -from unittest.mock import AsyncMock, MagicMock, patch +from typing import Any, Dict, List, Literal, Optional, Tuple, Type +from unittest import mock +from unittest.mock import AsyncMock, MagicMock import pytest from langchain_core.callbacks.manager import CallbackManager +from langchain_core.language_models import BaseChatModel from langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage +from langchain_tests.unit_tests import ChatModelUnitTests from pydantic import SecretStr -from langchain_community.chat_models.writer import ChatWriter, _convert_dict_to_message +from langchain_community.chat_models.writer import ChatWriter from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler +"""Classes for mocking Writer responses.""" + + +class ChoiceDelta: + def __init__(self, content: str): + self.content = content + + +class ChunkChoice: + def __init__(self, index: int, finish_reason: str, delta: ChoiceDelta): + self.index = index + self.finish_reason = finish_reason + self.delta = delta + + +class ChatCompletionChunk: + def __init__( + self, + id: str, + object: str, + created: int, + model: str, + choices: List[ChunkChoice], + ): + self.id = id + self.object = object + self.created = created + self.model = model + self.choices = choices + + +class ToolCallFunction: + def __init__(self, name: str, arguments: str): + self.name = name + self.arguments = arguments + + +class ChoiceMessageToolCall: + def __init__(self, id: str, type: str, function: ToolCallFunction): + self.id = id + self.type = type + self.function = function + + +class Usage: + def __init__( + self, + prompt_tokens: int, + completion_tokens: int, + total_tokens: int, + ): + self.prompt_tokens = prompt_tokens + self.completion_tokens = completion_tokens + self.total_tokens = total_tokens + + +class ChoiceMessage: + def __init__( + self, + role: str, + content: str, + tool_calls: Optional[List[ChoiceMessageToolCall]] = None, + ): + self.role = role + self.content = content + self.tool_calls = tool_calls + + +class Choice: + def __init__(self, index: int, finish_reason: str, message: ChoiceMessage): + self.index = index + self.finish_reason = finish_reason + self.message = message + + +class Chat: + def __init__( + self, + id: str, + object: str, + created: int, + system_fingerprint: str, + model: str, + usage: Usage, + choices: List[Choice], + ): + self.id = id + self.object = object + self.created = created + self.system_fingerprint = system_fingerprint + self.model = model + self.usage = usage + self.choices = choices + + +@pytest.mark.requires("writerai") +class TestChatWriterCustom: + """Test case for ChatWriter""" + + @pytest.fixture(autouse=True) + def mock_unstreaming_completion(self) -> Chat: + """Fixture providing a mock API response.""" + return Chat( + id="chat-12345", + object="chat.completion", + created=1699000000, + model="palmyra-x-004", + system_fingerprint="v1", + usage=Usage(prompt_tokens=10, completion_tokens=8, total_tokens=18), + choices=[ + Choice( + index=0, + finish_reason="stop", + message=ChoiceMessage( + role="assistant", + content="Hello! How can I help you?", + ), + ) + ], + ) + + @pytest.fixture(autouse=True) + def mock_tool_call_choice_response(self) -> Chat: + return Chat( + id="chat-12345", + object="chat.completion", + created=1699000000, + model="palmyra-x-004", + system_fingerprint="v1", + usage=Usage(prompt_tokens=29, completion_tokens=32, total_tokens=61), + choices=[ + Choice( + index=0, + finish_reason="tool_calls", + message=ChoiceMessage( + role="assistant", + content="", + tool_calls=[ + ChoiceMessageToolCall( + id="call_abc123", + type="function", + function=ToolCallFunction( + name="GetWeather", + arguments='{"location": "London"}', + ), + ) + ], + ), + ) + ], + ) + + @pytest.fixture(autouse=True) + def mock_streaming_chunks(self) -> List[ChatCompletionChunk]: + """Fixture providing mock streaming response chunks.""" + return [ + ChatCompletionChunk( + id="chat-12345", + object="chat.completion", + created=1699000000, + model="palmyra-x-004", + choices=[ + ChunkChoice( + index=0, + finish_reason="stop", + delta=ChoiceDelta(content="Hello! "), + ) + ], + ), + ChatCompletionChunk( + id="chat-12345", + object="chat.completion", + created=1699000000, + model="palmyra-x-004", + choices=[ + ChunkChoice( + index=0, + finish_reason="stop", + delta=ChoiceDelta(content="How can I help you?"), + ) + ], + ), + ] -class TestChatWriter: def test_writer_model_param(self) -> None: """Test different ways to initialize the chat model.""" test_cases: List[dict] = [ - {"model_name": "palmyra-x-004", "writer_api_key": "test-key"}, - {"model": "palmyra-x-004", "writer_api_key": "test-key"}, - {"model_name": "palmyra-x-004", "writer_api_key": "test-key"}, + { + "model_name": "palmyra-x-004", + "api_key": "key", + }, + { + "model": "palmyra-x-004", + "api_key": "key", + }, + { + "model_name": "palmyra-x-004", + "api_key": "key", + }, { "model": "palmyra-x-004", - "writer_api_key": "test-key", "temperature": 0.5, + "api_key": "key", }, ] for case in test_cases: chat = ChatWriter(**case) assert chat.model_name == "palmyra-x-004" - assert chat.writer_api_key - assert chat.writer_api_key.get_secret_value() == "test-key" assert chat.temperature == (0.5 if "temperature" in case else 0.7) - def test_convert_dict_to_message_human(self) -> None: + def test_convert_writer_to_langchain_human(self) -> None: """Test converting a human message dict to a LangChain message.""" message = {"role": "user", "content": "Hello"} - result = _convert_dict_to_message(message) + result = ChatWriter._convert_writer_to_langchain(message) assert isinstance(result, HumanMessage) assert result.content == "Hello" - def test_convert_dict_to_message_ai(self) -> None: + def test_convert_writer_to_langchain_ai(self) -> None: """Test converting an AI message dict to a LangChain message.""" message = {"role": "assistant", "content": "Hello"} - result = _convert_dict_to_message(message) + result = ChatWriter._convert_writer_to_langchain(message) assert isinstance(result, AIMessage) assert result.content == "Hello" - def test_convert_dict_to_message_system(self) -> None: + def test_convert_writer_to_langchain_system(self) -> None: """Test converting a system message dict to a LangChain message.""" message = {"role": "system", "content": "You are a helpful assistant"} - result = _convert_dict_to_message(message) + result = ChatWriter._convert_writer_to_langchain(message) assert isinstance(result, SystemMessage) assert result.content == "You are a helpful assistant" - def test_convert_dict_to_message_tool_call(self) -> None: + def test_convert_writer_to_langchain_tool_call(self) -> None: """Test converting a tool call message dict to a LangChain message.""" content = json.dumps({"result": 42}) message = { @@ -64,12 +254,12 @@ def test_convert_dict_to_message_tool_call(self) -> None: "content": content, "tool_call_id": "call_abc123", } - result = _convert_dict_to_message(message) + result = ChatWriter._convert_writer_to_langchain(message) assert isinstance(result, ToolMessage) assert result.name == "get_number" assert result.content == content - def test_convert_dict_to_message_with_tool_calls(self) -> None: + def test_convert_writer_to_langchain_with_tool_calls(self) -> None: """Test converting an AIMessage with tool calls.""" message = { "role": "assistant", @@ -85,131 +275,55 @@ def test_convert_dict_to_message_with_tool_calls(self) -> None: } ], } - result = _convert_dict_to_message(message) + result = ChatWriter._convert_writer_to_langchain(message) assert isinstance(result, AIMessage) assert result.tool_calls assert len(result.tool_calls) == 1 assert result.tool_calls[0]["name"] == "get_weather" assert result.tool_calls[0]["args"]["location"] == "London" - @pytest.fixture(autouse=True) - def mock_completion(self) -> Dict[str, Any]: - """Fixture providing a mock API response.""" - return { - "id": "chat-12345", - "object": "chat.completion", - "created": 1699000000, - "model": "palmyra-x-004", - "choices": [ - { - "index": 0, - "message": { - "role": "assistant", - "content": "Hello! How can I help you?", - }, - "finish_reason": "stop", - } - ], - "usage": {"prompt_tokens": 10, "completion_tokens": 8, "total_tokens": 18}, - } - - @pytest.fixture(autouse=True) - def mock_response(self) -> Dict[str, Any]: - response = { - "id": "chat-12345", - "choices": [ - { - "message": { - "role": "assistant", - "content": "", - "tool_calls": [ - { - "id": "call_abc123", - "type": "function", - "function": { - "name": "GetWeather", - "arguments": '{"location": "London"}', - }, - } - ], - }, - "finish_reason": "tool_calls", - } - ], - } - return response - - @pytest.fixture(autouse=True) - def mock_streaming_chunks(self) -> List[Dict[str, Any]]: - """Fixture providing mock streaming response chunks.""" - return [ - { - "id": "chat-12345", - "object": "chat.completion.chunk", - "created": 1699000000, - "model": "palmyra-x-004", - "choices": [ - { - "index": 0, - "delta": { - "role": "assistant", - "content": "Hello", - }, - "finish_reason": None, - } - ], - }, - { - "id": "chat-12345", - "object": "chat.completion.chunk", - "created": 1699000000, - "model": "palmyra-x-004", - "choices": [ - { - "index": 0, - "delta": { - "content": "!", - }, - "finish_reason": "stop", - } - ], - }, - ] - - def test_sync_completion(self, mock_completion: Dict[str, Any]) -> None: + def test_sync_completion( + self, mock_unstreaming_completion: List[ChatCompletionChunk] + ) -> None: """Test basic chat completion with mocked response.""" - chat = ChatWriter(api_key=SecretStr("test-key")) + chat = ChatWriter(api_key=SecretStr("key")) + mock_client = MagicMock() - mock_client.chat.chat.return_value = mock_completion + mock_client.chat.chat.return_value = mock_unstreaming_completion - with patch.object(chat, "client", mock_client): + with mock.patch.object(chat, "client", mock_client): message = HumanMessage(content="Hi there!") response = chat.invoke([message]) assert isinstance(response, AIMessage) assert response.content == "Hello! How can I help you?" - async def test_async_completion(self, mock_completion: Dict[str, Any]) -> None: + @pytest.mark.asyncio + async def test_async_completion( + self, mock_unstreaming_completion: List[ChatCompletionChunk] + ) -> None: """Test async chat completion with mocked response.""" - chat = ChatWriter(api_key=SecretStr("test-key")) - mock_client = AsyncMock() - mock_client.chat.chat.return_value = mock_completion + chat = ChatWriter(api_key=SecretStr("key")) + + mock_async_client = AsyncMock() + mock_async_client.chat.chat.return_value = mock_unstreaming_completion - with patch.object(chat, "async_client", mock_client): + with mock.patch.object(chat, "async_client", mock_async_client): message = HumanMessage(content="Hi there!") response = await chat.ainvoke([message]) assert isinstance(response, AIMessage) assert response.content == "Hello! How can I help you?" - def test_sync_streaming(self, mock_streaming_chunks: List[Dict[str, Any]]) -> None: + def test_sync_streaming( + self, mock_streaming_chunks: List[ChatCompletionChunk] + ) -> None: """Test sync streaming with callback handler.""" callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) chat = ChatWriter( - streaming=True, + api_key=SecretStr("key"), callback_manager=callback_manager, max_tokens=10, - api_key=SecretStr("test-key"), ) mock_client = MagicMock() @@ -217,42 +331,46 @@ def test_sync_streaming(self, mock_streaming_chunks: List[Dict[str, Any]]) -> No mock_response.__iter__.return_value = mock_streaming_chunks mock_client.chat.chat.return_value = mock_response - with patch.object(chat, "client", mock_client): + with mock.patch.object(chat, "client", mock_client): message = HumanMessage(content="Hi") - response = chat.invoke([message]) - - assert isinstance(response, AIMessage) + response = chat.stream([message]) + response_message = "" + for chunk in response: + response_message += str(chunk.content) assert callback_handler.llm_streams > 0 - assert response.content == "Hello!" + assert response_message == "Hello! How can I help you?" + @pytest.mark.asyncio async def test_async_streaming( - self, mock_streaming_chunks: List[Dict[str, Any]] + self, mock_streaming_chunks: List[ChatCompletionChunk] ) -> None: """Test async streaming with callback handler.""" callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) chat = ChatWriter( - streaming=True, + api_key=SecretStr("key"), callback_manager=callback_manager, max_tokens=10, - api_key=SecretStr("test-key"), ) - mock_client = AsyncMock() + mock_async_client = AsyncMock() mock_response = AsyncMock() mock_response.__aiter__.return_value = mock_streaming_chunks - mock_client.chat.chat.return_value = mock_response + mock_async_client.chat.chat.return_value = mock_response - with patch.object(chat, "async_client", mock_client): + with mock.patch.object(chat, "async_client", mock_async_client): message = HumanMessage(content="Hi") - response = await chat.ainvoke([message]) - - assert isinstance(response, AIMessage) + response = chat.astream([message]) + response_message = "" + async for chunk in response: + response_message += str(chunk.content) assert callback_handler.llm_streams > 0 - assert response.content == "Hello!" + assert response_message == "Hello! How can I help you?" - def test_sync_tool_calling(self, mock_response: Dict[str, Any]) -> None: + def test_sync_tool_calling( + self, mock_tool_call_choice_response: Dict[str, Any] + ) -> None: """Test synchronous tool calling functionality.""" from pydantic import BaseModel, Field @@ -261,23 +379,27 @@ class GetWeather(BaseModel): location: str = Field(..., description="The location to get weather for") - mock_client = MagicMock() - mock_client.chat.chat.return_value = mock_response + chat = ChatWriter(api_key=SecretStr("key")) - chat = ChatWriter(api_key=SecretStr("test-key"), client=mock_client) + mock_client = MagicMock() + mock_client.chat.chat.return_value = mock_tool_call_choice_response chat_with_tools = chat.bind_tools( tools=[GetWeather], tool_choice="GetWeather", ) - response = chat_with_tools.invoke("What's the weather in London?") - assert isinstance(response, AIMessage) - assert response.tool_calls - assert response.tool_calls[0]["name"] == "GetWeather" - assert response.tool_calls[0]["args"]["location"] == "London" + with mock.patch.object(chat, "client", mock_client): + response = chat_with_tools.invoke("What's the weather in London?") + assert isinstance(response, AIMessage) + assert response.tool_calls + assert response.tool_calls[0]["name"] == "GetWeather" + assert response.tool_calls[0]["args"]["location"] == "London" - async def test_async_tool_calling(self, mock_response: Dict[str, Any]) -> None: + @pytest.mark.asyncio + async def test_async_tool_calling( + self, mock_tool_call_choice_response: Dict[str, Any] + ) -> None: """Test asynchronous tool calling functionality.""" from pydantic import BaseModel, Field @@ -286,18 +408,101 @@ class GetWeather(BaseModel): location: str = Field(..., description="The location to get weather for") - mock_client = AsyncMock() - mock_client.chat.chat.return_value = mock_response + mock_async_client = AsyncMock() + mock_async_client.chat.chat.return_value = mock_tool_call_choice_response - chat = ChatWriter(api_key=SecretStr("test-key"), async_client=mock_client) + chat = ChatWriter(api_key=SecretStr("key")) chat_with_tools = chat.bind_tools( tools=[GetWeather], tool_choice="GetWeather", ) - response = await chat_with_tools.ainvoke("What's the weather in London?") - assert isinstance(response, AIMessage) - assert response.tool_calls - assert response.tool_calls[0]["name"] == "GetWeather" - assert response.tool_calls[0]["args"]["location"] == "London" + with mock.patch.object(chat, "async_client", mock_async_client): + response = await chat_with_tools.ainvoke("What's the weather in London?") + assert isinstance(response, AIMessage) + assert response.tool_calls + assert response.tool_calls[0]["name"] == "GetWeather" + assert response.tool_calls[0]["args"]["location"] == "London" + + +@pytest.mark.requires("writerai") +class TestChatWriterStandart(ChatModelUnitTests): + """Test case for ChatWriter that inherits from standard LangChain tests.""" + + @property + def chat_model_class(self) -> Type[BaseChatModel]: + """Return ChatWriter model class.""" + return ChatWriter + + @property + def chat_model_params(self) -> Dict: + """Return any additional parameters needed.""" + return { + "api_key": "fake-api-key", + "model_name": "palmyra-x-004", + } + + @property + def has_tool_calling(self) -> bool: + """Writer supports tool/function calling.""" + return True + + @property + def tool_choice_value(self) -> Optional[str]: + """Value to use for tool choice in tests.""" + return "auto" + + @property + def has_structured_output(self) -> bool: + """Writer does not yet support structured output.""" + return False + + @property + def supports_image_inputs(self) -> bool: + """Writer does not support image inputs.""" + return False + + @property + def supports_video_inputs(self) -> bool: + """Writer does not support video inputs.""" + return False + + @property + def returns_usage_metadata(self) -> bool: + """Writer returns token usage information.""" + return True + + @property + def supports_anthropic_inputs(self) -> bool: + """Writer does not support anthropic inputs.""" + return False + + @property + def supports_image_tool_message(self) -> bool: + """Writer does not support image tool message.""" + return False + + @property + def supported_usage_metadata_details( + self, + ) -> Dict[ + Literal["invoke", "stream"], + List[ + Literal[ + "audio_input", + "audio_output", + "reasoning_output", + "cache_read_input", + "cache_creation_input", + ] + ], + ]: + """Return which types of usage metadata your model supports.""" + return {"invoke": ["cache_creation_input"], "stream": ["reasoning_output"]} + + @property + def init_from_env_params(self) -> Tuple[dict, dict, dict]: + """Return env vars, init args, and expected instance attrs for initializing + from env vars.""" + return {"WRITER_API_KEY": "key"}, {"api_key": "key"}, {"api_key": "key"} diff --git a/libs/community/tests/unit_tests/document_loaders/test_confluence.py b/libs/community/tests/unit_tests/document_loaders/test_confluence.py index feecb1588b571..abb47326beef7 100644 --- a/libs/community/tests/unit_tests/document_loaders/test_confluence.py +++ b/libs/community/tests/unit_tests/document_loaders/test_confluence.py @@ -195,6 +195,36 @@ def test_confluence_loader_when_content_format_and_keep_markdown_format_enabled( assert mock_confluence.cql.call_count == 0 assert mock_confluence.get_page_child_by_type.call_count == 0 + @pytest.mark.requires("markdownify") + def test_confluence_loader_when_include_lables_set_to_true( + self, mock_confluence: MagicMock + ) -> None: + # one response with two pages + mock_confluence.get_all_pages_from_space.return_value = [ + self._get_mock_page("123", include_labels=True), + self._get_mock_page("456", include_labels=False), + ] + mock_confluence.get_all_restrictions_for_content.side_effect = [ + self._get_mock_page_restrictions("123"), + self._get_mock_page_restrictions("456"), + ] + + conflence_loader = self._get_mock_confluence_loader( + mock_confluence, + space_key=self.MOCK_SPACE_KEY, + include_labels=True, + max_pages=2, + ) + + documents = conflence_loader.load() + + assert mock_confluence.get_all_pages_from_space.call_count == 1 + + assert len(documents) == 2 + assert all(isinstance(doc, Document) for doc in documents) + assert documents[0].metadata["labels"] == ["l1", "l2"] + assert documents[1].metadata["labels"] == [] + def _get_mock_confluence_loader( self, mock_confluence: MagicMock, **kwargs: Any ) -> ConfluenceLoader: @@ -208,7 +238,10 @@ def _get_mock_confluence_loader( return confluence_loader def _get_mock_page( - self, page_id: str, content_format: ContentFormat = ContentFormat.STORAGE + self, + page_id: str, + content_format: ContentFormat = ContentFormat.STORAGE, + include_labels: bool = False, ) -> Dict: return { "id": f"{page_id}", @@ -216,6 +249,20 @@ def _get_mock_page( "body": { f"{content_format.name.lower()}": {"value": f"

      Content {page_id}

      "} }, + **( + { + "metadata": { + "labels": { + "results": [ + {"prefix": "global", "name": "l1", "id": "111"}, + {"prefix": "global", "name": "l2", "id": "222"}, + ] + } + } + if include_labels + else {}, + } + ), "status": "current", "type": "page", "_links": { diff --git a/libs/community/tests/unit_tests/document_loaders/test_imports.py b/libs/community/tests/unit_tests/document_loaders/test_imports.py index b49a1b7cc4a2e..ddeaf734b0fe8 100644 --- a/libs/community/tests/unit_tests/document_loaders/test_imports.py +++ b/libs/community/tests/unit_tests/document_loaders/test_imports.py @@ -105,6 +105,7 @@ "MergedDataLoader", "ModernTreasuryLoader", "MongodbLoader", + "NeedleLoader", "NewsURLLoader", "NotebookLoader", "NotionDBLoader", diff --git a/libs/community/tests/unit_tests/document_loaders/test_needle.py b/libs/community/tests/unit_tests/document_loaders/test_needle.py new file mode 100644 index 0000000000000..d8f7a22fb0f64 --- /dev/null +++ b/libs/community/tests/unit_tests/document_loaders/test_needle.py @@ -0,0 +1,75 @@ +import pytest +from pytest_mock import MockerFixture + + +@pytest.mark.requires("needle") +def test_add_and_fetch_files(mocker: MockerFixture) -> None: + """ + Test adding and fetching files using the NeedleLoader with a mock. + """ + from langchain_community.document_loaders.needle import NeedleLoader # noqa: I001 + from needle.v1.models import CollectionFile # noqa: I001 + + # Create mock instances using mocker + # Create mock instances using mocker + mock_files = mocker.Mock() + mock_files.add.return_value = [ + CollectionFile( + id="mock_id", + name="tech-radar-30.pdf", + url="https://example.com/", + status="indexed", + type="mock_type", + user_id="mock_user_id", + connector_id="mock_connector_id", + size=1234, + md5_hash="mock_md5_hash", + created_at="2024-01-01T00:00:00Z", + updated_at="2024-01-01T00:00:00Z", + ) + ] + mock_files.list.return_value = [ + CollectionFile( + id="mock_id", + name="tech-radar-30.pdf", + url="https://example.com/", + status="indexed", + type="mock_type", + user_id="mock_user_id", + connector_id="mock_connector_id", + size=1234, + md5_hash="mock_md5_hash", + created_at="2024-01-01T00:00:00Z", + updated_at="2024-01-01T00:00:00Z", + ) + ] + + mock_collections = mocker.Mock() + mock_collections.files = mock_files + + mock_needle_client = mocker.Mock() + mock_needle_client.collections = mock_collections + + # Patch the NeedleClient to return the mock client + mocker.patch("needle.v1.NeedleClient", return_value=mock_needle_client) + + # Initialize NeedleLoader with mock API key and collection ID + document_store = NeedleLoader( + needle_api_key="fake_api_key", + collection_id="fake_collection_id", + ) + + # Define files to add + files = { + "tech-radar-30.pdf": "https://www.thoughtworks.com/content/dam/thoughtworks/documents/radar/2024/04/tr_technology_radar_vol_30_en.pdf" + } + + # Add files to the collection using the mock client + document_store.add_files(files=files) + + # Fetch the added files using the mock client + added_files = document_store._fetch_documents() + + # Assertions to verify that the file was added and fetched correctly + assert isinstance(added_files[0].metadata["title"], str) + assert isinstance(added_files[0].metadata["source"], str) diff --git a/libs/community/tests/unit_tests/embeddings/test_imports.py b/libs/community/tests/unit_tests/embeddings/test_imports.py index a6f26ce0c3fa6..ba9e9590f8103 100644 --- a/libs/community/tests/unit_tests/embeddings/test_imports.py +++ b/libs/community/tests/unit_tests/embeddings/test_imports.py @@ -26,6 +26,7 @@ "MlflowAIGatewayEmbeddings", "MlflowEmbeddings", "MlflowCohereEmbeddings", + "Model2vecEmbeddings", "ModelScopeEmbeddings", "TensorflowHubEmbeddings", "SagemakerEndpointEmbeddings", diff --git a/libs/community/tests/unit_tests/embeddings/test_model2vec.py b/libs/community/tests/unit_tests/embeddings/test_model2vec.py new file mode 100644 index 0000000000000..f1f6d0788dfba --- /dev/null +++ b/libs/community/tests/unit_tests/embeddings/test_model2vec.py @@ -0,0 +1,11 @@ +from langchain_community.embeddings.model2vec import Model2vecEmbeddings + + +def test_hugginggface_inferenceapi_embedding_documents_init() -> None: + """Test model2vec embeddings.""" + try: + embedding = Model2vecEmbeddings("minishlab/potion-base-8M") + assert len(embedding.embed_query("hi")) == 256 + except Exception: + # model2vec is not installed + assert True diff --git a/libs/community/tests/unit_tests/llms/test_writer.py b/libs/community/tests/unit_tests/llms/test_writer.py new file mode 100644 index 0000000000000..ffdee04db0796 --- /dev/null +++ b/libs/community/tests/unit_tests/llms/test_writer.py @@ -0,0 +1,202 @@ +from typing import List +from unittest import mock +from unittest.mock import AsyncMock, MagicMock + +import pytest +from langchain_core.callbacks import CallbackManager +from pydantic import SecretStr + +from langchain_community.llms.writer import Writer +from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler + +"""Classes for mocking Writer responses.""" + + +class Choice: + def __init__(self, text: str): + self.text = text + + +class Completion: + def __init__(self, choices: List[Choice]): + self.choices = choices + + +class StreamingData: + def __init__(self, value: str): + self.value = value + + +@pytest.mark.requires("writerai") +class TestWriterLLM: + """Unit tests for Writer LLM integration.""" + + @pytest.fixture(autouse=True) + def mock_unstreaming_completion(self) -> Completion: + """Fixture providing a mock API response.""" + return Completion(choices=[Choice(text="Hello! How can I help you?")]) + + @pytest.fixture(autouse=True) + def mock_streaming_completion(self) -> List[StreamingData]: + """Fixture providing mock streaming response chunks.""" + return [ + StreamingData(value="Hello! "), + StreamingData(value="How can I"), + StreamingData(value=" help you?"), + ] + + def test_sync_unstream_completion( + self, mock_unstreaming_completion: Completion + ) -> None: + """Test basic llm call with mocked response.""" + mock_client = MagicMock() + mock_client.completions.create.return_value = mock_unstreaming_completion + + llm = Writer(api_key=SecretStr("key")) + + with mock.patch.object(llm, "client", mock_client): + response_text = llm.invoke(input="Hello") + + assert response_text == "Hello! How can I help you?" + + def test_sync_unstream_completion_with_params( + self, mock_unstreaming_completion: Completion + ) -> None: + """Test llm call with passed params with mocked response.""" + mock_client = MagicMock() + mock_client.completions.create.return_value = mock_unstreaming_completion + + llm = Writer(api_key=SecretStr("key"), temperature=1) + + with mock.patch.object(llm, "client", mock_client): + response_text = llm.invoke(input="Hello") + + assert response_text == "Hello! How can I help you?" + + @pytest.mark.asyncio + async def test_async_unstream_completion( + self, mock_unstreaming_completion: Completion + ) -> None: + """Test async chat completion with mocked response.""" + mock_async_client = AsyncMock() + mock_async_client.completions.create.return_value = mock_unstreaming_completion + + llm = Writer(api_key=SecretStr("key")) + + with mock.patch.object(llm, "async_client", mock_async_client): + response_text = await llm.ainvoke(input="Hello") + + assert response_text == "Hello! How can I help you?" + + @pytest.mark.asyncio + async def test_async_unstream_completion_with_params( + self, mock_unstreaming_completion: Completion + ) -> None: + """Test async llm call with passed params with mocked response.""" + mock_async_client = AsyncMock() + mock_async_client.completions.create.return_value = mock_unstreaming_completion + + llm = Writer(api_key=SecretStr("key"), temperature=1) + + with mock.patch.object(llm, "async_client", mock_async_client): + response_text = await llm.ainvoke(input="Hello") + + assert response_text == "Hello! How can I help you?" + + def test_sync_streaming_completion( + self, mock_streaming_completion: List[StreamingData] + ) -> None: + """Test sync streaming.""" + + mock_client = MagicMock() + mock_response = MagicMock() + mock_response.__iter__.return_value = mock_streaming_completion + mock_client.completions.create.return_value = mock_response + + llm = Writer(api_key=SecretStr("key")) + + with mock.patch.object(llm, "client", mock_client): + response = llm.stream(input="Hello") + + response_message = "" + for chunk in response: + response_message += chunk + + assert response_message == "Hello! How can I help you?" + + def test_sync_streaming_completion_with_callback_handler( + self, mock_streaming_completion: List[StreamingData] + ) -> None: + """Test sync streaming with callback handler.""" + callback_handler = FakeCallbackHandler() + callback_manager = CallbackManager([callback_handler]) + + mock_client = MagicMock() + mock_response = MagicMock() + mock_response.__iter__.return_value = mock_streaming_completion + mock_client.completions.create.return_value = mock_response + + llm = Writer( + api_key=SecretStr("key"), + callback_manager=callback_manager, + ) + + with mock.patch.object(llm, "client", mock_client): + response = llm.stream(input="Hello") + + response_message = "" + for chunk in response: + response_message += chunk + + assert callback_handler.llm_streams == 3 + assert response_message == "Hello! How can I help you?" + + @pytest.mark.asyncio + async def test_async_streaming_completion( + self, mock_streaming_completion: Completion + ) -> None: + """Test async streaming with callback handler.""" + + mock_async_client = AsyncMock() + mock_response = AsyncMock() + mock_response.__aiter__.return_value = mock_streaming_completion + mock_async_client.completions.create.return_value = mock_response + + llm = Writer(api_key=SecretStr("key")) + + with mock.patch.object(llm, "async_client", mock_async_client): + response = llm.astream(input="Hello") + + response_message = "" + async for chunk in response: + response_message += str(chunk) + + assert response_message == "Hello! How can I help you?" + + @pytest.mark.asyncio + async def test_async_streaming_completion_with_callback_handler( + self, mock_streaming_completion: Completion + ) -> None: + """Test async streaming with callback handler.""" + callback_handler = FakeCallbackHandler() + callback_manager = CallbackManager([callback_handler]) + + mock_async_client = AsyncMock() + mock_response = AsyncMock() + mock_response.__aiter__.return_value = mock_streaming_completion + mock_async_client.completions.create.return_value = mock_response + + llm = Writer( + api_key=SecretStr("key"), + callback_manager=callback_manager, + ) + + with mock.patch.object(llm, "async_client", mock_async_client): + response = llm.astream(input="Hello") + + response_message = "" + async for chunk in response: + response_message += str(chunk) + + assert callback_handler.llm_streams == 3 + assert response_message == "Hello! How can I help you?" diff --git a/libs/community/tests/unit_tests/query_constructors/test_databricks_vector_search.py b/libs/community/tests/unit_tests/query_constructors/test_databricks_vector_search.py index 1f38f3b1b6093..e71e32c34eb2d 100644 --- a/libs/community/tests/unit_tests/query_constructors/test_databricks_vector_search.py +++ b/libs/community/tests/unit_tests/query_constructors/test_databricks_vector_search.py @@ -109,7 +109,7 @@ def test_visit_structured_query_with_one_arg_filter() -> None: filter=comp, ) - expected = (query, {"filters": {"country": "France"}}) + expected = (query, {"filter": {"country": "France"}}) actual = DEFAULT_TRANSLATOR.visit_structured_query(structured_query) assert expected == actual @@ -134,7 +134,7 @@ def test_visit_structured_query_with_multiple_arg_filter_and_operator() -> None: expected = ( query, - {"filters": {"country": "France", "year >=": 1888, "year <=": 1900}}, + {"filter": {"country": "France", "year >=": 1888, "year <=": 1900}}, ) actual = DEFAULT_TRANSLATOR.visit_structured_query(structured_query) diff --git a/libs/community/tests/unit_tests/retrievers/test_bm25.py b/libs/community/tests/unit_tests/retrievers/test_bm25.py index ef40b25ba7dee..81afae84c72c7 100644 --- a/libs/community/tests/unit_tests/retrievers/test_bm25.py +++ b/libs/community/tests/unit_tests/retrievers/test_bm25.py @@ -43,3 +43,42 @@ def test_repr() -> None: ] bm25_retriever = BM25Retriever.from_documents(documents=input_docs) assert "I have a pen" not in repr(bm25_retriever) + + +@pytest.mark.requires("rank_bm25") +def test_doc_id() -> None: + docs_with_ids = [ + Document(page_content="I have a pen.", id="1"), + Document(page_content="Do you have a pen?", id="2"), + Document(page_content="I have a bag.", id="3"), + ] + docs_without_ids = [ + Document(page_content="I have a pen."), + Document(page_content="Do you have a pen?"), + Document(page_content="I have a bag."), + ] + docs_with_some_ids = [ + Document(page_content="I have a pen.", id="1"), + Document(page_content="Do you have a pen?"), + Document(page_content="I have a bag.", id="3"), + ] + bm25_retriever_with_ids = BM25Retriever.from_documents(documents=docs_with_ids) + bm25_retriever_without_ids = BM25Retriever.from_documents( + documents=docs_without_ids + ) + bm25_retriever_with_some_ids = BM25Retriever.from_documents( + documents=docs_with_some_ids + ) + for doc in bm25_retriever_with_ids.docs: + assert doc.id is not None + for doc in bm25_retriever_without_ids.docs: + assert doc.id is None + for doc in bm25_retriever_with_some_ids.docs: + if doc.page_content == "I have a pen.": + assert doc.id == "1" + elif doc.page_content == "Do you have a pen?": + assert doc.id is None + elif doc.page_content == "I have a bag.": + assert doc.id == "3" + else: + raise ValueError("Unexpected document") diff --git a/libs/community/tests/unit_tests/retrievers/test_imports.py b/libs/community/tests/unit_tests/retrievers/test_imports.py index f5b791139a867..dde08e2f81700 100644 --- a/libs/community/tests/unit_tests/retrievers/test_imports.py +++ b/libs/community/tests/unit_tests/retrievers/test_imports.py @@ -26,6 +26,7 @@ "MetalRetriever", "MilvusRetriever", "NanoPQRetriever", + "NeedleRetriever", "OutlineRetriever", "PineconeHybridSearchRetriever", "PubMedRetriever", diff --git a/libs/community/tests/unit_tests/retrievers/test_needle.py b/libs/community/tests/unit_tests/retrievers/test_needle.py new file mode 100644 index 0000000000000..853250d409ff7 --- /dev/null +++ b/libs/community/tests/unit_tests/retrievers/test_needle.py @@ -0,0 +1,72 @@ +from typing import Any + +import pytest +from pytest_mock import MockerFixture + + +# Mock class to simulate search results from Needle API +class MockSearchResult: + def __init__(self, content: str) -> None: + self.content = content + + +# Mock class to simulate NeedleClient and its collections behavior +class MockNeedleClient: + def __init__(self, api_key: str) -> None: + self.api_key = api_key + self.collections = self.MockCollections() + + class MockCollections: + def search(self, collection_id: str, text: str) -> list[MockSearchResult]: + return [ + MockSearchResult(content=f"Result for query: {text}"), + MockSearchResult(content=f"Another result for query: {text}"), + ] + + +@pytest.mark.requires("needle") +def test_needle_retriever_initialization() -> None: + """ + Test that the NeedleRetriever is initialized correctly. + """ + from langchain_community.retrievers.needle import NeedleRetriever # noqa: I001 + + retriever = NeedleRetriever( + needle_api_key="mock_api_key", + collection_id="mock_collection_id", + ) + + assert retriever.needle_api_key == "mock_api_key" + assert retriever.collection_id == "mock_collection_id" + + +@pytest.mark.requires("needle") +def test_get_relevant_documents(mocker: MockerFixture) -> None: + """ + Test that the retriever correctly fetches documents. + """ + from langchain_community.retrievers.needle import NeedleRetriever # noqa: I001 + + # Patch the actual NeedleClient import path used in the NeedleRetriever + mocker.patch("needle.v1.NeedleClient", new=MockNeedleClient) + + # Initialize the retriever with mocked API key and collection ID + retriever = NeedleRetriever( + needle_api_key="mock_api_key", + collection_id="mock_collection_id", + ) + + mock_run_manager: Any = None + + # Perform the search + query = "What is RAG?" + retrieved_documents = retriever._get_relevant_documents( + query, run_manager=mock_run_manager + ) + + # Validate the results + assert len(retrieved_documents) == 2 + assert retrieved_documents[0].page_content == "Result for query: What is RAG?" + assert ( + retrieved_documents[1].page_content == "Another result for query: What is RAG?" + ) diff --git a/libs/community/tests/unit_tests/vectorstores/test_inmemory.py b/libs/community/tests/unit_tests/vectorstores/test_inmemory.py index b650cda14fdd1..a2bebcd426982 100644 --- a/libs/community/tests/unit_tests/vectorstores/test_inmemory.py +++ b/libs/community/tests/unit_tests/vectorstores/test_inmemory.py @@ -3,10 +3,7 @@ import pytest from langchain_core.documents import Document -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_community.vectorstores.inmemory import InMemoryVectorStore from tests.integration_tests.vectorstores.fake_embeddings import ( @@ -26,18 +23,12 @@ def _AnyDocument(**kwargs: Any) -> Document: return doc -class TestInMemoryReadWriteTestSuite(ReadWriteTestSuite): +class TestInMemoryStandard(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> InMemoryVectorStore: return InMemoryVectorStore(embedding=self.get_embeddings()) -class TestAsyncInMemoryReadWriteTestSuite(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> InMemoryVectorStore: - return InMemoryVectorStore(embedding=self.get_embeddings()) - - async def test_inmemory() -> None: """Test end to end construction and search.""" store = await InMemoryVectorStore.afrom_texts( diff --git a/libs/core/README.md b/libs/core/README.md index c833c2039468f..fb09de946ec22 100644 --- a/libs/core/README.md +++ b/libs/core/README.md @@ -17,7 +17,7 @@ These abstractions are designed to be as modular and simple as possible. Example The benefit of having these abstractions is that any provider can implement the required interface and then easily be used in the rest of the LangChain ecosystem. -For full documentation see the [API reference](https://api.python.langchain.com/en/stable/core_api_reference.html). +For full documentation see the [API reference](https://python.langchain.com/api_reference/core/index.html). ## 1️⃣ Core Interface: Runnables diff --git a/libs/core/langchain_core/_api/deprecation.py b/libs/core/langchain_core/_api/deprecation.py index ab6e47d31590a..c7d1e87b3bac8 100644 --- a/libs/core/langchain_core/_api/deprecation.py +++ b/libs/core/langchain_core/_api/deprecation.py @@ -364,8 +364,15 @@ def finalize(wrapper: Callable[..., Any], new_doc: str) -> T: _package or _name.split(".")[0].replace("_", "-") if "." in _name else None ) since_str = f"{package}=={since}" if package else since + if removal: + if removal.startswith("1.") and package and package.startswith("langchain"): + removal_str = f"It will not be removed until {package}=={removal}." + else: + removal_str = f"It will be removed in {package}=={removal}." + else: + removal_str = "" new_doc = f"""\ -.. deprecated:: {since_str} {details} +.. deprecated:: {since_str} {details} {removal_str} {old_doc}\ """ diff --git a/libs/core/langchain_core/messages/utils.py b/libs/core/langchain_core/messages/utils.py index 2fce9f7dbcaf7..452d59a5d78bf 100644 --- a/libs/core/langchain_core/messages/utils.py +++ b/libs/core/langchain_core/messages/utils.py @@ -556,6 +556,8 @@ def merge_message_runs( else: last_chunk = _msg_to_chunk(last) curr_chunk = _msg_to_chunk(curr) + if curr_chunk.response_metadata: + curr_chunk.response_metadata.clear() if ( isinstance(last_chunk.content, str) and isinstance(curr_chunk.content, str) diff --git a/libs/core/langchain_core/retrievers.py b/libs/core/langchain_core/retrievers.py index 7462569ddd30d..e1be4588081a2 100644 --- a/libs/core/langchain_core/retrievers.py +++ b/libs/core/langchain_core/retrievers.py @@ -27,7 +27,7 @@ from typing import TYPE_CHECKING, Any, Optional from pydantic import ConfigDict -from typing_extensions import TypedDict +from typing_extensions import Self, TypedDict from langchain_core._api import deprecated from langchain_core.documents import Document @@ -180,6 +180,18 @@ def __init_subclass__(cls, **kwargs: Any) -> None: cls._aget_relevant_documents = aswap # type: ignore[assignment] parameters = signature(cls._get_relevant_documents).parameters cls._new_arg_supported = parameters.get("run_manager") is not None + if ( + not cls._new_arg_supported + and cls._aget_relevant_documents == BaseRetriever._aget_relevant_documents + ): + # we need to tolerate no run_manager in _aget_relevant_documents signature + async def _aget_relevant_documents( + self: Self, query: str + ) -> list[Document]: + return await run_in_executor(None, self._get_relevant_documents, query) # type: ignore + + cls._aget_relevant_documents = _aget_relevant_documents # type: ignore[assignment] + # If a V1 retriever broke the interface and expects additional arguments cls._expects_other_args = ( len(set(parameters.keys()) - {"self", "query", "run_manager"}) > 0 diff --git a/libs/core/langchain_core/runnables/base.py b/libs/core/langchain_core/runnables/base.py index 9f9a77bc70515..e6a61fdfc77e8 100644 --- a/libs/core/langchain_core/runnables/base.py +++ b/libs/core/langchain_core/runnables/base.py @@ -5217,7 +5217,7 @@ class RunnableBindingBase(RunnableSerializable[Input, Output]): kwargs. """ - config: RunnableConfig = Field(default_factory=dict) + config: RunnableConfig = Field(default_factory=RunnableConfig) # type: ignore """The config to bind to the underlying Runnable.""" config_factories: list[Callable[[RunnableConfig], RunnableConfig]] = Field( diff --git a/libs/core/langchain_core/runnables/graph.py b/libs/core/langchain_core/runnables/graph.py index 2cb57c4e0fec5..d0e69e0b481b5 100644 --- a/libs/core/langchain_core/runnables/graph.py +++ b/libs/core/langchain_core/runnables/graph.py @@ -470,14 +470,22 @@ def trim_first_node(self) -> None: """Remove the first node if it exists and has a single outgoing edge, i.e., if removing it would not leave the graph without a "first" node.""" first_node = self.first_node() - if first_node and _first_node(self, exclude=[first_node.id]): + if ( + first_node + and _first_node(self, exclude=[first_node.id]) + and len({e for e in self.edges if e.source == first_node.id}) == 1 + ): self.remove_node(first_node) def trim_last_node(self) -> None: """Remove the last node if it exists and has a single incoming edge, i.e., if removing it would not leave the graph without a "last" node.""" last_node = self.last_node() - if last_node and _last_node(self, exclude=[last_node.id]): + if ( + last_node + and _last_node(self, exclude=[last_node.id]) + and len({e for e in self.edges if e.target == last_node.id}) == 1 + ): self.remove_node(last_node) def draw_ascii(self) -> str: diff --git a/libs/core/langchain_core/tools/base.py b/libs/core/langchain_core/tools/base.py index 9782234dfb1a0..815607f3b4325 100644 --- a/libs/core/langchain_core/tools/base.py +++ b/libs/core/langchain_core/tools/base.py @@ -609,7 +609,7 @@ def run( run_id: The id of the run. Defaults to None. config: The configuration for the tool. Defaults to None. tool_call_id: The id of the tool call. Defaults to None. - kwargs: Additional arguments to pass to the tool + kwargs: Keyword arguments to be passed to tool callbacks Returns: The output of the tool. @@ -721,7 +721,7 @@ async def arun( run_id: The id of the run. Defaults to None. config: The configuration for the tool. Defaults to None. tool_call_id: The id of the tool call. Defaults to None. - kwargs: Additional arguments to pass to the tool + kwargs: Keyword arguments to be passed to tool callbacks Returns: The output of the tool. diff --git a/libs/core/langchain_core/utils/function_calling.py b/libs/core/langchain_core/utils/function_calling.py index 3aff07faecd4c..4779d26244203 100644 --- a/libs/core/langchain_core/utils/function_calling.py +++ b/libs/core/langchain_core/utils/function_calling.py @@ -22,7 +22,7 @@ from pydantic import BaseModel from typing_extensions import TypedDict, get_args, get_origin, is_typeddict -from langchain_core._api import deprecated +from langchain_core._api import beta, deprecated from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, ToolMessage from langchain_core.utils.json_schema import dereference_refs from langchain_core.utils.pydantic import is_basemodel_subclass @@ -494,21 +494,28 @@ def convert_to_openai_tool( return {"type": "function", "function": oai_function} +@beta() def tool_example_to_messages( - input: str, tool_calls: list[BaseModel], tool_outputs: Optional[list[str]] = None + input: str, + tool_calls: list[BaseModel], + tool_outputs: Optional[list[str]] = None, + *, + ai_response: Optional[str] = None, ) -> list[BaseMessage]: """Convert an example into a list of messages that can be fed into an LLM. This code is an adapter that converts a single example to a list of messages that can be fed into a chat model. - The list of messages per example corresponds to: + The list of messages per example by default corresponds to: 1) HumanMessage: contains the content from which content should be extracted. 2) AIMessage: contains the extracted information from the model 3) ToolMessage: contains confirmation to the model that the model requested a tool correctly. + If `ai_response` is specified, there will be a final AIMessage with that response. + The ToolMessage is required because some chat models are hyper-optimized for agents rather than for an extraction use case. @@ -519,6 +526,7 @@ def tool_example_to_messages( tool_outputs: Optional[List[str]], a list of tool call outputs. Does not need to be provided. If not provided, a placeholder value will be inserted. Defaults to None. + ai_response: Optional[str], if provided, content for a final AIMessage. Returns: A list of messages @@ -584,6 +592,9 @@ class Person(BaseModel): ) for output, tool_call_dict in zip(tool_outputs, openai_tool_calls): messages.append(ToolMessage(content=output, tool_call_id=tool_call_dict["id"])) # type: ignore + + if ai_response: + messages.append(AIMessage(content=ai_response)) return messages diff --git a/libs/core/langchain_core/utils/pydantic.py b/libs/core/langchain_core/utils/pydantic.py index 7d81b8f70f03c..0b87e2dcf85b2 100644 --- a/libs/core/langchain_core/utils/pydantic.py +++ b/libs/core/langchain_core/utils/pydantic.py @@ -48,7 +48,18 @@ def get_pydantic_major_version() -> int: return 0 +def _get_pydantic_minor_version() -> int: + """Get the minor version of Pydantic.""" + try: + import pydantic + + return int(pydantic.__version__.split(".")[1]) + except ImportError: + return 0 + + PYDANTIC_MAJOR_VERSION = get_pydantic_major_version() +PYDANTIC_MINOR_VERSION = _get_pydantic_minor_version() if PYDANTIC_MAJOR_VERSION == 1: @@ -200,7 +211,7 @@ def wrapper(cls: type[BaseModel], values: dict[str, Any]) -> dict[str, Any]: name not in values or values[name] is None ) and not field_info.is_required(): if field_info.default_factory is not None: - values[name] = field_info.default_factory() + values[name] = field_info.default_factory() # type: ignore else: values[name] = field_info.default diff --git a/libs/core/poetry.lock b/libs/core/poetry.lock index 2f76b5b2d9995..dfc6f8a05c59f 100644 --- a/libs/core/poetry.lock +++ b/libs/core/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. [[package]] name = "annotated-types" @@ -1190,7 +1190,7 @@ files = [ [[package]] name = "langchain-tests" -version = "0.3.1" +version = "0.3.4" description = "Standard tests for LangChain implementations" optional = false python-versions = ">=3.9,<4.0" @@ -1199,7 +1199,7 @@ develop = true [package.dependencies] httpx = "^0.27.0" -langchain-core = "^0.3.15" +langchain-core = "^0.3.19" pytest = ">=7,<9" syrupy = "^4" @@ -1894,22 +1894,19 @@ files = [ [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.1" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.1-py3-none-any.whl", hash = "sha256:a8d20db84de64cf4a7d59e899c2caf0fe9d660c7cfc482528e7020d7dd189a7e"}, + {file = "pydantic-2.10.1.tar.gz", hash = "sha256:a4daca2dc0aa429555e0656d6bf94873a7dc5f54ee42b1f5873d666fb3f35560"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -1917,100 +1914,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] diff --git a/libs/core/pyproject.toml b/libs/core/pyproject.toml index eb0b74f1828d7..af153d8b66267 100644 --- a/libs/core/pyproject.toml +++ b/libs/core/pyproject.toml @@ -1,10 +1,10 @@ [build-system] -requires = ["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-core" -version = "0.3.19" +version = "0.3.22" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -12,16 +12,10 @@ readme = "README.md" repository = "https://github.com/langchain-ai/langchain" [tool.mypy] -exclude = [ - "notebooks", - "examples", - "example_data", - "langchain_core/pydantic", - "tests/unit_tests/utils/test_function_calling.py", -] +exclude = [ "notebooks", "examples", "example_data", "langchain_core/pydantic", "tests/unit_tests/utils/test_function_calling.py",] disallow_untyped_defs = "True" [[tool.mypy.overrides]] -module = ["numpy", "pytest"] +module = [ "numpy", "pytest",] ignore_missing_imports = true [tool.ruff] @@ -50,53 +44,17 @@ python = ">=3.12.4" [tool.poetry.extras] [tool.ruff.lint] -select = [ - "ASYNC", - "B", - "C4", - "COM", - "DJ", - "E", - "EM", - "EXE", - "F", - "FLY", - "FURB", - "I", - "ICN", - "INT", - "LOG", - "N", - "NPY", - "PD", - "PIE", - "Q", - "RSE", - "S", - "SIM", - "SLOT", - "T10", - "T201", - "TID", - "UP", - "W", - "YTT", -] -ignore = ["COM812", "UP007", "W293", "S101", "S110", "S112"] +select = [ "ASYNC", "B", "C4", "COM", "DJ", "E", "EM", "EXE", "F", "FLY", "FURB", "I", "ICN", "INT", "LOG", "N", "NPY", "PD", "PIE", "Q", "RSE", "S", "SIM", "SLOT", "T10", "T201", "TID", "UP", "W", "YTT",] +ignore = [ "COM812", "UP007", "W293", "S101", "S110", "S112",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" -filterwarnings = [ - "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", -] +filterwarnings = [ "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning",] [tool.poetry.group.lint] optional = true @@ -114,37 +72,29 @@ optional = true optional = true [tool.ruff.lint.pep8-naming] -classmethod-decorators = [ - "classmethod", - "langchain_core.utils.pydantic.pre_init", - "pydantic.field_validator", - "pydantic.v1.root_validator", -] +classmethod-decorators = [ "classmethod", "langchain_core.utils.pydantic.pre_init", "pydantic.field_validator", "pydantic.v1.root_validator",] [tool.ruff.lint.per-file-ignores] -"tests/unit_tests/prompts/test_chat.py" = ["E501"] -"tests/unit_tests/runnables/test_runnable.py" = ["E501"] -"tests/unit_tests/runnables/test_graph.py" = ["E501"] -"tests/**" = ["S"] -"scripts/**" = ["S"] +"tests/unit_tests/prompts/test_chat.py" = [ "E501",] +"tests/unit_tests/runnables/test_runnable.py" = [ "E501",] +"tests/unit_tests/runnables/test_graph.py" = [ "E501",] +"tests/**" = [ "S",] +"scripts/**" = [ "S",] [tool.poetry.group.lint.dependencies] ruff = "^0.5" - [tool.poetry.group.typing.dependencies] mypy = ">=1.10,<1.11" types-pyyaml = "^6.0.12.2" types-requests = "^2.28.11.5" types-jinja2 = "^2.11.9" - [tool.poetry.group.dev.dependencies] jupyter = "^1.0.0" setuptools = "^67.6.1" grandalf = "^0.8" - [tool.poetry.group.test.dependencies] pytest = "^8" freezegun = "^1.2.2" @@ -163,15 +113,12 @@ python = "<3.12" version = ">=1.26.0,<3" python = ">=3.12" - [tool.poetry.group.test_integration.dependencies] - [tool.poetry.group.typing.dependencies.langchain-text-splitters] path = "../text-splitters" develop = true - [tool.poetry.group.test.dependencies.langchain-tests] path = "../standard-tests" develop = true diff --git a/libs/core/tests/unit_tests/_api/test_path.py b/libs/core/tests/unit_tests/_api/test_path.py index 89428c7cfcb85..93896aab1158e 100644 --- a/libs/core/tests/unit_tests/_api/test_path.py +++ b/libs/core/tests/unit_tests/_api/test_path.py @@ -10,7 +10,11 @@ def test_as_import_path() -> None: """Test that the path is converted to a LangChain import path.""" # Verify that default paths are correct - assert path.PACKAGE_DIR == ROOT / "langchain_core" + + # if editable install, check directory structure + if path.PACKAGE_DIR == ROOT / "langchain_core": + assert path.PACKAGE_DIR == ROOT / "langchain_core" + # Verify that as import path works correctly assert path.as_import_path(HERE, relative_to=ROOT) == "tests.unit_tests._api" assert ( diff --git a/libs/core/tests/unit_tests/messages/test_utils.py b/libs/core/tests/unit_tests/messages/test_utils.py index 5941c14831a7a..9f4a9a4cc6c36 100644 --- a/libs/core/tests/unit_tests/messages/test_utils.py +++ b/libs/core/tests/unit_tests/messages/test_utils.py @@ -59,6 +59,24 @@ def test_merge_message_runs_str_without_separator( assert messages == messages_model_copy +def test_merge_message_runs_response_metadata() -> None: + messages = [ + AIMessage("foo", id="1", response_metadata={"input_tokens": 1}), + AIMessage("bar", id="2", response_metadata={"input_tokens": 2}), + ] + expected = [ + AIMessage( + "foo\nbar", + id="1", + response_metadata={"input_tokens": 1}, + ) + ] + actual = merge_message_runs(messages) + assert actual == expected + # Check it's not mutated + assert messages[1].response_metadata == {"input_tokens": 2} + + def test_merge_message_runs_content() -> None: messages = [ AIMessage("foo", id="1"), diff --git a/libs/core/tests/unit_tests/prompts/__snapshots__/test_chat.ambr b/libs/core/tests/unit_tests/prompts/__snapshots__/test_chat.ambr index 8e5e5c61ef48c..7a24cf9dc6524 100644 --- a/libs/core/tests/unit_tests/prompts/__snapshots__/test_chat.ambr +++ b/libs/core/tests/unit_tests/prompts/__snapshots__/test_chat.ambr @@ -94,6 +94,7 @@ 'const': 'ai', 'default': 'ai', 'title': 'Type', + 'type': 'string', }), 'usage_metadata': dict({ 'anyOf': list([ @@ -206,6 +207,7 @@ 'const': 'AIMessageChunk', 'default': 'AIMessageChunk', 'title': 'Type', + 'type': 'string', }), 'usage_metadata': dict({ 'anyOf': list([ @@ -290,6 +292,7 @@ 'const': 'chat', 'default': 'chat', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -364,6 +367,7 @@ 'const': 'ChatMessageChunk', 'default': 'ChatMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -435,6 +439,7 @@ 'const': 'function', 'default': 'function', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -497,6 +502,7 @@ 'const': 'FunctionMessageChunk', 'default': 'FunctionMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -595,6 +601,7 @@ 'const': 'human', 'default': 'human', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -669,6 +676,7 @@ 'const': 'HumanMessageChunk', 'default': 'HumanMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -767,6 +775,7 @@ 'type': dict({ 'const': 'invalid_tool_call', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -892,6 +901,7 @@ 'const': 'system', 'default': 'system', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -961,6 +971,7 @@ 'const': 'SystemMessageChunk', 'default': 'SystemMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1009,6 +1020,7 @@ 'type': dict({ 'const': 'tool_call', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1087,6 +1099,7 @@ 'type': dict({ 'const': 'tool_call_chunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1209,6 +1222,7 @@ 'const': 'tool', 'default': 'tool', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1290,6 +1304,7 @@ 'const': 'ToolMessageChunk', 'default': 'ToolMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1509,6 +1524,7 @@ 'const': 'ai', 'default': 'ai', 'title': 'Type', + 'type': 'string', }), 'usage_metadata': dict({ 'anyOf': list([ @@ -1621,6 +1637,7 @@ 'const': 'AIMessageChunk', 'default': 'AIMessageChunk', 'title': 'Type', + 'type': 'string', }), 'usage_metadata': dict({ 'anyOf': list([ @@ -1705,6 +1722,7 @@ 'const': 'chat', 'default': 'chat', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1779,6 +1797,7 @@ 'const': 'ChatMessageChunk', 'default': 'ChatMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1850,6 +1869,7 @@ 'const': 'function', 'default': 'function', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1912,6 +1932,7 @@ 'const': 'FunctionMessageChunk', 'default': 'FunctionMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2010,6 +2031,7 @@ 'const': 'human', 'default': 'human', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2084,6 +2106,7 @@ 'const': 'HumanMessageChunk', 'default': 'HumanMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2182,6 +2205,7 @@ 'type': dict({ 'const': 'invalid_tool_call', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2307,6 +2331,7 @@ 'const': 'system', 'default': 'system', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2376,6 +2401,7 @@ 'const': 'SystemMessageChunk', 'default': 'SystemMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2424,6 +2450,7 @@ 'type': dict({ 'const': 'tool_call', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2502,6 +2529,7 @@ 'type': dict({ 'const': 'tool_call_chunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2624,6 +2652,7 @@ 'const': 'tool', 'default': 'tool', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -2705,6 +2734,7 @@ 'const': 'ToolMessageChunk', 'default': 'ToolMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ diff --git a/libs/core/tests/unit_tests/prompts/test_chat.py b/libs/core/tests/unit_tests/prompts/test_chat.py index 8038281b58d2a..6249aa6f47893 100644 --- a/libs/core/tests/unit_tests/prompts/test_chat.py +++ b/libs/core/tests/unit_tests/prompts/test_chat.py @@ -33,6 +33,7 @@ _convert_to_message, ) from langchain_core.prompts.string import PromptTemplateFormat +from langchain_core.utils.pydantic import PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION from tests.unit_tests.pydantic_utils import _normalize_schema @@ -852,18 +853,22 @@ def test_chat_input_schema(snapshot: SnapshotAssertion) -> None: assert prompt_all_required.optional_variables == [] with pytest.raises(ValidationError): prompt_all_required.input_schema(input="") - assert _normalize_schema(prompt_all_required.get_input_jsonschema()) == snapshot( - name="required" - ) + + if (PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION) >= (2, 10): + assert _normalize_schema( + prompt_all_required.get_input_jsonschema() + ) == snapshot(name="required") prompt_optional = ChatPromptTemplate( messages=[MessagesPlaceholder("history", optional=True), ("user", "${input}")] ) # input variables only lists required variables assert set(prompt_optional.input_variables) == {"input"} prompt_optional.input_schema(input="") # won't raise error - assert _normalize_schema(prompt_optional.get_input_jsonschema()) == snapshot( - name="partial" - ) + + if (PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION) >= (2, 10): + assert _normalize_schema(prompt_optional.get_input_jsonschema()) == snapshot( + name="partial" + ) def test_chat_prompt_w_msgs_placeholder_ser_des(snapshot: SnapshotAssertion) -> None: diff --git a/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr b/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr index 208bdbac45e7f..5a3b7126d9937 100644 --- a/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr +++ b/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr @@ -468,6 +468,7 @@ 'const': 'ai', 'default': 'ai', 'title': 'Type', + 'type': 'string', }), 'usage_metadata': dict({ 'anyOf': list([ @@ -580,6 +581,7 @@ 'const': 'AIMessageChunk', 'default': 'AIMessageChunk', 'title': 'Type', + 'type': 'string', }), 'usage_metadata': dict({ 'anyOf': list([ @@ -664,6 +666,7 @@ 'const': 'chat', 'default': 'chat', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -738,6 +741,7 @@ 'const': 'ChatMessageChunk', 'default': 'ChatMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -809,6 +813,7 @@ 'const': 'function', 'default': 'function', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -871,6 +876,7 @@ 'const': 'FunctionMessageChunk', 'default': 'FunctionMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -969,6 +975,7 @@ 'const': 'human', 'default': 'human', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1043,6 +1050,7 @@ 'const': 'HumanMessageChunk', 'default': 'HumanMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1141,6 +1149,7 @@ 'type': dict({ 'const': 'invalid_tool_call', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1266,6 +1275,7 @@ 'const': 'system', 'default': 'system', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1335,6 +1345,7 @@ 'const': 'SystemMessageChunk', 'default': 'SystemMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1383,6 +1394,7 @@ 'type': dict({ 'const': 'tool_call', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1461,6 +1473,7 @@ 'type': dict({ 'const': 'tool_call_chunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1583,6 +1596,7 @@ 'const': 'tool', 'default': 'tool', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ @@ -1664,6 +1678,7 @@ 'const': 'ToolMessageChunk', 'default': 'ToolMessageChunk', 'title': 'Type', + 'type': 'string', }), }), 'required': list([ diff --git a/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr b/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr index 38a99073107d6..cadfa74d9af03 100644 --- a/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr +++ b/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr @@ -14047,7 +14047,8 @@ "stop": [ "Thought:" ] - } + }, + "config": {} }, "name": "FakeListChatModel" }, diff --git a/libs/core/tests/unit_tests/runnables/test_graph.py b/libs/core/tests/unit_tests/runnables/test_graph.py index 39f2f2871a800..e98a0a18a9c5c 100644 --- a/libs/core/tests/unit_tests/runnables/test_graph.py +++ b/libs/core/tests/unit_tests/runnables/test_graph.py @@ -12,6 +12,7 @@ from langchain_core.runnables.base import Runnable, RunnableConfig from langchain_core.runnables.graph import Edge, Graph, Node from langchain_core.runnables.graph_mermaid import _escape_node_label +from langchain_core.utils.pydantic import PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION from tests.unit_tests.pydantic_utils import _normalize_schema @@ -68,6 +69,26 @@ class Schema(BaseModel): assert graph.last_node() is end +def test_trim_multi_edge() -> None: + class Scheme(BaseModel): + a: str + + graph = Graph() + start = graph.add_node(Scheme, id="__start__") + a = graph.add_node(Scheme, id="a") + last = graph.add_node(Scheme, id="__end__") + + graph.add_edge(start, a) + graph.add_edge(a, last) + graph.add_edge(start, last) + + graph.trim_first_node() # should not remove __start__ since it has 2 outgoing edges + assert graph.first_node() is start + + graph.trim_last_node() # should not remove the __end__ node since it has 2 incoming edges + assert graph.last_node() is last + + def test_graph_sequence(snapshot: SnapshotAssertion) -> None: fake_llm = FakeListLLM(responses=["a"]) prompt = PromptTemplate.from_template("Hello, {name}!") @@ -210,10 +231,15 @@ def conditional_str_parser(input: str) -> Runnable: } ) graph = sequence.get_graph() - assert _normalize_schema(graph.to_json(with_schemas=True)) == snapshot( - name="graph_with_schema" - ) - assert _normalize_schema(graph.to_json()) == snapshot(name="graph_no_schemas") + + if (PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION) >= (2, 10): + assert _normalize_schema(graph.to_json(with_schemas=True)) == snapshot( + name="graph_with_schema" + ) + + if (PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION) >= (2, 10): + assert _normalize_schema(graph.to_json()) == snapshot(name="graph_no_schemas") + assert graph.draw_ascii() == snapshot(name="ascii") assert graph.draw_mermaid() == snapshot(name="mermaid") assert graph.draw_mermaid(with_styles=False) == snapshot(name="mermaid-simple") diff --git a/libs/core/tests/unit_tests/runnables/test_runnable.py b/libs/core/tests/unit_tests/runnables/test_runnable.py index d1f67a6c8d9ef..828f4cafcabf9 100644 --- a/libs/core/tests/unit_tests/runnables/test_runnable.py +++ b/libs/core/tests/unit_tests/runnables/test_runnable.py @@ -87,6 +87,7 @@ RunLogPatch, ) from langchain_core.tracers.context import collect_runs +from langchain_core.utils.pydantic import PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION from tests.unit_tests.pydantic_utils import _normalize_schema, _schema from tests.unit_tests.stubs import AnyStr, _any_id_ai_message, _any_id_ai_message_chunk @@ -223,6 +224,13 @@ async def _aget_relevant_documents( return [Document(page_content="foo"), Document(page_content="bar")] +@pytest.mark.skipif( + (PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION) >= (2, 10), + reason=( + "Only test with most recent version of pydantic. " + "Pydantic introduced small fixes to generated JSONSchema on minor versions." + ), +) def test_schemas(snapshot: SnapshotAssertion) -> None: fake = FakeRunnable() # str -> int @@ -2941,7 +2949,9 @@ def test_seq_prompt_map(mocker: MockerFixture, snapshot: SnapshotAssertion) -> N assert chain.first == prompt assert chain.middle == [RunnableLambda(passthrough)] assert isinstance(chain.last, RunnableParallel) - assert dumps(chain, pretty=True) == snapshot + + if (PYDANTIC_MAJOR_VERSION, PYDANTIC_MINOR_VERSION) >= (2, 10): + assert dumps(chain, pretty=True) == snapshot # Test invoke prompt_spy = mocker.spy(prompt.__class__, "invoke") diff --git a/libs/core/tests/unit_tests/test_retrievers.py b/libs/core/tests/unit_tests/test_retrievers.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/libs/core/tests/unit_tests/utils/test_function_calling.py b/libs/core/tests/unit_tests/utils/test_function_calling.py index 4eaa3da2b19ab..ba4c50187f139 100644 --- a/libs/core/tests/unit_tests/utils/test_function_calling.py +++ b/libs/core/tests/unit_tests/utils/test_function_calling.py @@ -679,6 +679,24 @@ def test_tool_outputs() -> None: ] assert messages[2].content == "Output1" + # Test final AI response + messages = tool_example_to_messages( + input="This is an example", + tool_calls=[ + FakeCall(data="ToolCall1"), + ], + tool_outputs=["Output1"], + ai_response="The output is Output1", + ) + assert len(messages) == 4 + assert isinstance(messages[0], HumanMessage) + assert isinstance(messages[1], AIMessage) + assert isinstance(messages[2], ToolMessage) + assert isinstance(messages[3], AIMessage) + response = messages[3] + assert response.content == "The output is Output1" + assert not response.tool_calls + @pytest.mark.parametrize("use_extension_typed_dict", [True, False]) @pytest.mark.parametrize("use_extension_annotated", [True, False]) diff --git a/libs/core/tests/unit_tests/vectorstores/test_in_memory.py b/libs/core/tests/unit_tests/vectorstores/test_in_memory.py index 34764f99c1016..e76f843616be8 100644 --- a/libs/core/tests/unit_tests/vectorstores/test_in_memory.py +++ b/libs/core/tests/unit_tests/vectorstores/test_in_memory.py @@ -2,10 +2,7 @@ from unittest.mock import AsyncMock, Mock import pytest -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_core.documents import Document from langchain_core.embeddings.fake import DeterministicFakeEmbedding @@ -13,18 +10,12 @@ from tests.unit_tests.stubs import _any_id_document -class TestInMemoryReadWriteTestSuite(ReadWriteTestSuite): +class TestInMemoryStandard(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> InMemoryVectorStore: return InMemoryVectorStore(embedding=self.get_embeddings()) -class TestAsyncInMemoryReadWriteTestSuite(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> InMemoryVectorStore: - return InMemoryVectorStore(embedding=self.get_embeddings()) - - async def test_inmemory_similarity_search() -> None: """Test end to end similarity search.""" store = await InMemoryVectorStore.afrom_texts( diff --git a/libs/langchain/extended_testing_deps.txt b/libs/langchain/extended_testing_deps.txt index 45cc79e027eff..c83e10f475530 100644 --- a/libs/langchain/extended_testing_deps.txt +++ b/libs/langchain/extended_testing_deps.txt @@ -7,3 +7,4 @@ jsonschema>=4.22.0,<5 numexpr>=2.8.6,<3 rapidfuzz>=3.1.1,<4 aiosqlite>=0.19.0,<0.20 +greenlet>=3.1.0 diff --git a/libs/langchain/langchain/_api/deprecation.py b/libs/langchain/langchain/_api/deprecation.py index e85ab4046ce97..ecd5a71b8964f 100644 --- a/libs/langchain/langchain/_api/deprecation.py +++ b/libs/langchain/langchain/_api/deprecation.py @@ -7,7 +7,20 @@ warn_deprecated, ) +AGENT_DEPRECATION_WARNING = ( + "LangChain agents will continue to be supported, but it is recommended for new " + "use cases to be built with LangGraph. LangGraph offers a more flexible and " + "full-featured framework for building agents, including support for " + "tool-calling, persistence of state, and human-in-the-loop workflows. See " + "LangGraph documentation for more details: " + "https://langchain-ai.github.io/langgraph/. Refer here for its pre-built " + "ReAct agent: " + "https://langchain-ai.github.io/langgraph/how-tos/create-react-agent/" +) + + __all__ = [ + "AGENT_DEPRECATION_WARNING", "LangChainDeprecationWarning", "LangChainPendingDeprecationWarning", "deprecated", diff --git a/libs/langchain/langchain/agents/agent.py b/libs/langchain/langchain/agents/agent.py index 500e884cd732a..6d1facd3e52ca 100644 --- a/libs/langchain/langchain/agents/agent.py +++ b/libs/langchain/langchain/agents/agent.py @@ -47,6 +47,7 @@ from pydantic import BaseModel, ConfigDict, model_validator from typing_extensions import Self +from langchain._api.deprecation import AGENT_DEPRECATION_WARNING from langchain.agents.agent_iterator import AgentExecutorIterator from langchain.agents.agent_types import AgentType from langchain.agents.tools import InvalidTool @@ -633,10 +634,7 @@ async def aplan( @deprecated( "0.1.0", - message=( - "Use new agent constructor methods like create_react_agent, create_json_agent, " - "create_structured_chat_agent, etc." - ), + message=AGENT_DEPRECATION_WARNING, removal="1.0", ) class LLMSingleActionAgent(BaseSingleActionAgent): @@ -724,10 +722,7 @@ def tool_run_logging_kwargs(self) -> Dict: @deprecated( "0.1.0", - message=( - "Use new agent constructor methods like create_react_agent, create_json_agent, " - "create_structured_chat_agent, etc." - ), + message=AGENT_DEPRECATION_WARNING, removal="1.0", ) class Agent(BaseSingleActionAgent): diff --git a/libs/langchain/langchain/agents/agent_toolkits/vectorstore/base.py b/libs/langchain/langchain/agents/agent_toolkits/vectorstore/base.py index eb8548cc6e870..4a3e6e76f6df5 100644 --- a/libs/langchain/langchain/agents/agent_toolkits/vectorstore/base.py +++ b/libs/langchain/langchain/agents/agent_toolkits/vectorstore/base.py @@ -20,6 +20,10 @@ since="0.2.13", removal="1.0", message=( + "This function will continue to be supported, but it is recommended for new " + "use cases to be built with LangGraph. LangGraph offers a more flexible and " + "full-featured framework for building agents, including support for " + "tool-calling, persistence of state, and human-in-the-loop workflows. " "See API reference for this function for a replacement implementation: " "https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_agent.html " # noqa: E501 "Read more here on how to create agents that query vector stores: " @@ -109,6 +113,10 @@ def create_vectorstore_agent( since="0.2.13", removal="1.0", message=( + "This function will continue to be supported, but it is recommended for new " + "use cases to be built with LangGraph. LangGraph offers a more flexible and " + "full-featured framework for building agents, including support for " + "tool-calling, persistence of state, and human-in-the-loop workflows. " "See API reference for this function for a replacement implementation: " "https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_router_agent.html " # noqa: E501 "Read more here on how to create agents that query vector stores: " diff --git a/libs/langchain/langchain/agents/agent_types.py b/libs/langchain/langchain/agents/agent_types.py index 14844a2a38f97..e6a72a98aef1a 100644 --- a/libs/langchain/langchain/agents/agent_types.py +++ b/libs/langchain/langchain/agents/agent_types.py @@ -4,13 +4,12 @@ from langchain_core._api import deprecated +from langchain._api.deprecation import AGENT_DEPRECATION_WARNING + @deprecated( "0.1.0", - message=( - "Use new agent constructor methods like create_react_agent, create_json_agent, " - "create_structured_chat_agent, etc." - ), + message=AGENT_DEPRECATION_WARNING, removal="1.0", ) class AgentType(str, Enum): diff --git a/libs/langchain/langchain/agents/chat/base.py b/libs/langchain/langchain/agents/chat/base.py index 00ced776f1342..22f8e77c5ca03 100644 --- a/libs/langchain/langchain/agents/chat/base.py +++ b/libs/langchain/langchain/agents/chat/base.py @@ -13,6 +13,7 @@ from langchain_core.tools import BaseTool from pydantic import Field +from langchain._api.deprecation import AGENT_DEPRECATION_WARNING from langchain.agents.agent import Agent, AgentOutputParser from langchain.agents.chat.output_parser import ChatOutputParser from langchain.agents.chat.prompt import ( @@ -25,7 +26,11 @@ from langchain.chains.llm import LLMChain -@deprecated("0.1.0", alternative="create_react_agent", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class ChatAgent(Agent): """Chat Agent.""" diff --git a/libs/langchain/langchain/agents/conversational/base.py b/libs/langchain/langchain/agents/conversational/base.py index a0ef85946abd3..6d7fc0312b919 100644 --- a/libs/langchain/langchain/agents/conversational/base.py +++ b/libs/langchain/langchain/agents/conversational/base.py @@ -11,6 +11,7 @@ from langchain_core.tools import BaseTool from pydantic import Field +from langchain._api.deprecation import AGENT_DEPRECATION_WARNING from langchain.agents.agent import Agent, AgentOutputParser from langchain.agents.agent_types import AgentType from langchain.agents.conversational.output_parser import ConvoOutputParser @@ -19,7 +20,11 @@ from langchain.chains import LLMChain -@deprecated("0.1.0", alternative="create_react_agent", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class ConversationalAgent(Agent): """An agent that holds a conversation in addition to using tools.""" diff --git a/libs/langchain/langchain/agents/initialize.py b/libs/langchain/langchain/agents/initialize.py index 17765e92276ce..cbcf06c5a3a37 100644 --- a/libs/langchain/langchain/agents/initialize.py +++ b/libs/langchain/langchain/agents/initialize.py @@ -7,6 +7,7 @@ from langchain_core.language_models import BaseLanguageModel from langchain_core.tools import BaseTool +from langchain._api.deprecation import AGENT_DEPRECATION_WARNING from langchain.agents.agent import AgentExecutor from langchain.agents.agent_types import AgentType from langchain.agents.loading import AGENT_TO_CLASS, load_agent @@ -14,10 +15,7 @@ @deprecated( "0.1.0", - alternative=( - "Use new agent constructor methods like create_react_agent, create_json_agent, " - "create_structured_chat_agent, etc." - ), + message=AGENT_DEPRECATION_WARNING, removal="1.0", ) def initialize_agent( diff --git a/libs/langchain/langchain/agents/mrkl/base.py b/libs/langchain/langchain/agents/mrkl/base.py index cc4d9da5537d7..538a0bc828584 100644 --- a/libs/langchain/langchain/agents/mrkl/base.py +++ b/libs/langchain/langchain/agents/mrkl/base.py @@ -12,6 +12,7 @@ from langchain_core.tools.render import render_text_description from pydantic import Field +from langchain._api.deprecation import AGENT_DEPRECATION_WARNING from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser from langchain.agents.agent_types import AgentType from langchain.agents.mrkl.output_parser import MRKLOutputParser @@ -34,7 +35,11 @@ class ChainConfig(NamedTuple): action_description: str -@deprecated("0.1.0", alternative="create_react_agent", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class ZeroShotAgent(Agent): """Agent for the MRKL chain. @@ -168,7 +173,11 @@ def _validate_tools(cls, tools: Sequence[BaseTool]) -> None: super()._validate_tools(tools) -@deprecated("0.1.0", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class MRKLChain(AgentExecutor): """Chain that implements the MRKL system.""" diff --git a/libs/langchain/langchain/agents/react/base.py b/libs/langchain/langchain/agents/react/base.py index 81a38141fe686..1f9191ab7beb5 100644 --- a/libs/langchain/langchain/agents/react/base.py +++ b/libs/langchain/langchain/agents/react/base.py @@ -11,6 +11,7 @@ from langchain_core.tools import BaseTool, Tool from pydantic import Field +from langchain._api.deprecation import AGENT_DEPRECATION_WARNING from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser from langchain.agents.agent_types import AgentType from langchain.agents.react.output_parser import ReActOutputParser @@ -22,7 +23,11 @@ from langchain_community.docstore.base import Docstore -@deprecated("0.1.0", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class ReActDocstoreAgent(Agent): """Agent for the ReAct chain.""" @@ -69,7 +74,11 @@ def llm_prefix(self) -> str: return "Thought:" -@deprecated("0.1.0", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class DocstoreExplorer: """Class to assist with exploration of a document store.""" @@ -119,7 +128,11 @@ def _paragraphs(self) -> List[str]: return self.document.page_content.split("\n\n") -@deprecated("0.1.0", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class ReActTextWorldAgent(ReActDocstoreAgent): """Agent for the ReAct TextWorld chain.""" @@ -139,7 +152,11 @@ def _validate_tools(cls, tools: Sequence[BaseTool]) -> None: raise ValueError(f"Tool name should be Play, got {tool_names}") -@deprecated("0.1.0", removal="1.0") +@deprecated( + "0.1.0", + message=AGENT_DEPRECATION_WARNING, + removal="1.0", +) class ReActChain(AgentExecutor): """[Deprecated] Chain that implements the ReAct paper.""" diff --git a/libs/langchain/langchain/chains/api/base.py b/libs/langchain/langchain/chains/api/base.py index 0cb2dbd2855fa..c8d155f696ff7 100644 --- a/libs/langchain/langchain/chains/api/base.py +++ b/libs/langchain/langchain/chains/api/base.py @@ -198,7 +198,9 @@ async def acall_model(state: ChainState, config: RunnableConfig): api_docs: str question_key: str = "question" #: :meta private: output_key: str = "output" #: :meta private: - limit_to_domains: Optional[Sequence[str]] = Field(default_factory=list) + limit_to_domains: Optional[Sequence[str]] = Field( + default_factory=list # type: ignore + ) """Use to limit the domains that can be accessed by the API chain. * For example, to limit to just the domain `https://www.example.com`, set diff --git a/libs/langchain/langchain/chains/mapreduce.py b/libs/langchain/langchain/chains/mapreduce.py index d78d3f57c17aa..4b5a86a521517 100644 --- a/libs/langchain/langchain/chains/mapreduce.py +++ b/libs/langchain/langchain/chains/mapreduce.py @@ -28,10 +28,10 @@ since="0.2.13", removal="1.0", message=( - "Refer here for a recommended map-reduce implementation using langgraph: " - "https://langchain-ai.github.io/langgraph/how-tos/map-reduce/. See also " - "migration guide: " - "https://python.langchain.com/docs/versions/migrating_chains/map_reduce_chain/" # noqa: E501 + "Refer to migration guide here for a recommended implementation using " + "LangGraph: https://python.langchain.com/docs/versions/migrating_chains/map_reduce_chain/" # noqa: E501 + ". See also LangGraph guides for map-reduce: " + "https://langchain-ai.github.io/langgraph/how-tos/map-reduce/." ), ) class MapReduceChain(Chain): diff --git a/libs/langchain/langchain/chains/moderation.py b/libs/langchain/langchain/chains/moderation.py index 52590a597c0c3..9467b8894c12b 100644 --- a/libs/langchain/langchain/chains/moderation.py +++ b/libs/langchain/langchain/chains/moderation.py @@ -38,7 +38,7 @@ class OpenAIModerationChain(Chain): output_key: str = "output" #: :meta private: openai_api_key: Optional[str] = None openai_organization: Optional[str] = None - openai_pre_1_0: bool = Field(default=None) + openai_pre_1_0: bool = Field(default=False) @model_validator(mode="before") @classmethod diff --git a/libs/langchain/langchain/chains/natbot/base.py b/libs/langchain/langchain/chains/natbot/base.py index aca7fca8a7d8b..a8a3c48567849 100644 --- a/libs/langchain/langchain/chains/natbot/base.py +++ b/libs/langchain/langchain/chains/natbot/base.py @@ -6,7 +6,9 @@ from typing import Any, Dict, List, Optional from langchain_core._api import deprecated +from langchain_core.caches import BaseCache as BaseCache from langchain_core.callbacks import CallbackManagerForChainRun +from langchain_core.callbacks import Callbacks as Callbacks from langchain_core.language_models import BaseLanguageModel from langchain_core.output_parsers import StrOutputParser from langchain_core.runnables import Runnable @@ -156,3 +158,6 @@ def execute(self, url: str, browser_content: str) -> str: @property def _chain_type(self) -> str: return "nat_bot_chain" + + +NatBotChain.model_rebuild() diff --git a/libs/langchain/langchain/chains/router/multi_prompt.py b/libs/langchain/langchain/chains/router/multi_prompt.py index 214b9a2b37208..0531cdb834db3 100644 --- a/libs/langchain/langchain/chains/router/multi_prompt.py +++ b/libs/langchain/langchain/chains/router/multi_prompt.py @@ -20,9 +20,8 @@ since="0.2.12", removal="1.0", message=( - "Use RunnableLambda to select from multiple prompt templates. See example " - "in API reference: " - "https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html" # noqa: E501 + "Please see migration guide here for recommended implementation: " + "https://python.langchain.com/docs/versions/migrating_chains/multi_prompt_chain/" # noqa: E501 ), ) class MultiPromptChain(MultiRouteChain): @@ -37,60 +36,109 @@ class MultiPromptChain(MultiRouteChain): from operator import itemgetter from typing import Literal - from typing_extensions import TypedDict from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import ChatPromptTemplate - from langchain_core.runnables import RunnableLambda, RunnablePassthrough + from langchain_core.runnables import RunnableConfig from langchain_openai import ChatOpenAI + from langgraph.graph import END, START, StateGraph + from typing_extensions import TypedDict llm = ChatOpenAI(model="gpt-4o-mini") + # Define the prompts we will route to prompt_1 = ChatPromptTemplate.from_messages( [ ("system", "You are an expert on animals."), - ("human", "{query}"), + ("human", "{input}"), ] ) prompt_2 = ChatPromptTemplate.from_messages( [ ("system", "You are an expert on vegetables."), - ("human", "{query}"), + ("human", "{input}"), ] ) + # Construct the chains we will route to. These format the input query + # into the respective prompt, run it through a chat model, and cast + # the result to a string. chain_1 = prompt_1 | llm | StrOutputParser() chain_2 = prompt_2 | llm | StrOutputParser() + + # Next: define the chain that selects which branch to route to. + # Here we will take advantage of tool-calling features to force + # the output to select one of two desired branches. route_system = "Route the user's query to either the animal or vegetable expert." route_prompt = ChatPromptTemplate.from_messages( [ ("system", route_system), - ("human", "{query}"), + ("human", "{input}"), ] ) + # Define schema for output: class RouteQuery(TypedDict): - \"\"\"Route query to destination.\"\"\" + \"\"\"Route query to destination expert.\"\"\" + destination: Literal["animal", "vegetable"] - route_chain = ( - route_prompt - | llm.with_structured_output(RouteQuery) - | itemgetter("destination") - ) + route_chain = route_prompt | llm.with_structured_output(RouteQuery) - chain = { - "destination": route_chain, # "animal" or "vegetable" - "query": lambda x: x["query"], # pass through input query - } | RunnableLambda( - # if animal, chain_1. otherwise, chain_2. - lambda x: chain_1 if x["destination"] == "animal" else chain_2, - ) - chain.invoke({"query": "what color are carrots"}) + # For LangGraph, we will define the state of the graph to hold the query, + # destination, and final answer. + class State(TypedDict): + query: str + destination: RouteQuery + answer: str + + + # We define functions for each node, including routing the query: + async def route_query(state: State, config: RunnableConfig): + destination = await route_chain.ainvoke(state["query"], config) + return {"destination": destination} + + + # And one node for each prompt + async def prompt_1(state: State, config: RunnableConfig): + return {"answer": await chain_1.ainvoke(state["query"], config)} + + + async def prompt_2(state: State, config: RunnableConfig): + return {"answer": await chain_2.ainvoke(state["query"], config)} + + + # We then define logic that selects the prompt based on the classification + def select_node(state: State) -> Literal["prompt_1", "prompt_2"]: + if state["destination"] == "animal": + return "prompt_1" + else: + return "prompt_2" + + + # Finally, assemble the multi-prompt chain. This is a sequence of two steps: + # 1) Select "animal" or "vegetable" via the route_chain, and collect the answer + # alongside the input query. + # 2) Route the input query to chain_1 or chain_2, based on the + # selection. + graph = StateGraph(State) + graph.add_node("route_query", route_query) + graph.add_node("prompt_1", prompt_1) + graph.add_node("prompt_2", prompt_2) + + graph.add_edge(START, "route_query") + graph.add_conditional_edges("route_query", select_node) + graph.add_edge("prompt_1", END) + graph.add_edge("prompt_2", END) + app = graph.compile() + + result = await app.ainvoke({"query": "what color are carrots"}) + print(result["destination"]) + print(result["answer"]) """ # noqa: E501 @property diff --git a/libs/langchain/langchain/chat_models/base.py b/libs/langchain/langchain/chat_models/base.py index d17a2932bc8f2..730b7f8908f95 100644 --- a/libs/langchain/langchain/chat_models/base.py +++ b/libs/langchain/langchain/chat_models/base.py @@ -328,13 +328,7 @@ class GetPopulation(BaseModel): def _init_chat_model_helper( model: str, *, model_provider: Optional[str] = None, **kwargs: Any ) -> BaseChatModel: - model_provider = model_provider or _attempt_infer_model_provider(model) - if not model_provider: - raise ValueError( - f"Unable to infer model provider for {model=}, please specify " - f"model_provider directly." - ) - model_provider = model_provider.replace("-", "_").lower() + model, model_provider = _parse_model(model, model_provider) if model_provider == "openai": _check_pkg("langchain_openai") from langchain_openai import ChatOpenAI @@ -461,6 +455,24 @@ def _attempt_infer_model_provider(model_name: str) -> Optional[str]: return None +def _parse_model(model: str, model_provider: Optional[str]) -> Tuple[str, str]: + if ( + not model_provider + and ":" in model + and model.split(":")[0] in _SUPPORTED_PROVIDERS + ): + model_provider = model.split(":")[0] + model = ":".join(model.split(":")[1:]) + model_provider = model_provider or _attempt_infer_model_provider(model) + if not model_provider: + raise ValueError( + f"Unable to infer model provider for {model=}, please specify " + f"model_provider directly." + ) + model_provider = model_provider.replace("-", "_").lower() + return model, model_provider + + def _check_pkg(pkg: str) -> None: if not util.find_spec(pkg): pkg_kebab = pkg.replace("_", "-") diff --git a/libs/langchain/langchain/embeddings/__init__.py b/libs/langchain/langchain/embeddings/__init__.py index a2f95c71e3dc5..08bb679a552b3 100644 --- a/libs/langchain/langchain/embeddings/__init__.py +++ b/libs/langchain/langchain/embeddings/__init__.py @@ -14,6 +14,7 @@ from typing import TYPE_CHECKING, Any from langchain._api import create_importer +from langchain.embeddings.base import init_embeddings from langchain.embeddings.cache import CacheBackedEmbeddings if TYPE_CHECKING: @@ -221,4 +222,5 @@ def __getattr__(name: str) -> Any: "VertexAIEmbeddings", "VoyageEmbeddings", "XinferenceEmbeddings", + "init_embeddings", ] diff --git a/libs/langchain/langchain/embeddings/base.py b/libs/langchain/langchain/embeddings/base.py index 9e648a342eab1..a8c8a97939676 100644 --- a/libs/langchain/langchain/embeddings/base.py +++ b/libs/langchain/langchain/embeddings/base.py @@ -1,4 +1,224 @@ +import functools +from importlib import util +from typing import Any, List, Optional, Tuple, Union + +from langchain_core._api import beta from langchain_core.embeddings import Embeddings +from langchain_core.runnables import Runnable + +_SUPPORTED_PROVIDERS = { + "azure_openai": "langchain_openai", + "bedrock": "langchain_aws", + "cohere": "langchain_cohere", + "google_vertexai": "langchain_google_vertexai", + "huggingface": "langchain_huggingface", + "mistralai": "langchain_mistralai", + "openai": "langchain_openai", +} + + +def _get_provider_list() -> str: + """Get formatted list of providers and their packages.""" + return "\n".join( + f" - {p}: {pkg.replace('_', '-')}" for p, pkg in _SUPPORTED_PROVIDERS.items() + ) + + +def _parse_model_string(model_name: str) -> Tuple[str, str]: + """Parse a model string into provider and model name components. + + The model string should be in the format 'provider:model-name', where provider + is one of the supported providers. + + Args: + model_name: A model string in the format 'provider:model-name' + + Returns: + A tuple of (provider, model_name) + + .. code-block:: python + + _parse_model_string("openai:text-embedding-3-small") + # Returns: ("openai", "text-embedding-3-small") + + _parse_model_string("bedrock:amazon.titan-embed-text-v1") + # Returns: ("bedrock", "amazon.titan-embed-text-v1") + + Raises: + ValueError: If the model string is not in the correct format or + the provider is unsupported + """ + if ":" not in model_name: + providers = _SUPPORTED_PROVIDERS + raise ValueError( + f"Invalid model format '{model_name}'.\n" + f"Model name must be in format 'provider:model-name'\n" + f"Example valid model strings:\n" + f" - openai:text-embedding-3-small\n" + f" - bedrock:amazon.titan-embed-text-v1\n" + f" - cohere:embed-english-v3.0\n" + f"Supported providers: {providers}" + ) + + provider, model = model_name.split(":", 1) + provider = provider.lower().strip() + model = model.strip() + + if provider not in _SUPPORTED_PROVIDERS: + raise ValueError( + f"Provider '{provider}' is not supported.\n" + f"Supported providers and their required packages:\n" + f"{_get_provider_list()}" + ) + if not model: + raise ValueError("Model name cannot be empty") + return provider, model + + +def _infer_model_and_provider( + model: str, *, provider: Optional[str] = None +) -> Tuple[str, str]: + if not model.strip(): + raise ValueError("Model name cannot be empty") + if provider is None and ":" in model: + provider, model_name = _parse_model_string(model) + else: + provider = provider + model_name = model + + if not provider: + providers = _SUPPORTED_PROVIDERS + raise ValueError( + "Must specify either:\n" + "1. A model string in format 'provider:model-name'\n" + " Example: 'openai:text-embedding-3-small'\n" + "2. Or explicitly set provider from: " + f"{providers}" + ) + + if provider not in _SUPPORTED_PROVIDERS: + raise ValueError( + f"Provider '{provider}' is not supported.\n" + f"Supported providers and their required packages:\n" + f"{_get_provider_list()}" + ) + return provider, model_name + + +@functools.lru_cache(maxsize=len(_SUPPORTED_PROVIDERS)) +def _check_pkg(pkg: str) -> None: + """Check if a package is installed.""" + if not util.find_spec(pkg): + raise ImportError( + f"Could not import {pkg} python package. " + f"Please install it with `pip install {pkg}`" + ) + + +@beta() +def init_embeddings( + model: str, + *, + provider: Optional[str] = None, + **kwargs: Any, +) -> Union[Embeddings, Runnable[Any, List[float]]]: + """Initialize an embeddings model from a model name and optional provider. + + **Note:** Must have the integration package corresponding to the model provider + installed. + + Args: + model: Name of the model to use. Can be either: + - A model string like "openai:text-embedding-3-small" + - Just the model name if provider is specified + provider: Optional explicit provider name. If not specified, + will attempt to parse from the model string. Supported providers + and their required packages: + + {_get_provider_list()} + + **kwargs: Additional model-specific parameters passed to the embedding model. + These vary by provider, see the provider-specific documentation for details. + + Returns: + An Embeddings instance that can generate embeddings for text. + + Raises: + ValueError: If the model provider is not supported or cannot be determined + ImportError: If the required provider package is not installed + + .. dropdown:: Example Usage + :open: + + .. code-block:: python + + # Using a model string + model = init_embeddings("openai:text-embedding-3-small") + model.embed_query("Hello, world!") + + # Using explicit provider + model = init_embeddings( + model="text-embedding-3-small", + provider="openai" + ) + model.embed_documents(["Hello, world!", "Goodbye, world!"]) + + # With additional parameters + model = init_embeddings( + "openai:text-embedding-3-small", + api_key="sk-..." + ) + + .. versionadded:: 0.3.9 + """ + if not model: + providers = _SUPPORTED_PROVIDERS.keys() + raise ValueError( + "Must specify model name. " + f"Supported providers are: {', '.join(providers)}" + ) + + provider, model_name = _infer_model_and_provider(model, provider=provider) + pkg = _SUPPORTED_PROVIDERS[provider] + _check_pkg(pkg) + + if provider == "openai": + from langchain_openai import OpenAIEmbeddings + + return OpenAIEmbeddings(model=model_name, **kwargs) + elif provider == "azure_openai": + from langchain_openai import AzureOpenAIEmbeddings + + return AzureOpenAIEmbeddings(model=model_name, **kwargs) + elif provider == "google_vertexai": + from langchain_google_vertexai import VertexAIEmbeddings + + return VertexAIEmbeddings(model=model_name, **kwargs) + elif provider == "bedrock": + from langchain_aws import BedrockEmbeddings + + return BedrockEmbeddings(model_id=model_name, **kwargs) + elif provider == "cohere": + from langchain_cohere import CohereEmbeddings + + return CohereEmbeddings(model=model_name, **kwargs) + elif provider == "mistralai": + from langchain_mistralai import MistralAIEmbeddings + + return MistralAIEmbeddings(model=model_name, **kwargs) + elif provider == "huggingface": + from langchain_huggingface import HuggingFaceEmbeddings + + return HuggingFaceEmbeddings(model_name=model_name, **kwargs) + else: + raise ValueError( + f"Provider '{provider}' is not supported.\n" + f"Supported providers and their required packages:\n" + f"{_get_provider_list()}" + ) + -# This is for backwards compatibility -__all__ = ["Embeddings"] +__all__ = [ + "init_embeddings", + "Embeddings", # This one is for backwards compatibility +] diff --git a/libs/langchain/langchain/memory/summary.py b/libs/langchain/langchain/memory/summary.py index 64c843579befc..0c07ac6f754e9 100644 --- a/libs/langchain/langchain/memory/summary.py +++ b/libs/langchain/langchain/memory/summary.py @@ -3,6 +3,8 @@ from typing import Any, Dict, List, Type from langchain_core._api import deprecated +from langchain_core.caches import BaseCache as BaseCache # For model_rebuild +from langchain_core.callbacks import Callbacks as Callbacks # For model_rebuild from langchain_core.chat_history import BaseChatMessageHistory from langchain_core.language_models import BaseLanguageModel from langchain_core.messages import BaseMessage, SystemMessage, get_buffer_string @@ -131,3 +133,6 @@ def clear(self) -> None: """Clear memory contents.""" super().clear() self.buffer = "" + + +ConversationSummaryMemory.model_rebuild() diff --git a/libs/langchain/langchain/memory/vectorstore_token_buffer_memory.py b/libs/langchain/langchain/memory/vectorstore_token_buffer_memory.py index 293773e84a173..d1812e79dd7ce 100644 --- a/libs/langchain/langchain/memory/vectorstore_token_buffer_memory.py +++ b/libs/langchain/langchain/memory/vectorstore_token_buffer_memory.py @@ -109,7 +109,7 @@ class ConversationVectorStoreTokenBufferMemory(ConversationTokenBufferMemory): previous_history_template: str = DEFAULT_HISTORY_TEMPLATE split_chunk_size: int = 1000 - _memory_retriever: VectorStoreRetrieverMemory = PrivateAttr(default=None) + _memory_retriever: VectorStoreRetrieverMemory = PrivateAttr(default=None) # type: ignore _timestamps: List[datetime] = PrivateAttr(default_factory=list) @property diff --git a/libs/langchain/langchain/output_parsers/fix.py b/libs/langchain/langchain/output_parsers/fix.py index f0a1a701c2334..c5c3921a473c3 100644 --- a/libs/langchain/langchain/output_parsers/fix.py +++ b/libs/langchain/langchain/output_parsers/fix.py @@ -27,11 +27,12 @@ class OutputFixingParser(BaseOutputParser[T]): def is_lc_serializable(cls) -> bool: return True - parser: Annotated[BaseOutputParser[T], SkipValidation()] + parser: Annotated[Any, SkipValidation()] """The parser to use to parse the output.""" # Should be an LLMChain but we want to avoid top-level imports from langchain.chains - retry_chain: Union[ - RunnableSerializable[OutputFixingParserRetryChainInput, str], Any + retry_chain: Annotated[ + Union[RunnableSerializable[OutputFixingParserRetryChainInput, str], Any], + SkipValidation(), ] """The RunnableSerializable to use to retry the completion (Legacy: LLMChain).""" max_retries: int = 1 diff --git a/libs/langchain/langchain/output_parsers/retry.py b/libs/langchain/langchain/output_parsers/retry.py index 06e1b410f7291..5f52da2e817d4 100644 --- a/libs/langchain/langchain/output_parsers/retry.py +++ b/libs/langchain/langchain/output_parsers/retry.py @@ -57,7 +57,10 @@ class RetryOutputParser(BaseOutputParser[T]): parser: Annotated[BaseOutputParser[T], SkipValidation()] """The parser to use to parse the output.""" # Should be an LLMChain but we want to avoid top-level imports from langchain.chains - retry_chain: Union[RunnableSerializable[RetryOutputParserRetryChainInput, str], Any] + retry_chain: Annotated[ + Union[RunnableSerializable[RetryOutputParserRetryChainInput, str], Any], + SkipValidation(), + ] """The RunnableSerializable to use to retry the completion (Legacy: LLMChain).""" max_retries: int = 1 """The maximum number of times to retry the parse.""" @@ -187,8 +190,11 @@ class RetryWithErrorOutputParser(BaseOutputParser[T]): parser: Annotated[BaseOutputParser[T], SkipValidation()] """The parser to use to parse the output.""" # Should be an LLMChain but we want to avoid top-level imports from langchain.chains - retry_chain: Union[ - RunnableSerializable[RetryWithErrorOutputParserRetryChainInput, str], Any + retry_chain: Annotated[ + Union[ + RunnableSerializable[RetryWithErrorOutputParserRetryChainInput, str], Any + ], + SkipValidation(), ] """The RunnableSerializable to use to retry the completion (Legacy: LLMChain).""" max_retries: int = 1 diff --git a/libs/langchain/langchain/retrievers/self_query/base.py b/libs/langchain/langchain/retrievers/self_query/base.py index a5254d475924f..7a13362d55348 100644 --- a/libs/langchain/langchain/retrievers/self_query/base.py +++ b/libs/langchain/langchain/retrievers/self_query/base.py @@ -161,6 +161,14 @@ def _get_builtin_translator(vectorstore: VectorStore) -> Visitor: if isinstance(vectorstore, MongoDBAtlasVectorSearch): return MongoDBAtlasTranslator() + try: + from langchain_neo4j import Neo4jVector + except ImportError: + pass + else: + if isinstance(vectorstore, Neo4jVector): + return Neo4jTranslator() + try: from langchain_chroma import Chroma except ImportError: diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index 7ee448147cd35..6b965558b4b22 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -2,123 +2,109 @@ [[package]] name = "aiohappyeyeballs" -version = "2.4.3" +version = "2.4.4" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"}, - {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"}, + {file = "aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8"}, + {file = "aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745"}, ] [[package]] name = "aiohttp" -version = "3.10.10" +version = "3.11.10" description = "Async http client/server framework (asyncio)" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "aiohttp-3.10.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:be7443669ae9c016b71f402e43208e13ddf00912f47f623ee5994e12fc7d4b3f"}, - {file = "aiohttp-3.10.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7b06b7843929e41a94ea09eb1ce3927865387e3e23ebe108e0d0d09b08d25be9"}, - {file = "aiohttp-3.10.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:333cf6cf8e65f6a1e06e9eb3e643a0c515bb850d470902274239fea02033e9a8"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:274cfa632350225ce3fdeb318c23b4a10ec25c0e2c880eff951a3842cf358ac1"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9e5e4a85bdb56d224f412d9c98ae4cbd032cc4f3161818f692cd81766eee65a"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b606353da03edcc71130b52388d25f9a30a126e04caef1fd637e31683033abd"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ab5a5a0c7a7991d90446a198689c0535be89bbd6b410a1f9a66688f0880ec026"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:578a4b875af3e0daaf1ac6fa983d93e0bbfec3ead753b6d6f33d467100cdc67b"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8105fd8a890df77b76dd3054cddf01a879fc13e8af576805d667e0fa0224c35d"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3bcd391d083f636c06a68715e69467963d1f9600f85ef556ea82e9ef25f043f7"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fbc6264158392bad9df19537e872d476f7c57adf718944cc1e4495cbabf38e2a"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:e48d5021a84d341bcaf95c8460b152cfbad770d28e5fe14a768988c461b821bc"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:2609e9ab08474702cc67b7702dbb8a80e392c54613ebe80db7e8dbdb79837c68"}, - {file = "aiohttp-3.10.10-cp310-cp310-win32.whl", hash = "sha256:84afcdea18eda514c25bc68b9af2a2b1adea7c08899175a51fe7c4fb6d551257"}, - {file = "aiohttp-3.10.10-cp310-cp310-win_amd64.whl", hash = "sha256:9c72109213eb9d3874f7ac8c0c5fa90e072d678e117d9061c06e30c85b4cf0e6"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c30a0eafc89d28e7f959281b58198a9fa5e99405f716c0289b7892ca345fe45f"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:258c5dd01afc10015866114e210fb7365f0d02d9d059c3c3415382ab633fcbcb"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:15ecd889a709b0080f02721255b3f80bb261c2293d3c748151274dfea93ac871"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3935f82f6f4a3820270842e90456ebad3af15810cf65932bd24da4463bc0a4c"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:413251f6fcf552a33c981c4709a6bba37b12710982fec8e558ae944bfb2abd38"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d1720b4f14c78a3089562b8875b53e36b51c97c51adc53325a69b79b4b48ebcb"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:679abe5d3858b33c2cf74faec299fda60ea9de62916e8b67e625d65bf069a3b7"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:79019094f87c9fb44f8d769e41dbb664d6e8fcfd62f665ccce36762deaa0e911"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:fe2fb38c2ed905a2582948e2de560675e9dfbee94c6d5ccdb1301c6d0a5bf092"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:a3f00003de6eba42d6e94fabb4125600d6e484846dbf90ea8e48a800430cc142"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:1bbb122c557a16fafc10354b9d99ebf2f2808a660d78202f10ba9d50786384b9"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:30ca7c3b94708a9d7ae76ff281b2f47d8eaf2579cd05971b5dc681db8caac6e1"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:df9270660711670e68803107d55c2b5949c2e0f2e4896da176e1ecfc068b974a"}, - {file = "aiohttp-3.10.10-cp311-cp311-win32.whl", hash = "sha256:aafc8ee9b742ce75044ae9a4d3e60e3d918d15a4c2e08a6c3c3e38fa59b92d94"}, - {file = "aiohttp-3.10.10-cp311-cp311-win_amd64.whl", hash = "sha256:362f641f9071e5f3ee6f8e7d37d5ed0d95aae656adf4ef578313ee585b585959"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:9294bbb581f92770e6ed5c19559e1e99255e4ca604a22c5c6397b2f9dd3ee42c"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:a8fa23fe62c436ccf23ff930149c047f060c7126eae3ccea005f0483f27b2e28"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5c6a5b8c7926ba5d8545c7dd22961a107526562da31a7a32fa2456baf040939f"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:007ec22fbc573e5eb2fb7dec4198ef8f6bf2fe4ce20020798b2eb5d0abda6138"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9627cc1a10c8c409b5822a92d57a77f383b554463d1884008e051c32ab1b3742"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:50edbcad60d8f0e3eccc68da67f37268b5144ecc34d59f27a02f9611c1d4eec7"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a45d85cf20b5e0d0aa5a8dca27cce8eddef3292bc29d72dcad1641f4ed50aa16"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0b00807e2605f16e1e198f33a53ce3c4523114059b0c09c337209ae55e3823a8"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f2d4324a98062be0525d16f768a03e0bbb3b9fe301ceee99611dc9a7953124e6"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:438cd072f75bb6612f2aca29f8bd7cdf6e35e8f160bc312e49fbecab77c99e3a"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:baa42524a82f75303f714108fea528ccacf0386af429b69fff141ffef1c534f9"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a7d8d14fe962153fc681f6366bdec33d4356f98a3e3567782aac1b6e0e40109a"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c1277cd707c465cd09572a774559a3cc7c7a28802eb3a2a9472588f062097205"}, - {file = "aiohttp-3.10.10-cp312-cp312-win32.whl", hash = "sha256:59bb3c54aa420521dc4ce3cc2c3fe2ad82adf7b09403fa1f48ae45c0cbde6628"}, - {file = "aiohttp-3.10.10-cp312-cp312-win_amd64.whl", hash = "sha256:0e1b370d8007c4ae31ee6db7f9a2fe801a42b146cec80a86766e7ad5c4a259cf"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ad7593bb24b2ab09e65e8a1d385606f0f47c65b5a2ae6c551db67d6653e78c28"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:1eb89d3d29adaf533588f209768a9c02e44e4baf832b08118749c5fad191781d"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3fe407bf93533a6fa82dece0e74dbcaaf5d684e5a51862887f9eaebe6372cd79"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50aed5155f819873d23520919e16703fc8925e509abbb1a1491b0087d1cd969e"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4f05e9727ce409358baa615dbeb9b969db94324a79b5a5cea45d39bdb01d82e6"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3dffb610a30d643983aeb185ce134f97f290f8935f0abccdd32c77bed9388b42"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa6658732517ddabe22c9036479eabce6036655ba87a0224c612e1ae6af2087e"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:741a46d58677d8c733175d7e5aa618d277cd9d880301a380fd296975a9cdd7bc"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e00e3505cd80440f6c98c6d69269dcc2a119f86ad0a9fd70bccc59504bebd68a"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:ffe595f10566f8276b76dc3a11ae4bb7eba1aac8ddd75811736a15b0d5311414"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:bdfcf6443637c148c4e1a20c48c566aa694fa5e288d34b20fcdc58507882fed3"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:d183cf9c797a5291e8301790ed6d053480ed94070637bfaad914dd38b0981f67"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:77abf6665ae54000b98b3c742bc6ea1d1fb31c394bcabf8b5d2c1ac3ebfe7f3b"}, - {file = "aiohttp-3.10.10-cp313-cp313-win32.whl", hash = "sha256:4470c73c12cd9109db8277287d11f9dd98f77fc54155fc71a7738a83ffcc8ea8"}, - {file = "aiohttp-3.10.10-cp313-cp313-win_amd64.whl", hash = "sha256:486f7aabfa292719a2753c016cc3a8f8172965cabb3ea2e7f7436c7f5a22a151"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:1b66ccafef7336a1e1f0e389901f60c1d920102315a56df85e49552308fc0486"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:acd48d5b80ee80f9432a165c0ac8cbf9253eaddb6113269a5e18699b33958dbb"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:3455522392fb15ff549d92fbf4b73b559d5e43dc522588f7eb3e54c3f38beee7"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45c3b868724137f713a38376fef8120c166d1eadd50da1855c112fe97954aed8"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:da1dee8948d2137bb51fbb8a53cce6b1bcc86003c6b42565f008438b806cccd8"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c5ce2ce7c997e1971b7184ee37deb6ea9922ef5163c6ee5aa3c274b05f9e12fa"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:28529e08fde6f12eba8677f5a8608500ed33c086f974de68cc65ab218713a59d"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f7db54c7914cc99d901d93a34704833568d86c20925b2762f9fa779f9cd2e70f"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:03a42ac7895406220124c88911ebee31ba8b2d24c98507f4a8bf826b2937c7f2"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:7e338c0523d024fad378b376a79faff37fafb3c001872a618cde1d322400a572"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:038f514fe39e235e9fef6717fbf944057bfa24f9b3db9ee551a7ecf584b5b480"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:64f6c17757251e2b8d885d728b6433d9d970573586a78b78ba8929b0f41d045a"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:93429602396f3383a797a2a70e5f1de5df8e35535d7806c9f91df06f297e109b"}, - {file = "aiohttp-3.10.10-cp38-cp38-win32.whl", hash = "sha256:c823bc3971c44ab93e611ab1a46b1eafeae474c0c844aff4b7474287b75fe49c"}, - {file = "aiohttp-3.10.10-cp38-cp38-win_amd64.whl", hash = "sha256:54ca74df1be3c7ca1cf7f4c971c79c2daf48d9aa65dea1a662ae18926f5bc8ce"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:01948b1d570f83ee7bbf5a60ea2375a89dfb09fd419170e7f5af029510033d24"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9fc1500fd2a952c5c8e3b29aaf7e3cc6e27e9cfc0a8819b3bce48cc1b849e4cc"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f614ab0c76397661b90b6851a030004dac502e48260ea10f2441abd2207fbcc7"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:00819de9e45d42584bed046314c40ea7e9aea95411b38971082cad449392b08c"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:05646ebe6b94cc93407b3bf34b9eb26c20722384d068eb7339de802154d61bc5"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:998f3bd3cfc95e9424a6acd7840cbdd39e45bc09ef87533c006f94ac47296090"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d9010c31cd6fa59438da4e58a7f19e4753f7f264300cd152e7f90d4602449762"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ea7ffc6d6d6f8a11e6f40091a1040995cdff02cfc9ba4c2f30a516cb2633554"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:ef9c33cc5cbca35808f6c74be11eb7f5f6b14d2311be84a15b594bd3e58b5527"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:ce0cdc074d540265bfeb31336e678b4e37316849d13b308607efa527e981f5c2"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:597a079284b7ee65ee102bc3a6ea226a37d2b96d0418cc9047490f231dc09fe8"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:7789050d9e5d0c309c706953e5e8876e38662d57d45f936902e176d19f1c58ab"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:e7f8b04d83483577fd9200461b057c9f14ced334dcb053090cea1da9c8321a91"}, - {file = "aiohttp-3.10.10-cp39-cp39-win32.whl", hash = "sha256:c02a30b904282777d872266b87b20ed8cc0d1501855e27f831320f471d54d983"}, - {file = "aiohttp-3.10.10-cp39-cp39-win_amd64.whl", hash = "sha256:edfe3341033a6b53a5c522c802deb2079eee5cbfbb0af032a55064bd65c73a23"}, - {file = "aiohttp-3.10.10.tar.gz", hash = "sha256:0631dd7c9f0822cc61c88586ca76d5b5ada26538097d0f1df510b082bad3411a"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:cbad88a61fa743c5d283ad501b01c153820734118b65aee2bd7dbb735475ce0d"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:80886dac673ceaef499de2f393fc80bb4481a129e6cb29e624a12e3296cc088f"}, + {file = "aiohttp-3.11.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:61b9bae80ed1f338c42f57c16918853dc51775fb5cb61da70d590de14d8b5fb4"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9e2e576caec5c6a6b93f41626c9c02fc87cd91538b81a3670b2e04452a63def6"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:02c13415b5732fb6ee7ff64583a5e6ed1c57aa68f17d2bda79c04888dfdc2769"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4cfce37f31f20800a6a6620ce2cdd6737b82e42e06e6e9bd1b36f546feb3c44f"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3bbbfff4c679c64e6e23cb213f57cc2c9165c9a65d63717108a644eb5a7398df"}, + {file = "aiohttp-3.11.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:49c7dbbc1a559ae14fc48387a115b7d4bbc84b4a2c3b9299c31696953c2a5219"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:68386d78743e6570f054fe7949d6cb37ef2b672b4d3405ce91fafa996f7d9b4d"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9ef405356ba989fb57f84cac66f7b0260772836191ccefbb987f414bcd2979d9"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5d6958671b296febe7f5f859bea581a21c1d05430d1bbdcf2b393599b1cdce77"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:99b7920e7165be5a9e9a3a7f1b680f06f68ff0d0328ff4079e5163990d046767"}, + {file = "aiohttp-3.11.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:0dc49f42422163efb7e6f1df2636fe3db72713f6cd94688e339dbe33fe06d61d"}, + {file = "aiohttp-3.11.10-cp310-cp310-win32.whl", hash = "sha256:40d1c7a7f750b5648642586ba7206999650208dbe5afbcc5284bcec6579c9b91"}, + {file = "aiohttp-3.11.10-cp310-cp310-win_amd64.whl", hash = "sha256:68ff6f48b51bd78ea92b31079817aff539f6c8fc80b6b8d6ca347d7c02384e33"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:77c4aa15a89847b9891abf97f3d4048f3c2d667e00f8a623c89ad2dccee6771b"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:909af95a72cedbefe5596f0bdf3055740f96c1a4baa0dd11fd74ca4de0b4e3f1"}, + {file = "aiohttp-3.11.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:386fbe79863eb564e9f3615b959e28b222259da0c48fd1be5929ac838bc65683"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3de34936eb1a647aa919655ff8d38b618e9f6b7f250cc19a57a4bf7fd2062b6d"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0c9527819b29cd2b9f52033e7fb9ff08073df49b4799c89cb5754624ecd98299"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:65a96e3e03300b41f261bbfd40dfdbf1c301e87eab7cd61c054b1f2e7c89b9e8"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98f5635f7b74bcd4f6f72fcd85bea2154b323a9f05226a80bc7398d0c90763b0"}, + {file = "aiohttp-3.11.10-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:03b6002e20938fc6ee0918c81d9e776bebccc84690e2b03ed132331cca065ee5"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6362cc6c23c08d18ddbf0e8c4d5159b5df74fea1a5278ff4f2c79aed3f4e9f46"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:3691ed7726fef54e928fe26344d930c0c8575bc968c3e239c2e1a04bd8cf7838"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31d5093d3acd02b31c649d3a69bb072d539d4c7659b87caa4f6d2bcf57c2fa2b"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:8b3cf2dc0f0690a33f2d2b2cb15db87a65f1c609f53c37e226f84edb08d10f52"}, + {file = "aiohttp-3.11.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:fbbaea811a2bba171197b08eea288b9402faa2bab2ba0858eecdd0a4105753a3"}, + {file = "aiohttp-3.11.10-cp311-cp311-win32.whl", hash = "sha256:4b2c7ac59c5698a7a8207ba72d9e9c15b0fc484a560be0788b31312c2c5504e4"}, + {file = "aiohttp-3.11.10-cp311-cp311-win_amd64.whl", hash = "sha256:974d3a2cce5fcfa32f06b13ccc8f20c6ad9c51802bb7f829eae8a1845c4019ec"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:b78f053a7ecfc35f0451d961dacdc671f4bcbc2f58241a7c820e9d82559844cf"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ab7485222db0959a87fbe8125e233b5a6f01f4400785b36e8a7878170d8c3138"}, + {file = "aiohttp-3.11.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:cf14627232dfa8730453752e9cdc210966490992234d77ff90bc8dc0dce361d5"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:076bc454a7e6fd646bc82ea7f98296be0b1219b5e3ef8a488afbdd8e81fbac50"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:482cafb7dc886bebeb6c9ba7925e03591a62ab34298ee70d3dd47ba966370d2c"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf3d1a519a324af764a46da4115bdbd566b3c73fb793ffb97f9111dbc684fc4d"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24213ba85a419103e641e55c27dc7ff03536c4873470c2478cce3311ba1eee7b"}, + {file = "aiohttp-3.11.10-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b99acd4730ad1b196bfb03ee0803e4adac371ae8efa7e1cbc820200fc5ded109"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:14cdb5a9570be5a04eec2ace174a48ae85833c2aadc86de68f55541f66ce42ab"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:7e97d622cb083e86f18317282084bc9fbf261801b0192c34fe4b1febd9f7ae69"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:012f176945af138abc10c4a48743327a92b4ca9adc7a0e078077cdb5dbab7be0"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:44224d815853962f48fe124748227773acd9686eba6dc102578defd6fc99e8d9"}, + {file = "aiohttp-3.11.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c87bf31b7fdab94ae3adbe4a48e711bfc5f89d21cf4c197e75561def39e223bc"}, + {file = "aiohttp-3.11.10-cp312-cp312-win32.whl", hash = "sha256:06a8e2ee1cbac16fe61e51e0b0c269400e781b13bcfc33f5425912391a542985"}, + {file = "aiohttp-3.11.10-cp312-cp312-win_amd64.whl", hash = "sha256:be2b516f56ea883a3e14dda17059716593526e10fb6303189aaf5503937db408"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:8cc5203b817b748adccb07f36390feb730b1bc5f56683445bfe924fc270b8816"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:5ef359ebc6949e3a34c65ce20230fae70920714367c63afd80ea0c2702902ccf"}, + {file = "aiohttp-3.11.10-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9bca390cb247dbfaec3c664326e034ef23882c3f3bfa5fbf0b56cad0320aaca5"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:811f23b3351ca532af598405db1093f018edf81368e689d1b508c57dcc6b6a32"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ddf5f7d877615f6a1e75971bfa5ac88609af3b74796ff3e06879e8422729fd01"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6ab29b8a0beb6f8eaf1e5049252cfe74adbaafd39ba91e10f18caeb0e99ffb34"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c49a76c1038c2dd116fa443eba26bbb8e6c37e924e2513574856de3b6516be99"}, + {file = "aiohttp-3.11.10-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7f3dc0e330575f5b134918976a645e79adf333c0a1439dcf6899a80776c9ab39"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:efb15a17a12497685304b2d976cb4939e55137df7b09fa53f1b6a023f01fcb4e"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:db1d0b28fcb7f1d35600150c3e4b490775251dea70f894bf15c678fdd84eda6a"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:15fccaf62a4889527539ecb86834084ecf6e9ea70588efde86e8bc775e0e7542"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:593c114a2221444f30749cc5e5f4012488f56bd14de2af44fe23e1e9894a9c60"}, + {file = "aiohttp-3.11.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7852bbcb4d0d2f0c4d583f40c3bc750ee033265d80598d0f9cb6f372baa6b836"}, + {file = "aiohttp-3.11.10-cp313-cp313-win32.whl", hash = "sha256:65e55ca7debae8faaffee0ebb4b47a51b4075f01e9b641c31e554fd376595c6c"}, + {file = "aiohttp-3.11.10-cp313-cp313-win_amd64.whl", hash = "sha256:beb39a6d60a709ae3fb3516a1581777e7e8b76933bb88c8f4420d875bb0267c6"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:0580f2e12de2138f34debcd5d88894786453a76e98febaf3e8fe5db62d01c9bf"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a55d2ad345684e7c3dd2c20d2f9572e9e1d5446d57200ff630e6ede7612e307f"}, + {file = "aiohttp-3.11.10-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:04814571cb72d65a6899db6099e377ed00710bf2e3eafd2985166f2918beaf59"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e44a9a3c053b90c6f09b1bb4edd880959f5328cf63052503f892c41ea786d99f"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:502a1464ccbc800b4b1995b302efaf426e8763fadf185e933c2931df7db9a199"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:613e5169f8ae77b1933e42e418a95931fb4867b2991fc311430b15901ed67079"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4cca22a61b7fe45da8fc73c3443150c3608750bbe27641fc7558ec5117b27fdf"}, + {file = "aiohttp-3.11.10-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:86a5dfcc39309470bd7b68c591d84056d195428d5d2e0b5ccadfbaf25b026ebc"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:77ae58586930ee6b2b6f696c82cf8e78c8016ec4795c53e36718365f6959dc82"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:78153314f26d5abef3239b4a9af20c229c6f3ecb97d4c1c01b22c4f87669820c"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:98283b94cc0e11c73acaf1c9698dea80c830ca476492c0fe2622bd931f34b487"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:53bf2097e05c2accc166c142a2090e4c6fd86581bde3fd9b2d3f9e93dda66ac1"}, + {file = "aiohttp-3.11.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:c5532f0441fc09c119e1dca18fbc0687e64fbeb45aa4d6a87211ceaee50a74c4"}, + {file = "aiohttp-3.11.10-cp39-cp39-win32.whl", hash = "sha256:47ad15a65fb41c570cd0ad9a9ff8012489e68176e7207ec7b82a0940dddfd8be"}, + {file = "aiohttp-3.11.10-cp39-cp39-win_amd64.whl", hash = "sha256:c6b9e6d7e41656d78e37ce754813fa44b455c3d0d0dced2a047def7dc5570b74"}, + {file = "aiohttp-3.11.10.tar.gz", hash = "sha256:b1fc6b45010a8d0ff9e88f9f2418c6fd408c99c211257334aff41597ebece42e"}, ] [package.dependencies] aiohappyeyeballs = ">=2.3.0" aiosignal = ">=1.1.2" -async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""} +async-timeout = {version = ">=4.0,<6.0", markers = "python_version < \"3.11\""} attrs = ">=17.3.0" frozenlist = ">=1.1.1" multidict = ">=4.5,<7.0" -yarl = ">=1.12.0,<2.0" +propcache = ">=0.2.0" +yarl = ">=1.17.0,<2.0" [package.extras] speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"] @@ -150,24 +136,24 @@ files = [ [[package]] name = "anyio" -version = "4.6.2.post1" +version = "4.7.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.9" files = [ - {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"}, - {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"}, + {file = "anyio-4.7.0-py3-none-any.whl", hash = "sha256:ea60c3723ab42ba6fff7e8ccb0488c898ec538ff4df1f1d5e642c3601d07e352"}, + {file = "anyio-4.7.0.tar.gz", hash = "sha256:2f834749c602966b7d456a7567cafcb309f96482b5081d14ac93ccd457f9dd48"}, ] [package.dependencies] exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} idna = ">=2.8" sniffio = ">=1.1" -typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} +typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] -doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"] +doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"] trio = ["trio (>=0.26.1)"] [[package]] @@ -259,21 +245,18 @@ test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock [[package]] name = "asttokens" -version = "2.4.1" +version = "3.0.0" description = "Annotate AST trees with source code positions" optional = false -python-versions = "*" +python-versions = ">=3.8" files = [ - {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"}, - {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"}, + {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"}, + {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"}, ] -[package.dependencies] -six = ">=1.12.0" - [package.extras] -astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"] -test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"] +astroid = ["astroid (>=2,<4)"] +test = ["astroid (>=2,<4)", "pytest", "pytest-cov", "pytest-xdist"] [[package]] name = "async-lru" @@ -778,73 +761,73 @@ test = ["pytest"] [[package]] name = "coverage" -version = "7.6.4" +version = "7.6.9" description = "Code coverage measurement for Python" optional = false python-versions = ">=3.9" files = [ - {file = "coverage-7.6.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5f8ae553cba74085db385d489c7a792ad66f7f9ba2ee85bfa508aeb84cf0ba07"}, - {file = "coverage-7.6.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8165b796df0bd42e10527a3f493c592ba494f16ef3c8b531288e3d0d72c1f6f0"}, - {file = "coverage-7.6.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c7c8b95bf47db6d19096a5e052ffca0a05f335bc63cef281a6e8fe864d450a72"}, - {file = "coverage-7.6.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ed9281d1b52628e81393f5eaee24a45cbd64965f41857559c2b7ff19385df51"}, - {file = "coverage-7.6.4-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0809082ee480bb8f7416507538243c8863ac74fd8a5d2485c46f0f7499f2b491"}, - {file = "coverage-7.6.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d541423cdd416b78626b55f123412fcf979d22a2c39fce251b350de38c15c15b"}, - {file = "coverage-7.6.4-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:58809e238a8a12a625c70450b48e8767cff9eb67c62e6154a642b21ddf79baea"}, - {file = "coverage-7.6.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:c9b8e184898ed014884ca84c70562b4a82cbc63b044d366fedc68bc2b2f3394a"}, - {file = "coverage-7.6.4-cp310-cp310-win32.whl", hash = "sha256:6bd818b7ea14bc6e1f06e241e8234508b21edf1b242d49831831a9450e2f35fa"}, - {file = "coverage-7.6.4-cp310-cp310-win_amd64.whl", hash = "sha256:06babbb8f4e74b063dbaeb74ad68dfce9186c595a15f11f5d5683f748fa1d172"}, - {file = "coverage-7.6.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:73d2b73584446e66ee633eaad1a56aad577c077f46c35ca3283cd687b7715b0b"}, - {file = "coverage-7.6.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:51b44306032045b383a7a8a2c13878de375117946d68dcb54308111f39775a25"}, - {file = "coverage-7.6.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3fb02fe73bed561fa12d279a417b432e5b50fe03e8d663d61b3d5990f29546"}, - {file = "coverage-7.6.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed8fe9189d2beb6edc14d3ad19800626e1d9f2d975e436f84e19efb7fa19469b"}, - {file = "coverage-7.6.4-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b369ead6527d025a0fe7bd3864e46dbee3aa8f652d48df6174f8d0bac9e26e0e"}, - {file = "coverage-7.6.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:ade3ca1e5f0ff46b678b66201f7ff477e8fa11fb537f3b55c3f0568fbfe6e718"}, - {file = "coverage-7.6.4-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:27fb4a050aaf18772db513091c9c13f6cb94ed40eacdef8dad8411d92d9992db"}, - {file = "coverage-7.6.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:4f704f0998911abf728a7783799444fcbbe8261c4a6c166f667937ae6a8aa522"}, - {file = "coverage-7.6.4-cp311-cp311-win32.whl", hash = "sha256:29155cd511ee058e260db648b6182c419422a0d2e9a4fa44501898cf918866cf"}, - {file = "coverage-7.6.4-cp311-cp311-win_amd64.whl", hash = "sha256:8902dd6a30173d4ef09954bfcb24b5d7b5190cf14a43170e386979651e09ba19"}, - {file = "coverage-7.6.4-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:12394842a3a8affa3ba62b0d4ab7e9e210c5e366fbac3e8b2a68636fb19892c2"}, - {file = "coverage-7.6.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2b6b4c83d8e8ea79f27ab80778c19bc037759aea298da4b56621f4474ffeb117"}, - {file = "coverage-7.6.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1d5b8007f81b88696d06f7df0cb9af0d3b835fe0c8dbf489bad70b45f0e45613"}, - {file = "coverage-7.6.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b57b768feb866f44eeed9f46975f3d6406380275c5ddfe22f531a2bf187eda27"}, - {file = "coverage-7.6.4-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5915fcdec0e54ee229926868e9b08586376cae1f5faa9bbaf8faf3561b393d52"}, - {file = "coverage-7.6.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0b58c672d14f16ed92a48db984612f5ce3836ae7d72cdd161001cc54512571f2"}, - {file = "coverage-7.6.4-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:2fdef0d83a2d08d69b1f2210a93c416d54e14d9eb398f6ab2f0a209433db19e1"}, - {file = "coverage-7.6.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8cf717ee42012be8c0cb205dbbf18ffa9003c4cbf4ad078db47b95e10748eec5"}, - {file = "coverage-7.6.4-cp312-cp312-win32.whl", hash = "sha256:7bb92c539a624cf86296dd0c68cd5cc286c9eef2d0c3b8b192b604ce9de20a17"}, - {file = "coverage-7.6.4-cp312-cp312-win_amd64.whl", hash = "sha256:1032e178b76a4e2b5b32e19d0fd0abbce4b58e77a1ca695820d10e491fa32b08"}, - {file = "coverage-7.6.4-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:023bf8ee3ec6d35af9c1c6ccc1d18fa69afa1cb29eaac57cb064dbb262a517f9"}, - {file = "coverage-7.6.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:b0ac3d42cb51c4b12df9c5f0dd2f13a4f24f01943627120ec4d293c9181219ba"}, - {file = "coverage-7.6.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f8fe4984b431f8621ca53d9380901f62bfb54ff759a1348cd140490ada7b693c"}, - {file = "coverage-7.6.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5fbd612f8a091954a0c8dd4c0b571b973487277d26476f8480bfa4b2a65b5d06"}, - {file = "coverage-7.6.4-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dacbc52de979f2823a819571f2e3a350a7e36b8cb7484cdb1e289bceaf35305f"}, - {file = "coverage-7.6.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:dab4d16dfef34b185032580e2f2f89253d302facba093d5fa9dbe04f569c4f4b"}, - {file = "coverage-7.6.4-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:862264b12ebb65ad8d863d51f17758b1684560b66ab02770d4f0baf2ff75da21"}, - {file = "coverage-7.6.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5beb1ee382ad32afe424097de57134175fea3faf847b9af002cc7895be4e2a5a"}, - {file = "coverage-7.6.4-cp313-cp313-win32.whl", hash = "sha256:bf20494da9653f6410213424f5f8ad0ed885e01f7e8e59811f572bdb20b8972e"}, - {file = "coverage-7.6.4-cp313-cp313-win_amd64.whl", hash = "sha256:182e6cd5c040cec0a1c8d415a87b67ed01193ed9ad458ee427741c7d8513d963"}, - {file = "coverage-7.6.4-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:a181e99301a0ae128493a24cfe5cfb5b488c4e0bf2f8702091473d033494d04f"}, - {file = "coverage-7.6.4-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:df57bdbeffe694e7842092c5e2e0bc80fff7f43379d465f932ef36f027179806"}, - {file = "coverage-7.6.4-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0bcd1069e710600e8e4cf27f65c90c7843fa8edfb4520fb0ccb88894cad08b11"}, - {file = "coverage-7.6.4-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:99b41d18e6b2a48ba949418db48159d7a2e81c5cc290fc934b7d2380515bd0e3"}, - {file = "coverage-7.6.4-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a6b1e54712ba3474f34b7ef7a41e65bd9037ad47916ccb1cc78769bae324c01a"}, - {file = "coverage-7.6.4-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:53d202fd109416ce011578f321460795abfe10bb901b883cafd9b3ef851bacfc"}, - {file = "coverage-7.6.4-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:c48167910a8f644671de9f2083a23630fbf7a1cb70ce939440cd3328e0919f70"}, - {file = "coverage-7.6.4-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:cc8ff50b50ce532de2fa7a7daae9dd12f0a699bfcd47f20945364e5c31799fef"}, - {file = "coverage-7.6.4-cp313-cp313t-win32.whl", hash = "sha256:b8d3a03d9bfcaf5b0141d07a88456bb6a4c3ce55c080712fec8418ef3610230e"}, - {file = "coverage-7.6.4-cp313-cp313t-win_amd64.whl", hash = "sha256:f3ddf056d3ebcf6ce47bdaf56142af51bb7fad09e4af310241e9db7a3a8022e1"}, - {file = "coverage-7.6.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9cb7fa111d21a6b55cbf633039f7bc2749e74932e3aa7cb7333f675a58a58bf3"}, - {file = "coverage-7.6.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:11a223a14e91a4693d2d0755c7a043db43d96a7450b4f356d506c2562c48642c"}, - {file = "coverage-7.6.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a413a096c4cbac202433c850ee43fa326d2e871b24554da8327b01632673a076"}, - {file = "coverage-7.6.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:00a1d69c112ff5149cabe60d2e2ee948752c975d95f1e1096742e6077affd376"}, - {file = "coverage-7.6.4-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1f76846299ba5c54d12c91d776d9605ae33f8ae2b9d1d3c3703cf2db1a67f2c0"}, - {file = "coverage-7.6.4-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:fe439416eb6380de434886b00c859304338f8b19f6f54811984f3420a2e03858"}, - {file = "coverage-7.6.4-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:0294ca37f1ba500667b1aef631e48d875ced93ad5e06fa665a3295bdd1d95111"}, - {file = "coverage-7.6.4-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:6f01ba56b1c0e9d149f9ac85a2f999724895229eb36bd997b61e62999e9b0901"}, - {file = "coverage-7.6.4-cp39-cp39-win32.whl", hash = "sha256:bc66f0bf1d7730a17430a50163bb264ba9ded56739112368ba985ddaa9c3bd09"}, - {file = "coverage-7.6.4-cp39-cp39-win_amd64.whl", hash = "sha256:c481b47f6b5845064c65a7bc78bc0860e635a9b055af0df46fdf1c58cebf8e8f"}, - {file = "coverage-7.6.4-pp39.pp310-none-any.whl", hash = "sha256:3c65d37f3a9ebb703e710befdc489a38683a5b152242664b973a7b7b22348a4e"}, - {file = "coverage-7.6.4.tar.gz", hash = "sha256:29fc0f17b1d3fea332f8001d4558f8214af7f1d87a345f3a133c901d60347c73"}, + {file = "coverage-7.6.9-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:85d9636f72e8991a1706b2b55b06c27545448baf9f6dbf51c4004609aacd7dcb"}, + {file = "coverage-7.6.9-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:608a7fd78c67bee8936378299a6cb9f5149bb80238c7a566fc3e6717a4e68710"}, + {file = "coverage-7.6.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:96d636c77af18b5cb664ddf12dab9b15a0cfe9c0bde715da38698c8cea748bfa"}, + {file = "coverage-7.6.9-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d75cded8a3cff93da9edc31446872d2997e327921d8eed86641efafd350e1df1"}, + {file = "coverage-7.6.9-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f7b15f589593110ae767ce997775d645b47e5cbbf54fd322f8ebea6277466cec"}, + {file = "coverage-7.6.9-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:44349150f6811b44b25574839b39ae35291f6496eb795b7366fef3bd3cf112d3"}, + {file = "coverage-7.6.9-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:d891c136b5b310d0e702e186d70cd16d1119ea8927347045124cb286b29297e5"}, + {file = "coverage-7.6.9-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:db1dab894cc139f67822a92910466531de5ea6034ddfd2b11c0d4c6257168073"}, + {file = "coverage-7.6.9-cp310-cp310-win32.whl", hash = "sha256:41ff7b0da5af71a51b53f501a3bac65fb0ec311ebed1632e58fc6107f03b9198"}, + {file = "coverage-7.6.9-cp310-cp310-win_amd64.whl", hash = "sha256:35371f8438028fdccfaf3570b31d98e8d9eda8bb1d6ab9473f5a390969e98717"}, + {file = "coverage-7.6.9-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:932fc826442132dde42ee52cf66d941f581c685a6313feebed358411238f60f9"}, + {file = "coverage-7.6.9-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:085161be5f3b30fd9b3e7b9a8c301f935c8313dcf928a07b116324abea2c1c2c"}, + {file = "coverage-7.6.9-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ccc660a77e1c2bf24ddbce969af9447a9474790160cfb23de6be4fa88e3951c7"}, + {file = "coverage-7.6.9-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c69e42c892c018cd3c8d90da61d845f50a8243062b19d228189b0224150018a9"}, + {file = "coverage-7.6.9-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0824a28ec542a0be22f60c6ac36d679e0e262e5353203bea81d44ee81fe9c6d4"}, + {file = "coverage-7.6.9-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:4401ae5fc52ad8d26d2a5d8a7428b0f0c72431683f8e63e42e70606374c311a1"}, + {file = "coverage-7.6.9-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:98caba4476a6c8d59ec1eb00c7dd862ba9beca34085642d46ed503cc2d440d4b"}, + {file = "coverage-7.6.9-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ee5defd1733fd6ec08b168bd4f5387d5b322f45ca9e0e6c817ea6c4cd36313e3"}, + {file = "coverage-7.6.9-cp311-cp311-win32.whl", hash = "sha256:f2d1ec60d6d256bdf298cb86b78dd715980828f50c46701abc3b0a2b3f8a0dc0"}, + {file = "coverage-7.6.9-cp311-cp311-win_amd64.whl", hash = "sha256:0d59fd927b1f04de57a2ba0137166d31c1a6dd9e764ad4af552912d70428c92b"}, + {file = "coverage-7.6.9-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:99e266ae0b5d15f1ca8d278a668df6f51cc4b854513daab5cae695ed7b721cf8"}, + {file = "coverage-7.6.9-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9901d36492009a0a9b94b20e52ebfc8453bf49bb2b27bca2c9706f8b4f5a554a"}, + {file = "coverage-7.6.9-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:abd3e72dd5b97e3af4246cdada7738ef0e608168de952b837b8dd7e90341f015"}, + {file = "coverage-7.6.9-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff74026a461eb0660366fb01c650c1d00f833a086b336bdad7ab00cc952072b3"}, + {file = "coverage-7.6.9-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65dad5a248823a4996724a88eb51d4b31587aa7aa428562dbe459c684e5787ae"}, + {file = "coverage-7.6.9-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:22be16571504c9ccea919fcedb459d5ab20d41172056206eb2994e2ff06118a4"}, + {file = "coverage-7.6.9-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:0f957943bc718b87144ecaee70762bc2bc3f1a7a53c7b861103546d3a403f0a6"}, + {file = "coverage-7.6.9-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0ae1387db4aecb1f485fb70a6c0148c6cdaebb6038f1d40089b1fc84a5db556f"}, + {file = "coverage-7.6.9-cp312-cp312-win32.whl", hash = "sha256:1a330812d9cc7ac2182586f6d41b4d0fadf9be9049f350e0efb275c8ee8eb692"}, + {file = "coverage-7.6.9-cp312-cp312-win_amd64.whl", hash = "sha256:b12c6b18269ca471eedd41c1b6a1065b2f7827508edb9a7ed5555e9a56dcfc97"}, + {file = "coverage-7.6.9-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:899b8cd4781c400454f2f64f7776a5d87bbd7b3e7f7bda0cb18f857bb1334664"}, + {file = "coverage-7.6.9-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:61f70dc68bd36810972e55bbbe83674ea073dd1dcc121040a08cdf3416c5349c"}, + {file = "coverage-7.6.9-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8a289d23d4c46f1a82d5db4abeb40b9b5be91731ee19a379d15790e53031c014"}, + {file = "coverage-7.6.9-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7e216d8044a356fc0337c7a2a0536d6de07888d7bcda76febcb8adc50bdbbd00"}, + {file = "coverage-7.6.9-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3c026eb44f744acaa2bda7493dad903aa5bf5fc4f2554293a798d5606710055d"}, + {file = "coverage-7.6.9-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e77363e8425325384f9d49272c54045bbed2f478e9dd698dbc65dbc37860eb0a"}, + {file = "coverage-7.6.9-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:777abfab476cf83b5177b84d7486497e034eb9eaea0d746ce0c1268c71652077"}, + {file = "coverage-7.6.9-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:447af20e25fdbe16f26e84eb714ba21d98868705cb138252d28bc400381f6ffb"}, + {file = "coverage-7.6.9-cp313-cp313-win32.whl", hash = "sha256:d872ec5aeb086cbea771c573600d47944eea2dcba8be5f3ee649bfe3cb8dc9ba"}, + {file = "coverage-7.6.9-cp313-cp313-win_amd64.whl", hash = "sha256:fd1213c86e48dfdc5a0cc676551db467495a95a662d2396ecd58e719191446e1"}, + {file = "coverage-7.6.9-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:ba9e7484d286cd5a43744e5f47b0b3fb457865baf07bafc6bee91896364e1419"}, + {file = "coverage-7.6.9-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:e5ea1cf0872ee455c03e5674b5bca5e3e68e159379c1af0903e89f5eba9ccc3a"}, + {file = "coverage-7.6.9-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2d10e07aa2b91835d6abec555ec8b2733347956991901eea6ffac295f83a30e4"}, + {file = "coverage-7.6.9-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:13a9e2d3ee855db3dd6ea1ba5203316a1b1fd8eaeffc37c5b54987e61e4194ae"}, + {file = "coverage-7.6.9-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c38bf15a40ccf5619fa2fe8f26106c7e8e080d7760aeccb3722664c8656b030"}, + {file = "coverage-7.6.9-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:d5275455b3e4627c8e7154feaf7ee0743c2e7af82f6e3b561967b1cca755a0be"}, + {file = "coverage-7.6.9-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:8f8770dfc6e2c6a2d4569f411015c8d751c980d17a14b0530da2d7f27ffdd88e"}, + {file = "coverage-7.6.9-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:8d2dfa71665a29b153a9681edb1c8d9c1ea50dfc2375fb4dac99ea7e21a0bcd9"}, + {file = "coverage-7.6.9-cp313-cp313t-win32.whl", hash = "sha256:5e6b86b5847a016d0fbd31ffe1001b63355ed309651851295315031ea7eb5a9b"}, + {file = "coverage-7.6.9-cp313-cp313t-win_amd64.whl", hash = "sha256:97ddc94d46088304772d21b060041c97fc16bdda13c6c7f9d8fcd8d5ae0d8611"}, + {file = "coverage-7.6.9-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:adb697c0bd35100dc690de83154627fbab1f4f3c0386df266dded865fc50a902"}, + {file = "coverage-7.6.9-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:be57b6d56e49c2739cdf776839a92330e933dd5e5d929966fbbd380c77f060be"}, + {file = "coverage-7.6.9-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f1592791f8204ae9166de22ba7e6705fa4ebd02936c09436a1bb85aabca3e599"}, + {file = "coverage-7.6.9-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4e12ae8cc979cf83d258acb5e1f1cf2f3f83524d1564a49d20b8bec14b637f08"}, + {file = "coverage-7.6.9-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb5555cff66c4d3d6213a296b360f9e1a8e323e74e0426b6c10ed7f4d021e464"}, + {file = "coverage-7.6.9-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:b9389a429e0e5142e69d5bf4a435dd688c14478a19bb901735cdf75e57b13845"}, + {file = "coverage-7.6.9-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:592ac539812e9b46046620341498caf09ca21023c41c893e1eb9dbda00a70cbf"}, + {file = "coverage-7.6.9-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a27801adef24cc30871da98a105f77995e13a25a505a0161911f6aafbd66e678"}, + {file = "coverage-7.6.9-cp39-cp39-win32.whl", hash = "sha256:8e3c3e38930cfb729cb8137d7f055e5a473ddaf1217966aa6238c88bd9fd50e6"}, + {file = "coverage-7.6.9-cp39-cp39-win_amd64.whl", hash = "sha256:e28bf44afa2b187cc9f41749138a64435bf340adfcacb5b2290c070ce99839d4"}, + {file = "coverage-7.6.9-pp39.pp310-none-any.whl", hash = "sha256:f3ca78518bc6bc92828cd11867b121891d75cae4ea9e908d72030609b996db1b"}, + {file = "coverage-7.6.9.tar.gz", hash = "sha256:4a8d8977b0c6ef5aeadcb644da9e69ae0dcfe66ec7f368c89c72e058bd71164d"}, ] [package.dependencies] @@ -904,37 +887,37 @@ test-randomorder = ["pytest-randomly"] [[package]] name = "debugpy" -version = "1.8.7" +version = "1.8.9" description = "An implementation of the Debug Adapter Protocol for Python" optional = false python-versions = ">=3.8" files = [ - {file = "debugpy-1.8.7-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:95fe04a573b8b22896c404365e03f4eda0ce0ba135b7667a1e57bd079793b96b"}, - {file = "debugpy-1.8.7-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:628a11f4b295ffb4141d8242a9bb52b77ad4a63a2ad19217a93be0f77f2c28c9"}, - {file = "debugpy-1.8.7-cp310-cp310-win32.whl", hash = "sha256:85ce9c1d0eebf622f86cc68618ad64bf66c4fc3197d88f74bb695a416837dd55"}, - {file = "debugpy-1.8.7-cp310-cp310-win_amd64.whl", hash = "sha256:29e1571c276d643757ea126d014abda081eb5ea4c851628b33de0c2b6245b037"}, - {file = "debugpy-1.8.7-cp311-cp311-macosx_14_0_universal2.whl", hash = "sha256:caf528ff9e7308b74a1749c183d6808ffbedbb9fb6af78b033c28974d9b8831f"}, - {file = "debugpy-1.8.7-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cba1d078cf2e1e0b8402e6bda528bf8fda7ccd158c3dba6c012b7897747c41a0"}, - {file = "debugpy-1.8.7-cp311-cp311-win32.whl", hash = "sha256:171899588bcd412151e593bd40d9907133a7622cd6ecdbdb75f89d1551df13c2"}, - {file = "debugpy-1.8.7-cp311-cp311-win_amd64.whl", hash = "sha256:6e1c4ffb0c79f66e89dfd97944f335880f0d50ad29525dc792785384923e2211"}, - {file = "debugpy-1.8.7-cp312-cp312-macosx_14_0_universal2.whl", hash = "sha256:4d27d842311353ede0ad572600c62e4bcd74f458ee01ab0dd3a1a4457e7e3706"}, - {file = "debugpy-1.8.7-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:703c1fd62ae0356e194f3e7b7a92acd931f71fe81c4b3be2c17a7b8a4b546ec2"}, - {file = "debugpy-1.8.7-cp312-cp312-win32.whl", hash = "sha256:2f729228430ef191c1e4df72a75ac94e9bf77413ce5f3f900018712c9da0aaca"}, - {file = "debugpy-1.8.7-cp312-cp312-win_amd64.whl", hash = "sha256:45c30aaefb3e1975e8a0258f5bbd26cd40cde9bfe71e9e5a7ac82e79bad64e39"}, - {file = "debugpy-1.8.7-cp313-cp313-macosx_14_0_universal2.whl", hash = "sha256:d050a1ec7e925f514f0f6594a1e522580317da31fbda1af71d1530d6ea1f2b40"}, - {file = "debugpy-1.8.7-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2f4349a28e3228a42958f8ddaa6333d6f8282d5edaea456070e48609c5983b7"}, - {file = "debugpy-1.8.7-cp313-cp313-win32.whl", hash = "sha256:11ad72eb9ddb436afb8337891a986302e14944f0f755fd94e90d0d71e9100bba"}, - {file = "debugpy-1.8.7-cp313-cp313-win_amd64.whl", hash = "sha256:2efb84d6789352d7950b03d7f866e6d180284bc02c7e12cb37b489b7083d81aa"}, - {file = "debugpy-1.8.7-cp38-cp38-macosx_14_0_x86_64.whl", hash = "sha256:4b908291a1d051ef3331484de8e959ef3e66f12b5e610c203b5b75d2725613a7"}, - {file = "debugpy-1.8.7-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da8df5b89a41f1fd31503b179d0a84a5fdb752dddd5b5388dbd1ae23cda31ce9"}, - {file = "debugpy-1.8.7-cp38-cp38-win32.whl", hash = "sha256:b12515e04720e9e5c2216cc7086d0edadf25d7ab7e3564ec8b4521cf111b4f8c"}, - {file = "debugpy-1.8.7-cp38-cp38-win_amd64.whl", hash = "sha256:93176e7672551cb5281577cdb62c63aadc87ec036f0c6a486f0ded337c504596"}, - {file = "debugpy-1.8.7-cp39-cp39-macosx_14_0_x86_64.whl", hash = "sha256:90d93e4f2db442f8222dec5ec55ccfc8005821028982f1968ebf551d32b28907"}, - {file = "debugpy-1.8.7-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b6db2a370e2700557a976eaadb16243ec9c91bd46f1b3bb15376d7aaa7632c81"}, - {file = "debugpy-1.8.7-cp39-cp39-win32.whl", hash = "sha256:a6cf2510740e0c0b4a40330640e4b454f928c7b99b0c9dbf48b11efba08a8cda"}, - {file = "debugpy-1.8.7-cp39-cp39-win_amd64.whl", hash = "sha256:6a9d9d6d31846d8e34f52987ee0f1a904c7baa4912bf4843ab39dadf9b8f3e0d"}, - {file = "debugpy-1.8.7-py2.py3-none-any.whl", hash = "sha256:57b00de1c8d2c84a61b90880f7e5b6deaf4c312ecbde3a0e8912f2a56c4ac9ae"}, - {file = "debugpy-1.8.7.zip", hash = "sha256:18b8f731ed3e2e1df8e9cdaa23fb1fc9c24e570cd0081625308ec51c82efe42e"}, + {file = "debugpy-1.8.9-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:cfe1e6c6ad7178265f74981edf1154ffce97b69005212fbc90ca22ddfe3d017e"}, + {file = "debugpy-1.8.9-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ada7fb65102a4d2c9ab62e8908e9e9f12aed9d76ef44880367bc9308ebe49a0f"}, + {file = "debugpy-1.8.9-cp310-cp310-win32.whl", hash = "sha256:c36856343cbaa448171cba62a721531e10e7ffb0abff838004701454149bc037"}, + {file = "debugpy-1.8.9-cp310-cp310-win_amd64.whl", hash = "sha256:17c5e0297678442511cf00a745c9709e928ea4ca263d764e90d233208889a19e"}, + {file = "debugpy-1.8.9-cp311-cp311-macosx_14_0_universal2.whl", hash = "sha256:b74a49753e21e33e7cf030883a92fa607bddc4ede1aa4145172debc637780040"}, + {file = "debugpy-1.8.9-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:62d22dacdb0e296966d7d74a7141aaab4bec123fa43d1a35ddcb39bf9fd29d70"}, + {file = "debugpy-1.8.9-cp311-cp311-win32.whl", hash = "sha256:8138efff315cd09b8dcd14226a21afda4ca582284bf4215126d87342bba1cc66"}, + {file = "debugpy-1.8.9-cp311-cp311-win_amd64.whl", hash = "sha256:ff54ef77ad9f5c425398efb150239f6fe8e20c53ae2f68367eba7ece1e96226d"}, + {file = "debugpy-1.8.9-cp312-cp312-macosx_14_0_universal2.whl", hash = "sha256:957363d9a7a6612a37458d9a15e72d03a635047f946e5fceee74b50d52a9c8e2"}, + {file = "debugpy-1.8.9-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5e565fc54b680292b418bb809f1386f17081d1346dca9a871bf69a8ac4071afe"}, + {file = "debugpy-1.8.9-cp312-cp312-win32.whl", hash = "sha256:3e59842d6c4569c65ceb3751075ff8d7e6a6ada209ceca6308c9bde932bcef11"}, + {file = "debugpy-1.8.9-cp312-cp312-win_amd64.whl", hash = "sha256:66eeae42f3137eb428ea3a86d4a55f28da9bd5a4a3d369ba95ecc3a92c1bba53"}, + {file = "debugpy-1.8.9-cp313-cp313-macosx_14_0_universal2.whl", hash = "sha256:957ecffff80d47cafa9b6545de9e016ae8c9547c98a538ee96ab5947115fb3dd"}, + {file = "debugpy-1.8.9-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1efbb3ff61487e2c16b3e033bc8595aea578222c08aaf3c4bf0f93fadbd662ee"}, + {file = "debugpy-1.8.9-cp313-cp313-win32.whl", hash = "sha256:7c4d65d03bee875bcb211c76c1d8f10f600c305dbd734beaed4077e902606fee"}, + {file = "debugpy-1.8.9-cp313-cp313-win_amd64.whl", hash = "sha256:e46b420dc1bea64e5bbedd678148be512442bc589b0111bd799367cde051e71a"}, + {file = "debugpy-1.8.9-cp38-cp38-macosx_14_0_x86_64.whl", hash = "sha256:472a3994999fe6c0756945ffa359e9e7e2d690fb55d251639d07208dbc37caea"}, + {file = "debugpy-1.8.9-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:365e556a4772d7d0d151d7eb0e77ec4db03bcd95f26b67b15742b88cacff88e9"}, + {file = "debugpy-1.8.9-cp38-cp38-win32.whl", hash = "sha256:54a7e6d3014c408eb37b0b06021366ee985f1539e12fe49ca2ee0d392d9ceca5"}, + {file = "debugpy-1.8.9-cp38-cp38-win_amd64.whl", hash = "sha256:8e99c0b1cc7bf86d83fb95d5ccdc4ad0586d4432d489d1f54e4055bcc795f693"}, + {file = "debugpy-1.8.9-cp39-cp39-macosx_14_0_x86_64.whl", hash = "sha256:7e8b079323a56f719977fde9d8115590cb5e7a1cba2fcee0986ef8817116e7c1"}, + {file = "debugpy-1.8.9-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6953b335b804a41f16a192fa2e7851bdcfd92173cbb2f9f777bb934f49baab65"}, + {file = "debugpy-1.8.9-cp39-cp39-win32.whl", hash = "sha256:7e646e62d4602bb8956db88b1e72fe63172148c1e25c041e03b103a25f36673c"}, + {file = "debugpy-1.8.9-cp39-cp39-win_amd64.whl", hash = "sha256:3d9755e77a2d680ce3d2c5394a444cf42be4a592caaf246dbfbdd100ffcf7ae5"}, + {file = "debugpy-1.8.9-py2.py3-none-any.whl", hash = "sha256:cc37a6c9987ad743d9c3a14fa1b1a14b7e4e6041f9dd0c8abf8895fe7a97b899"}, + {file = "debugpy-1.8.9.zip", hash = "sha256:1339e14c7d980407248f09824d1b25ff5c5616651689f1e0f0e51bdead3ea13e"}, ] [[package]] @@ -972,63 +955,63 @@ files = [ [[package]] name = "duckdb" -version = "1.1.2" +version = "1.1.3" description = "DuckDB in-process database" optional = false python-versions = ">=3.7.0" files = [ - {file = "duckdb-1.1.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:91e7f99cf5cab1d26f92cb014429153497d805e79689baa44f4c4585a8cb243f"}, - {file = "duckdb-1.1.2-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:0107de622fe208142a1108263a03c43956048dcc99be3702d8e5d2aeaf99554c"}, - {file = "duckdb-1.1.2-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:8a09610f780857677725897856f8cdf3cafd8a991f871e6cb8ba88b2dbc8d737"}, - {file = "duckdb-1.1.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c0f0ddac0482f0f3fece54d720d13819e82ae26c01a939ffa66a87be53f7f665"}, - {file = "duckdb-1.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:84103373e818758dfa361d27781d0f096553843c5ffb9193260a0786c5248270"}, - {file = "duckdb-1.1.2-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:bfdfd23e2bf58014ad0673973bd0ed88cd048dfe8e82420814a71d7d52ef2288"}, - {file = "duckdb-1.1.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:25889e6e29b87047b1dd56385ac08156e4713c59326cc6fff89657d01b2c417b"}, - {file = "duckdb-1.1.2-cp310-cp310-win_amd64.whl", hash = "sha256:312570fa5277c3079de18388b86c2d87cbe1044838bb152b235c0227581d5d42"}, - {file = "duckdb-1.1.2-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:568439ea4fce8cb72ec1f767cd510686a9e7e29a011fc7c56d990059a6e94e48"}, - {file = "duckdb-1.1.2-cp311-cp311-macosx_12_0_universal2.whl", hash = "sha256:74974f2d7210623a5d61b1fb0cb589c6e5ffcbf7dbb757a04c5ba24adcfc8cac"}, - {file = "duckdb-1.1.2-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:e26422a3358c816d764639070945b73eef55d1b4df990989e3492c85ef725c21"}, - {file = "duckdb-1.1.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:87e972bd452eeeab197fe39dcaeecdb7c264b1f75a0ee67e532e235fe45b84df"}, - {file = "duckdb-1.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a6b73e70b73c8df85da383f6e557c03cad5c877868b9a7e41715761e8166c1e"}, - {file = "duckdb-1.1.2-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:623cb1952466aae5907af84107bcdec25a5ca021a8b6441e961f41edc724f6f2"}, - {file = "duckdb-1.1.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:d9fc0b550f96901fa7e76dc70a13f6477ad3e18ef1cb21d414c3a5569de3f27e"}, - {file = "duckdb-1.1.2-cp311-cp311-win_amd64.whl", hash = "sha256:181edb1973bd8f493bcb6ecfa035f1a592dff4667758592f300619012ba251c0"}, - {file = "duckdb-1.1.2-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:83372b1b411086cac01ab2071122772fa66170b1b41ddbc37527464066083668"}, - {file = "duckdb-1.1.2-cp312-cp312-macosx_12_0_universal2.whl", hash = "sha256:db37441deddfee6ac35a0c742d2f9e90e4e50b9e76d586a060d122b8fc56dada"}, - {file = "duckdb-1.1.2-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:19142a77e72874aeaa6fda30aeb13612c6de5e8c60fbcc3392cea6ef0694eeaf"}, - {file = "duckdb-1.1.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:099d99dd48d6e4682a3dd6233ceab73d977ebe1a87afaac54cf77c844e24514a"}, - {file = "duckdb-1.1.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:be86e586ca7af7e807f72479a2b8d0983565360b19dbda4ef8a9d7b3909b8e2c"}, - {file = "duckdb-1.1.2-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:578e0953e4d8ba8da0cd69fb2930c45f51ce47d213b77d8a4cd461f9c0960b87"}, - {file = "duckdb-1.1.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:72b5eb5762c1a5e68849c7143f3b3747a9f15c040e34e41559f233a1569ad16f"}, - {file = "duckdb-1.1.2-cp312-cp312-win_amd64.whl", hash = "sha256:9b4c6b6a08180261d98330d97355503961a25ca31cd9ef296e0681f7895b4a2c"}, - {file = "duckdb-1.1.2-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:695dcbc561374b126e86659709feadf883c9969ed718e94713edd4ba15d16619"}, - {file = "duckdb-1.1.2-cp313-cp313-macosx_12_0_universal2.whl", hash = "sha256:ada29be1e889f486c6cf1f6dffd15463e748faf361f33996f2e862779edc24a9"}, - {file = "duckdb-1.1.2-cp313-cp313-macosx_12_0_x86_64.whl", hash = "sha256:6ca722738fa9eb6218619740631de29acfdd132de6f6a6350fee5e291c2f6117"}, - {file = "duckdb-1.1.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c796d33f1e5a0c8c570d22da0c0b1db8578687e427029e1ce2c8ce3f9fffa6a3"}, - {file = "duckdb-1.1.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f5c0996988a70dd3bc8111d9b9aeab7e38ed1999a52607c5f1b528e362b4dd1c"}, - {file = "duckdb-1.1.2-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6c37b039f6d6fed14d89450f5ccf54922b3304192d7412e12d6cc8d9e757f7a2"}, - {file = "duckdb-1.1.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e8c766b87f675c76d6d17103bf6fb9fb1a9e2fcb3d9b25c28bbc634bde31223e"}, - {file = "duckdb-1.1.2-cp313-cp313-win_amd64.whl", hash = "sha256:e3e6300b7ccaf64b609f4f0780a6e1d25ab8cf34cceed46e62c35b6c4c5cb63b"}, - {file = "duckdb-1.1.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8a01fae9604a54ecbc26e7503c522311f15afbd2870e6d8f6fbef4545dfae550"}, - {file = "duckdb-1.1.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:492b1d86a696428bd3f14dc1c7c3230e2dbca8978f288be64b04a26e0e00fad5"}, - {file = "duckdb-1.1.2-cp37-cp37m-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1bba58459ad897a78c4e478a097626fc266459a40338cecc68a49a8d5dc72fb7"}, - {file = "duckdb-1.1.2-cp37-cp37m-win_amd64.whl", hash = "sha256:d395a3bf510bf24686821eec15802624797dcb33e8f14f8a7cc8e17d909474af"}, - {file = "duckdb-1.1.2-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:fd800f75728727fe699ed1eb22b636867cf48c9dd105ee88b977e20c89df4509"}, - {file = "duckdb-1.1.2-cp38-cp38-macosx_12_0_universal2.whl", hash = "sha256:d8caaf43909e49537e26df51d80d075ae2b25a610d28ed8bd31d6ccebeaf3c65"}, - {file = "duckdb-1.1.2-cp38-cp38-macosx_12_0_x86_64.whl", hash = "sha256:564166811c68d9c7f9911eb707ad32ec9c2507b98336d894fbe658b85bf1c697"}, - {file = "duckdb-1.1.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:19386aa09f0d6f97634ba2972096d1c80d880176dfb0e949eadc91c98262a663"}, - {file = "duckdb-1.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e9e8387bcc9a591ad14011ddfec0d408d1d9b1889c6c9b495a04c7016a24b9b3"}, - {file = "duckdb-1.1.2-cp38-cp38-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f8c5ff4970403ed3ff0ac71fe0ce1e6be3199df9d542afc84c424b444ba4ffe8"}, - {file = "duckdb-1.1.2-cp38-cp38-win_amd64.whl", hash = "sha256:9283dcca87c3260eb631a99d738fa72b8545ed45b475bc72ad254f7310e14284"}, - {file = "duckdb-1.1.2-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:f87edaf20001530e63a4f7bda13b55dc3152d7171226915f2bf34e0813c8759e"}, - {file = "duckdb-1.1.2-cp39-cp39-macosx_12_0_universal2.whl", hash = "sha256:efec169b3fe0b821e3207ba3e445f227d42dd62b4440ff79c37fa168a4fc5a71"}, - {file = "duckdb-1.1.2-cp39-cp39-macosx_12_0_x86_64.whl", hash = "sha256:89164a2d29d56605a95ee5032aa415dd487028c4fd3e06d971497840e74c56e7"}, - {file = "duckdb-1.1.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6858e10c60ff7e70e61d3dd53d2545c8b2609942e45fd6de38cd0dee52932de3"}, - {file = "duckdb-1.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7ca967c5a57b1d0cb0fd5e539ab24110e5a59dcbedd365bb2dc80533d6e44a8d"}, - {file = "duckdb-1.1.2-cp39-cp39-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4ce949f1d7999aa6a046eb64067eee41d4c5c2872ba4fa408c9947742d0c7231"}, - {file = "duckdb-1.1.2-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:9ba6d1f918e6ca47a368a0c32806016405cb9beb2c245806b0ca998f569d2bdf"}, - {file = "duckdb-1.1.2-cp39-cp39-win_amd64.whl", hash = "sha256:7111fd3e7b334a7be383313ce29918b7c643e4f6ef44d6d63c3ab3fa6716c114"}, - {file = "duckdb-1.1.2.tar.gz", hash = "sha256:c8232861dc8ec6daa29067056d5a0e5789919f2ab22ab792787616d7cd52f02a"}, + {file = "duckdb-1.1.3-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:1c0226dc43e2ee4cc3a5a4672fddb2d76fd2cf2694443f395c02dd1bea0b7fce"}, + {file = "duckdb-1.1.3-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:7c71169fa804c0b65e49afe423ddc2dc83e198640e3b041028da8110f7cd16f7"}, + {file = "duckdb-1.1.3-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:872d38b65b66e3219d2400c732585c5b4d11b13d7a36cd97908d7981526e9898"}, + {file = "duckdb-1.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25fb02629418c0d4d94a2bc1776edaa33f6f6ccaa00bd84eb96ecb97ae4b50e9"}, + {file = "duckdb-1.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9e3f5cd604e7c39527e6060f430769b72234345baaa0987f9500988b2814f5e4"}, + {file = "duckdb-1.1.3-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:08935700e49c187fe0e9b2b86b5aad8a2ccd661069053e38bfaed3b9ff795efd"}, + {file = "duckdb-1.1.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f9b47036945e1db32d70e414a10b1593aec641bd4c5e2056873d971cc21e978b"}, + {file = "duckdb-1.1.3-cp310-cp310-win_amd64.whl", hash = "sha256:35c420f58abc79a68a286a20fd6265636175fadeca1ce964fc8ef159f3acc289"}, + {file = "duckdb-1.1.3-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:4f0e2e5a6f5a53b79aee20856c027046fba1d73ada6178ed8467f53c3877d5e0"}, + {file = "duckdb-1.1.3-cp311-cp311-macosx_12_0_universal2.whl", hash = "sha256:911d58c22645bfca4a5a049ff53a0afd1537bc18fedb13bc440b2e5af3c46148"}, + {file = "duckdb-1.1.3-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:c443d3d502335e69fc1e35295fcfd1108f72cb984af54c536adfd7875e79cee5"}, + {file = "duckdb-1.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0a55169d2d2e2e88077d91d4875104b58de45eff6a17a59c7dc41562c73df4be"}, + {file = "duckdb-1.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d0767ada9f06faa5afcf63eb7ba1befaccfbcfdac5ff86f0168c673dd1f47aa"}, + {file = "duckdb-1.1.3-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:51c6d79e05b4a0933672b1cacd6338f882158f45ef9903aef350c4427d9fc898"}, + {file = "duckdb-1.1.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:183ac743f21c6a4d6adfd02b69013d5fd78e5e2cd2b4db023bc8a95457d4bc5d"}, + {file = "duckdb-1.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:a30dd599b8090ea6eafdfb5a9f1b872d78bac318b6914ada2d35c7974d643640"}, + {file = "duckdb-1.1.3-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:a433ae9e72c5f397c44abdaa3c781d94f94f4065bcbf99ecd39433058c64cb38"}, + {file = "duckdb-1.1.3-cp312-cp312-macosx_12_0_universal2.whl", hash = "sha256:d08308e0a46c748d9c30f1d67ee1143e9c5ea3fbcccc27a47e115b19e7e78aa9"}, + {file = "duckdb-1.1.3-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:5d57776539211e79b11e94f2f6d63de77885f23f14982e0fac066f2885fcf3ff"}, + {file = "duckdb-1.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e59087dbbb63705f2483544e01cccf07d5b35afa58be8931b224f3221361d537"}, + {file = "duckdb-1.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ebf5f60ddbd65c13e77cddb85fe4af671d31b851f125a4d002a313696af43f1"}, + {file = "duckdb-1.1.3-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e4ef7ba97a65bd39d66f2a7080e6fb60e7c3e41d4c1e19245f90f53b98e3ac32"}, + {file = "duckdb-1.1.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:f58db1b65593ff796c8ea6e63e2e144c944dd3d51c8d8e40dffa7f41693d35d3"}, + {file = "duckdb-1.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:e86006958e84c5c02f08f9b96f4bc26990514eab329b1b4f71049b3727ce5989"}, + {file = "duckdb-1.1.3-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:0897f83c09356206ce462f62157ce064961a5348e31ccb2a557a7531d814e70e"}, + {file = "duckdb-1.1.3-cp313-cp313-macosx_12_0_universal2.whl", hash = "sha256:cddc6c1a3b91dcc5f32493231b3ba98f51e6d3a44fe02839556db2b928087378"}, + {file = "duckdb-1.1.3-cp313-cp313-macosx_12_0_x86_64.whl", hash = "sha256:1d9ab6143e73bcf17d62566e368c23f28aa544feddfd2d8eb50ef21034286f24"}, + {file = "duckdb-1.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f073d15d11a328f2e6d5964a704517e818e930800b7f3fa83adea47f23720d3"}, + {file = "duckdb-1.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5724fd8a49e24d730be34846b814b98ba7c304ca904fbdc98b47fa95c0b0cee"}, + {file = "duckdb-1.1.3-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:51e7dbd968b393343b226ab3f3a7b5a68dee6d3fe59be9d802383bf916775cb8"}, + {file = "duckdb-1.1.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:00cca22df96aa3473fe4584f84888e2cf1c516e8c2dd837210daec44eadba586"}, + {file = "duckdb-1.1.3-cp313-cp313-win_amd64.whl", hash = "sha256:77f26884c7b807c7edd07f95cf0b00e6d47f0de4a534ac1706a58f8bc70d0d31"}, + {file = "duckdb-1.1.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a4748635875fc3c19a7320a6ae7410f9295557450c0ebab6d6712de12640929a"}, + {file = "duckdb-1.1.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b74e121ab65dbec5290f33ca92301e3a4e81797966c8d9feef6efdf05fc6dafd"}, + {file = "duckdb-1.1.3-cp37-cp37m-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9c619e4849837c8c83666f2cd5c6c031300cd2601e9564b47aa5de458ff6e69d"}, + {file = "duckdb-1.1.3-cp37-cp37m-win_amd64.whl", hash = "sha256:0ba6baa0af33ded836b388b09433a69b8bec00263247f6bf0a05c65c897108d3"}, + {file = "duckdb-1.1.3-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:ecb1dc9062c1cc4d2d88a5e5cd8cc72af7818ab5a3c0f796ef0ffd60cfd3efb4"}, + {file = "duckdb-1.1.3-cp38-cp38-macosx_12_0_universal2.whl", hash = "sha256:5ace6e4b1873afdd38bd6cc8fcf90310fb2d454f29c39a61d0c0cf1a24ad6c8d"}, + {file = "duckdb-1.1.3-cp38-cp38-macosx_12_0_x86_64.whl", hash = "sha256:a1fa0c502f257fa9caca60b8b1478ec0f3295f34bb2efdc10776fc731b8a6c5f"}, + {file = "duckdb-1.1.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6411e21a2128d478efbd023f2bdff12464d146f92bc3e9c49247240448ace5a6"}, + {file = "duckdb-1.1.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c5336939d83837af52731e02b6a78a446794078590aa71fd400eb17f083dda3e"}, + {file = "duckdb-1.1.3-cp38-cp38-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f549af9f7416573ee48db1cf8c9d27aeed245cb015f4b4f975289418c6cf7320"}, + {file = "duckdb-1.1.3-cp38-cp38-win_amd64.whl", hash = "sha256:2141c6b28162199999075d6031b5d63efeb97c1e68fb3d797279d31c65676269"}, + {file = "duckdb-1.1.3-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:09c68522c30fc38fc972b8a75e9201616b96ae6da3444585f14cf0d116008c95"}, + {file = "duckdb-1.1.3-cp39-cp39-macosx_12_0_universal2.whl", hash = "sha256:8ee97ec337794c162c0638dda3b4a30a483d0587deda22d45e1909036ff0b739"}, + {file = "duckdb-1.1.3-cp39-cp39-macosx_12_0_x86_64.whl", hash = "sha256:a1f83c7217c188b7ab42e6a0963f42070d9aed114f6200e3c923c8899c090f16"}, + {file = "duckdb-1.1.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1aa3abec8e8995a03ff1a904b0e66282d19919f562dd0a1de02f23169eeec461"}, + {file = "duckdb-1.1.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:80158f4c7c7ada46245837d5b6869a336bbaa28436fbb0537663fa324a2750cd"}, + {file = "duckdb-1.1.3-cp39-cp39-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:647f17bd126170d96a38a9a6f25fca47ebb0261e5e44881e3782989033c94686"}, + {file = "duckdb-1.1.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:252d9b17d354beb9057098d4e5d5698e091a4f4a0d38157daeea5fc0ec161670"}, + {file = "duckdb-1.1.3-cp39-cp39-win_amd64.whl", hash = "sha256:eeacb598120040e9591f5a4edecad7080853aa8ac27e62d280f151f8c862afa3"}, + {file = "duckdb-1.1.3.tar.gz", hash = "sha256:68c3a46ab08836fe041d15dcbf838f74a990d551db47cb24ab1c4576fc19351c"}, ] [[package]] @@ -1076,13 +1059,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth [[package]] name = "fastjsonschema" -version = "2.20.0" +version = "2.21.1" description = "Fastest Python implementation of JSON schema" optional = false python-versions = "*" files = [ - {file = "fastjsonschema-2.20.0-py3-none-any.whl", hash = "sha256:5875f0b0fa7a0043a91e93a9b8f793bcbbba9691e7fd83dca95c28ba26d21f0a"}, - {file = "fastjsonschema-2.20.0.tar.gz", hash = "sha256:3d48fc5300ee96f5d116f10fe6f28d938e6008f59a6a025c2649475b87f76a23"}, + {file = "fastjsonschema-2.21.1-py3-none-any.whl", hash = "sha256:c9e5b7e908310918cf494a434eeb31384dd84a98b57a30bcb1f535015b554667"}, + {file = "fastjsonschema-2.21.1.tar.gz", hash = "sha256:794d4f0a58f848961ba16af7b9c85a3e88cd360df008c59aac6fc5ae9323b5d4"}, ] [package.extras] @@ -1328,13 +1311,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.6" +version = "1.0.7" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"}, - {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"}, + {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, + {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, ] [package.dependencies] @@ -1349,13 +1332,13 @@ trio = ["trio (>=0.22.0,<1.0)"] [[package]] name = "httpx" -version = "0.27.2" +version = "0.28.1" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"}, - {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"}, + {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"}, + {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"}, ] [package.dependencies] @@ -1363,7 +1346,6 @@ anyio = "*" certifi = "*" httpcore = "==1.*" idna = "*" -sniffio = "*" [package.extras] brotli = ["brotli", "brotlicffi"] @@ -1527,22 +1509,22 @@ arrow = ">=0.15.0" [[package]] name = "jedi" -version = "0.19.1" +version = "0.19.2" description = "An autocompletion tool for Python that can be used for text editors." optional = false python-versions = ">=3.6" files = [ - {file = "jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0"}, - {file = "jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd"}, + {file = "jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9"}, + {file = "jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0"}, ] [package.dependencies] -parso = ">=0.8.3,<0.9.0" +parso = ">=0.8.4,<0.9.0" [package.extras] docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"] qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"] -testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"] +testing = ["Django", "attrs", "colorama", "docopt", "pytest (<9.0.0)"] [[package]] name = "jinja2" @@ -1563,97 +1545,102 @@ i18n = ["Babel (>=2.7)"] [[package]] name = "jiter" -version = "0.6.1" +version = "0.8.0" description = "Fast iterable JSON parser." optional = true python-versions = ">=3.8" files = [ - {file = "jiter-0.6.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:d08510593cb57296851080018006dfc394070178d238b767b1879dc1013b106c"}, - {file = "jiter-0.6.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:adef59d5e2394ebbad13b7ed5e0306cceb1df92e2de688824232a91588e77aa7"}, - {file = "jiter-0.6.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b3e02f7a27f2bcc15b7d455c9df05df8ffffcc596a2a541eeda9a3110326e7a3"}, - {file = "jiter-0.6.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed69a7971d67b08f152c17c638f0e8c2aa207e9dd3a5fcd3cba294d39b5a8d2d"}, - {file = "jiter-0.6.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b2019d966e98f7c6df24b3b8363998575f47d26471bfb14aade37630fae836a1"}, - {file = "jiter-0.6.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:36c0b51a285b68311e207a76c385650322734c8717d16c2eb8af75c9d69506e7"}, - {file = "jiter-0.6.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:220e0963b4fb507c525c8f58cde3da6b1be0bfddb7ffd6798fb8f2531226cdb1"}, - {file = "jiter-0.6.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:aa25c7a9bf7875a141182b9c95aed487add635da01942ef7ca726e42a0c09058"}, - {file = "jiter-0.6.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e90552109ca8ccd07f47ca99c8a1509ced93920d271bb81780a973279974c5ab"}, - {file = "jiter-0.6.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:67723a011964971864e0b484b0ecfee6a14de1533cff7ffd71189e92103b38a8"}, - {file = "jiter-0.6.1-cp310-none-win32.whl", hash = "sha256:33af2b7d2bf310fdfec2da0177eab2fedab8679d1538d5b86a633ebfbbac4edd"}, - {file = "jiter-0.6.1-cp310-none-win_amd64.whl", hash = "sha256:7cea41c4c673353799906d940eee8f2d8fd1d9561d734aa921ae0f75cb9732f4"}, - {file = "jiter-0.6.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:b03c24e7da7e75b170c7b2b172d9c5e463aa4b5c95696a368d52c295b3f6847f"}, - {file = "jiter-0.6.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:47fee1be677b25d0ef79d687e238dc6ac91a8e553e1a68d0839f38c69e0ee491"}, - {file = "jiter-0.6.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25f0d2f6e01a8a0fb0eab6d0e469058dab2be46ff3139ed2d1543475b5a1d8e7"}, - {file = "jiter-0.6.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0b809e39e342c346df454b29bfcc7bca3d957f5d7b60e33dae42b0e5ec13e027"}, - {file = "jiter-0.6.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e9ac7c2f092f231f5620bef23ce2e530bd218fc046098747cc390b21b8738a7a"}, - {file = "jiter-0.6.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e51a2d80d5fe0ffb10ed2c82b6004458be4a3f2b9c7d09ed85baa2fbf033f54b"}, - {file = "jiter-0.6.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3343d4706a2b7140e8bd49b6c8b0a82abf9194b3f0f5925a78fc69359f8fc33c"}, - {file = "jiter-0.6.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:82521000d18c71e41c96960cb36e915a357bc83d63a8bed63154b89d95d05ad1"}, - {file = "jiter-0.6.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:3c843e7c1633470708a3987e8ce617ee2979ee18542d6eb25ae92861af3f1d62"}, - {file = "jiter-0.6.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:a2e861658c3fe849efc39b06ebb98d042e4a4c51a8d7d1c3ddc3b1ea091d0784"}, - {file = "jiter-0.6.1-cp311-none-win32.whl", hash = "sha256:7d72fc86474862c9c6d1f87b921b70c362f2b7e8b2e3c798bb7d58e419a6bc0f"}, - {file = "jiter-0.6.1-cp311-none-win_amd64.whl", hash = "sha256:3e36a320634f33a07794bb15b8da995dccb94f944d298c8cfe2bd99b1b8a574a"}, - {file = "jiter-0.6.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:1fad93654d5a7dcce0809aff66e883c98e2618b86656aeb2129db2cd6f26f867"}, - {file = "jiter-0.6.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:4e6e340e8cd92edab7f6a3a904dbbc8137e7f4b347c49a27da9814015cc0420c"}, - {file = "jiter-0.6.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:691352e5653af84ed71763c3c427cff05e4d658c508172e01e9c956dfe004aba"}, - {file = "jiter-0.6.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:defee3949313c1f5b55e18be45089970cdb936eb2a0063f5020c4185db1b63c9"}, - {file = "jiter-0.6.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:26d2bdd5da097e624081c6b5d416d3ee73e5b13f1703bcdadbb1881f0caa1933"}, - {file = "jiter-0.6.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:18aa9d1626b61c0734b973ed7088f8a3d690d0b7f5384a5270cd04f4d9f26c86"}, - {file = "jiter-0.6.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7a3567c8228afa5ddcce950631c6b17397ed178003dc9ee7e567c4c4dcae9fa0"}, - {file = "jiter-0.6.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e5c0507131c922defe3f04c527d6838932fcdfd69facebafd7d3574fa3395314"}, - {file = "jiter-0.6.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:540fcb224d7dc1bcf82f90f2ffb652df96f2851c031adca3c8741cb91877143b"}, - {file = "jiter-0.6.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:e7b75436d4fa2032b2530ad989e4cb0ca74c655975e3ff49f91a1a3d7f4e1df2"}, - {file = "jiter-0.6.1-cp312-none-win32.whl", hash = "sha256:883d2ced7c21bf06874fdeecab15014c1c6d82216765ca6deef08e335fa719e0"}, - {file = "jiter-0.6.1-cp312-none-win_amd64.whl", hash = "sha256:91e63273563401aadc6c52cca64a7921c50b29372441adc104127b910e98a5b6"}, - {file = "jiter-0.6.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:852508a54fe3228432e56019da8b69208ea622a3069458252f725d634e955b31"}, - {file = "jiter-0.6.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f491cc69ff44e5a1e8bc6bf2b94c1f98d179e1aaf4a554493c171a5b2316b701"}, - {file = "jiter-0.6.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cc56c8f0b2a28ad4d8047f3ae62d25d0e9ae01b99940ec0283263a04724de1f3"}, - {file = "jiter-0.6.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:51b58f7a0d9e084a43b28b23da2b09fc5e8df6aa2b6a27de43f991293cab85fd"}, - {file = "jiter-0.6.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5f79ce15099154c90ef900d69c6b4c686b64dfe23b0114e0971f2fecd306ec6c"}, - {file = "jiter-0.6.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:03a025b52009f47e53ea619175d17e4ded7c035c6fbd44935cb3ada11e1fd592"}, - {file = "jiter-0.6.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c74a8d93718137c021d9295248a87c2f9fdc0dcafead12d2930bc459ad40f885"}, - {file = "jiter-0.6.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:40b03b75f903975f68199fc4ec73d546150919cb7e534f3b51e727c4d6ccca5a"}, - {file = "jiter-0.6.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:825651a3f04cf92a661d22cad61fc913400e33aa89b3e3ad9a6aa9dc8a1f5a71"}, - {file = "jiter-0.6.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:928bf25eb69ddb292ab8177fe69d3fbf76c7feab5fce1c09265a7dccf25d3991"}, - {file = "jiter-0.6.1-cp313-none-win32.whl", hash = "sha256:352cd24121e80d3d053fab1cc9806258cad27c53cad99b7a3cac57cf934b12e4"}, - {file = "jiter-0.6.1-cp313-none-win_amd64.whl", hash = "sha256:be7503dd6f4bf02c2a9bacb5cc9335bc59132e7eee9d3e931b13d76fd80d7fda"}, - {file = "jiter-0.6.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:31d8e00e1fb4c277df8ab6f31a671f509ebc791a80e5c61fdc6bc8696aaa297c"}, - {file = "jiter-0.6.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:77c296d65003cd7ee5d7b0965f6acbe6cffaf9d1fa420ea751f60ef24e85fed5"}, - {file = "jiter-0.6.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aeeb0c0325ef96c12a48ea7e23e2e86fe4838e6e0a995f464cf4c79fa791ceeb"}, - {file = "jiter-0.6.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a31c6fcbe7d6c25d6f1cc6bb1cba576251d32795d09c09961174fe461a1fb5bd"}, - {file = "jiter-0.6.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:59e2b37f3b9401fc9e619f4d4badcab2e8643a721838bcf695c2318a0475ae42"}, - {file = "jiter-0.6.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bae5ae4853cb9644144e9d0755854ce5108d470d31541d83f70ca7ecdc2d1637"}, - {file = "jiter-0.6.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9df588e9c830b72d8db1dd7d0175af6706b0904f682ea9b1ca8b46028e54d6e9"}, - {file = "jiter-0.6.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:15f8395e835cf561c85c1adee72d899abf2733d9df72e9798e6d667c9b5c1f30"}, - {file = "jiter-0.6.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:5a99d4e0b5fc3b05ea732d67eb2092fe894e95a90e6e413f2ea91387e228a307"}, - {file = "jiter-0.6.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:a311df1fa6be0ccd64c12abcd85458383d96e542531bafbfc0a16ff6feda588f"}, - {file = "jiter-0.6.1-cp38-none-win32.whl", hash = "sha256:81116a6c272a11347b199f0e16b6bd63f4c9d9b52bc108991397dd80d3c78aba"}, - {file = "jiter-0.6.1-cp38-none-win_amd64.whl", hash = "sha256:13f9084e3e871a7c0b6e710db54444088b1dd9fbefa54d449b630d5e73bb95d0"}, - {file = "jiter-0.6.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:f1c53615fcfec3b11527c08d19cff6bc870da567ce4e57676c059a3102d3a082"}, - {file = "jiter-0.6.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f791b6a4da23238c17a81f44f5b55d08a420c5692c1fda84e301a4b036744eb1"}, - {file = "jiter-0.6.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8c97e90fec2da1d5f68ef121444c2c4fa72eabf3240829ad95cf6bbeca42a301"}, - {file = "jiter-0.6.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3cbc1a66b4e41511209e97a2866898733c0110b7245791ac604117b7fb3fedb7"}, - {file = "jiter-0.6.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e4e85f9e12cd8418ab10e1fcf0e335ae5bb3da26c4d13a0fd9e6a17a674783b6"}, - {file = "jiter-0.6.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:08be33db6dcc374c9cc19d3633af5e47961a7b10d4c61710bd39e48d52a35824"}, - {file = "jiter-0.6.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:677be9550004f5e010d673d3b2a2b815a8ea07a71484a57d3f85dde7f14cf132"}, - {file = "jiter-0.6.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e8bd065be46c2eecc328e419d6557bbc37844c88bb07b7a8d2d6c91c7c4dedc9"}, - {file = "jiter-0.6.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:bd95375ce3609ec079a97c5d165afdd25693302c071ca60c7ae1cf826eb32022"}, - {file = "jiter-0.6.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:db459ed22d0208940d87f614e1f0ea5a946d29a3cfef71f7e1aab59b6c6b2afb"}, - {file = "jiter-0.6.1-cp39-none-win32.whl", hash = "sha256:d71c962f0971347bd552940ab96aa42ceefcd51b88c4ced8a27398182efa8d80"}, - {file = "jiter-0.6.1-cp39-none-win_amd64.whl", hash = "sha256:d465db62d2d10b489b7e7a33027c4ae3a64374425d757e963f86df5b5f2e7fc5"}, - {file = "jiter-0.6.1.tar.gz", hash = "sha256:e19cd21221fc139fb032e4112986656cb2739e9fe6d84c13956ab30ccc7d4449"}, + {file = "jiter-0.8.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:dee4eeb293ffcd2c3b31ebab684dbf7f7b71fe198f8eddcdf3a042cc6e10205a"}, + {file = "jiter-0.8.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:aad1e6e9b01cf0304dcee14db03e92e0073287a6297caf5caf2e9dbfea16a924"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:504099fb7acdbe763e10690d560a25d4aee03d918d6a063f3a761d8a09fb833f"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2373487caad7fe39581f588ab5c9262fc1ade078d448626fec93f4ffba528858"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c341ecc3f9bccde952898b0c97c24f75b84b56a7e2f8bbc7c8e38cab0875a027"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0e48e7a336529b9419d299b70c358d4ebf99b8f4b847ed3f1000ec9f320e8c0c"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f5ee157a8afd2943be690db679f82fafb8d347a8342e8b9c34863de30c538d55"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d7dceae3549b80087f913aad4acc2a7c1e0ab7cb983effd78bdc9c41cabdcf18"}, + {file = "jiter-0.8.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e29e9ecce53d396772590438214cac4ab89776f5e60bd30601f1050b34464019"}, + {file = "jiter-0.8.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:fa1782f22d5f92c620153133f35a9a395d3f3823374bceddd3e7032e2fdfa0b1"}, + {file = "jiter-0.8.0-cp310-none-win32.whl", hash = "sha256:f754ef13b4e4f67a3bf59fe974ef4342523801c48bf422f720bd37a02a360584"}, + {file = "jiter-0.8.0-cp310-none-win_amd64.whl", hash = "sha256:796f750b65f5d605f5e7acaccc6b051675e60c41d7ac3eab40dbd7b5b81a290f"}, + {file = "jiter-0.8.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:f6f4e645efd96b4690b9b6091dbd4e0fa2885ba5c57a0305c1916b75b4f30ff6"}, + {file = "jiter-0.8.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f61cf6d93c1ade9b8245c9f14b7900feadb0b7899dbe4aa8de268b705647df81"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0396bc5cb1309c6dab085e70bb3913cdd92218315e47b44afe9eace68ee8adaa"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:62d0e42ec5dc772bd8554a304358220be5d97d721c4648b23f3a9c01ccc2cb26"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ec4b711989860705733fc59fb8c41b2def97041cea656b37cf6c8ea8dee1c3f4"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:859cc35bf304ab066d88f10a44a3251a9cd057fb11ec23e00be22206db878f4f"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5000195921aa293b39b9b5bc959d7fa658e7f18f938c0e52732da8e3cc70a278"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:36050284c0abde57aba34964d3920f3d6228211b65df7187059bb7c7f143759a"}, + {file = "jiter-0.8.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:a88f608e050cfe45c48d771e86ecdbf5258314c883c986d4217cc79e1fb5f689"}, + {file = "jiter-0.8.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:646cf4237665b2e13b4159d8f26d53f59bc9f2e6e135e3a508a2e5dd26d978c6"}, + {file = "jiter-0.8.0-cp311-none-win32.whl", hash = "sha256:21fe5b8345db1b3023052b2ade9bb4d369417827242892051244af8fae8ba231"}, + {file = "jiter-0.8.0-cp311-none-win_amd64.whl", hash = "sha256:30c2161c5493acf6b6c3c909973fb64ae863747def01cc7574f3954e0a15042c"}, + {file = "jiter-0.8.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:d91a52d8f49ada2672a4b808a0c5c25d28f320a2c9ca690e30ebd561eb5a1002"}, + {file = "jiter-0.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c38cf25cf7862f61410b7a49684d34eb3b5bcbd7ddaf4773eea40e0bd43de706"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c6189beb5c4b3117624be6b2e84545cff7611f5855d02de2d06ff68e316182be"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e13fa849c0e30643554add089983caa82f027d69fad8f50acadcb21c462244ab"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d7765ca159d0a58e8e0f8ca972cd6d26a33bc97b4480d0d2309856763807cd28"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1b0befe7c6e9fc867d5bed21bab0131dfe27d1fa5cd52ba2bced67da33730b7d"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7d6363d4c6f1052b1d8b494eb9a72667c3ef5f80ebacfe18712728e85327000"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a873e57009863eeac3e3969e4653f07031d6270d037d6224415074ac17e5505c"}, + {file = "jiter-0.8.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:2582912473c0d9940791479fe1bf2976a34f212eb8e0a82ee9e645ac275c5d16"}, + {file = "jiter-0.8.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:646163201af42f55393ee6e8f6136b8df488253a6533f4230a64242ecbfe6048"}, + {file = "jiter-0.8.0-cp312-none-win32.whl", hash = "sha256:96e75c9abfbf7387cba89a324d2356d86d8897ac58c956017d062ad510832dae"}, + {file = "jiter-0.8.0-cp312-none-win_amd64.whl", hash = "sha256:ed6074552b4a32e047b52dad5ab497223721efbd0e9efe68c67749f094a092f7"}, + {file = "jiter-0.8.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:dd5e351cb9b3e676ec3360a85ea96def515ad2b83c8ae3a251ce84985a2c9a6f"}, + {file = "jiter-0.8.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ba9f12b0f801ecd5ed0cec29041dc425d1050922b434314c592fc30d51022467"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a7ba461c3681728d556392e8ae56fb44a550155a24905f01982317b367c21dd4"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3a15ed47ab09576db560dbc5c2c5a64477535beb056cd7d997d5dd0f2798770e"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cef55042816d0737142b0ec056c0356a5f681fb8d6aa8499b158e87098f4c6f8"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:549f170215adeb5e866f10617c3d019d8eb4e6d4e3c6b724b3b8c056514a3487"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f867edeb279d22020877640d2ea728de5817378c60a51be8af731a8a8f525306"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:aef8845f463093799db4464cee2aa59d61aa8edcb3762aaa4aacbec3f478c929"}, + {file = "jiter-0.8.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:d0d6e22e4062c3d3c1bf3594baa2f67fc9dcdda8275abad99e468e0c6540bc54"}, + {file = "jiter-0.8.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:079e62e64696241ac3f408e337aaac09137ed760ccf2b72b1094b48745c13641"}, + {file = "jiter-0.8.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:74d2b56ed3da5760544df53b5f5c39782e68efb64dc3aa0bba4cc08815e6fae8"}, + {file = "jiter-0.8.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:798dafe108cba58a7bb0a50d4d5971f98bb7f3c974e1373e750de6eb21c1a329"}, + {file = "jiter-0.8.0-cp313-none-win32.whl", hash = "sha256:ca6d3064dfc743eb0d3d7539d89d4ba886957c717567adc72744341c1e3573c9"}, + {file = "jiter-0.8.0-cp313-none-win_amd64.whl", hash = "sha256:38caedda64fe1f04b06d7011fc15e86b3b837ed5088657bf778656551e3cd8f9"}, + {file = "jiter-0.8.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:bb5c8a0a8d081c338db22e5b8d53a89a121790569cbb85f7d3cfb1fe0fbe9836"}, + {file = "jiter-0.8.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:202dbe8970bfb166fab950eaab8f829c505730a0b33cc5e1cfb0a1c9dd56b2f9"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9046812e5671fdcfb9ae02881fff1f6a14d484b7e8b3316179a372cdfa1e8026"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e6ac56425023e52d65150918ae25480d0a1ce2a6bf5ea2097f66a2cc50f6d692"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7dfcf97210c6eab9d2a1c6af15dd39e1d5154b96a7145d0a97fa1df865b7b834"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d4e3c8444d418686f78c9a547b9b90031faf72a0a1a46bfec7fb31edbd889c0d"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6507011a299b7f578559084256405a8428875540d8d13530e00b688e41b09493"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0aae4738eafdd34f0f25c2d3668ce9e8fa0d7cb75a2efae543c9a69aebc37323"}, + {file = "jiter-0.8.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:7f5d782e790396b13f2a7b36bdcaa3736a33293bdda80a4bf1a3ce0cd5ef9f15"}, + {file = "jiter-0.8.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:cc7f993bc2c4e03015445adbb16790c303282fce2e8d9dc3a3905b1d40e50564"}, + {file = "jiter-0.8.0-cp38-none-win32.whl", hash = "sha256:d4a8a6eda018a991fa58ef707dd51524055d11f5acb2f516d70b1be1d15ab39c"}, + {file = "jiter-0.8.0-cp38-none-win_amd64.whl", hash = "sha256:4cca948a3eda8ea24ed98acb0ee19dc755b6ad2e570ec85e1527d5167f91ff67"}, + {file = "jiter-0.8.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:ef89663678d8257063ce7c00d94638e05bd72f662c5e1eb0e07a172e6c1a9a9f"}, + {file = "jiter-0.8.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c402ddcba90b4cc71db3216e8330f4db36e0da2c78cf1d8a9c3ed8f272602a94"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a6dfe795b7a173a9f8ba7421cdd92193d60c1c973bbc50dc3758a9ad0fa5eb6"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8ec29a31b9abd6be39453a2c45da067138a3005d65d2c0507c530e0f1fdcd9a4"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2a488f8c54bddc3ddefaf3bfd6de4a52c97fc265d77bc2dcc6ee540c17e8c342"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:aeb5561adf4d26ca0d01b5811b4d7b56a8986699a473d700757b4758ef787883"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ab961858d7ad13132328517d29f121ae1b2d94502191d6bcf96bddcc8bb5d1c"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a207e718d114d23acf0850a2174d290f42763d955030d9924ffa4227dbd0018f"}, + {file = "jiter-0.8.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:733bc9dc8ff718a0ae4695239e9268eb93e88b73b367dfac3ec227d8ce2f1e77"}, + {file = "jiter-0.8.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d1ec27299e22d05e13a06e460bf7f75f26f9aaa0e0fb7d060f40e88df1d81faa"}, + {file = "jiter-0.8.0-cp39-none-win32.whl", hash = "sha256:e8dbfcb46553e6661d3fc1f33831598fcddf73d0f67834bce9fc3e9ebfe5c439"}, + {file = "jiter-0.8.0-cp39-none-win_amd64.whl", hash = "sha256:af2ce2487b3a93747e2cb5150081d4ae1e5874fce5924fc1a12e9e768e489ad8"}, + {file = "jiter-0.8.0.tar.gz", hash = "sha256:86fee98b569d4cc511ff2e3ec131354fafebd9348a487549c31ad371ae730310"}, ] [[package]] name = "json5" -version = "0.9.25" +version = "0.10.0" description = "A Python implementation of the JSON5 data format." optional = false -python-versions = ">=3.8" +python-versions = ">=3.8.0" files = [ - {file = "json5-0.9.25-py3-none-any.whl", hash = "sha256:34ed7d834b1341a86987ed52f3f76cd8ee184394906b6e22a1e0deb9ab294e8f"}, - {file = "json5-0.9.25.tar.gz", hash = "sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae"}, + {file = "json5-0.10.0-py3-none-any.whl", hash = "sha256:19b23410220a7271e8377f81ba8aacba2fdd56947fbb137ee5977cbe1f5e8dfa"}, + {file = "json5-0.10.0.tar.gz", hash = "sha256:e66941c8f0a02026943c52c2eb34ebeb2a6f819a0be05920a6f5243cd30fd559"}, ] +[package.extras] +dev = ["build (==1.2.2.post1)", "coverage (==7.5.3)", "mypy (==1.13.0)", "pip (==24.3.1)", "pylint (==3.2.3)", "ruff (==0.7.3)", "twine (==5.1.1)", "uv (==0.5.1)"] + [[package]] name = "jsonpatch" version = "1.33" @@ -1905,18 +1892,18 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (> [[package]] name = "jupyterlab" -version = "4.3.0" +version = "4.3.2" description = "JupyterLab computational environment" optional = false python-versions = ">=3.8" files = [ - {file = "jupyterlab-4.3.0-py3-none-any.whl", hash = "sha256:f67e1095ad61ae04349024f0b40345062ab108a0c6998d9810fec6a3c1a70cd5"}, - {file = "jupyterlab-4.3.0.tar.gz", hash = "sha256:7c6835cbf8df0af0ec8a39332e85ff11693fb9a468205343b4fc0bfbc74817e5"}, + {file = "jupyterlab-4.3.2-py3-none-any.whl", hash = "sha256:e87100cbab8b886ff7a4f325c856100ba6fdfe916162a85409daf0e707e19d1d"}, + {file = "jupyterlab-4.3.2.tar.gz", hash = "sha256:3c0a6882dbddcc0a7bfdd5e2236f351b2b263e48780236e6996c2aca13ac5b22"}, ] [package.dependencies] async-lru = ">=1.0.0" -httpx = ">=0.25.0" +httpx = ">=0.28.0,<0.29.0" importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""} ipykernel = ">=6.5.0" jinja2 = ">=3.0.3" @@ -1926,7 +1913,7 @@ jupyter-server = ">=2.4.0,<3" jupyterlab-server = ">=2.27.1,<3" notebook-shim = ">=0.2" packaging = "*" -setuptools = ">=40.1.0" +setuptools = ">=40.8.0" tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""} tornado = ">=6.2.0" traitlets = "*" @@ -1988,7 +1975,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.22" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -2013,7 +2000,7 @@ url = "../core" [[package]] name = "langchain-openai" -version = "0.2.8" +version = "0.2.11" description = "An integration package connecting OpenAI and LangChain" optional = true python-versions = ">=3.9,<4.0" @@ -2021,7 +2008,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.17" +langchain-core = "^0.3.21" openai = "^1.54.0" tiktoken = ">=0.7,<1" @@ -2031,7 +2018,7 @@ url = "../partners/openai" [[package]] name = "langchain-tests" -version = "0.3.1" +version = "0.3.5" description = "Standard tests for LangChain implementations" optional = false python-versions = ">=3.9,<4.0" @@ -2039,9 +2026,15 @@ files = [] develop = true [package.dependencies] -httpx = "^0.27.0" -langchain-core = "^0.3.15" +httpx = ">=0.25.0,<1" +langchain-core = "^0.3.21" +numpy = [ + {version = ">=1.24.0,<2.0.0", markers = "python_version < \"3.12\""}, + {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}, +] pytest = ">=7,<9" +pytest-asyncio = ">=0.20,<1" +pytest-socket = ">=0.6.0,<1" syrupy = "^4" [package.source] @@ -2082,18 +2075,18 @@ types-requests = ">=2.31.0.2,<3.0.0.0" [[package]] name = "langsmith" -version = "0.1.138" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.138-py3-none-any.whl", hash = "sha256:5c2bd5c11c75f7b3d06a0f06b115186e7326ca969fd26d66ffc65a0669012aee"}, - {file = "langsmith-0.1.138.tar.gz", hash = "sha256:1ecf613bb52f6bf17f1510e24ad8b70d4b0259bc9d3dbfd69b648c66d4644f0b"}, + {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"}, + {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -2101,6 +2094,9 @@ pydantic = [ requests = ">=2,<3" requests-toolbelt = ">=1.0.0,<2.0.0" +[package.extras] +langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"] + [[package]] name = "lark" version = "1.2.2" @@ -2398,13 +2394,13 @@ types-protobuf = ">=4.24" [[package]] name = "nbclient" -version = "0.10.0" +version = "0.10.1" description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." optional = false python-versions = ">=3.8.0" files = [ - {file = "nbclient-0.10.0-py3-none-any.whl", hash = "sha256:f13e3529332a1f1f81d82a53210322476a168bb7090a0289c795fe9cc11c9d3f"}, - {file = "nbclient-0.10.0.tar.gz", hash = "sha256:4b3f1b7dba531e498449c4db4f53da339c91d449dc11e9af3a43b4eb5c5abb09"}, + {file = "nbclient-0.10.1-py3-none-any.whl", hash = "sha256:949019b9240d66897e442888cfb618f69ef23dc71c01cb5fced8499c2cfc084d"}, + {file = "nbclient-0.10.1.tar.gz", hash = "sha256:3e93e348ab27e712acd46fccd809139e356eb9a31aab641d1a7991a6eb4e6f68"}, ] [package.dependencies] @@ -2415,7 +2411,7 @@ traitlets = ">=5.4" [package.extras] dev = ["pre-commit"] -docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"] +docs = ["autodoc-traits", "flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "mock", "moto", "myst-parser", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling", "testpath", "xmltodict"] test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"] [[package]] @@ -2490,26 +2486,26 @@ files = [ [[package]] name = "notebook" -version = "7.0.7" +version = "7.3.1" description = "Jupyter Notebook - A web-based notebook environment for interactive computing" optional = false python-versions = ">=3.8" files = [ - {file = "notebook-7.0.7-py3-none-any.whl", hash = "sha256:289b606d7e173f75a18beb1406ef411b43f97f7a9c55ba03efa3622905a62346"}, - {file = "notebook-7.0.7.tar.gz", hash = "sha256:3bcff00c17b3ac142ef5f436d50637d936b274cfa0b41f6ac0175363de9b4e09"}, + {file = "notebook-7.3.1-py3-none-any.whl", hash = "sha256:212e1486b2230fe22279043f33c7db5cf9a01d29feb063a85cb139747b7c9483"}, + {file = "notebook-7.3.1.tar.gz", hash = "sha256:84381c2a82d867517fd25b86e986dae1fe113a70b98f03edff9b94e499fec8fa"}, ] [package.dependencies] jupyter-server = ">=2.4.0,<3" -jupyterlab = ">=4.0.2,<5" -jupyterlab-server = ">=2.22.1,<3" +jupyterlab = ">=4.3.2,<4.4" +jupyterlab-server = ">=2.27.1,<3" notebook-shim = ">=0.2,<0.3" tornado = ">=6.2.0" [package.extras] dev = ["hatch", "pre-commit"] docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"] -test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.22.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"] +test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"] [[package]] name = "notebook-shim" @@ -2573,15 +2569,79 @@ files = [ {file = "numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010"}, ] +[[package]] +name = "numpy" +version = "2.1.3" +description = "Fundamental package for array computing in Python" +optional = false +python-versions = ">=3.10" +files = [ + {file = "numpy-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c894b4305373b9c5576d7a12b473702afdf48ce5369c074ba304cc5ad8730dff"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b47fbb433d3260adcd51eb54f92a2ffbc90a4595f8970ee00e064c644ac788f5"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:825656d0743699c529c5943554d223c021ff0494ff1442152ce887ef4f7561a1"}, + {file = "numpy-2.1.3-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:6a4825252fcc430a182ac4dee5a505053d262c807f8a924603d411f6718b88fd"}, + {file = "numpy-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e711e02f49e176a01d0349d82cb5f05ba4db7d5e7e0defd026328e5cfb3226d3"}, + {file = "numpy-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:78574ac2d1a4a02421f25da9559850d59457bac82f2b8d7a44fe83a64f770098"}, + {file = "numpy-2.1.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:c7662f0e3673fe4e832fe07b65c50342ea27d989f92c80355658c7f888fcc83c"}, + {file = "numpy-2.1.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:fa2d1337dc61c8dc417fbccf20f6d1e139896a30721b7f1e832b2bb6ef4eb6c4"}, + {file = "numpy-2.1.3-cp310-cp310-win32.whl", hash = "sha256:72dcc4a35a8515d83e76b58fdf8113a5c969ccd505c8a946759b24e3182d1f23"}, + {file = "numpy-2.1.3-cp310-cp310-win_amd64.whl", hash = "sha256:ecc76a9ba2911d8d37ac01de72834d8849e55473457558e12995f4cd53e778e0"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4d1167c53b93f1f5d8a139a742b3c6f4d429b54e74e6b57d0eff40045187b15d"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c80e4a09b3d95b4e1cac08643f1152fa71a0a821a2d4277334c88d54b2219a41"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:576a1c1d25e9e02ed7fa5477f30a127fe56debd53b8d2c89d5578f9857d03ca9"}, + {file = "numpy-2.1.3-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:973faafebaae4c0aaa1a1ca1ce02434554d67e628b8d805e61f874b84e136b09"}, + {file = "numpy-2.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:762479be47a4863e261a840e8e01608d124ee1361e48b96916f38b119cfda04a"}, + {file = "numpy-2.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc6f24b3d1ecc1eebfbf5d6051faa49af40b03be1aaa781ebdadcbc090b4539b"}, + {file = "numpy-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:17ee83a1f4fef3c94d16dc1802b998668b5419362c8a4f4e8a491de1b41cc3ee"}, + {file = "numpy-2.1.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:15cb89f39fa6d0bdfb600ea24b250e5f1a3df23f901f51c8debaa6a5d122b2f0"}, + {file = "numpy-2.1.3-cp311-cp311-win32.whl", hash = "sha256:d9beb777a78c331580705326d2367488d5bc473b49a9bc3036c154832520aca9"}, + {file = "numpy-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:d89dd2b6da69c4fff5e39c28a382199ddedc3a5be5390115608345dec660b9e2"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f55ba01150f52b1027829b50d70ef1dafd9821ea82905b63936668403c3b471e"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:13138eadd4f4da03074851a698ffa7e405f41a0845a6b1ad135b81596e4e9958"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:a6b46587b14b888e95e4a24d7b13ae91fa22386c199ee7b418f449032b2fa3b8"}, + {file = "numpy-2.1.3-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:0fa14563cc46422e99daef53d725d0c326e99e468a9320a240affffe87852564"}, + {file = "numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8637dcd2caa676e475503d1f8fdb327bc495554e10838019651b76d17b98e512"}, + {file = "numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2312b2aa89e1f43ecea6da6ea9a810d06aae08321609d8dc0d0eda6d946a541b"}, + {file = "numpy-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a38c19106902bb19351b83802531fea19dee18e5b37b36454f27f11ff956f7fc"}, + {file = "numpy-2.1.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:02135ade8b8a84011cbb67dc44e07c58f28575cf9ecf8ab304e51c05528c19f0"}, + {file = "numpy-2.1.3-cp312-cp312-win32.whl", hash = "sha256:e6988e90fcf617da2b5c78902fe8e668361b43b4fe26dbf2d7b0f8034d4cafb9"}, + {file = "numpy-2.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:0d30c543f02e84e92c4b1f415b7c6b5326cbe45ee7882b6b77db7195fb971e3a"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:96fe52fcdb9345b7cd82ecd34547fca4321f7656d500eca497eb7ea5a926692f"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f653490b33e9c3a4c1c01d41bc2aef08f9475af51146e4a7710c450cf9761598"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:dc258a761a16daa791081d026f0ed4399b582712e6fc887a95af09df10c5ca57"}, + {file = "numpy-2.1.3-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:016d0f6f5e77b0f0d45d77387ffa4bb89816b57c835580c3ce8e099ef830befe"}, + {file = "numpy-2.1.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c181ba05ce8299c7aa3125c27b9c2167bca4a4445b7ce73d5febc411ca692e43"}, + {file = "numpy-2.1.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5641516794ca9e5f8a4d17bb45446998c6554704d888f86df9b200e66bdcce56"}, + {file = "numpy-2.1.3-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ea4dedd6e394a9c180b33c2c872b92f7ce0f8e7ad93e9585312b0c5a04777a4a"}, + {file = "numpy-2.1.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:b0df3635b9c8ef48bd3be5f862cf71b0a4716fa0e702155c45067c6b711ddcef"}, + {file = "numpy-2.1.3-cp313-cp313-win32.whl", hash = "sha256:50ca6aba6e163363f132b5c101ba078b8cbd3fa92c7865fd7d4d62d9779ac29f"}, + {file = "numpy-2.1.3-cp313-cp313-win_amd64.whl", hash = "sha256:747641635d3d44bcb380d950679462fae44f54b131be347d5ec2bce47d3df9ed"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:996bb9399059c5b82f76b53ff8bb686069c05acc94656bb259b1d63d04a9506f"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:45966d859916ad02b779706bb43b954281db43e185015df6eb3323120188f9e4"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:baed7e8d7481bfe0874b566850cb0b85243e982388b7b23348c6db2ee2b2ae8e"}, + {file = "numpy-2.1.3-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:a9f7f672a3388133335589cfca93ed468509cb7b93ba3105fce780d04a6576a0"}, + {file = "numpy-2.1.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7aac50327da5d208db2eec22eb11e491e3fe13d22653dce51b0f4109101b408"}, + {file = "numpy-2.1.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4394bc0dbd074b7f9b52024832d16e019decebf86caf909d94f6b3f77a8ee3b6"}, + {file = "numpy-2.1.3-cp313-cp313t-musllinux_1_1_x86_64.whl", hash = "sha256:50d18c4358a0a8a53f12a8ba9d772ab2d460321e6a93d6064fc22443d189853f"}, + {file = "numpy-2.1.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:14e253bd43fc6b37af4921b10f6add6925878a42a0c5fe83daee390bca80bc17"}, + {file = "numpy-2.1.3-cp313-cp313t-win32.whl", hash = "sha256:08788d27a5fd867a663f6fc753fd7c3ad7e92747efc73c53bca2f19f8bc06f48"}, + {file = "numpy-2.1.3-cp313-cp313t-win_amd64.whl", hash = "sha256:2564fbdf2b99b3f815f2107c1bbc93e2de8ee655a69c261363a1172a79a257d4"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:4f2015dfe437dfebbfce7c85c7b53d81ba49e71ba7eadbf1df40c915af75979f"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:3522b0dfe983a575e6a9ab3a4a4dfe156c3e428468ff08ce582b9bb6bd1d71d4"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c006b607a865b07cd981ccb218a04fc86b600411d83d6fc261357f1c0966755d"}, + {file = "numpy-2.1.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:e14e26956e6f1696070788252dcdff11b4aca4c3e8bd166e0df1bb8f315a67cb"}, + {file = "numpy-2.1.3.tar.gz", hash = "sha256:aa08e04e08aaf974d4458def539dece0d28146d866a39da5639596f4921fd761"}, +] + [[package]] name = "openai" -version = "1.54.4" +version = "1.57.0" description = "The official Python library for the openai API" optional = true python-versions = ">=3.8" files = [ - {file = "openai-1.54.4-py3-none-any.whl", hash = "sha256:0d95cef99346bf9b6d7fbf57faf61a673924c3e34fa8af84c9ffe04660673a7e"}, - {file = "openai-1.54.4.tar.gz", hash = "sha256:50f3656e45401c54e973fa05dc29f3f0b0d19348d685b2f7ddb4d92bf7b1b6bf"}, + {file = "openai-1.57.0-py3-none-any.whl", hash = "sha256:972e36960b821797952da3dc4532f486c28e28a2a332d7d0c5407f242e9d9c39"}, + {file = "openai-1.57.0.tar.gz", hash = "sha256:76f91971c4bdbd78380c9970581075e0337b5d497c2fbf7b5255078f4b31abf9"}, ] [package.dependencies] @@ -2599,69 +2659,86 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"] [[package]] name = "orjson" -version = "3.10.10" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.10-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:b788a579b113acf1c57e0a68e558be71d5d09aa67f62ca1f68e01117e550a998"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:804b18e2b88022c8905bb79bd2cbe59c0cd014b9328f43da8d3b28441995cda4"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9972572a1d042ec9ee421b6da69f7cc823da5962237563fa548ab17f152f0b9b"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc6993ab1c2ae7dd0711161e303f1db69062955ac2668181bfdf2dd410e65258"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d78e4cacced5781b01d9bc0f0cd8b70b906a0e109825cb41c1b03f9c41e4ce86"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e6eb2598df518281ba0cbc30d24c5b06124ccf7e19169e883c14e0831217a0bc"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:23776265c5215ec532de6238a52707048401a568f0fa0d938008e92a147fe2c7"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8cc2a654c08755cef90b468ff17c102e2def0edd62898b2486767204a7f5cc9c"}, - {file = "orjson-3.10.10-cp310-none-win32.whl", hash = "sha256:081b3fc6a86d72efeb67c13d0ea7c030017bd95f9868b1e329a376edc456153b"}, - {file = "orjson-3.10.10-cp310-none-win_amd64.whl", hash = "sha256:ff38c5fb749347768a603be1fb8a31856458af839f31f064c5aa74aca5be9efe"}, - {file = "orjson-3.10.10-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:879e99486c0fbb256266c7c6a67ff84f46035e4f8749ac6317cc83dacd7f993a"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:019481fa9ea5ff13b5d5d95e6fd5ab25ded0810c80b150c2c7b1cc8660b662a7"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0dd57eff09894938b4c86d4b871a479260f9e156fa7f12f8cad4b39ea8028bb5"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dbde6d70cd95ab4d11ea8ac5e738e30764e510fc54d777336eec09bb93b8576c"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b2625cb37b8fb42e2147404e5ff7ef08712099197a9cd38895006d7053e69d6"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dbf3c20c6a7db69df58672a0d5815647ecf78c8e62a4d9bd284e8621c1fe5ccb"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:75c38f5647e02d423807d252ce4528bf6a95bd776af999cb1fb48867ed01d1f6"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:23458d31fa50ec18e0ec4b0b4343730928296b11111df5f547c75913714116b2"}, - {file = "orjson-3.10.10-cp311-none-win32.whl", hash = "sha256:2787cd9dedc591c989f3facd7e3e86508eafdc9536a26ec277699c0aa63c685b"}, - {file = "orjson-3.10.10-cp311-none-win_amd64.whl", hash = "sha256:6514449d2c202a75183f807bc755167713297c69f1db57a89a1ef4a0170ee269"}, - {file = "orjson-3.10.10-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:8564f48f3620861f5ef1e080ce7cd122ee89d7d6dacf25fcae675ff63b4d6e05"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5bf161a32b479034098c5b81f2608f09167ad2fa1c06abd4e527ea6bf4837a9"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:68b65c93617bcafa7f04b74ae8bc2cc214bd5cb45168a953256ff83015c6747d"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e8e28406f97fc2ea0c6150f4c1b6e8261453318930b334abc419214c82314f85"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e4d0d9fe174cc7a5bdce2e6c378bcdb4c49b2bf522a8f996aa586020e1b96cee"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b3be81c42f1242cbed03cbb3973501fcaa2675a0af638f8be494eaf37143d999"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:65f9886d3bae65be026219c0a5f32dbbe91a9e6272f56d092ab22561ad0ea33b"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:730ed5350147db7beb23ddaf072f490329e90a1d059711d364b49fe352ec987b"}, - {file = "orjson-3.10.10-cp312-none-win32.whl", hash = "sha256:a8f4bf5f1c85bea2170800020d53a8877812892697f9c2de73d576c9307a8a5f"}, - {file = "orjson-3.10.10-cp312-none-win_amd64.whl", hash = "sha256:384cd13579a1b4cd689d218e329f459eb9ddc504fa48c5a83ef4889db7fd7a4f"}, - {file = "orjson-3.10.10-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:44bffae68c291f94ff5a9b4149fe9d1bdd4cd0ff0fb575bcea8351d48db629a1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e27b4c6437315df3024f0835887127dac2a0a3ff643500ec27088d2588fa5ae1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca84df16d6b49325a4084fd8b2fe2229cb415e15c46c529f868c3387bb1339d"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c14ce70e8f39bd71f9f80423801b5d10bf93d1dceffdecd04df0f64d2c69bc01"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:24ac62336da9bda1bd93c0491eff0613003b48d3cb5d01470842e7b52a40d5b4"}, - {file = "orjson-3.10.10-cp313-none-win32.whl", hash = "sha256:eb0a42831372ec2b05acc9ee45af77bcaccbd91257345f93780a8e654efc75db"}, - {file = "orjson-3.10.10-cp313-none-win_amd64.whl", hash = "sha256:f0c4f37f8bf3f1075c6cc8dd8a9f843689a4b618628f8812d0a71e6968b95ffd"}, - {file = "orjson-3.10.10-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:829700cc18503efc0cf502d630f612884258020d98a317679cd2054af0259568"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e0ceb5e0e8c4f010ac787d29ae6299846935044686509e2f0f06ed441c1ca949"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0c25908eb86968613216f3db4d3003f1c45d78eb9046b71056ca327ff92bdbd4"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:218cb0bc03340144b6328a9ff78f0932e642199ac184dd74b01ad691f42f93ff"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e2277ec2cea3775640dc81ab5195bb5b2ada2fe0ea6eee4677474edc75ea6785"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:848ea3b55ab5ccc9d7bbd420d69432628b691fba3ca8ae3148c35156cbd282aa"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:e3e67b537ac0c835b25b5f7d40d83816abd2d3f4c0b0866ee981a045287a54f3"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:7948cfb909353fce2135dcdbe4521a5e7e1159484e0bb024c1722f272488f2b8"}, - {file = "orjson-3.10.10-cp38-none-win32.whl", hash = "sha256:78bee66a988f1a333dc0b6257503d63553b1957889c17b2c4ed72385cd1b96ae"}, - {file = "orjson-3.10.10-cp38-none-win_amd64.whl", hash = "sha256:f1d647ca8d62afeb774340a343c7fc023efacfd3a39f70c798991063f0c681dd"}, - {file = "orjson-3.10.10-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:5a059afddbaa6dd733b5a2d76a90dbc8af790b993b1b5cb97a1176ca713b5df8"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6f9b5c59f7e2a1a410f971c5ebc68f1995822837cd10905ee255f96074537ee6"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d5ef198bafdef4aa9d49a4165ba53ffdc0a9e1c7b6f76178572ab33118afea25"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:aaf29ce0bb5d3320824ec3d1508652421000ba466abd63bdd52c64bcce9eb1fa"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dddd5516bcc93e723d029c1633ae79c4417477b4f57dad9bfeeb6bc0315e654a"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a12f2003695b10817f0fa8b8fca982ed7f5761dcb0d93cff4f2f9f6709903fd7"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:672f9874a8a8fb9bb1b771331d31ba27f57702c8106cdbadad8bda5d10bc1019"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1dcbb0ca5fafb2b378b2c74419480ab2486326974826bbf6588f4dc62137570a"}, - {file = "orjson-3.10.10-cp39-none-win32.whl", hash = "sha256:d9bbd3a4b92256875cb058c3381b782649b9a3c68a4aa9a2fff020c2f9cfc1be"}, - {file = "orjson-3.10.10-cp39-none-win_amd64.whl", hash = "sha256:766f21487a53aee8524b97ca9582d5c6541b03ab6210fbaf10142ae2f3ced2aa"}, - {file = "orjson-3.10.10.tar.gz", hash = "sha256:37949383c4df7b4337ce82ee35b6d7471e55195efa7dcb45ab8226ceadb0fe3b"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] @@ -2677,13 +2754,13 @@ files = [ [[package]] name = "packaging" -version = "24.1" +version = "24.2" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" files = [ - {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"}, - {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"}, + {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, + {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, ] [[package]] @@ -2830,18 +2907,18 @@ type = ["mypy (>=1.11.2)"] [[package]] name = "playwright" -version = "1.48.0" +version = "1.49.0" description = "A high-level API to automate web browsers" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "playwright-1.48.0-py3-none-macosx_10_13_x86_64.whl", hash = "sha256:082bce2739f1078acc7d0734da8cc0e23eb91b7fae553f3316d733276f09a6b1"}, - {file = "playwright-1.48.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:7da2eb51a19c7f3b523e9faa9d98e7af92e52eb983a099979ea79c9668e3cbf7"}, - {file = "playwright-1.48.0-py3-none-macosx_11_0_universal2.whl", hash = "sha256:115b988d1da322358b77bc3bf2d3cc90f8c881e691461538e7df91614c4833c9"}, - {file = "playwright-1.48.0-py3-none-manylinux1_x86_64.whl", hash = "sha256:8dabb80e62f667fe2640a8b694e26a7b884c0b4803f7514a3954fc849126227b"}, - {file = "playwright-1.48.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8ff8303409ebed76bed4c3d655340320b768817d900ba208b394fdd7d7939a5c"}, - {file = "playwright-1.48.0-py3-none-win32.whl", hash = "sha256:85598c360c590076d4f435525be991246d74a905b654ac19d26eab7ed9b98b2d"}, - {file = "playwright-1.48.0-py3-none-win_amd64.whl", hash = "sha256:e0e87b0c4dc8fce83c725dd851aec37bc4e882bb225ec8a96bd83cf32d4f1623"}, + {file = "playwright-1.49.0-py3-none-macosx_10_13_x86_64.whl", hash = "sha256:704532a2d8ba580ec9e1895bfeafddce2e3d52320d4eb8aa38e80376acc5cbb0"}, + {file = "playwright-1.49.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:e453f02c4e5cc2db7e9759c47e7425f32e50ac76c76b7eb17c69eed72f01c4d8"}, + {file = "playwright-1.49.0-py3-none-macosx_11_0_universal2.whl", hash = "sha256:37ae985309184472946a6eb1a237e5d93c9e58a781fa73b75c8751325002a5d4"}, + {file = "playwright-1.49.0-py3-none-manylinux1_x86_64.whl", hash = "sha256:68d94beffb3c9213e3ceaafa66171affd9a5d9162e0c8a3eed1b1132c2e57598"}, + {file = "playwright-1.49.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f12d2aecdb41fc25a624cb15f3e8391c252ebd81985e3d5c1c261fe93779345"}, + {file = "playwright-1.49.0-py3-none-win32.whl", hash = "sha256:91103de52d470594ad375b512d7143fa95d6039111ae11a93eb4fe2f2b4a4858"}, + {file = "playwright-1.49.0-py3-none-win_amd64.whl", hash = "sha256:34d28a2c2d46403368610be4339898dc9c34eb9f7c578207b4715c49743a072a"}, ] [package.dependencies] @@ -2865,13 +2942,13 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "prometheus-client" -version = "0.21.0" +version = "0.21.1" description = "Python client for the Prometheus monitoring system." optional = false python-versions = ">=3.8" files = [ - {file = "prometheus_client-0.21.0-py3-none-any.whl", hash = "sha256:4fa6b4dd0ac16d58bb587c04b1caae65b8c5043e85f778f42f5f632f6af2e166"}, - {file = "prometheus_client-0.21.0.tar.gz", hash = "sha256:96c83c606b71ff2b0a433c98889d275f51ffec6c5e267de37c7a2b5c9aa9233e"}, + {file = "prometheus_client-0.21.1-py3-none-any.whl", hash = "sha256:594b45c410d6f4f8888940fe80b5cc2521b305a1fafe1c58609ef715a001f301"}, + {file = "prometheus_client-0.21.1.tar.gz", hash = "sha256:252505a722ac04b0456be05c05f75f45d760c2911ffc45f2a06bcaed9f3ae3fb"}, ] [package.extras] @@ -2893,129 +2970,113 @@ wcwidth = "*" [[package]] name = "propcache" -version = "0.2.0" +version = "0.2.1" description = "Accelerated property cache" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "propcache-0.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c5869b8fd70b81835a6f187c5fdbe67917a04d7e52b6e7cc4e5fe39d55c39d58"}, - {file = "propcache-0.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:952e0d9d07609d9c5be361f33b0d6d650cd2bae393aabb11d9b719364521984b"}, - {file = "propcache-0.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:33ac8f098df0585c0b53009f039dfd913b38c1d2edafed0cedcc0c32a05aa110"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:97e48e8875e6c13909c800fa344cd54cc4b2b0db1d5f911f840458a500fde2c2"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:388f3217649d6d59292b722d940d4d2e1e6a7003259eb835724092a1cca0203a"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f571aea50ba5623c308aa146eb650eebf7dbe0fd8c5d946e28343cb3b5aad577"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3dfafb44f7bb35c0c06eda6b2ab4bfd58f02729e7c4045e179f9a861b07c9850"}, - {file = "propcache-0.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a3ebe9a75be7ab0b7da2464a77bb27febcb4fab46a34f9288f39d74833db7f61"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d2f0d0f976985f85dfb5f3d685697ef769faa6b71993b46b295cdbbd6be8cc37"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a3dc1a4b165283bd865e8f8cb5f0c64c05001e0718ed06250d8cac9bec115b48"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9e0f07b42d2a50c7dd2d8675d50f7343d998c64008f1da5fef888396b7f84630"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e63e3e1e0271f374ed489ff5ee73d4b6e7c60710e1f76af5f0e1a6117cd26394"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:56bb5c98f058a41bb58eead194b4db8c05b088c93d94d5161728515bd52b052b"}, - {file = "propcache-0.2.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7665f04d0c7f26ff8bb534e1c65068409bf4687aa2534faf7104d7182debb336"}, - {file = "propcache-0.2.0-cp310-cp310-win32.whl", hash = "sha256:7cf18abf9764746b9c8704774d8b06714bcb0a63641518a3a89c7f85cc02c2ad"}, - {file = "propcache-0.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:cfac69017ef97db2438efb854edf24f5a29fd09a536ff3a992b75990720cdc99"}, - {file = "propcache-0.2.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:63f13bf09cc3336eb04a837490b8f332e0db41da66995c9fd1ba04552e516354"}, - {file = "propcache-0.2.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:608cce1da6f2672a56b24a015b42db4ac612ee709f3d29f27a00c943d9e851de"}, - {file = "propcache-0.2.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:466c219deee4536fbc83c08d09115249db301550625c7fef1c5563a584c9bc87"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fc2db02409338bf36590aa985a461b2c96fce91f8e7e0f14c50c5fcc4f229016"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a6ed8db0a556343d566a5c124ee483ae113acc9a557a807d439bcecc44e7dfbb"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:91997d9cb4a325b60d4e3f20967f8eb08dfcb32b22554d5ef78e6fd1dda743a2"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c7dde9e533c0a49d802b4f3f218fa9ad0a1ce21f2c2eb80d5216565202acab4"}, - {file = "propcache-0.2.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ffcad6c564fe6b9b8916c1aefbb37a362deebf9394bd2974e9d84232e3e08504"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:97a58a28bcf63284e8b4d7b460cbee1edaab24634e82059c7b8c09e65284f178"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:945db8ee295d3af9dbdbb698cce9bbc5c59b5c3fe328bbc4387f59a8a35f998d"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:39e104da444a34830751715f45ef9fc537475ba21b7f1f5b0f4d71a3b60d7fe2"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:c5ecca8f9bab618340c8e848d340baf68bcd8ad90a8ecd7a4524a81c1764b3db"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:c436130cc779806bdf5d5fae0d848713105472b8566b75ff70048c47d3961c5b"}, - {file = "propcache-0.2.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:191db28dc6dcd29d1a3e063c3be0b40688ed76434622c53a284e5427565bbd9b"}, - {file = "propcache-0.2.0-cp311-cp311-win32.whl", hash = "sha256:5f2564ec89058ee7c7989a7b719115bdfe2a2fb8e7a4543b8d1c0cc4cf6478c1"}, - {file = "propcache-0.2.0-cp311-cp311-win_amd64.whl", hash = "sha256:6e2e54267980349b723cff366d1e29b138b9a60fa376664a157a342689553f71"}, - {file = "propcache-0.2.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:2ee7606193fb267be4b2e3b32714f2d58cad27217638db98a60f9efb5efeccc2"}, - {file = "propcache-0.2.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:91ee8fc02ca52e24bcb77b234f22afc03288e1dafbb1f88fe24db308910c4ac7"}, - {file = "propcache-0.2.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2e900bad2a8456d00a113cad8c13343f3b1f327534e3589acc2219729237a2e8"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f52a68c21363c45297aca15561812d542f8fc683c85201df0bebe209e349f793"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1e41d67757ff4fbc8ef2af99b338bfb955010444b92929e9e55a6d4dcc3c4f09"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a64e32f8bd94c105cc27f42d3b658902b5bcc947ece3c8fe7bc1b05982f60e89"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:55346705687dbd7ef0d77883ab4f6fabc48232f587925bdaf95219bae072491e"}, - {file = "propcache-0.2.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:00181262b17e517df2cd85656fcd6b4e70946fe62cd625b9d74ac9977b64d8d9"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6994984550eaf25dd7fc7bd1b700ff45c894149341725bb4edc67f0ffa94efa4"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:56295eb1e5f3aecd516d91b00cfd8bf3a13991de5a479df9e27dd569ea23959c"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:439e76255daa0f8151d3cb325f6dd4a3e93043e6403e6491813bcaaaa8733887"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f6475a1b2ecb310c98c28d271a30df74f9dd436ee46d09236a6b750a7599ce57"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:3444cdba6628accf384e349014084b1cacd866fbb88433cd9d279d90a54e0b23"}, - {file = "propcache-0.2.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4a9d9b4d0a9b38d1c391bb4ad24aa65f306c6f01b512e10a8a34a2dc5675d348"}, - {file = "propcache-0.2.0-cp312-cp312-win32.whl", hash = "sha256:69d3a98eebae99a420d4b28756c8ce6ea5a29291baf2dc9ff9414b42676f61d5"}, - {file = "propcache-0.2.0-cp312-cp312-win_amd64.whl", hash = "sha256:ad9c9b99b05f163109466638bd30ada1722abb01bbb85c739c50b6dc11f92dc3"}, - {file = "propcache-0.2.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ecddc221a077a8132cf7c747d5352a15ed763b674c0448d811f408bf803d9ad7"}, - {file = "propcache-0.2.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0e53cb83fdd61cbd67202735e6a6687a7b491c8742dfc39c9e01e80354956763"}, - {file = "propcache-0.2.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:92fe151145a990c22cbccf9ae15cae8ae9eddabfc949a219c9f667877e40853d"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d6a21ef516d36909931a2967621eecb256018aeb11fc48656e3257e73e2e247a"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3f88a4095e913f98988f5b338c1d4d5d07dbb0b6bad19892fd447484e483ba6b"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5a5b3bb545ead161be780ee85a2b54fdf7092815995661947812dde94a40f6fb"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:67aeb72e0f482709991aa91345a831d0b707d16b0257e8ef88a2ad246a7280bf"}, - {file = "propcache-0.2.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3c997f8c44ec9b9b0bcbf2d422cc00a1d9b9c681f56efa6ca149a941e5560da2"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:2a66df3d4992bc1d725b9aa803e8c5a66c010c65c741ad901e260ece77f58d2f"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3ebbcf2a07621f29638799828b8d8668c421bfb94c6cb04269130d8de4fb7136"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1235c01ddaa80da8235741e80815ce381c5267f96cc49b1477fdcf8c047ef325"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:3947483a381259c06921612550867b37d22e1df6d6d7e8361264b6d037595f44"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:d5bed7f9805cc29c780f3aee05de3262ee7ce1f47083cfe9f77471e9d6777e83"}, - {file = "propcache-0.2.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e4a91d44379f45f5e540971d41e4626dacd7f01004826a18cb048e7da7e96544"}, - {file = "propcache-0.2.0-cp313-cp313-win32.whl", hash = "sha256:f902804113e032e2cdf8c71015651c97af6418363bea8d78dc0911d56c335032"}, - {file = "propcache-0.2.0-cp313-cp313-win_amd64.whl", hash = "sha256:8f188cfcc64fb1266f4684206c9de0e80f54622c3f22a910cbd200478aeae61e"}, - {file = "propcache-0.2.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:53d1bd3f979ed529f0805dd35ddaca330f80a9a6d90bc0121d2ff398f8ed8861"}, - {file = "propcache-0.2.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:83928404adf8fb3d26793665633ea79b7361efa0287dfbd372a7e74311d51ee6"}, - {file = "propcache-0.2.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:77a86c261679ea5f3896ec060be9dc8e365788248cc1e049632a1be682442063"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:218db2a3c297a3768c11a34812e63b3ac1c3234c3a086def9c0fee50d35add1f"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7735e82e3498c27bcb2d17cb65d62c14f1100b71723b68362872bca7d0913d90"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:20a617c776f520c3875cf4511e0d1db847a076d720714ae35ffe0df3e440be68"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:67b69535c870670c9f9b14a75d28baa32221d06f6b6fa6f77a0a13c5a7b0a5b9"}, - {file = "propcache-0.2.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4569158070180c3855e9c0791c56be3ceeb192defa2cdf6a3f39e54319e56b89"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:db47514ffdbd91ccdc7e6f8407aac4ee94cc871b15b577c1c324236b013ddd04"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:2a60ad3e2553a74168d275a0ef35e8c0a965448ffbc3b300ab3a5bb9956c2162"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:662dd62358bdeaca0aee5761de8727cfd6861432e3bb828dc2a693aa0471a563"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:25a1f88b471b3bc911d18b935ecb7115dff3a192b6fef46f0bfaf71ff4f12418"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:f60f0ac7005b9f5a6091009b09a419ace1610e163fa5deaba5ce3484341840e7"}, - {file = "propcache-0.2.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:74acd6e291f885678631b7ebc85d2d4aec458dd849b8c841b57ef04047833bed"}, - {file = "propcache-0.2.0-cp38-cp38-win32.whl", hash = "sha256:d9b6ddac6408194e934002a69bcaadbc88c10b5f38fb9307779d1c629181815d"}, - {file = "propcache-0.2.0-cp38-cp38-win_amd64.whl", hash = "sha256:676135dcf3262c9c5081cc8f19ad55c8a64e3f7282a21266d05544450bffc3a5"}, - {file = "propcache-0.2.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:25c8d773a62ce0451b020c7b29a35cfbc05de8b291163a7a0f3b7904f27253e6"}, - {file = "propcache-0.2.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:375a12d7556d462dc64d70475a9ee5982465fbb3d2b364f16b86ba9135793638"}, - {file = "propcache-0.2.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1ec43d76b9677637a89d6ab86e1fef70d739217fefa208c65352ecf0282be957"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f45eec587dafd4b2d41ac189c2156461ebd0c1082d2fe7013571598abb8505d1"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bc092ba439d91df90aea38168e11f75c655880c12782facf5cf9c00f3d42b562"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fa1076244f54bb76e65e22cb6910365779d5c3d71d1f18b275f1dfc7b0d71b4d"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:682a7c79a2fbf40f5dbb1eb6bfe2cd865376deeac65acf9beb607505dced9e12"}, - {file = "propcache-0.2.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8e40876731f99b6f3c897b66b803c9e1c07a989b366c6b5b475fafd1f7ba3fb8"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:363ea8cd3c5cb6679f1c2f5f1f9669587361c062e4899fce56758efa928728f8"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:140fbf08ab3588b3468932974a9331aff43c0ab8a2ec2c608b6d7d1756dbb6cb"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:e70fac33e8b4ac63dfc4c956fd7d85a0b1139adcfc0d964ce288b7c527537fea"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:b33d7a286c0dc1a15f5fc864cc48ae92a846df287ceac2dd499926c3801054a6"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:f6d5749fdd33d90e34c2efb174c7e236829147a2713334d708746e94c4bde40d"}, - {file = "propcache-0.2.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:22aa8f2272d81d9317ff5756bb108021a056805ce63dd3630e27d042c8092798"}, - {file = "propcache-0.2.0-cp39-cp39-win32.whl", hash = "sha256:73e4b40ea0eda421b115248d7e79b59214411109a5bc47d0d48e4c73e3b8fcf9"}, - {file = "propcache-0.2.0-cp39-cp39-win_amd64.whl", hash = "sha256:9517d5e9e0731957468c29dbfd0f976736a0e55afaea843726e887f36fe017df"}, - {file = "propcache-0.2.0-py3-none-any.whl", hash = "sha256:2ccc28197af5313706511fab3a8b66dcd6da067a1331372c82ea1cb74285e036"}, - {file = "propcache-0.2.0.tar.gz", hash = "sha256:df81779732feb9d01e5d513fad0122efb3d53bbc75f61b2a4f29a020bc985e70"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6b3f39a85d671436ee3d12c017f8fdea38509e4f25b28eb25877293c98c243f6"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d51fbe4285d5db5d92a929e3e21536ea3dd43732c5b177c7ef03f918dff9f2"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6445804cf4ec763dc70de65a3b0d9954e868609e83850a47ca4f0cb64bd79fea"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f9479aa06a793c5aeba49ce5c5692ffb51fcd9a7016e017d555d5e2b0045d212"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9631c5e8b5b3a0fda99cb0d29c18133bca1e18aea9effe55adb3da1adef80d3"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3156628250f46a0895f1f36e1d4fbe062a1af8718ec3ebeb746f1d23f0c5dc4d"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b6fb63ae352e13748289f04f37868099e69dba4c2b3e271c46061e82c745634"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:887d9b0a65404929641a9fabb6452b07fe4572b269d901d622d8a34a4e9043b2"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:a96dc1fa45bd8c407a0af03b2d5218392729e1822b0c32e62c5bf7eeb5fb3958"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a7e65eb5c003a303b94aa2c3852ef130230ec79e349632d030e9571b87c4698c"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:999779addc413181912e984b942fbcc951be1f5b3663cd80b2687758f434c583"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:19a0f89a7bb9d8048d9c4370c9c543c396e894c76be5525f5e1ad287f1750ddf"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:1ac2f5fe02fa75f56e1ad473f1175e11f475606ec9bd0be2e78e4734ad575034"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:574faa3b79e8ebac7cb1d7930f51184ba1ccf69adfdec53a12f319a06030a68b"}, + {file = "propcache-0.2.1-cp310-cp310-win32.whl", hash = "sha256:03ff9d3f665769b2a85e6157ac8b439644f2d7fd17615a82fa55739bc97863f4"}, + {file = "propcache-0.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:2d3af2e79991102678f53e0dbf4c35de99b6b8b58f29a27ca0325816364caaba"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ffc3cca89bb438fb9c95c13fc874012f7b9466b89328c3c8b1aa93cdcfadd16"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f174bbd484294ed9fdf09437f889f95807e5f229d5d93588d34e92106fbf6717"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:70693319e0b8fd35dd863e3e29513875eb15c51945bf32519ef52927ca883bc3"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b480c6a4e1138e1aa137c0079b9b6305ec6dcc1098a8ca5196283e8a49df95a9"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d27b84d5880f6d8aa9ae3edb253c59d9f6642ffbb2c889b78b60361eed449787"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:857112b22acd417c40fa4595db2fe28ab900c8c5fe4670c7989b1c0230955465"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf6c4150f8c0e32d241436526f3c3f9cbd34429492abddbada2ffcff506c51af"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66d4cfda1d8ed687daa4bc0274fcfd5267873db9a5bc0418c2da19273040eeb7"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c2f992c07c0fca81655066705beae35fc95a2fa7366467366db627d9f2ee097f"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:4a571d97dbe66ef38e472703067021b1467025ec85707d57e78711c085984e54"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:bb6178c241278d5fe853b3de743087be7f5f4c6f7d6d22a3b524d323eecec505"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:ad1af54a62ffe39cf34db1aa6ed1a1873bd548f6401db39d8e7cd060b9211f82"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e7048abd75fe40712005bcfc06bb44b9dfcd8e101dda2ecf2f5aa46115ad07ca"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:160291c60081f23ee43d44b08a7e5fb76681221a8e10b3139618c5a9a291b84e"}, + {file = "propcache-0.2.1-cp311-cp311-win32.whl", hash = "sha256:819ce3b883b7576ca28da3861c7e1a88afd08cc8c96908e08a3f4dd64a228034"}, + {file = "propcache-0.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:edc9fc7051e3350643ad929df55c451899bb9ae6d24998a949d2e4c87fb596d3"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:081a430aa8d5e8876c6909b67bd2d937bfd531b0382d3fdedb82612c618bc41a"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d2ccec9ac47cf4e04897619c0e0c1a48c54a71bdf045117d3a26f80d38ab1fb0"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:14d86fe14b7e04fa306e0c43cdbeebe6b2c2156a0c9ce56b815faacc193e320d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:049324ee97bb67285b49632132db351b41e77833678432be52bdd0289c0e05e4"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1cd9a1d071158de1cc1c71a26014dcdfa7dd3d5f4f88c298c7f90ad6f27bb46d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:98110aa363f1bb4c073e8dcfaefd3a5cea0f0834c2aab23dda657e4dab2f53b5"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:647894f5ae99c4cf6bb82a1bb3a796f6e06af3caa3d32e26d2350d0e3e3faf24"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bfd3223c15bebe26518d58ccf9a39b93948d3dcb3e57a20480dfdd315356baff"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d71264a80f3fcf512eb4f18f59423fe82d6e346ee97b90625f283df56aee103f"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:e73091191e4280403bde6c9a52a6999d69cdfde498f1fdf629105247599b57ec"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:3935bfa5fede35fb202c4b569bb9c042f337ca4ff7bd540a0aa5e37131659348"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f508b0491767bb1f2b87fdfacaba5f7eddc2f867740ec69ece6d1946d29029a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1672137af7c46662a1c2be1e8dc78cb6d224319aaa40271c9257d886be4363a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b74c261802d3d2b85c9df2dfb2fa81b6f90deeef63c2db9f0e029a3cac50b518"}, + {file = "propcache-0.2.1-cp312-cp312-win32.whl", hash = "sha256:d09c333d36c1409d56a9d29b3a1b800a42c76a57a5a8907eacdbce3f18768246"}, + {file = "propcache-0.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:c214999039d4f2a5b2073ac506bba279945233da8c786e490d411dfc30f855c1"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:aca405706e0b0a44cc6bfd41fbe89919a6a56999157f6de7e182a990c36e37bc"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:12d1083f001ace206fe34b6bdc2cb94be66d57a850866f0b908972f90996b3e9"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d93f3307ad32a27bda2e88ec81134b823c240aa3abb55821a8da553eed8d9439"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba278acf14471d36316159c94a802933d10b6a1e117b8554fe0d0d9b75c9d536"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4e6281aedfca15301c41f74d7005e6e3f4ca143584ba696ac69df4f02f40d629"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b750a8e5a1262434fb1517ddf64b5de58327f1adc3524a5e44c2ca43305eb0b"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf72af5e0fb40e9babf594308911436c8efde3cb5e75b6f206c34ad18be5c052"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b2d0a12018b04f4cb820781ec0dffb5f7c7c1d2a5cd22bff7fb055a2cb19ebce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e800776a79a5aabdb17dcc2346a7d66d0777e942e4cd251defeb084762ecd17d"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:4160d9283bd382fa6c0c2b5e017acc95bc183570cd70968b9202ad6d8fc48dce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:30b43e74f1359353341a7adb783c8f1b1c676367b011709f466f42fda2045e95"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:58791550b27d5488b1bb52bc96328456095d96206a250d28d874fafe11b3dfaf"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:0f022d381747f0dfe27e99d928e31bc51a18b65bb9e481ae0af1380a6725dd1f"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:297878dc9d0a334358f9b608b56d02e72899f3b8499fc6044133f0d319e2ec30"}, + {file = "propcache-0.2.1-cp313-cp313-win32.whl", hash = "sha256:ddfab44e4489bd79bda09d84c430677fc7f0a4939a73d2bba3073036f487a0a6"}, + {file = "propcache-0.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:556fc6c10989f19a179e4321e5d678db8eb2924131e64652a51fe83e4c3db0e1"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:6a9a8c34fb7bb609419a211e59da8887eeca40d300b5ea8e56af98f6fbbb1541"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ae1aa1cd222c6d205853b3013c69cd04515f9d6ab6de4b0603e2e1c33221303e"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:accb6150ce61c9c4b7738d45550806aa2b71c7668c6942f17b0ac182b6142fd4"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5eee736daafa7af6d0a2dc15cc75e05c64f37fc37bafef2e00d77c14171c2097"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f7a31fc1e1bd362874863fdeed71aed92d348f5336fd84f2197ba40c59f061bd"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cba4cfa1052819d16699e1d55d18c92b6e094d4517c41dd231a8b9f87b6fa681"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f089118d584e859c62b3da0892b88a83d611c2033ac410e929cb6754eec0ed16"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:781e65134efaf88feb447e8c97a51772aa75e48b794352f94cb7ea717dedda0d"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:31f5af773530fd3c658b32b6bdc2d0838543de70eb9a2156c03e410f7b0d3aae"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:a7a078f5d37bee6690959c813977da5291b24286e7b962e62a94cec31aa5188b"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:cea7daf9fc7ae6687cf1e2c049752f19f146fdc37c2cc376e7d0032cf4f25347"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:8b3489ff1ed1e8315674d0775dc7d2195fb13ca17b3808721b54dbe9fd020faf"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9403db39be1393618dd80c746cb22ccda168efce239c73af13c3763ef56ffc04"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5d97151bc92d2b2578ff7ce779cdb9174337390a535953cbb9452fb65164c587"}, + {file = "propcache-0.2.1-cp39-cp39-win32.whl", hash = "sha256:9caac6b54914bdf41bcc91e7eb9147d331d29235a7c967c150ef5df6464fd1bb"}, + {file = "propcache-0.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:92fc4500fcb33899b05ba73276dfb684a20d31caa567b7cb5252d48f896a91b1"}, + {file = "propcache-0.2.1-py3-none-any.whl", hash = "sha256:52277518d6aae65536e9cea52d4e7fd2f7a66f4aa2d30ed3f2fcea620ace3c54"}, + {file = "propcache-0.2.1.tar.gz", hash = "sha256:3f77ce728b19cb537714499928fe800c3dda29e8d9428778fc7c186da4c09a64"}, ] [[package]] name = "protobuf" -version = "5.28.3" +version = "5.29.1" description = "" optional = false python-versions = ">=3.8" files = [ - {file = "protobuf-5.28.3-cp310-abi3-win32.whl", hash = "sha256:0c4eec6f987338617072592b97943fdbe30d019c56126493111cf24344c1cc24"}, - {file = "protobuf-5.28.3-cp310-abi3-win_amd64.whl", hash = "sha256:91fba8f445723fcf400fdbe9ca796b19d3b1242cd873907979b9ed71e4afe868"}, - {file = "protobuf-5.28.3-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:a3f6857551e53ce35e60b403b8a27b0295f7d6eb63d10484f12bc6879c715687"}, - {file = "protobuf-5.28.3-cp38-abi3-manylinux2014_aarch64.whl", hash = "sha256:3fa2de6b8b29d12c61911505d893afe7320ce7ccba4df913e2971461fa36d584"}, - {file = "protobuf-5.28.3-cp38-abi3-manylinux2014_x86_64.whl", hash = "sha256:712319fbdddb46f21abb66cd33cb9e491a5763b2febd8f228251add221981135"}, - {file = "protobuf-5.28.3-cp38-cp38-win32.whl", hash = "sha256:3e6101d095dfd119513cde7259aa703d16c6bbdfae2554dfe5cfdbe94e32d548"}, - {file = "protobuf-5.28.3-cp38-cp38-win_amd64.whl", hash = "sha256:27b246b3723692bf1068d5734ddaf2fccc2cdd6e0c9b47fe099244d80200593b"}, - {file = "protobuf-5.28.3-cp39-cp39-win32.whl", hash = "sha256:135658402f71bbd49500322c0f736145731b16fc79dc8f367ab544a17eab4535"}, - {file = "protobuf-5.28.3-cp39-cp39-win_amd64.whl", hash = "sha256:70585a70fc2dd4818c51287ceef5bdba6387f88a578c86d47bb34669b5552c36"}, - {file = "protobuf-5.28.3-py3-none-any.whl", hash = "sha256:cee1757663fa32a1ee673434fcf3bf24dd54763c79690201208bafec62f19eed"}, - {file = "protobuf-5.28.3.tar.gz", hash = "sha256:64badbc49180a5e401f373f9ce7ab1d18b63f7dd4a9cdc43c92b9f0b481cef7b"}, + {file = "protobuf-5.29.1-cp310-abi3-win32.whl", hash = "sha256:22c1f539024241ee545cbcb00ee160ad1877975690b16656ff87dde107b5f110"}, + {file = "protobuf-5.29.1-cp310-abi3-win_amd64.whl", hash = "sha256:1fc55267f086dd4050d18ef839d7bd69300d0d08c2a53ca7df3920cc271a3c34"}, + {file = "protobuf-5.29.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:d473655e29c0c4bbf8b69e9a8fb54645bc289dead6d753b952e7aa660254ae18"}, + {file = "protobuf-5.29.1-cp38-abi3-manylinux2014_aarch64.whl", hash = "sha256:b5ba1d0e4c8a40ae0496d0e2ecfdbb82e1776928a205106d14ad6985a09ec155"}, + {file = "protobuf-5.29.1-cp38-abi3-manylinux2014_x86_64.whl", hash = "sha256:8ee1461b3af56145aca2800e6a3e2f928108c749ba8feccc6f5dd0062c410c0d"}, + {file = "protobuf-5.29.1-cp38-cp38-win32.whl", hash = "sha256:50879eb0eb1246e3a5eabbbe566b44b10348939b7cc1b267567e8c3d07213853"}, + {file = "protobuf-5.29.1-cp38-cp38-win_amd64.whl", hash = "sha256:027fbcc48cea65a6b17028510fdd054147057fa78f4772eb547b9274e5219331"}, + {file = "protobuf-5.29.1-cp39-cp39-win32.whl", hash = "sha256:5a41deccfa5e745cef5c65a560c76ec0ed8e70908a67cc8f4da5fce588b50d57"}, + {file = "protobuf-5.29.1-cp39-cp39-win_amd64.whl", hash = "sha256:012ce28d862ff417fd629285aca5d9772807f15ceb1a0dbd15b88f58c776c98c"}, + {file = "protobuf-5.29.1-py3-none-any.whl", hash = "sha256:32600ddb9c2a53dedc25b8581ea0f1fd8ea04956373c0c07577ce58d312522e0"}, + {file = "protobuf-5.29.1.tar.gz", hash = "sha256:683be02ca21a6ffe80db6dd02c0b5b2892322c59ca57fd6c872d652cb80549cb"}, ] [[package]] @@ -3086,22 +3147,19 @@ files = [ [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.3" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.3-py3-none-any.whl", hash = "sha256:be04d85bbc7b65651c5f8e6b9976ed9c6f41782a55524cef079a34a0bb82144d"}, + {file = "pydantic-2.10.3.tar.gz", hash = "sha256:cb5ac360ce894ceacd69c403187900a02c4b20b693a9dd1d643e1effab9eadf9"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -3109,100 +3167,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -3241,13 +3310,13 @@ windows-terminal = ["colorama (>=0.4.6)"] [[package]] name = "pytest" -version = "8.3.3" +version = "8.3.4" description = "pytest: simple powerful testing with Python" optional = false python-versions = ">=3.8" files = [ - {file = "pytest-8.3.3-py3-none-any.whl", hash = "sha256:a6853c7375b2663155079443d2e45de913a911a11d669df02a50814944db57b2"}, - {file = "pytest-8.3.3.tar.gz", hash = "sha256:70b98107bd648308a7952b06e6ca9a50bc660be218d53c257cc1fc94fda10181"}, + {file = "pytest-8.3.4-py3-none-any.whl", hash = "sha256:50e16d954148559c9a74109af1eaf0c945ba2d8f30f0a3d3335edde19788b6f6"}, + {file = "pytest-8.3.4.tar.gz", hash = "sha256:965370d062bce11e73868e0335abac31b4d3de0e82f4007408d242b4f8610761"}, ] [package.dependencies] @@ -3664,105 +3733,105 @@ rpds-py = ">=0.7.0" [[package]] name = "regex" -version = "2024.9.11" +version = "2024.11.6" description = "Alternative regular expression module, to replace re." optional = true python-versions = ">=3.8" files = [ - {file = "regex-2024.9.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1494fa8725c285a81d01dc8c06b55287a1ee5e0e382d8413adc0a9197aac6408"}, - {file = "regex-2024.9.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0e12c481ad92d129c78f13a2a3662317e46ee7ef96c94fd332e1c29131875b7d"}, - {file = "regex-2024.9.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:16e13a7929791ac1216afde26f712802e3df7bf0360b32e4914dca3ab8baeea5"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:46989629904bad940bbec2106528140a218b4a36bb3042d8406980be1941429c"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a906ed5e47a0ce5f04b2c981af1c9acf9e8696066900bf03b9d7879a6f679fc8"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e9a091b0550b3b0207784a7d6d0f1a00d1d1c8a11699c1a4d93db3fbefc3ad35"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ddcd9a179c0a6fa8add279a4444015acddcd7f232a49071ae57fa6e278f1f71"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6b41e1adc61fa347662b09398e31ad446afadff932a24807d3ceb955ed865cc8"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ced479f601cd2f8ca1fd7b23925a7e0ad512a56d6e9476f79b8f381d9d37090a"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:635a1d96665f84b292e401c3d62775851aedc31d4f8784117b3c68c4fcd4118d"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:c0256beda696edcf7d97ef16b2a33a8e5a875affd6fa6567b54f7c577b30a137"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:3ce4f1185db3fbde8ed8aa223fc9620f276c58de8b0d4f8cc86fd1360829edb6"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:09d77559e80dcc9d24570da3745ab859a9cf91953062e4ab126ba9d5993688ca"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a22ccefd4db3f12b526eccb129390942fe874a3a9fdbdd24cf55773a1faab1a"}, - {file = "regex-2024.9.11-cp310-cp310-win32.whl", hash = "sha256:f745ec09bc1b0bd15cfc73df6fa4f726dcc26bb16c23a03f9e3367d357eeedd0"}, - {file = "regex-2024.9.11-cp310-cp310-win_amd64.whl", hash = "sha256:01c2acb51f8a7d6494c8c5eafe3d8e06d76563d8a8a4643b37e9b2dd8a2ff623"}, - {file = "regex-2024.9.11-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:2cce2449e5927a0bf084d346da6cd5eb016b2beca10d0013ab50e3c226ffc0df"}, - {file = "regex-2024.9.11-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3b37fa423beefa44919e009745ccbf353d8c981516e807995b2bd11c2c77d268"}, - {file = "regex-2024.9.11-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:64ce2799bd75039b480cc0360907c4fb2f50022f030bf9e7a8705b636e408fad"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a4cc92bb6db56ab0c1cbd17294e14f5e9224f0cc6521167ef388332604e92679"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d05ac6fa06959c4172eccd99a222e1fbf17b5670c4d596cb1e5cde99600674c4"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:040562757795eeea356394a7fb13076ad4f99d3c62ab0f8bdfb21f99a1f85664"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6113c008a7780792efc80f9dfe10ba0cd043cbf8dc9a76ef757850f51b4edc50"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8e5fb5f77c8745a60105403a774fe2c1759b71d3e7b4ca237a5e67ad066c7199"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:54d9ff35d4515debf14bc27f1e3b38bfc453eff3220f5bce159642fa762fe5d4"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:df5cbb1fbc74a8305b6065d4ade43b993be03dbe0f8b30032cced0d7740994bd"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:7fb89ee5d106e4a7a51bce305ac4efb981536301895f7bdcf93ec92ae0d91c7f"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:a738b937d512b30bf75995c0159c0ddf9eec0775c9d72ac0202076c72f24aa96"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e28f9faeb14b6f23ac55bfbbfd3643f5c7c18ede093977f1df249f73fd22c7b1"}, - {file = "regex-2024.9.11-cp311-cp311-win32.whl", hash = "sha256:18e707ce6c92d7282dfce370cd205098384b8ee21544e7cb29b8aab955b66fa9"}, - {file = "regex-2024.9.11-cp311-cp311-win_amd64.whl", hash = "sha256:313ea15e5ff2a8cbbad96ccef6be638393041b0a7863183c2d31e0c6116688cf"}, - {file = "regex-2024.9.11-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:b0d0a6c64fcc4ef9c69bd5b3b3626cc3776520a1637d8abaa62b9edc147a58f7"}, - {file = "regex-2024.9.11-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:49b0e06786ea663f933f3710a51e9385ce0cba0ea56b67107fd841a55d56a231"}, - {file = "regex-2024.9.11-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5b513b6997a0b2f10e4fd3a1313568e373926e8c252bd76c960f96fd039cd28d"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ee439691d8c23e76f9802c42a95cfeebf9d47cf4ffd06f18489122dbb0a7ad64"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a8f877c89719d759e52783f7fe6e1c67121076b87b40542966c02de5503ace42"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23b30c62d0f16827f2ae9f2bb87619bc4fba2044911e2e6c2eb1af0161cdb766"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:85ab7824093d8f10d44330fe1e6493f756f252d145323dd17ab6b48733ff6c0a"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8dee5b4810a89447151999428fe096977346cf2f29f4d5e29609d2e19e0199c9"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:98eeee2f2e63edae2181c886d7911ce502e1292794f4c5ee71e60e23e8d26b5d"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:57fdd2e0b2694ce6fc2e5ccf189789c3e2962916fb38779d3e3521ff8fe7a822"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:d552c78411f60b1fdaafd117a1fca2f02e562e309223b9d44b7de8be451ec5e0"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a0b2b80321c2ed3fcf0385ec9e51a12253c50f146fddb2abbb10f033fe3d049a"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:18406efb2f5a0e57e3a5881cd9354c1512d3bb4f5c45d96d110a66114d84d23a"}, - {file = "regex-2024.9.11-cp312-cp312-win32.whl", hash = "sha256:e464b467f1588e2c42d26814231edecbcfe77f5ac414d92cbf4e7b55b2c2a776"}, - {file = "regex-2024.9.11-cp312-cp312-win_amd64.whl", hash = "sha256:9e8719792ca63c6b8340380352c24dcb8cd7ec49dae36e963742a275dfae6009"}, - {file = "regex-2024.9.11-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:c157bb447303070f256e084668b702073db99bbb61d44f85d811025fcf38f784"}, - {file = "regex-2024.9.11-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:4db21ece84dfeefc5d8a3863f101995de646c6cb0536952c321a2650aa202c36"}, - {file = "regex-2024.9.11-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:220e92a30b426daf23bb67a7962900ed4613589bab80382be09b48896d211e92"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eb1ae19e64c14c7ec1995f40bd932448713d3c73509e82d8cd7744dc00e29e86"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f47cd43a5bfa48f86925fe26fbdd0a488ff15b62468abb5d2a1e092a4fb10e85"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9d4a76b96f398697fe01117093613166e6aa8195d63f1b4ec3f21ab637632963"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0ea51dcc0835eea2ea31d66456210a4e01a076d820e9039b04ae8d17ac11dee6"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b7aaa315101c6567a9a45d2839322c51c8d6e81f67683d529512f5bcfb99c802"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c57d08ad67aba97af57a7263c2d9006d5c404d721c5f7542f077f109ec2a4a29"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f8404bf61298bb6f8224bb9176c1424548ee1181130818fcd2cbffddc768bed8"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:dd4490a33eb909ef5078ab20f5f000087afa2a4daa27b4c072ccb3cb3050ad84"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:eee9130eaad130649fd73e5cd92f60e55708952260ede70da64de420cdcad554"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6a2644a93da36c784e546de579ec1806bfd2763ef47babc1b03d765fe560c9f8"}, - {file = "regex-2024.9.11-cp313-cp313-win32.whl", hash = "sha256:e997fd30430c57138adc06bba4c7c2968fb13d101e57dd5bb9355bf8ce3fa7e8"}, - {file = "regex-2024.9.11-cp313-cp313-win_amd64.whl", hash = "sha256:042c55879cfeb21a8adacc84ea347721d3d83a159da6acdf1116859e2427c43f"}, - {file = "regex-2024.9.11-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:35f4a6f96aa6cb3f2f7247027b07b15a374f0d5b912c0001418d1d55024d5cb4"}, - {file = "regex-2024.9.11-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:55b96e7ce3a69a8449a66984c268062fbaa0d8ae437b285428e12797baefce7e"}, - {file = "regex-2024.9.11-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:cb130fccd1a37ed894824b8c046321540263013da72745d755f2d35114b81a60"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:323c1f04be6b2968944d730e5c2091c8c89767903ecaa135203eec4565ed2b2b"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:be1c8ed48c4c4065ecb19d882a0ce1afe0745dfad8ce48c49586b90a55f02366"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b5b029322e6e7b94fff16cd120ab35a253236a5f99a79fb04fda7ae71ca20ae8"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f6fff13ef6b5f29221d6904aa816c34701462956aa72a77f1f151a8ec4f56aeb"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:587d4af3979376652010e400accc30404e6c16b7df574048ab1f581af82065e4"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:079400a8269544b955ffa9e31f186f01d96829110a3bf79dc338e9910f794fca"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:f9268774428ec173654985ce55fc6caf4c6d11ade0f6f914d48ef4719eb05ebb"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:23f9985c8784e544d53fc2930fc1ac1a7319f5d5332d228437acc9f418f2f168"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:ae2941333154baff9838e88aa71c1d84f4438189ecc6021a12c7573728b5838e"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:e93f1c331ca8e86fe877a48ad64e77882c0c4da0097f2212873a69bbfea95d0c"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:846bc79ee753acf93aef4184c040d709940c9d001029ceb7b7a52747b80ed2dd"}, - {file = "regex-2024.9.11-cp38-cp38-win32.whl", hash = "sha256:c94bb0a9f1db10a1d16c00880bdebd5f9faf267273b8f5bd1878126e0fbde771"}, - {file = "regex-2024.9.11-cp38-cp38-win_amd64.whl", hash = "sha256:2b08fce89fbd45664d3df6ad93e554b6c16933ffa9d55cb7e01182baaf971508"}, - {file = "regex-2024.9.11-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:07f45f287469039ffc2c53caf6803cd506eb5f5f637f1d4acb37a738f71dd066"}, - {file = "regex-2024.9.11-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4838e24ee015101d9f901988001038f7f0d90dc0c3b115541a1365fb439add62"}, - {file = "regex-2024.9.11-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:6edd623bae6a737f10ce853ea076f56f507fd7726bee96a41ee3d68d347e4d16"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c69ada171c2d0e97a4b5aa78fbb835e0ffbb6b13fc5da968c09811346564f0d3"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:02087ea0a03b4af1ed6ebab2c54d7118127fee8d71b26398e8e4b05b78963199"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:69dee6a020693d12a3cf892aba4808fe168d2a4cef368eb9bf74f5398bfd4ee8"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:297f54910247508e6e5cae669f2bc308985c60540a4edd1c77203ef19bfa63ca"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ecea58b43a67b1b79805f1a0255730edaf5191ecef84dbc4cc85eb30bc8b63b9"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:eab4bb380f15e189d1313195b062a6aa908f5bd687a0ceccd47c8211e9cf0d4a"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:0cbff728659ce4bbf4c30b2a1be040faafaa9eca6ecde40aaff86f7889f4ab39"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:54c4a097b8bc5bb0dfc83ae498061d53ad7b5762e00f4adaa23bee22b012e6ba"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:73d6d2f64f4d894c96626a75578b0bf7d9e56dcda8c3d037a2118fdfe9b1c664"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:e53b5fbab5d675aec9f0c501274c467c0f9a5d23696cfc94247e1fb56501ed89"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:0ffbcf9221e04502fc35e54d1ce9567541979c3fdfb93d2c554f0ca583a19b35"}, - {file = "regex-2024.9.11-cp39-cp39-win32.whl", hash = "sha256:e4c22e1ac1f1ec1e09f72e6c44d8f2244173db7eb9629cc3a346a8d7ccc31142"}, - {file = "regex-2024.9.11-cp39-cp39-win_amd64.whl", hash = "sha256:faa3c142464efec496967359ca99696c896c591c56c53506bac1ad465f66e919"}, - {file = "regex-2024.9.11.tar.gz", hash = "sha256:6c188c307e8433bcb63dc1915022deb553b4203a70722fc542c363bf120a01fd"}, + {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff590880083d60acc0433f9c3f713c51f7ac6ebb9adf889c79a261ecf541aa91"}, + {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:658f90550f38270639e83ce492f27d2c8d2cd63805c65a13a14d36ca126753f0"}, + {file = "regex-2024.11.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:164d8b7b3b4bcb2068b97428060b2a53be050085ef94eca7f240e7947f1b080e"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d3660c82f209655a06b587d55e723f0b813d3a7db2e32e5e7dc64ac2a9e86fde"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d22326fcdef5e08c154280b71163ced384b428343ae16a5ab2b3354aed12436e"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f1ac758ef6aebfc8943560194e9fd0fa18bcb34d89fd8bd2af18183afd8da3a2"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:997d6a487ff00807ba810e0f8332c18b4eb8d29463cfb7c820dc4b6e7562d0cf"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:02a02d2bb04fec86ad61f3ea7f49c015a0681bf76abb9857f945d26159d2968c"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f02f93b92358ee3f78660e43b4b0091229260c5d5c408d17d60bf26b6c900e86"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:06eb1be98df10e81ebaded73fcd51989dcf534e3c753466e4b60c4697a003b67"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:040df6fe1a5504eb0f04f048e6d09cd7c7110fef851d7c567a6b6e09942feb7d"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fdabbfc59f2c6edba2a6622c647b716e34e8e3867e0ab975412c5c2f79b82da2"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8447d2d39b5abe381419319f942de20b7ecd60ce86f16a23b0698f22e1b70008"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:da8f5fc57d1933de22a9e23eec290a0d8a5927a5370d24bda9a6abe50683fe62"}, + {file = "regex-2024.11.6-cp310-cp310-win32.whl", hash = "sha256:b489578720afb782f6ccf2840920f3a32e31ba28a4b162e13900c3e6bd3f930e"}, + {file = "regex-2024.11.6-cp310-cp310-win_amd64.whl", hash = "sha256:5071b2093e793357c9d8b2929dfc13ac5f0a6c650559503bb81189d0a3814519"}, + {file = "regex-2024.11.6-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:5478c6962ad548b54a591778e93cd7c456a7a29f8eca9c49e4f9a806dcc5d638"}, + {file = "regex-2024.11.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2c89a8cc122b25ce6945f0423dc1352cb9593c68abd19223eebbd4e56612c5b7"}, + {file = "regex-2024.11.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:94d87b689cdd831934fa3ce16cc15cd65748e6d689f5d2b8f4f4df2065c9fa20"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1062b39a0a2b75a9c694f7a08e7183a80c63c0d62b301418ffd9c35f55aaa114"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:167ed4852351d8a750da48712c3930b031f6efdaa0f22fa1933716bfcd6bf4a3"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2d548dafee61f06ebdb584080621f3e0c23fff312f0de1afc776e2a2ba99a74f"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2a19f302cd1ce5dd01a9099aaa19cae6173306d1302a43b627f62e21cf18ac0"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bec9931dfb61ddd8ef2ebc05646293812cb6b16b60cf7c9511a832b6f1854b55"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9714398225f299aa85267fd222f7142fcb5c769e73d7733344efc46f2ef5cf89"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:202eb32e89f60fc147a41e55cb086db2a3f8cb82f9a9a88440dcfc5d37faae8d"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:4181b814e56078e9b00427ca358ec44333765f5ca1b45597ec7446d3a1ef6e34"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:068376da5a7e4da51968ce4c122a7cd31afaaec4fccc7856c92f63876e57b51d"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ac10f2c4184420d881a3475fb2c6f4d95d53a8d50209a2500723d831036f7c45"}, + {file = "regex-2024.11.6-cp311-cp311-win32.whl", hash = "sha256:c36f9b6f5f8649bb251a5f3f66564438977b7ef8386a52460ae77e6070d309d9"}, + {file = "regex-2024.11.6-cp311-cp311-win_amd64.whl", hash = "sha256:02e28184be537f0e75c1f9b2f8847dc51e08e6e171c6bde130b2687e0c33cf60"}, + {file = "regex-2024.11.6-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:52fb28f528778f184f870b7cf8f225f5eef0a8f6e3778529bdd40c7b3920796a"}, + {file = "regex-2024.11.6-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fdd6028445d2460f33136c55eeb1f601ab06d74cb3347132e1c24250187500d9"}, + {file = "regex-2024.11.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:805e6b60c54bf766b251e94526ebad60b7de0c70f70a4e6210ee2891acb70bf2"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b85c2530be953a890eaffde05485238f07029600e8f098cdf1848d414a8b45e4"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bb26437975da7dc36b7efad18aa9dd4ea569d2357ae6b783bf1118dabd9ea577"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:abfa5080c374a76a251ba60683242bc17eeb2c9818d0d30117b4486be10c59d3"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70b7fa6606c2881c1db9479b0eaa11ed5dfa11c8d60a474ff0e095099f39d98e"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0c32f75920cf99fe6b6c539c399a4a128452eaf1af27f39bce8909c9a3fd8cbe"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:982e6d21414e78e1f51cf595d7f321dcd14de1f2881c5dc6a6e23bbbbd68435e"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:a7c2155f790e2fb448faed6dd241386719802296ec588a8b9051c1f5c481bc29"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:149f5008d286636e48cd0b1dd65018548944e495b0265b45e1bffecce1ef7f39"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:e5364a4502efca094731680e80009632ad6624084aff9a23ce8c8c6820de3e51"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0a86e7eeca091c09e021db8eb72d54751e527fa47b8d5787caf96d9831bd02ad"}, + {file = "regex-2024.11.6-cp312-cp312-win32.whl", hash = "sha256:32f9a4c643baad4efa81d549c2aadefaeba12249b2adc5af541759237eee1c54"}, + {file = "regex-2024.11.6-cp312-cp312-win_amd64.whl", hash = "sha256:a93c194e2df18f7d264092dc8539b8ffb86b45b899ab976aa15d48214138e81b"}, + {file = "regex-2024.11.6-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:a6ba92c0bcdf96cbf43a12c717eae4bc98325ca3730f6b130ffa2e3c3c723d84"}, + {file = "regex-2024.11.6-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:525eab0b789891ac3be914d36893bdf972d483fe66551f79d3e27146191a37d4"}, + {file = "regex-2024.11.6-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:086a27a0b4ca227941700e0b31425e7a28ef1ae8e5e05a33826e17e47fbfdba0"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bde01f35767c4a7899b7eb6e823b125a64de314a8ee9791367c9a34d56af18d0"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b583904576650166b3d920d2bcce13971f6f9e9a396c673187f49811b2769dc7"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1c4de13f06a0d54fa0d5ab1b7138bfa0d883220965a29616e3ea61b35d5f5fc7"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3cde6e9f2580eb1665965ce9bf17ff4952f34f5b126beb509fee8f4e994f143c"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d7f453dca13f40a02b79636a339c5b62b670141e63efd511d3f8f73fba162b3"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:59dfe1ed21aea057a65c6b586afd2a945de04fc7db3de0a6e3ed5397ad491b07"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:b97c1e0bd37c5cd7902e65f410779d39eeda155800b65fc4d04cc432efa9bc6e"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:f9d1e379028e0fc2ae3654bac3cbbef81bf3fd571272a42d56c24007979bafb6"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:13291b39131e2d002a7940fb176e120bec5145f3aeb7621be6534e46251912c4"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4f51f88c126370dcec4908576c5a627220da6c09d0bff31cfa89f2523843316d"}, + {file = "regex-2024.11.6-cp313-cp313-win32.whl", hash = "sha256:63b13cfd72e9601125027202cad74995ab26921d8cd935c25f09c630436348ff"}, + {file = "regex-2024.11.6-cp313-cp313-win_amd64.whl", hash = "sha256:2b3361af3198667e99927da8b84c1b010752fa4b1115ee30beaa332cabc3ef1a"}, + {file = "regex-2024.11.6-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:3a51ccc315653ba012774efca4f23d1d2a8a8f278a6072e29c7147eee7da446b"}, + {file = "regex-2024.11.6-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ad182d02e40de7459b73155deb8996bbd8e96852267879396fb274e8700190e3"}, + {file = "regex-2024.11.6-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:ba9b72e5643641b7d41fa1f6d5abda2c9a263ae835b917348fc3c928182ad467"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40291b1b89ca6ad8d3f2b82782cc33807f1406cf68c8d440861da6304d8ffbbd"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cdf58d0e516ee426a48f7b2c03a332a4114420716d55769ff7108c37a09951bf"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a36fdf2af13c2b14738f6e973aba563623cb77d753bbbd8d414d18bfaa3105dd"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d1cee317bfc014c2419a76bcc87f071405e3966da434e03e13beb45f8aced1a6"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:50153825ee016b91549962f970d6a4442fa106832e14c918acd1c8e479916c4f"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ea1bfda2f7162605f6e8178223576856b3d791109f15ea99a9f95c16a7636fb5"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:df951c5f4a1b1910f1a99ff42c473ff60f8225baa1cdd3539fe2819d9543e9df"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:072623554418a9911446278f16ecb398fb3b540147a7828c06e2011fa531e773"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:f654882311409afb1d780b940234208a252322c24a93b442ca714d119e68086c"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:89d75e7293d2b3e674db7d4d9b1bee7f8f3d1609428e293771d1a962617150cc"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:f65557897fc977a44ab205ea871b690adaef6b9da6afda4790a2484b04293a5f"}, + {file = "regex-2024.11.6-cp38-cp38-win32.whl", hash = "sha256:6f44ec28b1f858c98d3036ad5d7d0bfc568bdd7a74f9c24e25f41ef1ebfd81a4"}, + {file = "regex-2024.11.6-cp38-cp38-win_amd64.whl", hash = "sha256:bb8f74f2f10dbf13a0be8de623ba4f9491faf58c24064f32b65679b021ed0001"}, + {file = "regex-2024.11.6-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:5704e174f8ccab2026bd2f1ab6c510345ae8eac818b613d7d73e785f1310f839"}, + {file = "regex-2024.11.6-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:220902c3c5cc6af55d4fe19ead504de80eb91f786dc102fbd74894b1551f095e"}, + {file = "regex-2024.11.6-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5e7e351589da0850c125f1600a4c4ba3c722efefe16b297de54300f08d734fbf"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5056b185ca113c88e18223183aa1a50e66507769c9640a6ff75859619d73957b"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2e34b51b650b23ed3354b5a07aab37034d9f923db2a40519139af34f485f77d0"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5670bce7b200273eee1840ef307bfa07cda90b38ae56e9a6ebcc9f50da9c469b"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:08986dce1339bc932923e7d1232ce9881499a0e02925f7402fb7c982515419ef"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:93c0b12d3d3bc25af4ebbf38f9ee780a487e8bf6954c115b9f015822d3bb8e48"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:764e71f22ab3b305e7f4c21f1a97e1526a25ebdd22513e251cf376760213da13"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:f056bf21105c2515c32372bbc057f43eb02aae2fda61052e2f7622c801f0b4e2"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:69ab78f848845569401469da20df3e081e6b5a11cb086de3eed1d48f5ed57c95"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:86fddba590aad9208e2fa8b43b4c098bb0ec74f15718bb6a704e3c63e2cef3e9"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:684d7a212682996d21ca12ef3c17353c021fe9de6049e19ac8481ec35574a70f"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a03e02f48cd1abbd9f3b7e3586d97c8f7a9721c436f51a5245b3b9483044480b"}, + {file = "regex-2024.11.6-cp39-cp39-win32.whl", hash = "sha256:41758407fc32d5c3c5de163888068cfee69cb4c2be844e7ac517a52770f9af57"}, + {file = "regex-2024.11.6-cp39-cp39-win_amd64.whl", hash = "sha256:b2837718570f95dd41675328e111345f9b7095d821bac435aac173ac80b19983"}, + {file = "regex-2024.11.6.tar.gz", hash = "sha256:7ab159b063c52a0333c884e4679f8d7a85112ee3078fe3d9004b2dd875585519"}, ] [[package]] @@ -3864,114 +3933,114 @@ files = [ [[package]] name = "rpds-py" -version = "0.20.0" +version = "0.22.3" description = "Python bindings to Rust's persistent data structures (rpds)" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "rpds_py-0.20.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:3ad0fda1635f8439cde85c700f964b23ed5fc2d28016b32b9ee5fe30da5c84e2"}, - {file = "rpds_py-0.20.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9bb4a0d90fdb03437c109a17eade42dfbf6190408f29b2744114d11586611d6f"}, - {file = "rpds_py-0.20.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c6377e647bbfd0a0b159fe557f2c6c602c159fc752fa316572f012fc0bf67150"}, - {file = "rpds_py-0.20.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eb851b7df9dda52dc1415ebee12362047ce771fc36914586b2e9fcbd7d293b3e"}, - {file = "rpds_py-0.20.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1e0f80b739e5a8f54837be5d5c924483996b603d5502bfff79bf33da06164ee2"}, - {file = "rpds_py-0.20.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5a8c94dad2e45324fc74dce25e1645d4d14df9a4e54a30fa0ae8bad9a63928e3"}, - {file = "rpds_py-0.20.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f8e604fe73ba048c06085beaf51147eaec7df856824bfe7b98657cf436623daf"}, - {file = "rpds_py-0.20.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:df3de6b7726b52966edf29663e57306b23ef775faf0ac01a3e9f4012a24a4140"}, - {file = "rpds_py-0.20.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cf258ede5bc22a45c8e726b29835b9303c285ab46fc7c3a4cc770736b5304c9f"}, - {file = "rpds_py-0.20.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:55fea87029cded5df854ca7e192ec7bdb7ecd1d9a3f63d5c4eb09148acf4a7ce"}, - {file = "rpds_py-0.20.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:ae94bd0b2f02c28e199e9bc51485d0c5601f58780636185660f86bf80c89af94"}, - {file = "rpds_py-0.20.0-cp310-none-win32.whl", hash = "sha256:28527c685f237c05445efec62426d285e47a58fb05ba0090a4340b73ecda6dee"}, - {file = "rpds_py-0.20.0-cp310-none-win_amd64.whl", hash = "sha256:238a2d5b1cad28cdc6ed15faf93a998336eb041c4e440dd7f902528b8891b399"}, - {file = "rpds_py-0.20.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac2f4f7a98934c2ed6505aead07b979e6f999389f16b714448fb39bbaa86a489"}, - {file = "rpds_py-0.20.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:220002c1b846db9afd83371d08d239fdc865e8f8c5795bbaec20916a76db3318"}, - {file = "rpds_py-0.20.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8d7919548df3f25374a1f5d01fbcd38dacab338ef5f33e044744b5c36729c8db"}, - {file = "rpds_py-0.20.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:758406267907b3781beee0f0edfe4a179fbd97c0be2e9b1154d7f0a1279cf8e5"}, - {file = "rpds_py-0.20.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3d61339e9f84a3f0767b1995adfb171a0d00a1185192718a17af6e124728e0f5"}, - {file = "rpds_py-0.20.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1259c7b3705ac0a0bd38197565a5d603218591d3f6cee6e614e380b6ba61c6f6"}, - {file = "rpds_py-0.20.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5c1dc0f53856b9cc9a0ccca0a7cc61d3d20a7088201c0937f3f4048c1718a209"}, - {file = "rpds_py-0.20.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7e60cb630f674a31f0368ed32b2a6b4331b8350d67de53c0359992444b116dd3"}, - {file = "rpds_py-0.20.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:dbe982f38565bb50cb7fb061ebf762c2f254ca3d8c20d4006878766e84266272"}, - {file = "rpds_py-0.20.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:514b3293b64187172bc77c8fb0cdae26981618021053b30d8371c3a902d4d5ad"}, - {file = "rpds_py-0.20.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:d0a26ffe9d4dd35e4dfdd1e71f46401cff0181c75ac174711ccff0459135fa58"}, - {file = "rpds_py-0.20.0-cp311-none-win32.whl", hash = "sha256:89c19a494bf3ad08c1da49445cc5d13d8fefc265f48ee7e7556839acdacf69d0"}, - {file = "rpds_py-0.20.0-cp311-none-win_amd64.whl", hash = "sha256:c638144ce971df84650d3ed0096e2ae7af8e62ecbbb7b201c8935c370df00a2c"}, - {file = "rpds_py-0.20.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:a84ab91cbe7aab97f7446652d0ed37d35b68a465aeef8fc41932a9d7eee2c1a6"}, - {file = "rpds_py-0.20.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:56e27147a5a4c2c21633ff8475d185734c0e4befd1c989b5b95a5d0db699b21b"}, - {file = "rpds_py-0.20.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2580b0c34583b85efec8c5c5ec9edf2dfe817330cc882ee972ae650e7b5ef739"}, - {file = "rpds_py-0.20.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b80d4a7900cf6b66bb9cee5c352b2d708e29e5a37fe9bf784fa97fc11504bf6c"}, - {file = "rpds_py-0.20.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:50eccbf054e62a7b2209b28dc7a22d6254860209d6753e6b78cfaeb0075d7bee"}, - {file = "rpds_py-0.20.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:49a8063ea4296b3a7e81a5dfb8f7b2d73f0b1c20c2af401fb0cdf22e14711a96"}, - {file = "rpds_py-0.20.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ea438162a9fcbee3ecf36c23e6c68237479f89f962f82dae83dc15feeceb37e4"}, - {file = "rpds_py-0.20.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:18d7585c463087bddcfa74c2ba267339f14f2515158ac4db30b1f9cbdb62c8ef"}, - {file = "rpds_py-0.20.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d4c7d1a051eeb39f5c9547e82ea27cbcc28338482242e3e0b7768033cb083821"}, - {file = "rpds_py-0.20.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:e4df1e3b3bec320790f699890d41c59d250f6beda159ea3c44c3f5bac1976940"}, - {file = "rpds_py-0.20.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2cf126d33a91ee6eedc7f3197b53e87a2acdac63602c0f03a02dd69e4b138174"}, - {file = "rpds_py-0.20.0-cp312-none-win32.whl", hash = "sha256:8bc7690f7caee50b04a79bf017a8d020c1f48c2a1077ffe172abec59870f1139"}, - {file = "rpds_py-0.20.0-cp312-none-win_amd64.whl", hash = "sha256:0e13e6952ef264c40587d510ad676a988df19adea20444c2b295e536457bc585"}, - {file = "rpds_py-0.20.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:aa9a0521aeca7d4941499a73ad7d4f8ffa3d1affc50b9ea11d992cd7eff18a29"}, - {file = "rpds_py-0.20.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:4a1f1d51eccb7e6c32ae89243cb352389228ea62f89cd80823ea7dd1b98e0b91"}, - {file = "rpds_py-0.20.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8a86a9b96070674fc88b6f9f71a97d2c1d3e5165574615d1f9168ecba4cecb24"}, - {file = "rpds_py-0.20.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6c8ef2ebf76df43f5750b46851ed1cdf8f109d7787ca40035fe19fbdc1acc5a7"}, - {file = "rpds_py-0.20.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b74b25f024b421d5859d156750ea9a65651793d51b76a2e9238c05c9d5f203a9"}, - {file = "rpds_py-0.20.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:57eb94a8c16ab08fef6404301c38318e2c5a32216bf5de453e2714c964c125c8"}, - {file = "rpds_py-0.20.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e1940dae14e715e2e02dfd5b0f64a52e8374a517a1e531ad9412319dc3ac7879"}, - {file = "rpds_py-0.20.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d20277fd62e1b992a50c43f13fbe13277a31f8c9f70d59759c88f644d66c619f"}, - {file = "rpds_py-0.20.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:06db23d43f26478303e954c34c75182356ca9aa7797d22c5345b16871ab9c45c"}, - {file = "rpds_py-0.20.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:b2a5db5397d82fa847e4c624b0c98fe59d2d9b7cf0ce6de09e4d2e80f8f5b3f2"}, - {file = "rpds_py-0.20.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5a35df9f5548fd79cb2f52d27182108c3e6641a4feb0f39067911bf2adaa3e57"}, - {file = "rpds_py-0.20.0-cp313-none-win32.whl", hash = "sha256:fd2d84f40633bc475ef2d5490b9c19543fbf18596dcb1b291e3a12ea5d722f7a"}, - {file = "rpds_py-0.20.0-cp313-none-win_amd64.whl", hash = "sha256:9bc2d153989e3216b0559251b0c260cfd168ec78b1fac33dd485750a228db5a2"}, - {file = "rpds_py-0.20.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:f2fbf7db2012d4876fb0d66b5b9ba6591197b0f165db8d99371d976546472a24"}, - {file = "rpds_py-0.20.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:1e5f3cd7397c8f86c8cc72d5a791071431c108edd79872cdd96e00abd8497d29"}, - {file = "rpds_py-0.20.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ce9845054c13696f7af7f2b353e6b4f676dab1b4b215d7fe5e05c6f8bb06f965"}, - {file = "rpds_py-0.20.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c3e130fd0ec56cb76eb49ef52faead8ff09d13f4527e9b0c400307ff72b408e1"}, - {file = "rpds_py-0.20.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4b16aa0107ecb512b568244ef461f27697164d9a68d8b35090e9b0c1c8b27752"}, - {file = "rpds_py-0.20.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:aa7f429242aae2947246587d2964fad750b79e8c233a2367f71b554e9447949c"}, - {file = "rpds_py-0.20.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:af0fc424a5842a11e28956e69395fbbeab2c97c42253169d87e90aac2886d751"}, - {file = "rpds_py-0.20.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b8c00a3b1e70c1d3891f0db1b05292747f0dbcfb49c43f9244d04c70fbc40eb8"}, - {file = "rpds_py-0.20.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:40ce74fc86ee4645d0a225498d091d8bc61f39b709ebef8204cb8b5a464d3c0e"}, - {file = "rpds_py-0.20.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:4fe84294c7019456e56d93e8ababdad5a329cd25975be749c3f5f558abb48253"}, - {file = "rpds_py-0.20.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:338ca4539aad4ce70a656e5187a3a31c5204f261aef9f6ab50e50bcdffaf050a"}, - {file = "rpds_py-0.20.0-cp38-none-win32.whl", hash = "sha256:54b43a2b07db18314669092bb2de584524d1ef414588780261e31e85846c26a5"}, - {file = "rpds_py-0.20.0-cp38-none-win_amd64.whl", hash = "sha256:a1862d2d7ce1674cffa6d186d53ca95c6e17ed2b06b3f4c476173565c862d232"}, - {file = "rpds_py-0.20.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:3fde368e9140312b6e8b6c09fb9f8c8c2f00999d1823403ae90cc00480221b22"}, - {file = "rpds_py-0.20.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:9824fb430c9cf9af743cf7aaf6707bf14323fb51ee74425c380f4c846ea70789"}, - {file = "rpds_py-0.20.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:11ef6ce74616342888b69878d45e9f779b95d4bd48b382a229fe624a409b72c5"}, - {file = "rpds_py-0.20.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c52d3f2f82b763a24ef52f5d24358553e8403ce05f893b5347098014f2d9eff2"}, - {file = "rpds_py-0.20.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9d35cef91e59ebbeaa45214861874bc6f19eb35de96db73e467a8358d701a96c"}, - {file = "rpds_py-0.20.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d72278a30111e5b5525c1dd96120d9e958464316f55adb030433ea905866f4de"}, - {file = "rpds_py-0.20.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b4c29cbbba378759ac5786730d1c3cb4ec6f8ababf5c42a9ce303dc4b3d08cda"}, - {file = "rpds_py-0.20.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6632f2d04f15d1bd6fe0eedd3b86d9061b836ddca4c03d5cf5c7e9e6b7c14580"}, - {file = "rpds_py-0.20.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:d0b67d87bb45ed1cd020e8fbf2307d449b68abc45402fe1a4ac9e46c3c8b192b"}, - {file = "rpds_py-0.20.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:ec31a99ca63bf3cd7f1a5ac9fe95c5e2d060d3c768a09bc1d16e235840861420"}, - {file = "rpds_py-0.20.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:22e6c9976e38f4d8c4a63bd8a8edac5307dffd3ee7e6026d97f3cc3a2dc02a0b"}, - {file = "rpds_py-0.20.0-cp39-none-win32.whl", hash = "sha256:569b3ea770c2717b730b61998b6c54996adee3cef69fc28d444f3e7920313cf7"}, - {file = "rpds_py-0.20.0-cp39-none-win_amd64.whl", hash = "sha256:e6900ecdd50ce0facf703f7a00df12374b74bbc8ad9fe0f6559947fb20f82364"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:617c7357272c67696fd052811e352ac54ed1d9b49ab370261a80d3b6ce385045"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:9426133526f69fcaba6e42146b4e12d6bc6c839b8b555097020e2b78ce908dcc"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:deb62214c42a261cb3eb04d474f7155279c1a8a8c30ac89b7dcb1721d92c3c02"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fcaeb7b57f1a1e071ebd748984359fef83ecb026325b9d4ca847c95bc7311c92"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d454b8749b4bd70dd0a79f428731ee263fa6995f83ccb8bada706e8d1d3ff89d"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d807dc2051abe041b6649681dce568f8e10668e3c1c6543ebae58f2d7e617855"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c3c20f0ddeb6e29126d45f89206b8291352b8c5b44384e78a6499d68b52ae511"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b7f19250ceef892adf27f0399b9e5afad019288e9be756d6919cb58892129f51"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:4f1ed4749a08379555cebf4650453f14452eaa9c43d0a95c49db50c18b7da075"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-musllinux_1_2_i686.whl", hash = "sha256:dcedf0b42bcb4cfff4101d7771a10532415a6106062f005ab97d1d0ab5681c60"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:39ed0d010457a78f54090fafb5d108501b5aa5604cc22408fc1c0c77eac14344"}, - {file = "rpds_py-0.20.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:bb273176be34a746bdac0b0d7e4e2c467323d13640b736c4c477881a3220a989"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f918a1a130a6dfe1d7fe0f105064141342e7dd1611f2e6a21cd2f5c8cb1cfb3e"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:f60012a73aa396be721558caa3a6fd49b3dd0033d1675c6d59c4502e870fcf0c"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3d2b1ad682a3dfda2a4e8ad8572f3100f95fad98cb99faf37ff0ddfe9cbf9d03"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:614fdafe9f5f19c63ea02817fa4861c606a59a604a77c8cdef5aa01d28b97921"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:fa518bcd7600c584bf42e6617ee8132869e877db2f76bcdc281ec6a4113a53ab"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f0475242f447cc6cb8a9dd486d68b2ef7fbee84427124c232bff5f63b1fe11e5"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f90a4cd061914a60bd51c68bcb4357086991bd0bb93d8aa66a6da7701370708f"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:def7400461c3a3f26e49078302e1c1b38f6752342c77e3cf72ce91ca69fb1bc1"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:65794e4048ee837494aea3c21a28ad5fc080994dfba5b036cf84de37f7ad5074"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-musllinux_1_2_i686.whl", hash = "sha256:faefcc78f53a88f3076b7f8be0a8f8d35133a3ecf7f3770895c25f8813460f08"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:5b4f105deeffa28bbcdff6c49b34e74903139afa690e35d2d9e3c2c2fba18cec"}, - {file = "rpds_py-0.20.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:fdfc3a892927458d98f3d55428ae46b921d1f7543b89382fdb483f5640daaec8"}, - {file = "rpds_py-0.20.0.tar.gz", hash = "sha256:d72a210824facfdaf8768cf2d7ca25a042c30320b3020de2fa04640920d4e121"}, + {file = "rpds_py-0.22.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:6c7b99ca52c2c1752b544e310101b98a659b720b21db00e65edca34483259967"}, + {file = "rpds_py-0.22.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:be2eb3f2495ba669d2a985f9b426c1797b7d48d6963899276d22f23e33d47e37"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:70eb60b3ae9245ddea20f8a4190bd79c705a22f8028aaf8bbdebe4716c3fab24"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4041711832360a9b75cfb11b25a6a97c8fb49c07b8bd43d0d02b45d0b499a4ff"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:64607d4cbf1b7e3c3c8a14948b99345eda0e161b852e122c6bb71aab6d1d798c"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e69b0a0e2537f26d73b4e43ad7bc8c8efb39621639b4434b76a3de50c6966e"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc27863442d388870c1809a87507727b799c8460573cfbb6dc0eeaef5a11b5ec"}, + {file = "rpds_py-0.22.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e79dd39f1e8c3504be0607e5fc6e86bb60fe3584bec8b782578c3b0fde8d932c"}, + {file = "rpds_py-0.22.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:e0fa2d4ec53dc51cf7d3bb22e0aa0143966119f42a0c3e4998293a3dd2856b09"}, + {file = "rpds_py-0.22.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fda7cb070f442bf80b642cd56483b5548e43d366fe3f39b98e67cce780cded00"}, + {file = "rpds_py-0.22.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:cff63a0272fcd259dcc3be1657b07c929c466b067ceb1c20060e8d10af56f5bf"}, + {file = "rpds_py-0.22.3-cp310-cp310-win32.whl", hash = "sha256:9bd7228827ec7bb817089e2eb301d907c0d9827a9e558f22f762bb690b131652"}, + {file = "rpds_py-0.22.3-cp310-cp310-win_amd64.whl", hash = "sha256:9beeb01d8c190d7581a4d59522cd3d4b6887040dcfc744af99aa59fef3e041a8"}, + {file = "rpds_py-0.22.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d20cfb4e099748ea39e6f7b16c91ab057989712d31761d3300d43134e26e165f"}, + {file = "rpds_py-0.22.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:68049202f67380ff9aa52f12e92b1c30115f32e6895cd7198fa2a7961621fc5a"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fb4f868f712b2dd4bcc538b0a0c1f63a2b1d584c925e69a224d759e7070a12d5"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bc51abd01f08117283c5ebf64844a35144a0843ff7b2983e0648e4d3d9f10dbb"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0f3cec041684de9a4684b1572fe28c7267410e02450f4561700ca5a3bc6695a2"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7ef9d9da710be50ff6809fed8f1963fecdfecc8b86656cadfca3bc24289414b0"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:59f4a79c19232a5774aee369a0c296712ad0e77f24e62cad53160312b1c1eaa1"}, + {file = "rpds_py-0.22.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1a60bce91f81ddaac922a40bbb571a12c1070cb20ebd6d49c48e0b101d87300d"}, + {file = "rpds_py-0.22.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:e89391e6d60251560f0a8f4bd32137b077a80d9b7dbe6d5cab1cd80d2746f648"}, + {file = "rpds_py-0.22.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e3fb866d9932a3d7d0c82da76d816996d1667c44891bd861a0f97ba27e84fc74"}, + {file = "rpds_py-0.22.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1352ae4f7c717ae8cba93421a63373e582d19d55d2ee2cbb184344c82d2ae55a"}, + {file = "rpds_py-0.22.3-cp311-cp311-win32.whl", hash = "sha256:b0b4136a252cadfa1adb705bb81524eee47d9f6aab4f2ee4fa1e9d3cd4581f64"}, + {file = "rpds_py-0.22.3-cp311-cp311-win_amd64.whl", hash = "sha256:8bd7c8cfc0b8247c8799080fbff54e0b9619e17cdfeb0478ba7295d43f635d7c"}, + {file = "rpds_py-0.22.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:27e98004595899949bd7a7b34e91fa7c44d7a97c40fcaf1d874168bb652ec67e"}, + {file = "rpds_py-0.22.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1978d0021e943aae58b9b0b196fb4895a25cc53d3956b8e35e0b7682eefb6d56"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:655ca44a831ecb238d124e0402d98f6212ac527a0ba6c55ca26f616604e60a45"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:feea821ee2a9273771bae61194004ee2fc33f8ec7db08117ef9147d4bbcbca8e"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:22bebe05a9ffc70ebfa127efbc429bc26ec9e9b4ee4d15a740033efda515cf3d"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3af6e48651c4e0d2d166dc1b033b7042ea3f871504b6805ba5f4fe31581d8d38"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e67ba3c290821343c192f7eae1d8fd5999ca2dc99994114643e2f2d3e6138b15"}, + {file = "rpds_py-0.22.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:02fbb9c288ae08bcb34fb41d516d5eeb0455ac35b5512d03181d755d80810059"}, + {file = "rpds_py-0.22.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f56a6b404f74ab372da986d240e2e002769a7d7102cc73eb238a4f72eec5284e"}, + {file = "rpds_py-0.22.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:0a0461200769ab3b9ab7e513f6013b7a97fdeee41c29b9db343f3c5a8e2b9e61"}, + {file = "rpds_py-0.22.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8633e471c6207a039eff6aa116e35f69f3156b3989ea3e2d755f7bc41754a4a7"}, + {file = "rpds_py-0.22.3-cp312-cp312-win32.whl", hash = "sha256:593eba61ba0c3baae5bc9be2f5232430453fb4432048de28399ca7376de9c627"}, + {file = "rpds_py-0.22.3-cp312-cp312-win_amd64.whl", hash = "sha256:d115bffdd417c6d806ea9069237a4ae02f513b778e3789a359bc5856e0404cc4"}, + {file = "rpds_py-0.22.3-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:ea7433ce7e4bfc3a85654aeb6747babe3f66eaf9a1d0c1e7a4435bbdf27fea84"}, + {file = "rpds_py-0.22.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:6dd9412824c4ce1aca56c47b0991e65bebb7ac3f4edccfd3f156150c96a7bf25"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:20070c65396f7373f5df4005862fa162db5d25d56150bddd0b3e8214e8ef45b4"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0b09865a9abc0ddff4e50b5ef65467cd94176bf1e0004184eb915cbc10fc05c5"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3453e8d41fe5f17d1f8e9c383a7473cd46a63661628ec58e07777c2fff7196dc"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f5d36399a1b96e1a5fdc91e0522544580dbebeb1f77f27b2b0ab25559e103b8b"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:009de23c9c9ee54bf11303a966edf4d9087cd43a6003672e6aa7def643d06518"}, + {file = "rpds_py-0.22.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1aef18820ef3e4587ebe8b3bc9ba6e55892a6d7b93bac6d29d9f631a3b4befbd"}, + {file = "rpds_py-0.22.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f60bd8423be1d9d833f230fdbccf8f57af322d96bcad6599e5a771b151398eb2"}, + {file = "rpds_py-0.22.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:62d9cfcf4948683a18a9aff0ab7e1474d407b7bab2ca03116109f8464698ab16"}, + {file = "rpds_py-0.22.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9253fc214112405f0afa7db88739294295f0e08466987f1d70e29930262b4c8f"}, + {file = "rpds_py-0.22.3-cp313-cp313-win32.whl", hash = "sha256:fb0ba113b4983beac1a2eb16faffd76cb41e176bf58c4afe3e14b9c681f702de"}, + {file = "rpds_py-0.22.3-cp313-cp313-win_amd64.whl", hash = "sha256:c58e2339def52ef6b71b8f36d13c3688ea23fa093353f3a4fee2556e62086ec9"}, + {file = "rpds_py-0.22.3-cp313-cp313t-macosx_10_12_x86_64.whl", hash = "sha256:f82a116a1d03628a8ace4859556fb39fd1424c933341a08ea3ed6de1edb0283b"}, + {file = "rpds_py-0.22.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:3dfcbc95bd7992b16f3f7ba05af8a64ca694331bd24f9157b49dadeeb287493b"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:59259dc58e57b10e7e18ce02c311804c10c5a793e6568f8af4dead03264584d1"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5725dd9cc02068996d4438d397e255dcb1df776b7ceea3b9cb972bdb11260a83"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:99b37292234e61325e7a5bb9689e55e48c3f5f603af88b1642666277a81f1fbd"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:27b1d3b3915a99208fee9ab092b8184c420f2905b7d7feb4aeb5e4a9c509b8a1"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f612463ac081803f243ff13cccc648578e2279295048f2a8d5eb430af2bae6e3"}, + {file = "rpds_py-0.22.3-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f73d3fef726b3243a811121de45193c0ca75f6407fe66f3f4e183c983573e130"}, + {file = "rpds_py-0.22.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:3f21f0495edea7fdbaaa87e633a8689cd285f8f4af5c869f27bc8074638ad69c"}, + {file = "rpds_py-0.22.3-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:1e9663daaf7a63ceccbbb8e3808fe90415b0757e2abddbfc2e06c857bf8c5e2b"}, + {file = "rpds_py-0.22.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:a76e42402542b1fae59798fab64432b2d015ab9d0c8c47ba7addddbaf7952333"}, + {file = "rpds_py-0.22.3-cp313-cp313t-win32.whl", hash = "sha256:69803198097467ee7282750acb507fba35ca22cc3b85f16cf45fb01cb9097730"}, + {file = "rpds_py-0.22.3-cp313-cp313t-win_amd64.whl", hash = "sha256:f5cf2a0c2bdadf3791b5c205d55a37a54025c6e18a71c71f82bb536cf9a454bf"}, + {file = "rpds_py-0.22.3-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:378753b4a4de2a7b34063d6f95ae81bfa7b15f2c1a04a9518e8644e81807ebea"}, + {file = "rpds_py-0.22.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3445e07bf2e8ecfeef6ef67ac83de670358abf2996916039b16a218e3d95e97e"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7b2513ba235829860b13faa931f3b6846548021846ac808455301c23a101689d"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eaf16ae9ae519a0e237a0f528fd9f0197b9bb70f40263ee57ae53c2b8d48aeb3"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:583f6a1993ca3369e0f80ba99d796d8e6b1a3a2a442dd4e1a79e652116413091"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4617e1915a539a0d9a9567795023de41a87106522ff83fbfaf1f6baf8e85437e"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0c150c7a61ed4a4f4955a96626574e9baf1adf772c2fb61ef6a5027e52803543"}, + {file = "rpds_py-0.22.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2fa4331c200c2521512595253f5bb70858b90f750d39b8cbfd67465f8d1b596d"}, + {file = "rpds_py-0.22.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:214b7a953d73b5e87f0ebece4a32a5bd83c60a3ecc9d4ec8f1dca968a2d91e99"}, + {file = "rpds_py-0.22.3-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:f47ad3d5f3258bd7058d2d506852217865afefe6153a36eb4b6928758041d831"}, + {file = "rpds_py-0.22.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:f276b245347e6e36526cbd4a266a417796fc531ddf391e43574cf6466c492520"}, + {file = "rpds_py-0.22.3-cp39-cp39-win32.whl", hash = "sha256:bbb232860e3d03d544bc03ac57855cd82ddf19c7a07651a7c0fdb95e9efea8b9"}, + {file = "rpds_py-0.22.3-cp39-cp39-win_amd64.whl", hash = "sha256:cfbc454a2880389dbb9b5b398e50d439e2e58669160f27b60e5eca11f68ae17c"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:d48424e39c2611ee1b84ad0f44fb3b2b53d473e65de061e3f460fc0be5f1939d"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:24e8abb5878e250f2eb0d7859a8e561846f98910326d06c0d51381fed59357bd"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4b232061ca880db21fa14defe219840ad9b74b6158adb52ddf0e87bead9e8493"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ac0a03221cdb5058ce0167ecc92a8c89e8d0decdc9e99a2ec23380793c4dcb96"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eb0c341fa71df5a4595f9501df4ac5abfb5a09580081dffbd1ddd4654e6e9123"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf9db5488121b596dbfc6718c76092fda77b703c1f7533a226a5a9f65248f8ad"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0b8db6b5b2d4491ad5b6bdc2bc7c017eec108acbf4e6785f42a9eb0ba234f4c9"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b3d504047aba448d70cf6fa22e06cb09f7cbd761939fdd47604f5e007675c24e"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:e61b02c3f7a1e0b75e20c3978f7135fd13cb6cf551bf4a6d29b999a88830a338"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_i686.whl", hash = "sha256:e35ba67d65d49080e8e5a1dd40101fccdd9798adb9b050ff670b7d74fa41c566"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:26fd7cac7dd51011a245f29a2cc6489c4608b5a8ce8d75661bb4a1066c52dfbe"}, + {file = "rpds_py-0.22.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:177c7c0fce2855833819c98e43c262007f42ce86651ffbb84f37883308cb0e7d"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:bb47271f60660803ad11f4c61b42242b8c1312a31c98c578f79ef9387bbde21c"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:70fb28128acbfd264eda9bf47015537ba3fe86e40d046eb2963d75024be4d055"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:44d61b4b7d0c2c9ac019c314e52d7cbda0ae31078aabd0f22e583af3e0d79723"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f0e260eaf54380380ac3808aa4ebe2d8ca28b9087cf411649f96bad6900c728"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b25bc607423935079e05619d7de556c91fb6adeae9d5f80868dde3468657994b"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fb6116dfb8d1925cbdb52595560584db42a7f664617a1f7d7f6e32f138cdf37d"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a63cbdd98acef6570c62b92a1e43266f9e8b21e699c363c0fef13bd530799c11"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b8f60e1b739a74bab7e01fcbe3dddd4657ec685caa04681df9d562ef15b625f"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:2e8b55d8517a2fda8d95cb45d62a5a8bbf9dd0ad39c5b25c8833efea07b880ca"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-musllinux_1_2_i686.whl", hash = "sha256:2de29005e11637e7a2361fa151f780ff8eb2543a0da1413bb951e9f14b699ef3"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:666ecce376999bf619756a24ce15bb14c5bfaf04bf00abc7e663ce17c3f34fe7"}, + {file = "rpds_py-0.22.3-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:5246b14ca64a8675e0a7161f7af68fe3e910e6b90542b4bfb5439ba752191df6"}, + {file = "rpds_py-0.22.3.tar.gz", hash = "sha256:e32fee8ab45d3c2db6da19a5323bc3362237c8b653c70194414b892fd06a080d"}, ] [[package]] @@ -4035,13 +4104,13 @@ testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs ( [[package]] name = "six" -version = "1.16.0" +version = "1.17.0" description = "Python 2 and 3 compatibility utilities" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" files = [ - {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"}, - {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"}, + {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"}, + {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"}, ] [[package]] @@ -4135,13 +4204,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"] [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -4261,51 +4330,82 @@ files = [ [[package]] name = "tomli" -version = "2.0.2" +version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"}, - {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"}, + {file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"}, + {file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"}, + {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"}, + {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"}, + {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"}, + {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"}, + {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"}, + {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"}, ] [[package]] name = "tornado" -version = "6.4.1" +version = "6.4.2" description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." optional = false python-versions = ">=3.8" files = [ - {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8"}, - {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14"}, - {file = "tornado-6.4.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4"}, - {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842"}, - {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3"}, - {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f"}, - {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4"}, - {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698"}, - {file = "tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d"}, - {file = "tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7"}, - {file = "tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9"}, + {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e828cce1123e9e44ae2a50a9de3055497ab1d0aeb440c5ac23064d9e44880da1"}, + {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:072ce12ada169c5b00b7d92a99ba089447ccc993ea2143c9ede887e0937aa803"}, + {file = "tornado-6.4.2-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a017d239bd1bb0919f72af256a970624241f070496635784d9bf0db640d3fec"}, + {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c36e62ce8f63409301537222faffcef7dfc5284f27eec227389f2ad11b09d946"}, + {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca9eb02196e789c9cb5c3c7c0f04fb447dc2adffd95265b2c7223a8a615ccbf"}, + {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:304463bd0772442ff4d0f5149c6f1c2135a1fae045adf070821c6cdc76980634"}, + {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:c82c46813ba483a385ab2a99caeaedf92585a1f90defb5693351fa7e4ea0bf73"}, + {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:932d195ca9015956fa502c6b56af9eb06106140d844a335590c1ec7f5277d10c"}, + {file = "tornado-6.4.2-cp38-abi3-win32.whl", hash = "sha256:2876cef82e6c5978fde1e0d5b1f919d756968d5b4282418f3146b79b58556482"}, + {file = "tornado-6.4.2-cp38-abi3-win_amd64.whl", hash = "sha256:908b71bf3ff37d81073356a5fadcc660eb10c1476ee6e2725588626ce7e5ca38"}, + {file = "tornado-6.4.2.tar.gz", hash = "sha256:92bad5b4746e9879fd7bf1eb21dce4e3fc5128d71601f80005afa39237ad620b"}, ] [[package]] name = "tqdm" -version = "4.66.6" +version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = true python-versions = ">=3.7" files = [ - {file = "tqdm-4.66.6-py3-none-any.whl", hash = "sha256:223e8b5359c2efc4b30555531f09e9f2f3589bcd7fdd389271191031b49b7a63"}, - {file = "tqdm-4.66.6.tar.gz", hash = "sha256:4bdd694238bef1485ce839d67967ab50af8f9272aab687c0d7702a01da0be090"}, + {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, + {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, ] [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} [package.extras] -dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"] +dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"] +discord = ["requests"] notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] telegram = ["requests"] @@ -4352,13 +4452,13 @@ files = [ [[package]] name = "types-protobuf" -version = "5.28.3.20241030" +version = "5.28.3.20241203" description = "Typing stubs for protobuf" optional = false python-versions = ">=3.8" files = [ - {file = "types-protobuf-5.28.3.20241030.tar.gz", hash = "sha256:f7e6b45845d75393fb41c0b3ce82c46d775f9771fae2097414a1dbfe5b51a988"}, - {file = "types_protobuf-5.28.3.20241030-py3-none-any.whl", hash = "sha256:f3dae16adf342d4fb5bb3673cabb22549a6252e5dd66fc52d8310b1a39c64ba9"}, + {file = "types_protobuf-5.28.3.20241203-py3-none-any.whl", hash = "sha256:5367632a4785394b0504e7c1e4d54a2dceeae9cd4f73a705d0f6499fc99cecb1"}, + {file = "types_protobuf-5.28.3.20241203.tar.gz", hash = "sha256:2e1c962bdf76c576506b5fc0678d28efa6652a54c04ae46562a6209e777bd789"}, ] [[package]] @@ -4378,13 +4478,13 @@ types-cffi = "*" [[package]] name = "types-python-dateutil" -version = "2.9.0.20241003" +version = "2.9.0.20241206" description = "Typing stubs for python-dateutil" optional = false python-versions = ">=3.8" files = [ - {file = "types-python-dateutil-2.9.0.20241003.tar.gz", hash = "sha256:58cb85449b2a56d6684e41aeefb4c4280631246a0da1a719bdbe6f3fb0317446"}, - {file = "types_python_dateutil-2.9.0.20241003-py3-none-any.whl", hash = "sha256:250e1d8e80e7bbc3a6c99b907762711d1a1cdd00e978ad39cb5940f6f0a87f3d"}, + {file = "types_python_dateutil-2.9.0.20241206-py3-none-any.whl", hash = "sha256:e248a4bc70a486d3e3ec84d0dc30eec3a5f979d6e7ee4123ae043eedbb987f53"}, + {file = "types_python_dateutil-2.9.0.20241206.tar.gz", hash = "sha256:18f493414c26ffba692a72369fea7a154c502646301ebfe3d56a04b3767284cb"}, ] [[package]] @@ -4424,6 +4524,20 @@ files = [ cryptography = ">=35.0.0" types-pyOpenSSL = "*" +[[package]] +name = "types-requests" +version = "2.31.0.6" +description = "Typing stubs for requests" +optional = false +python-versions = ">=3.7" +files = [ + {file = "types-requests-2.31.0.6.tar.gz", hash = "sha256:cd74ce3b53c461f1228a9b783929ac73a666658f223e28ed29753771477b3bd0"}, + {file = "types_requests-2.31.0.6-py3-none-any.whl", hash = "sha256:a2db9cb228a81da8348b49ad6db3f5519452dd20a9c1e1a868c83c5fe88fd1a9"}, +] + +[package.dependencies] +types-urllib3 = "*" + [[package]] name = "types-requests" version = "2.32.0.20241016" @@ -4440,13 +4554,13 @@ urllib3 = ">=2" [[package]] name = "types-setuptools" -version = "75.2.0.20241025" +version = "75.6.0.20241126" description = "Typing stubs for setuptools" optional = false python-versions = ">=3.8" files = [ - {file = "types-setuptools-75.2.0.20241025.tar.gz", hash = "sha256:2949913a518d5285ce00a3b7d88961c80a6e72ffb8f3da0a3f5650ea533bd45e"}, - {file = "types_setuptools-75.2.0.20241025-py3-none-any.whl", hash = "sha256:6721ac0f1a620321e2ccd87a9a747c4a383dc381f78d894ce37f2455b45fcf1c"}, + {file = "types_setuptools-75.6.0.20241126-py3-none-any.whl", hash = "sha256:aaae310a0e27033c1da8457d4d26ac673b0c8a0de7272d6d4708e263f2ea3b9b"}, + {file = "types_setuptools-75.6.0.20241126.tar.gz", hash = "sha256:7bf25ad4be39740e469f9268b6beddda6e088891fa5a27e985c6ce68bf62ace0"}, ] [[package]] @@ -4460,6 +4574,17 @@ files = [ {file = "types_toml-0.10.8.20240310-py3-none-any.whl", hash = "sha256:627b47775d25fa29977d9c70dc0cbab3f314f32c8d8d0c012f2ef5de7aaec05d"}, ] +[[package]] +name = "types-urllib3" +version = "1.26.25.14" +description = "Typing stubs for urllib3" +optional = false +python-versions = "*" +files = [ + {file = "types-urllib3-1.26.25.14.tar.gz", hash = "sha256:229b7f577c951b8c1b92c1bc2b2fdb0b49847bd2af6d1cc2a2e3dd340f3bda8f"}, + {file = "types_urllib3-1.26.25.14-py3-none-any.whl", hash = "sha256:9683bbb7fb72e32bfe9d2be6e04875fbe1b3eeec3cbb4ea231435aa7fd6b4f0e"}, +] + [[package]] name = "typing-extensions" version = "4.12.2" @@ -4496,6 +4621,22 @@ files = [ [package.extras] dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"] +[[package]] +name = "urllib3" +version = "1.26.20" +description = "HTTP library with thread-safe connection pooling, file post, and more." +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" +files = [ + {file = "urllib3-1.26.20-py2.py3-none-any.whl", hash = "sha256:0ed14ccfbf1c30a9072c7ca157e4319b70d65f623e91e7b32fadb2853431016e"}, + {file = "urllib3-1.26.20.tar.gz", hash = "sha256:40c2dc0c681e47eb8f90e7e27bf6ff7df2e677421fd46756da1161c39ca70d32"}, +] + +[package.extras] +brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"] +secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"] +socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] + [[package]] name = "urllib3" version = "2.2.3" @@ -4513,23 +4654,6 @@ h2 = ["h2 (>=4,<5)"] socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] zstd = ["zstandard (>=0.18.0)"] -[[package]] -name = "vcrpy" -version = "4.3.0" -description = "Automatically mock your HTTP interactions to simplify and speed up testing" -optional = false -python-versions = ">=3.7" -files = [ - {file = "vcrpy-4.3.0-py2.py3-none-any.whl", hash = "sha256:8fbd4be412e8a7f35f623dd61034e6380a1c8dbd0edf6e87277a3289f6e98093"}, - {file = "vcrpy-4.3.0.tar.gz", hash = "sha256:49c270ce67e826dba027d83e20d25b67a5885487697e97bca6dbdf53d750a0ac"}, -] - -[package.dependencies] -PyYAML = "*" -six = ">=1.5" -wrapt = "*" -yarl = "*" - [[package]] name = "vcrpy" version = "6.0.2" @@ -4543,7 +4667,10 @@ files = [ [package.dependencies] PyYAML = "*" -urllib3 = {version = "*", markers = "platform_python_implementation != \"PyPy\" and python_version >= \"3.10\""} +urllib3 = [ + {version = "<2", markers = "platform_python_implementation == \"PyPy\" or python_version < \"3.10\""}, + {version = "*", markers = "platform_python_implementation != \"PyPy\" and python_version >= \"3.10\""}, +] wrapt = "*" yarl = "*" @@ -4552,41 +4679,41 @@ tests = ["Werkzeug (==2.0.3)", "aiohttp", "boto3", "httplib2", "httpx", "pytest" [[package]] name = "watchdog" -version = "5.0.3" +version = "6.0.0" description = "Filesystem events monitoring" optional = false python-versions = ">=3.9" files = [ - {file = "watchdog-5.0.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:85527b882f3facda0579bce9d743ff7f10c3e1e0db0a0d0e28170a7d0e5ce2ea"}, - {file = "watchdog-5.0.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:53adf73dcdc0ef04f7735066b4a57a4cd3e49ef135daae41d77395f0b5b692cb"}, - {file = "watchdog-5.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e25adddab85f674acac303cf1f5835951345a56c5f7f582987d266679979c75b"}, - {file = "watchdog-5.0.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:f01f4a3565a387080dc49bdd1fefe4ecc77f894991b88ef927edbfa45eb10818"}, - {file = "watchdog-5.0.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:91b522adc25614cdeaf91f7897800b82c13b4b8ac68a42ca959f992f6990c490"}, - {file = "watchdog-5.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d52db5beb5e476e6853da2e2d24dbbbed6797b449c8bf7ea118a4ee0d2c9040e"}, - {file = "watchdog-5.0.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:94d11b07c64f63f49876e0ab8042ae034674c8653bfcdaa8c4b32e71cfff87e8"}, - {file = "watchdog-5.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:349c9488e1d85d0a58e8cb14222d2c51cbc801ce11ac3936ab4c3af986536926"}, - {file = "watchdog-5.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:53a3f10b62c2d569e260f96e8d966463dec1a50fa4f1b22aec69e3f91025060e"}, - {file = "watchdog-5.0.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:950f531ec6e03696a2414b6308f5c6ff9dab7821a768c9d5788b1314e9a46ca7"}, - {file = "watchdog-5.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ae6deb336cba5d71476caa029ceb6e88047fc1dc74b62b7c4012639c0b563906"}, - {file = "watchdog-5.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1021223c08ba8d2d38d71ec1704496471ffd7be42cfb26b87cd5059323a389a1"}, - {file = "watchdog-5.0.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:752fb40efc7cc8d88ebc332b8f4bcbe2b5cc7e881bccfeb8e25054c00c994ee3"}, - {file = "watchdog-5.0.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a2e8f3f955d68471fa37b0e3add18500790d129cc7efe89971b8a4cc6fdeb0b2"}, - {file = "watchdog-5.0.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b8ca4d854adcf480bdfd80f46fdd6fb49f91dd020ae11c89b3a79e19454ec627"}, - {file = "watchdog-5.0.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:90a67d7857adb1d985aca232cc9905dd5bc4803ed85cfcdcfcf707e52049eda7"}, - {file = "watchdog-5.0.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:720ef9d3a4f9ca575a780af283c8fd3a0674b307651c1976714745090da5a9e8"}, - {file = "watchdog-5.0.3-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:223160bb359281bb8e31c8f1068bf71a6b16a8ad3d9524ca6f523ac666bb6a1e"}, - {file = "watchdog-5.0.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:560135542c91eaa74247a2e8430cf83c4342b29e8ad4f520ae14f0c8a19cfb5b"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_aarch64.whl", hash = "sha256:dd021efa85970bd4824acacbb922066159d0f9e546389a4743d56919b6758b91"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_armv7l.whl", hash = "sha256:78864cc8f23dbee55be34cc1494632a7ba30263951b5b2e8fc8286b95845f82c"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_i686.whl", hash = "sha256:1e9679245e3ea6498494b3028b90c7b25dbb2abe65c7d07423ecfc2d6218ff7c"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_ppc64.whl", hash = "sha256:9413384f26b5d050b6978e6fcd0c1e7f0539be7a4f1a885061473c5deaa57221"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:294b7a598974b8e2c6123d19ef15de9abcd282b0fbbdbc4d23dfa812959a9e05"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_s390x.whl", hash = "sha256:26dd201857d702bdf9d78c273cafcab5871dd29343748524695cecffa44a8d97"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_x86_64.whl", hash = "sha256:0f9332243355643d567697c3e3fa07330a1d1abf981611654a1f2bf2175612b7"}, - {file = "watchdog-5.0.3-py3-none-win32.whl", hash = "sha256:c66f80ee5b602a9c7ab66e3c9f36026590a0902db3aea414d59a2f55188c1f49"}, - {file = "watchdog-5.0.3-py3-none-win_amd64.whl", hash = "sha256:f00b4cf737f568be9665563347a910f8bdc76f88c2970121c86243c8cfdf90e9"}, - {file = "watchdog-5.0.3-py3-none-win_ia64.whl", hash = "sha256:49f4d36cb315c25ea0d946e018c01bb028048023b9e103d3d3943f58e109dd45"}, - {file = "watchdog-5.0.3.tar.gz", hash = "sha256:108f42a7f0345042a854d4d0ad0834b741d421330d5f575b81cb27b883500176"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d1cdb490583ebd691c012b3d6dae011000fe42edb7a82ece80965b42abd61f26"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bc64ab3bdb6a04d69d4023b29422170b74681784ffb9463ed4870cf2f3e66112"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c897ac1b55c5a1461e16dae288d22bb2e412ba9807df8397a635d88f671d36c3"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6eb11feb5a0d452ee41f824e271ca311a09e250441c262ca2fd7ebcf2461a06c"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ef810fbf7b781a5a593894e4f439773830bdecb885e6880d957d5b9382a960d2"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:afd0fe1b2270917c5e23c2a65ce50c2a4abb63daafb0d419fde368e272a76b7c"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:bdd4e6f14b8b18c334febb9c4425a878a2ac20efd1e0b231978e7b150f92a948"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:c7c15dda13c4eb00d6fb6fc508b3c0ed88b9d5d374056b239c4ad1611125c860"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6f10cb2d5902447c7d0da897e2c6768bca89174d0c6e1e30abec5421af97a5b0"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:490ab2ef84f11129844c23fb14ecf30ef3d8a6abafd3754a6f75ca1e6654136c"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:76aae96b00ae814b181bb25b1b98076d5fc84e8a53cd8885a318b42b6d3a5134"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a175f755fc2279e0b7312c0035d52e27211a5bc39719dd529625b1930917345b"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:e6f0e77c9417e7cd62af82529b10563db3423625c5fce018430b249bf977f9e8"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:90c8e78f3b94014f7aaae121e6b909674df5b46ec24d6bebc45c44c56729af2a"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:e7631a77ffb1f7d2eefa4445ebbee491c720a5661ddf6df3498ebecae5ed375c"}, + {file = "watchdog-6.0.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:c7ac31a19f4545dd92fc25d200694098f42c9a8e391bc00bdd362c5736dbf881"}, + {file = "watchdog-6.0.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:9513f27a1a582d9808cf21a07dae516f0fab1cf2d7683a742c498b93eedabb11"}, + {file = "watchdog-6.0.0-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:7a0e56874cfbc4b9b05c60c8a1926fedf56324bb08cfbc188969777940aef3aa"}, + {file = "watchdog-6.0.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:e6439e374fc012255b4ec786ae3c4bc838cd7309a540e5fe0952d03687d8804e"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7607498efa04a3542ae3e05e64da8202e58159aa1fa4acddf7678d34a35d4f13"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_armv7l.whl", hash = "sha256:9041567ee8953024c83343288ccc458fd0a2d811d6a0fd68c4c22609e3490379"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_i686.whl", hash = "sha256:82dc3e3143c7e38ec49d61af98d6558288c415eac98486a5c581726e0737c00e"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_ppc64.whl", hash = "sha256:212ac9b8bf1161dc91bd09c048048a95ca3a4c4f5e5d4a7d1b1a7d5752a7f96f"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:e3df4cbb9a450c6d49318f6d14f4bbc80d763fa587ba46ec86f99f9e6876bb26"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_s390x.whl", hash = "sha256:2cce7cfc2008eb51feb6aab51251fd79b85d9894e98ba847408f662b3395ca3c"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:20ffe5b202af80ab4266dcd3e91aae72bf2da48c0d33bdb15c66658e685e94e2"}, + {file = "watchdog-6.0.0-py3-none-win32.whl", hash = "sha256:07df1fdd701c5d4c8e55ef6cf55b8f0120fe1aef7ef39a1c6fc6bc2e606d517a"}, + {file = "watchdog-6.0.0-py3-none-win_amd64.whl", hash = "sha256:cbafb470cf848d93b5d013e2ecb245d4aa1c8fd0504e863ccefa32445359d680"}, + {file = "watchdog-6.0.0-py3-none-win_ia64.whl", hash = "sha256:a1914259fa9e1454315171103c6a30961236f508b9b623eae470268bbcc6a22f"}, + {file = "watchdog-6.0.0.tar.gz", hash = "sha256:9ddf7c82fda3ae8e24decda1338ede66e1c99883db93711d8fb941eaa2d8c282"}, ] [package.extras] @@ -4605,19 +4732,15 @@ files = [ [[package]] name = "webcolors" -version = "24.8.0" +version = "24.11.1" description = "A library for working with the color formats defined by HTML and CSS." optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "webcolors-24.8.0-py3-none-any.whl", hash = "sha256:fc4c3b59358ada164552084a8ebee637c221e4059267d0f8325b3b560f6c7f0a"}, - {file = "webcolors-24.8.0.tar.gz", hash = "sha256:08b07af286a01bcd30d583a7acadf629583d1f79bfef27dd2c2c5c263817277d"}, + {file = "webcolors-24.11.1-py3-none-any.whl", hash = "sha256:515291393b4cdf0eb19c155749a096f779f7d909f7cceea072791cb9095b92e9"}, + {file = "webcolors-24.11.1.tar.gz", hash = "sha256:ecb3d768f32202af770477b8b65f318fa4f566c22948673a977b00d589dd80f6"}, ] -[package.extras] -docs = ["furo", "sphinx", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-notfound-page", "sphinxext-opengraph"] -tests = ["coverage[toml]"] - [[package]] name = "webencodings" version = "0.5.1" @@ -4658,172 +4781,167 @@ files = [ [[package]] name = "wrapt" -version = "1.16.0" +version = "1.17.0" description = "Module for decorators, wrappers and monkey patching." optional = false -python-versions = ">=3.6" +python-versions = ">=3.8" files = [ - {file = "wrapt-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ffa565331890b90056c01db69c0fe634a776f8019c143a5ae265f9c6bc4bd6d4"}, - {file = "wrapt-1.16.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e4fdb9275308292e880dcbeb12546df7f3e0f96c6b41197e0cf37d2826359020"}, - {file = "wrapt-1.16.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bb2dee3874a500de01c93d5c71415fcaef1d858370d405824783e7a8ef5db440"}, - {file = "wrapt-1.16.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2a88e6010048489cda82b1326889ec075a8c856c2e6a256072b28eaee3ccf487"}, - {file = "wrapt-1.16.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ac83a914ebaf589b69f7d0a1277602ff494e21f4c2f743313414378f8f50a4cf"}, - {file = "wrapt-1.16.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:73aa7d98215d39b8455f103de64391cb79dfcad601701a3aa0dddacf74911d72"}, - {file = "wrapt-1.16.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:807cc8543a477ab7422f1120a217054f958a66ef7314f76dd9e77d3f02cdccd0"}, - {file = "wrapt-1.16.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bf5703fdeb350e36885f2875d853ce13172ae281c56e509f4e6eca049bdfb136"}, - {file = "wrapt-1.16.0-cp310-cp310-win32.whl", hash = "sha256:f6b2d0c6703c988d334f297aa5df18c45e97b0af3679bb75059e0e0bd8b1069d"}, - {file = "wrapt-1.16.0-cp310-cp310-win_amd64.whl", hash = "sha256:decbfa2f618fa8ed81c95ee18a387ff973143c656ef800c9f24fb7e9c16054e2"}, - {file = "wrapt-1.16.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1a5db485fe2de4403f13fafdc231b0dbae5eca4359232d2efc79025527375b09"}, - {file = "wrapt-1.16.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:75ea7d0ee2a15733684badb16de6794894ed9c55aa5e9903260922f0482e687d"}, - {file = "wrapt-1.16.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a452f9ca3e3267cd4d0fcf2edd0d035b1934ac2bd7e0e57ac91ad6b95c0c6389"}, - {file = "wrapt-1.16.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:43aa59eadec7890d9958748db829df269f0368521ba6dc68cc172d5d03ed8060"}, - {file = "wrapt-1.16.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:72554a23c78a8e7aa02abbd699d129eead8b147a23c56e08d08dfc29cfdddca1"}, - {file = "wrapt-1.16.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d2efee35b4b0a347e0d99d28e884dfd82797852d62fcd7ebdeee26f3ceb72cf3"}, - {file = "wrapt-1.16.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:6dcfcffe73710be01d90cae08c3e548d90932d37b39ef83969ae135d36ef3956"}, - {file = "wrapt-1.16.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:eb6e651000a19c96f452c85132811d25e9264d836951022d6e81df2fff38337d"}, - {file = "wrapt-1.16.0-cp311-cp311-win32.whl", hash = "sha256:66027d667efe95cc4fa945af59f92c5a02c6f5bb6012bff9e60542c74c75c362"}, - {file = "wrapt-1.16.0-cp311-cp311-win_amd64.whl", hash = "sha256:aefbc4cb0a54f91af643660a0a150ce2c090d3652cf4052a5397fb2de549cd89"}, - {file = "wrapt-1.16.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:5eb404d89131ec9b4f748fa5cfb5346802e5ee8836f57d516576e61f304f3b7b"}, - {file = "wrapt-1.16.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9090c9e676d5236a6948330e83cb89969f433b1943a558968f659ead07cb3b36"}, - {file = "wrapt-1.16.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94265b00870aa407bd0cbcfd536f17ecde43b94fb8d228560a1e9d3041462d73"}, - {file = "wrapt-1.16.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f2058f813d4f2b5e3a9eb2eb3faf8f1d99b81c3e51aeda4b168406443e8ba809"}, - {file = "wrapt-1.16.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98b5e1f498a8ca1858a1cdbffb023bfd954da4e3fa2c0cb5853d40014557248b"}, - {file = "wrapt-1.16.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:14d7dc606219cdd7405133c713f2c218d4252f2a469003f8c46bb92d5d095d81"}, - {file = "wrapt-1.16.0-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:49aac49dc4782cb04f58986e81ea0b4768e4ff197b57324dcbd7699c5dfb40b9"}, - {file = "wrapt-1.16.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:418abb18146475c310d7a6dc71143d6f7adec5b004ac9ce08dc7a34e2babdc5c"}, - {file = "wrapt-1.16.0-cp312-cp312-win32.whl", hash = "sha256:685f568fa5e627e93f3b52fda002c7ed2fa1800b50ce51f6ed1d572d8ab3e7fc"}, - {file = "wrapt-1.16.0-cp312-cp312-win_amd64.whl", hash = "sha256:dcdba5c86e368442528f7060039eda390cc4091bfd1dca41e8046af7c910dda8"}, - {file = "wrapt-1.16.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:d462f28826f4657968ae51d2181a074dfe03c200d6131690b7d65d55b0f360f8"}, - {file = "wrapt-1.16.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a33a747400b94b6d6b8a165e4480264a64a78c8a4c734b62136062e9a248dd39"}, - {file = "wrapt-1.16.0-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b3646eefa23daeba62643a58aac816945cadc0afaf21800a1421eeba5f6cfb9c"}, - {file = "wrapt-1.16.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ebf019be5c09d400cf7b024aa52b1f3aeebeff51550d007e92c3c1c4afc2a40"}, - {file = "wrapt-1.16.0-cp36-cp36m-musllinux_1_1_aarch64.whl", hash = "sha256:0d2691979e93d06a95a26257adb7bfd0c93818e89b1406f5a28f36e0d8c1e1fc"}, - {file = "wrapt-1.16.0-cp36-cp36m-musllinux_1_1_i686.whl", hash = "sha256:1acd723ee2a8826f3d53910255643e33673e1d11db84ce5880675954183ec47e"}, - {file = "wrapt-1.16.0-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:bc57efac2da352a51cc4658878a68d2b1b67dbe9d33c36cb826ca449d80a8465"}, - {file = "wrapt-1.16.0-cp36-cp36m-win32.whl", hash = "sha256:da4813f751142436b075ed7aa012a8778aa43a99f7b36afe9b742d3ed8bdc95e"}, - {file = "wrapt-1.16.0-cp36-cp36m-win_amd64.whl", hash = "sha256:6f6eac2360f2d543cc875a0e5efd413b6cbd483cb3ad7ebf888884a6e0d2e966"}, - {file = "wrapt-1.16.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:a0ea261ce52b5952bf669684a251a66df239ec6d441ccb59ec7afa882265d593"}, - {file = "wrapt-1.16.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7bd2d7ff69a2cac767fbf7a2b206add2e9a210e57947dd7ce03e25d03d2de292"}, - {file = "wrapt-1.16.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9159485323798c8dc530a224bd3ffcf76659319ccc7bbd52e01e73bd0241a0c5"}, - {file = "wrapt-1.16.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a86373cf37cd7764f2201b76496aba58a52e76dedfaa698ef9e9688bfd9e41cf"}, - {file = "wrapt-1.16.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:73870c364c11f03ed072dda68ff7aea6d2a3a5c3fe250d917a429c7432e15228"}, - {file = "wrapt-1.16.0-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:b935ae30c6e7400022b50f8d359c03ed233d45b725cfdd299462f41ee5ffba6f"}, - {file = "wrapt-1.16.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:db98ad84a55eb09b3c32a96c576476777e87c520a34e2519d3e59c44710c002c"}, - {file = "wrapt-1.16.0-cp37-cp37m-win32.whl", hash = "sha256:9153ed35fc5e4fa3b2fe97bddaa7cbec0ed22412b85bcdaf54aeba92ea37428c"}, - {file = "wrapt-1.16.0-cp37-cp37m-win_amd64.whl", hash = "sha256:66dfbaa7cfa3eb707bbfcd46dab2bc6207b005cbc9caa2199bcbc81d95071a00"}, - {file = "wrapt-1.16.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:1dd50a2696ff89f57bd8847647a1c363b687d3d796dc30d4dd4a9d1689a706f0"}, - {file = "wrapt-1.16.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:44a2754372e32ab315734c6c73b24351d06e77ffff6ae27d2ecf14cf3d229202"}, - {file = "wrapt-1.16.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8e9723528b9f787dc59168369e42ae1c3b0d3fadb2f1a71de14531d321ee05b0"}, - {file = "wrapt-1.16.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:dbed418ba5c3dce92619656802cc5355cb679e58d0d89b50f116e4a9d5a9603e"}, - {file = "wrapt-1.16.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:941988b89b4fd6b41c3f0bfb20e92bd23746579736b7343283297c4c8cbae68f"}, - {file = "wrapt-1.16.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:6a42cd0cfa8ffc1915aef79cb4284f6383d8a3e9dcca70c445dcfdd639d51267"}, - {file = "wrapt-1.16.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:1ca9b6085e4f866bd584fb135a041bfc32cab916e69f714a7d1d397f8c4891ca"}, - {file = "wrapt-1.16.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:d5e49454f19ef621089e204f862388d29e6e8d8b162efce05208913dde5b9ad6"}, - {file = "wrapt-1.16.0-cp38-cp38-win32.whl", hash = "sha256:c31f72b1b6624c9d863fc095da460802f43a7c6868c5dda140f51da24fd47d7b"}, - {file = "wrapt-1.16.0-cp38-cp38-win_amd64.whl", hash = "sha256:490b0ee15c1a55be9c1bd8609b8cecd60e325f0575fc98f50058eae366e01f41"}, - {file = "wrapt-1.16.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9b201ae332c3637a42f02d1045e1d0cccfdc41f1f2f801dafbaa7e9b4797bfc2"}, - {file = "wrapt-1.16.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2076fad65c6736184e77d7d4729b63a6d1ae0b70da4868adeec40989858eb3fb"}, - {file = "wrapt-1.16.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5cd603b575ebceca7da5a3a251e69561bec509e0b46e4993e1cac402b7247b8"}, - {file = "wrapt-1.16.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b47cfad9e9bbbed2339081f4e346c93ecd7ab504299403320bf85f7f85c7d46c"}, - {file = "wrapt-1.16.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f8212564d49c50eb4565e502814f694e240c55551a5f1bc841d4fcaabb0a9b8a"}, - {file = "wrapt-1.16.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:5f15814a33e42b04e3de432e573aa557f9f0f56458745c2074952f564c50e664"}, - {file = "wrapt-1.16.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:db2e408d983b0e61e238cf579c09ef7020560441906ca990fe8412153e3b291f"}, - {file = "wrapt-1.16.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:edfad1d29c73f9b863ebe7082ae9321374ccb10879eeabc84ba3b69f2579d537"}, - {file = "wrapt-1.16.0-cp39-cp39-win32.whl", hash = "sha256:ed867c42c268f876097248e05b6117a65bcd1e63b779e916fe2e33cd6fd0d3c3"}, - {file = "wrapt-1.16.0-cp39-cp39-win_amd64.whl", hash = "sha256:eb1b046be06b0fce7249f1d025cd359b4b80fc1c3e24ad9eca33e0dcdb2e4a35"}, - {file = "wrapt-1.16.0-py3-none-any.whl", hash = "sha256:6906c4100a8fcbf2fa735f6059214bb13b97f75b1a61777fcf6432121ef12ef1"}, - {file = "wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d"}, + {file = "wrapt-1.17.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2a0c23b8319848426f305f9cb0c98a6e32ee68a36264f45948ccf8e7d2b941f8"}, + {file = "wrapt-1.17.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b1ca5f060e205f72bec57faae5bd817a1560fcfc4af03f414b08fa29106b7e2d"}, + {file = "wrapt-1.17.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e185ec6060e301a7e5f8461c86fb3640a7beb1a0f0208ffde7a65ec4074931df"}, + {file = "wrapt-1.17.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb90765dd91aed05b53cd7a87bd7f5c188fcd95960914bae0d32c5e7f899719d"}, + {file = "wrapt-1.17.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:879591c2b5ab0a7184258274c42a126b74a2c3d5a329df16d69f9cee07bba6ea"}, + {file = "wrapt-1.17.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fce6fee67c318fdfb7f285c29a82d84782ae2579c0e1b385b7f36c6e8074fffb"}, + {file = "wrapt-1.17.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:0698d3a86f68abc894d537887b9bbf84d29bcfbc759e23f4644be27acf6da301"}, + {file = "wrapt-1.17.0-cp310-cp310-win32.whl", hash = "sha256:69d093792dc34a9c4c8a70e4973a3361c7a7578e9cd86961b2bbf38ca71e4e22"}, + {file = "wrapt-1.17.0-cp310-cp310-win_amd64.whl", hash = "sha256:f28b29dc158ca5d6ac396c8e0a2ef45c4e97bb7e65522bfc04c989e6fe814575"}, + {file = "wrapt-1.17.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:74bf625b1b4caaa7bad51d9003f8b07a468a704e0644a700e936c357c17dd45a"}, + {file = "wrapt-1.17.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f2a28eb35cf99d5f5bd12f5dd44a0f41d206db226535b37b0c60e9da162c3ed"}, + {file = "wrapt-1.17.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:81b1289e99cf4bad07c23393ab447e5e96db0ab50974a280f7954b071d41b489"}, + {file = "wrapt-1.17.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f2939cd4a2a52ca32bc0b359015718472d7f6de870760342e7ba295be9ebaf9"}, + {file = "wrapt-1.17.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6a9653131bda68a1f029c52157fd81e11f07d485df55410401f745007bd6d339"}, + {file = "wrapt-1.17.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:4e4b4385363de9052dac1a67bfb535c376f3d19c238b5f36bddc95efae15e12d"}, + {file = "wrapt-1.17.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:bdf62d25234290db1837875d4dceb2151e4ea7f9fff2ed41c0fde23ed542eb5b"}, + {file = "wrapt-1.17.0-cp311-cp311-win32.whl", hash = "sha256:5d8fd17635b262448ab8f99230fe4dac991af1dabdbb92f7a70a6afac8a7e346"}, + {file = "wrapt-1.17.0-cp311-cp311-win_amd64.whl", hash = "sha256:92a3d214d5e53cb1db8b015f30d544bc9d3f7179a05feb8f16df713cecc2620a"}, + {file = "wrapt-1.17.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:89fc28495896097622c3fc238915c79365dd0ede02f9a82ce436b13bd0ab7569"}, + {file = "wrapt-1.17.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:875d240fdbdbe9e11f9831901fb8719da0bd4e6131f83aa9f69b96d18fae7504"}, + {file = "wrapt-1.17.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e5ed16d95fd142e9c72b6c10b06514ad30e846a0d0917ab406186541fe68b451"}, + {file = "wrapt-1.17.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:18b956061b8db634120b58f668592a772e87e2e78bc1f6a906cfcaa0cc7991c1"}, + {file = "wrapt-1.17.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:daba396199399ccabafbfc509037ac635a6bc18510ad1add8fd16d4739cdd106"}, + {file = "wrapt-1.17.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:4d63f4d446e10ad19ed01188d6c1e1bb134cde8c18b0aa2acfd973d41fcc5ada"}, + {file = "wrapt-1.17.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8a5e7cc39a45fc430af1aefc4d77ee6bad72c5bcdb1322cfde852c15192b8bd4"}, + {file = "wrapt-1.17.0-cp312-cp312-win32.whl", hash = "sha256:0a0a1a1ec28b641f2a3a2c35cbe86c00051c04fffcfcc577ffcdd707df3f8635"}, + {file = "wrapt-1.17.0-cp312-cp312-win_amd64.whl", hash = "sha256:3c34f6896a01b84bab196f7119770fd8466c8ae3dfa73c59c0bb281e7b588ce7"}, + {file = "wrapt-1.17.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:714c12485aa52efbc0fc0ade1e9ab3a70343db82627f90f2ecbc898fdf0bb181"}, + {file = "wrapt-1.17.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:da427d311782324a376cacb47c1a4adc43f99fd9d996ffc1b3e8529c4074d393"}, + {file = "wrapt-1.17.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ba1739fb38441a27a676f4de4123d3e858e494fac05868b7a281c0a383c098f4"}, + {file = "wrapt-1.17.0-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e711fc1acc7468463bc084d1b68561e40d1eaa135d8c509a65dd534403d83d7b"}, + {file = "wrapt-1.17.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:140ea00c87fafc42739bd74a94a5a9003f8e72c27c47cd4f61d8e05e6dec8721"}, + {file = "wrapt-1.17.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:73a96fd11d2b2e77d623a7f26e004cc31f131a365add1ce1ce9a19e55a1eef90"}, + {file = "wrapt-1.17.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:0b48554952f0f387984da81ccfa73b62e52817a4386d070c75e4db7d43a28c4a"}, + {file = "wrapt-1.17.0-cp313-cp313-win32.whl", hash = "sha256:498fec8da10e3e62edd1e7368f4b24aa362ac0ad931e678332d1b209aec93045"}, + {file = "wrapt-1.17.0-cp313-cp313-win_amd64.whl", hash = "sha256:fd136bb85f4568fffca995bd3c8d52080b1e5b225dbf1c2b17b66b4c5fa02838"}, + {file = "wrapt-1.17.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:17fcf043d0b4724858f25b8826c36e08f9fb2e475410bece0ec44a22d533da9b"}, + {file = "wrapt-1.17.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e4a557d97f12813dc5e18dad9fa765ae44ddd56a672bb5de4825527c847d6379"}, + {file = "wrapt-1.17.0-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0229b247b0fc7dee0d36176cbb79dbaf2a9eb7ecc50ec3121f40ef443155fb1d"}, + {file = "wrapt-1.17.0-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8425cfce27b8b20c9b89d77fb50e368d8306a90bf2b6eef2cdf5cd5083adf83f"}, + {file = "wrapt-1.17.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:9c900108df470060174108012de06d45f514aa4ec21a191e7ab42988ff42a86c"}, + {file = "wrapt-1.17.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:4e547b447073fc0dbfcbff15154c1be8823d10dab4ad401bdb1575e3fdedff1b"}, + {file = "wrapt-1.17.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:914f66f3b6fc7b915d46c1cc424bc2441841083de01b90f9e81109c9759e43ab"}, + {file = "wrapt-1.17.0-cp313-cp313t-win32.whl", hash = "sha256:a4192b45dff127c7d69b3bdfb4d3e47b64179a0b9900b6351859f3001397dabf"}, + {file = "wrapt-1.17.0-cp313-cp313t-win_amd64.whl", hash = "sha256:4f643df3d4419ea3f856c5c3f40fec1d65ea2e89ec812c83f7767c8730f9827a"}, + {file = "wrapt-1.17.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:69c40d4655e078ede067a7095544bcec5a963566e17503e75a3a3e0fe2803b13"}, + {file = "wrapt-1.17.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f495b6754358979379f84534f8dd7a43ff8cff2558dcdea4a148a6e713a758f"}, + {file = "wrapt-1.17.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:baa7ef4e0886a6f482e00d1d5bcd37c201b383f1d314643dfb0367169f94f04c"}, + {file = "wrapt-1.17.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a8fc931382e56627ec4acb01e09ce66e5c03c384ca52606111cee50d931a342d"}, + {file = "wrapt-1.17.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:8f8909cdb9f1b237786c09a810e24ee5e15ef17019f7cecb207ce205b9b5fcce"}, + {file = "wrapt-1.17.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:ad47b095f0bdc5585bced35bd088cbfe4177236c7df9984b3cc46b391cc60627"}, + {file = "wrapt-1.17.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:948a9bd0fb2c5120457b07e59c8d7210cbc8703243225dbd78f4dfc13c8d2d1f"}, + {file = "wrapt-1.17.0-cp38-cp38-win32.whl", hash = "sha256:5ae271862b2142f4bc687bdbfcc942e2473a89999a54231aa1c2c676e28f29ea"}, + {file = "wrapt-1.17.0-cp38-cp38-win_amd64.whl", hash = "sha256:f335579a1b485c834849e9075191c9898e0731af45705c2ebf70e0cd5d58beed"}, + {file = "wrapt-1.17.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:d751300b94e35b6016d4b1e7d0e7bbc3b5e1751e2405ef908316c2a9024008a1"}, + {file = "wrapt-1.17.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7264cbb4a18dc4acfd73b63e4bcfec9c9802614572025bdd44d0721983fc1d9c"}, + {file = "wrapt-1.17.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:33539c6f5b96cf0b1105a0ff4cf5db9332e773bb521cc804a90e58dc49b10578"}, + {file = "wrapt-1.17.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c30970bdee1cad6a8da2044febd824ef6dc4cc0b19e39af3085c763fdec7de33"}, + {file = "wrapt-1.17.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:bc7f729a72b16ee21795a943f85c6244971724819819a41ddbaeb691b2dd85ad"}, + {file = "wrapt-1.17.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:6ff02a91c4fc9b6a94e1c9c20f62ea06a7e375f42fe57587f004d1078ac86ca9"}, + {file = "wrapt-1.17.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:2dfb7cff84e72e7bf975b06b4989477873dcf160b2fd89959c629535df53d4e0"}, + {file = "wrapt-1.17.0-cp39-cp39-win32.whl", hash = "sha256:2399408ac33ffd5b200480ee858baa58d77dd30e0dd0cab6a8a9547135f30a88"}, + {file = "wrapt-1.17.0-cp39-cp39-win_amd64.whl", hash = "sha256:4f763a29ee6a20c529496a20a7bcb16a73de27f5da6a843249c7047daf135977"}, + {file = "wrapt-1.17.0-py3-none-any.whl", hash = "sha256:d2c63b93548eda58abf5188e505ffed0229bf675f7c3090f8e36ad55b8cbc371"}, + {file = "wrapt-1.17.0.tar.gz", hash = "sha256:16187aa2317c731170a88ef35e8937ae0f533c402872c1ee5e6d079fcf320801"}, ] [[package]] name = "yarl" -version = "1.17.1" +version = "1.18.3" description = "Yet another URL library" optional = false python-versions = ">=3.9" files = [ - {file = "yarl-1.17.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b1794853124e2f663f0ea54efb0340b457f08d40a1cef78edfa086576179c91"}, - {file = "yarl-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:fbea1751729afe607d84acfd01efd95e3b31db148a181a441984ce9b3d3469da"}, - {file = "yarl-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8ee427208c675f1b6e344a1f89376a9613fc30b52646a04ac0c1f6587c7e46ec"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3b74ff4767d3ef47ffe0cd1d89379dc4d828d4873e5528976ced3b44fe5b0a21"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:62a91aefff3d11bf60e5956d340eb507a983a7ec802b19072bb989ce120cd948"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:846dd2e1243407133d3195d2d7e4ceefcaa5f5bf7278f0a9bda00967e6326b04"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3e844be8d536afa129366d9af76ed7cb8dfefec99f5f1c9e4f8ae542279a6dc3"}, - {file = "yarl-1.17.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:cc7c92c1baa629cb03ecb0c3d12564f172218fb1739f54bf5f3881844daadc6d"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:ae3476e934b9d714aa8000d2e4c01eb2590eee10b9d8cd03e7983ad65dfbfcba"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c7e177c619342e407415d4f35dec63d2d134d951e24b5166afcdfd1362828e17"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:64cc6e97f14cf8a275d79c5002281f3040c12e2e4220623b5759ea7f9868d6a5"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:84c063af19ef5130084db70ada40ce63a84f6c1ef4d3dbc34e5e8c4febb20822"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:482c122b72e3c5ec98f11457aeb436ae4aecca75de19b3d1de7cf88bc40db82f"}, - {file = "yarl-1.17.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:380e6c38ef692b8fd5a0f6d1fa8774d81ebc08cfbd624b1bca62a4d4af2f9931"}, - {file = "yarl-1.17.1-cp310-cp310-win32.whl", hash = "sha256:16bca6678a83657dd48df84b51bd56a6c6bd401853aef6d09dc2506a78484c7b"}, - {file = "yarl-1.17.1-cp310-cp310-win_amd64.whl", hash = "sha256:561c87fea99545ef7d692403c110b2f99dced6dff93056d6e04384ad3bc46243"}, - {file = "yarl-1.17.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:cbad927ea8ed814622305d842c93412cb47bd39a496ed0f96bfd42b922b4a217"}, - {file = "yarl-1.17.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:fca4b4307ebe9c3ec77a084da3a9d1999d164693d16492ca2b64594340999988"}, - {file = "yarl-1.17.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ff5c6771c7e3511a06555afa317879b7db8d640137ba55d6ab0d0c50425cab75"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5b29beab10211a746f9846baa39275e80034e065460d99eb51e45c9a9495bcca"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1a52a1ffdd824fb1835272e125385c32fd8b17fbdefeedcb4d543cc23b332d74"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:58c8e9620eb82a189c6c40cb6b59b4e35b2ee68b1f2afa6597732a2b467d7e8f"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d216e5d9b8749563c7f2c6f7a0831057ec844c68b4c11cb10fc62d4fd373c26d"}, - {file = "yarl-1.17.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:881764d610e3269964fc4bb3c19bb6fce55422828e152b885609ec176b41cf11"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8c79e9d7e3d8a32d4824250a9c6401194fb4c2ad9a0cec8f6a96e09a582c2cc0"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:299f11b44d8d3a588234adbe01112126010bd96d9139c3ba7b3badd9829261c3"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:cc7d768260f4ba4ea01741c1b5fe3d3a6c70eb91c87f4c8761bbcce5181beafe"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:de599af166970d6a61accde358ec9ded821234cbbc8c6413acfec06056b8e860"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:2b24ec55fad43e476905eceaf14f41f6478780b870eda5d08b4d6de9a60b65b4"}, - {file = "yarl-1.17.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:9fb815155aac6bfa8d86184079652c9715c812d506b22cfa369196ef4e99d1b4"}, - {file = "yarl-1.17.1-cp311-cp311-win32.whl", hash = "sha256:7615058aabad54416ddac99ade09a5510cf77039a3b903e94e8922f25ed203d7"}, - {file = "yarl-1.17.1-cp311-cp311-win_amd64.whl", hash = "sha256:14bc88baa44e1f84164a392827b5defb4fa8e56b93fecac3d15315e7c8e5d8b3"}, - {file = "yarl-1.17.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:327828786da2006085a4d1feb2594de6f6d26f8af48b81eb1ae950c788d97f61"}, - {file = "yarl-1.17.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:cc353841428d56b683a123a813e6a686e07026d6b1c5757970a877195f880c2d"}, - {file = "yarl-1.17.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c73df5b6e8fabe2ddb74876fb82d9dd44cbace0ca12e8861ce9155ad3c886139"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0bdff5e0995522706c53078f531fb586f56de9c4c81c243865dd5c66c132c3b5"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:06157fb3c58f2736a5e47c8fcbe1afc8b5de6fb28b14d25574af9e62150fcaac"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1654ec814b18be1af2c857aa9000de7a601400bd4c9ca24629b18486c2e35463"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f6595c852ca544aaeeb32d357e62c9c780eac69dcd34e40cae7b55bc4fb1147"}, - {file = "yarl-1.17.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:459e81c2fb920b5f5df744262d1498ec2c8081acdcfe18181da44c50f51312f7"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:7e48cdb8226644e2fbd0bdb0a0f87906a3db07087f4de77a1b1b1ccfd9e93685"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:d9b6b28a57feb51605d6ae5e61a9044a31742db557a3b851a74c13bc61de5172"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:e594b22688d5747b06e957f1ef822060cb5cb35b493066e33ceac0cf882188b7"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:5f236cb5999ccd23a0ab1bd219cfe0ee3e1c1b65aaf6dd3320e972f7ec3a39da"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a2a64e62c7a0edd07c1c917b0586655f3362d2c2d37d474db1a509efb96fea1c"}, - {file = "yarl-1.17.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:d0eea830b591dbc68e030c86a9569826145df485b2b4554874b07fea1275a199"}, - {file = "yarl-1.17.1-cp312-cp312-win32.whl", hash = "sha256:46ddf6e0b975cd680eb83318aa1d321cb2bf8d288d50f1754526230fcf59ba96"}, - {file = "yarl-1.17.1-cp312-cp312-win_amd64.whl", hash = "sha256:117ed8b3732528a1e41af3aa6d4e08483c2f0f2e3d3d7dca7cf538b3516d93df"}, - {file = "yarl-1.17.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:5d1d42556b063d579cae59e37a38c61f4402b47d70c29f0ef15cee1acaa64488"}, - {file = "yarl-1.17.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:c0167540094838ee9093ef6cc2c69d0074bbf84a432b4995835e8e5a0d984374"}, - {file = "yarl-1.17.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:2f0a6423295a0d282d00e8701fe763eeefba8037e984ad5de44aa349002562ac"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e5b078134f48552c4d9527db2f7da0b5359abd49393cdf9794017baec7506170"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d401f07261dc5aa36c2e4efc308548f6ae943bfff20fcadb0a07517a26b196d8"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b5f1ac7359e17efe0b6e5fec21de34145caef22b260e978336f325d5c84e6938"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f63d176a81555984e91f2c84c2a574a61cab7111cc907e176f0f01538e9ff6e"}, - {file = "yarl-1.17.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9e275792097c9f7e80741c36de3b61917aebecc08a67ae62899b074566ff8556"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:81713b70bea5c1386dc2f32a8f0dab4148a2928c7495c808c541ee0aae614d67"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:aa46dce75078fceaf7cecac5817422febb4355fbdda440db55206e3bd288cfb8"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1ce36ded585f45b1e9bb36d0ae94765c6608b43bd2e7f5f88079f7a85c61a4d3"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:2d374d70fdc36f5863b84e54775452f68639bc862918602d028f89310a034ab0"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:2d9f0606baaec5dd54cb99667fcf85183a7477f3766fbddbe3f385e7fc253299"}, - {file = "yarl-1.17.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:b0341e6d9a0c0e3cdc65857ef518bb05b410dbd70d749a0d33ac0f39e81a4258"}, - {file = "yarl-1.17.1-cp313-cp313-win32.whl", hash = "sha256:2e7ba4c9377e48fb7b20dedbd473cbcbc13e72e1826917c185157a137dac9df2"}, - {file = "yarl-1.17.1-cp313-cp313-win_amd64.whl", hash = "sha256:949681f68e0e3c25377462be4b658500e85ca24323d9619fdc41f68d46a1ffda"}, - {file = "yarl-1.17.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:8994b29c462de9a8fce2d591028b986dbbe1b32f3ad600b2d3e1c482c93abad6"}, - {file = "yarl-1.17.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f9cbfbc5faca235fbdf531b93aa0f9f005ec7d267d9d738761a4d42b744ea159"}, - {file = "yarl-1.17.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b40d1bf6e6f74f7c0a567a9e5e778bbd4699d1d3d2c0fe46f4b717eef9e96b95"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f5efe0661b9fcd6246f27957f6ae1c0eb29bc60552820f01e970b4996e016004"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b5c4804e4039f487e942c13381e6c27b4b4e66066d94ef1fae3f6ba8b953f383"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b5d6a6c9602fd4598fa07e0389e19fe199ae96449008d8304bf5d47cb745462e"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6f4c9156c4d1eb490fe374fb294deeb7bc7eaccda50e23775b2354b6a6739934"}, - {file = "yarl-1.17.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d6324274b4e0e2fa1b3eccb25997b1c9ed134ff61d296448ab8269f5ac068c4c"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:d8a8b74d843c2638f3864a17d97a4acda58e40d3e44b6303b8cc3d3c44ae2d29"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7fac95714b09da9278a0b52e492466f773cfe37651cf467a83a1b659be24bf71"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:c180ac742a083e109c1a18151f4dd8675f32679985a1c750d2ff806796165b55"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:578d00c9b7fccfa1745a44f4eddfdc99d723d157dad26764538fbdda37209857"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:1a3b91c44efa29e6c8ef8a9a2b583347998e2ba52c5d8280dbd5919c02dfc3b5"}, - {file = "yarl-1.17.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a7ac5b4984c468ce4f4a553df281450df0a34aefae02e58d77a0847be8d1e11f"}, - {file = "yarl-1.17.1-cp39-cp39-win32.whl", hash = "sha256:7294e38f9aa2e9f05f765b28ffdc5d81378508ce6dadbe93f6d464a8c9594473"}, - {file = "yarl-1.17.1-cp39-cp39-win_amd64.whl", hash = "sha256:eb6dce402734575e1a8cc0bb1509afca508a400a57ce13d306ea2c663bad1138"}, - {file = "yarl-1.17.1-py3-none-any.whl", hash = "sha256:f1790a4b1e8e8e028c391175433b9c8122c39b46e1663228158e61e6f915bf06"}, - {file = "yarl-1.17.1.tar.gz", hash = "sha256:067a63fcfda82da6b198fa73079b1ca40b7c9b7994995b6ee38acda728b64d47"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:602d98f2c2d929f8e697ed274fbadc09902c4025c5a9963bf4e9edfc3ab6f7ed"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c654d5207c78e0bd6d749f6dae1dcbbfde3403ad3a4b11f3c5544d9906969dde"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5094d9206c64181d0f6e76ebd8fb2f8fe274950a63890ee9e0ebfd58bf9d787b"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35098b24e0327fc4ebdc8ffe336cee0a87a700c24ffed13161af80124b7dc8e5"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3236da9272872443f81fedc389bace88408f64f89f75d1bdb2256069a8730ccc"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e2c08cc9b16f4f4bc522771d96734c7901e7ebef70c6c5c35dd0f10845270bcd"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:80316a8bd5109320d38eef8833ccf5f89608c9107d02d2a7f985f98ed6876990"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c1e1cc06da1491e6734f0ea1e6294ce00792193c463350626571c287c9a704db"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fea09ca13323376a2fdfb353a5fa2e59f90cd18d7ca4eaa1fd31f0a8b4f91e62"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e3b9fd71836999aad54084906f8663dffcd2a7fb5cdafd6c37713b2e72be1760"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:757e81cae69244257d125ff31663249b3013b5dc0a8520d73694aed497fb195b"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b1771de9944d875f1b98a745bc547e684b863abf8f8287da8466cf470ef52690"}, + {file = "yarl-1.18.3-cp310-cp310-win32.whl", hash = "sha256:8874027a53e3aea659a6d62751800cf6e63314c160fd607489ba5c2edd753cf6"}, + {file = "yarl-1.18.3-cp310-cp310-win_amd64.whl", hash = "sha256:93b2e109287f93db79210f86deb6b9bbb81ac32fc97236b16f7433db7fc437d8"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8503ad47387b8ebd39cbbbdf0bf113e17330ffd339ba1144074da24c545f0069"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02ddb6756f8f4517a2d5e99d8b2f272488e18dd0bfbc802f31c16c6c20f22193"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:67a283dd2882ac98cc6318384f565bffc751ab564605959df4752d42483ad889"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d980e0325b6eddc81331d3f4551e2a333999fb176fd153e075c6d1c2530aa8a8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b643562c12680b01e17239be267bc306bbc6aac1f34f6444d1bded0c5ce438ca"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c017a3b6df3a1bd45b9fa49a0f54005e53fbcad16633870104b66fa1a30a29d8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75674776d96d7b851b6498f17824ba17849d790a44d282929c42dbb77d4f17ae"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ccaa3a4b521b780a7e771cc336a2dba389a0861592bbce09a476190bb0c8b4b3"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d06d3005e668744e11ed80812e61efd77d70bb7f03e33c1598c301eea20efbb"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:9d41beda9dc97ca9ab0b9888cb71f7539124bc05df02c0cff6e5acc5a19dcc6e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:ba23302c0c61a9999784e73809427c9dbedd79f66a13d84ad1b1943802eaaf59"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:6748dbf9bfa5ba1afcc7556b71cda0d7ce5f24768043a02a58846e4a443d808d"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:0b0cad37311123211dc91eadcb322ef4d4a66008d3e1bdc404808992260e1a0e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0fb2171a4486bb075316ee754c6d8382ea6eb8b399d4ec62fde2b591f879778a"}, + {file = "yarl-1.18.3-cp311-cp311-win32.whl", hash = "sha256:61b1a825a13bef4a5f10b1885245377d3cd0bf87cba068e1d9a88c2ae36880e1"}, + {file = "yarl-1.18.3-cp311-cp311-win_amd64.whl", hash = "sha256:b9d60031cf568c627d028239693fd718025719c02c9f55df0a53e587aab951b5"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1dd4bdd05407ced96fed3d7f25dbbf88d2ffb045a0db60dbc247f5b3c5c25d50"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7c33dd1931a95e5d9a772d0ac5e44cac8957eaf58e3c8da8c1414de7dd27c576"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:25b411eddcfd56a2f0cd6a384e9f4f7aa3efee14b188de13048c25b5e91f1640"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:436c4fc0a4d66b2badc6c5fc5ef4e47bb10e4fd9bf0c79524ac719a01f3607c2"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e35ef8683211db69ffe129a25d5634319a677570ab6b2eba4afa860f54eeaf75"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84b2deecba4a3f1a398df819151eb72d29bfeb3b69abb145a00ddc8d30094512"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e5a1fea0fd4f5bfa7440a47eff01d9822a65b4488f7cff83155a0f31a2ecba"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0e883008013c0e4aef84dcfe2a0b172c4d23c2669412cf5b3371003941f72bb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5a3f356548e34a70b0172d8890006c37be92995f62d95a07b4a42e90fba54272"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ccd17349166b1bee6e529b4add61727d3f55edb7babbe4069b5764c9587a8cc6"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b958ddd075ddba5b09bb0be8a6d9906d2ce933aee81100db289badbeb966f54e"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c7d79f7d9aabd6011004e33b22bc13056a3e3fb54794d138af57f5ee9d9032cb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:4891ed92157e5430874dad17b15eb1fda57627710756c27422200c52d8a4e393"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ce1af883b94304f493698b00d0f006d56aea98aeb49d75ec7d98cd4a777e9285"}, + {file = "yarl-1.18.3-cp312-cp312-win32.whl", hash = "sha256:f91c4803173928a25e1a55b943c81f55b8872f0018be83e3ad4938adffb77dd2"}, + {file = "yarl-1.18.3-cp312-cp312-win_amd64.whl", hash = "sha256:7e2ee16578af3b52ac2f334c3b1f92262f47e02cc6193c598502bd46f5cd1477"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:90adb47ad432332d4f0bc28f83a5963f426ce9a1a8809f5e584e704b82685dcb"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:913829534200eb0f789d45349e55203a091f45c37a2674678744ae52fae23efa"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ef9f7768395923c3039055c14334ba4d926f3baf7b776c923c93d80195624782"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88a19f62ff30117e706ebc9090b8ecc79aeb77d0b1f5ec10d2d27a12bc9f66d0"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e17c9361d46a4d5addf777c6dd5eab0715a7684c2f11b88c67ac37edfba6c482"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a74a13a4c857a84a845505fd2d68e54826a2cd01935a96efb1e9d86c728e186"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41f7ce59d6ee7741af71d82020346af364949314ed3d87553763a2df1829cc58"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f52a265001d830bc425f82ca9eabda94a64a4d753b07d623a9f2863fde532b53"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:82123d0c954dc58db301f5021a01854a85bf1f3bb7d12ae0c01afc414a882ca2"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:2ec9bbba33b2d00999af4631a3397d1fd78290c48e2a3e52d8dd72db3a067ac8"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:fbd6748e8ab9b41171bb95c6142faf068f5ef1511935a0aa07025438dd9a9bc1"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:877d209b6aebeb5b16c42cbb377f5f94d9e556626b1bfff66d7b0d115be88d0a"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:b464c4ab4bfcb41e3bfd3f1c26600d038376c2de3297760dfe064d2cb7ea8e10"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8d39d351e7faf01483cc7ff7c0213c412e38e5a340238826be7e0e4da450fdc8"}, + {file = "yarl-1.18.3-cp313-cp313-win32.whl", hash = "sha256:61ee62ead9b68b9123ec24bc866cbef297dd266175d53296e2db5e7f797f902d"}, + {file = "yarl-1.18.3-cp313-cp313-win_amd64.whl", hash = "sha256:578e281c393af575879990861823ef19d66e2b1d0098414855dd367e234f5b3c"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:61e5e68cb65ac8f547f6b5ef933f510134a6bf31bb178be428994b0cb46c2a04"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:fe57328fbc1bfd0bd0514470ac692630f3901c0ee39052ae47acd1d90a436719"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a440a2a624683108a1b454705ecd7afc1c3438a08e890a1513d468671d90a04e"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:09c7907c8548bcd6ab860e5f513e727c53b4a714f459b084f6580b49fa1b9cee"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b4f6450109834af88cb4cc5ecddfc5380ebb9c228695afc11915a0bf82116789"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9ca04806f3be0ac6d558fffc2fdf8fcef767e0489d2684a21912cc4ed0cd1b8"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77a6e85b90a7641d2e07184df5557132a337f136250caafc9ccaa4a2a998ca2c"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6333c5a377c8e2f5fae35e7b8f145c617b02c939d04110c76f29ee3676b5f9a5"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:0b3c92fa08759dbf12b3a59579a4096ba9af8dd344d9a813fc7f5070d86bbab1"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:4ac515b860c36becb81bb84b667466885096b5fc85596948548b667da3bf9f24"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:045b8482ce9483ada4f3f23b3774f4e1bf4f23a2d5c912ed5170f68efb053318"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:a4bb030cf46a434ec0225bddbebd4b89e6471814ca851abb8696170adb163985"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:54d6921f07555713b9300bee9c50fb46e57e2e639027089b1d795ecd9f7fa910"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1d407181cfa6e70077df3377938c08012d18893f9f20e92f7d2f314a437c30b1"}, + {file = "yarl-1.18.3-cp39-cp39-win32.whl", hash = "sha256:ac36703a585e0929b032fbaab0707b75dc12703766d0b53486eabd5139ebadd5"}, + {file = "yarl-1.18.3-cp39-cp39-win_amd64.whl", hash = "sha256:ba87babd629f8af77f557b61e49e7c7cac36f22f871156b91e10a6e9d4f829e9"}, + {file = "yarl-1.18.3-py3-none-any.whl", hash = "sha256:b57f4f58099328dfb26c6a771d09fb20dbbae81d20cfb66141251ea063bd101b"}, + {file = "yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1"}, ] [package.dependencies] @@ -4833,13 +4951,13 @@ propcache = ">=0.2.0" [[package]] name = "zipp" -version = "3.20.2" +version = "3.21.0" description = "Backport of pathlib-compatible object wrapper for zip files" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"}, - {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"}, + {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"}, + {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"}, ] [package.extras] @@ -4853,4 +4971,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "e0b37255a15bdc97b4f164a1c0af09bc89b812aebff988e0ff9728038a09a4b3" +content-hash = "281ab0dd41e4fc73f4d91dab9dbfccf0282c4eb34068f3059f28b9b67aec40e0" diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml index cab42740df9b6..85bb4fc724e41 100644 --- a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -1,10 +1,10 @@ [build-system] -requires = ["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain" -version = "0.3.7" +version = "0.3.10" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -12,12 +12,12 @@ readme = "README.md" repository = "https://github.com/langchain-ai/langchain" [tool.ruff] -exclude = ["tests/integration_tests/examples/non-utf8-encoding.py"] +exclude = [ "tests/integration_tests/examples/non-utf8-encoding.py",] [tool.mypy] ignore_missing_imports = "True" disallow_untyped_defs = "True" -exclude = ["notebooks", "examples", "example_data"] +exclude = [ "notebooks", "examples", "example_data",] [tool.codespell] skip = ".git,*.pdf,*.svg,*.pdf,*.yaml,*.ipynb,poetry.lock,*.min.js,*.css,package-lock.json,example_data,_dist,examples,*.trig" @@ -33,7 +33,7 @@ langchain-server = "langchain.server:main" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.15" +langchain-core = "^0.3.22" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" pydantic = "^2.7.4" @@ -47,28 +47,20 @@ version = ">=1.22.4,<2" python = "<3.12" [[tool.poetry.dependencies.numpy]] -version = ">=1.26.2,<2" +version = ">=1.26.2,<3" python = ">=3.12" [tool.ruff.lint] -select = ["E", "F", "I", "T201"] +select = [ "E", "F", "I", "T201",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--strict-markers --strict-config --durations=5 --snapshot-warn-unused -vv" -markers = [ - "requires: mark tests as requiring a specific library", - "scheduled: mark tests to run in scheduled testing", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "scheduled: mark tests to run in scheduled testing", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" -filterwarnings = [ - "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", - "ignore::langchain_core._api.deprecation.LangChainDeprecationWarning:tests", - "ignore::langchain_core._api.deprecation.LangChainPendingDeprecationWarning:tests", -] +filterwarnings = [ "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", "ignore::langchain_core._api.deprecation.LangChainDeprecationWarning:tests", "ignore::langchain_core._api.deprecation.LangChainPendingDeprecationWarning:tests",] [tool.poetry.dependencies.async-timeout] version = "^4.0.0" diff --git a/libs/langchain/tests/integration_tests/embeddings/__init__.py b/libs/langchain/tests/integration_tests/embeddings/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/libs/langchain/tests/integration_tests/embeddings/test_base.py b/libs/langchain/tests/integration_tests/embeddings/test_base.py new file mode 100644 index 0000000000000..204754642fdf5 --- /dev/null +++ b/libs/langchain/tests/integration_tests/embeddings/test_base.py @@ -0,0 +1,44 @@ +"""Test embeddings base module.""" + +import importlib + +import pytest +from langchain_core.embeddings import Embeddings + +from langchain.embeddings.base import _SUPPORTED_PROVIDERS, init_embeddings + + +@pytest.mark.parametrize( + "provider, model", + [ + ("openai", "text-embedding-3-large"), + ("google_vertexai", "text-embedding-gecko@003"), + ("bedrock", "amazon.titan-embed-text-v1"), + ("cohere", "embed-english-v2.0"), + ], +) +async def test_init_embedding_model(provider: str, model: str) -> None: + package = _SUPPORTED_PROVIDERS[provider] + try: + importlib.import_module(package) + except ImportError: + pytest.skip(f"Package {package} is not installed") + + model_colon = init_embeddings(f"{provider}:{model}") + assert isinstance(model_colon, Embeddings) + + model_explicit = init_embeddings( + model=model, + provider=provider, + ) + assert isinstance(model_explicit, Embeddings) + + text = "Hello world" + + embedding_colon = await model_colon.aembed_query(text) + assert isinstance(embedding_colon, list) + assert all(isinstance(x, float) for x in embedding_colon) + + embedding_explicit = await model_explicit.aembed_query(text) + assert isinstance(embedding_explicit, list) + assert all(isinstance(x, float) for x in embedding_explicit) diff --git a/libs/langchain/tests/unit_tests/chat_models/test_base.py b/libs/langchain/tests/unit_tests/chat_models/test_base.py index fd5e3e80f21fd..c06e844073150 100644 --- a/libs/langchain/tests/unit_tests/chat_models/test_base.py +++ b/libs/langchain/tests/unit_tests/chat_models/test_base.py @@ -1,4 +1,5 @@ import os +from typing import Optional from unittest import mock import pytest @@ -26,7 +27,6 @@ def test_all_imports() -> None: "langchain_openai", "langchain_anthropic", "langchain_fireworks", - "langchain_mistralai", "langchain_groq", ) @pytest.mark.parametrize( @@ -38,10 +38,14 @@ def test_all_imports() -> None: ("mixtral-8x7b-32768", "groq"), ], ) -def test_init_chat_model(model_name: str, model_provider: str) -> None: - _: BaseChatModel = init_chat_model( +def test_init_chat_model(model_name: str, model_provider: Optional[str]) -> None: + llm1: BaseChatModel = init_chat_model( model_name, model_provider=model_provider, api_key="foo" ) + llm2: BaseChatModel = init_chat_model( + f"{model_provider}:{model_name}", api_key="foo" + ) + assert llm1.dict() == llm2.dict() def test_init_missing_dep() -> None: diff --git a/libs/langchain/tests/unit_tests/embeddings/test_base.py b/libs/langchain/tests/unit_tests/embeddings/test_base.py new file mode 100644 index 0000000000000..5ca919497458b --- /dev/null +++ b/libs/langchain/tests/unit_tests/embeddings/test_base.py @@ -0,0 +1,111 @@ +"""Test embeddings base module.""" + +import pytest + +from langchain.embeddings.base import ( + _SUPPORTED_PROVIDERS, + _infer_model_and_provider, + _parse_model_string, +) + + +def test_parse_model_string() -> None: + """Test parsing model strings into provider and model components.""" + assert _parse_model_string("openai:text-embedding-3-small") == ( + "openai", + "text-embedding-3-small", + ) + assert _parse_model_string("bedrock:amazon.titan-embed-text-v1") == ( + "bedrock", + "amazon.titan-embed-text-v1", + ) + assert _parse_model_string("huggingface:BAAI/bge-base-en:v1.5") == ( + "huggingface", + "BAAI/bge-base-en:v1.5", + ) + + +def test_parse_model_string_errors() -> None: + """Test error cases for model string parsing.""" + with pytest.raises(ValueError, match="Model name must be"): + _parse_model_string("just-a-model-name") + + with pytest.raises(ValueError, match="Invalid model format "): + _parse_model_string("") + + with pytest.raises(ValueError, match="is not supported"): + _parse_model_string(":model-name") + + with pytest.raises(ValueError, match="Model name cannot be empty"): + _parse_model_string("openai:") + + with pytest.raises( + ValueError, match="Provider 'invalid-provider' is not supported" + ): + _parse_model_string("invalid-provider:model-name") + + for provider in _SUPPORTED_PROVIDERS: + with pytest.raises(ValueError, match=f"{provider}"): + _parse_model_string("invalid-provider:model-name") + + +def test_infer_model_and_provider() -> None: + """Test model and provider inference from different input formats.""" + assert _infer_model_and_provider("openai:text-embedding-3-small") == ( + "openai", + "text-embedding-3-small", + ) + + assert _infer_model_and_provider( + model="text-embedding-3-small", provider="openai" + ) == ("openai", "text-embedding-3-small") + + assert _infer_model_and_provider( + model="ft:text-embedding-3-small", provider="openai" + ) == ("openai", "ft:text-embedding-3-small") + + assert _infer_model_and_provider(model="openai:ft:text-embedding-3-small") == ( + "openai", + "ft:text-embedding-3-small", + ) + + +def test_infer_model_and_provider_errors() -> None: + """Test error cases for model and provider inference.""" + # Test missing provider + with pytest.raises(ValueError, match="Must specify either"): + _infer_model_and_provider("text-embedding-3-small") + + # Test empty model + with pytest.raises(ValueError, match="Model name cannot be empty"): + _infer_model_and_provider("") + + # Test empty provider with model + with pytest.raises(ValueError, match="Must specify either"): + _infer_model_and_provider("model", provider="") + + # Test invalid provider + with pytest.raises(ValueError, match="is not supported"): + _infer_model_and_provider("model", provider="invalid") + + # Test provider list is in error + with pytest.raises(ValueError) as exc: + _infer_model_and_provider("model", provider="invalid") + for provider in _SUPPORTED_PROVIDERS: + assert provider in str(exc.value) + + +@pytest.mark.parametrize( + "provider", + sorted(_SUPPORTED_PROVIDERS.keys()), +) +def test_supported_providers_package_names(provider: str) -> None: + """Test that all supported providers have valid package names.""" + package = _SUPPORTED_PROVIDERS[provider] + assert "-" not in package + assert package.startswith("langchain_") + assert package.islower() + + +def test_is_sorted() -> None: + assert list(_SUPPORTED_PROVIDERS) == sorted(_SUPPORTED_PROVIDERS.keys()) diff --git a/libs/langchain/tests/unit_tests/embeddings/test_imports.py b/libs/langchain/tests/unit_tests/embeddings/test_imports.py index c6d7a8207d1c5..b44acf1a6032d 100644 --- a/libs/langchain/tests/unit_tests/embeddings/test_imports.py +++ b/libs/langchain/tests/unit_tests/embeddings/test_imports.py @@ -55,6 +55,7 @@ "JohnSnowLabsEmbeddings", "VoyageEmbeddings", "BookendEmbeddings", + "init_embeddings", ] diff --git a/libs/langchain/tests/unit_tests/output_parsers/test_fix.py b/libs/langchain/tests/unit_tests/output_parsers/test_fix.py index a8961663925ef..98fe71bce6e27 100644 --- a/libs/langchain/tests/unit_tests/output_parsers/test_fix.py +++ b/libs/langchain/tests/unit_tests/output_parsers/test_fix.py @@ -50,7 +50,7 @@ def test_output_fixing_parser_parse( base_parser.attemp_count_before_success ) # Success on the (n+1)-th attempt # noqa base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n) - parser = OutputFixingParser( + parser = OutputFixingParser[str]( parser=base_parser, max_retries=n, # n times to retry, that is, (n+1) times call retry_chain=RunnablePassthrough(), @@ -94,7 +94,7 @@ async def test_output_fixing_parser_aparse( base_parser.attemp_count_before_success ) # Success on the (n+1)-th attempt # noqa base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n) - parser = OutputFixingParser( + parser = OutputFixingParser[str]( parser=base_parser, max_retries=n, # n times to retry, that is, (n+1) times call retry_chain=RunnablePassthrough(), @@ -108,7 +108,7 @@ async def test_output_fixing_parser_aparse( def test_output_fixing_parser_parse_fail() -> None: n: int = 5 # Success on the (n+1)-th attempt base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n) - parser = OutputFixingParser( + parser = OutputFixingParser[str]( parser=base_parser, max_retries=n - 1, # n-1 times to retry, that is, n times call retry_chain=RunnablePassthrough(), @@ -122,7 +122,7 @@ def test_output_fixing_parser_parse_fail() -> None: async def test_output_fixing_parser_aparse_fail() -> None: n: int = 5 # Success on the (n+1)-th attempt base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n) - parser = OutputFixingParser( + parser = OutputFixingParser[str]( parser=base_parser, max_retries=n - 1, # n-1 times to retry, that is, n times call retry_chain=RunnablePassthrough(), @@ -143,7 +143,9 @@ async def test_output_fixing_parser_aparse_fail() -> None: def test_output_fixing_parser_output_type( base_parser: BaseOutputParser, ) -> None: - parser = OutputFixingParser(parser=base_parser, retry_chain=RunnablePassthrough()) + parser = OutputFixingParser[str]( + parser=base_parser, retry_chain=RunnablePassthrough() + ) assert parser.OutputType is base_parser.OutputType @@ -176,7 +178,7 @@ def test_output_fixing_parser_parse_with_retry_chain( instructions = base_parser.get_format_instructions() object.__setattr__(base_parser, "get_format_instructions", lambda: instructions) # test - parser = OutputFixingParser( + parser = OutputFixingParser[str]( parser=base_parser, retry_chain=retry_chain, legacy=False, @@ -212,7 +214,7 @@ async def test_output_fixing_parser_aparse_with_retry_chain( instructions = base_parser.get_format_instructions() object.__setattr__(base_parser, "get_format_instructions", lambda: instructions) # test - parser = OutputFixingParser( + parser = OutputFixingParser[str]( parser=base_parser, retry_chain=retry_chain, legacy=False, diff --git a/libs/packages.yml b/libs/packages.yml index 388f307b8dfc8..7be568aa646d4 100644 --- a/libs/packages.yml +++ b/libs/packages.yml @@ -68,6 +68,9 @@ packages: - name: langchain-qdrant repo: langchain-ai/langchain path: libs/partners/qdrant + - name: langchain-scrapegraph + repo: ScrapeGraphAI/langchain-scrapegraph + path: . - name: langchain-sema4 repo: langchain-ai/langchain-sema4 path: libs/sema4 @@ -147,3 +150,6 @@ packages: - name: langchain-tests repo: langchain-ai/langchain path: libs/standard-tests + - name: langchain-neo4j + repo: langchain-ai/langchain-neo4j + path: libs/neo4j diff --git a/libs/partners/anthropic/Makefile b/libs/partners/anthropic/Makefile index 7a32f31997ab5..256ab677b83de 100644 --- a/libs/partners/anthropic/Makefile +++ b/libs/partners/anthropic/Makefile @@ -8,7 +8,7 @@ TEST_FILE ?= tests/unit_tests/ integration_test integration_tests: TEST_FILE=tests/integration_tests/ test tests integration_test integration_tests: - poetry run pytest $(TEST_FILE) + poetry run pytest -vvv --timeout 10 $(TEST_FILE) test_watch: poetry run ptw --snapshot-update --now . -- -vv $(TEST_FILE) diff --git a/libs/partners/anthropic/poetry.lock b/libs/partners/anthropic/poetry.lock index 24666fc665745..0770706b18597 100644 --- a/libs/partners/anthropic/poetry.lock +++ b/libs/partners/anthropic/poetry.lock @@ -852,6 +852,20 @@ pytest = ">=6.2.5" [package.extras] dev = ["pre-commit", "pytest-asyncio", "tox"] +[[package]] +name = "pytest-timeout" +version = "2.3.1" +description = "pytest plugin to abort hanging tests" +optional = false +python-versions = ">=3.7" +files = [ + {file = "pytest-timeout-2.3.1.tar.gz", hash = "sha256:12397729125c6ecbdaca01035b9e5239d4db97352320af155b3f5de1ba5165d9"}, + {file = "pytest_timeout-2.3.1-py3-none-any.whl", hash = "sha256:68188cb703edfc6a18fad98dc25a3c61e9f24d644b0b70f33af545219fc7813e"}, +] + +[package.dependencies] +pytest = ">=7.0.0" + [[package]] name = "pytest-watcher" version = "0.3.5" @@ -1140,4 +1154,4 @@ watchmedo = ["PyYAML (>=3.10)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "ee4aaa06307b4dc7f7913147bf58f3f36245193c9d4a79c43aba07641f7b6ab9" +content-hash = "7d24a5eb5b867fa9ad80cbc9fb80d630e7cb00a490b62502cdb57c2fe95cd125" diff --git a/libs/partners/anthropic/pyproject.toml b/libs/partners/anthropic/pyproject.toml index cda312230357f..b6ff159efccb9 100644 --- a/libs/partners/anthropic/pyproject.toml +++ b/libs/partners/anthropic/pyproject.toml @@ -65,6 +65,7 @@ syrupy = "^4.0.2" pytest-watcher = "^0.3.4" pytest-asyncio = "^0.21.1" defusedxml = "^0.7.1" +pytest-timeout = "^2.3.1" [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" diff --git a/libs/partners/anthropic/tests/integration_tests/test_chat_models.py b/libs/partners/anthropic/tests/integration_tests/test_chat_models.py index 5c2295492632d..8ff2396c9d1c9 100644 --- a/libs/partners/anthropic/tests/integration_tests/test_chat_models.py +++ b/libs/partners/anthropic/tests/integration_tests/test_chat_models.py @@ -22,7 +22,7 @@ from langchain_anthropic import ChatAnthropic, ChatAnthropicMessages from tests.unit_tests._utils import FakeCallbackHandler -MODEL_NAME = "claude-3-sonnet-20240229" +MODEL_NAME = "claude-3-5-sonnet-20240620" def test_stream() -> None: diff --git a/libs/partners/chroma/langchain_chroma/vectorstores.py b/libs/partners/chroma/langchain_chroma/vectorstores.py index 35146fdcc7603..afb9191c60a31 100644 --- a/libs/partners/chroma/langchain_chroma/vectorstores.py +++ b/libs/partners/chroma/langchain_chroma/vectorstores.py @@ -16,6 +16,7 @@ Iterable, List, Optional, + Sequence, Tuple, Type, Union, @@ -44,15 +45,30 @@ def _results_to_docs_and_scores(results: Any) -> List[Tuple[Document, float]]: return [ # TODO: Chroma can do batch querying, # we shouldn't hard code to the 1st result - (Document(page_content=result[0], metadata=result[1] or {}), result[2]) + ( + Document(page_content=result[0], metadata=result[1] or {}, id=result[2]), + result[3], + ) for result in zip( results["documents"][0], results["metadatas"][0], + results["ids"][0], results["distances"][0], ) ] +def _results_to_docs_and_vectors(results: Any) -> List[Tuple[Document, np.ndarray]]: + return [ + (Document(page_content=result[0], metadata=result[1] or {}), result[2]) + for result in zip( + results["documents"][0], + results["metadatas"][0], + results["embeddings"][0], + ) + ] + + Matrix = Union[List[List[float]], List[np.ndarray], np.ndarray] @@ -502,6 +518,11 @@ def add_texts( """ if ids is None: ids = [str(uuid.uuid4()) for _ in texts] + else: + # Assign strings to any null IDs + for idx, _id in enumerate(ids): + if _id is None: + ids[idx] = str(uuid.uuid4()) embeddings = None texts = list(texts) if self._embedding_function is not None: @@ -687,12 +708,57 @@ def similarity_search_with_score( return _results_to_docs_and_scores(results) + def similarity_search_with_vectors( + self, + query: str, + k: int = DEFAULT_K, + filter: Optional[Dict[str, str]] = None, + where_document: Optional[Dict[str, str]] = None, + **kwargs: Any, + ) -> List[Tuple[Document, np.ndarray]]: + """Run similarity search with Chroma with vectors. + + Args: + query: Query text to search for. + k: Number of results to return. Defaults to 4. + filter: Filter by metadata. Defaults to None. + where_document: dict used to filter by the documents. + E.g. {$contains: {"text": "hello"}}. + kwargs: Additional keyword arguments to pass to Chroma collection query. + + Returns: + List of documents most similar to the query text and + embedding vectors for each. + """ + include = ["documents", "metadatas", "embeddings"] + if self._embedding_function is None: + results = self.__query_collection( + query_texts=[query], + n_results=k, + where=filter, + where_document=where_document, + include=include, + **kwargs, + ) + else: + query_embedding = self._embedding_function.embed_query(query) + results = self.__query_collection( + query_embeddings=[query_embedding], + n_results=k, + where=filter, + where_document=where_document, + include=include, + **kwargs, + ) + + return _results_to_docs_and_vectors(results) + def _select_relevance_score_fn(self) -> Callable[[float], float]: """Select the relevance score function based on collections distance metric. The most similar documents will have the lowest relevance score. Default relevance score function is euclidean distance. Distance metric must be - provided in `collection_metadata` during initizalition of Chroma object. + provided in `collection_metadata` during initialization of Chroma object. Example: collection_metadata={"hnsw:space": "cosine"}. Available distance metrics are: 'cosine', 'l2' and 'ip'. @@ -968,6 +1034,38 @@ def get( return self._collection.get(**kwargs) # type: ignore + def get_by_ids(self, ids: Sequence[str], /) -> list[Document]: + """Get documents by their IDs. + + The returned documents are expected to have the ID field set to the ID of the + document in the vector store. + + Fewer documents may be returned than requested if some IDs are not found or + if there are duplicated IDs. + + Users should not assume that the order of the returned documents matches + the order of the input IDs. Instead, users should rely on the ID field of the + returned documents. + + This method should **NOT** raise exceptions if no documents are found for + some IDs. + + Args: + ids: List of ids to retrieve. + + Returns: + List of Documents. + + .. versionadded:: 0.2.1 + """ + results = self.get(ids=list(ids)) + return [ + Document(page_content=doc, metadata=meta, id=doc_id) + for doc, meta, doc_id in zip( + results["documents"], results["metadatas"], results["ids"] + ) + ] + def update_document(self, document_id: str, document: Document) -> None: """Update a document in the collection. @@ -1129,6 +1227,8 @@ def from_documents( """ texts = [doc.page_content for doc in documents] metadatas = [doc.metadata for doc in documents] + if ids is None: + ids = [doc.id if doc.id else str(uuid.uuid4()) for doc in documents] return cls.from_texts( texts=texts, embedding=embedding, diff --git a/libs/partners/chroma/poetry.lock b/libs/partners/chroma/poetry.lock index 19729f51db44d..f4b4192f448a0 100644 --- a/libs/partners/chroma/poetry.lock +++ b/libs/partners/chroma/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. [[package]] name = "annotated-types" @@ -932,7 +932,7 @@ adal = ["adal (>=1.0.2)"] [[package]] name = "langchain-core" -version = "0.3.15" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -955,6 +955,25 @@ typing-extensions = ">=4.7" type = "directory" url = "../../core" +[[package]] +name = "langchain-tests" +version = "0.3.4" +description = "Standard tests for LangChain implementations" +optional = false +python-versions = ">=3.9,<4.0" +files = [] +develop = true + +[package.dependencies] +httpx = "^0.27.0" +langchain-core = "^0.3.19" +pytest = ">=7,<9" +syrupy = "^4" + +[package.source] +type = "directory" +url = "../../standard-tests" + [[package]] name = "langsmith" version = "0.1.139" @@ -2259,111 +2278,26 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tokenizers" -version = "0.20.1" +version = "0.21.0" description = "" optional = false python-versions = ">=3.7" files = [ - {file = "tokenizers-0.20.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:439261da7c0a5c88bda97acb284d49fbdaf67e9d3b623c0bfd107512d22787a9"}, - {file = "tokenizers-0.20.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:03dae629d99068b1ea5416d50de0fea13008f04129cc79af77a2a6392792d93c"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b61f561f329ffe4b28367798b89d60c4abf3f815d37413b6352bc6412a359867"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ec870fce1ee5248a10be69f7a8408a234d6f2109f8ea827b4f7ecdbf08c9fd15"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d388d1ea8b7447da784e32e3b86a75cce55887e3b22b31c19d0b186b1c677800"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:299c85c1d21135bc01542237979bf25c32efa0d66595dd0069ae259b97fb2dbe"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e96f6c14c9752bb82145636b614d5a78e9cde95edfbe0a85dad0dd5ddd6ec95c"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc9e95ad49c932b80abfbfeaf63b155761e695ad9f8a58c52a47d962d76e310f"}, - {file = "tokenizers-0.20.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:f22dee205329a636148c325921c73cf3e412e87d31f4d9c3153b302a0200057b"}, - {file = "tokenizers-0.20.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a2ffd9a8895575ac636d44500c66dffaef133823b6b25067604fa73bbc5ec09d"}, - {file = "tokenizers-0.20.1-cp310-none-win32.whl", hash = "sha256:2847843c53f445e0f19ea842a4e48b89dd0db4e62ba6e1e47a2749d6ec11f50d"}, - {file = "tokenizers-0.20.1-cp310-none-win_amd64.whl", hash = "sha256:f9aa93eacd865f2798b9e62f7ce4533cfff4f5fbd50c02926a78e81c74e432cd"}, - {file = "tokenizers-0.20.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4a717dcb08f2dabbf27ae4b6b20cbbb2ad7ed78ce05a829fae100ff4b3c7ff15"}, - {file = "tokenizers-0.20.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3f84dad1ff1863c648d80628b1b55353d16303431283e4efbb6ab1af56a75832"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:929c8f3afa16a5130a81ab5079c589226273ec618949cce79b46d96e59a84f61"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d10766473954397e2d370f215ebed1cc46dcf6fd3906a2a116aa1d6219bfedc3"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9300fac73ddc7e4b0330acbdda4efaabf74929a4a61e119a32a181f534a11b47"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0ecaf7b0e39caeb1aa6dd6e0975c405716c82c1312b55ac4f716ef563a906969"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5170be9ec942f3d1d317817ced8d749b3e1202670865e4fd465e35d8c259de83"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ef3f1ae08fa9aea5891cbd69df29913e11d3841798e0bfb1ff78b78e4e7ea0a4"}, - {file = "tokenizers-0.20.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:ee86d4095d3542d73579e953c2e5e07d9321af2ffea6ecc097d16d538a2dea16"}, - {file = "tokenizers-0.20.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:86dcd08da163912e17b27bbaba5efdc71b4fbffb841530fdb74c5707f3c49216"}, - {file = "tokenizers-0.20.1-cp311-none-win32.whl", hash = "sha256:9af2dc4ee97d037bc6b05fa4429ddc87532c706316c5e11ce2f0596dfcfa77af"}, - {file = "tokenizers-0.20.1-cp311-none-win_amd64.whl", hash = "sha256:899152a78b095559c287b4c6d0099469573bb2055347bb8154db106651296f39"}, - {file = "tokenizers-0.20.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:407ab666b38e02228fa785e81f7cf79ef929f104bcccf68a64525a54a93ceac9"}, - {file = "tokenizers-0.20.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2f13a2d16032ebc8bd812eb8099b035ac65887d8f0c207261472803b9633cf3e"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e98eee4dca22849fbb56a80acaa899eec5b72055d79637dd6aa15d5e4b8628c9"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:47c1bcdd61e61136087459cb9e0b069ff23b5568b008265e5cbc927eae3387ce"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:128c1110e950534426e2274837fc06b118ab5f2fa61c3436e60e0aada0ccfd67"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e2e2d47a819d2954f2c1cd0ad51bb58ffac6f53a872d5d82d65d79bf76b9896d"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bdd67a0e3503a9a7cf8bc5a4a49cdde5fa5bada09a51e4c7e1c73900297539bd"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:689b93d2e26d04da337ac407acec8b5d081d8d135e3e5066a88edd5bdb5aff89"}, - {file = "tokenizers-0.20.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:0c6a796ddcd9a19ad13cf146997cd5895a421fe6aec8fd970d69f9117bddb45c"}, - {file = "tokenizers-0.20.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:3ea919687aa7001a8ff1ba36ac64f165c4e89035f57998fa6cedcfd877be619d"}, - {file = "tokenizers-0.20.1-cp312-none-win32.whl", hash = "sha256:6d3ac5c1f48358ffe20086bf065e843c0d0a9fce0d7f0f45d5f2f9fba3609ca5"}, - {file = "tokenizers-0.20.1-cp312-none-win_amd64.whl", hash = "sha256:b0874481aea54a178f2bccc45aa2d0c99cd3f79143a0948af6a9a21dcc49173b"}, - {file = "tokenizers-0.20.1-cp37-cp37m-macosx_10_12_x86_64.whl", hash = "sha256:96af92e833bd44760fb17f23f402e07a66339c1dcbe17d79a9b55bb0cc4f038e"}, - {file = "tokenizers-0.20.1-cp37-cp37m-macosx_11_0_arm64.whl", hash = "sha256:65f34e5b731a262dfa562820818533c38ce32a45864437f3d9c82f26c139ca7f"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:17f98fccb5c12ab1ce1f471731a9cd86df5d4bd2cf2880c5a66b229802d96145"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b8c0fc3542cf9370bf92c932eb71bdeb33d2d4aeeb4126d9fd567b60bd04cb30"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4b39356df4575d37f9b187bb623aab5abb7b62c8cb702867a1768002f814800c"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bfdad27b0e50544f6b838895a373db6114b85112ba5c0cefadffa78d6daae563"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:094663dd0e85ee2e573126918747bdb40044a848fde388efb5b09d57bc74c680"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:14e4cf033a2aa207d7ac790e91adca598b679999710a632c4a494aab0fc3a1b2"}, - {file = "tokenizers-0.20.1-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:9310951c92c9fb91660de0c19a923c432f110dbfad1a2d429fbc44fa956bf64f"}, - {file = "tokenizers-0.20.1-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:05e41e302c315bd2ed86c02e917bf03a6cf7d2f652c9cee1a0eb0d0f1ca0d32c"}, - {file = "tokenizers-0.20.1-cp37-none-win32.whl", hash = "sha256:212231ab7dfcdc879baf4892ca87c726259fa7c887e1688e3f3cead384d8c305"}, - {file = "tokenizers-0.20.1-cp37-none-win_amd64.whl", hash = "sha256:896195eb9dfdc85c8c052e29947169c1fcbe75a254c4b5792cdbd451587bce85"}, - {file = "tokenizers-0.20.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:741fb22788482d09d68e73ece1495cfc6d9b29a06c37b3df90564a9cfa688e6d"}, - {file = "tokenizers-0.20.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:10be14ebd8082086a342d969e17fc2d6edc856c59dbdbddd25f158fa40eaf043"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:514cf279b22fa1ae0bc08e143458c74ad3b56cd078b319464959685a35c53d5e"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a647c5b7cb896d6430cf3e01b4e9a2d77f719c84cefcef825d404830c2071da2"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7cdf379219e1e1dd432091058dab325a2e6235ebb23e0aec8d0508567c90cd01"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ba72260449e16c4c2f6f3252823b059fbf2d31b32617e582003f2b18b415c39"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:910b96ed87316e4277b23c7bcaf667ce849c7cc379a453fa179e7e09290eeb25"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e53975a6694428a0586534cc1354b2408d4e010a3103117f617cbb550299797c"}, - {file = "tokenizers-0.20.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:07c4b7be58da142b0730cc4e5fd66bb7bf6f57f4986ddda73833cd39efef8a01"}, - {file = "tokenizers-0.20.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b605c540753e62199bf15cf69c333e934077ef2350262af2ccada46026f83d1c"}, - {file = "tokenizers-0.20.1-cp38-none-win32.whl", hash = "sha256:88b3bc76ab4db1ab95ead623d49c95205411e26302cf9f74203e762ac7e85685"}, - {file = "tokenizers-0.20.1-cp38-none-win_amd64.whl", hash = "sha256:d412a74cf5b3f68a90c615611a5aa4478bb303d1c65961d22db45001df68afcb"}, - {file = "tokenizers-0.20.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a25dcb2f41a0a6aac31999e6c96a75e9152fa0127af8ece46c2f784f23b8197a"}, - {file = "tokenizers-0.20.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a12c3cebb8c92e9c35a23ab10d3852aee522f385c28d0b4fe48c0b7527d59762"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:02e18da58cf115b7c40de973609c35bde95856012ba42a41ee919c77935af251"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f326a1ac51ae909b9760e34671c26cd0dfe15662f447302a9d5bb2d872bab8ab"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0b4872647ea6f25224e2833b044b0b19084e39400e8ead3cfe751238b0802140"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ce6238a3311bb8e4c15b12600927d35c267b92a52c881ef5717a900ca14793f7"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:57b7a8880b208866508b06ce365dc631e7a2472a3faa24daa430d046fb56c885"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a908c69c2897a68f412aa05ba38bfa87a02980df70f5a72fa8490479308b1f2d"}, - {file = "tokenizers-0.20.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:da1001aa46f4490099c82e2facc4fbc06a6a32bf7de3918ba798010954b775e0"}, - {file = "tokenizers-0.20.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:42c097390e2f0ed0a5c5d569e6669dd4e9fff7b31c6a5ce6e9c66a61687197de"}, - {file = "tokenizers-0.20.1-cp39-none-win32.whl", hash = "sha256:3d4d218573a3d8b121a1f8c801029d70444ffb6d8f129d4cca1c7b672ee4a24c"}, - {file = "tokenizers-0.20.1-cp39-none-win_amd64.whl", hash = "sha256:37d1e6f616c84fceefa7c6484a01df05caf1e207669121c66213cb5b2911d653"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:48689da7a395df41114f516208d6550e3e905e1239cc5ad386686d9358e9cef0"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:712f90ea33f9bd2586b4a90d697c26d56d0a22fd3c91104c5858c4b5b6489a79"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:359eceb6a620c965988fc559cebc0a98db26713758ec4df43fb76d41486a8ed5"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d3caf244ce89d24c87545aafc3448be15870096e796c703a0d68547187192e1"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03b03cf8b9a32254b1bf8a305fb95c6daf1baae0c1f93b27f2b08c9759f41dee"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:218e5a3561561ea0f0ef1559c6d95b825308dbec23fb55b70b92589e7ff2e1e8"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f40df5e0294a95131cc5f0e0eb91fe86d88837abfbee46b9b3610b09860195a7"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-macosx_10_12_x86_64.whl", hash = "sha256:08aaa0d72bb65058e8c4b0455f61b840b156c557e2aca57627056624c3a93976"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:998700177b45f70afeb206ad22c08d9e5f3a80639dae1032bf41e8cbc4dada4b"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:62f7fbd3c2c38b179556d879edae442b45f68312019c3a6013e56c3947a4e648"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:31e87fca4f6bbf5cc67481b562147fe932f73d5602734de7dd18a8f2eee9c6dd"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:956f21d359ae29dd51ca5726d2c9a44ffafa041c623f5aa33749da87cfa809b9"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:1fbbaf17a393c78d8aedb6a334097c91cb4119a9ced4764ab8cfdc8d254dc9f9"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-macosx_10_12_x86_64.whl", hash = "sha256:ebe63e31f9c1a970c53866d814e35ec2ec26fda03097c486f82f3891cee60830"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-macosx_11_0_arm64.whl", hash = "sha256:81970b80b8ac126910295f8aab2d7ef962009ea39e0d86d304769493f69aaa1e"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:130e35e76f9337ed6c31be386e75d4925ea807055acf18ca1a9b0eec03d8fe23"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:cd28a8614f5c82a54ab2463554e84ad79526c5184cf4573bbac2efbbbcead457"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9041ee665d0fa7f5c4ccf0f81f5e6b7087f797f85b143c094126fc2611fec9d0"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:62eb9daea2a2c06bcd8113a5824af8ef8ee7405d3a71123ba4d52c79bb3d9f1a"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f861889707b54a9ab1204030b65fd6c22bdd4a95205deec7994dc22a8baa2ea4"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:89d5c337d74ea6e5e7dc8af124cf177be843bbb9ca6e58c01f75ea103c12c8a9"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:0b7f515c83397e73292accdbbbedc62264e070bae9682f06061e2ddce67cacaf"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3e0305fc1ec6b1e5052d30d9c1d5c807081a7bd0cae46a33d03117082e91908c"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5dc611e6ac0fa00a41de19c3bf6391a05ea201d2d22b757d63f5491ec0e67faa"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c5ffe0d7f7bfcfa3b2585776ecf11da2e01c317027c8573c78ebcb8985279e23"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:e7edb8ec12c100d5458d15b1e47c0eb30ad606a05641f19af7563bc3d1608c14"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:de291633fb9303555793cc544d4a86e858da529b7d0b752bcaf721ae1d74b2c9"}, - {file = "tokenizers-0.20.1.tar.gz", hash = "sha256:84edcc7cdeeee45ceedb65d518fffb77aec69311c9c8e30f77ad84da3025f002"}, + {file = "tokenizers-0.21.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:3c4c93eae637e7d2aaae3d376f06085164e1660f89304c0ab2b1d08a406636b2"}, + {file = "tokenizers-0.21.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:f53ea537c925422a2e0e92a24cce96f6bc5046bbef24a1652a5edc8ba975f62e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b177fb54c4702ef611de0c069d9169f0004233890e0c4c5bd5508ae05abf193"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6b43779a269f4629bebb114e19c3fca0223296ae9fea8bb9a7a6c6fb0657ff8e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9aeb255802be90acfd363626753fda0064a8df06031012fe7d52fd9a905eb00e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d8b09dbeb7a8d73ee204a70f94fc06ea0f17dcf0844f16102b9f414f0b7463ba"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:400832c0904f77ce87c40f1a8a27493071282f785724ae62144324f171377273"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e84ca973b3a96894d1707e189c14a774b701596d579ffc7e69debfc036a61a04"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:eb7202d231b273c34ec67767378cd04c767e967fda12d4a9e36208a34e2f137e"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:089d56db6782a73a27fd8abf3ba21779f5b85d4a9f35e3b493c7bbcbbf0d539b"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:c87ca3dc48b9b1222d984b6b7490355a6fdb411a2d810f6f05977258400ddb74"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:4145505a973116f91bc3ac45988a92e618a6f83eb458f49ea0790df94ee243ff"}, + {file = "tokenizers-0.21.0-cp39-abi3-win32.whl", hash = "sha256:eb1702c2f27d25d9dd5b389cc1f2f51813e99f8ca30d9e25348db6585a97e24a"}, + {file = "tokenizers-0.21.0-cp39-abi3-win_amd64.whl", hash = "sha256:87841da5a25a3a5f70c102de371db120f41873b854ba65e52bccd57df5a3780c"}, + {file = "tokenizers-0.21.0.tar.gz", hash = "sha256:ee0894bf311b75b0c03079f33859ae4b2334d675d4e93f5a4132e1eae2834fe4"}, ] [package.dependencies] @@ -2890,4 +2824,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4" -content-hash = "2747536a10c5e463604c0ff0024055c186363e673fe755b01df356deb9800435" +content-hash = "2d6bc4b9a18a322c326c3f7d5786c4b196a997458e6d2ca4043cb6b7a4a123b3" diff --git a/libs/partners/chroma/pyproject.toml b/libs/partners/chroma/pyproject.toml index 3fa59a97f74e3..8a7e18bdf1bf3 100644 --- a/libs/partners/chroma/pyproject.toml +++ b/libs/partners/chroma/pyproject.toml @@ -23,11 +23,11 @@ python = ">=3.9,<4" langchain-core = ">=0.2.43,<0.4.0,!=0.3.0,!=0.3.1,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14" [[tool.poetry.dependencies.numpy]] -version = "^1" +version = "^1.22.4" python = "<3.12" [[tool.poetry.dependencies.numpy]] -version = "^1.26.0" +version = "^1.26.2" python = ">=3.12" [tool.ruff.lint] @@ -90,6 +90,10 @@ python = ">=3.9" version = ">=0.1.40,<0.3" python = "<3.9" +[[tool.poetry.group.test.dependencies.langchain-tests]] +path = "../../standard-tests" +develop = true + [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" diff --git a/libs/partners/chroma/tests/integration_tests/test_standard.py b/libs/partners/chroma/tests/integration_tests/test_standard.py new file mode 100644 index 0000000000000..3e2945cb7fa39 --- /dev/null +++ b/libs/partners/chroma/tests/integration_tests/test_standard.py @@ -0,0 +1,19 @@ +from typing import Generator + +import pytest +from langchain_core.vectorstores import VectorStore +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests + +from langchain_chroma import Chroma + + +class TestChromaStandard(VectorStoreIntegrationTests): + @pytest.fixture() + def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore + """Get an empty vectorstore for unit tests.""" + store = Chroma(embedding_function=self.get_embeddings()) + try: + yield store + finally: + store.delete_collection() + pass diff --git a/libs/partners/chroma/tests/integration_tests/test_vectorstores.py b/libs/partners/chroma/tests/integration_tests/test_vectorstores.py index 4393d5f339b09..f7bed4cfa5588 100644 --- a/libs/partners/chroma/tests/integration_tests/test_vectorstores.py +++ b/libs/partners/chroma/tests/integration_tests/test_vectorstores.py @@ -46,8 +46,43 @@ def test_chroma() -> None: output = docsearch.similarity_search("foo", k=1) docsearch.delete_collection() + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id is not None - assert output == [Document(page_content="foo")] + +def test_from_documents() -> None: + """Test init using .from_documents.""" + documents = [ + Document(page_content="foo"), + Document(page_content="bar"), + Document(page_content="baz"), + ] + docsearch = Chroma.from_documents(documents=documents, embedding=FakeEmbeddings()) + output = docsearch.similarity_search("foo", k=1) + + docsearch.delete_collection() + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id is not None + + +def test_chroma_with_ids() -> None: + """Test end to end construction and search.""" + texts = ["foo", "bar", "baz"] + ids = [f"id_{i}" for i in range(len(texts))] + docsearch = Chroma.from_texts( + collection_name="test_collection", + texts=texts, + embedding=FakeEmbeddings(), + ids=ids, + ) + output = docsearch.similarity_search("foo", k=1) + + docsearch.delete_collection() + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id == "id_0" async def test_chroma_async() -> None: @@ -59,7 +94,27 @@ async def test_chroma_async() -> None: output = await docsearch.asimilarity_search("foo", k=1) docsearch.delete_collection() - assert output == [Document(page_content="foo")] + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id is not None + + +async def test_chroma_async_with_ids() -> None: + """Test end to end construction and search.""" + texts = ["foo", "bar", "baz"] + ids = [f"id_{i}" for i in range(len(texts))] + docsearch = Chroma.from_texts( + collection_name="test_collection", + texts=texts, + embedding=FakeEmbeddings(), + ids=ids, + ) + output = await docsearch.asimilarity_search("foo", k=1) + + docsearch.delete_collection() + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id == "id_0" def test_chroma_with_metadatas() -> None: @@ -74,28 +129,74 @@ def test_chroma_with_metadatas() -> None: ) output = docsearch.similarity_search("foo", k=1) docsearch.delete_collection() - assert output == [Document(page_content="foo", metadata={"page": "0"})] + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].metadata == {"page": "0"} + assert output[0].id is not None -def test_chroma_with_metadatas_with_scores() -> None: +def test_chroma_with_metadatas_and_ids() -> None: + """Test end to end construction and search.""" + texts = ["foo", "bar", "baz"] + metadatas = [{"page": str(i)} for i in range(len(texts))] + ids = [f"id_{i}" for i in range(len(texts))] + docsearch = Chroma.from_texts( + collection_name="test_collection", + texts=texts, + embedding=FakeEmbeddings(), + metadatas=metadatas, + ids=ids, + ) + output = docsearch.similarity_search("foo", k=1) + docsearch.delete_collection() + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].metadata == {"page": "0"} + assert output[0].id == "id_0" + + +def test_chroma_with_metadatas_with_scores_and_ids() -> None: """Test end to end construction and scored search.""" texts = ["foo", "bar", "baz"] metadatas = [{"page": str(i)} for i in range(len(texts))] + ids = [f"id_{i}" for i in range(len(texts))] docsearch = Chroma.from_texts( collection_name="test_collection", texts=texts, embedding=FakeEmbeddings(), metadatas=metadatas, + ids=ids, ) output = docsearch.similarity_search_with_score("foo", k=1) docsearch.delete_collection() - assert output == [(Document(page_content="foo", metadata={"page": "0"}), 0.0)] + assert output == [ + (Document(page_content="foo", metadata={"page": "0"}, id="id_0"), 0.0) + ] + + +def test_chroma_with_metadatas_with_vectors() -> None: + """Test end to end construction and scored search.""" + texts = ["foo", "bar", "baz"] + metadatas = [{"page": str(i)} for i in range(len(texts))] + embeddings = ConsistentFakeEmbeddings() + docsearch = Chroma.from_texts( + collection_name="test_collection", + texts=texts, + embedding=embeddings, + metadatas=metadatas, + ) + vec_1 = embeddings.embed_query(texts[0]) + output = docsearch.similarity_search_with_vectors("foo", k=1) + docsearch.delete_collection() + assert output[0][0] == Document(page_content="foo", metadata={"page": "0"}) + assert (output[0][1] == vec_1).all() def test_chroma_with_metadatas_with_scores_using_vector() -> None: """Test end to end construction and scored search, using embedding vector.""" texts = ["foo", "bar", "baz"] metadatas = [{"page": str(i)} for i in range(len(texts))] + ids = [f"id_{i}" for i in range(len(texts))] embeddings = FakeEmbeddings() docsearch = Chroma.from_texts( @@ -103,41 +204,52 @@ def test_chroma_with_metadatas_with_scores_using_vector() -> None: texts=texts, embedding=embeddings, metadatas=metadatas, + ids=ids, ) embedded_query = embeddings.embed_query("foo") output = docsearch.similarity_search_by_vector_with_relevance_scores( embedding=embedded_query, k=1 ) docsearch.delete_collection() - assert output == [(Document(page_content="foo", metadata={"page": "0"}), 0.0)] + assert output == [ + (Document(page_content="foo", metadata={"page": "0"}, id="id_0"), 0.0) + ] def test_chroma_search_filter() -> None: """Test end to end construction and search with metadata filtering.""" texts = ["far", "bar", "baz"] metadatas = [{"first_letter": "{}".format(text[0])} for text in texts] + ids = [f"id_{i}" for i in range(len(texts))] docsearch = Chroma.from_texts( collection_name="test_collection", texts=texts, embedding=FakeEmbeddings(), metadatas=metadatas, + ids=ids, ) output1 = docsearch.similarity_search("far", k=1, filter={"first_letter": "f"}) output2 = docsearch.similarity_search("far", k=1, filter={"first_letter": "b"}) docsearch.delete_collection() - assert output1 == [Document(page_content="far", metadata={"first_letter": "f"})] - assert output2 == [Document(page_content="bar", metadata={"first_letter": "b"})] + assert output1 == [ + Document(page_content="far", metadata={"first_letter": "f"}, id="id_0") + ] + assert output2 == [ + Document(page_content="bar", metadata={"first_letter": "b"}, id="id_1") + ] def test_chroma_search_filter_with_scores() -> None: """Test end to end construction and scored search with metadata filtering.""" texts = ["far", "bar", "baz"] metadatas = [{"first_letter": "{}".format(text[0])} for text in texts] + ids = [f"id_{i}" for i in range(len(texts))] docsearch = Chroma.from_texts( collection_name="test_collection", texts=texts, embedding=FakeEmbeddings(), metadatas=metadatas, + ids=ids, ) output1 = docsearch.similarity_search_with_score( "far", k=1, filter={"first_letter": "f"} @@ -147,10 +259,10 @@ def test_chroma_search_filter_with_scores() -> None: ) docsearch.delete_collection() assert output1 == [ - (Document(page_content="far", metadata={"first_letter": "f"}), 0.0) + (Document(page_content="far", metadata={"first_letter": "f"}, id="id_0"), 0.0) ] assert output2 == [ - (Document(page_content="bar", metadata={"first_letter": "b"}), 1.0) + (Document(page_content="bar", metadata={"first_letter": "b"}, id="id_1"), 1.0) ] @@ -159,15 +271,18 @@ def test_chroma_with_persistence() -> None: chroma_persist_dir = "./tests/persist_dir" collection_name = "test_collection" texts = ["foo", "bar", "baz"] + ids = [f"id_{i}" for i in range(len(texts))] + docsearch = Chroma.from_texts( collection_name=collection_name, texts=texts, embedding=FakeEmbeddings(), persist_directory=chroma_persist_dir, + ids=ids, ) output = docsearch.similarity_search("foo", k=1) - assert output == [Document(page_content="foo")] + assert output == [Document(page_content="foo", id="id_0")] # Get a new VectorStore from the persisted directory docsearch = Chroma( @@ -176,6 +291,7 @@ def test_chroma_with_persistence() -> None: persist_directory=chroma_persist_dir, ) output = docsearch.similarity_search("foo", k=1) + assert output == [Document(page_content="foo", id="id_0")] # Clean up docsearch.delete_collection() @@ -193,7 +309,9 @@ def test_chroma_mmr() -> None: ) output = docsearch.max_marginal_relevance_search("foo", k=1) docsearch.delete_collection() - assert output == [Document(page_content="foo")] + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id is not None def test_chroma_mmr_by_vector() -> None: @@ -206,7 +324,9 @@ def test_chroma_mmr_by_vector() -> None: embedded_query = embeddings.embed_query("foo") output = docsearch.max_marginal_relevance_search_by_vector(embedded_query, k=1) docsearch.delete_collection() - assert output == [Document(page_content="foo")] + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id is not None def test_chroma_with_include_parameter() -> None: @@ -223,7 +343,10 @@ def test_chroma_with_include_parameter() -> None: def test_chroma_update_document() -> None: - """Test the update_document function in the Chroma class.""" + """Test the update_document function in the Chroma class. + + Uses an external document id. + """ # Make a consistent embedding embedding = ConsistentFakeEmbeddings() @@ -265,7 +388,66 @@ def test_chroma_update_document() -> None: docsearch.delete_collection() # Assert that the updated document is returned by the search - assert output == [Document(page_content=updated_content, metadata={"page": "0"})] + assert output == [ + Document(page_content=updated_content, metadata={"page": "0"}, id=document_id) + ] + + assert list(new_embedding) == list(embedding.embed_documents([updated_content])[0]) + assert list(new_embedding) != list(old_embedding) + + +def test_chroma_update_document_with_id() -> None: + """Test the update_document function in the Chroma class. + + Uses an internal document id. + """ + # Make a consistent embedding + embedding = ConsistentFakeEmbeddings() + + # Initial document content and id + initial_content = "foo" + document_id = "doc1" + + # Create an instance of Document with initial content and metadata + original_doc = Document( + page_content=initial_content, metadata={"page": "0"}, id=document_id + ) + + # Initialize a Chroma instance with the original document + docsearch = Chroma.from_documents( + collection_name="test_collection", + documents=[original_doc], + embedding=embedding, + ) + old_embedding = docsearch._collection.peek()["embeddings"][ # type: ignore + docsearch._collection.peek()["ids"].index(document_id) + ] + + # Define updated content for the document + updated_content = "updated foo" + + # Create a new Document instance with the updated content and the same id + updated_doc = Document( + page_content=updated_content, metadata={"page": "0"}, id=document_id + ) + + # Update the document in the Chroma instance + docsearch.update_document(document_id=document_id, document=updated_doc) + + # Perform a similarity search with the updated content + output = docsearch.similarity_search(updated_content, k=1) + + # Assert that the new embedding is correct + new_embedding = docsearch._collection.peek()["embeddings"][ # type: ignore + docsearch._collection.peek()["ids"].index(document_id) + ] + + docsearch.delete_collection() + + # Assert that the updated document is returned by the search + assert output == [ + Document(page_content=updated_content, metadata={"page": "0"}, id=document_id) + ] assert list(new_embedding) == list(embedding.embed_documents([updated_content])[0]) assert list(new_embedding) != list(old_embedding) @@ -276,20 +458,22 @@ def test_chroma_with_relevance_score_custom_normalization_fn() -> None: """Test searching with relevance score and custom normalization function.""" texts = ["foo", "bar", "baz"] metadatas = [{"page": str(i)} for i in range(len(texts))] + ids = [f"id_{i}" for i in range(len(texts))] docsearch = Chroma.from_texts( collection_name="test1_collection", texts=texts, embedding=FakeEmbeddings(), metadatas=metadatas, + ids=ids, relevance_score_fn=lambda d: d * 0, collection_metadata={"hnsw:space": "l2"}, ) output = docsearch.similarity_search_with_relevance_scores("foo", k=3) docsearch.delete_collection() assert output == [ - (Document(page_content="foo", metadata={"page": "0"}), 0.0), - (Document(page_content="bar", metadata={"page": "1"}), 0.0), - (Document(page_content="baz", metadata={"page": "2"}), 0.0), + (Document(page_content="foo", metadata={"page": "0"}, id="id_0"), 0.0), + (Document(page_content="bar", metadata={"page": "1"}, id="id_1"), 0.0), + (Document(page_content="baz", metadata={"page": "2"}, id="id_2"), 0.0), ] @@ -314,11 +498,11 @@ def test_chroma_add_documents_no_metadata() -> None: def test_chroma_add_documents_mixed_metadata() -> None: db = Chroma(embedding_function=FakeEmbeddings()) docs = [ - Document(page_content="foo"), - Document(page_content="bar", metadata={"baz": 1}), + Document(page_content="foo", id="0"), + Document(page_content="bar", metadata={"baz": 1}, id="1"), ] ids = ["0", "1"] - actual_ids = db.add_documents(docs, ids=ids) + actual_ids = db.add_documents(docs) search = db.similarity_search("foo bar") db.delete_collection() diff --git a/libs/partners/chroma/tests/unit_tests/test_vectorstores.py b/libs/partners/chroma/tests/unit_tests/test_vectorstores.py index 84d8637879e29..66ac3b0622465 100644 --- a/libs/partners/chroma/tests/unit_tests/test_vectorstores.py +++ b/libs/partners/chroma/tests/unit_tests/test_vectorstores.py @@ -13,3 +13,18 @@ def test_initialization() -> None: texts=texts, embedding=FakeEmbeddings(size=10), ) + + +def test_similarity_search() -> None: + """Test similarity search by Chroma.""" + texts = ["foo", "bar", "baz"] + metadatas = [{"page": str(i)} for i in range(len(texts))] + docsearch = Chroma.from_texts( + collection_name="test_collection", + texts=texts, + embedding=FakeEmbeddings(size=10), + metadatas=metadatas, + ) + output = docsearch.similarity_search("foo", k=1) + docsearch.delete_collection() + assert len(output) == 1 diff --git a/libs/partners/couchbase/poetry.lock b/libs/partners/couchbase/poetry.lock index 5931a6a913b83..328d7abc51d7c 100644 --- a/libs/partners/couchbase/poetry.lock +++ b/libs/partners/couchbase/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -13,112 +13,98 @@ files = [ [[package]] name = "aiohttp" -version = "3.10.10" +version = "3.11.7" description = "Async http client/server framework (asyncio)" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "aiohttp-3.10.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:be7443669ae9c016b71f402e43208e13ddf00912f47f623ee5994e12fc7d4b3f"}, - {file = "aiohttp-3.10.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7b06b7843929e41a94ea09eb1ce3927865387e3e23ebe108e0d0d09b08d25be9"}, - {file = "aiohttp-3.10.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:333cf6cf8e65f6a1e06e9eb3e643a0c515bb850d470902274239fea02033e9a8"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:274cfa632350225ce3fdeb318c23b4a10ec25c0e2c880eff951a3842cf358ac1"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9e5e4a85bdb56d224f412d9c98ae4cbd032cc4f3161818f692cd81766eee65a"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b606353da03edcc71130b52388d25f9a30a126e04caef1fd637e31683033abd"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ab5a5a0c7a7991d90446a198689c0535be89bbd6b410a1f9a66688f0880ec026"}, - {file = "aiohttp-3.10.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:578a4b875af3e0daaf1ac6fa983d93e0bbfec3ead753b6d6f33d467100cdc67b"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8105fd8a890df77b76dd3054cddf01a879fc13e8af576805d667e0fa0224c35d"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3bcd391d083f636c06a68715e69467963d1f9600f85ef556ea82e9ef25f043f7"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fbc6264158392bad9df19537e872d476f7c57adf718944cc1e4495cbabf38e2a"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:e48d5021a84d341bcaf95c8460b152cfbad770d28e5fe14a768988c461b821bc"}, - {file = "aiohttp-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:2609e9ab08474702cc67b7702dbb8a80e392c54613ebe80db7e8dbdb79837c68"}, - {file = "aiohttp-3.10.10-cp310-cp310-win32.whl", hash = "sha256:84afcdea18eda514c25bc68b9af2a2b1adea7c08899175a51fe7c4fb6d551257"}, - {file = "aiohttp-3.10.10-cp310-cp310-win_amd64.whl", hash = "sha256:9c72109213eb9d3874f7ac8c0c5fa90e072d678e117d9061c06e30c85b4cf0e6"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c30a0eafc89d28e7f959281b58198a9fa5e99405f716c0289b7892ca345fe45f"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:258c5dd01afc10015866114e210fb7365f0d02d9d059c3c3415382ab633fcbcb"}, - {file = "aiohttp-3.10.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:15ecd889a709b0080f02721255b3f80bb261c2293d3c748151274dfea93ac871"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3935f82f6f4a3820270842e90456ebad3af15810cf65932bd24da4463bc0a4c"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:413251f6fcf552a33c981c4709a6bba37b12710982fec8e558ae944bfb2abd38"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d1720b4f14c78a3089562b8875b53e36b51c97c51adc53325a69b79b4b48ebcb"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:679abe5d3858b33c2cf74faec299fda60ea9de62916e8b67e625d65bf069a3b7"}, - {file = "aiohttp-3.10.10-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:79019094f87c9fb44f8d769e41dbb664d6e8fcfd62f665ccce36762deaa0e911"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:fe2fb38c2ed905a2582948e2de560675e9dfbee94c6d5ccdb1301c6d0a5bf092"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:a3f00003de6eba42d6e94fabb4125600d6e484846dbf90ea8e48a800430cc142"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:1bbb122c557a16fafc10354b9d99ebf2f2808a660d78202f10ba9d50786384b9"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:30ca7c3b94708a9d7ae76ff281b2f47d8eaf2579cd05971b5dc681db8caac6e1"}, - {file = "aiohttp-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:df9270660711670e68803107d55c2b5949c2e0f2e4896da176e1ecfc068b974a"}, - {file = "aiohttp-3.10.10-cp311-cp311-win32.whl", hash = "sha256:aafc8ee9b742ce75044ae9a4d3e60e3d918d15a4c2e08a6c3c3e38fa59b92d94"}, - {file = "aiohttp-3.10.10-cp311-cp311-win_amd64.whl", hash = "sha256:362f641f9071e5f3ee6f8e7d37d5ed0d95aae656adf4ef578313ee585b585959"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:9294bbb581f92770e6ed5c19559e1e99255e4ca604a22c5c6397b2f9dd3ee42c"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:a8fa23fe62c436ccf23ff930149c047f060c7126eae3ccea005f0483f27b2e28"}, - {file = "aiohttp-3.10.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5c6a5b8c7926ba5d8545c7dd22961a107526562da31a7a32fa2456baf040939f"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:007ec22fbc573e5eb2fb7dec4198ef8f6bf2fe4ce20020798b2eb5d0abda6138"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9627cc1a10c8c409b5822a92d57a77f383b554463d1884008e051c32ab1b3742"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:50edbcad60d8f0e3eccc68da67f37268b5144ecc34d59f27a02f9611c1d4eec7"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a45d85cf20b5e0d0aa5a8dca27cce8eddef3292bc29d72dcad1641f4ed50aa16"}, - {file = "aiohttp-3.10.10-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0b00807e2605f16e1e198f33a53ce3c4523114059b0c09c337209ae55e3823a8"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f2d4324a98062be0525d16f768a03e0bbb3b9fe301ceee99611dc9a7953124e6"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:438cd072f75bb6612f2aca29f8bd7cdf6e35e8f160bc312e49fbecab77c99e3a"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:baa42524a82f75303f714108fea528ccacf0386af429b69fff141ffef1c534f9"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a7d8d14fe962153fc681f6366bdec33d4356f98a3e3567782aac1b6e0e40109a"}, - {file = "aiohttp-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c1277cd707c465cd09572a774559a3cc7c7a28802eb3a2a9472588f062097205"}, - {file = "aiohttp-3.10.10-cp312-cp312-win32.whl", hash = "sha256:59bb3c54aa420521dc4ce3cc2c3fe2ad82adf7b09403fa1f48ae45c0cbde6628"}, - {file = "aiohttp-3.10.10-cp312-cp312-win_amd64.whl", hash = "sha256:0e1b370d8007c4ae31ee6db7f9a2fe801a42b146cec80a86766e7ad5c4a259cf"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ad7593bb24b2ab09e65e8a1d385606f0f47c65b5a2ae6c551db67d6653e78c28"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:1eb89d3d29adaf533588f209768a9c02e44e4baf832b08118749c5fad191781d"}, - {file = "aiohttp-3.10.10-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3fe407bf93533a6fa82dece0e74dbcaaf5d684e5a51862887f9eaebe6372cd79"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50aed5155f819873d23520919e16703fc8925e509abbb1a1491b0087d1cd969e"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4f05e9727ce409358baa615dbeb9b969db94324a79b5a5cea45d39bdb01d82e6"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3dffb610a30d643983aeb185ce134f97f290f8935f0abccdd32c77bed9388b42"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa6658732517ddabe22c9036479eabce6036655ba87a0224c612e1ae6af2087e"}, - {file = "aiohttp-3.10.10-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:741a46d58677d8c733175d7e5aa618d277cd9d880301a380fd296975a9cdd7bc"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e00e3505cd80440f6c98c6d69269dcc2a119f86ad0a9fd70bccc59504bebd68a"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:ffe595f10566f8276b76dc3a11ae4bb7eba1aac8ddd75811736a15b0d5311414"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:bdfcf6443637c148c4e1a20c48c566aa694fa5e288d34b20fcdc58507882fed3"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:d183cf9c797a5291e8301790ed6d053480ed94070637bfaad914dd38b0981f67"}, - {file = "aiohttp-3.10.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:77abf6665ae54000b98b3c742bc6ea1d1fb31c394bcabf8b5d2c1ac3ebfe7f3b"}, - {file = "aiohttp-3.10.10-cp313-cp313-win32.whl", hash = "sha256:4470c73c12cd9109db8277287d11f9dd98f77fc54155fc71a7738a83ffcc8ea8"}, - {file = "aiohttp-3.10.10-cp313-cp313-win_amd64.whl", hash = "sha256:486f7aabfa292719a2753c016cc3a8f8172965cabb3ea2e7f7436c7f5a22a151"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:1b66ccafef7336a1e1f0e389901f60c1d920102315a56df85e49552308fc0486"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:acd48d5b80ee80f9432a165c0ac8cbf9253eaddb6113269a5e18699b33958dbb"}, - {file = "aiohttp-3.10.10-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:3455522392fb15ff549d92fbf4b73b559d5e43dc522588f7eb3e54c3f38beee7"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45c3b868724137f713a38376fef8120c166d1eadd50da1855c112fe97954aed8"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:da1dee8948d2137bb51fbb8a53cce6b1bcc86003c6b42565f008438b806cccd8"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c5ce2ce7c997e1971b7184ee37deb6ea9922ef5163c6ee5aa3c274b05f9e12fa"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:28529e08fde6f12eba8677f5a8608500ed33c086f974de68cc65ab218713a59d"}, - {file = "aiohttp-3.10.10-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f7db54c7914cc99d901d93a34704833568d86c20925b2762f9fa779f9cd2e70f"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:03a42ac7895406220124c88911ebee31ba8b2d24c98507f4a8bf826b2937c7f2"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:7e338c0523d024fad378b376a79faff37fafb3c001872a618cde1d322400a572"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:038f514fe39e235e9fef6717fbf944057bfa24f9b3db9ee551a7ecf584b5b480"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:64f6c17757251e2b8d885d728b6433d9d970573586a78b78ba8929b0f41d045a"}, - {file = "aiohttp-3.10.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:93429602396f3383a797a2a70e5f1de5df8e35535d7806c9f91df06f297e109b"}, - {file = "aiohttp-3.10.10-cp38-cp38-win32.whl", hash = "sha256:c823bc3971c44ab93e611ab1a46b1eafeae474c0c844aff4b7474287b75fe49c"}, - {file = "aiohttp-3.10.10-cp38-cp38-win_amd64.whl", hash = "sha256:54ca74df1be3c7ca1cf7f4c971c79c2daf48d9aa65dea1a662ae18926f5bc8ce"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:01948b1d570f83ee7bbf5a60ea2375a89dfb09fd419170e7f5af029510033d24"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9fc1500fd2a952c5c8e3b29aaf7e3cc6e27e9cfc0a8819b3bce48cc1b849e4cc"}, - {file = "aiohttp-3.10.10-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f614ab0c76397661b90b6851a030004dac502e48260ea10f2441abd2207fbcc7"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:00819de9e45d42584bed046314c40ea7e9aea95411b38971082cad449392b08c"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:05646ebe6b94cc93407b3bf34b9eb26c20722384d068eb7339de802154d61bc5"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:998f3bd3cfc95e9424a6acd7840cbdd39e45bc09ef87533c006f94ac47296090"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d9010c31cd6fa59438da4e58a7f19e4753f7f264300cd152e7f90d4602449762"}, - {file = "aiohttp-3.10.10-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ea7ffc6d6d6f8a11e6f40091a1040995cdff02cfc9ba4c2f30a516cb2633554"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:ef9c33cc5cbca35808f6c74be11eb7f5f6b14d2311be84a15b594bd3e58b5527"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:ce0cdc074d540265bfeb31336e678b4e37316849d13b308607efa527e981f5c2"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:597a079284b7ee65ee102bc3a6ea226a37d2b96d0418cc9047490f231dc09fe8"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:7789050d9e5d0c309c706953e5e8876e38662d57d45f936902e176d19f1c58ab"}, - {file = "aiohttp-3.10.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:e7f8b04d83483577fd9200461b057c9f14ced334dcb053090cea1da9c8321a91"}, - {file = "aiohttp-3.10.10-cp39-cp39-win32.whl", hash = "sha256:c02a30b904282777d872266b87b20ed8cc0d1501855e27f831320f471d54d983"}, - {file = "aiohttp-3.10.10-cp39-cp39-win_amd64.whl", hash = "sha256:edfe3341033a6b53a5c522c802deb2079eee5cbfbb0af032a55064bd65c73a23"}, - {file = "aiohttp-3.10.10.tar.gz", hash = "sha256:0631dd7c9f0822cc61c88586ca76d5b5ada26538097d0f1df510b082bad3411a"}, + {file = "aiohttp-3.11.7-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:8bedb1f6cb919af3b6353921c71281b1491f948ca64408871465d889b4ee1b66"}, + {file = "aiohttp-3.11.7-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f5022504adab881e2d801a88b748ea63f2a9d130e0b2c430824682a96f6534be"}, + {file = "aiohttp-3.11.7-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e22d1721c978a6494adc824e0916f9d187fa57baeda34b55140315fa2f740184"}, + {file = "aiohttp-3.11.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e993676c71288618eb07e20622572b1250d8713e7e00ab3aabae28cb70f3640d"}, + {file = "aiohttp-3.11.7-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e13a05db87d3b241c186d0936808d0e4e12decc267c617d54e9c643807e968b6"}, + {file = "aiohttp-3.11.7-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4ba8d043fed7ffa117024d7ba66fdea011c0e7602327c6d73cacaea38abe4491"}, + {file = "aiohttp-3.11.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dda3ed0a7869d2fa16aa41f9961ade73aa2c2e3b2fcb0a352524e7b744881889"}, + {file = "aiohttp-3.11.7-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:43bfd25113c1e98aec6c70e26d5f4331efbf4aa9037ba9ad88f090853bf64d7f"}, + {file = "aiohttp-3.11.7-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3dd3e7e7c9ef3e7214f014f1ae260892286647b3cf7c7f1b644a568fd410f8ca"}, + {file = "aiohttp-3.11.7-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:78c657ece7a73b976905ab9ec8be9ef2df12ed8984c24598a1791c58ce3b4ce4"}, + {file = "aiohttp-3.11.7-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:db70a47987e34494b451a334605bee57a126fe8d290511349e86810b4be53b01"}, + {file = "aiohttp-3.11.7-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:9e67531370a3b07e49b280c1f8c2df67985c790ad2834d1b288a2f13cd341c5f"}, + {file = "aiohttp-3.11.7-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:9202f184cc0582b1db15056f2225ab4c1e3dac4d9ade50dd0613ac3c46352ac2"}, + {file = "aiohttp-3.11.7-cp310-cp310-win32.whl", hash = "sha256:2257bdd5cf54a4039a4337162cd8048f05a724380a2283df34620f55d4e29341"}, + {file = "aiohttp-3.11.7-cp310-cp310-win_amd64.whl", hash = "sha256:b7215bf2b53bc6cb35808149980c2ae80a4ae4e273890ac85459c014d5aa60ac"}, + {file = "aiohttp-3.11.7-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:cea52d11e02123f125f9055dfe0ccf1c3857225fb879e4a944fae12989e2aef2"}, + {file = "aiohttp-3.11.7-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3ce18f703b7298e7f7633efd6a90138d99a3f9a656cb52c1201e76cb5d79cf08"}, + {file = "aiohttp-3.11.7-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:670847ee6aeb3a569cd7cdfbe0c3bec1d44828bbfbe78c5d305f7f804870ef9e"}, + {file = "aiohttp-3.11.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4dda726f89bfa5c465ba45b76515135a3ece0088dfa2da49b8bb278f3bdeea12"}, + {file = "aiohttp-3.11.7-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c25b74a811dba37c7ea6a14d99eb9402d89c8d739d50748a75f3cf994cf19c43"}, + {file = "aiohttp-3.11.7-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e5522ee72f95661e79db691310290c4618b86dff2d9b90baedf343fd7a08bf79"}, + {file = "aiohttp-3.11.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1fbf41a6bbc319a7816ae0f0177c265b62f2a59ad301a0e49b395746eb2a9884"}, + {file = "aiohttp-3.11.7-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:59ee1925b5a5efdf6c4e7be51deee93984d0ac14a6897bd521b498b9916f1544"}, + {file = "aiohttp-3.11.7-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:24054fce8c6d6f33a3e35d1c603ef1b91bbcba73e3f04a22b4f2f27dac59b347"}, + {file = "aiohttp-3.11.7-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:351849aca2c6f814575c1a485c01c17a4240413f960df1bf9f5deb0003c61a53"}, + {file = "aiohttp-3.11.7-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:12724f3a211fa243570e601f65a8831372caf1a149d2f1859f68479f07efec3d"}, + {file = "aiohttp-3.11.7-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:7ea4490360b605804bea8173d2d086b6c379d6bb22ac434de605a9cbce006e7d"}, + {file = "aiohttp-3.11.7-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e0bf378db07df0a713a1e32381a1b277e62ad106d0dbe17b5479e76ec706d720"}, + {file = "aiohttp-3.11.7-cp311-cp311-win32.whl", hash = "sha256:cd8d62cab363dfe713067027a5adb4907515861f1e4ce63e7be810b83668b847"}, + {file = "aiohttp-3.11.7-cp311-cp311-win_amd64.whl", hash = "sha256:bf0e6cce113596377cadda4e3ac5fb89f095bd492226e46d91b4baef1dd16f60"}, + {file = "aiohttp-3.11.7-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:4bb7493c3e3a36d3012b8564bd0e2783259ddd7ef3a81a74f0dbfa000fce48b7"}, + {file = "aiohttp-3.11.7-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:e143b0ef9cb1a2b4f74f56d4fbe50caa7c2bb93390aff52f9398d21d89bc73ea"}, + {file = "aiohttp-3.11.7-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f7c58a240260822dc07f6ae32a0293dd5bccd618bb2d0f36d51c5dbd526f89c0"}, + {file = "aiohttp-3.11.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8d20cfe63a1c135d26bde8c1d0ea46fd1200884afbc523466d2f1cf517d1fe33"}, + {file = "aiohttp-3.11.7-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:12e4d45847a174f77b2b9919719203769f220058f642b08504cf8b1cf185dacf"}, + {file = "aiohttp-3.11.7-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cf4efa2d01f697a7dbd0509891a286a4af0d86902fc594e20e3b1712c28c0106"}, + {file = "aiohttp-3.11.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ee6a4cdcbf54b8083dc9723cdf5f41f722c00db40ccf9ec2616e27869151129"}, + {file = "aiohttp-3.11.7-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c6095aaf852c34f42e1bd0cf0dc32d1e4b48a90bfb5054abdbb9d64b36acadcb"}, + {file = "aiohttp-3.11.7-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1cf03d27885f8c5ebf3993a220cc84fc66375e1e6e812731f51aab2b2748f4a6"}, + {file = "aiohttp-3.11.7-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:1a17f6a230f81eb53282503823f59d61dff14fb2a93847bf0399dc8e87817307"}, + {file = "aiohttp-3.11.7-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:481f10a1a45c5f4c4a578bbd74cff22eb64460a6549819242a87a80788461fba"}, + {file = "aiohttp-3.11.7-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:db37248535d1ae40735d15bdf26ad43be19e3d93ab3f3dad8507eb0f85bb8124"}, + {file = "aiohttp-3.11.7-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:9d18a8b44ec8502a7fde91446cd9c9b95ce7c49f1eacc1fb2358b8907d4369fd"}, + {file = "aiohttp-3.11.7-cp312-cp312-win32.whl", hash = "sha256:3d1c9c15d3999107cbb9b2d76ca6172e6710a12fda22434ee8bd3f432b7b17e8"}, + {file = "aiohttp-3.11.7-cp312-cp312-win_amd64.whl", hash = "sha256:018f1b04883a12e77e7fc161934c0f298865d3a484aea536a6a2ca8d909f0ba0"}, + {file = "aiohttp-3.11.7-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:241a6ca732d2766836d62c58c49ca7a93d08251daef0c1e3c850df1d1ca0cbc4"}, + {file = "aiohttp-3.11.7-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:aa3705a8d14de39898da0fbad920b2a37b7547c3afd2a18b9b81f0223b7d0f68"}, + {file = "aiohttp-3.11.7-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9acfc7f652b31853eed3b92095b0acf06fd5597eeea42e939bd23a17137679d5"}, + {file = "aiohttp-3.11.7-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcefcf2915a2dbdbce37e2fc1622129a1918abfe3d06721ce9f6cdac9b6d2eaa"}, + {file = "aiohttp-3.11.7-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c1f6490dd1862af5aae6cfcf2a274bffa9a5b32a8f5acb519a7ecf5a99a88866"}, + {file = "aiohttp-3.11.7-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f1ac5462582d6561c1c1708853a9faf612ff4e5ea5e679e99be36143d6eabd8e"}, + {file = "aiohttp-3.11.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c1a6309005acc4b2bcc577ba3b9169fea52638709ffacbd071f3503264620da"}, + {file = "aiohttp-3.11.7-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f5b973cce96793725ef63eb449adfb74f99c043c718acb76e0d2a447ae369962"}, + {file = "aiohttp-3.11.7-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ce91a24aac80de6be8512fb1c4838a9881aa713f44f4e91dd7bb3b34061b497d"}, + {file = "aiohttp-3.11.7-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:875f7100ce0e74af51d4139495eec4025affa1a605280f23990b6434b81df1bd"}, + {file = "aiohttp-3.11.7-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:c171fc35d3174bbf4787381716564042a4cbc008824d8195eede3d9b938e29a8"}, + {file = "aiohttp-3.11.7-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:ee9afa1b0d2293c46954f47f33e150798ad68b78925e3710044e0d67a9487791"}, + {file = "aiohttp-3.11.7-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8360c7cc620abb320e1b8d603c39095101391a82b1d0be05fb2225471c9c5c52"}, + {file = "aiohttp-3.11.7-cp313-cp313-win32.whl", hash = "sha256:7a9318da4b4ada9a67c1dd84d1c0834123081e746bee311a16bb449f363d965e"}, + {file = "aiohttp-3.11.7-cp313-cp313-win_amd64.whl", hash = "sha256:fc6da202068e0a268e298d7cd09b6e9f3997736cd9b060e2750963754552a0a9"}, + {file = "aiohttp-3.11.7-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:17829f37c0d31d89aa6b8b010475a10233774771f9b6dc2cc352ea4f8ce95d9a"}, + {file = "aiohttp-3.11.7-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d6177077a31b1aecfc3c9070bd2f11419dbb4a70f30f4c65b124714f525c2e48"}, + {file = "aiohttp-3.11.7-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:badda65ac99555791eed75e234afb94686ed2317670c68bff8a4498acdaee935"}, + {file = "aiohttp-3.11.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0de6466b9d742b4ee56fe1b2440706e225eb48c77c63152b1584864a236e7a50"}, + {file = "aiohttp-3.11.7-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:04b0cc74d5a882c9dacaeeccc1444f0233212b6f5be8bc90833feef1e1ce14b9"}, + {file = "aiohttp-3.11.7-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28c7af3e50e5903d21d7b935aceed901cc2475463bc16ddd5587653548661fdb"}, + {file = "aiohttp-3.11.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c63f898f683d1379b9be5afc3dd139e20b30b0b1e0bf69a3fc3681f364cf1629"}, + {file = "aiohttp-3.11.7-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:fdadc3f6a32d6eca45f9a900a254757fd7855dfb2d8f8dcf0e88f0fae3ff8eb1"}, + {file = "aiohttp-3.11.7-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:d329300fb23e14ed1f8c6d688dfd867d1dcc3b1d7cd49b7f8c5b44e797ce0932"}, + {file = "aiohttp-3.11.7-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:5578cf40440eafcb054cf859964bc120ab52ebe0e0562d2b898126d868749629"}, + {file = "aiohttp-3.11.7-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:7b2f8107a3c329789f3c00b2daad0e35f548d0a55cda6291579136622099a46e"}, + {file = "aiohttp-3.11.7-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:43dd89a6194f6ab02a3fe36b09e42e2df19c211fc2050ce37374d96f39604997"}, + {file = "aiohttp-3.11.7-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:d2fa6fc7cc865d26ff42480ac9b52b8c9b7da30a10a6442a9cdf429de840e949"}, + {file = "aiohttp-3.11.7-cp39-cp39-win32.whl", hash = "sha256:a7d9a606355655617fee25dd7e54d3af50804d002f1fd3118dd6312d26692d70"}, + {file = "aiohttp-3.11.7-cp39-cp39-win_amd64.whl", hash = "sha256:53c921b58fdc6485d6b2603e0132bb01cd59b8f0620ffc0907f525e0ba071687"}, + {file = "aiohttp-3.11.7.tar.gz", hash = "sha256:01a8aca4af3da85cea5c90141d23f4b0eee3cbecfd33b029a45a80f28c66c668"}, ] [package.dependencies] aiohappyeyeballs = ">=2.3.0" aiosignal = ">=1.1.2" -async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""} +async-timeout = {version = ">=4.0,<6.0", markers = "python_version < \"3.11\""} attrs = ">=17.3.0" frozenlist = ">=1.1.1" multidict = ">=4.5,<7.0" -yarl = ">=1.12.0,<2.0" +propcache = ">=0.2.0" +yarl = ">=1.17.0,<2.0" [package.extras] speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"] @@ -355,42 +341,42 @@ files = [ [[package]] name = "couchbase" -version = "4.3.2" +version = "4.3.4" description = "Python Client for Couchbase" optional = false python-versions = ">=3.7" files = [ - {file = "couchbase-4.3.2-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:85df43305f2646203192d67a9433abb5e1098390cba6adec8c4f675ba9ba7fdc"}, - {file = "couchbase-4.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:5b8ee78c7a4b7451db6fcd534dc24462f2cd0e863f16495e687a23b7aecf8296"}, - {file = "couchbase-4.3.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:2841b86eb80454279548d8102ce6e71f5bc791eb4a83cb3575b7cf4104c374b2"}, - {file = "couchbase-4.3.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:540545fd867de02985eb16733c1b16228b0e09461e44a9c2bfad0200fdf7d09a"}, - {file = "couchbase-4.3.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:52cdcd65fb6565f51ea4540fe823143f0fb9d650136b96b904b1650b05a06746"}, - {file = "couchbase-4.3.2-cp310-cp310-win_amd64.whl", hash = "sha256:3fb88b9f52c2099a4e25fbc30f27734c3da5c86af930de1f4102d03a3df8e77a"}, - {file = "couchbase-4.3.2-cp311-cp311-macosx_10_15_x86_64.whl", hash = "sha256:b12288e15326b6fae027a419467403d6c9f3f9641cd9cfee0ab0930a9d2315cd"}, - {file = "couchbase-4.3.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:86e2713759b26ee279574d740151ba4b0ad859a45fc7ac1d13fcdd39d8ee2951"}, - {file = "couchbase-4.3.2-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:6a43ce67ffe90bbb5460da5c95d778e804bcd81c037cc8a347f2966afc6c4b5a"}, - {file = "couchbase-4.3.2-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:401a7d5a442196bf805746b8354636753ec12c788fba918245345c32211bdf0c"}, - {file = "couchbase-4.3.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:aac415f89c38482ac076b4b766537701e99f728cc1c5b2de8c16fa28ce7caa53"}, - {file = "couchbase-4.3.2-cp311-cp311-win_amd64.whl", hash = "sha256:220fe6b75ebbda4651a8e0370642c0f5db5da7f3b0acd9fc8e2b5b31427f9fb1"}, - {file = "couchbase-4.3.2-cp312-cp312-macosx_10_15_x86_64.whl", hash = "sha256:bf5814a8e9efe405c9c81145c8afca7e55b964543984c9d8dc340163597b09b2"}, - {file = "couchbase-4.3.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:bd93d352ccb35c86eec9e5b4d1de015c26c15b52c80204f75189bde627b8b529"}, - {file = "couchbase-4.3.2-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:bbefa6111be033587b04b2586f5fc8d6db9a76ec138fea5288c8698c8f294bc2"}, - {file = "couchbase-4.3.2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:419a79b2a98bf3d168b264e0dfc1a0949727a2c3ef455e2ffe8e734a2fdc6e7a"}, - {file = "couchbase-4.3.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:30115cde63fc18abe587d167bbb0d37e8c253f7430e08e69f64eaca2eb7e4ca0"}, - {file = "couchbase-4.3.2-cp312-cp312-win_amd64.whl", hash = "sha256:5b4eccd4a0ac30d58ea0570a1882a8c0e367a9d54d80c0f6a288e348d1b2b41e"}, - {file = "couchbase-4.3.2-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:c18b7c937e63e6d869371d9c4b0a0f9cc1a87dba48950a4276e294c091d76ce5"}, - {file = "couchbase-4.3.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:46e492814163162a43d5cbf867eac0d685ea73c803f3238f65c0068ea4a2ce61"}, - {file = "couchbase-4.3.2-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:11ce688ed46edf8387bf51866618c7b4e06399e7fb34a6df002764996c109d1f"}, - {file = "couchbase-4.3.2-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:a4b964dd2b804036c57b670734b7aa02985dc5cf6d1a8f9f7d4af8feaf012fef"}, - {file = "couchbase-4.3.2-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:687cb157c89822f463fd5373356e38ee7ebecf6306c9da9cae5b54cedad2b66d"}, - {file = "couchbase-4.3.2-cp38-cp38-win_amd64.whl", hash = "sha256:6dcff2c9907ee506e63814c417212e9b51760b914609771dff92508888031dfa"}, - {file = "couchbase-4.3.2-cp39-cp39-macosx_10_15_x86_64.whl", hash = "sha256:1f0bf68a2a67958db87a81da4d30d63915f39598482d62cd7fe9752b625dcb19"}, - {file = "couchbase-4.3.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c50ae993c81d81ed0f02a37cbe034825408195b9fe29980b3379e2e05b2e1bec"}, - {file = "couchbase-4.3.2-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:841c59deff25a3185469726d96cce0e120e6b062e724cb6981d1a2c1e2a629e5"}, - {file = "couchbase-4.3.2-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c139c594118e1df6932491c26b825ac777fd201f49cda303892065e607f9c3ef"}, - {file = "couchbase-4.3.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:6f820249b9d71593b29fb0ab3eff66ba36914076e00486ca0b99ce6ac6fd1ce9"}, - {file = "couchbase-4.3.2-cp39-cp39-win_amd64.whl", hash = "sha256:032a180afd6621358b2c73543b9c5db9939b442fc3ad6d54417c36c8a8f65838"}, - {file = "couchbase-4.3.2.tar.gz", hash = "sha256:6f3c2fc874a8b6ca7e6c8b3aaebcbfa4e14937afdb470aaa9b16724c4746b8d5"}, + {file = "couchbase-4.3.4-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:395e7b05495132a071dce5cdd84a3ec6e803205875f8ee22e85a89a16bb1b5f4"}, + {file = "couchbase-4.3.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:263a18307d1f1a141b93ae370b19843b1160dd702559152aea19dd08768f59f5"}, + {file = "couchbase-4.3.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:16751d4f3b0fe49666515ebed7967e8f38ec3862b329f773f88252acfd7c2b1f"}, + {file = "couchbase-4.3.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4dcc7eb9f57825c0097785d1c042e146908d2883f5e733d4ca07ac548bb532a2"}, + {file = "couchbase-4.3.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:42f16ca2ec636db9ecacd3b97db85c923be8374eaae2fe097124d8eb92b4293f"}, + {file = "couchbase-4.3.4-cp310-cp310-win_amd64.whl", hash = "sha256:8eecc9cdead68efe4119ebe41b065dadf83bc1653ec56470800c5093e378cacc"}, + {file = "couchbase-4.3.4-cp311-cp311-macosx_10_15_x86_64.whl", hash = "sha256:1a6d6c4542e4ffe223960553e057bc175cfcee3fe274f63551e9d90d7c2435c5"}, + {file = "couchbase-4.3.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ae44db4ce78b691028075fc54beec2dc1a59829f53a2b282f9a8b3ea6b71ad22"}, + {file = "couchbase-4.3.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:a175f1e447b9aeb7ab5aab66350261be28ad7d9a07fff9c7fe48c55828133ec3"}, + {file = "couchbase-4.3.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:efb0170d5e7766593d47292c14a782e201f0167175f0e60cd7ba3b9acd75e349"}, + {file = "couchbase-4.3.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:3f7d9e0492727b8560d36f5cb45c2a6ec9507dd2120ddd6313fd21e04cfc2ab9"}, + {file = "couchbase-4.3.4-cp311-cp311-win_amd64.whl", hash = "sha256:f32e9d87e5157b86af5de85200cab433690789551d2bda1b8e7a25bf2680d511"}, + {file = "couchbase-4.3.4-cp312-cp312-macosx_10_15_x86_64.whl", hash = "sha256:395afab875aa3d293429cebc080cc12ac6e32c665275740d5a8445c688ad84ce"}, + {file = "couchbase-4.3.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:852ff1e36668a9b0e0e4dc015df06e3a663bd5e0301a52c25b724969073a1a11"}, + {file = "couchbase-4.3.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:79ab95992829de574e23588ce35fc14ab6f8a5fd378c046522a678b7583a9b29"}, + {file = "couchbase-4.3.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:88827951b4132b89b6f37f1f2706b1e2f04870825c420e931c3caa770fc4a4e8"}, + {file = "couchbase-4.3.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:d8f88c731d0d28132a992978aae5e1140a71276cc528ecc2ed408b2e386d1183"}, + {file = "couchbase-4.3.4-cp312-cp312-win_amd64.whl", hash = "sha256:fb137358e249c752dbecb44393769696c07fd069eb976b2a9890ddd457d35fcb"}, + {file = "couchbase-4.3.4-cp313-cp313-macosx_10_15_x86_64.whl", hash = "sha256:d3f84932dd2d26a06048fe0858be21f5c6907a304ce59d673d56691e6eda7626"}, + {file = "couchbase-4.3.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f0975f9efeba9c425c2c73e5c3b6f3b4041cb61e1c5c0240c581454b0fc222fe"}, + {file = "couchbase-4.3.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:43609d64306ac8be7c396c0395a140c8f6b5bbab889e4b943f1b0dd500e34568"}, + {file = "couchbase-4.3.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c8a549126875e38a79f7f7d97094a482b3fd446c20266ddb5c274d6398be8477"}, + {file = "couchbase-4.3.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:c1adc3c7cf411f1c61e2f9b4454719d25f7229594280d7dedc7a8c9c2da8189f"}, + {file = "couchbase-4.3.4-cp313-cp313-win_amd64.whl", hash = "sha256:9b34b9599b29c2366e2943309c45c0666956e458848eb9b88a43a765afc8728c"}, + {file = "couchbase-4.3.4-cp39-cp39-macosx_10_15_x86_64.whl", hash = "sha256:f9b9b5523fbc89189119eceea170c329cf02115e1eba59818faefb594b729520"}, + {file = "couchbase-4.3.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:e2cb01a0b567694a12abdb01f73392cf64cbc881e496e70b32f05f36ac50ca0f"}, + {file = "couchbase-4.3.4-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:31eb077c2cd9694b933a8a18836c117f6682a220b33a767b3379934b540e6e1c"}, + {file = "couchbase-4.3.4-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4ad97d9467485667f8ba2b644c5823bb53fb1799dca5a29b671258d6af719ca0"}, + {file = "couchbase-4.3.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:51f50dd684e9894d5c8059ee6da5e9bc6e1a47ab3be103a3b299e7d01de02bab"}, + {file = "couchbase-4.3.4-cp39-cp39-win_amd64.whl", hash = "sha256:1059b4358d1f1b69812f114d0c5a547f830ab9fb24bcd5076a05ceb4788adee1"}, + {file = "couchbase-4.3.4.tar.gz", hash = "sha256:f195958606cf3a255fd96646ca3dd7e2ddcecf3664b3883826c7b89ef680088e"}, ] [[package]] @@ -409,88 +395,103 @@ test = ["pytest (>=6)"] [[package]] name = "frozenlist" -version = "1.4.1" +version = "1.5.0" description = "A list-like structure which implements collections.abc.MutableSequence" optional = false python-versions = ">=3.8" files = [ - {file = "frozenlist-1.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:f9aa1878d1083b276b0196f2dfbe00c9b7e752475ed3b682025ff20c1c1f51ac"}, - {file = "frozenlist-1.4.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:29acab3f66f0f24674b7dc4736477bcd4bc3ad4b896f5f45379a67bce8b96868"}, - {file = "frozenlist-1.4.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:74fb4bee6880b529a0c6560885fce4dc95936920f9f20f53d99a213f7bf66776"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:590344787a90ae57d62511dd7c736ed56b428f04cd8c161fcc5e7232c130c69a"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:068b63f23b17df8569b7fdca5517edef76171cf3897eb68beb01341131fbd2ad"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5c849d495bf5154cd8da18a9eb15db127d4dba2968d88831aff6f0331ea9bd4c"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9750cc7fe1ae3b1611bb8cfc3f9ec11d532244235d75901fb6b8e42ce9229dfe"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a9b2de4cf0cdd5bd2dee4c4f63a653c61d2408055ab77b151c1957f221cabf2a"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:0633c8d5337cb5c77acbccc6357ac49a1770b8c487e5b3505c57b949b4b82e98"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:27657df69e8801be6c3638054e202a135c7f299267f1a55ed3a598934f6c0d75"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:f9a3ea26252bd92f570600098783d1371354d89d5f6b7dfd87359d669f2109b5"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:4f57dab5fe3407b6c0c1cc907ac98e8a189f9e418f3b6e54d65a718aaafe3950"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:e02a0e11cf6597299b9f3bbd3f93d79217cb90cfd1411aec33848b13f5c656cc"}, - {file = "frozenlist-1.4.1-cp310-cp310-win32.whl", hash = "sha256:a828c57f00f729620a442881cc60e57cfcec6842ba38e1b19fd3e47ac0ff8dc1"}, - {file = "frozenlist-1.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:f56e2333dda1fe0f909e7cc59f021eba0d2307bc6f012a1ccf2beca6ba362439"}, - {file = "frozenlist-1.4.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:a0cb6f11204443f27a1628b0e460f37fb30f624be6051d490fa7d7e26d4af3d0"}, - {file = "frozenlist-1.4.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b46c8ae3a8f1f41a0d2ef350c0b6e65822d80772fe46b653ab6b6274f61d4a49"}, - {file = "frozenlist-1.4.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:fde5bd59ab5357e3853313127f4d3565fc7dad314a74d7b5d43c22c6a5ed2ced"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:722e1124aec435320ae01ee3ac7bec11a5d47f25d0ed6328f2273d287bc3abb0"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2471c201b70d58a0f0c1f91261542a03d9a5e088ed3dc6c160d614c01649c106"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c757a9dd70d72b076d6f68efdbb9bc943665ae954dad2801b874c8c69e185068"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f146e0911cb2f1da549fc58fc7bcd2b836a44b79ef871980d605ec392ff6b0d2"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4f9c515e7914626b2a2e1e311794b4c35720a0be87af52b79ff8e1429fc25f19"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:c302220494f5c1ebeb0912ea782bcd5e2f8308037b3c7553fad0e48ebad6ad82"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:442acde1e068288a4ba7acfe05f5f343e19fac87bfc96d89eb886b0363e977ec"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:1b280e6507ea8a4fa0c0a7150b4e526a8d113989e28eaaef946cc77ffd7efc0a"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:fe1a06da377e3a1062ae5fe0926e12b84eceb8a50b350ddca72dc85015873f74"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:db9e724bebd621d9beca794f2a4ff1d26eed5965b004a97f1f1685a173b869c2"}, - {file = "frozenlist-1.4.1-cp311-cp311-win32.whl", hash = "sha256:e774d53b1a477a67838a904131c4b0eef6b3d8a651f8b138b04f748fccfefe17"}, - {file = "frozenlist-1.4.1-cp311-cp311-win_amd64.whl", hash = "sha256:fb3c2db03683b5767dedb5769b8a40ebb47d6f7f45b1b3e3b4b51ec8ad9d9825"}, - {file = "frozenlist-1.4.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:1979bc0aeb89b33b588c51c54ab0161791149f2461ea7c7c946d95d5f93b56ae"}, - {file = "frozenlist-1.4.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:cc7b01b3754ea68a62bd77ce6020afaffb44a590c2289089289363472d13aedb"}, - {file = "frozenlist-1.4.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c9c92be9fd329ac801cc420e08452b70e7aeab94ea4233a4804f0915c14eba9b"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5c3894db91f5a489fc8fa6a9991820f368f0b3cbdb9cd8849547ccfab3392d86"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ba60bb19387e13597fb059f32cd4d59445d7b18b69a745b8f8e5db0346f33480"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8aefbba5f69d42246543407ed2461db31006b0f76c4e32dfd6f42215a2c41d09"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:780d3a35680ced9ce682fbcf4cb9c2bad3136eeff760ab33707b71db84664e3a"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9acbb16f06fe7f52f441bb6f413ebae6c37baa6ef9edd49cdd567216da8600cd"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:23b701e65c7b36e4bf15546a89279bd4d8675faabc287d06bbcfac7d3c33e1e6"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:3e0153a805a98f5ada7e09826255ba99fb4f7524bb81bf6b47fb702666484ae1"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:dd9b1baec094d91bf36ec729445f7769d0d0cf6b64d04d86e45baf89e2b9059b"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_s390x.whl", hash = "sha256:1a4471094e146b6790f61b98616ab8e44f72661879cc63fa1049d13ef711e71e"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:5667ed53d68d91920defdf4035d1cdaa3c3121dc0b113255124bcfada1cfa1b8"}, - {file = "frozenlist-1.4.1-cp312-cp312-win32.whl", hash = "sha256:beee944ae828747fd7cb216a70f120767fc9f4f00bacae8543c14a6831673f89"}, - {file = "frozenlist-1.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:64536573d0a2cb6e625cf309984e2d873979709f2cf22839bf2d61790b448ad5"}, - {file = "frozenlist-1.4.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:20b51fa3f588ff2fe658663db52a41a4f7aa6c04f6201449c6c7c476bd255c0d"}, - {file = "frozenlist-1.4.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:410478a0c562d1a5bcc2f7ea448359fcb050ed48b3c6f6f4f18c313a9bdb1826"}, - {file = "frozenlist-1.4.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:c6321c9efe29975232da3bd0af0ad216800a47e93d763ce64f291917a381b8eb"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:48f6a4533887e189dae092f1cf981f2e3885175f7a0f33c91fb5b7b682b6bab6"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6eb73fa5426ea69ee0e012fb59cdc76a15b1283d6e32e4f8dc4482ec67d1194d"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fbeb989b5cc29e8daf7f976b421c220f1b8c731cbf22b9130d8815418ea45887"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:32453c1de775c889eb4e22f1197fe3bdfe457d16476ea407472b9442e6295f7a"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:693945278a31f2086d9bf3df0fe8254bbeaef1fe71e1351c3bd730aa7d31c41b"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:1d0ce09d36d53bbbe566fe296965b23b961764c0bcf3ce2fa45f463745c04701"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:3a670dc61eb0d0eb7080890c13de3066790f9049b47b0de04007090807c776b0"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:dca69045298ce5c11fd539682cff879cc1e664c245d1c64da929813e54241d11"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:a06339f38e9ed3a64e4c4e43aec7f59084033647f908e4259d279a52d3757d09"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b7f2f9f912dca3934c1baec2e4585a674ef16fe00218d833856408c48d5beee7"}, - {file = "frozenlist-1.4.1-cp38-cp38-win32.whl", hash = "sha256:e7004be74cbb7d9f34553a5ce5fb08be14fb33bc86f332fb71cbe5216362a497"}, - {file = "frozenlist-1.4.1-cp38-cp38-win_amd64.whl", hash = "sha256:5a7d70357e7cee13f470c7883a063aae5fe209a493c57d86eb7f5a6f910fae09"}, - {file = "frozenlist-1.4.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:bfa4a17e17ce9abf47a74ae02f32d014c5e9404b6d9ac7f729e01562bbee601e"}, - {file = "frozenlist-1.4.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b7e3ed87d4138356775346e6845cccbe66cd9e207f3cd11d2f0b9fd13681359d"}, - {file = "frozenlist-1.4.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c99169d4ff810155ca50b4da3b075cbde79752443117d89429595c2e8e37fed8"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:edb678da49d9f72c9f6c609fbe41a5dfb9a9282f9e6a2253d5a91e0fc382d7c0"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6db4667b187a6742b33afbbaf05a7bc551ffcf1ced0000a571aedbb4aa42fc7b"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:55fdc093b5a3cb41d420884cdaf37a1e74c3c37a31f46e66286d9145d2063bd0"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:82e8211d69a4f4bc360ea22cd6555f8e61a1bd211d1d5d39d3d228b48c83a897"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89aa2c2eeb20957be2d950b85974b30a01a762f3308cd02bb15e1ad632e22dc7"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:9d3e0c25a2350080e9319724dede4f31f43a6c9779be48021a7f4ebde8b2d742"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:7268252af60904bf52c26173cbadc3a071cece75f873705419c8681f24d3edea"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:0c250a29735d4f15321007fb02865f0e6b6a41a6b88f1f523ca1596ab5f50bd5"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:96ec70beabbd3b10e8bfe52616a13561e58fe84c0101dd031dc78f250d5128b9"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:23b2d7679b73fe0e5a4560b672a39f98dfc6f60df63823b0a9970525325b95f6"}, - {file = "frozenlist-1.4.1-cp39-cp39-win32.whl", hash = "sha256:a7496bfe1da7fb1a4e1cc23bb67c58fab69311cc7d32b5a99c2007b4b2a0e932"}, - {file = "frozenlist-1.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:e6a20a581f9ce92d389a8c7d7c3dd47c81fd5d6e655c8dddf341e14aa48659d0"}, - {file = "frozenlist-1.4.1-py3-none-any.whl", hash = "sha256:04ced3e6a46b4cfffe20f9ae482818e34eba9b5fb0ce4056e4cc9b6e212d09b7"}, - {file = "frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5b6a66c18b5b9dd261ca98dffcb826a525334b2f29e7caa54e182255c5f6a65a"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1b3eb7b05ea246510b43a7e53ed1653e55c2121019a97e60cad7efb881a97bb"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:15538c0cbf0e4fa11d1e3a71f823524b0c46299aed6e10ebb4c2089abd8c3bec"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e79225373c317ff1e35f210dd5f1344ff31066ba8067c307ab60254cd3a78ad5"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9272fa73ca71266702c4c3e2d4a28553ea03418e591e377a03b8e3659d94fa76"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:498524025a5b8ba81695761d78c8dd7382ac0b052f34e66939c42df860b8ff17"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:92b5278ed9d50fe610185ecd23c55d8b307d75ca18e94c0e7de328089ac5dcba"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f3c8c1dacd037df16e85227bac13cca58c30da836c6f936ba1df0c05d046d8d"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f2ac49a9bedb996086057b75bf93538240538c6d9b38e57c82d51f75a73409d2"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e66cc454f97053b79c2ab09c17fbe3c825ea6b4de20baf1be28919460dd7877f"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5a3ba5f9a0dfed20337d3e966dc359784c9f96503674c2faf015f7fe8e96798c"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:6321899477db90bdeb9299ac3627a6a53c7399c8cd58d25da094007402b039ab"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:76e4753701248476e6286f2ef492af900ea67d9706a0155335a40ea21bf3b2f5"}, + {file = "frozenlist-1.5.0-cp310-cp310-win32.whl", hash = "sha256:977701c081c0241d0955c9586ffdd9ce44f7a7795df39b9151cd9a6fd0ce4cfb"}, + {file = "frozenlist-1.5.0-cp310-cp310-win_amd64.whl", hash = "sha256:189f03b53e64144f90990d29a27ec4f7997d91ed3d01b51fa39d2dbe77540fd4"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:fd74520371c3c4175142d02a976aee0b4cb4a7cc912a60586ffd8d5929979b30"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2f3f7a0fbc219fb4455264cae4d9f01ad41ae6ee8524500f381de64ffaa077d5"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f47c9c9028f55a04ac254346e92977bf0f166c483c74b4232bee19a6697e4778"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0996c66760924da6e88922756d99b47512a71cfd45215f3570bf1e0b694c206a"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a2fe128eb4edeabe11896cb6af88fca5346059f6c8d807e3b910069f39157869"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a8ea951bbb6cacd492e3948b8da8c502a3f814f5d20935aae74b5df2b19cf3d"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de537c11e4aa01d37db0d403b57bd6f0546e71a82347a97c6a9f0dcc532b3a45"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c2623347b933fcb9095841f1cc5d4ff0b278addd743e0e966cb3d460278840d"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:cee6798eaf8b1416ef6909b06f7dc04b60755206bddc599f52232606e18179d3"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:f5f9da7f5dbc00a604fe74aa02ae7c98bcede8a3b8b9666f9f86fc13993bc71a"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:90646abbc7a5d5c7c19461d2e3eeb76eb0b204919e6ece342feb6032c9325ae9"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:bdac3c7d9b705d253b2ce370fde941836a5f8b3c5c2b8fd70940a3ea3af7f4f2"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:03d33c2ddbc1816237a67f66336616416e2bbb6beb306e5f890f2eb22b959cdf"}, + {file = "frozenlist-1.5.0-cp311-cp311-win32.whl", hash = "sha256:237f6b23ee0f44066219dae14c70ae38a63f0440ce6750f868ee08775073f942"}, + {file = "frozenlist-1.5.0-cp311-cp311-win_amd64.whl", hash = "sha256:0cc974cc93d32c42e7b0f6cf242a6bd941c57c61b618e78b6c0a96cb72788c1d"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:31115ba75889723431aa9a4e77d5f398f5cf976eea3bdf61749731f62d4a4a21"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7437601c4d89d070eac8323f121fcf25f88674627505334654fd027b091db09d"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7948140d9f8ece1745be806f2bfdf390127cf1a763b925c4a805c603df5e697e"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:feeb64bc9bcc6b45c6311c9e9b99406660a9c05ca8a5b30d14a78555088b0b3a"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:683173d371daad49cffb8309779e886e59c2f369430ad28fe715f66d08d4ab1a"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7d57d8f702221405a9d9b40f9da8ac2e4a1a8b5285aac6100f3393675f0a85ee"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:30c72000fbcc35b129cb09956836c7d7abf78ab5416595e4857d1cae8d6251a6"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:000a77d6034fbad9b6bb880f7ec073027908f1b40254b5d6f26210d2dab1240e"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5d7f5a50342475962eb18b740f3beecc685a15b52c91f7d975257e13e029eca9"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:87f724d055eb4785d9be84e9ebf0f24e392ddfad00b3fe036e43f489fafc9039"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:6e9080bb2fb195a046e5177f10d9d82b8a204c0736a97a153c2466127de87784"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:9b93d7aaa36c966fa42efcaf716e6b3900438632a626fb09c049f6a2f09fc631"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:52ef692a4bc60a6dd57f507429636c2af8b6046db8b31b18dac02cbc8f507f7f"}, + {file = "frozenlist-1.5.0-cp312-cp312-win32.whl", hash = "sha256:29d94c256679247b33a3dc96cce0f93cbc69c23bf75ff715919332fdbb6a32b8"}, + {file = "frozenlist-1.5.0-cp312-cp312-win_amd64.whl", hash = "sha256:8969190d709e7c48ea386db202d708eb94bdb29207a1f269bab1196ce0dcca1f"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:7a1a048f9215c90973402e26c01d1cff8a209e1f1b53f72b95c13db61b00f953"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:dd47a5181ce5fcb463b5d9e17ecfdb02b678cca31280639255ce9d0e5aa67af0"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1431d60b36d15cda188ea222033eec8e0eab488f39a272461f2e6d9e1a8e63c2"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6482a5851f5d72767fbd0e507e80737f9c8646ae7fd303def99bfe813f76cf7f"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:44c49271a937625619e862baacbd037a7ef86dd1ee215afc298a417ff3270608"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:12f78f98c2f1c2429d42e6a485f433722b0061d5c0b0139efa64f396efb5886b"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ce3aa154c452d2467487765e3adc730a8c153af77ad84096bc19ce19a2400840"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b7dc0c4338e6b8b091e8faf0db3168a37101943e687f373dce00959583f7439"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:45e0896250900b5aa25180f9aec243e84e92ac84bd4a74d9ad4138ef3f5c97de"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:561eb1c9579d495fddb6da8959fd2a1fca2c6d060d4113f5844b433fc02f2641"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:df6e2f325bfee1f49f81aaac97d2aa757c7646534a06f8f577ce184afe2f0a9e"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:140228863501b44b809fb39ec56b5d4071f4d0aa6d216c19cbb08b8c5a7eadb9"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7707a25d6a77f5d27ea7dc7d1fc608aa0a478193823f88511ef5e6b8a48f9d03"}, + {file = "frozenlist-1.5.0-cp313-cp313-win32.whl", hash = "sha256:31a9ac2b38ab9b5a8933b693db4939764ad3f299fcaa931a3e605bc3460e693c"}, + {file = "frozenlist-1.5.0-cp313-cp313-win_amd64.whl", hash = "sha256:11aabdd62b8b9c4b84081a3c246506d1cddd2dd93ff0ad53ede5defec7886b28"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:dd94994fc91a6177bfaafd7d9fd951bc8689b0a98168aa26b5f543868548d3ca"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2d0da8bbec082bf6bf18345b180958775363588678f64998c2b7609e34719b10"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:73f2e31ea8dd7df61a359b731716018c2be196e5bb3b74ddba107f694fbd7604"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:828afae9f17e6de596825cf4228ff28fbdf6065974e5ac1410cecc22f699d2b3"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f1577515d35ed5649d52ab4319db757bb881ce3b2b796d7283e6634d99ace307"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2150cc6305a2c2ab33299453e2968611dacb970d2283a14955923062c8d00b10"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a72b7a6e3cd2725eff67cd64c8f13335ee18fc3c7befc05aed043d24c7b9ccb9"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c16d2fa63e0800723139137d667e1056bee1a1cf7965153d2d104b62855e9b99"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:17dcc32fc7bda7ce5875435003220a457bcfa34ab7924a49a1c19f55b6ee185c"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:97160e245ea33d8609cd2b8fd997c850b56db147a304a262abc2b3be021a9171"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:f1e6540b7fa044eee0bb5111ada694cf3dc15f2b0347ca125ee9ca984d5e9e6e"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:91d6c171862df0a6c61479d9724f22efb6109111017c87567cfeb7b5d1449fdf"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c1fac3e2ace2eb1052e9f7c7db480818371134410e1f5c55d65e8f3ac6d1407e"}, + {file = "frozenlist-1.5.0-cp38-cp38-win32.whl", hash = "sha256:b97f7b575ab4a8af9b7bc1d2ef7f29d3afee2226bd03ca3875c16451ad5a7723"}, + {file = "frozenlist-1.5.0-cp38-cp38-win_amd64.whl", hash = "sha256:374ca2dabdccad8e2a76d40b1d037f5bd16824933bf7bcea3e59c891fd4a0923"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:9bbcdfaf4af7ce002694a4e10a0159d5a8d20056a12b05b45cea944a4953f972"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1893f948bf6681733aaccf36c5232c231e3b5166d607c5fa77773611df6dc336"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2b5e23253bb709ef57a8e95e6ae48daa9ac5f265637529e4ce6b003a37b2621f"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f253985bb515ecd89629db13cb58d702035ecd8cfbca7d7a7e29a0e6d39af5f"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:04a5c6babd5e8fb7d3c871dc8b321166b80e41b637c31a995ed844a6139942b6"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9fe0f1c29ba24ba6ff6abf688cb0b7cf1efab6b6aa6adc55441773c252f7411"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:226d72559fa19babe2ccd920273e767c96a49b9d3d38badd7c91a0fdeda8ea08"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:15b731db116ab3aedec558573c1a5eec78822b32292fe4f2f0345b7f697745c2"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:366d8f93e3edfe5a918c874702f78faac300209a4d5bf38352b2c1bdc07a766d"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:1b96af8c582b94d381a1c1f51ffaedeb77c821c690ea5f01da3d70a487dd0a9b"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:c03eff4a41bd4e38415cbed054bbaff4a075b093e2394b6915dca34a40d1e38b"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:50cf5e7ee9b98f22bdecbabf3800ae78ddcc26e4a435515fc72d97903e8488e0"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1e76bfbc72353269c44e0bc2cfe171900fbf7f722ad74c9a7b638052afe6a00c"}, + {file = "frozenlist-1.5.0-cp39-cp39-win32.whl", hash = "sha256:666534d15ba8f0fda3f53969117383d5dc021266b3c1a42c9ec4855e4b58b9d3"}, + {file = "frozenlist-1.5.0-cp39-cp39-win_amd64.whl", hash = "sha256:5c28f4b5dbef8a0d8aad0d4de24d1e9e981728628afaf4ea0792f5d0939372f0"}, + {file = "frozenlist-1.5.0-py3-none-any.whl", hash = "sha256:d994863bba198a4a518b467bb971c56e1db3f180a25c6cf7bb1949c267f748c3"}, + {file = "frozenlist-1.5.0.tar.gz", hash = "sha256:81d5af29e61b9c8348e876d442253723928dce6433e0e76cd925cd83f1b4b817"}, ] [[package]] @@ -592,13 +593,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.6" +version = "1.0.7" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"}, - {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"}, + {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, + {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, ] [package.dependencies] @@ -688,34 +689,34 @@ files = [ [[package]] name = "langchain" -version = "0.3.3" +version = "0.3.8" description = "Building applications with LLMs through composability" optional = false python-versions = "<4.0,>=3.9" files = [ - {file = "langchain-0.3.3-py3-none-any.whl", hash = "sha256:05ac98c674853c2386d043172820e37ceac9b913aaaf1e51217f0fc424112c72"}, - {file = "langchain-0.3.3.tar.gz", hash = "sha256:6435882996a029a60c61c356bbe51bab4a8f43a54210f5f03e3c4474d19d1842"}, + {file = "langchain-0.3.8-py3-none-any.whl", hash = "sha256:5cae404da30bf6730639a9ad85d3bf4fbb350c0038e5a0b81890e5883b4cff5c"}, + {file = "langchain-0.3.8.tar.gz", hash = "sha256:1cbbf7379b5b2f11b751fc527016f29ee5fe8a2697d166b52b7b5c63fc9702f9"}, ] [package.dependencies] aiohttp = ">=3.8.3,<4.0.0" async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""} -langchain-core = ">=0.3.10,<0.4.0" +langchain-core = ">=0.3.21,<0.4.0" langchain-text-splitters = ">=0.3.0,<0.4.0" langsmith = ">=0.1.17,<0.2.0" numpy = [ - {version = ">=1,<2", markers = "python_version < \"3.12\""}, - {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""}, + {version = ">=1.22.4,<2", markers = "python_version < \"3.12\""}, + {version = ">=1.26.2,<2", markers = "python_version >= \"3.12\""}, ] pydantic = ">=2.7.4,<3.0.0" PyYAML = ">=5.3" requests = ">=2,<3" SQLAlchemy = ">=1.4,<3" -tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0" +tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10" [[package]] name = "langchain-core" -version = "0.3.15" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -740,32 +741,32 @@ url = "../../core" [[package]] name = "langchain-text-splitters" -version = "0.3.0" +version = "0.3.2" description = "LangChain text splitting utilities" optional = false python-versions = "<4.0,>=3.9" files = [ - {file = "langchain_text_splitters-0.3.0-py3-none-any.whl", hash = "sha256:e84243e45eaff16e5b776cd9c81b6d07c55c010ebcb1965deb3d1792b7358e83"}, - {file = "langchain_text_splitters-0.3.0.tar.gz", hash = "sha256:f9fe0b4d244db1d6de211e7343d4abc4aa90295aa22e1f0c89e51f33c55cd7ce"}, + {file = "langchain_text_splitters-0.3.2-py3-none-any.whl", hash = "sha256:0db28c53f41d1bc024cdb3b1646741f6d46d5371e90f31e7e7c9fbe75d01c726"}, + {file = "langchain_text_splitters-0.3.2.tar.gz", hash = "sha256:81e6515d9901d6dd8e35fb31ccd4f30f76d44b771890c789dc835ef9f16204df"}, ] [package.dependencies] -langchain-core = ">=0.3.0,<0.4.0" +langchain-core = ">=0.3.15,<0.4.0" [[package]] name = "langsmith" -version = "0.1.135" +version = "0.1.146" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.135-py3-none-any.whl", hash = "sha256:b1d1ca3bad483a4239745c57e9b9157b4d099fbf3149be21e3d112c94ede06ac"}, - {file = "langsmith-0.1.135.tar.gz", hash = "sha256:7abed7e141386af99a2177f0b3600b124ae3ad1b482879ba0724ce92ef998a11"}, + {file = "langsmith-0.1.146-py3-none-any.whl", hash = "sha256:9d062222f1a32c9b047dab0149b24958f988989cd8d4a5f9139ff959a51e59d8"}, + {file = "langsmith-0.1.146.tar.gz", hash = "sha256:ead8b0b9d5b6cd3ac42937ec48bdf09d4afe7ca1bba22dc05eb65591a18106f8"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -879,43 +880,43 @@ typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""} [[package]] name = "mypy" -version = "1.12.0" +version = "1.13.0" description = "Optional static typing for Python" optional = false python-versions = ">=3.8" files = [ - {file = "mypy-1.12.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:4397081e620dc4dc18e2f124d5e1d2c288194c2c08df6bdb1db31c38cd1fe1ed"}, - {file = "mypy-1.12.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:684a9c508a283f324804fea3f0effeb7858eb03f85c4402a967d187f64562469"}, - {file = "mypy-1.12.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6cabe4cda2fa5eca7ac94854c6c37039324baaa428ecbf4de4567279e9810f9e"}, - {file = "mypy-1.12.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:060a07b10e999ac9e7fa249ce2bdcfa9183ca2b70756f3bce9df7a92f78a3c0a"}, - {file = "mypy-1.12.0-cp310-cp310-win_amd64.whl", hash = "sha256:0eff042d7257f39ba4ca06641d110ca7d2ad98c9c1fb52200fe6b1c865d360ff"}, - {file = "mypy-1.12.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4b86de37a0da945f6d48cf110d5206c5ed514b1ca2614d7ad652d4bf099c7de7"}, - {file = "mypy-1.12.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:20c7c5ce0c1be0b0aea628374e6cf68b420bcc772d85c3c974f675b88e3e6e57"}, - {file = "mypy-1.12.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a64ee25f05fc2d3d8474985c58042b6759100a475f8237da1f4faf7fcd7e6309"}, - {file = "mypy-1.12.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:faca7ab947c9f457a08dcb8d9a8664fd438080e002b0fa3e41b0535335edcf7f"}, - {file = "mypy-1.12.0-cp311-cp311-win_amd64.whl", hash = "sha256:5bc81701d52cc8767005fdd2a08c19980de9ec61a25dbd2a937dfb1338a826f9"}, - {file = "mypy-1.12.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:8462655b6694feb1c99e433ea905d46c478041a8b8f0c33f1dab00ae881b2164"}, - {file = "mypy-1.12.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:923ea66d282d8af9e0f9c21ffc6653643abb95b658c3a8a32dca1eff09c06475"}, - {file = "mypy-1.12.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1ebf9e796521f99d61864ed89d1fb2926d9ab6a5fab421e457cd9c7e4dd65aa9"}, - {file = "mypy-1.12.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:e478601cc3e3fa9d6734d255a59c7a2e5c2934da4378f3dd1e3411ea8a248642"}, - {file = "mypy-1.12.0-cp312-cp312-win_amd64.whl", hash = "sha256:c72861b7139a4f738344faa0e150834467521a3fba42dc98264e5aa9507dd601"}, - {file = "mypy-1.12.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:52b9e1492e47e1790360a43755fa04101a7ac72287b1a53ce817f35899ba0521"}, - {file = "mypy-1.12.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:48d3e37dd7d9403e38fa86c46191de72705166d40b8c9f91a3de77350daa0893"}, - {file = "mypy-1.12.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2f106db5ccb60681b622ac768455743ee0e6a857724d648c9629a9bd2ac3f721"}, - {file = "mypy-1.12.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:233e11b3f73ee1f10efada2e6da0f555b2f3a5316e9d8a4a1224acc10e7181d3"}, - {file = "mypy-1.12.0-cp313-cp313-win_amd64.whl", hash = "sha256:4ae8959c21abcf9d73aa6c74a313c45c0b5a188752bf37dace564e29f06e9c1b"}, - {file = "mypy-1.12.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:eafc1b7319b40ddabdc3db8d7d48e76cfc65bbeeafaa525a4e0fa6b76175467f"}, - {file = "mypy-1.12.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:9b9ce1ad8daeb049c0b55fdb753d7414260bad8952645367e70ac91aec90e07e"}, - {file = "mypy-1.12.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bfe012b50e1491d439172c43ccb50db66d23fab714d500b57ed52526a1020bb7"}, - {file = "mypy-1.12.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:2c40658d4fa1ab27cb53d9e2f1066345596af2f8fe4827defc398a09c7c9519b"}, - {file = "mypy-1.12.0-cp38-cp38-win_amd64.whl", hash = "sha256:dee78a8b9746c30c1e617ccb1307b351ded57f0de0d287ca6276378d770006c0"}, - {file = "mypy-1.12.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:6b5df6c8a8224f6b86746bda716bbe4dbe0ce89fd67b1fa4661e11bfe38e8ec8"}, - {file = "mypy-1.12.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5feee5c74eb9749e91b77f60b30771563327329e29218d95bedbe1257e2fe4b0"}, - {file = "mypy-1.12.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:77278e8c6ffe2abfba6db4125de55f1024de9a323be13d20e4f73b8ed3402bd1"}, - {file = "mypy-1.12.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:dcfb754dea911039ac12434d1950d69a2f05acd4d56f7935ed402be09fad145e"}, - {file = "mypy-1.12.0-cp39-cp39-win_amd64.whl", hash = "sha256:06de0498798527451ffb60f68db0d368bd2bae2bbfb5237eae616d4330cc87aa"}, - {file = "mypy-1.12.0-py3-none-any.whl", hash = "sha256:fd313226af375d52e1e36c383f39bf3836e1f192801116b31b090dfcd3ec5266"}, - {file = "mypy-1.12.0.tar.gz", hash = "sha256:65a22d87e757ccd95cbbf6f7e181e6caa87128255eb2b6be901bb71b26d8a99d"}, + {file = "mypy-1.13.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6607e0f1dd1fb7f0aca14d936d13fd19eba5e17e1cd2a14f808fa5f8f6d8f60a"}, + {file = "mypy-1.13.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8a21be69bd26fa81b1f80a61ee7ab05b076c674d9b18fb56239d72e21d9f4c80"}, + {file = "mypy-1.13.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7b2353a44d2179846a096e25691d54d59904559f4232519d420d64da6828a3a7"}, + {file = "mypy-1.13.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0730d1c6a2739d4511dc4253f8274cdd140c55c32dfb0a4cf8b7a43f40abfa6f"}, + {file = "mypy-1.13.0-cp310-cp310-win_amd64.whl", hash = "sha256:c5fc54dbb712ff5e5a0fca797e6e0aa25726c7e72c6a5850cfd2adbc1eb0a372"}, + {file = "mypy-1.13.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:581665e6f3a8a9078f28d5502f4c334c0c8d802ef55ea0e7276a6e409bc0d82d"}, + {file = "mypy-1.13.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3ddb5b9bf82e05cc9a627e84707b528e5c7caaa1c55c69e175abb15a761cec2d"}, + {file = "mypy-1.13.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:20c7ee0bc0d5a9595c46f38beb04201f2620065a93755704e141fcac9f59db2b"}, + {file = "mypy-1.13.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:3790ded76f0b34bc9c8ba4def8f919dd6a46db0f5a6610fb994fe8efdd447f73"}, + {file = "mypy-1.13.0-cp311-cp311-win_amd64.whl", hash = "sha256:51f869f4b6b538229c1d1bcc1dd7d119817206e2bc54e8e374b3dfa202defcca"}, + {file = "mypy-1.13.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:5c7051a3461ae84dfb5dd15eff5094640c61c5f22257c8b766794e6dd85e72d5"}, + {file = "mypy-1.13.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:39bb21c69a5d6342f4ce526e4584bc5c197fd20a60d14a8624d8743fffb9472e"}, + {file = "mypy-1.13.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:164f28cb9d6367439031f4c81e84d3ccaa1e19232d9d05d37cb0bd880d3f93c2"}, + {file = "mypy-1.13.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a4c1bfcdbce96ff5d96fc9b08e3831acb30dc44ab02671eca5953eadad07d6d0"}, + {file = "mypy-1.13.0-cp312-cp312-win_amd64.whl", hash = "sha256:a0affb3a79a256b4183ba09811e3577c5163ed06685e4d4b46429a271ba174d2"}, + {file = "mypy-1.13.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:a7b44178c9760ce1a43f544e595d35ed61ac2c3de306599fa59b38a6048e1aa7"}, + {file = "mypy-1.13.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:5d5092efb8516d08440e36626f0153b5006d4088c1d663d88bf79625af3d1d62"}, + {file = "mypy-1.13.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:de2904956dac40ced10931ac967ae63c5089bd498542194b436eb097a9f77bc8"}, + {file = "mypy-1.13.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:7bfd8836970d33c2105562650656b6846149374dc8ed77d98424b40b09340ba7"}, + {file = "mypy-1.13.0-cp313-cp313-win_amd64.whl", hash = "sha256:9f73dba9ec77acb86457a8fc04b5239822df0c14a082564737833d2963677dbc"}, + {file = "mypy-1.13.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:100fac22ce82925f676a734af0db922ecfea991e1d7ec0ceb1e115ebe501301a"}, + {file = "mypy-1.13.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:7bcb0bb7f42a978bb323a7c88f1081d1b5dee77ca86f4100735a6f541299d8fb"}, + {file = "mypy-1.13.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bde31fc887c213e223bbfc34328070996061b0833b0a4cfec53745ed61f3519b"}, + {file = "mypy-1.13.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:07de989f89786f62b937851295ed62e51774722e5444a27cecca993fc3f9cd74"}, + {file = "mypy-1.13.0-cp38-cp38-win_amd64.whl", hash = "sha256:4bde84334fbe19bad704b3f5b78c4abd35ff1026f8ba72b29de70dda0916beb6"}, + {file = "mypy-1.13.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0246bcb1b5de7f08f2826451abd947bf656945209b140d16ed317f65a17dc7dc"}, + {file = "mypy-1.13.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:7f5b7deae912cf8b77e990b9280f170381fdfbddf61b4ef80927edd813163732"}, + {file = "mypy-1.13.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7029881ec6ffb8bc233a4fa364736789582c738217b133f1b55967115288a2bc"}, + {file = "mypy-1.13.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:3e38b980e5681f28f033f3be86b099a247b13c491f14bb8b1e1e134d23bb599d"}, + {file = "mypy-1.13.0-cp39-cp39-win_amd64.whl", hash = "sha256:a6789be98a2017c912ae6ccb77ea553bbaf13d27605d2ca20a76dfbced631b24"}, + {file = "mypy-1.13.0-py3-none-any.whl", hash = "sha256:9c250883f9fd81d212e0952c92dbfcc96fc237f4b7c92f56ac81fd48460b3e5a"}, + {file = "mypy-1.13.0.tar.gz", hash = "sha256:0291a61b6fbf3e6673e3405cfcc0e7650bebc7939659fdca2702958038bd835e"}, ] [package.dependencies] @@ -925,6 +926,7 @@ typing-extensions = ">=4.6.0" [package.extras] dmypy = ["psutil (>=4.0)"] +faster-cache = ["orjson"] install-types = ["pip"] mypyc = ["setuptools (>=50)"] reports = ["lxml"] @@ -987,79 +989,97 @@ files = [ [[package]] name = "orjson" -version = "3.10.7" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.7-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:74f4544f5a6405b90da8ea724d15ac9c36da4d72a738c64685003337401f5c12"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34a566f22c28222b08875b18b0dfbf8a947e69df21a9ed5c51a6bf91cfb944ac"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bf6ba8ebc8ef5792e2337fb0419f8009729335bb400ece005606336b7fd7bab7"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ac7cf6222b29fbda9e3a472b41e6a5538b48f2c8f99261eecd60aafbdb60690c"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de817e2f5fc75a9e7dd350c4b0f54617b280e26d1631811a43e7e968fa71e3e9"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:348bdd16b32556cf8d7257b17cf2bdb7ab7976af4af41ebe79f9796c218f7e91"}, - {file = "orjson-3.10.7-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:479fd0844ddc3ca77e0fd99644c7fe2de8e8be1efcd57705b5c92e5186e8a250"}, - {file = "orjson-3.10.7-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:fdf5197a21dd660cf19dfd2a3ce79574588f8f5e2dbf21bda9ee2d2b46924d84"}, - {file = "orjson-3.10.7-cp310-none-win32.whl", hash = "sha256:d374d36726746c81a49f3ff8daa2898dccab6596864ebe43d50733275c629175"}, - {file = "orjson-3.10.7-cp310-none-win_amd64.whl", hash = "sha256:cb61938aec8b0ffb6eef484d480188a1777e67b05d58e41b435c74b9d84e0b9c"}, - {file = "orjson-3.10.7-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7db8539039698ddfb9a524b4dd19508256107568cdad24f3682d5773e60504a2"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:480f455222cb7a1dea35c57a67578848537d2602b46c464472c995297117fa09"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8a9c9b168b3a19e37fe2778c0003359f07822c90fdff8f98d9d2a91b3144d8e0"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8de062de550f63185e4c1c54151bdddfc5625e37daf0aa1e75d2a1293e3b7d9a"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6b0dd04483499d1de9c8f6203f8975caf17a6000b9c0c54630cef02e44ee624e"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b58d3795dafa334fc8fd46f7c5dc013e6ad06fd5b9a4cc98cb1456e7d3558bd6"}, - {file = "orjson-3.10.7-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:33cfb96c24034a878d83d1a9415799a73dc77480e6c40417e5dda0710d559ee6"}, - {file = "orjson-3.10.7-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e724cebe1fadc2b23c6f7415bad5ee6239e00a69f30ee423f319c6af70e2a5c0"}, - {file = "orjson-3.10.7-cp311-none-win32.whl", hash = "sha256:82763b46053727a7168d29c772ed5c870fdae2f61aa8a25994c7984a19b1021f"}, - {file = "orjson-3.10.7-cp311-none-win_amd64.whl", hash = "sha256:eb8d384a24778abf29afb8e41d68fdd9a156cf6e5390c04cc07bbc24b89e98b5"}, - {file = "orjson-3.10.7-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:44a96f2d4c3af51bfac6bc4ef7b182aa33f2f054fd7f34cc0ee9a320d051d41f"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:76ac14cd57df0572453543f8f2575e2d01ae9e790c21f57627803f5e79b0d3c3"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bdbb61dcc365dd9be94e8f7df91975edc9364d6a78c8f7adb69c1cdff318ec93"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b48b3db6bb6e0a08fa8c83b47bc169623f801e5cc4f24442ab2b6617da3b5313"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23820a1563a1d386414fef15c249040042b8e5d07b40ab3fe3efbfbbcbcb8864"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0c6a008e91d10a2564edbb6ee5069a9e66df3fbe11c9a005cb411f441fd2c09"}, - {file = "orjson-3.10.7-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d352ee8ac1926d6193f602cbe36b1643bbd1bbcb25e3c1a657a4390f3000c9a5"}, - {file = "orjson-3.10.7-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:d2d9f990623f15c0ae7ac608103c33dfe1486d2ed974ac3f40b693bad1a22a7b"}, - {file = "orjson-3.10.7-cp312-none-win32.whl", hash = "sha256:7c4c17f8157bd520cdb7195f75ddbd31671997cbe10aee559c2d613592e7d7eb"}, - {file = "orjson-3.10.7-cp312-none-win_amd64.whl", hash = "sha256:1d9c0e733e02ada3ed6098a10a8ee0052dd55774de3d9110d29868d24b17faa1"}, - {file = "orjson-3.10.7-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:77d325ed866876c0fa6492598ec01fe30e803272a6e8b10e992288b009cbe149"}, - {file = "orjson-3.10.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ea2c232deedcb605e853ae1db2cc94f7390ac776743b699b50b071b02bea6fe"}, - {file = "orjson-3.10.7-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3dcfbede6737fdbef3ce9c37af3fb6142e8e1ebc10336daa05872bfb1d87839c"}, - {file = "orjson-3.10.7-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:11748c135f281203f4ee695b7f80bb1358a82a63905f9f0b794769483ea854ad"}, - {file = "orjson-3.10.7-cp313-none-win32.whl", hash = "sha256:a7e19150d215c7a13f39eb787d84db274298d3f83d85463e61d277bbd7f401d2"}, - {file = "orjson-3.10.7-cp313-none-win_amd64.whl", hash = "sha256:eef44224729e9525d5261cc8d28d6b11cafc90e6bd0be2157bde69a52ec83024"}, - {file = "orjson-3.10.7-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6ea2b2258eff652c82652d5e0f02bd5e0463a6a52abb78e49ac288827aaa1469"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:430ee4d85841e1483d487e7b81401785a5dfd69db5de01314538f31f8fbf7ee1"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4b6146e439af4c2472c56f8540d799a67a81226e11992008cb47e1267a9b3225"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:084e537806b458911137f76097e53ce7bf5806dda33ddf6aaa66a028f8d43a23"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4829cf2195838e3f93b70fd3b4292156fc5e097aac3739859ac0dcc722b27ac0"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1193b2416cbad1a769f868b1749535d5da47626ac29445803dae7cc64b3f5c98"}, - {file = "orjson-3.10.7-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:4e6c3da13e5a57e4b3dca2de059f243ebec705857522f188f0180ae88badd354"}, - {file = "orjson-3.10.7-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c31008598424dfbe52ce8c5b47e0752dca918a4fdc4a2a32004efd9fab41d866"}, - {file = "orjson-3.10.7-cp38-none-win32.whl", hash = "sha256:7122a99831f9e7fe977dc45784d3b2edc821c172d545e6420c375e5a935f5a1c"}, - {file = "orjson-3.10.7-cp38-none-win_amd64.whl", hash = "sha256:a763bc0e58504cc803739e7df040685816145a6f3c8a589787084b54ebc9f16e"}, - {file = "orjson-3.10.7-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:e76be12658a6fa376fcd331b1ea4e58f5a06fd0220653450f0d415b8fd0fbe20"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ed350d6978d28b92939bfeb1a0570c523f6170efc3f0a0ef1f1df287cd4f4960"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:144888c76f8520e39bfa121b31fd637e18d4cc2f115727865fdf9fa325b10412"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:09b2d92fd95ad2402188cf51573acde57eb269eddabaa60f69ea0d733e789fe9"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b24a579123fa884f3a3caadaed7b75eb5715ee2b17ab5c66ac97d29b18fe57f"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e72591bcfe7512353bd609875ab38050efe3d55e18934e2f18950c108334b4ff"}, - {file = "orjson-3.10.7-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:f4db56635b58cd1a200b0a23744ff44206ee6aa428185e2b6c4a65b3197abdcd"}, - {file = "orjson-3.10.7-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:0fa5886854673222618638c6df7718ea7fe2f3f2384c452c9ccedc70b4a510a5"}, - {file = "orjson-3.10.7-cp39-none-win32.whl", hash = "sha256:8272527d08450ab16eb405f47e0f4ef0e5ff5981c3d82afe0efd25dcbef2bcd2"}, - {file = "orjson-3.10.7-cp39-none-win_amd64.whl", hash = "sha256:974683d4618c0c7dbf4f69c95a979734bf183d0658611760017f6e70a145af58"}, - {file = "orjson-3.10.7.tar.gz", hash = "sha256:75ef0640403f945f3a1f9f6400686560dbfb0fb5b16589ad62cd477043c4eee3"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] name = "packaging" -version = "24.1" +version = "24.2" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" files = [ - {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"}, - {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"}, + {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, + {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, ] [[package]] @@ -1186,22 +1206,19 @@ files = [ [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.2" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.2-py3-none-any.whl", hash = "sha256:cfb96e45951117c3024e6b67b25cdc33a3cb7b2fa62e239f7af1378358a1d99e"}, + {file = "pydantic-2.10.2.tar.gz", hash = "sha256:2bc2d7f17232e0841cbba4641e65ba1eb6fafb3a08de3a091ff3ce14a197c4fa"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -1209,100 +1226,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -1594,13 +1622,13 @@ sqlcipher = ["sqlcipher3_binary"] [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -1608,13 +1636,13 @@ pytest = ">=7.0.0,<9.0.0" [[package]] name = "tenacity" -version = "8.5.0" +version = "9.0.0" description = "Retry code until it succeeds" optional = false python-versions = ">=3.8" files = [ - {file = "tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687"}, - {file = "tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78"}, + {file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"}, + {file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"}, ] [package.extras] @@ -1623,13 +1651,13 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tomli" -version = "2.0.2" +version = "2.1.0" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"}, - {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"}, + {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, + {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, ] [[package]] @@ -1662,109 +1690,93 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "yarl" -version = "1.15.2" +version = "1.18.0" description = "Yet another URL library" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "yarl-1.15.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e4ee8b8639070ff246ad3649294336b06db37a94bdea0d09ea491603e0be73b8"}, - {file = "yarl-1.15.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a7cf963a357c5f00cb55b1955df8bbe68d2f2f65de065160a1c26b85a1e44172"}, - {file = "yarl-1.15.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:43ebdcc120e2ca679dba01a779333a8ea76b50547b55e812b8b92818d604662c"}, - {file = "yarl-1.15.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3433da95b51a75692dcf6cc8117a31410447c75a9a8187888f02ad45c0a86c50"}, - {file = "yarl-1.15.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:38d0124fa992dbacd0c48b1b755d3ee0a9f924f427f95b0ef376556a24debf01"}, - {file = "yarl-1.15.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ded1b1803151dd0f20a8945508786d57c2f97a50289b16f2629f85433e546d47"}, - {file = "yarl-1.15.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ace4cad790f3bf872c082366c9edd7f8f8f77afe3992b134cfc810332206884f"}, - {file = "yarl-1.15.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c77494a2f2282d9bbbbcab7c227a4d1b4bb829875c96251f66fb5f3bae4fb053"}, - {file = "yarl-1.15.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:b7f227ca6db5a9fda0a2b935a2ea34a7267589ffc63c8045f0e4edb8d8dcf956"}, - {file = "yarl-1.15.2-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:31561a5b4d8dbef1559b3600b045607cf804bae040f64b5f5bca77da38084a8a"}, - {file = "yarl-1.15.2-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3e52474256a7db9dcf3c5f4ca0b300fdea6c21cca0148c8891d03a025649d935"}, - {file = "yarl-1.15.2-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:0e1af74a9529a1137c67c887ed9cde62cff53aa4d84a3adbec329f9ec47a3936"}, - {file = "yarl-1.15.2-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:15c87339490100c63472a76d87fe7097a0835c705eb5ae79fd96e343473629ed"}, - {file = "yarl-1.15.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:74abb8709ea54cc483c4fb57fb17bb66f8e0f04438cff6ded322074dbd17c7ec"}, - {file = "yarl-1.15.2-cp310-cp310-win32.whl", hash = "sha256:ffd591e22b22f9cb48e472529db6a47203c41c2c5911ff0a52e85723196c0d75"}, - {file = "yarl-1.15.2-cp310-cp310-win_amd64.whl", hash = "sha256:1695497bb2a02a6de60064c9f077a4ae9c25c73624e0d43e3aa9d16d983073c2"}, - {file = "yarl-1.15.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:9fcda20b2de7042cc35cf911702fa3d8311bd40055a14446c1e62403684afdc5"}, - {file = "yarl-1.15.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0545de8c688fbbf3088f9e8b801157923be4bf8e7b03e97c2ecd4dfa39e48e0e"}, - {file = "yarl-1.15.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:fbda058a9a68bec347962595f50546a8a4a34fd7b0654a7b9697917dc2bf810d"}, - {file = "yarl-1.15.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d1ac2bc069f4a458634c26b101c2341b18da85cb96afe0015990507efec2e417"}, - {file = "yarl-1.15.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cd126498171f752dd85737ab1544329a4520c53eed3997f9b08aefbafb1cc53b"}, - {file = "yarl-1.15.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3db817b4e95eb05c362e3b45dafe7144b18603e1211f4a5b36eb9522ecc62bcf"}, - {file = "yarl-1.15.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:076b1ed2ac819933895b1a000904f62d615fe4533a5cf3e052ff9a1da560575c"}, - {file = "yarl-1.15.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f8cfd847e6b9ecf9f2f2531c8427035f291ec286c0a4944b0a9fce58c6446046"}, - {file = "yarl-1.15.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:32b66be100ac5739065496c74c4b7f3015cef792c3174982809274d7e51b3e04"}, - {file = "yarl-1.15.2-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:34a2d76a1984cac04ff8b1bfc939ec9dc0914821264d4a9c8fd0ed6aa8d4cfd2"}, - {file = "yarl-1.15.2-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:0afad2cd484908f472c8fe2e8ef499facee54a0a6978be0e0cff67b1254fd747"}, - {file = "yarl-1.15.2-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:c68e820879ff39992c7f148113b46efcd6ec765a4865581f2902b3c43a5f4bbb"}, - {file = "yarl-1.15.2-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:98f68df80ec6ca3015186b2677c208c096d646ef37bbf8b49764ab4a38183931"}, - {file = "yarl-1.15.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:3c56ec1eacd0a5d35b8a29f468659c47f4fe61b2cab948ca756c39b7617f0aa5"}, - {file = "yarl-1.15.2-cp311-cp311-win32.whl", hash = "sha256:eedc3f247ee7b3808ea07205f3e7d7879bc19ad3e6222195cd5fbf9988853e4d"}, - {file = "yarl-1.15.2-cp311-cp311-win_amd64.whl", hash = "sha256:0ccaa1bc98751fbfcf53dc8dfdb90d96e98838010fc254180dd6707a6e8bb179"}, - {file = "yarl-1.15.2-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:82d5161e8cb8f36ec778fd7ac4d740415d84030f5b9ef8fe4da54784a1f46c94"}, - {file = "yarl-1.15.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fa2bea05ff0a8fb4d8124498e00e02398f06d23cdadd0fe027d84a3f7afde31e"}, - {file = "yarl-1.15.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:99e12d2bf587b44deb74e0d6170fec37adb489964dbca656ec41a7cd8f2ff178"}, - {file = "yarl-1.15.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:243fbbbf003754fe41b5bdf10ce1e7f80bcc70732b5b54222c124d6b4c2ab31c"}, - {file = "yarl-1.15.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:856b7f1a7b98a8c31823285786bd566cf06226ac4f38b3ef462f593c608a9bd6"}, - {file = "yarl-1.15.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:553dad9af802a9ad1a6525e7528152a015b85fb8dbf764ebfc755c695f488367"}, - {file = "yarl-1.15.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:30c3ff305f6e06650a761c4393666f77384f1cc6c5c0251965d6bfa5fbc88f7f"}, - {file = "yarl-1.15.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:353665775be69bbfc6d54c8d134bfc533e332149faeddd631b0bc79df0897f46"}, - {file = "yarl-1.15.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f4fe99ce44128c71233d0d72152db31ca119711dfc5f2c82385ad611d8d7f897"}, - {file = "yarl-1.15.2-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:9c1e3ff4b89cdd2e1a24c214f141e848b9e0451f08d7d4963cb4108d4d798f1f"}, - {file = "yarl-1.15.2-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:711bdfae4e699a6d4f371137cbe9e740dc958530cb920eb6f43ff9551e17cfbc"}, - {file = "yarl-1.15.2-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:4388c72174868884f76affcdd3656544c426407e0043c89b684d22fb265e04a5"}, - {file = "yarl-1.15.2-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:f0e1844ad47c7bd5d6fa784f1d4accc5f4168b48999303a868fe0f8597bde715"}, - {file = "yarl-1.15.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:a5cafb02cf097a82d74403f7e0b6b9df3ffbfe8edf9415ea816314711764a27b"}, - {file = "yarl-1.15.2-cp312-cp312-win32.whl", hash = "sha256:156ececdf636143f508770bf8a3a0498de64da5abd890c7dbb42ca9e3b6c05b8"}, - {file = "yarl-1.15.2-cp312-cp312-win_amd64.whl", hash = "sha256:435aca062444a7f0c884861d2e3ea79883bd1cd19d0a381928b69ae1b85bc51d"}, - {file = "yarl-1.15.2-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:416f2e3beaeae81e2f7a45dc711258be5bdc79c940a9a270b266c0bec038fb84"}, - {file = "yarl-1.15.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:173563f3696124372831007e3d4b9821746964a95968628f7075d9231ac6bb33"}, - {file = "yarl-1.15.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9ce2e0f6123a60bd1a7f5ae3b2c49b240c12c132847f17aa990b841a417598a2"}, - {file = "yarl-1.15.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eaea112aed589131f73d50d570a6864728bd7c0c66ef6c9154ed7b59f24da611"}, - {file = "yarl-1.15.2-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e4ca3b9f370f218cc2a0309542cab8d0acdfd66667e7c37d04d617012485f904"}, - {file = "yarl-1.15.2-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23ec1d3c31882b2a8a69c801ef58ebf7bae2553211ebbddf04235be275a38548"}, - {file = "yarl-1.15.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75119badf45f7183e10e348edff5a76a94dc19ba9287d94001ff05e81475967b"}, - {file = "yarl-1.15.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:78e6fdc976ec966b99e4daa3812fac0274cc28cd2b24b0d92462e2e5ef90d368"}, - {file = "yarl-1.15.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:8657d3f37f781d987037f9cc20bbc8b40425fa14380c87da0cb8dfce7c92d0fb"}, - {file = "yarl-1.15.2-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:93bed8a8084544c6efe8856c362af08a23e959340c87a95687fdbe9c9f280c8b"}, - {file = "yarl-1.15.2-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:69d5856d526802cbda768d3e6246cd0d77450fa2a4bc2ea0ea14f0d972c2894b"}, - {file = "yarl-1.15.2-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:ccad2800dfdff34392448c4bf834be124f10a5bc102f254521d931c1c53c455a"}, - {file = "yarl-1.15.2-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:a880372e2e5dbb9258a4e8ff43f13888039abb9dd6d515f28611c54361bc5644"}, - {file = "yarl-1.15.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:c998d0558805860503bc3a595994895ca0f7835e00668dadc673bbf7f5fbfcbe"}, - {file = "yarl-1.15.2-cp313-cp313-win32.whl", hash = "sha256:533a28754e7f7439f217550a497bb026c54072dbe16402b183fdbca2431935a9"}, - {file = "yarl-1.15.2-cp313-cp313-win_amd64.whl", hash = "sha256:5838f2b79dc8f96fdc44077c9e4e2e33d7089b10788464609df788eb97d03aad"}, - {file = "yarl-1.15.2-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:fbbb63bed5fcd70cd3dd23a087cd78e4675fb5a2963b8af53f945cbbca79ae16"}, - {file = "yarl-1.15.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:e2e93b88ecc8f74074012e18d679fb2e9c746f2a56f79cd5e2b1afcf2a8a786b"}, - {file = "yarl-1.15.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:af8ff8d7dc07ce873f643de6dfbcd45dc3db2c87462e5c387267197f59e6d776"}, - {file = "yarl-1.15.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:66f629632220a4e7858b58e4857927dd01a850a4cef2fb4044c8662787165cf7"}, - {file = "yarl-1.15.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:833547179c31f9bec39b49601d282d6f0ea1633620701288934c5f66d88c3e50"}, - {file = "yarl-1.15.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2aa738e0282be54eede1e3f36b81f1e46aee7ec7602aa563e81e0e8d7b67963f"}, - {file = "yarl-1.15.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a13a07532e8e1c4a5a3afff0ca4553da23409fad65def1b71186fb867eeae8d"}, - {file = "yarl-1.15.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c45817e3e6972109d1a2c65091504a537e257bc3c885b4e78a95baa96df6a3f8"}, - {file = "yarl-1.15.2-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:670eb11325ed3a6209339974b276811867defe52f4188fe18dc49855774fa9cf"}, - {file = "yarl-1.15.2-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:d417a4f6943112fae3924bae2af7112562285848d9bcee737fc4ff7cbd450e6c"}, - {file = "yarl-1.15.2-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:bc8936d06cd53fddd4892677d65e98af514c8d78c79864f418bbf78a4a2edde4"}, - {file = "yarl-1.15.2-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:954dde77c404084c2544e572f342aef384240b3e434e06cecc71597e95fd1ce7"}, - {file = "yarl-1.15.2-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:5bc0df728e4def5e15a754521e8882ba5a5121bd6b5a3a0ff7efda5d6558ab3d"}, - {file = "yarl-1.15.2-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:b71862a652f50babab4a43a487f157d26b464b1dedbcc0afda02fd64f3809d04"}, - {file = "yarl-1.15.2-cp38-cp38-win32.whl", hash = "sha256:63eab904f8630aed5a68f2d0aeab565dcfc595dc1bf0b91b71d9ddd43dea3aea"}, - {file = "yarl-1.15.2-cp38-cp38-win_amd64.whl", hash = "sha256:2cf441c4b6e538ba0d2591574f95d3fdd33f1efafa864faa077d9636ecc0c4e9"}, - {file = "yarl-1.15.2-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:a32d58f4b521bb98b2c0aa9da407f8bd57ca81f34362bcb090e4a79e9924fefc"}, - {file = "yarl-1.15.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:766dcc00b943c089349d4060b935c76281f6be225e39994c2ccec3a2a36ad627"}, - {file = "yarl-1.15.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:bed1b5dbf90bad3bfc19439258c97873eab453c71d8b6869c136346acfe497e7"}, - {file = "yarl-1.15.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ed20a4bdc635f36cb19e630bfc644181dd075839b6fc84cac51c0f381ac472e2"}, - {file = "yarl-1.15.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d538df442c0d9665664ab6dd5fccd0110fa3b364914f9c85b3ef9b7b2e157980"}, - {file = "yarl-1.15.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28c6cf1d92edf936ceedc7afa61b07e9d78a27b15244aa46bbcd534c7458ee1b"}, - {file = "yarl-1.15.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ce44217ad99ffad8027d2fde0269ae368c86db66ea0571c62a000798d69401fb"}, - {file = "yarl-1.15.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b47a6000a7e833ebfe5886b56a31cb2ff12120b1efd4578a6fcc38df16cc77bd"}, - {file = "yarl-1.15.2-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:e52f77a0cd246086afde8815039f3e16f8d2be51786c0a39b57104c563c5cbb0"}, - {file = "yarl-1.15.2-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:f9ca0e6ce7774dc7830dc0cc4bb6b3eec769db667f230e7c770a628c1aa5681b"}, - {file = "yarl-1.15.2-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:136f9db0f53c0206db38b8cd0c985c78ded5fd596c9a86ce5c0b92afb91c3a19"}, - {file = "yarl-1.15.2-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:173866d9f7409c0fb514cf6e78952e65816600cb888c68b37b41147349fe0057"}, - {file = "yarl-1.15.2-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:6e840553c9c494a35e449a987ca2c4f8372668ee954a03a9a9685075228e5036"}, - {file = "yarl-1.15.2-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:458c0c65802d816a6b955cf3603186de79e8fdb46d4f19abaec4ef0a906f50a7"}, - {file = "yarl-1.15.2-cp39-cp39-win32.whl", hash = "sha256:5b48388ded01f6f2429a8c55012bdbd1c2a0c3735b3e73e221649e524c34a58d"}, - {file = "yarl-1.15.2-cp39-cp39-win_amd64.whl", hash = "sha256:81dadafb3aa124f86dc267a2168f71bbd2bfb163663661ab0038f6e4b8edb810"}, - {file = "yarl-1.15.2-py3-none-any.whl", hash = "sha256:0d3105efab7c5c091609abacad33afff33bdff0035bece164c98bcf5a85ef90a"}, - {file = "yarl-1.15.2.tar.gz", hash = "sha256:a39c36f4218a5bb668b4f06874d676d35a035ee668e6e7e3538835c703634b84"}, + {file = "yarl-1.18.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:074fee89caab89a97e18ef5f29060ef61ba3cae6cd77673acc54bfdd3214b7b7"}, + {file = "yarl-1.18.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b026cf2c32daf48d90c0c4e406815c3f8f4cfe0c6dfccb094a9add1ff6a0e41a"}, + {file = "yarl-1.18.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:ae38bd86eae3ba3d2ce5636cc9e23c80c9db2e9cb557e40b98153ed102b5a736"}, + {file = "yarl-1.18.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:685cc37f3f307c6a8e879986c6d85328f4c637f002e219f50e2ef66f7e062c1d"}, + {file = "yarl-1.18.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8254dbfce84ee5d1e81051ee7a0f1536c108ba294c0fdb5933476398df0654f3"}, + {file = "yarl-1.18.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:20de4a8b04de70c49698dc2390b7fd2d18d424d3b876371f9b775e2b462d4b41"}, + {file = "yarl-1.18.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b0a2074a37285570d54b55820687de3d2f2b9ecf1b714e482e48c9e7c0402038"}, + {file = "yarl-1.18.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3f576ed278860df2721a5d57da3381040176ef1d07def9688a385c8330db61a1"}, + {file = "yarl-1.18.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3a3709450a574d61be6ac53d582496014342ea34876af8dc17cc16da32826c9a"}, + {file = "yarl-1.18.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:bd80ed29761490c622edde5dd70537ca8c992c2952eb62ed46984f8eff66d6e8"}, + {file = "yarl-1.18.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:32141e13a1d5a48525e519c9197d3f4d9744d818d5c7d6547524cc9eccc8971e"}, + {file = "yarl-1.18.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:8b8d3e4e014fb4274f1c5bf61511d2199e263909fb0b8bda2a7428b0894e8dc6"}, + {file = "yarl-1.18.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:701bb4a8f4de191c8c0cc9a1e6d5142f4df880e9d1210e333b829ca9425570ed"}, + {file = "yarl-1.18.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:a45d94075ac0647621eaaf693c8751813a3eccac455d423f473ffed38c8ac5c9"}, + {file = "yarl-1.18.0-cp310-cp310-win32.whl", hash = "sha256:34176bfb082add67cb2a20abd85854165540891147f88b687a5ed0dc225750a0"}, + {file = "yarl-1.18.0-cp310-cp310-win_amd64.whl", hash = "sha256:73553bbeea7d6ec88c08ad8027f4e992798f0abc459361bf06641c71972794dc"}, + {file = "yarl-1.18.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:b8e8c516dc4e1a51d86ac975b0350735007e554c962281c432eaa5822aa9765c"}, + {file = "yarl-1.18.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2e6b4466714a73f5251d84b471475850954f1fa6acce4d3f404da1d55d644c34"}, + {file = "yarl-1.18.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c893f8c1a6d48b25961e00922724732d00b39de8bb0b451307482dc87bddcd74"}, + {file = "yarl-1.18.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:13aaf2bdbc8c86ddce48626b15f4987f22e80d898818d735b20bd58f17292ee8"}, + {file = "yarl-1.18.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dd21c0128e301851de51bc607b0a6da50e82dc34e9601f4b508d08cc89ee7929"}, + {file = "yarl-1.18.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:205de377bd23365cd85562c9c6c33844050a93661640fda38e0567d2826b50df"}, + {file = "yarl-1.18.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ed69af4fe2a0949b1ea1d012bf065c77b4c7822bad4737f17807af2adb15a73c"}, + {file = "yarl-1.18.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8e1c18890091aa3cc8a77967943476b729dc2016f4cfe11e45d89b12519d4a93"}, + {file = "yarl-1.18.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:91b8fb9427e33f83ca2ba9501221ffaac1ecf0407f758c4d2f283c523da185ee"}, + {file = "yarl-1.18.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:536a7a8a53b75b2e98ff96edb2dfb91a26b81c4fed82782035767db5a465be46"}, + {file = "yarl-1.18.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:a64619a9c47c25582190af38e9eb382279ad42e1f06034f14d794670796016c0"}, + {file = "yarl-1.18.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:c73a6bbc97ba1b5a0c3c992ae93d721c395bdbb120492759b94cc1ac71bc6350"}, + {file = "yarl-1.18.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:a173401d7821a2a81c7b47d4e7d5c4021375a1441af0c58611c1957445055056"}, + {file = "yarl-1.18.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:7520e799b1f84e095cce919bd6c23c9d49472deeef25fe1ef960b04cca51c3fc"}, + {file = "yarl-1.18.0-cp311-cp311-win32.whl", hash = "sha256:c4cb992d8090d5ae5f7afa6754d7211c578be0c45f54d3d94f7781c495d56716"}, + {file = "yarl-1.18.0-cp311-cp311-win_amd64.whl", hash = "sha256:52c136f348605974c9b1c878addd6b7a60e3bf2245833e370862009b86fa4689"}, + {file = "yarl-1.18.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1ece25e2251c28bab737bdf0519c88189b3dd9492dc086a1d77336d940c28ced"}, + {file = "yarl-1.18.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:454902dc1830d935c90b5b53c863ba2a98dcde0fbaa31ca2ed1ad33b2a7171c6"}, + {file = "yarl-1.18.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:01be8688fc211dc237e628fcc209dda412d35de7642453059a0553747018d075"}, + {file = "yarl-1.18.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4d26f1fa9fa2167bb238f6f4b20218eb4e88dd3ef21bb8f97439fa6b5313e30d"}, + {file = "yarl-1.18.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b234a4a9248a9f000b7a5dfe84b8cb6210ee5120ae70eb72a4dcbdb4c528f72f"}, + {file = "yarl-1.18.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fe94d1de77c4cd8caff1bd5480e22342dbd54c93929f5943495d9c1e8abe9f42"}, + {file = "yarl-1.18.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b4c90c5363c6b0a54188122b61edb919c2cd1119684999d08cd5e538813a28e"}, + {file = "yarl-1.18.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:49a98ecadc5a241c9ba06de08127ee4796e1009555efd791bac514207862b43d"}, + {file = "yarl-1.18.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:9106025c7f261f9f5144f9aa7681d43867eed06349a7cfb297a1bc804de2f0d1"}, + {file = "yarl-1.18.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:f275ede6199d0f1ed4ea5d55a7b7573ccd40d97aee7808559e1298fe6efc8dbd"}, + {file = "yarl-1.18.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f7edeb1dcc7f50a2c8e08b9dc13a413903b7817e72273f00878cb70e766bdb3b"}, + {file = "yarl-1.18.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c083f6dd6951b86e484ebfc9c3524b49bcaa9c420cb4b2a78ef9f7a512bfcc85"}, + {file = "yarl-1.18.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:80741ec5b471fbdfb997821b2842c59660a1c930ceb42f8a84ba8ca0f25a66aa"}, + {file = "yarl-1.18.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b1a3297b9cad594e1ff0c040d2881d7d3a74124a3c73e00c3c71526a1234a9f7"}, + {file = "yarl-1.18.0-cp312-cp312-win32.whl", hash = "sha256:cd6ab7d6776c186f544f893b45ee0c883542b35e8a493db74665d2e594d3ca75"}, + {file = "yarl-1.18.0-cp312-cp312-win_amd64.whl", hash = "sha256:039c299a0864d1f43c3e31570045635034ea7021db41bf4842693a72aca8df3a"}, + {file = "yarl-1.18.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:6fb64dd45453225f57d82c4764818d7a205ee31ce193e9f0086e493916bd4f72"}, + {file = "yarl-1.18.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:3adaaf9c6b1b4fc258584f4443f24d775a2086aee82d1387e48a8b4f3d6aecf6"}, + {file = "yarl-1.18.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:da206d1ec78438a563c5429ab808a2b23ad7bc025c8adbf08540dde202be37d5"}, + {file = "yarl-1.18.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:576d258b21c1db4c6449b1c572c75d03f16a482eb380be8003682bdbe7db2f28"}, + {file = "yarl-1.18.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c60e547c0a375c4bfcdd60eef82e7e0e8698bf84c239d715f5c1278a73050393"}, + {file = "yarl-1.18.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e3818eabaefb90adeb5e0f62f047310079d426387991106d4fbf3519eec7d90a"}, + {file = "yarl-1.18.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a5f72421246c21af6a92fbc8c13b6d4c5427dfd949049b937c3b731f2f9076bd"}, + {file = "yarl-1.18.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7fa7d37f2ada0f42e0723632993ed422f2a679af0e200874d9d861720a54f53e"}, + {file = "yarl-1.18.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:42ba84e2ac26a3f252715f8ec17e6fdc0cbf95b9617c5367579fafcd7fba50eb"}, + {file = "yarl-1.18.0-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:6a49ad0102c0f0ba839628d0bf45973c86ce7b590cdedf7540d5b1833ddc6f00"}, + {file = "yarl-1.18.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:96404e8d5e1bbe36bdaa84ef89dc36f0e75939e060ca5cd45451aba01db02902"}, + {file = "yarl-1.18.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:a0509475d714df8f6d498935b3f307cd122c4ca76f7d426c7e1bb791bcd87eda"}, + {file = "yarl-1.18.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:1ff116f0285b5c8b3b9a2680aeca29a858b3b9e0402fc79fd850b32c2bcb9f8b"}, + {file = "yarl-1.18.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e2580c1d7e66e6d29d6e11855e3b1c6381971e0edd9a5066e6c14d79bc8967af"}, + {file = "yarl-1.18.0-cp313-cp313-win32.whl", hash = "sha256:14408cc4d34e202caba7b5ac9cc84700e3421a9e2d1b157d744d101b061a4a88"}, + {file = "yarl-1.18.0-cp313-cp313-win_amd64.whl", hash = "sha256:1db1537e9cb846eb0ff206eac667f627794be8b71368c1ab3207ec7b6f8c5afc"}, + {file = "yarl-1.18.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:fa2c9cb607e0f660d48c54a63de7a9b36fef62f6b8bd50ff592ce1137e73ac7d"}, + {file = "yarl-1.18.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c0f4808644baf0a434a3442df5e0bedf8d05208f0719cedcd499e168b23bfdc4"}, + {file = "yarl-1.18.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:7db9584235895a1dffca17e1c634b13870852094f6389b68dcc6338086aa7b08"}, + {file = "yarl-1.18.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:309f8d27d6f93ceeeb80aa6980e883aa57895270f7f41842b92247e65d7aeddf"}, + {file = "yarl-1.18.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:609ffd44fed2ed88d9b4ef62ee860cf86446cf066333ad4ce4123505b819e581"}, + {file = "yarl-1.18.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f172b8b2c72a13a06ea49225a9c47079549036ad1b34afa12d5491b881f5b993"}, + {file = "yarl-1.18.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d89ae7de94631b60d468412c18290d358a9d805182373d804ec839978b120422"}, + {file = "yarl-1.18.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:466d31fd043ef9af822ee3f1df8fdff4e8c199a7f4012c2642006af240eade17"}, + {file = "yarl-1.18.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:7609b8462351c4836b3edce4201acb6dd46187b207c589b30a87ffd1813b48dc"}, + {file = "yarl-1.18.0-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:d9d4f5e471e8dc49b593a80766c2328257e405f943c56a3dc985c125732bc4cf"}, + {file = "yarl-1.18.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:67b336c15e564d76869c9a21316f90edf546809a5796a083b8f57c845056bc01"}, + {file = "yarl-1.18.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:b212452b80cae26cb767aa045b051740e464c5129b7bd739c58fbb7deb339e7b"}, + {file = "yarl-1.18.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:38b39b7b3e692b6c92b986b00137a3891eddb66311b229d1940dcbd4f025083c"}, + {file = "yarl-1.18.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a7ee6884a8848792d58b854946b685521f41d8871afa65e0d4a774954e9c9e89"}, + {file = "yarl-1.18.0-cp39-cp39-win32.whl", hash = "sha256:b4095c5019bb889aa866bf12ed4c85c0daea5aafcb7c20d1519f02a1e738f07f"}, + {file = "yarl-1.18.0-cp39-cp39-win_amd64.whl", hash = "sha256:2d90f2e4d16a5b0915ee065218b435d2ef619dd228973b1b47d262a6f7cd8fa5"}, + {file = "yarl-1.18.0-py3-none-any.whl", hash = "sha256:dbf53db46f7cf176ee01d8d98c39381440776fcda13779d269a8ba664f69bec0"}, + {file = "yarl-1.18.0.tar.gz", hash = "sha256:20d95535e7d833889982bfe7cc321b7f63bf8879788fee982c76ae2b24cfb715"}, ] [package.dependencies] diff --git a/libs/partners/fireworks/tests/integration_tests/test_standard.py b/libs/partners/fireworks/tests/integration_tests/test_standard.py index 692dcb40cf357..7a595e4c7da44 100644 --- a/libs/partners/fireworks/tests/integration_tests/test_standard.py +++ b/libs/partners/fireworks/tests/integration_tests/test_standard.py @@ -4,6 +4,7 @@ import pytest from langchain_core.language_models import BaseChatModel +from langchain_core.tools import BaseTool from langchain_tests.integration_tests import ( # type: ignore[import-not-found] ChatModelIntegrationTests, # type: ignore[import-not-found] ) @@ -24,5 +25,7 @@ def chat_model_params(self) -> dict: } @pytest.mark.xfail(reason="Not yet implemented.") - def test_tool_message_histories_list_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_list_content(model) + def test_tool_message_histories_list_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_list_content(model, my_adder_tool) diff --git a/libs/partners/groq/tests/integration_tests/test_standard.py b/libs/partners/groq/tests/integration_tests/test_standard.py index 3870ae953f6ee..b97b8c10422ef 100644 --- a/libs/partners/groq/tests/integration_tests/test_standard.py +++ b/libs/partners/groq/tests/integration_tests/test_standard.py @@ -5,6 +5,7 @@ import pytest from langchain_core.language_models import BaseChatModel from langchain_core.rate_limiters import InMemoryRateLimiter +from langchain_core.tools import BaseTool from langchain_tests.integration_tests import ( ChatModelIntegrationTests, ) @@ -20,8 +21,10 @@ def chat_model_class(self) -> Type[BaseChatModel]: return ChatGroq @pytest.mark.xfail(reason="Not yet implemented.") - def test_tool_message_histories_list_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_list_content(model) + def test_tool_message_histories_list_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_list_content(model, my_adder_tool) class TestGroqLlama(BaseTestGroq): @@ -47,8 +50,10 @@ def test_tool_calling_with_no_arguments(self, model: BaseChatModel) -> None: @pytest.mark.xfail( reason=("Fails with 'Failed to call a function. Please adjust your prompt.'") ) - def test_tool_message_histories_string_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_string_content(model) + def test_tool_message_histories_string_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_string_content(model, my_adder_tool) @pytest.mark.xfail( reason=( diff --git a/libs/partners/mistralai/langchain_mistralai/chat_models.py b/libs/partners/mistralai/langchain_mistralai/chat_models.py index 85924a714543c..be973f3b9ec78 100644 --- a/libs/partners/mistralai/langchain_mistralai/chat_models.py +++ b/libs/partners/mistralai/langchain_mistralai/chat_models.py @@ -353,7 +353,9 @@ def _convert_message_to_mistral_chat_message( "role": "tool", "content": message.content, "name": message.name, - "tool_call_id": message.tool_call_id, + "tool_call_id": _convert_tool_call_id_to_mistral_compatible( + message.tool_call_id + ), } else: raise ValueError(f"Got unknown type {message}") @@ -386,7 +388,7 @@ class ChatMistralAI(BaseChatModel): """Decode using nucleus sampling: consider the smallest set of tokens whose probability sum is at least top_p. Must be in the closed interval [0.0, 1.0].""" random_seed: Optional[int] = None - safe_mode: bool = False + safe_mode: Optional[bool] = None streaming: bool = False model_config = ConfigDict( @@ -593,7 +595,7 @@ def _stream( for chunk in self.completion_with_retry( messages=message_dicts, run_manager=run_manager, **params ): - if len(chunk["choices"]) == 0: + if len(chunk.get("choices", [])) == 0: continue new_chunk = _convert_chunk_to_message_chunk(chunk, default_chunk_class) # make future chunks same type as first chunk @@ -619,7 +621,7 @@ async def _astream( async for chunk in await acompletion_with_retry( self, messages=message_dicts, run_manager=run_manager, **params ): - if len(chunk["choices"]) == 0: + if len(chunk.get("choices", [])) == 0: continue new_chunk = _convert_chunk_to_message_chunk(chunk, default_chunk_class) # make future chunks same type as first chunk diff --git a/libs/partners/mistralai/poetry.lock b/libs/partners/mistralai/poetry.lock index a6fb4a2aaee16..152e34f833acb 100644 --- a/libs/partners/mistralai/poetry.lock +++ b/libs/partners/mistralai/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "annotated-types" @@ -325,13 +325,13 @@ files = [ [[package]] name = "huggingface-hub" -version = "0.26.2" +version = "0.26.3" description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub" optional = false python-versions = ">=3.8.0" files = [ - {file = "huggingface_hub-0.26.2-py3-none-any.whl", hash = "sha256:98c2a5a8e786c7b2cb6fdeb2740893cba4d53e312572ed3d8afafda65b128c46"}, - {file = "huggingface_hub-0.26.2.tar.gz", hash = "sha256:b100d853465d965733964d123939ba287da60a547087783ddff8a323f340332b"}, + {file = "huggingface_hub-0.26.3-py3-none-any.whl", hash = "sha256:e66aa99e569c2d5419240a9e553ad07245a5b1300350bfbc5a4945cf7432991b"}, + {file = "huggingface_hub-0.26.3.tar.gz", hash = "sha256:90e1fe62ffc26757a073aaad618422b899ccf9447c2bba8c902a90bef5b42e1d"}, ] [package.dependencies] @@ -409,7 +409,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -434,7 +434,7 @@ url = "../../core" [[package]] name = "langchain-tests" -version = "0.3.2" +version = "0.3.4" description = "Standard tests for LangChain implementations" optional = false python-versions = ">=3.9,<4.0" @@ -443,7 +443,7 @@ develop = true [package.dependencies] httpx = "^0.27.0" -langchain-core = "^0.3.15" +langchain-core = "^0.3.19" pytest = ">=7,<9" syrupy = "^4" @@ -453,18 +453,18 @@ url = "../../standard-tests" [[package]] name = "langsmith" -version = "0.1.143" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.143-py3-none-any.whl", hash = "sha256:ba0d827269e9b03a90fababe41fa3e4e3f833300b95add10184f7e67167dde6f"}, - {file = "langsmith-0.1.143.tar.gz", hash = "sha256:4c5159e5cd84b3f8499433009e72d2076dd2daf6c044ac8a3611b30d0d0161c5"}, + {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"}, + {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -472,6 +472,9 @@ pydantic = [ requests = ">=2,<3" requests-toolbelt = ">=1.0.0,<2.0.0" +[package.extras] +langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"] + [[package]] name = "mypy" version = "1.13.0" @@ -538,69 +541,86 @@ files = [ [[package]] name = "orjson" -version = "3.10.11" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.11-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6dade64687f2bd7c090281652fe18f1151292d567a9302b34c2dbb92a3872f1f"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82f07c550a6ccd2b9290849b22316a609023ed851a87ea888c0456485a7d196a"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd9a187742d3ead9df2e49240234d728c67c356516cf4db018833a86f20ec18c"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:77b0fed6f209d76c1c39f032a70df2d7acf24b1812ca3e6078fd04e8972685a3"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:63fc9d5fe1d4e8868f6aae547a7b8ba0a2e592929245fff61d633f4caccdcdd6"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65cd3e3bb4fbb4eddc3c1e8dce10dc0b73e808fcb875f9fab40c81903dd9323e"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6f67c570602300c4befbda12d153113b8974a3340fdcf3d6de095ede86c06d92"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:1f39728c7f7d766f1f5a769ce4d54b5aaa4c3f92d5b84817053cc9995b977acc"}, - {file = "orjson-3.10.11-cp310-none-win32.whl", hash = "sha256:1789d9db7968d805f3d94aae2c25d04014aae3a2fa65b1443117cd462c6da647"}, - {file = "orjson-3.10.11-cp310-none-win_amd64.whl", hash = "sha256:5576b1e5a53a5ba8f8df81872bb0878a112b3ebb1d392155f00f54dd86c83ff6"}, - {file = "orjson-3.10.11-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1444f9cb7c14055d595de1036f74ecd6ce15f04a715e73f33bb6326c9cef01b6"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdec57fe3b4bdebcc08a946db3365630332dbe575125ff3d80a3272ebd0ddafe"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4eed32f33a0ea6ef36ccc1d37f8d17f28a1d6e8eefae5928f76aff8f1df85e67"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:80df27dd8697242b904f4ea54820e2d98d3f51f91e97e358fc13359721233e4b"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:705f03cee0cb797256d54de6695ef219e5bc8c8120b6654dd460848d57a9af3d"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03246774131701de8e7059b2e382597da43144a9a7400f178b2a32feafc54bd5"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8b5759063a6c940a69c728ea70d7c33583991c6982915a839c8da5f957e0103a"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:677f23e32491520eebb19c99bb34675daf5410c449c13416f7f0d93e2cf5f981"}, - {file = "orjson-3.10.11-cp311-none-win32.whl", hash = "sha256:a11225d7b30468dcb099498296ffac36b4673a8398ca30fdaec1e6c20df6aa55"}, - {file = "orjson-3.10.11-cp311-none-win_amd64.whl", hash = "sha256:df8c677df2f9f385fcc85ab859704045fa88d4668bc9991a527c86e710392bec"}, - {file = "orjson-3.10.11-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:360a4e2c0943da7c21505e47cf6bd725588962ff1d739b99b14e2f7f3545ba51"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:496e2cb45de21c369079ef2d662670a4892c81573bcc143c4205cae98282ba97"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7dfa8db55c9792d53c5952900c6a919cfa377b4f4534c7a786484a6a4a350c19"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:51f3382415747e0dbda9dade6f1e1a01a9d37f630d8c9049a8ed0e385b7a90c0"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f35a1b9f50a219f470e0e497ca30b285c9f34948d3c8160d5ad3a755d9299433"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e2f3b7c5803138e67028dde33450e054c87e0703afbe730c105f1fcd873496d5"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f91d9eb554310472bd09f5347950b24442600594c2edc1421403d7610a0998fd"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dfbb2d460a855c9744bbc8e36f9c3a997c4b27d842f3d5559ed54326e6911f9b"}, - {file = "orjson-3.10.11-cp312-none-win32.whl", hash = "sha256:d4a62c49c506d4d73f59514986cadebb7e8d186ad510c518f439176cf8d5359d"}, - {file = "orjson-3.10.11-cp312-none-win_amd64.whl", hash = "sha256:f1eec3421a558ff7a9b010a6c7effcfa0ade65327a71bb9b02a1c3b77a247284"}, - {file = "orjson-3.10.11-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c46294faa4e4d0eb73ab68f1a794d2cbf7bab33b1dda2ac2959ffb7c61591899"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:52e5834d7d6e58a36846e059d00559cb9ed20410664f3ad156cd2cc239a11230"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2fc947e5350fdce548bfc94f434e8760d5cafa97fb9c495d2fef6757aa02ec0"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0efabbf839388a1dab5b72b5d3baedbd6039ac83f3b55736eb9934ea5494d258"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a3f29634260708c200c4fe148e42b4aae97d7b9fee417fbdd74f8cfc265f15b0"}, - {file = "orjson-3.10.11-cp313-none-win32.whl", hash = "sha256:1a1222ffcee8a09476bbdd5d4f6f33d06d0d6642df2a3d78b7a195ca880d669b"}, - {file = "orjson-3.10.11-cp313-none-win_amd64.whl", hash = "sha256:bc274ac261cc69260913b2d1610760e55d3c0801bb3457ba7b9004420b6b4270"}, - {file = "orjson-3.10.11-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:19b3763e8bbf8ad797df6b6b5e0fc7c843ec2e2fc0621398534e0c6400098f87"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1be83a13312e5e58d633580c5eb8d0495ae61f180da2722f20562974188af205"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:afacfd1ab81f46dedd7f6001b6d4e8de23396e4884cd3c3436bd05defb1a6446"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb4d0bea56bba596723d73f074c420aec3b2e5d7d30698bc56e6048066bd560c"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96ed1de70fcb15d5fed529a656df29f768187628727ee2788344e8a51e1c1350"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4bfb30c891b530f3f80e801e3ad82ef150b964e5c38e1fb8482441c69c35c61c"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:d496c74fc2b61341e3cefda7eec21b7854c5f672ee350bc55d9a4997a8a95204"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:655a493bac606655db9a47fe94d3d84fc7f3ad766d894197c94ccf0c5408e7d3"}, - {file = "orjson-3.10.11-cp38-none-win32.whl", hash = "sha256:b9546b278c9fb5d45380f4809e11b4dd9844ca7aaf1134024503e134ed226161"}, - {file = "orjson-3.10.11-cp38-none-win_amd64.whl", hash = "sha256:b592597fe551d518f42c5a2eb07422eb475aa8cfdc8c51e6da7054b836b26782"}, - {file = "orjson-3.10.11-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c95f2ecafe709b4e5c733b5e2768ac569bed308623c85806c395d9cca00e08af"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:80c00d4acded0c51c98754fe8218cb49cb854f0f7eb39ea4641b7f71732d2cb7"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:461311b693d3d0a060439aa669c74f3603264d4e7a08faa68c47ae5a863f352d"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52ca832f17d86a78cbab86cdc25f8c13756ebe182b6fc1a97d534051c18a08de"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c57ea78a753812f528178aa2f1c57da633754c91d2124cb28991dab4c79a54"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7fcfc6f7ca046383fb954ba528587e0f9336828b568282b27579c49f8e16aad"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:86b9dd983857970c29e4c71bb3e95ff085c07d3e83e7c46ebe959bac07ebd80b"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:4d83f87582d223e54efb2242a79547611ba4ebae3af8bae1e80fa9a0af83bb7f"}, - {file = "orjson-3.10.11-cp39-none-win32.whl", hash = "sha256:9fd0ad1c129bc9beb1154c2655f177620b5beaf9a11e0d10bac63ef3fce96950"}, - {file = "orjson-3.10.11-cp39-none-win_amd64.whl", hash = "sha256:10f416b2a017c8bd17f325fb9dee1fb5cdd7a54e814284896b7c3f2763faa017"}, - {file = "orjson-3.10.11.tar.gz", hash = "sha256:e35b6d730de6384d5b2dab5fd23f0d76fae8bbc8c353c2f78210aa5fa4beb3ef"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] @@ -631,18 +651,18 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "pydantic" -version = "2.10.0" +version = "2.10.2" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.10.0-py3-none-any.whl", hash = "sha256:5e7807ba9201bdf61b1b58aa6eb690916c40a47acfb114b1b4fef3e7fd5b30fc"}, - {file = "pydantic-2.10.0.tar.gz", hash = "sha256:0aca0f045ff6e2f097f1fe89521115335f15049eeb8a7bef3dafe4b19a74e289"}, + {file = "pydantic-2.10.2-py3-none-any.whl", hash = "sha256:cfb96e45951117c3024e6b67b25cdc33a3cb7b2fa62e239f7af1378358a1d99e"}, + {file = "pydantic-2.10.2.tar.gz", hash = "sha256:2bc2d7f17232e0841cbba4641e65ba1eb6fafb3a08de3a091ff3ce14a197c4fa"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.27.0" +pydantic-core = "2.27.1" typing-extensions = ">=4.12.2" [package.extras] @@ -651,111 +671,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.27.0" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.27.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:cd2ac6b919f7fed71b17fe0b4603c092a4c9b5bae414817c9c81d3c22d1e1bcc"}, - {file = "pydantic_core-2.27.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e015833384ca3e1a0565a79f5d953b0629d9138021c27ad37c92a9fa1af7623c"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:db72e40628967f6dc572020d04b5f800d71264e0531c6da35097e73bdf38b003"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:df45c4073bed486ea2f18757057953afed8dd77add7276ff01bccb79982cf46c"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:836a4bfe0cc6d36dc9a9cc1a7b391265bf6ce9d1eb1eac62ac5139f5d8d9a6fa"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4bf1340ae507f6da6360b24179c2083857c8ca7644aab65807023cf35404ea8d"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ab325fc86fbc077284c8d7f996d904d30e97904a87d6fb303dce6b3de7ebba9"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1da0c98a85a6c6ed702d5556db3b09c91f9b0b78de37b7593e2de8d03238807a"}, - {file = "pydantic_core-2.27.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:7b0202ebf2268954090209a84f9897345719e46a57c5f2c9b7b250ca0a9d3e63"}, - {file = "pydantic_core-2.27.0-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:35380671c3c921fe8adf31ad349dc6f7588b7e928dbe44e1093789734f607399"}, - {file = "pydantic_core-2.27.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6b4c19525c3538fbc0bbda6229f9682fb8199ce9ac37395880e6952798e00373"}, - {file = "pydantic_core-2.27.0-cp310-none-win32.whl", hash = "sha256:333c840a1303d1474f491e7be0b718226c730a39ead0f7dab2c7e6a2f3855555"}, - {file = "pydantic_core-2.27.0-cp310-none-win_amd64.whl", hash = "sha256:99b2863c1365f43f74199c980a3d40f18a218fbe683dd64e470199db426c4d6a"}, - {file = "pydantic_core-2.27.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4523c4009c3f39d948e01962223c9f5538602e7087a628479b723c939fab262d"}, - {file = "pydantic_core-2.27.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:84af1cf7bfdcbc6fcf5a5f70cc9896205e0350306e4dd73d54b6a18894f79386"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e65466b31be1070b4a5b7dbfbd14b247884cb8e8b79c64fb0f36b472912dbaea"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a5c022bb0d453192426221605efc865373dde43b17822a264671c53b068ac20c"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6bb69bf3b6500f195c3deb69c1205ba8fc3cb21d1915f1f158a10d6b1ef29b6a"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0aa4d1b2eba9a325897308b3124014a142cdccb9f3e016f31d3ebee6b5ea5e75"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8e96ca781e0c01e32115912ebdf7b3fb0780ce748b80d7d28a0802fa9fbaf44e"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b872c86d8d71827235c7077461c502feb2db3f87d9d6d5a9daa64287d75e4fa0"}, - {file = "pydantic_core-2.27.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:82e1ad4ca170e8af4c928b67cff731b6296e6a0a0981b97b2eb7c275cc4e15bd"}, - {file = "pydantic_core-2.27.0-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:eb40f828bc2f73f777d1eb8fee2e86cd9692a4518b63b6b5aa8af915dfd3207b"}, - {file = "pydantic_core-2.27.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:9a8fbf506fde1529a1e3698198fe64bfbe2e0c09557bc6a7dcf872e7c01fec40"}, - {file = "pydantic_core-2.27.0-cp311-none-win32.whl", hash = "sha256:24f984fc7762ed5f806d9e8c4c77ea69fdb2afd987b4fd319ef06c87595a8c55"}, - {file = "pydantic_core-2.27.0-cp311-none-win_amd64.whl", hash = "sha256:68950bc08f9735306322bfc16a18391fcaac99ded2509e1cc41d03ccb6013cfe"}, - {file = "pydantic_core-2.27.0-cp311-none-win_arm64.whl", hash = "sha256:3eb8849445c26b41c5a474061032c53e14fe92a11a5db969f722a2716cd12206"}, - {file = "pydantic_core-2.27.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:8117839a9bdbba86e7f9df57018fe3b96cec934c3940b591b0fd3fbfb485864a"}, - {file = "pydantic_core-2.27.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a291d0b4243a259c8ea7e2b84eb9ccb76370e569298875a7c5e3e71baf49057a"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:84e35afd9e10b2698e6f2f32256678cb23ca6c1568d02628033a837638b3ed12"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:58ab0d979c969983cdb97374698d847a4acffb217d543e172838864636ef10d9"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0d06b667e53320332be2bf6f9461f4a9b78092a079b8ce8634c9afaa7e10cd9f"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:78f841523729e43e3928a364ec46e2e3f80e6625a4f62aca5c345f3f626c6e8a"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:400bf470e4327e920883b51e255617dfe4496d4e80c3fea0b5a5d0bf2c404dd4"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:951e71da6c89d354572098bada5ba5b5dc3a9390c933af8a614e37755d3d1840"}, - {file = "pydantic_core-2.27.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:2a51ce96224eadd1845150b204389623c8e129fde5a67a84b972bd83a85c6c40"}, - {file = "pydantic_core-2.27.0-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:483c2213a609e7db2c592bbc015da58b6c75af7360ca3c981f178110d9787bcf"}, - {file = "pydantic_core-2.27.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:359e7951f04ad35111b5ddce184db3391442345d0ab073aa63a95eb8af25a5ef"}, - {file = "pydantic_core-2.27.0-cp312-none-win32.whl", hash = "sha256:ee7d9d5537daf6d5c74a83b38a638cc001b648096c1cae8ef695b0c919d9d379"}, - {file = "pydantic_core-2.27.0-cp312-none-win_amd64.whl", hash = "sha256:2be0ad541bb9f059954ccf8877a49ed73877f862529575ff3d54bf4223e4dd61"}, - {file = "pydantic_core-2.27.0-cp312-none-win_arm64.whl", hash = "sha256:6e19401742ed7b69e51d8e4df3c03ad5ec65a83b36244479fd70edde2828a5d9"}, - {file = "pydantic_core-2.27.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:5f2b19b8d6fca432cb3acf48cf5243a7bf512988029b6e6fd27e9e8c0a204d85"}, - {file = "pydantic_core-2.27.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:c86679f443e7085ea55a7376462553996c688395d18ef3f0d3dbad7838f857a2"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:510b11e9c3b1a852876d1ccd8d5903684336d635214148637ceb27366c75a467"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eb704155e73b833801c247f39d562229c0303f54770ca14fb1c053acb376cf10"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9ce048deb1e033e7a865ca384770bccc11d44179cf09e5193a535c4c2f497bdc"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:58560828ee0951bb125c6f2862fbc37f039996d19ceb6d8ff1905abf7da0bf3d"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:abb4785894936d7682635726613c44578c420a096729f1978cd061a7e72d5275"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2883b260f7a93235488699d39cbbd94fa7b175d3a8063fbfddd3e81ad9988cb2"}, - {file = "pydantic_core-2.27.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:c6fcb3fa3855d583aa57b94cf146f7781d5d5bc06cb95cb3afece33d31aac39b"}, - {file = "pydantic_core-2.27.0-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:e851a051f7260e6d688267eb039c81f05f23a19431bd7dfa4bf5e3cb34c108cd"}, - {file = "pydantic_core-2.27.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:edb1bfd45227dec8d50bc7c7d86463cd8728bcc574f9b07de7369880de4626a3"}, - {file = "pydantic_core-2.27.0-cp313-none-win32.whl", hash = "sha256:678f66462058dd978702db17eb6a3633d634f7aa0deaea61e0a674152766d3fc"}, - {file = "pydantic_core-2.27.0-cp313-none-win_amd64.whl", hash = "sha256:d28ca7066d6cdd347a50d8b725dc10d9a1d6a1cce09836cf071ea6a2d4908be0"}, - {file = "pydantic_core-2.27.0-cp313-none-win_arm64.whl", hash = "sha256:6f4a53af9e81d757756508b57cae1cf28293f0f31b9fa2bfcb416cc7fb230f9d"}, - {file = "pydantic_core-2.27.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:e9f9feee7f334b72ceae46313333d002b56f325b5f04271b4ae2aadd9e993ae4"}, - {file = "pydantic_core-2.27.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:225bfff5d425c34e1fd562cef52d673579d59b967d9de06178850c4802af9039"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c921ad596ff1a82f9c692b0758c944355abc9f0de97a4c13ca60ffc6d8dc15d4"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6354e18a9be37bfa124d6b288a87fb30c673745806c92956f1a25e3ae6e76b96"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8ee4c2a75af9fe21269a4a0898c5425afb01af1f5d276063f57e2ae1bc64e191"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c91e3c04f5191fd3fb68764bddeaf02025492d5d9f23343b283870f6ace69708"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7a6ebfac28fd51890a61df36ef202adbd77d00ee5aca4a3dadb3d9ed49cfb929"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:36aa167f69d8807ba7e341d67ea93e50fcaaf6bc433bb04939430fa3dab06f31"}, - {file = "pydantic_core-2.27.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:3e8d89c276234579cd3d095d5fa2a44eb10db9a218664a17b56363cddf226ff3"}, - {file = "pydantic_core-2.27.0-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:5cc822ab90a70ea3a91e6aed3afac570b276b1278c6909b1d384f745bd09c714"}, - {file = "pydantic_core-2.27.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:e15315691fe2253eb447503153acef4d7223dfe7e7702f9ed66539fcd0c43801"}, - {file = "pydantic_core-2.27.0-cp38-none-win32.whl", hash = "sha256:dfa5f5c0a4c8fced1422dc2ca7eefd872d5d13eb33cf324361dbf1dbfba0a9fe"}, - {file = "pydantic_core-2.27.0-cp38-none-win_amd64.whl", hash = "sha256:513cb14c0cc31a4dfd849a4674b20c46d87b364f997bbcb02282306f5e187abf"}, - {file = "pydantic_core-2.27.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:4148dc9184ab79e356dc00a4199dc0ee8647973332cb385fc29a7cced49b9f9c"}, - {file = "pydantic_core-2.27.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5fc72fbfebbf42c0856a824b8b0dc2b5cd2e4a896050281a21cfa6fed8879cb1"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:185ef205256cd8b38431205698531026979db89a79587725c1e55c59101d64e9"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:395e3e1148fa7809016231f8065f30bb0dc285a97b4dc4360cd86e17bab58af7"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:33d14369739c5d07e2e7102cdb0081a1fa46ed03215e07f097b34e020b83b1ae"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e7820bb0d65e3ce1e3e70b6708c2f66143f55912fa02f4b618d0f08b61575f12"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:43b61989068de9ce62296cde02beffabcadb65672207fc51e7af76dca75e6636"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:15e350efb67b855cd014c218716feea4986a149ed1f42a539edd271ee074a196"}, - {file = "pydantic_core-2.27.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:433689845288f9a1ee5714444e65957be26d30915f7745091ede4a83cfb2d7bb"}, - {file = "pydantic_core-2.27.0-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:3fd8bc2690e7c39eecdf9071b6a889ce7b22b72073863940edc2a0a23750ca90"}, - {file = "pydantic_core-2.27.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:884f1806609c2c66564082540cffc96868c5571c7c3cf3a783f63f2fb49bd3cd"}, - {file = "pydantic_core-2.27.0-cp39-none-win32.whl", hash = "sha256:bf37b72834e7239cf84d4a0b2c050e7f9e48bced97bad9bdf98d26b8eb72e846"}, - {file = "pydantic_core-2.27.0-cp39-none-win_amd64.whl", hash = "sha256:31a2cae5f059329f9cfe3d8d266d3da1543b60b60130d186d9b6a3c20a346361"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:4fb49cfdb53af5041aba909be00cccfb2c0d0a2e09281bf542371c5fd36ad04c"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:49633583eb7dc5cba61aaf7cdb2e9e662323ad394e543ee77af265736bcd3eaa"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:153017e3d6cd3ce979de06d84343ca424bb6092727375eba1968c8b4693c6ecb"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ff63a92f6e249514ef35bc795de10745be0226eaea06eb48b4bbeaa0c8850a4a"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5982048129f40b082c2654de10c0f37c67a14f5ff9d37cf35be028ae982f26df"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:91bc66f878557313c2a6bcf396e7befcffe5ab4354cfe4427318968af31143c3"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:68ef5377eb582fa4343c9d0b57a5b094046d447b4c73dd9fbd9ffb216f829e7d"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:c5726eec789ee38f2c53b10b1821457b82274f81f4f746bb1e666d8741fcfadb"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:c0c431e4be5c1a0c6654e0c31c661cd89e0ca956ef65305c3c3fd96f4e72ca39"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:8e21d927469d04b39386255bf00d0feedead16f6253dcc85e9e10ddebc334084"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:4b51f964fcbb02949fc546022e56cdb16cda457af485e9a3e8b78ac2ecf5d77e"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25a7fd4de38f7ff99a37e18fa0098c3140286451bc823d1746ba80cec5b433a1"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6fda87808429c520a002a85d6e7cdadbf58231d60e96260976c5b8f9a12a8e13"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8a150392102c402c538190730fda06f3bce654fc498865579a9f2c1d2b425833"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:c9ed88b398ba7e3bad7bd64d66cc01dcde9cfcb7ec629a6fd78a82fa0b559d78"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:9fe94d9d2a2b4edd7a4b22adcd45814b1b59b03feb00e56deb2e89747aec7bfe"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:d8b5ee4ae9170e2775d495b81f414cc20268041c42571530513496ba61e94ba3"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:d29e235ce13c91902ef3efc3d883a677655b3908b1cbc73dee816e5e1f8f7739"}, - {file = "pydantic_core-2.27.0.tar.gz", hash = "sha256:f57783fbaf648205ac50ae7d646f27582fc706be3977e87c3c124e7a92407b10"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -953,13 +973,13 @@ files = [ [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -982,123 +1002,26 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tokenizers" -version = "0.20.3" +version = "0.21.0" description = "" optional = false python-versions = ">=3.7" files = [ - {file = "tokenizers-0.20.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:31ccab28dbb1a9fe539787210b0026e22debeab1662970f61c2d921f7557f7e4"}, - {file = "tokenizers-0.20.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c6361191f762bda98c773da418cf511cbaa0cb8d0a1196f16f8c0119bde68ff8"}, - {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f128d5da1202b78fa0a10d8d938610472487da01b57098d48f7e944384362514"}, - {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:79c4121a2e9433ad7ef0769b9ca1f7dd7fa4c0cd501763d0a030afcbc6384481"}, - {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b7850fde24197fe5cd6556e2fdba53a6d3bae67c531ea33a3d7c420b90904141"}, - {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b357970c095dc134978a68c67d845a1e3803ab7c4fbb39195bde914e7e13cf8b"}, - {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a333d878c4970b72d6c07848b90c05f6b045cf9273fc2bc04a27211721ad6118"}, - {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1fd9fee817f655a8f50049f685e224828abfadd436b8ff67979fc1d054b435f1"}, - {file = "tokenizers-0.20.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9e7816808b402129393a435ea2a509679b41246175d6e5e9f25b8692bfaa272b"}, - {file = "tokenizers-0.20.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ba96367db9d8a730d3a1d5996b4b7babb846c3994b8ef14008cd8660f55db59d"}, - {file = "tokenizers-0.20.3-cp310-none-win32.whl", hash = "sha256:ee31ba9d7df6a98619426283e80c6359f167e2e9882d9ce1b0254937dbd32f3f"}, - {file = "tokenizers-0.20.3-cp310-none-win_amd64.whl", hash = "sha256:a845c08fdad554fe0871d1255df85772f91236e5fd6b9287ef8b64f5807dbd0c"}, - {file = "tokenizers-0.20.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:585b51e06ca1f4839ce7759941e66766d7b060dccfdc57c4ca1e5b9a33013a90"}, - {file = "tokenizers-0.20.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:61cbf11954f3b481d08723ebd048ba4b11e582986f9be74d2c3bdd9293a4538d"}, - {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ef820880d5e4e8484e2fa54ff8d297bb32519eaa7815694dc835ace9130a3eea"}, - {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:67ef4dcb8841a4988cd00dd288fb95dfc8e22ed021f01f37348fd51c2b055ba9"}, - {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff1ef8bd47a02b0dc191688ccb4da53600df5d4c9a05a4b68e1e3de4823e78eb"}, - {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:444d188186eab3148baf0615b522461b41b1f0cd58cd57b862ec94b6ac9780f1"}, - {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:37c04c032c1442740b2c2d925f1857885c07619224a533123ac7ea71ca5713da"}, - {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:453c7769d22231960ee0e883d1005c93c68015025a5e4ae56275406d94a3c907"}, - {file = "tokenizers-0.20.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4bb31f7b2847e439766aaa9cc7bccf7ac7088052deccdb2275c952d96f691c6a"}, - {file = "tokenizers-0.20.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:843729bf0f991b29655a069a2ff58a4c24375a553c70955e15e37a90dd4e045c"}, - {file = "tokenizers-0.20.3-cp311-none-win32.whl", hash = "sha256:efcce3a927b1e20ca694ba13f7a68c59b0bd859ef71e441db68ee42cf20c2442"}, - {file = "tokenizers-0.20.3-cp311-none-win_amd64.whl", hash = "sha256:88301aa0801f225725b6df5dea3d77c80365ff2362ca7e252583f2b4809c4cc0"}, - {file = "tokenizers-0.20.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:49d12a32e190fad0e79e5bdb788d05da2f20d8e006b13a70859ac47fecf6ab2f"}, - {file = "tokenizers-0.20.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:282848cacfb9c06d5e51489f38ec5aa0b3cd1e247a023061945f71f41d949d73"}, - {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:abe4e08c7d0cd6154c795deb5bf81d2122f36daf075e0c12a8b050d824ef0a64"}, - {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ca94fc1b73b3883c98f0c88c77700b13d55b49f1071dfd57df2b06f3ff7afd64"}, - {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ef279c7e239f95c8bdd6ff319d9870f30f0d24915b04895f55b1adcf96d6c60d"}, - {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:16384073973f6ccbde9852157a4fdfe632bb65208139c9d0c0bd0176a71fd67f"}, - {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:312d522caeb8a1a42ebdec87118d99b22667782b67898a76c963c058a7e41d4f"}, - {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2b7cb962564785a83dafbba0144ecb7f579f1d57d8c406cdaa7f32fe32f18ad"}, - {file = "tokenizers-0.20.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:124c5882ebb88dadae1fc788a582299fcd3a8bd84fc3e260b9918cf28b8751f5"}, - {file = "tokenizers-0.20.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:2b6e54e71f84c4202111a489879005cb14b92616a87417f6c102c833af961ea2"}, - {file = "tokenizers-0.20.3-cp312-none-win32.whl", hash = "sha256:83d9bfbe9af86f2d9df4833c22e94d94750f1d0cd9bfb22a7bb90a86f61cdb1c"}, - {file = "tokenizers-0.20.3-cp312-none-win_amd64.whl", hash = "sha256:44def74cee574d609a36e17c8914311d1b5dbcfe37c55fd29369d42591b91cf2"}, - {file = "tokenizers-0.20.3-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:e0b630e0b536ef0e3c8b42c685c1bc93bd19e98c0f1543db52911f8ede42cf84"}, - {file = "tokenizers-0.20.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a02d160d2b19bcbfdf28bd9a4bf11be4cb97d0499c000d95d4c4b1a4312740b6"}, - {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e3d80d89b068bc30034034b5319218c7c0a91b00af19679833f55f3becb6945"}, - {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:174a54910bed1b089226512b4458ea60d6d6fd93060254734d3bc3540953c51c"}, - {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:098b8a632b8656aa5802c46689462c5c48f02510f24029d71c208ec2c822e771"}, - {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:78c8c143e3ae41e718588281eb3e212c2b31623c9d6d40410ec464d7d6221fb5"}, - {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b26b0aadb18cd8701077362ba359a06683662d5cafe3e8e8aba10eb05c037f1"}, - {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:07d7851a72717321022f3774e84aa9d595a041d643fafa2e87fbc9b18711dac0"}, - {file = "tokenizers-0.20.3-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:bd44e48a430ada902c6266a8245f5036c4fe744fcb51f699999fbe82aa438797"}, - {file = "tokenizers-0.20.3-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:a4c186bb006ccbe1f5cc4e0380d1ce7806f5955c244074fd96abc55e27b77f01"}, - {file = "tokenizers-0.20.3-cp313-none-win32.whl", hash = "sha256:6e19e0f1d854d6ab7ea0c743d06e764d1d9a546932be0a67f33087645f00fe13"}, - {file = "tokenizers-0.20.3-cp313-none-win_amd64.whl", hash = "sha256:d50ede425c7e60966a9680d41b58b3a0950afa1bb570488e2972fa61662c4273"}, - {file = "tokenizers-0.20.3-cp37-cp37m-macosx_10_12_x86_64.whl", hash = "sha256:9adda1ff5fb9dcdf899ceca672a4e2ce9e797adb512a6467305ca3d8bfcfbdd0"}, - {file = "tokenizers-0.20.3-cp37-cp37m-macosx_11_0_arm64.whl", hash = "sha256:6dde2cae6004ba7a3badff4a11911cae03ebf23e97eebfc0e71fef2530e5074f"}, - {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c4a7fd678b35614fca708579eb95b7587a5e8a6d328171bd2488fd9f27d82be4"}, - {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1b80e3c7283a01a356bd2210f53d1a4a5d32b269c2024389ed0173137708d50e"}, - {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a8cc0e8176b762973758a77f0d9c4467d310e33165fb74173418ca3734944da4"}, - {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d5634b2e2f5f3d2b4439d2d74066e22eb4b1f04f3fea05cb2a3c12d89b5a3bcd"}, - {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b4ba635165bc1ea46f2da8e5d80b5f70f6ec42161e38d96dbef33bb39df73964"}, - {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:18e4c7c64172e7789bd8b07aa3087ea87c4c4de7e90937a2aa036b5d92332536"}, - {file = "tokenizers-0.20.3-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:1f74909ef7675c26d4095a817ec3393d67f3158ca4836c233212e5613ef640c4"}, - {file = "tokenizers-0.20.3-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:0e9b81321a1e05b16487d312b4264984513f8b4a7556229cafac6e88c2036b09"}, - {file = "tokenizers-0.20.3-cp37-none-win32.whl", hash = "sha256:ab48184cd58b4a03022a2ec75b54c9f600ffea9a733612c02325ed636f353729"}, - {file = "tokenizers-0.20.3-cp37-none-win_amd64.whl", hash = "sha256:60ac483cebee1c12c71878523e768df02fa17e4c54412966cb3ac862c91b36c1"}, - {file = "tokenizers-0.20.3-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:3229ef103c89583d10b9378afa5d601b91e6337530a0988e17ca8d635329a996"}, - {file = "tokenizers-0.20.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:6ac52cc24bad3de865c7e65b1c4e7b70d00938a8ae09a92a453b8f676e714ad5"}, - {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:04627b7b502fa6a2a005e1bd446fa4247d89abcb1afaa1b81eb90e21aba9a60f"}, - {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c27ceb887f0e81a3c377eb4605dca7a95a81262761c0fba308d627b2abb98f2b"}, - {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:65ab780194da4e1fcf5670523a2f377c4838ebf5249efe41fa1eddd2a84fb49d"}, - {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:98d343134f47159e81f7f242264b0eb222e6b802f37173c8d7d7b64d5c9d1388"}, - {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f2475bb004ab2009d29aff13b5047bfdb3d4b474f0aa9d4faa13a7f34dbbbb43"}, - {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7b6583a65c01db1197c1eb36857ceba8ec329d53afadd268b42a6b04f4965724"}, - {file = "tokenizers-0.20.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:62d00ba208358c037eeab7bfc00a905adc67b2d31b68ab40ed09d75881e114ea"}, - {file = "tokenizers-0.20.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:0fc7a39e5bedc817bda395a798dfe2d9c5f7c71153c90d381b5135a0328d9520"}, - {file = "tokenizers-0.20.3-cp38-none-win32.whl", hash = "sha256:84d40ee0f8550d64d3ea92dd7d24a8557a9172165bdb986c9fb2503b4fe4e3b6"}, - {file = "tokenizers-0.20.3-cp38-none-win_amd64.whl", hash = "sha256:205a45246ed7f1718cf3785cff88450ba603352412aaf220ace026384aa3f1c0"}, - {file = "tokenizers-0.20.3-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:93e37f0269a11dc3b1a953f1fca9707f0929ebf8b4063c591c71a0664219988e"}, - {file = "tokenizers-0.20.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f4cb0c614b0135e781de96c2af87e73da0389ac1458e2a97562ed26e29490d8d"}, - {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7eb2fb1c432f5746b22f8a7f09fc18c4156cb0031c77f53cb19379d82d43297a"}, - {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bfa8d029bb156181b006643309d6b673615a24e4ed24cf03aa191d599b996f51"}, - {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6f90549622de3bf476ad9f1dd6f3f952ec3ed6ab8615ae88ef060d0c5bfad55d"}, - {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a1d469c74eebf5c43fd61cd9b030e271d17198edd7bd45392e03a3c091d7d6d4"}, - {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bee8f53b2594749f4460d53253bae55d718f04e9b633efa0f5df8938bd98e4f0"}, - {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:938441babf3e5720e4459e306ef2809fb267680df9d1ff2873458b22aef60248"}, - {file = "tokenizers-0.20.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:7310ab23d7b0caebecc0e8be11a1146f320f5f07284000f6ea54793e83de1b75"}, - {file = "tokenizers-0.20.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:16121eb030a2b13094cfec936b0c12e8b4063c5f839591ea7d0212336d8f9921"}, - {file = "tokenizers-0.20.3-cp39-none-win32.whl", hash = "sha256:401cc21ef642ee235985d747f65e18f639464d377c70836c9003df208d582064"}, - {file = "tokenizers-0.20.3-cp39-none-win_amd64.whl", hash = "sha256:7498f3ea7746133335a6adb67a77cf77227a8b82c8483f644a2e5f86fea42b8d"}, - {file = "tokenizers-0.20.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:e919f2e3e68bb51dc31de4fcbbeff3bdf9c1cad489044c75e2b982a91059bd3c"}, - {file = "tokenizers-0.20.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:b8e9608f2773996cc272156e305bd79066163a66b0390fe21750aff62df1ac07"}, - {file = "tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:39270a7050deaf50f7caff4c532c01b3c48f6608d42b3eacdebdc6795478c8df"}, - {file = "tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e005466632b1c5d2d2120f6de8aa768cc9d36cd1ab7d51d0c27a114c91a1e6ee"}, - {file = "tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a07962340b36189b6c8feda552ea1bfeee6cf067ff922a1d7760662c2ee229e5"}, - {file = "tokenizers-0.20.3-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:55046ad3dd5f2b3c67501fcc8c9cbe3e901d8355f08a3b745e9b57894855f85b"}, - {file = "tokenizers-0.20.3-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:efcf0eb939988b627558aaf2b9dc3e56d759cad2e0cfa04fcab378e4b48fc4fd"}, - {file = "tokenizers-0.20.3-pp37-pypy37_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f3558a7ae6a6d38a77dfce12172a1e2e1bf3e8871e744a1861cd7591ea9ebe24"}, - {file = "tokenizers-0.20.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4d53029fe44bc70c3ff14ef512460a0cf583495a0f8e2f4b70e26eb9438e38a9"}, - {file = "tokenizers-0.20.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:57a2a56397b2bec5a629b516b23f0f8a3e4f978c7488d4a299980f8375954b85"}, - {file = "tokenizers-0.20.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b1e5bfaae740ef9ece000f8a07e78ac0e2b085c5ce9648f8593ddf0243c9f76d"}, - {file = "tokenizers-0.20.3-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:fbaf3ea28fedfb2283da60e710aff25492e795a7397cad8a50f1e079b65a5a70"}, - {file = "tokenizers-0.20.3-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:c47c037116310dc976eb96b008e41b9cfaba002ed8005848d4d632ee0b7ba9ae"}, - {file = "tokenizers-0.20.3-pp38-pypy38_pp73-macosx_10_12_x86_64.whl", hash = "sha256:c31751f0721f58f5e19bb27c1acc259aeff860d8629c4e1a900b26a1979ada8e"}, - {file = "tokenizers-0.20.3-pp38-pypy38_pp73-macosx_11_0_arm64.whl", hash = "sha256:c697cbd3be7a79ea250ea5f380d6f12e534c543cfb137d5c734966b3ee4f34cc"}, - {file = "tokenizers-0.20.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b48971b88ef9130bf35b41b35fd857c3c4dae4a9cd7990ebc7fc03e59cc92438"}, - {file = "tokenizers-0.20.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4e615de179bbe060ab33773f0d98a8a8572b5883dd7dac66c1de8c056c7e748c"}, - {file = "tokenizers-0.20.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da1ec842035ed9999c62e45fbe0ff14b7e8a7e02bb97688cc6313cf65e5cd755"}, - {file = "tokenizers-0.20.3-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:6ee4954c1dd23aadc27958dad759006e71659d497dcb0ef0c7c87ea992c16ebd"}, - {file = "tokenizers-0.20.3-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:3eda46ca402751ec82553a321bf35a617b76bbed7586e768c02ccacbdda94d6d"}, - {file = "tokenizers-0.20.3-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:de082392a85eb0055cc055c535bff2f0cc15d7a000bdc36fbf601a0f3cf8507a"}, - {file = "tokenizers-0.20.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:c3db46cc0647bfd88263afdb739b92017a02a87ee30945cb3e86c7e25c7c9917"}, - {file = "tokenizers-0.20.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a292392f24ab9abac5cfa8197e5a6208f2e43723420217e1ceba0b4ec77816ac"}, - {file = "tokenizers-0.20.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8dcd91f4e60f62b20d83a87a84fe062035a1e3ff49a8c2bbdeb2d441c8e311f4"}, - {file = "tokenizers-0.20.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:900991a2b8ee35961b1095db7e265342e0e42a84c1a594823d5ee9f8fb791958"}, - {file = "tokenizers-0.20.3-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:5a8d8261ca2133d4f98aa9627c748189502b3787537ba3d7e2beb4f7cfc5d627"}, - {file = "tokenizers-0.20.3-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:c4fd4d71e6deb6ddf99d8d0eab87d1d16f635898906e631914a9bae8ae9f2cfb"}, - {file = "tokenizers-0.20.3.tar.gz", hash = "sha256:2278b34c5d0dd78e087e1ca7f9b1dcbf129d80211afa645f214bd6e051037539"}, + {file = "tokenizers-0.21.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:3c4c93eae637e7d2aaae3d376f06085164e1660f89304c0ab2b1d08a406636b2"}, + {file = "tokenizers-0.21.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:f53ea537c925422a2e0e92a24cce96f6bc5046bbef24a1652a5edc8ba975f62e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b177fb54c4702ef611de0c069d9169f0004233890e0c4c5bd5508ae05abf193"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6b43779a269f4629bebb114e19c3fca0223296ae9fea8bb9a7a6c6fb0657ff8e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9aeb255802be90acfd363626753fda0064a8df06031012fe7d52fd9a905eb00e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d8b09dbeb7a8d73ee204a70f94fc06ea0f17dcf0844f16102b9f414f0b7463ba"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:400832c0904f77ce87c40f1a8a27493071282f785724ae62144324f171377273"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e84ca973b3a96894d1707e189c14a774b701596d579ffc7e69debfc036a61a04"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:eb7202d231b273c34ec67767378cd04c767e967fda12d4a9e36208a34e2f137e"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:089d56db6782a73a27fd8abf3ba21779f5b85d4a9f35e3b493c7bbcbbf0d539b"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:c87ca3dc48b9b1222d984b6b7490355a6fdb411a2d810f6f05977258400ddb74"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:4145505a973116f91bc3ac45988a92e618a6f83eb458f49ea0790df94ee243ff"}, + {file = "tokenizers-0.21.0-cp39-abi3-win32.whl", hash = "sha256:eb1702c2f27d25d9dd5b389cc1f2f51813e99f8ca30d9e25348db6585a97e24a"}, + {file = "tokenizers-0.21.0-cp39-abi3-win_amd64.whl", hash = "sha256:87841da5a25a3a5f70c102de371db120f41873b854ba65e52bccd57df5a3780c"}, + {file = "tokenizers-0.21.0.tar.gz", hash = "sha256:ee0894bf311b75b0c03079f33859ae4b2334d675d4e93f5a4132e1eae2834fe4"}, ] [package.dependencies] @@ -1111,31 +1034,61 @@ testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"] [[package]] name = "tomli" -version = "2.1.0" +version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, - {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"}, + {file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"}, + {file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"}, + {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"}, + {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"}, + {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"}, + {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"}, + {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"}, + {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"}, ] [[package]] name = "tqdm" -version = "4.67.0" +version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = false python-versions = ">=3.7" files = [ - {file = "tqdm-4.67.0-py3-none-any.whl", hash = "sha256:0cd8af9d56911acab92182e88d763100d4788bdf421d251616040cc4d44863be"}, - {file = "tqdm-4.67.0.tar.gz", hash = "sha256:fe5a6f95e6fe0b9755e9469b77b9c3cf850048224ecaa8293d7d2d31f97d869a"}, + {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, + {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, ] [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} [package.extras] -dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"] +dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"] discord = ["requests"] notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] @@ -1214,4 +1167,4 @@ watchmedo = ["PyYAML (>=3.10)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "4a86b5a8d678aa583d949272e47d16b9a1ecde22ce590d903bcb1a386dc4ecdf" +content-hash = "a89781c86a72349bba46de58ba88102bf2ae1f58a9b0fe79d952caecb656a585" diff --git a/libs/partners/mistralai/pyproject.toml b/libs/partners/mistralai/pyproject.toml index b2ae7a83bfd4a..8060a88fc69dd 100644 --- a/libs/partners/mistralai/pyproject.toml +++ b/libs/partners/mistralai/pyproject.toml @@ -1,10 +1,10 @@ [build-system] -requires = ["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-mistralai" -version = "0.2.2" +version = "0.2.3" description = "An integration package connecting Mistral and LangChain" authors = [] readme = "README.md" @@ -20,24 +20,21 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.15" +langchain-core = "^0.3.21" tokenizers = ">=0.15.1,<1" httpx = ">=0.25.2,<1" httpx-sse = ">=0.3.1,<1" pydantic = ">=2,<3" [tool.ruff.lint] -select = ["E", "F", "I", "T201"] +select = [ "E", "F", "I", "T201",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--strict-markers --strict-config --durations=5" -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" [tool.poetry.group.test] diff --git a/libs/partners/nomic/poetry.lock b/libs/partners/nomic/poetry.lock index 6e6ee05ccdc46..499f04c4df082 100644 --- a/libs/partners/nomic/poetry.lock +++ b/libs/partners/nomic/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. [[package]] name = "annotated-types" @@ -260,13 +260,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.6" +version = "1.0.7" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"}, - {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"}, + {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, + {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, ] [package.dependencies] @@ -370,7 +370,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.15" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -395,18 +395,18 @@ url = "../../core" [[package]] name = "langsmith" -version = "0.1.139" +version = "0.1.146" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, - {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, + {file = "langsmith-0.1.146-py3-none-any.whl", hash = "sha256:9d062222f1a32c9b047dab0149b24958f988989cd8d4a5f9139ff959a51e59d8"}, + {file = "langsmith-0.1.146.tar.gz", hash = "sha256:ead8b0b9d5b6cd3ac42937ec48bdf09d4afe7ca1bba22dc05eb65591a18106f8"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -530,12 +530,12 @@ files = [ [[package]] name = "nomic" -version = "3.3.0" +version = "3.3.3" description = "The official Nomic python client." optional = false python-versions = "*" files = [ - {file = "nomic-3.3.0.tar.gz", hash = "sha256:ef8916f1258db34fd8fb3db5512ae7a4af57bb2aedfee0eb7a2c2a9dde67721f"}, + {file = "nomic-3.3.3.tar.gz", hash = "sha256:6914081529c722840bcdec6e03e1cab86284f6e8aa00e8038823fc685506cfd9"}, ] [package.dependencies] @@ -605,80 +605,97 @@ files = [ [[package]] name = "orjson" -version = "3.10.10" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.10-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:b788a579b113acf1c57e0a68e558be71d5d09aa67f62ca1f68e01117e550a998"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:804b18e2b88022c8905bb79bd2cbe59c0cd014b9328f43da8d3b28441995cda4"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9972572a1d042ec9ee421b6da69f7cc823da5962237563fa548ab17f152f0b9b"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc6993ab1c2ae7dd0711161e303f1db69062955ac2668181bfdf2dd410e65258"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d78e4cacced5781b01d9bc0f0cd8b70b906a0e109825cb41c1b03f9c41e4ce86"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e6eb2598df518281ba0cbc30d24c5b06124ccf7e19169e883c14e0831217a0bc"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:23776265c5215ec532de6238a52707048401a568f0fa0d938008e92a147fe2c7"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8cc2a654c08755cef90b468ff17c102e2def0edd62898b2486767204a7f5cc9c"}, - {file = "orjson-3.10.10-cp310-none-win32.whl", hash = "sha256:081b3fc6a86d72efeb67c13d0ea7c030017bd95f9868b1e329a376edc456153b"}, - {file = "orjson-3.10.10-cp310-none-win_amd64.whl", hash = "sha256:ff38c5fb749347768a603be1fb8a31856458af839f31f064c5aa74aca5be9efe"}, - {file = "orjson-3.10.10-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:879e99486c0fbb256266c7c6a67ff84f46035e4f8749ac6317cc83dacd7f993a"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:019481fa9ea5ff13b5d5d95e6fd5ab25ded0810c80b150c2c7b1cc8660b662a7"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0dd57eff09894938b4c86d4b871a479260f9e156fa7f12f8cad4b39ea8028bb5"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dbde6d70cd95ab4d11ea8ac5e738e30764e510fc54d777336eec09bb93b8576c"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b2625cb37b8fb42e2147404e5ff7ef08712099197a9cd38895006d7053e69d6"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dbf3c20c6a7db69df58672a0d5815647ecf78c8e62a4d9bd284e8621c1fe5ccb"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:75c38f5647e02d423807d252ce4528bf6a95bd776af999cb1fb48867ed01d1f6"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:23458d31fa50ec18e0ec4b0b4343730928296b11111df5f547c75913714116b2"}, - {file = "orjson-3.10.10-cp311-none-win32.whl", hash = "sha256:2787cd9dedc591c989f3facd7e3e86508eafdc9536a26ec277699c0aa63c685b"}, - {file = "orjson-3.10.10-cp311-none-win_amd64.whl", hash = "sha256:6514449d2c202a75183f807bc755167713297c69f1db57a89a1ef4a0170ee269"}, - {file = "orjson-3.10.10-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:8564f48f3620861f5ef1e080ce7cd122ee89d7d6dacf25fcae675ff63b4d6e05"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5bf161a32b479034098c5b81f2608f09167ad2fa1c06abd4e527ea6bf4837a9"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:68b65c93617bcafa7f04b74ae8bc2cc214bd5cb45168a953256ff83015c6747d"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e8e28406f97fc2ea0c6150f4c1b6e8261453318930b334abc419214c82314f85"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e4d0d9fe174cc7a5bdce2e6c378bcdb4c49b2bf522a8f996aa586020e1b96cee"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b3be81c42f1242cbed03cbb3973501fcaa2675a0af638f8be494eaf37143d999"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:65f9886d3bae65be026219c0a5f32dbbe91a9e6272f56d092ab22561ad0ea33b"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:730ed5350147db7beb23ddaf072f490329e90a1d059711d364b49fe352ec987b"}, - {file = "orjson-3.10.10-cp312-none-win32.whl", hash = "sha256:a8f4bf5f1c85bea2170800020d53a8877812892697f9c2de73d576c9307a8a5f"}, - {file = "orjson-3.10.10-cp312-none-win_amd64.whl", hash = "sha256:384cd13579a1b4cd689d218e329f459eb9ddc504fa48c5a83ef4889db7fd7a4f"}, - {file = "orjson-3.10.10-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:44bffae68c291f94ff5a9b4149fe9d1bdd4cd0ff0fb575bcea8351d48db629a1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e27b4c6437315df3024f0835887127dac2a0a3ff643500ec27088d2588fa5ae1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca84df16d6b49325a4084fd8b2fe2229cb415e15c46c529f868c3387bb1339d"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c14ce70e8f39bd71f9f80423801b5d10bf93d1dceffdecd04df0f64d2c69bc01"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:24ac62336da9bda1bd93c0491eff0613003b48d3cb5d01470842e7b52a40d5b4"}, - {file = "orjson-3.10.10-cp313-none-win32.whl", hash = "sha256:eb0a42831372ec2b05acc9ee45af77bcaccbd91257345f93780a8e654efc75db"}, - {file = "orjson-3.10.10-cp313-none-win_amd64.whl", hash = "sha256:f0c4f37f8bf3f1075c6cc8dd8a9f843689a4b618628f8812d0a71e6968b95ffd"}, - {file = "orjson-3.10.10-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:829700cc18503efc0cf502d630f612884258020d98a317679cd2054af0259568"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e0ceb5e0e8c4f010ac787d29ae6299846935044686509e2f0f06ed441c1ca949"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0c25908eb86968613216f3db4d3003f1c45d78eb9046b71056ca327ff92bdbd4"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:218cb0bc03340144b6328a9ff78f0932e642199ac184dd74b01ad691f42f93ff"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e2277ec2cea3775640dc81ab5195bb5b2ada2fe0ea6eee4677474edc75ea6785"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:848ea3b55ab5ccc9d7bbd420d69432628b691fba3ca8ae3148c35156cbd282aa"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:e3e67b537ac0c835b25b5f7d40d83816abd2d3f4c0b0866ee981a045287a54f3"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:7948cfb909353fce2135dcdbe4521a5e7e1159484e0bb024c1722f272488f2b8"}, - {file = "orjson-3.10.10-cp38-none-win32.whl", hash = "sha256:78bee66a988f1a333dc0b6257503d63553b1957889c17b2c4ed72385cd1b96ae"}, - {file = "orjson-3.10.10-cp38-none-win_amd64.whl", hash = "sha256:f1d647ca8d62afeb774340a343c7fc023efacfd3a39f70c798991063f0c681dd"}, - {file = "orjson-3.10.10-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:5a059afddbaa6dd733b5a2d76a90dbc8af790b993b1b5cb97a1176ca713b5df8"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6f9b5c59f7e2a1a410f971c5ebc68f1995822837cd10905ee255f96074537ee6"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d5ef198bafdef4aa9d49a4165ba53ffdc0a9e1c7b6f76178572ab33118afea25"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:aaf29ce0bb5d3320824ec3d1508652421000ba466abd63bdd52c64bcce9eb1fa"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dddd5516bcc93e723d029c1633ae79c4417477b4f57dad9bfeeb6bc0315e654a"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a12f2003695b10817f0fa8b8fca982ed7f5761dcb0d93cff4f2f9f6709903fd7"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:672f9874a8a8fb9bb1b771331d31ba27f57702c8106cdbadad8bda5d10bc1019"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1dcbb0ca5fafb2b378b2c74419480ab2486326974826bbf6588f4dc62137570a"}, - {file = "orjson-3.10.10-cp39-none-win32.whl", hash = "sha256:d9bbd3a4b92256875cb058c3381b782649b9a3c68a4aa9a2fff020c2f9cfc1be"}, - {file = "orjson-3.10.10-cp39-none-win_amd64.whl", hash = "sha256:766f21487a53aee8524b97ca9582d5c6541b03ab6210fbaf10142ae2f3ced2aa"}, - {file = "orjson-3.10.10.tar.gz", hash = "sha256:37949383c4df7b4337ce82ee35b6d7471e55195efa7dcb45ab8226ceadb0fe3b"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] name = "packaging" -version = "24.1" +version = "24.2" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" files = [ - {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"}, - {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"}, + {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, + {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, ] [[package]] @@ -692,41 +709,30 @@ files = [ {file = "pandas-2.2.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:381175499d3802cde0eabbaf6324cce0c4f5d52ca6f8c377c29ad442f50f6348"}, {file = "pandas-2.2.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d9c45366def9a3dd85a6454c0e7908f2b3b8e9c138f5dc38fed7ce720d8453ed"}, {file = "pandas-2.2.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:86976a1c5b25ae3f8ccae3a5306e443569ee3c3faf444dfd0f41cda24667ad57"}, - {file = "pandas-2.2.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:b8661b0238a69d7aafe156b7fa86c44b881387509653fdf857bebc5e4008ad42"}, {file = "pandas-2.2.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:37e0aced3e8f539eccf2e099f65cdb9c8aa85109b0be6e93e2baff94264bdc6f"}, {file = "pandas-2.2.3-cp310-cp310-win_amd64.whl", hash = "sha256:56534ce0746a58afaf7942ba4863e0ef81c9c50d3f0ae93e9497d6a41a057645"}, {file = "pandas-2.2.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:66108071e1b935240e74525006034333f98bcdb87ea116de573a6a0dccb6c039"}, {file = "pandas-2.2.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7c2875855b0ff77b2a64a0365e24455d9990730d6431b9e0ee18ad8acee13dbd"}, - {file = "pandas-2.2.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cd8d0c3be0515c12fed0bdbae072551c8b54b7192c7b1fda0ba56059a0179698"}, {file = "pandas-2.2.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c124333816c3a9b03fbeef3a9f230ba9a737e9e5bb4060aa2107a86cc0a497fc"}, - {file = "pandas-2.2.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:63cc132e40a2e084cf01adf0775b15ac515ba905d7dcca47e9a251819c575ef3"}, {file = "pandas-2.2.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:29401dbfa9ad77319367d36940cd8a0b3a11aba16063e39632d98b0e931ddf32"}, {file = "pandas-2.2.3-cp311-cp311-win_amd64.whl", hash = "sha256:3fc6873a41186404dad67245896a6e440baacc92f5b716ccd1bc9ed2995ab2c5"}, {file = "pandas-2.2.3-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:b1d432e8d08679a40e2a6d8b2f9770a5c21793a6f9f47fdd52c5ce1948a5a8a9"}, {file = "pandas-2.2.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a5a1595fe639f5988ba6a8e5bc9649af3baf26df3998a0abe56c02609392e0a4"}, - {file = "pandas-2.2.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5de54125a92bb4d1c051c0659e6fcb75256bf799a732a87184e5ea503965bce3"}, {file = "pandas-2.2.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fffb8ae78d8af97f849404f21411c95062db1496aeb3e56f146f0355c9989319"}, - {file = "pandas-2.2.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6dfcb5ee8d4d50c06a51c2fffa6cff6272098ad6540aed1a76d15fb9318194d8"}, {file = "pandas-2.2.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:062309c1b9ea12a50e8ce661145c6aab431b1e99530d3cd60640e255778bd43a"}, {file = "pandas-2.2.3-cp312-cp312-win_amd64.whl", hash = "sha256:59ef3764d0fe818125a5097d2ae867ca3fa64df032331b7e0917cf5d7bf66b13"}, {file = "pandas-2.2.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f00d1345d84d8c86a63e476bb4955e46458b304b9575dcf71102b5c705320015"}, {file = "pandas-2.2.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3508d914817e153ad359d7e069d752cdd736a247c322d932eb89e6bc84217f28"}, - {file = "pandas-2.2.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:22a9d949bfc9a502d320aa04e5d02feab689d61da4e7764b62c30b991c42c5f0"}, {file = "pandas-2.2.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f3a255b2c19987fbbe62a9dfd6cff7ff2aa9ccab3fc75218fd4b7530f01efa24"}, - {file = "pandas-2.2.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:800250ecdadb6d9c78eae4990da62743b857b470883fa27f652db8bdde7f6659"}, {file = "pandas-2.2.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6374c452ff3ec675a8f46fd9ab25c4ad0ba590b71cf0656f8b6daa5202bca3fb"}, {file = "pandas-2.2.3-cp313-cp313-win_amd64.whl", hash = "sha256:61c5ad4043f791b61dd4752191d9f07f0ae412515d59ba8f005832a532f8736d"}, {file = "pandas-2.2.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:3b71f27954685ee685317063bf13c7709a7ba74fc996b84fc6821c59b0f06468"}, {file = "pandas-2.2.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:38cf8125c40dae9d5acc10fa66af8ea6fdf760b2714ee482ca691fc66e6fcb18"}, - {file = "pandas-2.2.3-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:ba96630bc17c875161df3818780af30e43be9b166ce51c9a18c1feae342906c2"}, {file = "pandas-2.2.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1db71525a1538b30142094edb9adc10be3f3e176748cd7acc2240c2f2e5aa3a4"}, - {file = "pandas-2.2.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:15c0e1e02e93116177d29ff83e8b1619c93ddc9c49083f237d4312337a61165d"}, {file = "pandas-2.2.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:ad5b65698ab28ed8d7f18790a0dc58005c7629f227be9ecc1072aa74c0c1d43a"}, {file = "pandas-2.2.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:bc6b93f9b966093cb0fd62ff1a7e4c09e6d546ad7c1de191767baffc57628f39"}, {file = "pandas-2.2.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5dbca4c1acd72e8eeef4753eeca07de9b1db4f398669d5994086f788a5d7cc30"}, - {file = "pandas-2.2.3-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:8cd6d7cc958a3910f934ea8dbdf17b2364827bb4dafc38ce6eef6bb3d65ff09c"}, {file = "pandas-2.2.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:99df71520d25fade9db7c1076ac94eb994f4d2673ef2aa2e86ee039b6746d20c"}, - {file = "pandas-2.2.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:31d0ced62d4ea3e231a9f228366919a5ea0b07440d9d4dac345376fd8e1477ea"}, {file = "pandas-2.2.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:7eee9e7cea6adf3e3d24e304ac6b8300646e2a5d1cd3a3c2abed9101b0846761"}, {file = "pandas-2.2.3-cp39-cp39-win_amd64.whl", hash = "sha256:4850ba03528b6dd51d6c5d273c46f183f39a9baf3f0143e566b89450965b105e"}, {file = "pandas-2.2.3.tar.gz", hash = "sha256:4f18ba62b61d7e192368b84517265a99b4d7ee8912f8708660fb4a366cc82667"}, @@ -881,53 +887,53 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "pyarrow" -version = "18.0.0" +version = "18.1.0" description = "Python library for Apache Arrow" optional = false python-versions = ">=3.9" files = [ - {file = "pyarrow-18.0.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:2333f93260674e185cfbf208d2da3007132572e56871f451ba1a556b45dae6e2"}, - {file = "pyarrow-18.0.0-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:4c381857754da44326f3a49b8b199f7f87a51c2faacd5114352fc78de30d3aba"}, - {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:603cd8ad4976568954598ef0a6d4ed3dfb78aff3d57fa8d6271f470f0ce7d34f"}, - {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58a62549a3e0bc9e03df32f350e10e1efb94ec6cf63e3920c3385b26663948ce"}, - {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:bc97316840a349485fbb137eb8d0f4d7057e1b2c1272b1a20eebbbe1848f5122"}, - {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:2e549a748fa8b8715e734919923f69318c953e077e9c02140ada13e59d043310"}, - {file = "pyarrow-18.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:606e9a3dcb0f52307c5040698ea962685fb1c852d72379ee9412be7de9c5f9e2"}, - {file = "pyarrow-18.0.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:d5795e37c0a33baa618c5e054cd61f586cf76850a251e2b21355e4085def6280"}, - {file = "pyarrow-18.0.0-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:5f0510608ccd6e7f02ca8596962afb8c6cc84c453e7be0da4d85f5f4f7b0328a"}, - {file = "pyarrow-18.0.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:616ea2826c03c16e87f517c46296621a7c51e30400f6d0a61be645f203aa2b93"}, - {file = "pyarrow-18.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a1824f5b029ddd289919f354bc285992cb4e32da518758c136271cf66046ef22"}, - {file = "pyarrow-18.0.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:6dd1b52d0d58dd8f685ced9971eb49f697d753aa7912f0a8f50833c7a7426319"}, - {file = "pyarrow-18.0.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:320ae9bd45ad7ecc12ec858b3e8e462578de060832b98fc4d671dee9f10d9954"}, - {file = "pyarrow-18.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:2c992716cffb1088414f2b478f7af0175fd0a76fea80841b1706baa8fb0ebaad"}, - {file = "pyarrow-18.0.0-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:e7ab04f272f98ebffd2a0661e4e126036f6936391ba2889ed2d44c5006237802"}, - {file = "pyarrow-18.0.0-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:03f40b65a43be159d2f97fd64dc998f769d0995a50c00f07aab58b0b3da87e1f"}, - {file = "pyarrow-18.0.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:be08af84808dff63a76860847c48ec0416928a7b3a17c2f49a072cac7c45efbd"}, - {file = "pyarrow-18.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8c70c1965cde991b711a98448ccda3486f2a336457cf4ec4dca257a926e149c9"}, - {file = "pyarrow-18.0.0-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:00178509f379415a3fcf855af020e3340254f990a8534294ec3cf674d6e255fd"}, - {file = "pyarrow-18.0.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:a71ab0589a63a3e987beb2bc172e05f000a5c5be2636b4b263c44034e215b5d7"}, - {file = "pyarrow-18.0.0-cp312-cp312-win_amd64.whl", hash = "sha256:fe92efcdbfa0bcf2fa602e466d7f2905500f33f09eb90bf0bcf2e6ca41b574c8"}, - {file = "pyarrow-18.0.0-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:907ee0aa8ca576f5e0cdc20b5aeb2ad4d3953a3b4769fc4b499e00ef0266f02f"}, - {file = "pyarrow-18.0.0-cp313-cp313-macosx_12_0_x86_64.whl", hash = "sha256:66dcc216ebae2eb4c37b223feaf82f15b69d502821dde2da138ec5a3716e7463"}, - {file = "pyarrow-18.0.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bc1daf7c425f58527900876354390ee41b0ae962a73ad0959b9d829def583bb1"}, - {file = "pyarrow-18.0.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:871b292d4b696b09120ed5bde894f79ee2a5f109cb84470546471df264cae136"}, - {file = "pyarrow-18.0.0-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:082ba62bdcb939824ba1ce10b8acef5ab621da1f4c4805e07bfd153617ac19d4"}, - {file = "pyarrow-18.0.0-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:2c664ab88b9766413197733c1720d3dcd4190e8fa3bbdc3710384630a0a7207b"}, - {file = "pyarrow-18.0.0-cp313-cp313-win_amd64.whl", hash = "sha256:dc892be34dbd058e8d189b47db1e33a227d965ea8805a235c8a7286f7fd17d3a"}, - {file = "pyarrow-18.0.0-cp313-cp313t-macosx_12_0_arm64.whl", hash = "sha256:28f9c39a56d2c78bf6b87dcc699d520ab850919d4a8c7418cd20eda49874a2ea"}, - {file = "pyarrow-18.0.0-cp313-cp313t-macosx_12_0_x86_64.whl", hash = "sha256:f1a198a50c409ab2d009fbf20956ace84567d67f2c5701511d4dd561fae6f32e"}, - {file = "pyarrow-18.0.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b5bd7fd32e3ace012d43925ea4fc8bd1b02cc6cc1e9813b518302950e89b5a22"}, - {file = "pyarrow-18.0.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:336addb8b6f5208be1b2398442c703a710b6b937b1a046065ee4db65e782ff5a"}, - {file = "pyarrow-18.0.0-cp313-cp313t-manylinux_2_28_aarch64.whl", hash = "sha256:45476490dd4adec5472c92b4d253e245258745d0ccaabe706f8d03288ed60a79"}, - {file = "pyarrow-18.0.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:b46591222c864e7da7faa3b19455196416cd8355ff6c2cc2e65726a760a3c420"}, - {file = "pyarrow-18.0.0-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:eb7e3abcda7e1e6b83c2dc2909c8d045881017270a119cc6ee7fdcfe71d02df8"}, - {file = "pyarrow-18.0.0-cp39-cp39-macosx_12_0_x86_64.whl", hash = "sha256:09f30690b99ce34e0da64d20dab372ee54431745e4efb78ac938234a282d15f9"}, - {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4d5ca5d707e158540312e09fd907f9f49bacbe779ab5236d9699ced14d2293b8"}, - {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d6331f280c6e4521c69b201a42dd978f60f7e129511a55da9e0bfe426b4ebb8d"}, - {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:3ac24b2be732e78a5a3ac0b3aa870d73766dd00beba6e015ea2ea7394f8b4e55"}, - {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:b30a927c6dff89ee702686596f27c25160dd6c99be5bcc1513a763ae5b1bfc03"}, - {file = "pyarrow-18.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:8f40ec677e942374e3d7f2fad6a67a4c2811a8b975e8703c6fd26d3b168a90e2"}, - {file = "pyarrow-18.0.0.tar.gz", hash = "sha256:a6aa027b1a9d2970cf328ccd6dbe4a996bc13c39fd427f502782f5bdb9ca20f5"}, + {file = "pyarrow-18.1.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:e21488d5cfd3d8b500b3238a6c4b075efabc18f0f6d80b29239737ebd69caa6c"}, + {file = "pyarrow-18.1.0-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:b516dad76f258a702f7ca0250885fc93d1fa5ac13ad51258e39d402bd9e2e1e4"}, + {file = "pyarrow-18.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4f443122c8e31f4c9199cb23dca29ab9427cef990f283f80fe15b8e124bcc49b"}, + {file = "pyarrow-18.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c0a03da7f2758645d17b7b4f83c8bffeae5bbb7f974523fe901f36288d2eab71"}, + {file = "pyarrow-18.1.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:ba17845efe3aa358ec266cf9cc2800fa73038211fb27968bfa88acd09261a470"}, + {file = "pyarrow-18.1.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:3c35813c11a059056a22a3bef520461310f2f7eea5c8a11ef9de7062a23f8d56"}, + {file = "pyarrow-18.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:9736ba3c85129d72aefa21b4f3bd715bc4190fe4426715abfff90481e7d00812"}, + {file = "pyarrow-18.1.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:eaeabf638408de2772ce3d7793b2668d4bb93807deed1725413b70e3156a7854"}, + {file = "pyarrow-18.1.0-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:3b2e2239339c538f3464308fd345113f886ad031ef8266c6f004d49769bb074c"}, + {file = "pyarrow-18.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f39a2e0ed32a0970e4e46c262753417a60c43a3246972cfc2d3eb85aedd01b21"}, + {file = "pyarrow-18.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e31e9417ba9c42627574bdbfeada7217ad8a4cbbe45b9d6bdd4b62abbca4c6f6"}, + {file = "pyarrow-18.1.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:01c034b576ce0eef554f7c3d8c341714954be9b3f5d5bc7117006b85fcf302fe"}, + {file = "pyarrow-18.1.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:f266a2c0fc31995a06ebd30bcfdb7f615d7278035ec5b1cd71c48d56daaf30b0"}, + {file = "pyarrow-18.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:d4f13eee18433f99adefaeb7e01d83b59f73360c231d4782d9ddfaf1c3fbde0a"}, + {file = "pyarrow-18.1.0-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:9f3a76670b263dc41d0ae877f09124ab96ce10e4e48f3e3e4257273cee61ad0d"}, + {file = "pyarrow-18.1.0-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:da31fbca07c435be88a0c321402c4e31a2ba61593ec7473630769de8346b54ee"}, + {file = "pyarrow-18.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:543ad8459bc438efc46d29a759e1079436290bd583141384c6f7a1068ed6f992"}, + {file = "pyarrow-18.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0743e503c55be0fdb5c08e7d44853da27f19dc854531c0570f9f394ec9671d54"}, + {file = "pyarrow-18.1.0-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:d4b3d2a34780645bed6414e22dda55a92e0fcd1b8a637fba86800ad737057e33"}, + {file = "pyarrow-18.1.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:c52f81aa6f6575058d8e2c782bf79d4f9fdc89887f16825ec3a66607a5dd8e30"}, + {file = "pyarrow-18.1.0-cp312-cp312-win_amd64.whl", hash = "sha256:0ad4892617e1a6c7a551cfc827e072a633eaff758fa09f21c4ee548c30bcaf99"}, + {file = "pyarrow-18.1.0-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:84e314d22231357d473eabec709d0ba285fa706a72377f9cc8e1cb3c8013813b"}, + {file = "pyarrow-18.1.0-cp313-cp313-macosx_12_0_x86_64.whl", hash = "sha256:f591704ac05dfd0477bb8f8e0bd4b5dc52c1cadf50503858dce3a15db6e46ff2"}, + {file = "pyarrow-18.1.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:acb7564204d3c40babf93a05624fc6a8ec1ab1def295c363afc40b0c9e66c191"}, + {file = "pyarrow-18.1.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:74de649d1d2ccb778f7c3afff6085bd5092aed4c23df9feeb45dd6b16f3811aa"}, + {file = "pyarrow-18.1.0-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:f96bd502cb11abb08efea6dab09c003305161cb6c9eafd432e35e76e7fa9b90c"}, + {file = "pyarrow-18.1.0-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:36ac22d7782554754a3b50201b607d553a8d71b78cdf03b33c1125be4b52397c"}, + {file = "pyarrow-18.1.0-cp313-cp313-win_amd64.whl", hash = "sha256:25dbacab8c5952df0ca6ca0af28f50d45bd31c1ff6fcf79e2d120b4a65ee7181"}, + {file = "pyarrow-18.1.0-cp313-cp313t-macosx_12_0_arm64.whl", hash = "sha256:6a276190309aba7bc9d5bd2933230458b3521a4317acfefe69a354f2fe59f2bc"}, + {file = "pyarrow-18.1.0-cp313-cp313t-macosx_12_0_x86_64.whl", hash = "sha256:ad514dbfcffe30124ce655d72771ae070f30bf850b48bc4d9d3b25993ee0e386"}, + {file = "pyarrow-18.1.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aebc13a11ed3032d8dd6e7171eb6e86d40d67a5639d96c35142bd568b9299324"}, + {file = "pyarrow-18.1.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d6cf5c05f3cee251d80e98726b5c7cc9f21bab9e9783673bac58e6dfab57ecc8"}, + {file = "pyarrow-18.1.0-cp313-cp313t-manylinux_2_28_aarch64.whl", hash = "sha256:11b676cd410cf162d3f6a70b43fb9e1e40affbc542a1e9ed3681895f2962d3d9"}, + {file = "pyarrow-18.1.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:b76130d835261b38f14fc41fdfb39ad8d672afb84c447126b84d5472244cfaba"}, + {file = "pyarrow-18.1.0-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:0b331e477e40f07238adc7ba7469c36b908f07c89b95dd4bd3a0ec84a3d1e21e"}, + {file = "pyarrow-18.1.0-cp39-cp39-macosx_12_0_x86_64.whl", hash = "sha256:2c4dd0c9010a25ba03e198fe743b1cc03cd33c08190afff371749c52ccbbaf76"}, + {file = "pyarrow-18.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4f97b31b4c4e21ff58c6f330235ff893cc81e23da081b1a4b1c982075e0ed4e9"}, + {file = "pyarrow-18.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a4813cb8ecf1809871fd2d64a8eff740a1bd3691bbe55f01a3cf6c5ec869754"}, + {file = "pyarrow-18.1.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:05a5636ec3eb5cc2a36c6edb534a38ef57b2ab127292a716d00eabb887835f1e"}, + {file = "pyarrow-18.1.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:73eeed32e724ea3568bb06161cad5fa7751e45bc2228e33dcb10c614044165c7"}, + {file = "pyarrow-18.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:a1880dd6772b685e803011a6b43a230c23b566859a6e0c9a276c1e0faf4f4052"}, + {file = "pyarrow-18.1.0.tar.gz", hash = "sha256:9386d3ca9c145b5539a1cfc75df07757dff870168c959b473a0bccbc3abc8c73"}, ] [package.extras] @@ -935,22 +941,19 @@ test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"] [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.2" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.2-py3-none-any.whl", hash = "sha256:cfb96e45951117c3024e6b67b25cdc33a3cb7b2fa62e239f7af1378358a1d99e"}, + {file = "pydantic-2.10.2.tar.gz", hash = "sha256:2bc2d7f17232e0841cbba4641e65ba1eb6fafb3a08de3a091ff3ce14a197c4fa"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -958,100 +961,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -1073,13 +1087,13 @@ windows-terminal = ["colorama (>=0.4.6)"] [[package]] name = "pyjwt" -version = "2.9.0" +version = "2.10.0" description = "JSON Web Token implementation in Python" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "PyJWT-2.9.0-py3-none-any.whl", hash = "sha256:3b02fb0f44517787776cf48f2ae25d8e14f300e6d7545a4315cee571a415e850"}, - {file = "pyjwt-2.9.0.tar.gz", hash = "sha256:7e1e5b56cc735432a7369cbfa0efe50fa113ebecdc04ae6922deba8b84582d0c"}, + {file = "PyJWT-2.10.0-py3-none-any.whl", hash = "sha256:543b77207db656de204372350926bed5a86201c4cbff159f623f79c7bb487a15"}, + {file = "pyjwt-2.10.0.tar.gz", hash = "sha256:7628a7eb7938959ac1b26e819a1df0fd3259505627b575e4bad6d08f76db695c"}, ] [package.extras] @@ -1351,13 +1365,13 @@ files = [ [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -1380,31 +1394,32 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tomli" -version = "2.0.2" +version = "2.1.0" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"}, - {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"}, + {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, + {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, ] [[package]] name = "tqdm" -version = "4.66.6" +version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = false python-versions = ">=3.7" files = [ - {file = "tqdm-4.66.6-py3-none-any.whl", hash = "sha256:223e8b5359c2efc4b30555531f09e9f2f3589bcd7fdd389271191031b49b7a63"}, - {file = "tqdm-4.66.6.tar.gz", hash = "sha256:4bdd694238bef1485ce839d67967ab50af8f9272aab687c0d7702a01da0be090"}, + {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, + {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, ] [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} [package.extras] -dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"] +dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"] +discord = ["requests"] notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] telegram = ["requests"] diff --git a/libs/partners/ollama/langchain_ollama/chat_models.py b/libs/partners/ollama/langchain_ollama/chat_models.py index d6ece0d66a854..4f074206c8f00 100644 --- a/libs/partners/ollama/langchain_ollama/chat_models.py +++ b/libs/partners/ollama/langchain_ollama/chat_models.py @@ -1,5 +1,6 @@ """Ollama chat models.""" +import json from typing import ( Any, AsyncIterator, @@ -21,6 +22,7 @@ CallbackManagerForLLMRun, ) from langchain_core.callbacks.manager import AsyncCallbackManagerForLLMRun +from langchain_core.exceptions import OutputParserException from langchain_core.language_models import LanguageModelInput from langchain_core.language_models.chat_models import BaseChatModel, LangSmithParams from langchain_core.messages import ( @@ -60,19 +62,85 @@ def _get_usage_metadata_from_generation_info( return None +def _parse_json_string( + json_string: str, raw_tool_call: dict[str, Any], skip: bool +) -> Any: + """Attempt to parse a JSON string for tool calling. + + Args: + json_string: JSON string to parse. + skip: Whether to ignore parsing errors and return the value anyways. + raw_tool_call: Raw tool call to include in error message. + + Returns: + The parsed JSON string. + + Raises: + OutputParserException: If the JSON string wrong invalid and skip=False. + """ + try: + return json.loads(json_string) + except json.JSONDecodeError as e: + if skip: + return json_string + msg = ( + f"Function {raw_tool_call['function']['name']} arguments:\n\n" + f"{raw_tool_call['function']['arguments']}\n\nare not valid JSON. " + f"Received JSONDecodeError {e}" + ) + raise OutputParserException(msg) from e + except TypeError as e: + if skip: + return json_string + msg = ( + f"Function {raw_tool_call['function']['name']} arguments:\n\n" + f"{raw_tool_call['function']['arguments']}\n\nare not a string or a " + f"dictionary. Received TypeError {e}" + ) + raise OutputParserException(msg) from e + + +def _parse_arguments_from_tool_call( + raw_tool_call: dict[str, Any], +) -> Optional[dict[str, Any]]: + """Parse arguments by trying to parse any shallowly nested string-encoded JSON. + + Band-aid fix for issue in Ollama with inconsistent tool call argument structure. + Should be removed/changed if fixed upstream. + See https://github.com/ollama/ollama/issues/6155 + """ + if "function" not in raw_tool_call: + return None + arguments = raw_tool_call["function"]["arguments"] + parsed_arguments = {} + if isinstance(arguments, dict): + for key, value in arguments.items(): + if isinstance(value, str): + parsed_arguments[key] = _parse_json_string( + value, skip=True, raw_tool_call=raw_tool_call + ) + else: + parsed_arguments[key] = value + else: + parsed_arguments = _parse_json_string( + arguments, skip=False, raw_tool_call=raw_tool_call + ) + return parsed_arguments + + def _get_tool_calls_from_response( response: Mapping[str, Any], ) -> List[ToolCall]: """Get tool calls from ollama response.""" tool_calls = [] if "message" in response: - if "tool_calls" in response["message"]: - for tc in response["message"]["tool_calls"]: + if raw_tool_calls := response["message"].get("tool_calls"): + for tc in raw_tool_calls: tool_calls.append( tool_call( id=str(uuid4()), name=tc["function"]["name"], - args=tc["function"]["arguments"], + args=_parse_arguments_from_tool_call(tc) or {}, ) ) return tool_calls @@ -331,23 +399,32 @@ class Multiply(BaseModel): For a full list of the params, see [this link](https://pydoc.dev/httpx/latest/httpx.Client.html) """ - _client: Client = PrivateAttr(default=None) + _client: Client = PrivateAttr(default=None) # type: ignore """ The client to use for making requests. """ - _async_client: AsyncClient = PrivateAttr(default=None) + _async_client: AsyncClient = PrivateAttr(default=None) # type: ignore """ The async client to use for making requests. """ - @property - def _default_params(self) -> Dict[str, Any]: - """Get the default parameters for calling Ollama.""" - return { - "model": self.model, - "format": self.format, - "options": { + def _chat_params( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + **kwargs: Any, + ) -> Dict[str, Any]: + ollama_messages = self._convert_messages_to_ollama_messages(messages) + + if self.stop is not None and stop is not None: + raise ValueError("`stop` found in both the input and default params.") + elif self.stop is not None: + stop = self.stop + + options_dict = kwargs.pop( + "options", + { "mirostat": self.mirostat, "mirostat_eta": self.mirostat_eta, "mirostat_tau": self.mirostat_tau, @@ -359,14 +436,31 @@ def _default_params(self) -> Dict[str, Any]: "repeat_penalty": self.repeat_penalty, "temperature": self.temperature, "seed": self.seed, - "stop": self.stop, + "stop": self.stop if stop is None else stop, "tfs_z": self.tfs_z, "top_k": self.top_k, "top_p": self.top_p, }, - "keep_alive": self.keep_alive, + ) + + tools = kwargs.get("tools") + default_stream = not bool(tools) + + params = { + "messages": ollama_messages, + "stream": kwargs.pop("stream", default_stream), + "model": kwargs.pop("model", self.model), + "format": kwargs.pop("format", self.format), + "options": Options(**options_dict), + "keep_alive": kwargs.pop("keep_alive", self.keep_alive), + **kwargs, } + if tools: + params["tools"] = tools + + return params + @model_validator(mode="after") def _set_clients(self) -> Self: """Set clients to use for ollama.""" @@ -464,34 +558,9 @@ async def _acreate_chat_stream( stop: Optional[List[str]] = None, **kwargs: Any, ) -> AsyncIterator[Union[Mapping[str, Any], str]]: - ollama_messages = self._convert_messages_to_ollama_messages(messages) - - stop = stop if stop is not None else self.stop + chat_params = self._chat_params(messages, stop, **kwargs) - params = self._default_params - - for key in self._default_params: - if key in kwargs: - params[key] = kwargs[key] - - params["options"]["stop"] = stop - - tools = kwargs.get("tools", None) - stream = tools is None or len(tools) == 0 - - chat_params = { - "model": params["model"], - "messages": ollama_messages, - "stream": stream, - "options": Options(**params["options"]), - "keep_alive": params["keep_alive"], - "format": params["format"], - } - - if tools is not None: - chat_params["tools"] = tools - - if stream: + if chat_params["stream"]: async for part in await self._async_client.chat(**chat_params): yield part else: @@ -503,34 +572,9 @@ def _create_chat_stream( stop: Optional[List[str]] = None, **kwargs: Any, ) -> Iterator[Union[Mapping[str, Any], str]]: - ollama_messages = self._convert_messages_to_ollama_messages(messages) - - stop = stop if stop is not None else self.stop - - params = self._default_params - - for key in self._default_params: - if key in kwargs: - params[key] = kwargs[key] - - params["options"]["stop"] = stop - - tools = kwargs.get("tools", None) - stream = tools is None or len(tools) == 0 - - chat_params = { - "model": params["model"], - "messages": ollama_messages, - "stream": stream, - "options": Options(**params["options"]), - "keep_alive": params["keep_alive"], - "format": params["format"], - } - - if tools is not None: - chat_params["tools"] = tools + chat_params = self._chat_params(messages, stop, **kwargs) - if stream: + if chat_params["stream"]: yield from self._client.chat(**chat_params) else: yield self._client.chat(**chat_params) @@ -752,6 +796,8 @@ def _llm_type(self) -> str: def bind_tools( self, tools: Sequence[Union[Dict[str, Any], Type, Callable, BaseTool]], + *, + tool_choice: Optional[Union[dict, str, Literal["auto", "any"], bool]] = None, **kwargs: Any, ) -> Runnable[LanguageModelInput, BaseMessage]: """Bind tool-like objects to this chat model. @@ -762,6 +808,8 @@ def bind_tools( tools: A list of tool definitions to bind to this chat model. Supports any tool definition handled by :meth:`langchain_core.utils.function_calling.convert_to_openai_tool`. + tool_choice: If provided, which tool for model to call. **This parameter + is currently ignored as it is not supported by Ollama.** kwargs: Any additional parameters are passed directly to ``self.bind(**kwargs)``. """ # noqa: E501 diff --git a/libs/partners/ollama/langchain_ollama/embeddings.py b/libs/partners/ollama/langchain_ollama/embeddings.py index 81dfd75b02f68..80783ec18b4d3 100644 --- a/libs/partners/ollama/langchain_ollama/embeddings.py +++ b/libs/partners/ollama/langchain_ollama/embeddings.py @@ -1,4 +1,5 @@ """Ollama embeddings models.""" + from typing import ( List, Optional, @@ -133,12 +134,12 @@ class OllamaEmbeddings(BaseModel, Embeddings): For a full list of the params, see [this link](https://pydoc.dev/httpx/latest/httpx.Client.html) """ - _client: Client = PrivateAttr(default=None) + _client: Client = PrivateAttr(default=None) # type: ignore """ The client to use for making requests. """ - _async_client: AsyncClient = PrivateAttr(default=None) + _async_client: AsyncClient = PrivateAttr(default=None) # type: ignore """ The async client to use for making requests. """ diff --git a/libs/partners/ollama/langchain_ollama/llms.py b/libs/partners/ollama/langchain_ollama/llms.py index 783d20104ef44..16b307041b58c 100644 --- a/libs/partners/ollama/langchain_ollama/llms.py +++ b/libs/partners/ollama/langchain_ollama/llms.py @@ -116,23 +116,30 @@ class OllamaLLM(BaseLLM): For a full list of the params, see [this link](https://pydoc.dev/httpx/latest/httpx.Client.html) """ - _client: Client = PrivateAttr(default=None) + _client: Client = PrivateAttr(default=None) # type: ignore """ The client to use for making requests. """ - _async_client: AsyncClient = PrivateAttr(default=None) + _async_client: AsyncClient = PrivateAttr(default=None) # type: ignore """ The async client to use for making requests. """ - @property - def _default_params(self) -> Dict[str, Any]: - """Get the default parameters for calling Ollama.""" - return { - "model": self.model, - "format": self.format, - "options": { + def _generate_params( + self, + prompt: str, + stop: Optional[List[str]] = None, + **kwargs: Any, + ) -> Dict[str, Any]: + if self.stop is not None and stop is not None: + raise ValueError("`stop` found in both the input and default params.") + elif self.stop is not None: + stop = self.stop + + options_dict = kwargs.pop( + "options", + { "mirostat": self.mirostat, "mirostat_eta": self.mirostat_eta, "mirostat_tau": self.mirostat_tau, @@ -143,14 +150,25 @@ def _default_params(self) -> Dict[str, Any]: "repeat_last_n": self.repeat_last_n, "repeat_penalty": self.repeat_penalty, "temperature": self.temperature, - "stop": self.stop, + "stop": self.stop if stop is None else stop, "tfs_z": self.tfs_z, "top_k": self.top_k, "top_p": self.top_p, }, - "keep_alive": self.keep_alive, + ) + + params = { + "prompt": prompt, + "stream": kwargs.pop("stream", True), + "model": kwargs.pop("model", self.model), + "format": kwargs.pop("format", self.format), + "options": Options(**options_dict), + "keep_alive": kwargs.pop("keep_alive", self.keep_alive), + **kwargs, } + return params + @property def _llm_type(self) -> str: """Return type of LLM.""" @@ -179,27 +197,10 @@ async def _acreate_generate_stream( stop: Optional[List[str]] = None, **kwargs: Any, ) -> AsyncIterator[Union[Mapping[str, Any], str]]: - if self.stop is not None and stop is not None: - raise ValueError("`stop` found in both the input and default params.") - elif self.stop is not None: - stop = self.stop - - params = self._default_params - - for key in self._default_params: - if key in kwargs: - params[key] = kwargs[key] - - params["options"]["stop"] = stop async for part in await self._async_client.generate( - model=params["model"], - prompt=prompt, - stream=True, - options=Options(**params["options"]), - keep_alive=params["keep_alive"], - format=params["format"], + **self._generate_params(prompt, stop=stop, **kwargs) ): # type: ignore - yield part + yield part # type: ignore def _create_generate_stream( self, @@ -207,26 +208,9 @@ def _create_generate_stream( stop: Optional[List[str]] = None, **kwargs: Any, ) -> Iterator[Union[Mapping[str, Any], str]]: - if self.stop is not None and stop is not None: - raise ValueError("`stop` found in both the input and default params.") - elif self.stop is not None: - stop = self.stop - - params = self._default_params - - for key in self._default_params: - if key in kwargs: - params[key] = kwargs[key] - - params["options"]["stop"] = stop yield from self._client.generate( - model=params["model"], - prompt=prompt, - stream=True, - options=Options(**params["options"]), - keep_alive=params["keep_alive"], - format=params["format"], - ) + **self._generate_params(prompt, stop=stop, **kwargs) + ) # type: ignore async def _astream_with_aggregation( self, diff --git a/libs/partners/ollama/poetry.lock b/libs/partners/ollama/poetry.lock index e07a4ff15f36c..47e6066ced28b 100644 --- a/libs/partners/ollama/poetry.lock +++ b/libs/partners/ollama/poetry.lock @@ -213,13 +213,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.6" +version = "1.0.7" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"}, - {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"}, + {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, + {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, ] [package.dependencies] @@ -309,7 +309,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -334,7 +334,7 @@ url = "../../core" [[package]] name = "langchain-tests" -version = "0.3.1" +version = "0.3.4" description = "Standard tests for LangChain implementations" optional = false python-versions = ">=3.9,<4.0" @@ -343,7 +343,7 @@ develop = true [package.dependencies] httpx = "^0.27.0" -langchain-core = "^0.3.15" +langchain-core = "^0.3.19" pytest = ">=7,<9" syrupy = "^4" @@ -353,18 +353,18 @@ url = "../../standard-tests" [[package]] name = "langsmith" -version = "0.1.138" +version = "0.1.144" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.138-py3-none-any.whl", hash = "sha256:5c2bd5c11c75f7b3d06a0f06b115186e7326ca969fd26d66ffc65a0669012aee"}, - {file = "langsmith-0.1.138.tar.gz", hash = "sha256:1ecf613bb52f6bf17f1510e24ad8b70d4b0259bc9d3dbfd69b648c66d4644f0b"}, + {file = "langsmith-0.1.144-py3-none-any.whl", hash = "sha256:08ffb975bff2e82fc6f5428837c64c074ea25102d08a25e256361a80812c6100"}, + {file = "langsmith-0.1.144.tar.gz", hash = "sha256:b621f358d5a33441d7b5e7264c376bf4ea82bfc62d7e41aafc0f8094e3bd6369"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -438,94 +438,95 @@ files = [ [[package]] name = "ollama" -version = "0.3.3" +version = "0.4.1" description = "The official Python client for Ollama." optional = false python-versions = "<4.0,>=3.8" files = [ - {file = "ollama-0.3.3-py3-none-any.whl", hash = "sha256:ca6242ce78ab34758082b7392df3f9f6c2cb1d070a9dede1a4c545c929e16dba"}, - {file = "ollama-0.3.3.tar.gz", hash = "sha256:f90a6d61803117f40b0e8ff17465cab5e1eb24758a473cfe8101aff38bc13b51"}, + {file = "ollama-0.4.1-py3-none-any.whl", hash = "sha256:b6fb16aa5a3652633e1716acb12cf2f44aa18beb229329e46a0302734822dfad"}, + {file = "ollama-0.4.1.tar.gz", hash = "sha256:8c6b5e7ff80dd0b8692150b03359f60bac7ca162b088c604069409142a684ad3"}, ] [package.dependencies] httpx = ">=0.27.0,<0.28.0" +pydantic = ">=2.9.0,<3.0.0" [[package]] name = "orjson" -version = "3.10.10" +version = "3.10.11" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.10-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:b788a579b113acf1c57e0a68e558be71d5d09aa67f62ca1f68e01117e550a998"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:804b18e2b88022c8905bb79bd2cbe59c0cd014b9328f43da8d3b28441995cda4"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9972572a1d042ec9ee421b6da69f7cc823da5962237563fa548ab17f152f0b9b"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc6993ab1c2ae7dd0711161e303f1db69062955ac2668181bfdf2dd410e65258"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d78e4cacced5781b01d9bc0f0cd8b70b906a0e109825cb41c1b03f9c41e4ce86"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e6eb2598df518281ba0cbc30d24c5b06124ccf7e19169e883c14e0831217a0bc"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:23776265c5215ec532de6238a52707048401a568f0fa0d938008e92a147fe2c7"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8cc2a654c08755cef90b468ff17c102e2def0edd62898b2486767204a7f5cc9c"}, - {file = "orjson-3.10.10-cp310-none-win32.whl", hash = "sha256:081b3fc6a86d72efeb67c13d0ea7c030017bd95f9868b1e329a376edc456153b"}, - {file = "orjson-3.10.10-cp310-none-win_amd64.whl", hash = "sha256:ff38c5fb749347768a603be1fb8a31856458af839f31f064c5aa74aca5be9efe"}, - {file = "orjson-3.10.10-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:879e99486c0fbb256266c7c6a67ff84f46035e4f8749ac6317cc83dacd7f993a"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:019481fa9ea5ff13b5d5d95e6fd5ab25ded0810c80b150c2c7b1cc8660b662a7"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0dd57eff09894938b4c86d4b871a479260f9e156fa7f12f8cad4b39ea8028bb5"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dbde6d70cd95ab4d11ea8ac5e738e30764e510fc54d777336eec09bb93b8576c"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b2625cb37b8fb42e2147404e5ff7ef08712099197a9cd38895006d7053e69d6"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dbf3c20c6a7db69df58672a0d5815647ecf78c8e62a4d9bd284e8621c1fe5ccb"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:75c38f5647e02d423807d252ce4528bf6a95bd776af999cb1fb48867ed01d1f6"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:23458d31fa50ec18e0ec4b0b4343730928296b11111df5f547c75913714116b2"}, - {file = "orjson-3.10.10-cp311-none-win32.whl", hash = "sha256:2787cd9dedc591c989f3facd7e3e86508eafdc9536a26ec277699c0aa63c685b"}, - {file = "orjson-3.10.10-cp311-none-win_amd64.whl", hash = "sha256:6514449d2c202a75183f807bc755167713297c69f1db57a89a1ef4a0170ee269"}, - {file = "orjson-3.10.10-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:8564f48f3620861f5ef1e080ce7cd122ee89d7d6dacf25fcae675ff63b4d6e05"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5bf161a32b479034098c5b81f2608f09167ad2fa1c06abd4e527ea6bf4837a9"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:68b65c93617bcafa7f04b74ae8bc2cc214bd5cb45168a953256ff83015c6747d"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e8e28406f97fc2ea0c6150f4c1b6e8261453318930b334abc419214c82314f85"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e4d0d9fe174cc7a5bdce2e6c378bcdb4c49b2bf522a8f996aa586020e1b96cee"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b3be81c42f1242cbed03cbb3973501fcaa2675a0af638f8be494eaf37143d999"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:65f9886d3bae65be026219c0a5f32dbbe91a9e6272f56d092ab22561ad0ea33b"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:730ed5350147db7beb23ddaf072f490329e90a1d059711d364b49fe352ec987b"}, - {file = "orjson-3.10.10-cp312-none-win32.whl", hash = "sha256:a8f4bf5f1c85bea2170800020d53a8877812892697f9c2de73d576c9307a8a5f"}, - {file = "orjson-3.10.10-cp312-none-win_amd64.whl", hash = "sha256:384cd13579a1b4cd689d218e329f459eb9ddc504fa48c5a83ef4889db7fd7a4f"}, - {file = "orjson-3.10.10-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:44bffae68c291f94ff5a9b4149fe9d1bdd4cd0ff0fb575bcea8351d48db629a1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e27b4c6437315df3024f0835887127dac2a0a3ff643500ec27088d2588fa5ae1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca84df16d6b49325a4084fd8b2fe2229cb415e15c46c529f868c3387bb1339d"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c14ce70e8f39bd71f9f80423801b5d10bf93d1dceffdecd04df0f64d2c69bc01"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:24ac62336da9bda1bd93c0491eff0613003b48d3cb5d01470842e7b52a40d5b4"}, - {file = "orjson-3.10.10-cp313-none-win32.whl", hash = "sha256:eb0a42831372ec2b05acc9ee45af77bcaccbd91257345f93780a8e654efc75db"}, - {file = "orjson-3.10.10-cp313-none-win_amd64.whl", hash = "sha256:f0c4f37f8bf3f1075c6cc8dd8a9f843689a4b618628f8812d0a71e6968b95ffd"}, - {file = "orjson-3.10.10-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:829700cc18503efc0cf502d630f612884258020d98a317679cd2054af0259568"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e0ceb5e0e8c4f010ac787d29ae6299846935044686509e2f0f06ed441c1ca949"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0c25908eb86968613216f3db4d3003f1c45d78eb9046b71056ca327ff92bdbd4"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:218cb0bc03340144b6328a9ff78f0932e642199ac184dd74b01ad691f42f93ff"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e2277ec2cea3775640dc81ab5195bb5b2ada2fe0ea6eee4677474edc75ea6785"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:848ea3b55ab5ccc9d7bbd420d69432628b691fba3ca8ae3148c35156cbd282aa"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:e3e67b537ac0c835b25b5f7d40d83816abd2d3f4c0b0866ee981a045287a54f3"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:7948cfb909353fce2135dcdbe4521a5e7e1159484e0bb024c1722f272488f2b8"}, - {file = "orjson-3.10.10-cp38-none-win32.whl", hash = "sha256:78bee66a988f1a333dc0b6257503d63553b1957889c17b2c4ed72385cd1b96ae"}, - {file = "orjson-3.10.10-cp38-none-win_amd64.whl", hash = "sha256:f1d647ca8d62afeb774340a343c7fc023efacfd3a39f70c798991063f0c681dd"}, - {file = "orjson-3.10.10-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:5a059afddbaa6dd733b5a2d76a90dbc8af790b993b1b5cb97a1176ca713b5df8"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6f9b5c59f7e2a1a410f971c5ebc68f1995822837cd10905ee255f96074537ee6"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d5ef198bafdef4aa9d49a4165ba53ffdc0a9e1c7b6f76178572ab33118afea25"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:aaf29ce0bb5d3320824ec3d1508652421000ba466abd63bdd52c64bcce9eb1fa"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dddd5516bcc93e723d029c1633ae79c4417477b4f57dad9bfeeb6bc0315e654a"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a12f2003695b10817f0fa8b8fca982ed7f5761dcb0d93cff4f2f9f6709903fd7"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:672f9874a8a8fb9bb1b771331d31ba27f57702c8106cdbadad8bda5d10bc1019"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1dcbb0ca5fafb2b378b2c74419480ab2486326974826bbf6588f4dc62137570a"}, - {file = "orjson-3.10.10-cp39-none-win32.whl", hash = "sha256:d9bbd3a4b92256875cb058c3381b782649b9a3c68a4aa9a2fff020c2f9cfc1be"}, - {file = "orjson-3.10.10-cp39-none-win_amd64.whl", hash = "sha256:766f21487a53aee8524b97ca9582d5c6541b03ab6210fbaf10142ae2f3ced2aa"}, - {file = "orjson-3.10.10.tar.gz", hash = "sha256:37949383c4df7b4337ce82ee35b6d7471e55195efa7dcb45ab8226ceadb0fe3b"}, + {file = "orjson-3.10.11-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6dade64687f2bd7c090281652fe18f1151292d567a9302b34c2dbb92a3872f1f"}, + {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82f07c550a6ccd2b9290849b22316a609023ed851a87ea888c0456485a7d196a"}, + {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd9a187742d3ead9df2e49240234d728c67c356516cf4db018833a86f20ec18c"}, + {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:77b0fed6f209d76c1c39f032a70df2d7acf24b1812ca3e6078fd04e8972685a3"}, + {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:63fc9d5fe1d4e8868f6aae547a7b8ba0a2e592929245fff61d633f4caccdcdd6"}, + {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65cd3e3bb4fbb4eddc3c1e8dce10dc0b73e808fcb875f9fab40c81903dd9323e"}, + {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6f67c570602300c4befbda12d153113b8974a3340fdcf3d6de095ede86c06d92"}, + {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:1f39728c7f7d766f1f5a769ce4d54b5aaa4c3f92d5b84817053cc9995b977acc"}, + {file = "orjson-3.10.11-cp310-none-win32.whl", hash = "sha256:1789d9db7968d805f3d94aae2c25d04014aae3a2fa65b1443117cd462c6da647"}, + {file = "orjson-3.10.11-cp310-none-win_amd64.whl", hash = "sha256:5576b1e5a53a5ba8f8df81872bb0878a112b3ebb1d392155f00f54dd86c83ff6"}, + {file = "orjson-3.10.11-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1444f9cb7c14055d595de1036f74ecd6ce15f04a715e73f33bb6326c9cef01b6"}, + {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdec57fe3b4bdebcc08a946db3365630332dbe575125ff3d80a3272ebd0ddafe"}, + {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4eed32f33a0ea6ef36ccc1d37f8d17f28a1d6e8eefae5928f76aff8f1df85e67"}, + {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:80df27dd8697242b904f4ea54820e2d98d3f51f91e97e358fc13359721233e4b"}, + {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:705f03cee0cb797256d54de6695ef219e5bc8c8120b6654dd460848d57a9af3d"}, + {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03246774131701de8e7059b2e382597da43144a9a7400f178b2a32feafc54bd5"}, + {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8b5759063a6c940a69c728ea70d7c33583991c6982915a839c8da5f957e0103a"}, + {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:677f23e32491520eebb19c99bb34675daf5410c449c13416f7f0d93e2cf5f981"}, + {file = "orjson-3.10.11-cp311-none-win32.whl", hash = "sha256:a11225d7b30468dcb099498296ffac36b4673a8398ca30fdaec1e6c20df6aa55"}, + {file = "orjson-3.10.11-cp311-none-win_amd64.whl", hash = "sha256:df8c677df2f9f385fcc85ab859704045fa88d4668bc9991a527c86e710392bec"}, + {file = "orjson-3.10.11-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:360a4e2c0943da7c21505e47cf6bd725588962ff1d739b99b14e2f7f3545ba51"}, + {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:496e2cb45de21c369079ef2d662670a4892c81573bcc143c4205cae98282ba97"}, + {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7dfa8db55c9792d53c5952900c6a919cfa377b4f4534c7a786484a6a4a350c19"}, + {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:51f3382415747e0dbda9dade6f1e1a01a9d37f630d8c9049a8ed0e385b7a90c0"}, + {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f35a1b9f50a219f470e0e497ca30b285c9f34948d3c8160d5ad3a755d9299433"}, + {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e2f3b7c5803138e67028dde33450e054c87e0703afbe730c105f1fcd873496d5"}, + {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f91d9eb554310472bd09f5347950b24442600594c2edc1421403d7610a0998fd"}, + {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dfbb2d460a855c9744bbc8e36f9c3a997c4b27d842f3d5559ed54326e6911f9b"}, + {file = "orjson-3.10.11-cp312-none-win32.whl", hash = "sha256:d4a62c49c506d4d73f59514986cadebb7e8d186ad510c518f439176cf8d5359d"}, + {file = "orjson-3.10.11-cp312-none-win_amd64.whl", hash = "sha256:f1eec3421a558ff7a9b010a6c7effcfa0ade65327a71bb9b02a1c3b77a247284"}, + {file = "orjson-3.10.11-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c46294faa4e4d0eb73ab68f1a794d2cbf7bab33b1dda2ac2959ffb7c61591899"}, + {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:52e5834d7d6e58a36846e059d00559cb9ed20410664f3ad156cd2cc239a11230"}, + {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2fc947e5350fdce548bfc94f434e8760d5cafa97fb9c495d2fef6757aa02ec0"}, + {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0efabbf839388a1dab5b72b5d3baedbd6039ac83f3b55736eb9934ea5494d258"}, + {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a3f29634260708c200c4fe148e42b4aae97d7b9fee417fbdd74f8cfc265f15b0"}, + {file = "orjson-3.10.11-cp313-none-win32.whl", hash = "sha256:1a1222ffcee8a09476bbdd5d4f6f33d06d0d6642df2a3d78b7a195ca880d669b"}, + {file = "orjson-3.10.11-cp313-none-win_amd64.whl", hash = "sha256:bc274ac261cc69260913b2d1610760e55d3c0801bb3457ba7b9004420b6b4270"}, + {file = "orjson-3.10.11-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:19b3763e8bbf8ad797df6b6b5e0fc7c843ec2e2fc0621398534e0c6400098f87"}, + {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1be83a13312e5e58d633580c5eb8d0495ae61f180da2722f20562974188af205"}, + {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:afacfd1ab81f46dedd7f6001b6d4e8de23396e4884cd3c3436bd05defb1a6446"}, + {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb4d0bea56bba596723d73f074c420aec3b2e5d7d30698bc56e6048066bd560c"}, + {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96ed1de70fcb15d5fed529a656df29f768187628727ee2788344e8a51e1c1350"}, + {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4bfb30c891b530f3f80e801e3ad82ef150b964e5c38e1fb8482441c69c35c61c"}, + {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:d496c74fc2b61341e3cefda7eec21b7854c5f672ee350bc55d9a4997a8a95204"}, + {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:655a493bac606655db9a47fe94d3d84fc7f3ad766d894197c94ccf0c5408e7d3"}, + {file = "orjson-3.10.11-cp38-none-win32.whl", hash = "sha256:b9546b278c9fb5d45380f4809e11b4dd9844ca7aaf1134024503e134ed226161"}, + {file = "orjson-3.10.11-cp38-none-win_amd64.whl", hash = "sha256:b592597fe551d518f42c5a2eb07422eb475aa8cfdc8c51e6da7054b836b26782"}, + {file = "orjson-3.10.11-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c95f2ecafe709b4e5c733b5e2768ac569bed308623c85806c395d9cca00e08af"}, + {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:80c00d4acded0c51c98754fe8218cb49cb854f0f7eb39ea4641b7f71732d2cb7"}, + {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:461311b693d3d0a060439aa669c74f3603264d4e7a08faa68c47ae5a863f352d"}, + {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52ca832f17d86a78cbab86cdc25f8c13756ebe182b6fc1a97d534051c18a08de"}, + {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c57ea78a753812f528178aa2f1c57da633754c91d2124cb28991dab4c79a54"}, + {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7fcfc6f7ca046383fb954ba528587e0f9336828b568282b27579c49f8e16aad"}, + {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:86b9dd983857970c29e4c71bb3e95ff085c07d3e83e7c46ebe959bac07ebd80b"}, + {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:4d83f87582d223e54efb2242a79547611ba4ebae3af8bae1e80fa9a0af83bb7f"}, + {file = "orjson-3.10.11-cp39-none-win32.whl", hash = "sha256:9fd0ad1c129bc9beb1154c2655f177620b5beaf9a11e0d10bac63ef3fce96950"}, + {file = "orjson-3.10.11-cp39-none-win_amd64.whl", hash = "sha256:10f416b2a017c8bd17f325fb9dee1fb5cdd7a54e814284896b7c3f2763faa017"}, + {file = "orjson-3.10.11.tar.gz", hash = "sha256:e35b6d730de6384d5b2dab5fd23f0d76fae8bbc8c353c2f78210aa5fa4beb3ef"}, ] [[package]] name = "packaging" -version = "24.1" +version = "24.2" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" files = [ - {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"}, - {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"}, + {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, + {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, ] [[package]] @@ -545,22 +546,19 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.1" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.1-py3-none-any.whl", hash = "sha256:a8d20db84de64cf4a7d59e899c2caf0fe9d660c7cfc482528e7020d7dd189a7e"}, + {file = "pydantic-2.10.1.tar.gz", hash = "sha256:a4daca2dc0aa429555e0656d6bf94873a7dc5f54ee42b1f5873d666fb3f35560"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -568,100 +566,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -901,13 +910,13 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tomli" -version = "2.0.2" +version = "2.1.0" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"}, - {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"}, + {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, + {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, ] [[package]] @@ -940,41 +949,41 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "watchdog" -version = "5.0.3" +version = "6.0.0" description = "Filesystem events monitoring" optional = false python-versions = ">=3.9" files = [ - {file = "watchdog-5.0.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:85527b882f3facda0579bce9d743ff7f10c3e1e0db0a0d0e28170a7d0e5ce2ea"}, - {file = "watchdog-5.0.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:53adf73dcdc0ef04f7735066b4a57a4cd3e49ef135daae41d77395f0b5b692cb"}, - {file = "watchdog-5.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e25adddab85f674acac303cf1f5835951345a56c5f7f582987d266679979c75b"}, - {file = "watchdog-5.0.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:f01f4a3565a387080dc49bdd1fefe4ecc77f894991b88ef927edbfa45eb10818"}, - {file = "watchdog-5.0.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:91b522adc25614cdeaf91f7897800b82c13b4b8ac68a42ca959f992f6990c490"}, - {file = "watchdog-5.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d52db5beb5e476e6853da2e2d24dbbbed6797b449c8bf7ea118a4ee0d2c9040e"}, - {file = "watchdog-5.0.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:94d11b07c64f63f49876e0ab8042ae034674c8653bfcdaa8c4b32e71cfff87e8"}, - {file = "watchdog-5.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:349c9488e1d85d0a58e8cb14222d2c51cbc801ce11ac3936ab4c3af986536926"}, - {file = "watchdog-5.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:53a3f10b62c2d569e260f96e8d966463dec1a50fa4f1b22aec69e3f91025060e"}, - {file = "watchdog-5.0.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:950f531ec6e03696a2414b6308f5c6ff9dab7821a768c9d5788b1314e9a46ca7"}, - {file = "watchdog-5.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ae6deb336cba5d71476caa029ceb6e88047fc1dc74b62b7c4012639c0b563906"}, - {file = "watchdog-5.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1021223c08ba8d2d38d71ec1704496471ffd7be42cfb26b87cd5059323a389a1"}, - {file = "watchdog-5.0.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:752fb40efc7cc8d88ebc332b8f4bcbe2b5cc7e881bccfeb8e25054c00c994ee3"}, - {file = "watchdog-5.0.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a2e8f3f955d68471fa37b0e3add18500790d129cc7efe89971b8a4cc6fdeb0b2"}, - {file = "watchdog-5.0.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b8ca4d854adcf480bdfd80f46fdd6fb49f91dd020ae11c89b3a79e19454ec627"}, - {file = "watchdog-5.0.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:90a67d7857adb1d985aca232cc9905dd5bc4803ed85cfcdcfcf707e52049eda7"}, - {file = "watchdog-5.0.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:720ef9d3a4f9ca575a780af283c8fd3a0674b307651c1976714745090da5a9e8"}, - {file = "watchdog-5.0.3-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:223160bb359281bb8e31c8f1068bf71a6b16a8ad3d9524ca6f523ac666bb6a1e"}, - {file = "watchdog-5.0.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:560135542c91eaa74247a2e8430cf83c4342b29e8ad4f520ae14f0c8a19cfb5b"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_aarch64.whl", hash = "sha256:dd021efa85970bd4824acacbb922066159d0f9e546389a4743d56919b6758b91"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_armv7l.whl", hash = "sha256:78864cc8f23dbee55be34cc1494632a7ba30263951b5b2e8fc8286b95845f82c"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_i686.whl", hash = "sha256:1e9679245e3ea6498494b3028b90c7b25dbb2abe65c7d07423ecfc2d6218ff7c"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_ppc64.whl", hash = "sha256:9413384f26b5d050b6978e6fcd0c1e7f0539be7a4f1a885061473c5deaa57221"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:294b7a598974b8e2c6123d19ef15de9abcd282b0fbbdbc4d23dfa812959a9e05"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_s390x.whl", hash = "sha256:26dd201857d702bdf9d78c273cafcab5871dd29343748524695cecffa44a8d97"}, - {file = "watchdog-5.0.3-py3-none-manylinux2014_x86_64.whl", hash = "sha256:0f9332243355643d567697c3e3fa07330a1d1abf981611654a1f2bf2175612b7"}, - {file = "watchdog-5.0.3-py3-none-win32.whl", hash = "sha256:c66f80ee5b602a9c7ab66e3c9f36026590a0902db3aea414d59a2f55188c1f49"}, - {file = "watchdog-5.0.3-py3-none-win_amd64.whl", hash = "sha256:f00b4cf737f568be9665563347a910f8bdc76f88c2970121c86243c8cfdf90e9"}, - {file = "watchdog-5.0.3-py3-none-win_ia64.whl", hash = "sha256:49f4d36cb315c25ea0d946e018c01bb028048023b9e103d3d3943f58e109dd45"}, - {file = "watchdog-5.0.3.tar.gz", hash = "sha256:108f42a7f0345042a854d4d0ad0834b741d421330d5f575b81cb27b883500176"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d1cdb490583ebd691c012b3d6dae011000fe42edb7a82ece80965b42abd61f26"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bc64ab3bdb6a04d69d4023b29422170b74681784ffb9463ed4870cf2f3e66112"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c897ac1b55c5a1461e16dae288d22bb2e412ba9807df8397a635d88f671d36c3"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6eb11feb5a0d452ee41f824e271ca311a09e250441c262ca2fd7ebcf2461a06c"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ef810fbf7b781a5a593894e4f439773830bdecb885e6880d957d5b9382a960d2"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:afd0fe1b2270917c5e23c2a65ce50c2a4abb63daafb0d419fde368e272a76b7c"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:bdd4e6f14b8b18c334febb9c4425a878a2ac20efd1e0b231978e7b150f92a948"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:c7c15dda13c4eb00d6fb6fc508b3c0ed88b9d5d374056b239c4ad1611125c860"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6f10cb2d5902447c7d0da897e2c6768bca89174d0c6e1e30abec5421af97a5b0"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:490ab2ef84f11129844c23fb14ecf30ef3d8a6abafd3754a6f75ca1e6654136c"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:76aae96b00ae814b181bb25b1b98076d5fc84e8a53cd8885a318b42b6d3a5134"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a175f755fc2279e0b7312c0035d52e27211a5bc39719dd529625b1930917345b"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:e6f0e77c9417e7cd62af82529b10563db3423625c5fce018430b249bf977f9e8"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:90c8e78f3b94014f7aaae121e6b909674df5b46ec24d6bebc45c44c56729af2a"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:e7631a77ffb1f7d2eefa4445ebbee491c720a5661ddf6df3498ebecae5ed375c"}, + {file = "watchdog-6.0.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:c7ac31a19f4545dd92fc25d200694098f42c9a8e391bc00bdd362c5736dbf881"}, + {file = "watchdog-6.0.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:9513f27a1a582d9808cf21a07dae516f0fab1cf2d7683a742c498b93eedabb11"}, + {file = "watchdog-6.0.0-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:7a0e56874cfbc4b9b05c60c8a1926fedf56324bb08cfbc188969777940aef3aa"}, + {file = "watchdog-6.0.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:e6439e374fc012255b4ec786ae3c4bc838cd7309a540e5fe0952d03687d8804e"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7607498efa04a3542ae3e05e64da8202e58159aa1fa4acddf7678d34a35d4f13"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_armv7l.whl", hash = "sha256:9041567ee8953024c83343288ccc458fd0a2d811d6a0fd68c4c22609e3490379"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_i686.whl", hash = "sha256:82dc3e3143c7e38ec49d61af98d6558288c415eac98486a5c581726e0737c00e"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_ppc64.whl", hash = "sha256:212ac9b8bf1161dc91bd09c048048a95ca3a4c4f5e5d4a7d1b1a7d5752a7f96f"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:e3df4cbb9a450c6d49318f6d14f4bbc80d763fa587ba46ec86f99f9e6876bb26"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_s390x.whl", hash = "sha256:2cce7cfc2008eb51feb6aab51251fd79b85d9894e98ba847408f662b3395ca3c"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:20ffe5b202af80ab4266dcd3e91aae72bf2da48c0d33bdb15c66658e685e94e2"}, + {file = "watchdog-6.0.0-py3-none-win32.whl", hash = "sha256:07df1fdd701c5d4c8e55ef6cf55b8f0120fe1aef7ef39a1c6fc6bc2e606d517a"}, + {file = "watchdog-6.0.0-py3-none-win_amd64.whl", hash = "sha256:cbafb470cf848d93b5d013e2ecb245d4aa1c8fd0504e863ccefa32445359d680"}, + {file = "watchdog-6.0.0-py3-none-win_ia64.whl", hash = "sha256:a1914259fa9e1454315171103c6a30961236f508b9b623eae470268bbcc6a22f"}, + {file = "watchdog-6.0.0.tar.gz", hash = "sha256:9ddf7c82fda3ae8e24decda1338ede66e1c99883db93711d8fb941eaa2d8c282"}, ] [package.extras] @@ -983,4 +992,4 @@ watchmedo = ["PyYAML (>=3.10)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "a5c369fbd4c7e6fea27200bec1537de641ac19b5ede12eaefec73d3461a440c7" +content-hash = "078fb5da0212681a4fc4d02e4e4112fe7a3ebda0923411e72ad706a097a989ae" diff --git a/libs/partners/ollama/pyproject.toml b/libs/partners/ollama/pyproject.toml index 9ec652e57d3ea..bab24cf619887 100644 --- a/libs/partners/ollama/pyproject.toml +++ b/libs/partners/ollama/pyproject.toml @@ -21,7 +21,7 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" ollama = ">=0.3.0,<1" -langchain-core = "^0.3.15" +langchain-core = "^0.3.20" [tool.ruff.lint] select = [ diff --git a/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models.py b/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models.py new file mode 100644 index 0000000000000..837df8c5164eb --- /dev/null +++ b/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models.py @@ -0,0 +1,41 @@ +"""Ollama specific chat model integration tests""" + +from typing import List, Optional + +import pytest +from pydantic import BaseModel, Field + +from langchain_ollama import ChatOllama + + +@pytest.mark.parametrize(("model"), [("llama3.1")]) +def test_structured_output_deeply_nested(model: str) -> None: + """Test to verify structured output with a nested objects.""" + llm = ChatOllama(model=model, temperature=0) + + class Person(BaseModel): + """Information about a person.""" + + name: Optional[str] = Field(default=None, description="The name of the person") + hair_color: Optional[str] = Field( + default=None, description="The color of the person's hair if known" + ) + height_in_meters: Optional[str] = Field( + default=None, description="Height measured in meters" + ) + + class Data(BaseModel): + """Extracted data about people.""" + + people: List[Person] + + chat = llm.with_structured_output(Data) # type: ignore[arg-type] + text = ( + "Alan Smith is 6 feet tall and has blond hair." + "Alan Poe is 3 feet tall and has grey hair." + ) + result = chat.invoke(text) + assert isinstance(result, Data) + + for chunk in chat.stream(text): + assert isinstance(chunk, Data) diff --git a/libs/partners/ollama/tests/integration_tests/test_chat_models.py b/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_standard.py similarity index 90% rename from libs/partners/ollama/tests/integration_tests/test_chat_models.py rename to libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_standard.py index 9133106cae7b9..476640ddd79c9 100644 --- a/libs/partners/ollama/tests/integration_tests/test_chat_models.py +++ b/libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_standard.py @@ -1,4 +1,4 @@ -"""Test chat model integration.""" +"""Test chat model integration using standard integration tests.""" from typing import Type @@ -16,7 +16,7 @@ def chat_model_class(self) -> Type[ChatOllama]: @property def chat_model_params(self) -> dict: - return {"model": "llama3-groq-tool-use"} + return {"model": "llama3.1"} @property def supports_image_inputs(self) -> bool: diff --git a/libs/partners/openai/langchain_openai/chat_models/base.py b/libs/partners/openai/langchain_openai/chat_models/base.py index 4579e94a4966f..e312ed249c88e 100644 --- a/libs/partners/openai/langchain_openai/chat_models/base.py +++ b/libs/partners/openai/langchain_openai/chat_models/base.py @@ -435,7 +435,7 @@ class BaseChatOpenAI(BaseChatModel): """Number of chat completions to generate for each prompt.""" top_p: Optional[float] = None """Total probability mass of tokens to consider at each step.""" - max_tokens: Optional[int] = None + max_tokens: Optional[int] = Field(default=None) """Maximum number of tokens to generate.""" tiktoken_model_name: Optional[str] = None """The model name to pass to tiktoken when using this class. @@ -699,6 +699,7 @@ def _get_request_payload( messages = self._convert_input(input_).to_messages() if stop is not None: kwargs["stop"] = stop + return { "messages": [_convert_message_to_dict(m) for m in messages], **self._default_params, @@ -853,7 +854,9 @@ def _get_ls_params( ls_model_type="chat", ls_temperature=params.get("temperature", self.temperature), ) - if ls_max_tokens := params.get("max_tokens", self.max_tokens): + if ls_max_tokens := params.get("max_tokens", self.max_tokens) or params.get( + "max_completion_tokens", self.max_tokens + ): ls_params["ls_max_tokens"] = ls_max_tokens if ls_stop := stop or params.get("stop", None): ls_params["ls_stop"] = ls_stop @@ -1501,7 +1504,7 @@ def _filter_disabled_params(self, **kwargs: Any) -> Dict[str, Any]: return filtered -class ChatOpenAI(BaseChatOpenAI): +class ChatOpenAI(BaseChatOpenAI): # type: ignore[override] """OpenAI chat model integration. .. dropdown:: Setup @@ -1963,6 +1966,9 @@ class Joke(BaseModel): message chunks will be generated during the stream including usage metadata. """ + max_tokens: Optional[int] = Field(default=None, alias="max_completion_tokens") + """Maximum number of tokens to generate.""" + @property def lc_secrets(self) -> Dict[str, str]: return {"openai_api_key": "OPENAI_API_KEY"} @@ -1992,6 +1998,29 @@ def is_lc_serializable(cls) -> bool: """Return whether this model can be serialized by Langchain.""" return True + @property + def _default_params(self) -> Dict[str, Any]: + """Get the default parameters for calling OpenAI API.""" + params = super()._default_params + if "max_tokens" in params: + params["max_completion_tokens"] = params.pop("max_tokens") + + return params + + def _get_request_payload( + self, + input_: LanguageModelInput, + *, + stop: Optional[List[str]] = None, + **kwargs: Any, + ) -> dict: + payload = super()._get_request_payload(input_, stop=stop, **kwargs) + # max_tokens was deprecated in favor of max_completion_tokens + # in September 2024 release + if "max_tokens" in payload: + payload["max_completion_tokens"] = payload.pop("max_tokens") + return payload + def _should_stream_usage( self, stream_usage: Optional[bool] = None, **kwargs: Any ) -> bool: diff --git a/libs/partners/openai/langchain_openai/llms/base.py b/libs/partners/openai/langchain_openai/llms/base.py index 633d473ae81d5..b910f2e404dd8 100644 --- a/libs/partners/openai/langchain_openai/llms/base.py +++ b/libs/partners/openai/langchain_openai/llms/base.py @@ -113,7 +113,7 @@ class BaseOpenAI(BaseLLM): ) """Timeout for requests to OpenAI completion API. Can be float, httpx.Timeout or None.""" - logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict) + logit_bias: Optional[Dict[str, float]] = None """Adjust the probability of specific tokens being generated.""" max_retries: int = 2 """Maximum number of retries to make when generating.""" @@ -205,11 +205,13 @@ def _default_params(self) -> Dict[str, Any]: "frequency_penalty": self.frequency_penalty, "presence_penalty": self.presence_penalty, "n": self.n, - "logit_bias": self.logit_bias, "seed": self.seed, "logprobs": self.logprobs, } + if self.logit_bias is not None: + normal_params["logit_bias"] = self.logit_bias + if self.max_tokens is not None: normal_params["max_tokens"] = self.max_tokens diff --git a/libs/partners/openai/poetry.lock b/libs/partners/openai/poetry.lock index 118f8dc31d35c..913cacca821f6 100644 --- a/libs/partners/openai/poetry.lock +++ b/libs/partners/openai/poetry.lock @@ -188,73 +188,73 @@ files = [ [[package]] name = "coverage" -version = "7.6.7" +version = "7.6.8" description = "Code coverage measurement for Python" optional = false python-versions = ">=3.9" files = [ - {file = "coverage-7.6.7-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:108bb458827765d538abcbf8288599fee07d2743357bdd9b9dad456c287e121e"}, - {file = "coverage-7.6.7-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c973b2fe4dc445cb865ab369df7521df9c27bf40715c837a113edaa2aa9faf45"}, - {file = "coverage-7.6.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3c6b24007c4bcd0b19fac25763a7cac5035c735ae017e9a349b927cfc88f31c1"}, - {file = "coverage-7.6.7-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:acbb8af78f8f91b3b51f58f288c0994ba63c646bc1a8a22ad072e4e7e0a49f1c"}, - {file = "coverage-7.6.7-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ad32a981bcdedb8d2ace03b05e4fd8dace8901eec64a532b00b15217d3677dd2"}, - {file = "coverage-7.6.7-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:34d23e28ccb26236718a3a78ba72744212aa383141961dd6825f6595005c8b06"}, - {file = "coverage-7.6.7-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e25bacb53a8c7325e34d45dddd2f2fbae0dbc230d0e2642e264a64e17322a777"}, - {file = "coverage-7.6.7-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:af05bbba896c4472a29408455fe31b3797b4d8648ed0a2ccac03e074a77e2314"}, - {file = "coverage-7.6.7-cp310-cp310-win32.whl", hash = "sha256:796c9b107d11d2d69e1849b2dfe41730134b526a49d3acb98ca02f4985eeff7a"}, - {file = "coverage-7.6.7-cp310-cp310-win_amd64.whl", hash = "sha256:987a8e3da7da4eed10a20491cf790589a8e5e07656b6dc22d3814c4d88faf163"}, - {file = "coverage-7.6.7-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:7e61b0e77ff4dddebb35a0e8bb5a68bf0f8b872407d8d9f0c726b65dfabe2469"}, - {file = "coverage-7.6.7-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1a5407a75ca4abc20d6252efeb238377a71ce7bda849c26c7a9bece8680a5d99"}, - {file = "coverage-7.6.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df002e59f2d29e889c37abd0b9ee0d0e6e38c24f5f55d71ff0e09e3412a340ec"}, - {file = "coverage-7.6.7-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:673184b3156cba06154825f25af33baa2671ddae6343f23175764e65a8c4c30b"}, - {file = "coverage-7.6.7-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e69ad502f1a2243f739f5bd60565d14a278be58be4c137d90799f2c263e7049a"}, - {file = "coverage-7.6.7-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:60dcf7605c50ea72a14490d0756daffef77a5be15ed1b9fea468b1c7bda1bc3b"}, - {file = "coverage-7.6.7-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:9c2eb378bebb2c8f65befcb5147877fc1c9fbc640fc0aad3add759b5df79d55d"}, - {file = "coverage-7.6.7-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:3c0317288f032221d35fa4cbc35d9f4923ff0dfd176c79c9b356e8ef8ef2dff4"}, - {file = "coverage-7.6.7-cp311-cp311-win32.whl", hash = "sha256:951aade8297358f3618a6e0660dc74f6b52233c42089d28525749fc8267dccd2"}, - {file = "coverage-7.6.7-cp311-cp311-win_amd64.whl", hash = "sha256:5e444b8e88339a2a67ce07d41faabb1d60d1004820cee5a2c2b54e2d8e429a0f"}, - {file = "coverage-7.6.7-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f07ff574986bc3edb80e2c36391678a271d555f91fd1d332a1e0f4b5ea4b6ea9"}, - {file = "coverage-7.6.7-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:49ed5ee4109258973630c1f9d099c7e72c5c36605029f3a91fe9982c6076c82b"}, - {file = "coverage-7.6.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3e8796434a8106b3ac025fd15417315d7a58ee3e600ad4dbcfddc3f4b14342c"}, - {file = "coverage-7.6.7-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a3b925300484a3294d1c70f6b2b810d6526f2929de954e5b6be2bf8caa1f12c1"}, - {file = "coverage-7.6.7-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3c42ec2c522e3ddd683dec5cdce8e62817afb648caedad9da725001fa530d354"}, - {file = "coverage-7.6.7-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0266b62cbea568bd5e93a4da364d05de422110cbed5056d69339bd5af5685433"}, - {file = "coverage-7.6.7-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:e5f2a0f161d126ccc7038f1f3029184dbdf8f018230af17ef6fd6a707a5b881f"}, - {file = "coverage-7.6.7-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c132b5a22821f9b143f87446805e13580b67c670a548b96da945a8f6b4f2efbb"}, - {file = "coverage-7.6.7-cp312-cp312-win32.whl", hash = "sha256:7c07de0d2a110f02af30883cd7dddbe704887617d5c27cf373362667445a4c76"}, - {file = "coverage-7.6.7-cp312-cp312-win_amd64.whl", hash = "sha256:fd49c01e5057a451c30c9b892948976f5d38f2cbd04dc556a82743ba8e27ed8c"}, - {file = "coverage-7.6.7-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:46f21663e358beae6b368429ffadf14ed0a329996248a847a4322fb2e35d64d3"}, - {file = "coverage-7.6.7-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:40cca284c7c310d622a1677f105e8507441d1bb7c226f41978ba7c86979609ab"}, - {file = "coverage-7.6.7-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:77256ad2345c29fe59ae861aa11cfc74579c88d4e8dbf121cbe46b8e32aec808"}, - {file = "coverage-7.6.7-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:87ea64b9fa52bf395272e54020537990a28078478167ade6c61da7ac04dc14bc"}, - {file = "coverage-7.6.7-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2d608a7808793e3615e54e9267519351c3ae204a6d85764d8337bd95993581a8"}, - {file = "coverage-7.6.7-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:cdd94501d65adc5c24f8a1a0eda110452ba62b3f4aeaba01e021c1ed9cb8f34a"}, - {file = "coverage-7.6.7-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:82c809a62e953867cf57e0548c2b8464207f5f3a6ff0e1e961683e79b89f2c55"}, - {file = "coverage-7.6.7-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:bb684694e99d0b791a43e9fc0fa58efc15ec357ac48d25b619f207c41f2fd384"}, - {file = "coverage-7.6.7-cp313-cp313-win32.whl", hash = "sha256:963e4a08cbb0af6623e61492c0ec4c0ec5c5cf74db5f6564f98248d27ee57d30"}, - {file = "coverage-7.6.7-cp313-cp313-win_amd64.whl", hash = "sha256:14045b8bfd5909196a90da145a37f9d335a5d988a83db34e80f41e965fb7cb42"}, - {file = "coverage-7.6.7-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:f2c7a045eef561e9544359a0bf5784b44e55cefc7261a20e730baa9220c83413"}, - {file = "coverage-7.6.7-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:5dd4e4a49d9c72a38d18d641135d2fb0bdf7b726ca60a103836b3d00a1182acd"}, - {file = "coverage-7.6.7-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5c95e0fa3d1547cb6f021ab72f5c23402da2358beec0a8e6d19a368bd7b0fb37"}, - {file = "coverage-7.6.7-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f63e21ed474edd23f7501f89b53280014436e383a14b9bd77a648366c81dce7b"}, - {file = "coverage-7.6.7-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ead9b9605c54d15be228687552916c89c9683c215370c4a44f1f217d2adcc34d"}, - {file = "coverage-7.6.7-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:0573f5cbf39114270842d01872952d301027d2d6e2d84013f30966313cadb529"}, - {file = "coverage-7.6.7-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:e2c8e3384c12dfa19fa9a52f23eb091a8fad93b5b81a41b14c17c78e23dd1d8b"}, - {file = "coverage-7.6.7-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:70a56a2ec1869e6e9fa69ef6b76b1a8a7ef709972b9cc473f9ce9d26b5997ce3"}, - {file = "coverage-7.6.7-cp313-cp313t-win32.whl", hash = "sha256:dbba8210f5067398b2c4d96b4e64d8fb943644d5eb70be0d989067c8ca40c0f8"}, - {file = "coverage-7.6.7-cp313-cp313t-win_amd64.whl", hash = "sha256:dfd14bcae0c94004baba5184d1c935ae0d1231b8409eb6c103a5fd75e8ecdc56"}, - {file = "coverage-7.6.7-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:37a15573f988b67f7348916077c6d8ad43adb75e478d0910957394df397d2874"}, - {file = "coverage-7.6.7-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b6cce5c76985f81da3769c52203ee94722cd5d5889731cd70d31fee939b74bf0"}, - {file = "coverage-7.6.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a1ab9763d291a17b527ac6fd11d1a9a9c358280adb320e9c2672a97af346ac2c"}, - {file = "coverage-7.6.7-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6cf96ceaa275f071f1bea3067f8fd43bec184a25a962c754024c973af871e1b7"}, - {file = "coverage-7.6.7-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aee9cf6b0134d6f932d219ce253ef0e624f4fa588ee64830fcba193269e4daa3"}, - {file = "coverage-7.6.7-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:2bc3e45c16564cc72de09e37413262b9f99167803e5e48c6156bccdfb22c8327"}, - {file = "coverage-7.6.7-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:623e6965dcf4e28a3debaa6fcf4b99ee06d27218f46d43befe4db1c70841551c"}, - {file = "coverage-7.6.7-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:850cfd2d6fc26f8346f422920ac204e1d28814e32e3a58c19c91980fa74d8289"}, - {file = "coverage-7.6.7-cp39-cp39-win32.whl", hash = "sha256:c296263093f099da4f51b3dff1eff5d4959b527d4f2f419e16508c5da9e15e8c"}, - {file = "coverage-7.6.7-cp39-cp39-win_amd64.whl", hash = "sha256:90746521206c88bdb305a4bf3342b1b7316ab80f804d40c536fc7d329301ee13"}, - {file = "coverage-7.6.7-pp39.pp310-none-any.whl", hash = "sha256:0ddcb70b3a3a57581b450571b31cb774f23eb9519c2aaa6176d3a84c9fc57671"}, - {file = "coverage-7.6.7.tar.gz", hash = "sha256:d79d4826e41441c9a118ff045e4bccb9fdbdcb1d02413e7ea6eb5c87b5439d24"}, + {file = "coverage-7.6.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b39e6011cd06822eb964d038d5dff5da5d98652b81f5ecd439277b32361a3a50"}, + {file = "coverage-7.6.8-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:63c19702db10ad79151a059d2d6336fe0c470f2e18d0d4d1a57f7f9713875dcf"}, + {file = "coverage-7.6.8-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3985b9be361d8fb6b2d1adc9924d01dec575a1d7453a14cccd73225cb79243ee"}, + {file = "coverage-7.6.8-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:644ec81edec0f4ad17d51c838a7d01e42811054543b76d4ba2c5d6af741ce2a6"}, + {file = "coverage-7.6.8-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1f188a2402f8359cf0c4b1fe89eea40dc13b52e7b4fd4812450da9fcd210181d"}, + {file = "coverage-7.6.8-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:e19122296822deafce89a0c5e8685704c067ae65d45e79718c92df7b3ec3d331"}, + {file = "coverage-7.6.8-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:13618bed0c38acc418896005732e565b317aa9e98d855a0e9f211a7ffc2d6638"}, + {file = "coverage-7.6.8-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:193e3bffca48ad74b8c764fb4492dd875038a2f9925530cb094db92bb5e47bed"}, + {file = "coverage-7.6.8-cp310-cp310-win32.whl", hash = "sha256:3988665ee376abce49613701336544041f2117de7b7fbfe91b93d8ff8b151c8e"}, + {file = "coverage-7.6.8-cp310-cp310-win_amd64.whl", hash = "sha256:f56f49b2553d7dd85fd86e029515a221e5c1f8cb3d9c38b470bc38bde7b8445a"}, + {file = "coverage-7.6.8-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:86cffe9c6dfcfe22e28027069725c7f57f4b868a3f86e81d1c62462764dc46d4"}, + {file = "coverage-7.6.8-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d82ab6816c3277dc962cfcdc85b1efa0e5f50fb2c449432deaf2398a2928ab94"}, + {file = "coverage-7.6.8-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:13690e923a3932e4fad4c0ebfb9cb5988e03d9dcb4c5150b5fcbf58fd8bddfc4"}, + {file = "coverage-7.6.8-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4be32da0c3827ac9132bb488d331cb32e8d9638dd41a0557c5569d57cf22c9c1"}, + {file = "coverage-7.6.8-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:44e6c85bbdc809383b509d732b06419fb4544dca29ebe18480379633623baafb"}, + {file = "coverage-7.6.8-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:768939f7c4353c0fac2f7c37897e10b1414b571fd85dd9fc49e6a87e37a2e0d8"}, + {file = "coverage-7.6.8-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e44961e36cb13c495806d4cac67640ac2866cb99044e210895b506c26ee63d3a"}, + {file = "coverage-7.6.8-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:3ea8bb1ab9558374c0ab591783808511d135a833c3ca64a18ec927f20c4030f0"}, + {file = "coverage-7.6.8-cp311-cp311-win32.whl", hash = "sha256:629a1ba2115dce8bf75a5cce9f2486ae483cb89c0145795603d6554bdc83e801"}, + {file = "coverage-7.6.8-cp311-cp311-win_amd64.whl", hash = "sha256:fb9fc32399dca861584d96eccd6c980b69bbcd7c228d06fb74fe53e007aa8ef9"}, + {file = "coverage-7.6.8-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:e683e6ecc587643f8cde8f5da6768e9d165cd31edf39ee90ed7034f9ca0eefee"}, + {file = "coverage-7.6.8-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1defe91d41ce1bd44b40fabf071e6a01a5aa14de4a31b986aa9dfd1b3e3e414a"}, + {file = "coverage-7.6.8-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7ad66e8e50225ebf4236368cc43c37f59d5e6728f15f6e258c8639fa0dd8e6d"}, + {file = "coverage-7.6.8-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3fe47da3e4fda5f1abb5709c156eca207eacf8007304ce3019eb001e7a7204cb"}, + {file = "coverage-7.6.8-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:202a2d645c5a46b84992f55b0a3affe4f0ba6b4c611abec32ee88358db4bb649"}, + {file = "coverage-7.6.8-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:4674f0daa1823c295845b6a740d98a840d7a1c11df00d1fd62614545c1583787"}, + {file = "coverage-7.6.8-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:74610105ebd6f33d7c10f8907afed696e79c59e3043c5f20eaa3a46fddf33b4c"}, + {file = "coverage-7.6.8-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:37cda8712145917105e07aab96388ae76e787270ec04bcb9d5cc786d7cbb8443"}, + {file = "coverage-7.6.8-cp312-cp312-win32.whl", hash = "sha256:9e89d5c8509fbd6c03d0dd1972925b22f50db0792ce06324ba069f10787429ad"}, + {file = "coverage-7.6.8-cp312-cp312-win_amd64.whl", hash = "sha256:379c111d3558272a2cae3d8e57e6b6e6f4fe652905692d54bad5ea0ca37c5ad4"}, + {file = "coverage-7.6.8-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0b0c69f4f724c64dfbfe79f5dfb503b42fe6127b8d479b2677f2b227478db2eb"}, + {file = "coverage-7.6.8-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:c15b32a7aca8038ed7644f854bf17b663bc38e1671b5d6f43f9a2b2bd0c46f63"}, + {file = "coverage-7.6.8-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63068a11171e4276f6ece913bde059e77c713b48c3a848814a6537f35afb8365"}, + {file = "coverage-7.6.8-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6f4548c5ead23ad13fb7a2c8ea541357474ec13c2b736feb02e19a3085fac002"}, + {file = "coverage-7.6.8-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3b4b4299dd0d2c67caaaf286d58aef5e75b125b95615dda4542561a5a566a1e3"}, + {file = "coverage-7.6.8-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c9ebfb2507751f7196995142f057d1324afdab56db1d9743aab7f50289abd022"}, + {file = "coverage-7.6.8-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:c1b4474beee02ede1eef86c25ad4600a424fe36cff01a6103cb4533c6bf0169e"}, + {file = "coverage-7.6.8-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:d9fd2547e6decdbf985d579cf3fc78e4c1d662b9b0ff7cc7862baaab71c9cc5b"}, + {file = "coverage-7.6.8-cp313-cp313-win32.whl", hash = "sha256:8aae5aea53cbfe024919715eca696b1a3201886ce83790537d1c3668459c7146"}, + {file = "coverage-7.6.8-cp313-cp313-win_amd64.whl", hash = "sha256:ae270e79f7e169ccfe23284ff5ea2d52a6f401dc01b337efb54b3783e2ce3f28"}, + {file = "coverage-7.6.8-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:de38add67a0af869b0d79c525d3e4588ac1ffa92f39116dbe0ed9753f26eba7d"}, + {file = "coverage-7.6.8-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:b07c25d52b1c16ce5de088046cd2432b30f9ad5e224ff17c8f496d9cb7d1d451"}, + {file = "coverage-7.6.8-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:62a66ff235e4c2e37ed3b6104d8b478d767ff73838d1222132a7a026aa548764"}, + {file = "coverage-7.6.8-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09b9f848b28081e7b975a3626e9081574a7b9196cde26604540582da60235fdf"}, + {file = "coverage-7.6.8-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:093896e530c38c8e9c996901858ac63f3d4171268db2c9c8b373a228f459bbc5"}, + {file = "coverage-7.6.8-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:9a7b8ac36fd688c8361cbc7bf1cb5866977ece6e0b17c34aa0df58bda4fa18a4"}, + {file = "coverage-7.6.8-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:38c51297b35b3ed91670e1e4efb702b790002e3245a28c76e627478aa3c10d83"}, + {file = "coverage-7.6.8-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:2e4e0f60cb4bd7396108823548e82fdab72d4d8a65e58e2c19bbbc2f1e2bfa4b"}, + {file = "coverage-7.6.8-cp313-cp313t-win32.whl", hash = "sha256:6535d996f6537ecb298b4e287a855f37deaf64ff007162ec0afb9ab8ba3b8b71"}, + {file = "coverage-7.6.8-cp313-cp313t-win_amd64.whl", hash = "sha256:c79c0685f142ca53256722a384540832420dff4ab15fec1863d7e5bc8691bdcc"}, + {file = "coverage-7.6.8-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3ac47fa29d8d41059ea3df65bd3ade92f97ee4910ed638e87075b8e8ce69599e"}, + {file = "coverage-7.6.8-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:24eda3a24a38157eee639ca9afe45eefa8d2420d49468819ac5f88b10de84f4c"}, + {file = "coverage-7.6.8-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e4c81ed2820b9023a9a90717020315e63b17b18c274a332e3b6437d7ff70abe0"}, + {file = "coverage-7.6.8-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bd55f8fc8fa494958772a2a7302b0354ab16e0b9272b3c3d83cdb5bec5bd1779"}, + {file = "coverage-7.6.8-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f39e2f3530ed1626c66e7493be7a8423b023ca852aacdc91fb30162c350d2a92"}, + {file = "coverage-7.6.8-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:716a78a342679cd1177bc8c2fe957e0ab91405bd43a17094324845200b2fddf4"}, + {file = "coverage-7.6.8-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:177f01eeaa3aee4a5ffb0d1439c5952b53d5010f86e9d2667963e632e30082cc"}, + {file = "coverage-7.6.8-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:912e95017ff51dc3d7b6e2be158dedc889d9a5cc3382445589ce554f1a34c0ea"}, + {file = "coverage-7.6.8-cp39-cp39-win32.whl", hash = "sha256:4db3ed6a907b555e57cc2e6f14dc3a4c2458cdad8919e40b5357ab9b6db6c43e"}, + {file = "coverage-7.6.8-cp39-cp39-win_amd64.whl", hash = "sha256:428ac484592f780e8cd7b6b14eb568f7c85460c92e2a37cb0c0e5186e1a0d076"}, + {file = "coverage-7.6.8-pp39.pp310-none-any.whl", hash = "sha256:5c52a036535d12590c32c49209e79cabaad9f9ad8aa4cbd875b68c4d67a9cbce"}, + {file = "coverage-7.6.8.tar.gz", hash = "sha256:8b2b8503edb06822c86d82fa64a4a5cb0760bb8f31f26e138ec743f422f37cfc"}, ] [package.dependencies] @@ -386,84 +386,86 @@ files = [ [[package]] name = "jiter" -version = "0.7.1" +version = "0.8.0" description = "Fast iterable JSON parser." optional = false python-versions = ">=3.8" files = [ - {file = "jiter-0.7.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:262e96d06696b673fad6f257e6a0abb6e873dc22818ca0e0600f4a1189eb334f"}, - {file = "jiter-0.7.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:be6de02939aac5be97eb437f45cfd279b1dc9de358b13ea6e040e63a3221c40d"}, - {file = "jiter-0.7.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:935f10b802bc1ce2b2f61843e498c7720aa7f4e4bb7797aa8121eab017293c3d"}, - {file = "jiter-0.7.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9cd3cccccabf5064e4bb3099c87bf67db94f805c1e62d1aefd2b7476e90e0ee2"}, - {file = "jiter-0.7.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4aa919ebfc5f7b027cc368fe3964c0015e1963b92e1db382419dadb098a05192"}, - {file = "jiter-0.7.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ae2d01e82c94491ce4d6f461a837f63b6c4e6dd5bb082553a70c509034ff3d4"}, - {file = "jiter-0.7.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f9568cd66dbbdab67ae1b4c99f3f7da1228c5682d65913e3f5f95586b3cb9a9"}, - {file = "jiter-0.7.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9ecbf4e20ec2c26512736284dc1a3f8ed79b6ca7188e3b99032757ad48db97dc"}, - {file = "jiter-0.7.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:b1a0508fddc70ce00b872e463b387d49308ef02b0787992ca471c8d4ba1c0fa1"}, - {file = "jiter-0.7.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f84c9996664c460f24213ff1e5881530abd8fafd82058d39af3682d5fd2d6316"}, - {file = "jiter-0.7.1-cp310-none-win32.whl", hash = "sha256:c915e1a1960976ba4dfe06551ea87063b2d5b4d30759012210099e712a414d9f"}, - {file = "jiter-0.7.1-cp310-none-win_amd64.whl", hash = "sha256:75bf3b7fdc5c0faa6ffffcf8028a1f974d126bac86d96490d1b51b3210aa0f3f"}, - {file = "jiter-0.7.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ad04a23a91f3d10d69d6c87a5f4471b61c2c5cd6e112e85136594a02043f462c"}, - {file = "jiter-0.7.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1e47a554de88dff701226bb5722b7f1b6bccd0b98f1748459b7e56acac2707a5"}, - {file = "jiter-0.7.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1e44fff69c814a2e96a20b4ecee3e2365e9b15cf5fe4e00869d18396daa91dab"}, - {file = "jiter-0.7.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:df0a1d05081541b45743c965436f8b5a1048d6fd726e4a030113a2699a6046ea"}, - {file = "jiter-0.7.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f22cf8f236a645cb6d8ffe2a64edb5d2b66fb148bf7c75eea0cb36d17014a7bc"}, - {file = "jiter-0.7.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:da8589f50b728ea4bf22e0632eefa125c8aa9c38ed202a5ee6ca371f05eeb3ff"}, - {file = "jiter-0.7.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f20de711224f2ca2dbb166a8d512f6ff48c9c38cc06b51f796520eb4722cc2ce"}, - {file = "jiter-0.7.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8a9803396032117b85ec8cbf008a54590644a062fedd0425cbdb95e4b2b60479"}, - {file = "jiter-0.7.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:3d8bae77c82741032e9d89a4026479061aba6e646de3bf5f2fc1ae2bbd9d06e0"}, - {file = "jiter-0.7.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:3dc9939e576bbc68c813fc82f6620353ed68c194c7bcf3d58dc822591ec12490"}, - {file = "jiter-0.7.1-cp311-none-win32.whl", hash = "sha256:f7605d24cd6fab156ec89e7924578e21604feee9c4f1e9da34d8b67f63e54892"}, - {file = "jiter-0.7.1-cp311-none-win_amd64.whl", hash = "sha256:f3ea649e7751a1a29ea5ecc03c4ada0a833846c59c6da75d747899f9b48b7282"}, - {file = "jiter-0.7.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:ad36a1155cbd92e7a084a568f7dc6023497df781adf2390c345dd77a120905ca"}, - {file = "jiter-0.7.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7ba52e6aaed2dc5c81a3d9b5e4ab95b039c4592c66ac973879ba57c3506492bb"}, - {file = "jiter-0.7.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2b7de0b6f6728b678540c7927587e23f715284596724be203af952418acb8a2d"}, - {file = "jiter-0.7.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9463b62bd53c2fb85529c700c6a3beb2ee54fde8bef714b150601616dcb184a6"}, - {file = "jiter-0.7.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:627164ec01d28af56e1f549da84caf0fe06da3880ebc7b7ee1ca15df106ae172"}, - {file = "jiter-0.7.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:25d0e5bf64e368b0aa9e0a559c3ab2f9b67e35fe7269e8a0d81f48bbd10e8963"}, - {file = "jiter-0.7.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c244261306f08f8008b3087059601997016549cb8bb23cf4317a4827f07b7d74"}, - {file = "jiter-0.7.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7ded4e4b75b68b843b7cea5cd7c55f738c20e1394c68c2cb10adb655526c5f1b"}, - {file = "jiter-0.7.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:80dae4f1889b9d09e5f4de6b58c490d9c8ce7730e35e0b8643ab62b1538f095c"}, - {file = "jiter-0.7.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:5970cf8ec943b51bce7f4b98d2e1ed3ada170c2a789e2db3cb484486591a176a"}, - {file = "jiter-0.7.1-cp312-none-win32.whl", hash = "sha256:701d90220d6ecb3125d46853c8ca8a5bc158de8c49af60fd706475a49fee157e"}, - {file = "jiter-0.7.1-cp312-none-win_amd64.whl", hash = "sha256:7824c3ecf9ecf3321c37f4e4d4411aad49c666ee5bc2a937071bdd80917e4533"}, - {file = "jiter-0.7.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:097676a37778ba3c80cb53f34abd6943ceb0848263c21bf423ae98b090f6c6ba"}, - {file = "jiter-0.7.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3298af506d4271257c0a8f48668b0f47048d69351675dd8500f22420d4eec378"}, - {file = "jiter-0.7.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:12fd88cfe6067e2199964839c19bd2b422ca3fd792949b8f44bb8a4e7d21946a"}, - {file = "jiter-0.7.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:dacca921efcd21939123c8ea8883a54b9fa7f6545c8019ffcf4f762985b6d0c8"}, - {file = "jiter-0.7.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:de3674a5fe1f6713a746d25ad9c32cd32fadc824e64b9d6159b3b34fd9134143"}, - {file = "jiter-0.7.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:65df9dbae6d67e0788a05b4bad5706ad40f6f911e0137eb416b9eead6ba6f044"}, - {file = "jiter-0.7.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7ba9a358d59a0a55cccaa4957e6ae10b1a25ffdabda863c0343c51817610501d"}, - {file = "jiter-0.7.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:576eb0f0c6207e9ede2b11ec01d9c2182973986514f9c60bc3b3b5d5798c8f50"}, - {file = "jiter-0.7.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:e550e29cdf3577d2c970a18f3959e6b8646fd60ef1b0507e5947dc73703b5627"}, - {file = "jiter-0.7.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:81d968dbf3ce0db2e0e4dec6b0a0d5d94f846ee84caf779b07cab49f5325ae43"}, - {file = "jiter-0.7.1-cp313-none-win32.whl", hash = "sha256:f892e547e6e79a1506eb571a676cf2f480a4533675f834e9ae98de84f9b941ac"}, - {file = "jiter-0.7.1-cp313-none-win_amd64.whl", hash = "sha256:0302f0940b1455b2a7fb0409b8d5b31183db70d2b07fd177906d83bf941385d1"}, - {file = "jiter-0.7.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:c65a3ce72b679958b79d556473f192a4dfc5895e8cc1030c9f4e434690906076"}, - {file = "jiter-0.7.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:e80052d3db39f9bb8eb86d207a1be3d9ecee5e05fdec31380817f9609ad38e60"}, - {file = "jiter-0.7.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:70a497859c4f3f7acd71c8bd89a6f9cf753ebacacf5e3e799138b8e1843084e3"}, - {file = "jiter-0.7.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c1288bc22b9e36854a0536ba83666c3b1fb066b811019d7b682c9cf0269cdf9f"}, - {file = "jiter-0.7.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b096ca72dd38ef35675e1d3b01785874315182243ef7aea9752cb62266ad516f"}, - {file = "jiter-0.7.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8dbbd52c50b605af13dbee1a08373c520e6fcc6b5d32f17738875847fea4e2cd"}, - {file = "jiter-0.7.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:af29c5c6eb2517e71ffa15c7ae9509fa5e833ec2a99319ac88cc271eca865519"}, - {file = "jiter-0.7.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f114a4df1e40c03c0efbf974b376ed57756a1141eb27d04baee0680c5af3d424"}, - {file = "jiter-0.7.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:191fbaee7cf46a9dd9b817547bf556facde50f83199d07fc48ebeff4082f9df4"}, - {file = "jiter-0.7.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:0e2b445e5ee627fb4ee6bbceeb486251e60a0c881a8e12398dfdff47c56f0723"}, - {file = "jiter-0.7.1-cp38-none-win32.whl", hash = "sha256:47ac4c3cf8135c83e64755b7276339b26cd3c7ddadf9e67306ace4832b283edf"}, - {file = "jiter-0.7.1-cp38-none-win_amd64.whl", hash = "sha256:60b49c245cd90cde4794f5c30f123ee06ccf42fb8730a019a2870cd005653ebd"}, - {file = "jiter-0.7.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:8f212eeacc7203256f526f550d105d8efa24605828382cd7d296b703181ff11d"}, - {file = "jiter-0.7.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:d9e247079d88c00e75e297e6cb3a18a039ebcd79fefc43be9ba4eb7fb43eb726"}, - {file = "jiter-0.7.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f0aacaa56360139c53dcf352992b0331f4057a0373bbffd43f64ba0c32d2d155"}, - {file = "jiter-0.7.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bc1b55314ca97dbb6c48d9144323896e9c1a25d41c65bcb9550b3e0c270ca560"}, - {file = "jiter-0.7.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f281aae41b47e90deb70e7386558e877a8e62e1693e0086f37d015fa1c102289"}, - {file = "jiter-0.7.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:93c20d2730a84d43f7c0b6fb2579dc54335db742a59cf9776d0b80e99d587382"}, - {file = "jiter-0.7.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e81ccccd8069110e150613496deafa10da2f6ff322a707cbec2b0d52a87b9671"}, - {file = "jiter-0.7.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0a7d5e85766eff4c9be481d77e2226b4c259999cb6862ccac5ef6621d3c8dcce"}, - {file = "jiter-0.7.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:f52ce5799df5b6975439ecb16b1e879d7655e1685b6e3758c9b1b97696313bfb"}, - {file = "jiter-0.7.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:e0c91a0304373fdf97d56f88356a010bba442e6d995eb7773cbe32885b71cdd8"}, - {file = "jiter-0.7.1-cp39-none-win32.whl", hash = "sha256:5c08adf93e41ce2755970e8aa95262298afe2bf58897fb9653c47cd93c3c6cdc"}, - {file = "jiter-0.7.1-cp39-none-win_amd64.whl", hash = "sha256:6592f4067c74176e5f369228fb2995ed01400c9e8e1225fb73417183a5e635f0"}, - {file = "jiter-0.7.1.tar.gz", hash = "sha256:448cf4f74f7363c34cdef26214da527e8eeffd88ba06d0b80b485ad0667baf5d"}, + {file = "jiter-0.8.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:dee4eeb293ffcd2c3b31ebab684dbf7f7b71fe198f8eddcdf3a042cc6e10205a"}, + {file = "jiter-0.8.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:aad1e6e9b01cf0304dcee14db03e92e0073287a6297caf5caf2e9dbfea16a924"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:504099fb7acdbe763e10690d560a25d4aee03d918d6a063f3a761d8a09fb833f"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2373487caad7fe39581f588ab5c9262fc1ade078d448626fec93f4ffba528858"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c341ecc3f9bccde952898b0c97c24f75b84b56a7e2f8bbc7c8e38cab0875a027"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0e48e7a336529b9419d299b70c358d4ebf99b8f4b847ed3f1000ec9f320e8c0c"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f5ee157a8afd2943be690db679f82fafb8d347a8342e8b9c34863de30c538d55"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d7dceae3549b80087f913aad4acc2a7c1e0ab7cb983effd78bdc9c41cabdcf18"}, + {file = "jiter-0.8.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e29e9ecce53d396772590438214cac4ab89776f5e60bd30601f1050b34464019"}, + {file = "jiter-0.8.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:fa1782f22d5f92c620153133f35a9a395d3f3823374bceddd3e7032e2fdfa0b1"}, + {file = "jiter-0.8.0-cp310-none-win32.whl", hash = "sha256:f754ef13b4e4f67a3bf59fe974ef4342523801c48bf422f720bd37a02a360584"}, + {file = "jiter-0.8.0-cp310-none-win_amd64.whl", hash = "sha256:796f750b65f5d605f5e7acaccc6b051675e60c41d7ac3eab40dbd7b5b81a290f"}, + {file = "jiter-0.8.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:f6f4e645efd96b4690b9b6091dbd4e0fa2885ba5c57a0305c1916b75b4f30ff6"}, + {file = "jiter-0.8.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f61cf6d93c1ade9b8245c9f14b7900feadb0b7899dbe4aa8de268b705647df81"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0396bc5cb1309c6dab085e70bb3913cdd92218315e47b44afe9eace68ee8adaa"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:62d0e42ec5dc772bd8554a304358220be5d97d721c4648b23f3a9c01ccc2cb26"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ec4b711989860705733fc59fb8c41b2def97041cea656b37cf6c8ea8dee1c3f4"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:859cc35bf304ab066d88f10a44a3251a9cd057fb11ec23e00be22206db878f4f"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5000195921aa293b39b9b5bc959d7fa658e7f18f938c0e52732da8e3cc70a278"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:36050284c0abde57aba34964d3920f3d6228211b65df7187059bb7c7f143759a"}, + {file = "jiter-0.8.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:a88f608e050cfe45c48d771e86ecdbf5258314c883c986d4217cc79e1fb5f689"}, + {file = "jiter-0.8.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:646cf4237665b2e13b4159d8f26d53f59bc9f2e6e135e3a508a2e5dd26d978c6"}, + {file = "jiter-0.8.0-cp311-none-win32.whl", hash = "sha256:21fe5b8345db1b3023052b2ade9bb4d369417827242892051244af8fae8ba231"}, + {file = "jiter-0.8.0-cp311-none-win_amd64.whl", hash = "sha256:30c2161c5493acf6b6c3c909973fb64ae863747def01cc7574f3954e0a15042c"}, + {file = "jiter-0.8.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:d91a52d8f49ada2672a4b808a0c5c25d28f320a2c9ca690e30ebd561eb5a1002"}, + {file = "jiter-0.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c38cf25cf7862f61410b7a49684d34eb3b5bcbd7ddaf4773eea40e0bd43de706"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c6189beb5c4b3117624be6b2e84545cff7611f5855d02de2d06ff68e316182be"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e13fa849c0e30643554add089983caa82f027d69fad8f50acadcb21c462244ab"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d7765ca159d0a58e8e0f8ca972cd6d26a33bc97b4480d0d2309856763807cd28"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1b0befe7c6e9fc867d5bed21bab0131dfe27d1fa5cd52ba2bced67da33730b7d"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7d6363d4c6f1052b1d8b494eb9a72667c3ef5f80ebacfe18712728e85327000"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a873e57009863eeac3e3969e4653f07031d6270d037d6224415074ac17e5505c"}, + {file = "jiter-0.8.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:2582912473c0d9940791479fe1bf2976a34f212eb8e0a82ee9e645ac275c5d16"}, + {file = "jiter-0.8.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:646163201af42f55393ee6e8f6136b8df488253a6533f4230a64242ecbfe6048"}, + {file = "jiter-0.8.0-cp312-none-win32.whl", hash = "sha256:96e75c9abfbf7387cba89a324d2356d86d8897ac58c956017d062ad510832dae"}, + {file = "jiter-0.8.0-cp312-none-win_amd64.whl", hash = "sha256:ed6074552b4a32e047b52dad5ab497223721efbd0e9efe68c67749f094a092f7"}, + {file = "jiter-0.8.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:dd5e351cb9b3e676ec3360a85ea96def515ad2b83c8ae3a251ce84985a2c9a6f"}, + {file = "jiter-0.8.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ba9f12b0f801ecd5ed0cec29041dc425d1050922b434314c592fc30d51022467"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a7ba461c3681728d556392e8ae56fb44a550155a24905f01982317b367c21dd4"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3a15ed47ab09576db560dbc5c2c5a64477535beb056cd7d997d5dd0f2798770e"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cef55042816d0737142b0ec056c0356a5f681fb8d6aa8499b158e87098f4c6f8"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:549f170215adeb5e866f10617c3d019d8eb4e6d4e3c6b724b3b8c056514a3487"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f867edeb279d22020877640d2ea728de5817378c60a51be8af731a8a8f525306"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:aef8845f463093799db4464cee2aa59d61aa8edcb3762aaa4aacbec3f478c929"}, + {file = "jiter-0.8.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:d0d6e22e4062c3d3c1bf3594baa2f67fc9dcdda8275abad99e468e0c6540bc54"}, + {file = "jiter-0.8.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:079e62e64696241ac3f408e337aaac09137ed760ccf2b72b1094b48745c13641"}, + {file = "jiter-0.8.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:74d2b56ed3da5760544df53b5f5c39782e68efb64dc3aa0bba4cc08815e6fae8"}, + {file = "jiter-0.8.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:798dafe108cba58a7bb0a50d4d5971f98bb7f3c974e1373e750de6eb21c1a329"}, + {file = "jiter-0.8.0-cp313-none-win32.whl", hash = "sha256:ca6d3064dfc743eb0d3d7539d89d4ba886957c717567adc72744341c1e3573c9"}, + {file = "jiter-0.8.0-cp313-none-win_amd64.whl", hash = "sha256:38caedda64fe1f04b06d7011fc15e86b3b837ed5088657bf778656551e3cd8f9"}, + {file = "jiter-0.8.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:bb5c8a0a8d081c338db22e5b8d53a89a121790569cbb85f7d3cfb1fe0fbe9836"}, + {file = "jiter-0.8.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:202dbe8970bfb166fab950eaab8f829c505730a0b33cc5e1cfb0a1c9dd56b2f9"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9046812e5671fdcfb9ae02881fff1f6a14d484b7e8b3316179a372cdfa1e8026"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e6ac56425023e52d65150918ae25480d0a1ce2a6bf5ea2097f66a2cc50f6d692"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7dfcf97210c6eab9d2a1c6af15dd39e1d5154b96a7145d0a97fa1df865b7b834"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d4e3c8444d418686f78c9a547b9b90031faf72a0a1a46bfec7fb31edbd889c0d"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6507011a299b7f578559084256405a8428875540d8d13530e00b688e41b09493"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0aae4738eafdd34f0f25c2d3668ce9e8fa0d7cb75a2efae543c9a69aebc37323"}, + {file = "jiter-0.8.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:7f5d782e790396b13f2a7b36bdcaa3736a33293bdda80a4bf1a3ce0cd5ef9f15"}, + {file = "jiter-0.8.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:cc7f993bc2c4e03015445adbb16790c303282fce2e8d9dc3a3905b1d40e50564"}, + {file = "jiter-0.8.0-cp38-none-win32.whl", hash = "sha256:d4a8a6eda018a991fa58ef707dd51524055d11f5acb2f516d70b1be1d15ab39c"}, + {file = "jiter-0.8.0-cp38-none-win_amd64.whl", hash = "sha256:4cca948a3eda8ea24ed98acb0ee19dc755b6ad2e570ec85e1527d5167f91ff67"}, + {file = "jiter-0.8.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:ef89663678d8257063ce7c00d94638e05bd72f662c5e1eb0e07a172e6c1a9a9f"}, + {file = "jiter-0.8.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c402ddcba90b4cc71db3216e8330f4db36e0da2c78cf1d8a9c3ed8f272602a94"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a6dfe795b7a173a9f8ba7421cdd92193d60c1c973bbc50dc3758a9ad0fa5eb6"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8ec29a31b9abd6be39453a2c45da067138a3005d65d2c0507c530e0f1fdcd9a4"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2a488f8c54bddc3ddefaf3bfd6de4a52c97fc265d77bc2dcc6ee540c17e8c342"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:aeb5561adf4d26ca0d01b5811b4d7b56a8986699a473d700757b4758ef787883"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ab961858d7ad13132328517d29f121ae1b2d94502191d6bcf96bddcc8bb5d1c"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a207e718d114d23acf0850a2174d290f42763d955030d9924ffa4227dbd0018f"}, + {file = "jiter-0.8.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:733bc9dc8ff718a0ae4695239e9268eb93e88b73b367dfac3ec227d8ce2f1e77"}, + {file = "jiter-0.8.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d1ec27299e22d05e13a06e460bf7f75f26f9aaa0e0fb7d060f40e88df1d81faa"}, + {file = "jiter-0.8.0-cp39-none-win32.whl", hash = "sha256:e8dbfcb46553e6661d3fc1f33831598fcddf73d0f67834bce9fc3e9ebfe5c439"}, + {file = "jiter-0.8.0-cp39-none-win_amd64.whl", hash = "sha256:af2ce2487b3a93747e2cb5150081d4ae1e5874fce5924fc1a12e9e768e489ad8"}, + {file = "jiter-0.8.0.tar.gz", hash = "sha256:86fee98b569d4cc511ff2e3ec131354fafebd9348a487549c31ad371ae730310"}, ] [[package]] @@ -493,7 +495,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.22" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -518,7 +520,7 @@ url = "../../core" [[package]] name = "langchain-tests" -version = "0.3.1" +version = "0.3.6" description = "Standard tests for LangChain implementations" optional = false python-versions = ">=3.9,<4.0" @@ -526,9 +528,15 @@ files = [] develop = true [package.dependencies] -httpx = "^0.27.0" -langchain-core = "^0.3.15" +httpx = ">=0.25.0,<1" +langchain-core = "^0.3.22" +numpy = [ + {version = ">=1.24.0,<2.0.0", markers = "python_version < \"3.12\""}, + {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}, +] pytest = ">=7,<9" +pytest-asyncio = ">=0.20,<1" +pytest-socket = ">=0.6.0,<1" syrupy = "^4" [package.source] @@ -537,18 +545,18 @@ url = "../../standard-tests" [[package]] name = "langsmith" -version = "0.1.143" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.143-py3-none-any.whl", hash = "sha256:ba0d827269e9b03a90fababe41fa3e4e3f833300b95add10184f7e67167dde6f"}, - {file = "langsmith-0.1.143.tar.gz", hash = "sha256:4c5159e5cd84b3f8499433009e72d2076dd2daf6c044ac8a3611b30d0d0161c5"}, + {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"}, + {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -556,6 +564,9 @@ pydantic = [ requests = ">=2,<3" requests-toolbelt = ">=1.0.0,<2.0.0" +[package.extras] +langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"] + [[package]] name = "mypy" version = "1.13.0" @@ -667,13 +678,13 @@ files = [ [[package]] name = "openai" -version = "1.54.4" +version = "1.56.0" description = "The official Python library for the openai API" optional = false python-versions = ">=3.8" files = [ - {file = "openai-1.54.4-py3-none-any.whl", hash = "sha256:0d95cef99346bf9b6d7fbf57faf61a673924c3e34fa8af84c9ffe04660673a7e"}, - {file = "openai-1.54.4.tar.gz", hash = "sha256:50f3656e45401c54e973fa05dc29f3f0b0d19348d685b2f7ddb4d92bf7b1b6bf"}, + {file = "openai-1.56.0-py3-none-any.whl", hash = "sha256:0751a6e139a09fca2e9cbbe8a62bfdab901b5865249d2555d005decf966ef9c3"}, + {file = "openai-1.56.0.tar.gz", hash = "sha256:f7fa159c8e18e7f9a8d71ff4b8052452ae70a4edc6b76a6e97eda00d5364923f"}, ] [package.dependencies] @@ -691,69 +702,86 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"] [[package]] name = "orjson" -version = "3.10.11" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.11-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6dade64687f2bd7c090281652fe18f1151292d567a9302b34c2dbb92a3872f1f"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82f07c550a6ccd2b9290849b22316a609023ed851a87ea888c0456485a7d196a"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd9a187742d3ead9df2e49240234d728c67c356516cf4db018833a86f20ec18c"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:77b0fed6f209d76c1c39f032a70df2d7acf24b1812ca3e6078fd04e8972685a3"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:63fc9d5fe1d4e8868f6aae547a7b8ba0a2e592929245fff61d633f4caccdcdd6"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65cd3e3bb4fbb4eddc3c1e8dce10dc0b73e808fcb875f9fab40c81903dd9323e"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6f67c570602300c4befbda12d153113b8974a3340fdcf3d6de095ede86c06d92"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:1f39728c7f7d766f1f5a769ce4d54b5aaa4c3f92d5b84817053cc9995b977acc"}, - {file = "orjson-3.10.11-cp310-none-win32.whl", hash = "sha256:1789d9db7968d805f3d94aae2c25d04014aae3a2fa65b1443117cd462c6da647"}, - {file = "orjson-3.10.11-cp310-none-win_amd64.whl", hash = "sha256:5576b1e5a53a5ba8f8df81872bb0878a112b3ebb1d392155f00f54dd86c83ff6"}, - {file = "orjson-3.10.11-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1444f9cb7c14055d595de1036f74ecd6ce15f04a715e73f33bb6326c9cef01b6"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdec57fe3b4bdebcc08a946db3365630332dbe575125ff3d80a3272ebd0ddafe"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4eed32f33a0ea6ef36ccc1d37f8d17f28a1d6e8eefae5928f76aff8f1df85e67"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:80df27dd8697242b904f4ea54820e2d98d3f51f91e97e358fc13359721233e4b"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:705f03cee0cb797256d54de6695ef219e5bc8c8120b6654dd460848d57a9af3d"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03246774131701de8e7059b2e382597da43144a9a7400f178b2a32feafc54bd5"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8b5759063a6c940a69c728ea70d7c33583991c6982915a839c8da5f957e0103a"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:677f23e32491520eebb19c99bb34675daf5410c449c13416f7f0d93e2cf5f981"}, - {file = "orjson-3.10.11-cp311-none-win32.whl", hash = "sha256:a11225d7b30468dcb099498296ffac36b4673a8398ca30fdaec1e6c20df6aa55"}, - {file = "orjson-3.10.11-cp311-none-win_amd64.whl", hash = "sha256:df8c677df2f9f385fcc85ab859704045fa88d4668bc9991a527c86e710392bec"}, - {file = "orjson-3.10.11-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:360a4e2c0943da7c21505e47cf6bd725588962ff1d739b99b14e2f7f3545ba51"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:496e2cb45de21c369079ef2d662670a4892c81573bcc143c4205cae98282ba97"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7dfa8db55c9792d53c5952900c6a919cfa377b4f4534c7a786484a6a4a350c19"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:51f3382415747e0dbda9dade6f1e1a01a9d37f630d8c9049a8ed0e385b7a90c0"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f35a1b9f50a219f470e0e497ca30b285c9f34948d3c8160d5ad3a755d9299433"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e2f3b7c5803138e67028dde33450e054c87e0703afbe730c105f1fcd873496d5"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f91d9eb554310472bd09f5347950b24442600594c2edc1421403d7610a0998fd"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dfbb2d460a855c9744bbc8e36f9c3a997c4b27d842f3d5559ed54326e6911f9b"}, - {file = "orjson-3.10.11-cp312-none-win32.whl", hash = "sha256:d4a62c49c506d4d73f59514986cadebb7e8d186ad510c518f439176cf8d5359d"}, - {file = "orjson-3.10.11-cp312-none-win_amd64.whl", hash = "sha256:f1eec3421a558ff7a9b010a6c7effcfa0ade65327a71bb9b02a1c3b77a247284"}, - {file = "orjson-3.10.11-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c46294faa4e4d0eb73ab68f1a794d2cbf7bab33b1dda2ac2959ffb7c61591899"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:52e5834d7d6e58a36846e059d00559cb9ed20410664f3ad156cd2cc239a11230"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2fc947e5350fdce548bfc94f434e8760d5cafa97fb9c495d2fef6757aa02ec0"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0efabbf839388a1dab5b72b5d3baedbd6039ac83f3b55736eb9934ea5494d258"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a3f29634260708c200c4fe148e42b4aae97d7b9fee417fbdd74f8cfc265f15b0"}, - {file = "orjson-3.10.11-cp313-none-win32.whl", hash = "sha256:1a1222ffcee8a09476bbdd5d4f6f33d06d0d6642df2a3d78b7a195ca880d669b"}, - {file = "orjson-3.10.11-cp313-none-win_amd64.whl", hash = "sha256:bc274ac261cc69260913b2d1610760e55d3c0801bb3457ba7b9004420b6b4270"}, - {file = "orjson-3.10.11-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:19b3763e8bbf8ad797df6b6b5e0fc7c843ec2e2fc0621398534e0c6400098f87"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1be83a13312e5e58d633580c5eb8d0495ae61f180da2722f20562974188af205"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:afacfd1ab81f46dedd7f6001b6d4e8de23396e4884cd3c3436bd05defb1a6446"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb4d0bea56bba596723d73f074c420aec3b2e5d7d30698bc56e6048066bd560c"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96ed1de70fcb15d5fed529a656df29f768187628727ee2788344e8a51e1c1350"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4bfb30c891b530f3f80e801e3ad82ef150b964e5c38e1fb8482441c69c35c61c"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:d496c74fc2b61341e3cefda7eec21b7854c5f672ee350bc55d9a4997a8a95204"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:655a493bac606655db9a47fe94d3d84fc7f3ad766d894197c94ccf0c5408e7d3"}, - {file = "orjson-3.10.11-cp38-none-win32.whl", hash = "sha256:b9546b278c9fb5d45380f4809e11b4dd9844ca7aaf1134024503e134ed226161"}, - {file = "orjson-3.10.11-cp38-none-win_amd64.whl", hash = "sha256:b592597fe551d518f42c5a2eb07422eb475aa8cfdc8c51e6da7054b836b26782"}, - {file = "orjson-3.10.11-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c95f2ecafe709b4e5c733b5e2768ac569bed308623c85806c395d9cca00e08af"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:80c00d4acded0c51c98754fe8218cb49cb854f0f7eb39ea4641b7f71732d2cb7"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:461311b693d3d0a060439aa669c74f3603264d4e7a08faa68c47ae5a863f352d"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52ca832f17d86a78cbab86cdc25f8c13756ebe182b6fc1a97d534051c18a08de"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c57ea78a753812f528178aa2f1c57da633754c91d2124cb28991dab4c79a54"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7fcfc6f7ca046383fb954ba528587e0f9336828b568282b27579c49f8e16aad"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:86b9dd983857970c29e4c71bb3e95ff085c07d3e83e7c46ebe959bac07ebd80b"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:4d83f87582d223e54efb2242a79547611ba4ebae3af8bae1e80fa9a0af83bb7f"}, - {file = "orjson-3.10.11-cp39-none-win32.whl", hash = "sha256:9fd0ad1c129bc9beb1154c2655f177620b5beaf9a11e0d10bac63ef3fce96950"}, - {file = "orjson-3.10.11-cp39-none-win_amd64.whl", hash = "sha256:10f416b2a017c8bd17f325fb9dee1fb5cdd7a54e814284896b7c3f2763faa017"}, - {file = "orjson-3.10.11.tar.gz", hash = "sha256:e35b6d730de6384d5b2dab5fd23f0d76fae8bbc8c353c2f78210aa5fa4beb3ef"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] @@ -881,22 +909,19 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.2" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.2-py3-none-any.whl", hash = "sha256:cfb96e45951117c3024e6b67b25cdc33a3cb7b2fa62e239f7af1378358a1d99e"}, + {file = "pydantic-2.10.2.tar.gz", hash = "sha256:2bc2d7f17232e0841cbba4641e65ba1eb6fafb3a08de3a091ff3ce14a197c4fa"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -904,100 +929,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -1372,13 +1408,13 @@ files = [ [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -1448,47 +1484,94 @@ blobfile = ["blobfile (>=2)"] [[package]] name = "tomli" -version = "2.1.0" +version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, - {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"}, + {file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"}, + {file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"}, + {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"}, + {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"}, + {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"}, + {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"}, + {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"}, + {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"}, ] [[package]] name = "tqdm" -version = "4.67.0" +version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = false python-versions = ">=3.7" files = [ - {file = "tqdm-4.67.0-py3-none-any.whl", hash = "sha256:0cd8af9d56911acab92182e88d763100d4788bdf421d251616040cc4d44863be"}, - {file = "tqdm-4.67.0.tar.gz", hash = "sha256:fe5a6f95e6fe0b9755e9469b77b9c3cf850048224ecaa8293d7d2d31f97d869a"}, + {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, + {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, ] [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} [package.extras] -dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"] +dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"] discord = ["requests"] notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] telegram = ["requests"] +[[package]] +name = "types-requests" +version = "2.32.0.20241016" +description = "Typing stubs for requests" +optional = false +python-versions = ">=3.8" +files = [ + {file = "types-requests-2.32.0.20241016.tar.gz", hash = "sha256:0d9cad2f27515d0e3e3da7134a1b6f28fb97129d86b867f24d9c726452634d95"}, + {file = "types_requests-2.32.0.20241016-py3-none-any.whl", hash = "sha256:4195d62d6d3e043a4eaaf08ff8a62184584d2e8684e9d2aa178c7915a7da3747"}, +] + +[package.dependencies] +urllib3 = ">=2" + [[package]] name = "types-tqdm" -version = "4.66.0.20240417" +version = "4.67.0.20241119" description = "Typing stubs for tqdm" optional = false python-versions = ">=3.8" files = [ - {file = "types-tqdm-4.66.0.20240417.tar.gz", hash = "sha256:16dce9ef522ea8d40e4f5b8d84dd8a1166eefc13ceee7a7e158bf0f1a1421a31"}, - {file = "types_tqdm-4.66.0.20240417-py3-none-any.whl", hash = "sha256:248aef1f9986b7b8c2c12b3cb4399fc17dba0a29e7e3f3f9cd704babb879383d"}, + {file = "types-tqdm-4.67.0.20241119.tar.gz", hash = "sha256:1769e0e94d5e6d8fa814965f9cf3d9928376dd15dabcbcb784bb8769081092b4"}, + {file = "types_tqdm-4.67.0.20241119-py3-none-any.whl", hash = "sha256:a18d4eb62db0d35c52707ae13d821b5a57970755273ecb56e133ccc0ac7e7c79"}, ] +[package.dependencies] +types-requests = "*" + [[package]] name = "typing-extensions" version = "4.12.2" @@ -1562,4 +1645,4 @@ watchmedo = ["PyYAML (>=3.10)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "79ff1e8bd2a97aefd574186299e51f9e2487ee51bcde1e199d6e786c3fdde8ea" +content-hash = "6fb8c9f98c76ba402d53234ac2ac78bcebafbe818e64cd849e0ae26cafcd5ba4" diff --git a/libs/partners/openai/pyproject.toml b/libs/partners/openai/pyproject.toml index 744812533a7eb..a85ab72b05f51 100644 --- a/libs/partners/openai/pyproject.toml +++ b/libs/partners/openai/pyproject.toml @@ -1,10 +1,10 @@ [build-system] -requires = ["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-openai" -version = "0.2.9" +version = "0.2.12" description = "An integration package connecting OpenAI and LangChain" authors = [] readme = "README.md" @@ -23,31 +23,25 @@ ignore_missing_imports = true [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.17" -openai = "^1.54.0" +langchain-core = "^0.3.21" +openai = "^1.55.3" tiktoken = ">=0.7,<1" [tool.ruff.lint] -select = ["E", "F", "I", "T201"] +select = [ "E", "F", "I", "T201",] [tool.ruff.format] docstring-code-format = true skip-magic-trailing-comma = true [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5 --cov=langchain_openai" -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", - "scheduled: mark tests to run in scheduled testing", -] +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them", "scheduled: mark tests to run in scheduled testing",] asyncio_mode = "auto" -filterwarnings = [ - "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", -] +filterwarnings = [ "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning",] [tool.poetry.group.test] optional = true diff --git a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py index cbee0d7041850..1204ccef87c4e 100644 --- a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py +++ b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py @@ -44,7 +44,7 @@ def test_chat_openai() -> None: max_retries=3, http_client=None, n=1, - max_tokens=10, + max_completion_tokens=10, default_headers=None, default_query=None, ) @@ -64,7 +64,7 @@ def test_chat_openai_model() -> None: def test_chat_openai_system_message() -> None: """Test ChatOpenAI wrapper with system message.""" - chat = ChatOpenAI(max_tokens=10) + chat = ChatOpenAI(max_completion_tokens=10) system_message = SystemMessage(content="You are to chat with the user.") human_message = HumanMessage(content="Hello") response = chat.invoke([system_message, human_message]) @@ -75,7 +75,7 @@ def test_chat_openai_system_message() -> None: @pytest.mark.scheduled def test_chat_openai_generate() -> None: """Test ChatOpenAI wrapper with generate.""" - chat = ChatOpenAI(max_tokens=10, n=2) + chat = ChatOpenAI(max_completion_tokens=10, n=2) message = HumanMessage(content="Hello") response = chat.generate([[message], [message]]) assert isinstance(response, LLMResult) @@ -92,7 +92,7 @@ def test_chat_openai_generate() -> None: @pytest.mark.scheduled def test_chat_openai_multiple_completions() -> None: """Test ChatOpenAI wrapper with multiple completions.""" - chat = ChatOpenAI(max_tokens=10, n=5) + chat = ChatOpenAI(max_completion_tokens=10, n=5) message = HumanMessage(content="Hello") response = chat._generate([message]) assert isinstance(response, ChatResult) @@ -108,7 +108,7 @@ def test_chat_openai_streaming() -> None: callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) chat = ChatOpenAI( - max_tokens=10, + max_completion_tokens=10, streaming=True, temperature=0, callback_manager=callback_manager, @@ -133,7 +133,9 @@ def on_llm_end(self, *args: Any, **kwargs: Any) -> Any: callback = _FakeCallback() callback_manager = CallbackManager([callback]) - chat = ChatOpenAI(max_tokens=2, temperature=0, callback_manager=callback_manager) + chat = ChatOpenAI( + max_completion_tokens=2, temperature=0, callback_manager=callback_manager + ) list(chat.stream("hi")) generation = callback.saved_things["generation"] # `Hello!` is two tokens, assert that that is what is returned @@ -142,7 +144,7 @@ def on_llm_end(self, *args: Any, **kwargs: Any) -> Any: def test_chat_openai_llm_output_contains_model_name() -> None: """Test llm_output contains model_name.""" - chat = ChatOpenAI(max_tokens=10) + chat = ChatOpenAI(max_completion_tokens=10) message = HumanMessage(content="Hello") llm_result = chat.generate([[message]]) assert llm_result.llm_output is not None @@ -151,7 +153,7 @@ def test_chat_openai_llm_output_contains_model_name() -> None: def test_chat_openai_streaming_llm_output_contains_model_name() -> None: """Test llm_output contains model_name.""" - chat = ChatOpenAI(max_tokens=10, streaming=True) + chat = ChatOpenAI(max_completion_tokens=10, streaming=True) message = HumanMessage(content="Hello") llm_result = chat.generate([[message]]) assert llm_result.llm_output is not None @@ -161,13 +163,13 @@ def test_chat_openai_streaming_llm_output_contains_model_name() -> None: def test_chat_openai_invalid_streaming_params() -> None: """Test that streaming correctly invokes on_llm_new_token callback.""" with pytest.raises(ValueError): - ChatOpenAI(max_tokens=10, streaming=True, temperature=0, n=5) + ChatOpenAI(max_completion_tokens=10, streaming=True, temperature=0, n=5) @pytest.mark.scheduled async def test_async_chat_openai() -> None: """Test async generation.""" - chat = ChatOpenAI(max_tokens=10, n=2) + chat = ChatOpenAI(max_completion_tokens=10, n=2) message = HumanMessage(content="Hello") response = await chat.agenerate([[message], [message]]) assert isinstance(response, LLMResult) @@ -187,7 +189,7 @@ async def test_async_chat_openai_streaming() -> None: callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) chat = ChatOpenAI( - max_tokens=10, + max_completion_tokens=10, streaming=True, temperature=0, callback_manager=callback_manager, @@ -219,7 +221,7 @@ class Person(BaseModel): default=None, title="Fav Food", description="The person's favorite food" ) - chat = ChatOpenAI(max_tokens=30, n=1, streaming=True).bind_functions( + chat = ChatOpenAI(max_completion_tokens=30, n=1, streaming=True).bind_functions( functions=[Person], function_call="Person" ) @@ -241,7 +243,7 @@ class Person(BaseModel): @pytest.mark.scheduled def test_openai_streaming() -> None: """Test streaming tokens from OpenAI.""" - llm = ChatOpenAI(max_tokens=10) + llm = ChatOpenAI(max_completion_tokens=10) for token in llm.stream("I'm Pickle Rick"): assert isinstance(token.content, str) @@ -250,7 +252,7 @@ def test_openai_streaming() -> None: @pytest.mark.scheduled async def test_openai_astream() -> None: """Test streaming tokens from OpenAI.""" - llm = ChatOpenAI(max_tokens=10) + llm = ChatOpenAI(max_completion_tokens=10) async for token in llm.astream("I'm Pickle Rick"): assert isinstance(token.content, str) @@ -259,7 +261,7 @@ async def test_openai_astream() -> None: @pytest.mark.scheduled async def test_openai_abatch() -> None: """Test streaming tokens from ChatOpenAI.""" - llm = ChatOpenAI(max_tokens=10) + llm = ChatOpenAI(max_completion_tokens=10) result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) for token in result: @@ -269,7 +271,7 @@ async def test_openai_abatch() -> None: @pytest.mark.scheduled async def test_openai_abatch_tags() -> None: """Test batch tokens from ChatOpenAI.""" - llm = ChatOpenAI(max_tokens=10) + llm = ChatOpenAI(max_completion_tokens=10) result = await llm.abatch( ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]} @@ -281,7 +283,7 @@ async def test_openai_abatch_tags() -> None: @pytest.mark.scheduled def test_openai_batch() -> None: """Test batch tokens from ChatOpenAI.""" - llm = ChatOpenAI(max_tokens=10) + llm = ChatOpenAI(max_completion_tokens=10) result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) for token in result: @@ -291,7 +293,7 @@ def test_openai_batch() -> None: @pytest.mark.scheduled async def test_openai_ainvoke() -> None: """Test invoke tokens from ChatOpenAI.""" - llm = ChatOpenAI(max_tokens=10) + llm = ChatOpenAI(max_completion_tokens=10) result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) assert isinstance(result.content, str) @@ -300,7 +302,7 @@ async def test_openai_ainvoke() -> None: @pytest.mark.scheduled def test_openai_invoke() -> None: """Test invoke tokens from ChatOpenAI.""" - llm = ChatOpenAI(max_tokens=10) + llm = ChatOpenAI(max_completion_tokens=10) result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) assert isinstance(result.content, str) @@ -385,7 +387,7 @@ async def _test_stream(stream: AsyncIterator, expect_usage: bool) -> None: assert chunks_with_token_counts == 0 assert full.usage_metadata is None - llm = ChatOpenAI(temperature=0, max_tokens=5) + llm = ChatOpenAI(temperature=0, max_completion_tokens=5) await _test_stream(llm.astream("Hello"), expect_usage=False) await _test_stream( llm.astream("Hello", stream_options={"include_usage": True}), expect_usage=True @@ -393,7 +395,7 @@ async def _test_stream(stream: AsyncIterator, expect_usage: bool) -> None: await _test_stream(llm.astream("Hello", stream_usage=True), expect_usage=True) llm = ChatOpenAI( temperature=0, - max_tokens=5, + max_completion_tokens=5, model_kwargs={"stream_options": {"include_usage": True}}, ) await _test_stream(llm.astream("Hello"), expect_usage=True) @@ -401,7 +403,7 @@ async def _test_stream(stream: AsyncIterator, expect_usage: bool) -> None: llm.astream("Hello", stream_options={"include_usage": False}), expect_usage=False, ) - llm = ChatOpenAI(temperature=0, max_tokens=5, stream_usage=True) + llm = ChatOpenAI(temperature=0, max_completion_tokens=5, stream_usage=True) await _test_stream(llm.astream("Hello"), expect_usage=True) await _test_stream(llm.astream("Hello", stream_usage=False), expect_usage=False) @@ -666,7 +668,7 @@ def test_openai_response_headers() -> None: """Test ChatOpenAI response headers.""" chat_openai = ChatOpenAI(include_response_headers=True) query = "I'm Pickle Rick" - result = chat_openai.invoke(query, max_tokens=10) + result = chat_openai.invoke(query, max_completion_tokens=10) headers = result.response_metadata["headers"] assert headers assert isinstance(headers, dict) @@ -674,7 +676,7 @@ def test_openai_response_headers() -> None: # Stream full: Optional[BaseMessageChunk] = None - for chunk in chat_openai.stream(query, max_tokens=10): + for chunk in chat_openai.stream(query, max_completion_tokens=10): full = chunk if full is None else full + chunk assert isinstance(full, AIMessage) headers = full.response_metadata["headers"] @@ -687,7 +689,7 @@ async def test_openai_response_headers_async() -> None: """Test ChatOpenAI response headers.""" chat_openai = ChatOpenAI(include_response_headers=True) query = "I'm Pickle Rick" - result = await chat_openai.ainvoke(query, max_tokens=10) + result = await chat_openai.ainvoke(query, max_completion_tokens=10) headers = result.response_metadata["headers"] assert headers assert isinstance(headers, dict) @@ -695,7 +697,7 @@ async def test_openai_response_headers_async() -> None: # Stream full: Optional[BaseMessageChunk] = None - async for chunk in chat_openai.astream(query, max_tokens=10): + async for chunk in chat_openai.astream(query, max_completion_tokens=10): full = chunk if full is None else full + chunk assert isinstance(full, AIMessage) headers = full.response_metadata["headers"] @@ -1085,3 +1087,13 @@ async def test_astream_response_format() -> None: "how are ya", response_format=Foo ): pass + + +def test_o1_max_tokens() -> None: + response = ChatOpenAI(model="o1-mini", max_tokens=10).invoke("how are you") # type: ignore[call-arg] + assert isinstance(response, AIMessage) + + response = ChatOpenAI(model="gpt-4o", max_completion_tokens=10).invoke( + "how are you" + ) + assert isinstance(response, AIMessage) diff --git a/libs/partners/openai/tests/integration_tests/embeddings/test_base_standard.py b/libs/partners/openai/tests/integration_tests/embeddings/test_base_standard.py new file mode 100644 index 0000000000000..66f74f1687fd5 --- /dev/null +++ b/libs/partners/openai/tests/integration_tests/embeddings/test_base_standard.py @@ -0,0 +1,18 @@ +"""Standard LangChain interface tests""" + +from typing import Type + +from langchain_core.embeddings import Embeddings +from langchain_tests.integration_tests.embeddings import EmbeddingsIntegrationTests + +from langchain_openai import OpenAIEmbeddings + + +class TestOpenAIStandard(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[Embeddings]: + return OpenAIEmbeddings + + @property + def embedding_model_params(self) -> dict: + return {"model": "text-embedding-3-small", "dimensions": 128} diff --git a/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py b/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py index 3d1faa97db485..f74f1c6804f3a 100644 --- a/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py +++ b/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py @@ -4,6 +4,7 @@ import pytest from langchain_core.language_models import BaseChatModel +from langchain_core.tools import BaseTool from langchain_tests.unit_tests import ChatModelUnitTests from langchain_openai import AzureChatOpenAI @@ -23,8 +24,10 @@ def chat_model_params(self) -> dict: } @pytest.mark.xfail(reason="AzureOpenAI does not support tool_choice='any'") - def test_bind_tool_pydantic(self, model: BaseChatModel) -> None: - super().test_bind_tool_pydantic(model) + def test_bind_tool_pydantic( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_bind_tool_pydantic(model, my_adder_tool) @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: diff --git a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py index b97819e218888..aea480a748177 100644 --- a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py +++ b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py @@ -36,6 +36,11 @@ def test_openai_model_param() -> None: llm = ChatOpenAI(model_name="foo") # type: ignore[call-arg] assert llm.model_name == "foo" + llm = ChatOpenAI(max_tokens=10) # type: ignore[call-arg] + assert llm.max_tokens == 10 + llm = ChatOpenAI(max_completion_tokens=10) + assert llm.max_tokens == 10 + def test_openai_o1_temperature() -> None: llm = ChatOpenAI(model="o1-preview") diff --git a/libs/partners/pinecone/langchain_pinecone/embeddings.py b/libs/partners/pinecone/langchain_pinecone/embeddings.py index 2dc964ed562b8..d3cdd73fe7d9b 100644 --- a/libs/partners/pinecone/langchain_pinecone/embeddings.py +++ b/libs/partners/pinecone/langchain_pinecone/embeddings.py @@ -33,7 +33,7 @@ class PineconeEmbeddings(BaseModel, Embeddings): # Clients _client: PineconeClient = PrivateAttr(default=None) - _async_client: aiohttp.ClientSession = PrivateAttr(default=None) + _async_client: Optional[aiohttp.ClientSession] = PrivateAttr(default=None) model: str """Model to use for example 'multilingual-e5-large'.""" # Config @@ -65,6 +65,19 @@ class PineconeEmbeddings(BaseModel, Embeddings): protected_namespaces=(), ) + @property + def async_client(self) -> aiohttp.ClientSession: + """Lazily initialize the async client.""" + if self._async_client is None: + self._async_client = aiohttp.ClientSession( + headers={ + "Api-Key": self.pinecone_api_key.get_secret_value(), + "Content-Type": "application/json", + "X-Pinecone-API-Version": "2024-10", + } + ) + return self._async_client + @model_validator(mode="before") @classmethod def set_default_config(cls, values: dict) -> Any: @@ -92,15 +105,8 @@ def validate_environment(self) -> Self: client = PineconeClient(api_key=api_key_str, source_tag="langchain") self._client = client - # initialize async client - if not self._async_client: - self._async_client = aiohttp.ClientSession( - headers={ - "Api-Key": api_key_str, - "Content-Type": "application/json", - "X-Pinecone-API-Version": "2024-07", - } - ) + # Ensure async_client is lazily initialized + _ = self.async_client return self def _get_batch_iterator(self, texts: List[str]) -> Iterable: @@ -174,7 +180,7 @@ async def _aembed_texts( "inputs": [{"text": text} for text in texts], "parameters": parameters, } - async with self._async_client.post( + async with self.async_client.post( "https://api.pinecone.io/embed", json=data ) as response: response_data = await response.json(content_type=None) diff --git a/libs/partners/pinecone/langchain_pinecone/vectorstores.py b/libs/partners/pinecone/langchain_pinecone/vectorstores.py index 9dacbd2488f71..2e98afad7c454 100644 --- a/libs/partners/pinecone/langchain_pinecone/vectorstores.py +++ b/libs/partners/pinecone/langchain_pinecone/vectorstores.py @@ -74,6 +74,7 @@ class PineconeVectorStore(VectorStore): dimension=1536, metric="cosine", spec=ServerlessSpec(cloud="aws", region="us-east-1"), + deletion_protection="enabled", # Defaults to "disabled" ) while not pc.describe_index(index_name).status["ready"]: time.sleep(1) diff --git a/libs/partners/pinecone/poetry.lock b/libs/partners/pinecone/poetry.lock index a169779e0f698..3122fd088d064 100644 --- a/libs/partners/pinecone/poetry.lock +++ b/libs/partners/pinecone/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. [[package]] name = "aiohttp" @@ -123,13 +123,13 @@ files = [ [[package]] name = "anyio" -version = "4.4.0" +version = "4.6.2.post1" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"}, - {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"}, + {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"}, + {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"}, ] [package.dependencies] @@ -139,9 +139,9 @@ sniffio = ">=1.1" typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} [package.extras] -doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] -trio = ["trio (>=0.23)"] +doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"] +trio = ["trio (>=0.26.1)"] [[package]] name = "async-timeout" @@ -186,101 +186,116 @@ files = [ [[package]] name = "charset-normalizer" -version = "3.3.2" +version = "3.4.0" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." optional = false python-versions = ">=3.7.0" files = [ - {file = "charset-normalizer-3.3.2.tar.gz", hash = "sha256:f30c3cb33b24454a82faecaf01b19c18562b1e89558fb6c56de4d9118a032fd5"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:25baf083bf6f6b341f4121c2f3c548875ee6f5339300e08be3f2b2ba1721cdd3"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:06435b539f889b1f6f4ac1758871aae42dc3a8c0e24ac9e60c2384973ad73027"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9063e24fdb1e498ab71cb7419e24622516c4a04476b17a2dab57e8baa30d6e03"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6897af51655e3691ff853668779c7bad41579facacf5fd7253b0133308cf000d"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1d3193f4a680c64b4b6a9115943538edb896edc190f0b222e73761716519268e"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cd70574b12bb8a4d2aaa0094515df2463cb429d8536cfb6c7ce983246983e5a6"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8465322196c8b4d7ab6d1e049e4c5cb460d0394da4a27d23cc242fbf0034b6b5"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a9a8e9031d613fd2009c182b69c7b2c1ef8239a0efb1df3f7c8da66d5dd3d537"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:beb58fe5cdb101e3a055192ac291b7a21e3b7ef4f67fa1d74e331a7f2124341c"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:e06ed3eb3218bc64786f7db41917d4e686cc4856944f53d5bdf83a6884432e12"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:2e81c7b9c8979ce92ed306c249d46894776a909505d8f5a4ba55b14206e3222f"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:572c3763a264ba47b3cf708a44ce965d98555f618ca42c926a9c1616d8f34269"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-win32.whl", hash = "sha256:3d47fa203a7bd9c5b6cee4736ee84ca03b8ef23193c0d1ca99b5089f72645c73"}, - {file = "charset_normalizer-3.3.2-cp310-cp310-win_amd64.whl", hash = "sha256:10955842570876604d404661fbccbc9c7e684caf432c09c715ec38fbae45ae09"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:802fe99cca7457642125a8a88a084cef28ff0cf9407060f7b93dca5aa25480db"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:573f6eac48f4769d667c4442081b1794f52919e7edada77495aaed9236d13a96"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:549a3a73da901d5bc3ce8d24e0600d1fa85524c10287f6004fbab87672bf3e1e"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f27273b60488abe721a075bcca6d7f3964f9f6f067c8c4c605743023d7d3944f"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ceae2f17a9c33cb48e3263960dc5fc8005351ee19db217e9b1bb15d28c02574"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:65f6f63034100ead094b8744b3b97965785388f308a64cf8d7c34f2f2e5be0c4"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:753f10e867343b4511128c6ed8c82f7bec3bd026875576dfd88483c5c73b2fd8"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4a78b2b446bd7c934f5dcedc588903fb2f5eec172f3d29e52a9096a43722adfc"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:e537484df0d8f426ce2afb2d0f8e1c3d0b114b83f8850e5f2fbea0e797bd82ae"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:eb6904c354526e758fda7167b33005998fb68c46fbc10e013ca97f21ca5c8887"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:deb6be0ac38ece9ba87dea880e438f25ca3eddfac8b002a2ec3d9183a454e8ae"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:4ab2fe47fae9e0f9dee8c04187ce5d09f48eabe611be8259444906793ab7cbce"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:80402cd6ee291dcb72644d6eac93785fe2c8b9cb30893c1af5b8fdd753b9d40f"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-win32.whl", hash = "sha256:7cd13a2e3ddeed6913a65e66e94b51d80a041145a026c27e6bb76c31a853c6ab"}, - {file = "charset_normalizer-3.3.2-cp311-cp311-win_amd64.whl", hash = "sha256:663946639d296df6a2bb2aa51b60a2454ca1cb29835324c640dafb5ff2131a77"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:0b2b64d2bb6d3fb9112bafa732def486049e63de9618b5843bcdd081d8144cd8"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:ddbb2551d7e0102e7252db79ba445cdab71b26640817ab1e3e3648dad515003b"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:55086ee1064215781fff39a1af09518bc9255b50d6333f2e4c74ca09fac6a8f6"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8f4a014bc36d3c57402e2977dada34f9c12300af536839dc38c0beab8878f38a"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a10af20b82360ab00827f916a6058451b723b4e65030c5a18577c8b2de5b3389"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8d756e44e94489e49571086ef83b2bb8ce311e730092d2c34ca8f7d925cb20aa"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:90d558489962fd4918143277a773316e56c72da56ec7aa3dc3dbbe20fdfed15b"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6ac7ffc7ad6d040517be39eb591cac5ff87416c2537df6ba3cba3bae290c0fed"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:7ed9e526742851e8d5cc9e6cf41427dfc6068d4f5a3bb03659444b4cabf6bc26"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:8bdb58ff7ba23002a4c5808d608e4e6c687175724f54a5dade5fa8c67b604e4d"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:6b3251890fff30ee142c44144871185dbe13b11bab478a88887a639655be1068"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_s390x.whl", hash = "sha256:b4a23f61ce87adf89be746c8a8974fe1c823c891d8f86eb218bb957c924bb143"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:efcb3f6676480691518c177e3b465bcddf57cea040302f9f4e6e191af91174d4"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-win32.whl", hash = "sha256:d965bba47ddeec8cd560687584e88cf699fd28f192ceb452d1d7ee807c5597b7"}, - {file = "charset_normalizer-3.3.2-cp312-cp312-win_amd64.whl", hash = "sha256:96b02a3dc4381e5494fad39be677abcb5e6634bf7b4fa83a6dd3112607547001"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:95f2a5796329323b8f0512e09dbb7a1860c46a39da62ecb2324f116fa8fdc85c"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c002b4ffc0be611f0d9da932eb0f704fe2602a9a949d1f738e4c34c75b0863d5"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a981a536974bbc7a512cf44ed14938cf01030a99e9b3a06dd59578882f06f985"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3287761bc4ee9e33561a7e058c72ac0938c4f57fe49a09eae428fd88aafe7bb6"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:42cb296636fcc8b0644486d15c12376cb9fa75443e00fb25de0b8602e64c1714"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0a55554a2fa0d408816b3b5cedf0045f4b8e1a6065aec45849de2d6f3f8e9786"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:c083af607d2515612056a31f0a8d9e0fcb5876b7bfc0abad3ecd275bc4ebc2d5"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:87d1351268731db79e0f8e745d92493ee2841c974128ef629dc518b937d9194c"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:bd8f7df7d12c2db9fab40bdd87a7c09b1530128315d047a086fa3ae3435cb3a8"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:c180f51afb394e165eafe4ac2936a14bee3eb10debc9d9e4db8958fe36afe711"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:8c622a5fe39a48f78944a87d4fb8a53ee07344641b0562c540d840748571b811"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-win32.whl", hash = "sha256:db364eca23f876da6f9e16c9da0df51aa4f104a972735574842618b8c6d999d4"}, - {file = "charset_normalizer-3.3.2-cp37-cp37m-win_amd64.whl", hash = "sha256:86216b5cee4b06df986d214f664305142d9c76df9b6512be2738aa72a2048f99"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:6463effa3186ea09411d50efc7d85360b38d5f09b870c48e4600f63af490e56a"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:6c4caeef8fa63d06bd437cd4bdcf3ffefe6738fb1b25951440d80dc7df8c03ac"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:37e55c8e51c236f95b033f6fb391d7d7970ba5fe7ff453dad675e88cf303377a"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fb69256e180cb6c8a894fee62b3afebae785babc1ee98b81cdf68bbca1987f33"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ae5f4161f18c61806f411a13b0310bea87f987c7d2ecdbdaad0e94eb2e404238"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b2b0a0c0517616b6869869f8c581d4eb2dd83a4d79e0ebcb7d373ef9956aeb0a"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45485e01ff4d3630ec0d9617310448a8702f70e9c01906b0d0118bdf9d124cf2"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:eb00ed941194665c332bf8e078baf037d6c35d7c4f3102ea2d4f16ca94a26dc8"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:2127566c664442652f024c837091890cb1942c30937add288223dc895793f898"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:a50aebfa173e157099939b17f18600f72f84eed3049e743b68ad15bd69b6bf99"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:4d0d1650369165a14e14e1e47b372cfcb31d6ab44e6e33cb2d4e57265290044d"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:923c0c831b7cfcb071580d3f46c4baf50f174be571576556269530f4bbd79d04"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:06a81e93cd441c56a9b65d8e1d043daeb97a3d0856d177d5c90ba85acb3db087"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-win32.whl", hash = "sha256:6ef1d82a3af9d3eecdba2321dc1b3c238245d890843e040e41e470ffa64c3e25"}, - {file = "charset_normalizer-3.3.2-cp38-cp38-win_amd64.whl", hash = "sha256:eb8821e09e916165e160797a6c17edda0679379a4be5c716c260e836e122f54b"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:c235ebd9baae02f1b77bcea61bce332cb4331dc3617d254df3323aa01ab47bd4"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:5b4c145409bef602a690e7cfad0a15a55c13320ff7a3ad7ca59c13bb8ba4d45d"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:68d1f8a9e9e37c1223b656399be5d6b448dea850bed7d0f87a8311f1ff3dabb0"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:22afcb9f253dac0696b5a4be4a1c0f8762f8239e21b99680099abd9b2b1b2269"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e27ad930a842b4c5eb8ac0016b0a54f5aebbe679340c26101df33424142c143c"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1f79682fbe303db92bc2b1136016a38a42e835d932bab5b3b1bfcfbf0640e519"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b261ccdec7821281dade748d088bb6e9b69e6d15b30652b74cbbac25e280b796"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:122c7fa62b130ed55f8f285bfd56d5f4b4a5b503609d181f9ad85e55c89f4185"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:d0eccceffcb53201b5bfebb52600a5fb483a20b61da9dbc885f8b103cbe7598c"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:9f96df6923e21816da7e0ad3fd47dd8f94b2a5ce594e00677c0013018b813458"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:7f04c839ed0b6b98b1a7501a002144b76c18fb1c1850c8b98d458ac269e26ed2"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:34d1c8da1e78d2e001f363791c98a272bb734000fcef47a491c1e3b0505657a8"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-win32.whl", hash = "sha256:aed38f6e4fb3f5d6bf81bfa990a07806be9d83cf7bacef998ab1a9bd660a581f"}, - {file = "charset_normalizer-3.3.2-cp39-cp39-win_amd64.whl", hash = "sha256:b01b88d45a6fcb69667cd6d2f7a9aeb4bf53760d7fc536bf679ec94fe9f3ff3d"}, - {file = "charset_normalizer-3.3.2-py3-none-any.whl", hash = "sha256:3e4d1f6587322d2788836a99c69062fbb091331ec940e02d12d179c1d53e25fc"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:4f9fc98dad6c2eaa32fc3af1417d95b5e3d08aff968df0cd320066def971f9a6"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0de7b687289d3c1b3e8660d0741874abe7888100efe14bd0f9fd7141bcbda92b"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:5ed2e36c3e9b4f21dd9422f6893dec0abf2cca553af509b10cd630f878d3eb99"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40d3ff7fc90b98c637bda91c89d51264a3dcf210cade3a2c6f838c7268d7a4ca"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1110e22af8ca26b90bd6364fe4c763329b0ebf1ee213ba32b68c73de5752323d"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:86f4e8cca779080f66ff4f191a685ced73d2f72d50216f7112185dc02b90b9b7"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f683ddc7eedd742e2889d2bfb96d69573fde1d92fcb811979cdb7165bb9c7d3"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:27623ba66c183eca01bf9ff833875b459cad267aeeb044477fedac35e19ba907"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f606a1881d2663630ea5b8ce2efe2111740df4b687bd78b34a8131baa007f79b"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:0b309d1747110feb25d7ed6b01afdec269c647d382c857ef4663bbe6ad95a912"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:136815f06a3ae311fae551c3df1f998a1ebd01ddd424aa5603a4336997629e95"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:14215b71a762336254351b00ec720a8e85cada43b987da5a042e4ce3e82bd68e"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:79983512b108e4a164b9c8d34de3992f76d48cadc9554c9e60b43f308988aabe"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-win32.whl", hash = "sha256:c94057af19bc953643a33581844649a7fdab902624d2eb739738a30e2b3e60fc"}, + {file = "charset_normalizer-3.4.0-cp310-cp310-win_amd64.whl", hash = "sha256:55f56e2ebd4e3bc50442fbc0888c9d8c94e4e06a933804e2af3e89e2f9c1c749"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:0d99dd8ff461990f12d6e42c7347fd9ab2532fb70e9621ba520f9e8637161d7c"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c57516e58fd17d03ebe67e181a4e4e2ccab1168f8c2976c6a334d4f819fe5944"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:6dba5d19c4dfab08e58d5b36304b3f92f3bd5d42c1a3fa37b5ba5cdf6dfcbcee"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bf4475b82be41b07cc5e5ff94810e6a01f276e37c2d55571e3fe175e467a1a1c"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ce031db0408e487fd2775d745ce30a7cd2923667cf3b69d48d219f1d8f5ddeb6"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8ff4e7cdfdb1ab5698e675ca622e72d58a6fa2a8aa58195de0c0061288e6e3ea"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3710a9751938947e6327ea9f3ea6332a09bf0ba0c09cae9cb1f250bd1f1549bc"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:82357d85de703176b5587dbe6ade8ff67f9f69a41c0733cf2425378b49954de5"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:47334db71978b23ebcf3c0f9f5ee98b8d65992b65c9c4f2d34c2eaf5bcaf0594"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:8ce7fd6767a1cc5a92a639b391891bf1c268b03ec7e021c7d6d902285259685c"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:f1a2f519ae173b5b6a2c9d5fa3116ce16e48b3462c8b96dfdded11055e3d6365"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:63bc5c4ae26e4bc6be6469943b8253c0fd4e4186c43ad46e713ea61a0ba49129"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:bcb4f8ea87d03bc51ad04add8ceaf9b0f085ac045ab4d74e73bbc2dc033f0236"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-win32.whl", hash = "sha256:9ae4ef0b3f6b41bad6366fb0ea4fc1d7ed051528e113a60fa2a65a9abb5b1d99"}, + {file = "charset_normalizer-3.4.0-cp311-cp311-win_amd64.whl", hash = "sha256:cee4373f4d3ad28f1ab6290684d8e2ebdb9e7a1b74fdc39e4c211995f77bec27"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0713f3adb9d03d49d365b70b84775d0a0d18e4ab08d12bc46baa6132ba78aaf6"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:de7376c29d95d6719048c194a9cf1a1b0393fbe8488a22008610b0361d834ecf"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:4a51b48f42d9358460b78725283f04bddaf44a9358197b889657deba38f329db"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b295729485b06c1a0683af02a9e42d2caa9db04a373dc38a6a58cdd1e8abddf1"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ee803480535c44e7f5ad00788526da7d85525cfefaf8acf8ab9a310000be4b03"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3d59d125ffbd6d552765510e3f31ed75ebac2c7470c7274195b9161a32350284"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8cda06946eac330cbe6598f77bb54e690b4ca93f593dee1568ad22b04f347c15"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:07afec21bbbbf8a5cc3651aa96b980afe2526e7f048fdfb7f1014d84acc8b6d8"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6b40e8d38afe634559e398cc32b1472f376a4099c75fe6299ae607e404c033b2"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b8dcd239c743aa2f9c22ce674a145e0a25cb1566c495928440a181ca1ccf6719"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:84450ba661fb96e9fd67629b93d2941c871ca86fc38d835d19d4225ff946a631"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:44aeb140295a2f0659e113b31cfe92c9061622cadbc9e2a2f7b8ef6b1e29ef4b"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:1db4e7fefefd0f548d73e2e2e041f9df5c59e178b4c72fbac4cc6f535cfb1565"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-win32.whl", hash = "sha256:5726cf76c982532c1863fb64d8c6dd0e4c90b6ece9feb06c9f202417a31f7dd7"}, + {file = "charset_normalizer-3.4.0-cp312-cp312-win_amd64.whl", hash = "sha256:b197e7094f232959f8f20541ead1d9862ac5ebea1d58e9849c1bf979255dfac9"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:dd4eda173a9fcccb5f2e2bd2a9f423d180194b1bf17cf59e3269899235b2a114"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:e9e3c4c9e1ed40ea53acf11e2a386383c3304212c965773704e4603d589343ed"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:92a7e36b000bf022ef3dbb9c46bfe2d52c047d5e3f3343f43204263c5addc250"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:54b6a92d009cbe2fb11054ba694bc9e284dad30a26757b1e372a1fdddaf21920"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ffd9493de4c922f2a38c2bf62b831dcec90ac673ed1ca182fe11b4d8e9f2a64"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35c404d74c2926d0287fbd63ed5d27eb911eb9e4a3bb2c6d294f3cfd4a9e0c23"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4796efc4faf6b53a18e3d46343535caed491776a22af773f366534056c4e1fbc"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e7fdd52961feb4c96507aa649550ec2a0d527c086d284749b2f582f2d40a2e0d"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:92db3c28b5b2a273346bebb24857fda45601aef6ae1c011c0a997106581e8a88"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:ab973df98fc99ab39080bfb0eb3a925181454d7c3ac8a1e695fddfae696d9e90"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:4b67fdab07fdd3c10bb21edab3cbfe8cf5696f453afce75d815d9d7223fbe88b"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:aa41e526a5d4a9dfcfbab0716c7e8a1b215abd3f3df5a45cf18a12721d31cb5d"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:ffc519621dce0c767e96b9c53f09c5d215578e10b02c285809f76509a3931482"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-win32.whl", hash = "sha256:f19c1585933c82098c2a520f8ec1227f20e339e33aca8fa6f956f6691b784e67"}, + {file = "charset_normalizer-3.4.0-cp313-cp313-win_amd64.whl", hash = "sha256:707b82d19e65c9bd28b81dde95249b07bf9f5b90ebe1ef17d9b57473f8a64b7b"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:dbe03226baf438ac4fda9e2d0715022fd579cb641c4cf639fa40d53b2fe6f3e2"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dd9a8bd8900e65504a305bf8ae6fa9fbc66de94178c420791d0293702fce2df7"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b8831399554b92b72af5932cdbbd4ddc55c55f631bb13ff8fe4e6536a06c5c51"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a14969b8691f7998e74663b77b4c36c0337cb1df552da83d5c9004a93afdb574"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dcaf7c1524c0542ee2fc82cc8ec337f7a9f7edee2532421ab200d2b920fc97cf"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:425c5f215d0eecee9a56cdb703203dda90423247421bf0d67125add85d0c4455"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:d5b054862739d276e09928de37c79ddeec42a6e1bfc55863be96a36ba22926f6"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-musllinux_1_2_i686.whl", hash = "sha256:f3e73a4255342d4eb26ef6df01e3962e73aa29baa3124a8e824c5d3364a65748"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-musllinux_1_2_ppc64le.whl", hash = "sha256:2f6c34da58ea9c1a9515621f4d9ac379871a8f21168ba1b5e09d74250de5ad62"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-musllinux_1_2_s390x.whl", hash = "sha256:f09cb5a7bbe1ecae6e87901a2eb23e0256bb524a79ccc53eb0b7629fbe7677c4"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:0099d79bdfcf5c1f0c2c72f91516702ebf8b0b8ddd8905f97a8aecf49712c621"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-win32.whl", hash = "sha256:9c98230f5042f4945f957d006edccc2af1e03ed5e37ce7c373f00a5a4daa6149"}, + {file = "charset_normalizer-3.4.0-cp37-cp37m-win_amd64.whl", hash = "sha256:62f60aebecfc7f4b82e3f639a7d1433a20ec32824db2199a11ad4f5e146ef5ee"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:af73657b7a68211996527dbfeffbb0864e043d270580c5aef06dc4b659a4b578"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:cab5d0b79d987c67f3b9e9c53f54a61360422a5a0bc075f43cab5621d530c3b6"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:9289fd5dddcf57bab41d044f1756550f9e7cf0c8e373b8cdf0ce8773dc4bd417"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b493a043635eb376e50eedf7818f2f322eabbaa974e948bd8bdd29eb7ef2a51"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9fa2566ca27d67c86569e8c85297aaf413ffab85a8960500f12ea34ff98e4c41"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a8e538f46104c815be19c975572d74afb53f29650ea2025bbfaef359d2de2f7f"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6fd30dc99682dc2c603c2b315bded2799019cea829f8bf57dc6b61efde6611c8"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2006769bd1640bdf4d5641c69a3d63b71b81445473cac5ded39740a226fa88ab"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:dc15e99b2d8a656f8e666854404f1ba54765871104e50c8e9813af8a7db07f12"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:ab2e5bef076f5a235c3774b4f4028a680432cded7cad37bba0fd90d64b187d19"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:4ec9dd88a5b71abfc74e9df5ebe7921c35cbb3b641181a531ca65cdb5e8e4dea"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:43193c5cda5d612f247172016c4bb71251c784d7a4d9314677186a838ad34858"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:aa693779a8b50cd97570e5a0f343538a8dbd3e496fa5dcb87e29406ad0299654"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-win32.whl", hash = "sha256:7706f5850360ac01d80c89bcef1640683cc12ed87f42579dab6c5d3ed6888613"}, + {file = "charset_normalizer-3.4.0-cp38-cp38-win_amd64.whl", hash = "sha256:c3e446d253bd88f6377260d07c895816ebf33ffffd56c1c792b13bff9c3e1ade"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:980b4f289d1d90ca5efcf07958d3eb38ed9c0b7676bf2831a54d4f66f9c27dfa"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f28f891ccd15c514a0981f3b9db9aa23d62fe1a99997512b0491d2ed323d229a"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a8aacce6e2e1edcb6ac625fb0f8c3a9570ccc7bfba1f63419b3769ccf6a00ed0"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd7af3717683bea4c87acd8c0d3d5b44d56120b26fd3f8a692bdd2d5260c620a"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5ff2ed8194587faf56555927b3aa10e6fb69d931e33953943bc4f837dfee2242"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e91f541a85298cf35433bf66f3fab2a4a2cff05c127eeca4af174f6d497f0d4b"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:309a7de0a0ff3040acaebb35ec45d18db4b28232f21998851cfa709eeff49d62"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:285e96d9d53422efc0d7a17c60e59f37fbf3dfa942073f666db4ac71e8d726d0"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5d447056e2ca60382d460a604b6302d8db69476fd2015c81e7c35417cfabe4cd"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:20587d20f557fe189b7947d8e7ec5afa110ccf72a3128d61a2a387c3313f46be"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:130272c698667a982a5d0e626851ceff662565379baf0ff2cc58067b81d4f11d"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:ab22fbd9765e6954bc0bcff24c25ff71dcbfdb185fcdaca49e81bac68fe724d3"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:7782afc9b6b42200f7362858f9e73b1f8316afb276d316336c0ec3bd73312742"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-win32.whl", hash = "sha256:2de62e8801ddfff069cd5c504ce3bc9672b23266597d4e4f50eda28846c322f2"}, + {file = "charset_normalizer-3.4.0-cp39-cp39-win_amd64.whl", hash = "sha256:95c3c157765b031331dd4db3c775e58deaee050a3042fcad72cbc4189d7c8dca"}, + {file = "charset_normalizer-3.4.0-py3-none-any.whl", hash = "sha256:fe9f97feb71aa9896b81973a7bbada8c49501dc73e58a10fcef6663af95e5079"}, + {file = "charset_normalizer-3.4.0.tar.gz", hash = "sha256:223217c3d4f82c3ac5e29032b3f1c2eb0fb591b72161f86d93f5719079dae93e"}, ] [[package]] @@ -352,88 +367,103 @@ python-dateutil = ">=2.7" [[package]] name = "frozenlist" -version = "1.4.1" +version = "1.5.0" description = "A list-like structure which implements collections.abc.MutableSequence" optional = false python-versions = ">=3.8" files = [ - {file = "frozenlist-1.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:f9aa1878d1083b276b0196f2dfbe00c9b7e752475ed3b682025ff20c1c1f51ac"}, - {file = "frozenlist-1.4.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:29acab3f66f0f24674b7dc4736477bcd4bc3ad4b896f5f45379a67bce8b96868"}, - {file = "frozenlist-1.4.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:74fb4bee6880b529a0c6560885fce4dc95936920f9f20f53d99a213f7bf66776"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:590344787a90ae57d62511dd7c736ed56b428f04cd8c161fcc5e7232c130c69a"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:068b63f23b17df8569b7fdca5517edef76171cf3897eb68beb01341131fbd2ad"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5c849d495bf5154cd8da18a9eb15db127d4dba2968d88831aff6f0331ea9bd4c"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9750cc7fe1ae3b1611bb8cfc3f9ec11d532244235d75901fb6b8e42ce9229dfe"}, - {file = "frozenlist-1.4.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a9b2de4cf0cdd5bd2dee4c4f63a653c61d2408055ab77b151c1957f221cabf2a"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:0633c8d5337cb5c77acbccc6357ac49a1770b8c487e5b3505c57b949b4b82e98"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:27657df69e8801be6c3638054e202a135c7f299267f1a55ed3a598934f6c0d75"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:f9a3ea26252bd92f570600098783d1371354d89d5f6b7dfd87359d669f2109b5"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:4f57dab5fe3407b6c0c1cc907ac98e8a189f9e418f3b6e54d65a718aaafe3950"}, - {file = "frozenlist-1.4.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:e02a0e11cf6597299b9f3bbd3f93d79217cb90cfd1411aec33848b13f5c656cc"}, - {file = "frozenlist-1.4.1-cp310-cp310-win32.whl", hash = "sha256:a828c57f00f729620a442881cc60e57cfcec6842ba38e1b19fd3e47ac0ff8dc1"}, - {file = "frozenlist-1.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:f56e2333dda1fe0f909e7cc59f021eba0d2307bc6f012a1ccf2beca6ba362439"}, - {file = "frozenlist-1.4.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:a0cb6f11204443f27a1628b0e460f37fb30f624be6051d490fa7d7e26d4af3d0"}, - {file = "frozenlist-1.4.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b46c8ae3a8f1f41a0d2ef350c0b6e65822d80772fe46b653ab6b6274f61d4a49"}, - {file = "frozenlist-1.4.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:fde5bd59ab5357e3853313127f4d3565fc7dad314a74d7b5d43c22c6a5ed2ced"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:722e1124aec435320ae01ee3ac7bec11a5d47f25d0ed6328f2273d287bc3abb0"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2471c201b70d58a0f0c1f91261542a03d9a5e088ed3dc6c160d614c01649c106"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c757a9dd70d72b076d6f68efdbb9bc943665ae954dad2801b874c8c69e185068"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f146e0911cb2f1da549fc58fc7bcd2b836a44b79ef871980d605ec392ff6b0d2"}, - {file = "frozenlist-1.4.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4f9c515e7914626b2a2e1e311794b4c35720a0be87af52b79ff8e1429fc25f19"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:c302220494f5c1ebeb0912ea782bcd5e2f8308037b3c7553fad0e48ebad6ad82"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:442acde1e068288a4ba7acfe05f5f343e19fac87bfc96d89eb886b0363e977ec"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:1b280e6507ea8a4fa0c0a7150b4e526a8d113989e28eaaef946cc77ffd7efc0a"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:fe1a06da377e3a1062ae5fe0926e12b84eceb8a50b350ddca72dc85015873f74"}, - {file = "frozenlist-1.4.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:db9e724bebd621d9beca794f2a4ff1d26eed5965b004a97f1f1685a173b869c2"}, - {file = "frozenlist-1.4.1-cp311-cp311-win32.whl", hash = "sha256:e774d53b1a477a67838a904131c4b0eef6b3d8a651f8b138b04f748fccfefe17"}, - {file = "frozenlist-1.4.1-cp311-cp311-win_amd64.whl", hash = "sha256:fb3c2db03683b5767dedb5769b8a40ebb47d6f7f45b1b3e3b4b51ec8ad9d9825"}, - {file = "frozenlist-1.4.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:1979bc0aeb89b33b588c51c54ab0161791149f2461ea7c7c946d95d5f93b56ae"}, - {file = "frozenlist-1.4.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:cc7b01b3754ea68a62bd77ce6020afaffb44a590c2289089289363472d13aedb"}, - {file = "frozenlist-1.4.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c9c92be9fd329ac801cc420e08452b70e7aeab94ea4233a4804f0915c14eba9b"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5c3894db91f5a489fc8fa6a9991820f368f0b3cbdb9cd8849547ccfab3392d86"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ba60bb19387e13597fb059f32cd4d59445d7b18b69a745b8f8e5db0346f33480"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8aefbba5f69d42246543407ed2461db31006b0f76c4e32dfd6f42215a2c41d09"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:780d3a35680ced9ce682fbcf4cb9c2bad3136eeff760ab33707b71db84664e3a"}, - {file = "frozenlist-1.4.1-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9acbb16f06fe7f52f441bb6f413ebae6c37baa6ef9edd49cdd567216da8600cd"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:23b701e65c7b36e4bf15546a89279bd4d8675faabc287d06bbcfac7d3c33e1e6"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:3e0153a805a98f5ada7e09826255ba99fb4f7524bb81bf6b47fb702666484ae1"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:dd9b1baec094d91bf36ec729445f7769d0d0cf6b64d04d86e45baf89e2b9059b"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_s390x.whl", hash = "sha256:1a4471094e146b6790f61b98616ab8e44f72661879cc63fa1049d13ef711e71e"}, - {file = "frozenlist-1.4.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:5667ed53d68d91920defdf4035d1cdaa3c3121dc0b113255124bcfada1cfa1b8"}, - {file = "frozenlist-1.4.1-cp312-cp312-win32.whl", hash = "sha256:beee944ae828747fd7cb216a70f120767fc9f4f00bacae8543c14a6831673f89"}, - {file = "frozenlist-1.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:64536573d0a2cb6e625cf309984e2d873979709f2cf22839bf2d61790b448ad5"}, - {file = "frozenlist-1.4.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:20b51fa3f588ff2fe658663db52a41a4f7aa6c04f6201449c6c7c476bd255c0d"}, - {file = "frozenlist-1.4.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:410478a0c562d1a5bcc2f7ea448359fcb050ed48b3c6f6f4f18c313a9bdb1826"}, - {file = "frozenlist-1.4.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:c6321c9efe29975232da3bd0af0ad216800a47e93d763ce64f291917a381b8eb"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:48f6a4533887e189dae092f1cf981f2e3885175f7a0f33c91fb5b7b682b6bab6"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6eb73fa5426ea69ee0e012fb59cdc76a15b1283d6e32e4f8dc4482ec67d1194d"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fbeb989b5cc29e8daf7f976b421c220f1b8c731cbf22b9130d8815418ea45887"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:32453c1de775c889eb4e22f1197fe3bdfe457d16476ea407472b9442e6295f7a"}, - {file = "frozenlist-1.4.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:693945278a31f2086d9bf3df0fe8254bbeaef1fe71e1351c3bd730aa7d31c41b"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:1d0ce09d36d53bbbe566fe296965b23b961764c0bcf3ce2fa45f463745c04701"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:3a670dc61eb0d0eb7080890c13de3066790f9049b47b0de04007090807c776b0"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:dca69045298ce5c11fd539682cff879cc1e664c245d1c64da929813e54241d11"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:a06339f38e9ed3a64e4c4e43aec7f59084033647f908e4259d279a52d3757d09"}, - {file = "frozenlist-1.4.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b7f2f9f912dca3934c1baec2e4585a674ef16fe00218d833856408c48d5beee7"}, - {file = "frozenlist-1.4.1-cp38-cp38-win32.whl", hash = "sha256:e7004be74cbb7d9f34553a5ce5fb08be14fb33bc86f332fb71cbe5216362a497"}, - {file = "frozenlist-1.4.1-cp38-cp38-win_amd64.whl", hash = "sha256:5a7d70357e7cee13f470c7883a063aae5fe209a493c57d86eb7f5a6f910fae09"}, - {file = "frozenlist-1.4.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:bfa4a17e17ce9abf47a74ae02f32d014c5e9404b6d9ac7f729e01562bbee601e"}, - {file = "frozenlist-1.4.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b7e3ed87d4138356775346e6845cccbe66cd9e207f3cd11d2f0b9fd13681359d"}, - {file = "frozenlist-1.4.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c99169d4ff810155ca50b4da3b075cbde79752443117d89429595c2e8e37fed8"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:edb678da49d9f72c9f6c609fbe41a5dfb9a9282f9e6a2253d5a91e0fc382d7c0"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6db4667b187a6742b33afbbaf05a7bc551ffcf1ced0000a571aedbb4aa42fc7b"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:55fdc093b5a3cb41d420884cdaf37a1e74c3c37a31f46e66286d9145d2063bd0"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:82e8211d69a4f4bc360ea22cd6555f8e61a1bd211d1d5d39d3d228b48c83a897"}, - {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89aa2c2eeb20957be2d950b85974b30a01a762f3308cd02bb15e1ad632e22dc7"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:9d3e0c25a2350080e9319724dede4f31f43a6c9779be48021a7f4ebde8b2d742"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:7268252af60904bf52c26173cbadc3a071cece75f873705419c8681f24d3edea"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:0c250a29735d4f15321007fb02865f0e6b6a41a6b88f1f523ca1596ab5f50bd5"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:96ec70beabbd3b10e8bfe52616a13561e58fe84c0101dd031dc78f250d5128b9"}, - {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:23b2d7679b73fe0e5a4560b672a39f98dfc6f60df63823b0a9970525325b95f6"}, - {file = "frozenlist-1.4.1-cp39-cp39-win32.whl", hash = "sha256:a7496bfe1da7fb1a4e1cc23bb67c58fab69311cc7d32b5a99c2007b4b2a0e932"}, - {file = "frozenlist-1.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:e6a20a581f9ce92d389a8c7d7c3dd47c81fd5d6e655c8dddf341e14aa48659d0"}, - {file = "frozenlist-1.4.1-py3-none-any.whl", hash = "sha256:04ced3e6a46b4cfffe20f9ae482818e34eba9b5fb0ce4056e4cc9b6e212d09b7"}, - {file = "frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5b6a66c18b5b9dd261ca98dffcb826a525334b2f29e7caa54e182255c5f6a65a"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1b3eb7b05ea246510b43a7e53ed1653e55c2121019a97e60cad7efb881a97bb"}, + {file = "frozenlist-1.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:15538c0cbf0e4fa11d1e3a71f823524b0c46299aed6e10ebb4c2089abd8c3bec"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e79225373c317ff1e35f210dd5f1344ff31066ba8067c307ab60254cd3a78ad5"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9272fa73ca71266702c4c3e2d4a28553ea03418e591e377a03b8e3659d94fa76"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:498524025a5b8ba81695761d78c8dd7382ac0b052f34e66939c42df860b8ff17"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:92b5278ed9d50fe610185ecd23c55d8b307d75ca18e94c0e7de328089ac5dcba"}, + {file = "frozenlist-1.5.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f3c8c1dacd037df16e85227bac13cca58c30da836c6f936ba1df0c05d046d8d"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f2ac49a9bedb996086057b75bf93538240538c6d9b38e57c82d51f75a73409d2"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e66cc454f97053b79c2ab09c17fbe3c825ea6b4de20baf1be28919460dd7877f"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5a3ba5f9a0dfed20337d3e966dc359784c9f96503674c2faf015f7fe8e96798c"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:6321899477db90bdeb9299ac3627a6a53c7399c8cd58d25da094007402b039ab"}, + {file = "frozenlist-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:76e4753701248476e6286f2ef492af900ea67d9706a0155335a40ea21bf3b2f5"}, + {file = "frozenlist-1.5.0-cp310-cp310-win32.whl", hash = "sha256:977701c081c0241d0955c9586ffdd9ce44f7a7795df39b9151cd9a6fd0ce4cfb"}, + {file = "frozenlist-1.5.0-cp310-cp310-win_amd64.whl", hash = "sha256:189f03b53e64144f90990d29a27ec4f7997d91ed3d01b51fa39d2dbe77540fd4"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:fd74520371c3c4175142d02a976aee0b4cb4a7cc912a60586ffd8d5929979b30"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2f3f7a0fbc219fb4455264cae4d9f01ad41ae6ee8524500f381de64ffaa077d5"}, + {file = "frozenlist-1.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f47c9c9028f55a04ac254346e92977bf0f166c483c74b4232bee19a6697e4778"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0996c66760924da6e88922756d99b47512a71cfd45215f3570bf1e0b694c206a"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a2fe128eb4edeabe11896cb6af88fca5346059f6c8d807e3b910069f39157869"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a8ea951bbb6cacd492e3948b8da8c502a3f814f5d20935aae74b5df2b19cf3d"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de537c11e4aa01d37db0d403b57bd6f0546e71a82347a97c6a9f0dcc532b3a45"}, + {file = "frozenlist-1.5.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c2623347b933fcb9095841f1cc5d4ff0b278addd743e0e966cb3d460278840d"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:cee6798eaf8b1416ef6909b06f7dc04b60755206bddc599f52232606e18179d3"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:f5f9da7f5dbc00a604fe74aa02ae7c98bcede8a3b8b9666f9f86fc13993bc71a"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:90646abbc7a5d5c7c19461d2e3eeb76eb0b204919e6ece342feb6032c9325ae9"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:bdac3c7d9b705d253b2ce370fde941836a5f8b3c5c2b8fd70940a3ea3af7f4f2"}, + {file = "frozenlist-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:03d33c2ddbc1816237a67f66336616416e2bbb6beb306e5f890f2eb22b959cdf"}, + {file = "frozenlist-1.5.0-cp311-cp311-win32.whl", hash = "sha256:237f6b23ee0f44066219dae14c70ae38a63f0440ce6750f868ee08775073f942"}, + {file = "frozenlist-1.5.0-cp311-cp311-win_amd64.whl", hash = "sha256:0cc974cc93d32c42e7b0f6cf242a6bd941c57c61b618e78b6c0a96cb72788c1d"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:31115ba75889723431aa9a4e77d5f398f5cf976eea3bdf61749731f62d4a4a21"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7437601c4d89d070eac8323f121fcf25f88674627505334654fd027b091db09d"}, + {file = "frozenlist-1.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7948140d9f8ece1745be806f2bfdf390127cf1a763b925c4a805c603df5e697e"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:feeb64bc9bcc6b45c6311c9e9b99406660a9c05ca8a5b30d14a78555088b0b3a"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:683173d371daad49cffb8309779e886e59c2f369430ad28fe715f66d08d4ab1a"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7d57d8f702221405a9d9b40f9da8ac2e4a1a8b5285aac6100f3393675f0a85ee"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:30c72000fbcc35b129cb09956836c7d7abf78ab5416595e4857d1cae8d6251a6"}, + {file = "frozenlist-1.5.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:000a77d6034fbad9b6bb880f7ec073027908f1b40254b5d6f26210d2dab1240e"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5d7f5a50342475962eb18b740f3beecc685a15b52c91f7d975257e13e029eca9"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:87f724d055eb4785d9be84e9ebf0f24e392ddfad00b3fe036e43f489fafc9039"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:6e9080bb2fb195a046e5177f10d9d82b8a204c0736a97a153c2466127de87784"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:9b93d7aaa36c966fa42efcaf716e6b3900438632a626fb09c049f6a2f09fc631"}, + {file = "frozenlist-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:52ef692a4bc60a6dd57f507429636c2af8b6046db8b31b18dac02cbc8f507f7f"}, + {file = "frozenlist-1.5.0-cp312-cp312-win32.whl", hash = "sha256:29d94c256679247b33a3dc96cce0f93cbc69c23bf75ff715919332fdbb6a32b8"}, + {file = "frozenlist-1.5.0-cp312-cp312-win_amd64.whl", hash = "sha256:8969190d709e7c48ea386db202d708eb94bdb29207a1f269bab1196ce0dcca1f"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:7a1a048f9215c90973402e26c01d1cff8a209e1f1b53f72b95c13db61b00f953"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:dd47a5181ce5fcb463b5d9e17ecfdb02b678cca31280639255ce9d0e5aa67af0"}, + {file = "frozenlist-1.5.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1431d60b36d15cda188ea222033eec8e0eab488f39a272461f2e6d9e1a8e63c2"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6482a5851f5d72767fbd0e507e80737f9c8646ae7fd303def99bfe813f76cf7f"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:44c49271a937625619e862baacbd037a7ef86dd1ee215afc298a417ff3270608"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:12f78f98c2f1c2429d42e6a485f433722b0061d5c0b0139efa64f396efb5886b"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ce3aa154c452d2467487765e3adc730a8c153af77ad84096bc19ce19a2400840"}, + {file = "frozenlist-1.5.0-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b7dc0c4338e6b8b091e8faf0db3168a37101943e687f373dce00959583f7439"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:45e0896250900b5aa25180f9aec243e84e92ac84bd4a74d9ad4138ef3f5c97de"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:561eb1c9579d495fddb6da8959fd2a1fca2c6d060d4113f5844b433fc02f2641"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:df6e2f325bfee1f49f81aaac97d2aa757c7646534a06f8f577ce184afe2f0a9e"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:140228863501b44b809fb39ec56b5d4071f4d0aa6d216c19cbb08b8c5a7eadb9"}, + {file = "frozenlist-1.5.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7707a25d6a77f5d27ea7dc7d1fc608aa0a478193823f88511ef5e6b8a48f9d03"}, + {file = "frozenlist-1.5.0-cp313-cp313-win32.whl", hash = "sha256:31a9ac2b38ab9b5a8933b693db4939764ad3f299fcaa931a3e605bc3460e693c"}, + {file = "frozenlist-1.5.0-cp313-cp313-win_amd64.whl", hash = "sha256:11aabdd62b8b9c4b84081a3c246506d1cddd2dd93ff0ad53ede5defec7886b28"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:dd94994fc91a6177bfaafd7d9fd951bc8689b0a98168aa26b5f543868548d3ca"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2d0da8bbec082bf6bf18345b180958775363588678f64998c2b7609e34719b10"}, + {file = "frozenlist-1.5.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:73f2e31ea8dd7df61a359b731716018c2be196e5bb3b74ddba107f694fbd7604"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:828afae9f17e6de596825cf4228ff28fbdf6065974e5ac1410cecc22f699d2b3"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f1577515d35ed5649d52ab4319db757bb881ce3b2b796d7283e6634d99ace307"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2150cc6305a2c2ab33299453e2968611dacb970d2283a14955923062c8d00b10"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a72b7a6e3cd2725eff67cd64c8f13335ee18fc3c7befc05aed043d24c7b9ccb9"}, + {file = "frozenlist-1.5.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c16d2fa63e0800723139137d667e1056bee1a1cf7965153d2d104b62855e9b99"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:17dcc32fc7bda7ce5875435003220a457bcfa34ab7924a49a1c19f55b6ee185c"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:97160e245ea33d8609cd2b8fd997c850b56db147a304a262abc2b3be021a9171"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:f1e6540b7fa044eee0bb5111ada694cf3dc15f2b0347ca125ee9ca984d5e9e6e"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:91d6c171862df0a6c61479d9724f22efb6109111017c87567cfeb7b5d1449fdf"}, + {file = "frozenlist-1.5.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c1fac3e2ace2eb1052e9f7c7db480818371134410e1f5c55d65e8f3ac6d1407e"}, + {file = "frozenlist-1.5.0-cp38-cp38-win32.whl", hash = "sha256:b97f7b575ab4a8af9b7bc1d2ef7f29d3afee2226bd03ca3875c16451ad5a7723"}, + {file = "frozenlist-1.5.0-cp38-cp38-win_amd64.whl", hash = "sha256:374ca2dabdccad8e2a76d40b1d037f5bd16824933bf7bcea3e59c891fd4a0923"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:9bbcdfaf4af7ce002694a4e10a0159d5a8d20056a12b05b45cea944a4953f972"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1893f948bf6681733aaccf36c5232c231e3b5166d607c5fa77773611df6dc336"}, + {file = "frozenlist-1.5.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2b5e23253bb709ef57a8e95e6ae48daa9ac5f265637529e4ce6b003a37b2621f"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f253985bb515ecd89629db13cb58d702035ecd8cfbca7d7a7e29a0e6d39af5f"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:04a5c6babd5e8fb7d3c871dc8b321166b80e41b637c31a995ed844a6139942b6"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9fe0f1c29ba24ba6ff6abf688cb0b7cf1efab6b6aa6adc55441773c252f7411"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:226d72559fa19babe2ccd920273e767c96a49b9d3d38badd7c91a0fdeda8ea08"}, + {file = "frozenlist-1.5.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:15b731db116ab3aedec558573c1a5eec78822b32292fe4f2f0345b7f697745c2"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:366d8f93e3edfe5a918c874702f78faac300209a4d5bf38352b2c1bdc07a766d"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:1b96af8c582b94d381a1c1f51ffaedeb77c821c690ea5f01da3d70a487dd0a9b"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:c03eff4a41bd4e38415cbed054bbaff4a075b093e2394b6915dca34a40d1e38b"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:50cf5e7ee9b98f22bdecbabf3800ae78ddcc26e4a435515fc72d97903e8488e0"}, + {file = "frozenlist-1.5.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1e76bfbc72353269c44e0bc2cfe171900fbf7f722ad74c9a7b638052afe6a00c"}, + {file = "frozenlist-1.5.0-cp39-cp39-win32.whl", hash = "sha256:666534d15ba8f0fda3f53969117383d5dc021266b3c1a42c9ec4855e4b58b9d3"}, + {file = "frozenlist-1.5.0-cp39-cp39-win_amd64.whl", hash = "sha256:5c28f4b5dbef8a0d8aad0d4de24d1e9e981728628afaf4ea0792f5d0939372f0"}, + {file = "frozenlist-1.5.0-py3-none-any.whl", hash = "sha256:d994863bba198a4a518b467bb971c56e1db3f180a25c6cf7bb1949c267f748c3"}, + {file = "frozenlist-1.5.0.tar.gz", hash = "sha256:81d5af29e61b9c8348e876d442253723928dce6433e0e76cd925cd83f1b4b817"}, ] [[package]] @@ -449,13 +479,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.5" +version = "1.0.7" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"}, - {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"}, + {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, + {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, ] [package.dependencies] @@ -466,17 +496,17 @@ h11 = ">=0.13,<0.15" asyncio = ["anyio (>=4.0,<5.0)"] http2 = ["h2 (>=3,<5)"] socks = ["socksio (==1.*)"] -trio = ["trio (>=0.22.0,<0.26.0)"] +trio = ["trio (>=0.22.0,<1.0)"] [[package]] name = "httpx" -version = "0.27.2" +version = "0.28.0" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"}, - {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"}, + {file = "httpx-0.28.0-py3-none-any.whl", hash = "sha256:dc0b419a0cfeb6e8b34e85167c0da2671206f5095f1baa9663d23bcfd6b535fc"}, + {file = "httpx-0.28.0.tar.gz", hash = "sha256:0858d3bab51ba7e386637f22a61d8ccddaeec5f3fe4209da3a6168dbb91573e0"}, ] [package.dependencies] @@ -484,7 +514,6 @@ anyio = "*" certifi = "*" httpcore = "==1.*" idna = "*" -sniffio = "*" [package.extras] brotli = ["brotli", "brotlicffi"] @@ -495,15 +524,18 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "idna" -version = "3.8" +version = "3.10" description = "Internationalized Domain Names in Applications (IDNA)" optional = false python-versions = ">=3.6" files = [ - {file = "idna-3.8-py3-none-any.whl", hash = "sha256:050b4e5baadcd44d760cedbd2b8e639f2ff89bbc7a5730fcc662954303377aac"}, - {file = "idna-3.8.tar.gz", hash = "sha256:d838c2c0ed6fced7693d5e8ab8e734d5f8fda53a039c0164afb0b82e771e3603"}, + {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"}, + {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"}, ] +[package.extras] +all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"] + [[package]] name = "iniconfig" version = "2.0.0" @@ -517,72 +549,86 @@ files = [ [[package]] name = "jiter" -version = "0.5.0" +version = "0.8.0" description = "Fast iterable JSON parser." optional = false python-versions = ">=3.8" files = [ - {file = "jiter-0.5.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b599f4e89b3def9a94091e6ee52e1d7ad7bc33e238ebb9c4c63f211d74822c3f"}, - {file = "jiter-0.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2a063f71c4b06225543dddadbe09d203dc0c95ba352d8b85f1221173480a71d5"}, - {file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:acc0d5b8b3dd12e91dd184b87273f864b363dfabc90ef29a1092d269f18c7e28"}, - {file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c22541f0b672f4d741382a97c65609332a783501551445ab2df137ada01e019e"}, - {file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:63314832e302cc10d8dfbda0333a384bf4bcfce80d65fe99b0f3c0da8945a91a"}, - {file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a25fbd8a5a58061e433d6fae6d5298777c0814a8bcefa1e5ecfff20c594bd749"}, - {file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:503b2c27d87dfff5ab717a8200fbbcf4714516c9d85558048b1fc14d2de7d8dc"}, - {file = "jiter-0.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6d1f3d27cce923713933a844872d213d244e09b53ec99b7a7fdf73d543529d6d"}, - {file = "jiter-0.5.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:c95980207b3998f2c3b3098f357994d3fd7661121f30669ca7cb945f09510a87"}, - {file = "jiter-0.5.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:afa66939d834b0ce063f57d9895e8036ffc41c4bd90e4a99631e5f261d9b518e"}, - {file = "jiter-0.5.0-cp310-none-win32.whl", hash = "sha256:f16ca8f10e62f25fd81d5310e852df6649af17824146ca74647a018424ddeccf"}, - {file = "jiter-0.5.0-cp310-none-win_amd64.whl", hash = "sha256:b2950e4798e82dd9176935ef6a55cf6a448b5c71515a556da3f6b811a7844f1e"}, - {file = "jiter-0.5.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d4c8e1ed0ef31ad29cae5ea16b9e41529eb50a7fba70600008e9f8de6376d553"}, - {file = "jiter-0.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c6f16e21276074a12d8421692515b3fd6d2ea9c94fd0734c39a12960a20e85f3"}, - {file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5280e68e7740c8c128d3ae5ab63335ce6d1fb6603d3b809637b11713487af9e6"}, - {file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:583c57fc30cc1fec360e66323aadd7fc3edeec01289bfafc35d3b9dcb29495e4"}, - {file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:26351cc14507bdf466b5f99aba3df3143a59da75799bf64a53a3ad3155ecded9"}, - {file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4829df14d656b3fb87e50ae8b48253a8851c707da9f30d45aacab2aa2ba2d614"}, - {file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a42a4bdcf7307b86cb863b2fb9bb55029b422d8f86276a50487982d99eed7c6e"}, - {file = "jiter-0.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:04d461ad0aebf696f8da13c99bc1b3e06f66ecf6cfd56254cc402f6385231c06"}, - {file = "jiter-0.5.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:e6375923c5f19888c9226582a124b77b622f8fd0018b843c45eeb19d9701c403"}, - {file = "jiter-0.5.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:2cec323a853c24fd0472517113768c92ae0be8f8c384ef4441d3632da8baa646"}, - {file = "jiter-0.5.0-cp311-none-win32.whl", hash = "sha256:aa1db0967130b5cab63dfe4d6ff547c88b2a394c3410db64744d491df7f069bb"}, - {file = "jiter-0.5.0-cp311-none-win_amd64.whl", hash = "sha256:aa9d2b85b2ed7dc7697597dcfaac66e63c1b3028652f751c81c65a9f220899ae"}, - {file = "jiter-0.5.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9f664e7351604f91dcdd557603c57fc0d551bc65cc0a732fdacbf73ad335049a"}, - {file = "jiter-0.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:044f2f1148b5248ad2c8c3afb43430dccf676c5a5834d2f5089a4e6c5bbd64df"}, - {file = "jiter-0.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:702e3520384c88b6e270c55c772d4bd6d7b150608dcc94dea87ceba1b6391248"}, - {file = "jiter-0.5.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:528d742dcde73fad9d63e8242c036ab4a84389a56e04efd854062b660f559544"}, - {file = "jiter-0.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8cf80e5fe6ab582c82f0c3331df27a7e1565e2dcf06265afd5173d809cdbf9ba"}, - {file = "jiter-0.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:44dfc9ddfb9b51a5626568ef4e55ada462b7328996294fe4d36de02fce42721f"}, - {file = "jiter-0.5.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c451f7922992751a936b96c5f5b9bb9312243d9b754c34b33d0cb72c84669f4e"}, - {file = "jiter-0.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:308fce789a2f093dca1ff91ac391f11a9f99c35369117ad5a5c6c4903e1b3e3a"}, - {file = "jiter-0.5.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:7f5ad4a7c6b0d90776fdefa294f662e8a86871e601309643de30bf94bb93a64e"}, - {file = "jiter-0.5.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:ea189db75f8eca08807d02ae27929e890c7d47599ce3d0a6a5d41f2419ecf338"}, - {file = "jiter-0.5.0-cp312-none-win32.whl", hash = "sha256:e3bbe3910c724b877846186c25fe3c802e105a2c1fc2b57d6688b9f8772026e4"}, - {file = "jiter-0.5.0-cp312-none-win_amd64.whl", hash = "sha256:a586832f70c3f1481732919215f36d41c59ca080fa27a65cf23d9490e75b2ef5"}, - {file = "jiter-0.5.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:f04bc2fc50dc77be9d10f73fcc4e39346402ffe21726ff41028f36e179b587e6"}, - {file = "jiter-0.5.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:6f433a4169ad22fcb550b11179bb2b4fd405de9b982601914ef448390b2954f3"}, - {file = "jiter-0.5.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ad4a6398c85d3a20067e6c69890ca01f68659da94d74c800298581724e426c7e"}, - {file = "jiter-0.5.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6baa88334e7af3f4d7a5c66c3a63808e5efbc3698a1c57626541ddd22f8e4fbf"}, - {file = "jiter-0.5.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ece0a115c05efca597c6d938f88c9357c843f8c245dbbb53361a1c01afd7148"}, - {file = "jiter-0.5.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:335942557162ad372cc367ffaf93217117401bf930483b4b3ebdb1223dbddfa7"}, - {file = "jiter-0.5.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:649b0ee97a6e6da174bffcb3c8c051a5935d7d4f2f52ea1583b5b3e7822fbf14"}, - {file = "jiter-0.5.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f4be354c5de82157886ca7f5925dbda369b77344b4b4adf2723079715f823989"}, - {file = "jiter-0.5.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:5206144578831a6de278a38896864ded4ed96af66e1e63ec5dd7f4a1fce38a3a"}, - {file = "jiter-0.5.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:8120c60f8121ac3d6f072b97ef0e71770cc72b3c23084c72c4189428b1b1d3b6"}, - {file = "jiter-0.5.0-cp38-none-win32.whl", hash = "sha256:6f1223f88b6d76b519cb033a4d3687ca157c272ec5d6015c322fc5b3074d8a5e"}, - {file = "jiter-0.5.0-cp38-none-win_amd64.whl", hash = "sha256:c59614b225d9f434ea8fc0d0bec51ef5fa8c83679afedc0433905994fb36d631"}, - {file = "jiter-0.5.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:0af3838cfb7e6afee3f00dc66fa24695199e20ba87df26e942820345b0afc566"}, - {file = "jiter-0.5.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:550b11d669600dbc342364fd4adbe987f14d0bbedaf06feb1b983383dcc4b961"}, - {file = "jiter-0.5.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:489875bf1a0ffb3cb38a727b01e6673f0f2e395b2aad3c9387f94187cb214bbf"}, - {file = "jiter-0.5.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b250ca2594f5599ca82ba7e68785a669b352156260c5362ea1b4e04a0f3e2389"}, - {file = "jiter-0.5.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8ea18e01f785c6667ca15407cd6dabbe029d77474d53595a189bdc813347218e"}, - {file = "jiter-0.5.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:462a52be85b53cd9bffd94e2d788a09984274fe6cebb893d6287e1c296d50653"}, - {file = "jiter-0.5.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:92cc68b48d50fa472c79c93965e19bd48f40f207cb557a8346daa020d6ba973b"}, - {file = "jiter-0.5.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1c834133e59a8521bc87ebcad773608c6fa6ab5c7a022df24a45030826cf10bc"}, - {file = "jiter-0.5.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:ab3a71ff31cf2d45cb216dc37af522d335211f3a972d2fe14ea99073de6cb104"}, - {file = "jiter-0.5.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:cccd3af9c48ac500c95e1bcbc498020c87e1781ff0345dd371462d67b76643eb"}, - {file = "jiter-0.5.0-cp39-none-win32.whl", hash = "sha256:368084d8d5c4fc40ff7c3cc513c4f73e02c85f6009217922d0823a48ee7adf61"}, - {file = "jiter-0.5.0-cp39-none-win_amd64.whl", hash = "sha256:ce03f7b4129eb72f1687fa11300fbf677b02990618428934662406d2a76742a1"}, - {file = "jiter-0.5.0.tar.gz", hash = "sha256:1d916ba875bcab5c5f7d927df998c4cb694d27dceddf3392e58beaf10563368a"}, + {file = "jiter-0.8.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:dee4eeb293ffcd2c3b31ebab684dbf7f7b71fe198f8eddcdf3a042cc6e10205a"}, + {file = "jiter-0.8.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:aad1e6e9b01cf0304dcee14db03e92e0073287a6297caf5caf2e9dbfea16a924"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:504099fb7acdbe763e10690d560a25d4aee03d918d6a063f3a761d8a09fb833f"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2373487caad7fe39581f588ab5c9262fc1ade078d448626fec93f4ffba528858"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c341ecc3f9bccde952898b0c97c24f75b84b56a7e2f8bbc7c8e38cab0875a027"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0e48e7a336529b9419d299b70c358d4ebf99b8f4b847ed3f1000ec9f320e8c0c"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f5ee157a8afd2943be690db679f82fafb8d347a8342e8b9c34863de30c538d55"}, + {file = "jiter-0.8.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d7dceae3549b80087f913aad4acc2a7c1e0ab7cb983effd78bdc9c41cabdcf18"}, + {file = "jiter-0.8.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e29e9ecce53d396772590438214cac4ab89776f5e60bd30601f1050b34464019"}, + {file = "jiter-0.8.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:fa1782f22d5f92c620153133f35a9a395d3f3823374bceddd3e7032e2fdfa0b1"}, + {file = "jiter-0.8.0-cp310-none-win32.whl", hash = "sha256:f754ef13b4e4f67a3bf59fe974ef4342523801c48bf422f720bd37a02a360584"}, + {file = "jiter-0.8.0-cp310-none-win_amd64.whl", hash = "sha256:796f750b65f5d605f5e7acaccc6b051675e60c41d7ac3eab40dbd7b5b81a290f"}, + {file = "jiter-0.8.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:f6f4e645efd96b4690b9b6091dbd4e0fa2885ba5c57a0305c1916b75b4f30ff6"}, + {file = "jiter-0.8.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f61cf6d93c1ade9b8245c9f14b7900feadb0b7899dbe4aa8de268b705647df81"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0396bc5cb1309c6dab085e70bb3913cdd92218315e47b44afe9eace68ee8adaa"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:62d0e42ec5dc772bd8554a304358220be5d97d721c4648b23f3a9c01ccc2cb26"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ec4b711989860705733fc59fb8c41b2def97041cea656b37cf6c8ea8dee1c3f4"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:859cc35bf304ab066d88f10a44a3251a9cd057fb11ec23e00be22206db878f4f"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5000195921aa293b39b9b5bc959d7fa658e7f18f938c0e52732da8e3cc70a278"}, + {file = "jiter-0.8.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:36050284c0abde57aba34964d3920f3d6228211b65df7187059bb7c7f143759a"}, + {file = "jiter-0.8.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:a88f608e050cfe45c48d771e86ecdbf5258314c883c986d4217cc79e1fb5f689"}, + {file = "jiter-0.8.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:646cf4237665b2e13b4159d8f26d53f59bc9f2e6e135e3a508a2e5dd26d978c6"}, + {file = "jiter-0.8.0-cp311-none-win32.whl", hash = "sha256:21fe5b8345db1b3023052b2ade9bb4d369417827242892051244af8fae8ba231"}, + {file = "jiter-0.8.0-cp311-none-win_amd64.whl", hash = "sha256:30c2161c5493acf6b6c3c909973fb64ae863747def01cc7574f3954e0a15042c"}, + {file = "jiter-0.8.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:d91a52d8f49ada2672a4b808a0c5c25d28f320a2c9ca690e30ebd561eb5a1002"}, + {file = "jiter-0.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c38cf25cf7862f61410b7a49684d34eb3b5bcbd7ddaf4773eea40e0bd43de706"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c6189beb5c4b3117624be6b2e84545cff7611f5855d02de2d06ff68e316182be"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e13fa849c0e30643554add089983caa82f027d69fad8f50acadcb21c462244ab"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d7765ca159d0a58e8e0f8ca972cd6d26a33bc97b4480d0d2309856763807cd28"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1b0befe7c6e9fc867d5bed21bab0131dfe27d1fa5cd52ba2bced67da33730b7d"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7d6363d4c6f1052b1d8b494eb9a72667c3ef5f80ebacfe18712728e85327000"}, + {file = "jiter-0.8.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a873e57009863eeac3e3969e4653f07031d6270d037d6224415074ac17e5505c"}, + {file = "jiter-0.8.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:2582912473c0d9940791479fe1bf2976a34f212eb8e0a82ee9e645ac275c5d16"}, + {file = "jiter-0.8.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:646163201af42f55393ee6e8f6136b8df488253a6533f4230a64242ecbfe6048"}, + {file = "jiter-0.8.0-cp312-none-win32.whl", hash = "sha256:96e75c9abfbf7387cba89a324d2356d86d8897ac58c956017d062ad510832dae"}, + {file = "jiter-0.8.0-cp312-none-win_amd64.whl", hash = "sha256:ed6074552b4a32e047b52dad5ab497223721efbd0e9efe68c67749f094a092f7"}, + {file = "jiter-0.8.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:dd5e351cb9b3e676ec3360a85ea96def515ad2b83c8ae3a251ce84985a2c9a6f"}, + {file = "jiter-0.8.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ba9f12b0f801ecd5ed0cec29041dc425d1050922b434314c592fc30d51022467"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a7ba461c3681728d556392e8ae56fb44a550155a24905f01982317b367c21dd4"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3a15ed47ab09576db560dbc5c2c5a64477535beb056cd7d997d5dd0f2798770e"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cef55042816d0737142b0ec056c0356a5f681fb8d6aa8499b158e87098f4c6f8"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:549f170215adeb5e866f10617c3d019d8eb4e6d4e3c6b724b3b8c056514a3487"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f867edeb279d22020877640d2ea728de5817378c60a51be8af731a8a8f525306"}, + {file = "jiter-0.8.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:aef8845f463093799db4464cee2aa59d61aa8edcb3762aaa4aacbec3f478c929"}, + {file = "jiter-0.8.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:d0d6e22e4062c3d3c1bf3594baa2f67fc9dcdda8275abad99e468e0c6540bc54"}, + {file = "jiter-0.8.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:079e62e64696241ac3f408e337aaac09137ed760ccf2b72b1094b48745c13641"}, + {file = "jiter-0.8.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:74d2b56ed3da5760544df53b5f5c39782e68efb64dc3aa0bba4cc08815e6fae8"}, + {file = "jiter-0.8.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:798dafe108cba58a7bb0a50d4d5971f98bb7f3c974e1373e750de6eb21c1a329"}, + {file = "jiter-0.8.0-cp313-none-win32.whl", hash = "sha256:ca6d3064dfc743eb0d3d7539d89d4ba886957c717567adc72744341c1e3573c9"}, + {file = "jiter-0.8.0-cp313-none-win_amd64.whl", hash = "sha256:38caedda64fe1f04b06d7011fc15e86b3b837ed5088657bf778656551e3cd8f9"}, + {file = "jiter-0.8.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:bb5c8a0a8d081c338db22e5b8d53a89a121790569cbb85f7d3cfb1fe0fbe9836"}, + {file = "jiter-0.8.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:202dbe8970bfb166fab950eaab8f829c505730a0b33cc5e1cfb0a1c9dd56b2f9"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9046812e5671fdcfb9ae02881fff1f6a14d484b7e8b3316179a372cdfa1e8026"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e6ac56425023e52d65150918ae25480d0a1ce2a6bf5ea2097f66a2cc50f6d692"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7dfcf97210c6eab9d2a1c6af15dd39e1d5154b96a7145d0a97fa1df865b7b834"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d4e3c8444d418686f78c9a547b9b90031faf72a0a1a46bfec7fb31edbd889c0d"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6507011a299b7f578559084256405a8428875540d8d13530e00b688e41b09493"}, + {file = "jiter-0.8.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0aae4738eafdd34f0f25c2d3668ce9e8fa0d7cb75a2efae543c9a69aebc37323"}, + {file = "jiter-0.8.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:7f5d782e790396b13f2a7b36bdcaa3736a33293bdda80a4bf1a3ce0cd5ef9f15"}, + {file = "jiter-0.8.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:cc7f993bc2c4e03015445adbb16790c303282fce2e8d9dc3a3905b1d40e50564"}, + {file = "jiter-0.8.0-cp38-none-win32.whl", hash = "sha256:d4a8a6eda018a991fa58ef707dd51524055d11f5acb2f516d70b1be1d15ab39c"}, + {file = "jiter-0.8.0-cp38-none-win_amd64.whl", hash = "sha256:4cca948a3eda8ea24ed98acb0ee19dc755b6ad2e570ec85e1527d5167f91ff67"}, + {file = "jiter-0.8.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:ef89663678d8257063ce7c00d94638e05bd72f662c5e1eb0e07a172e6c1a9a9f"}, + {file = "jiter-0.8.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c402ddcba90b4cc71db3216e8330f4db36e0da2c78cf1d8a9c3ed8f272602a94"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a6dfe795b7a173a9f8ba7421cdd92193d60c1c973bbc50dc3758a9ad0fa5eb6"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8ec29a31b9abd6be39453a2c45da067138a3005d65d2c0507c530e0f1fdcd9a4"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2a488f8c54bddc3ddefaf3bfd6de4a52c97fc265d77bc2dcc6ee540c17e8c342"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:aeb5561adf4d26ca0d01b5811b4d7b56a8986699a473d700757b4758ef787883"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ab961858d7ad13132328517d29f121ae1b2d94502191d6bcf96bddcc8bb5d1c"}, + {file = "jiter-0.8.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a207e718d114d23acf0850a2174d290f42763d955030d9924ffa4227dbd0018f"}, + {file = "jiter-0.8.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:733bc9dc8ff718a0ae4695239e9268eb93e88b73b367dfac3ec227d8ce2f1e77"}, + {file = "jiter-0.8.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d1ec27299e22d05e13a06e460bf7f75f26f9aaa0e0fb7d060f40e88df1d81faa"}, + {file = "jiter-0.8.0-cp39-none-win32.whl", hash = "sha256:e8dbfcb46553e6661d3fc1f33831598fcddf73d0f67834bce9fc3e9ebfe5c439"}, + {file = "jiter-0.8.0-cp39-none-win_amd64.whl", hash = "sha256:af2ce2487b3a93747e2cb5150081d4ae1e5874fce5924fc1a12e9e768e489ad8"}, + {file = "jiter-0.8.0.tar.gz", hash = "sha256:86fee98b569d4cc511ff2e3ec131354fafebd9348a487549c31ad371ae730310"}, ] [[package]] @@ -612,7 +658,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.15" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -637,7 +683,7 @@ url = "../../core" [[package]] name = "langchain-openai" -version = "0.2.5" +version = "0.2.11" description = "An integration package connecting OpenAI and LangChain" optional = false python-versions = ">=3.9,<4.0" @@ -645,8 +691,8 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.15" -openai = "^1.52.0" +langchain-core = "^0.3.21" +openai = "^1.54.0" tiktoken = ">=0.7,<1" [package.source] @@ -655,18 +701,18 @@ url = "../openai" [[package]] name = "langsmith" -version = "0.1.139" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, - {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, + {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"}, + {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -674,6 +720,9 @@ pydantic = [ requests = ">=2,<3" requests-toolbelt = ">=1.0.0,<2.0.0" +[package.extras] +langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"] + [[package]] name = "multidict" version = "6.1.0" @@ -780,38 +829,43 @@ typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""} [[package]] name = "mypy" -version = "1.11.2" +version = "1.13.0" description = "Optional static typing for Python" optional = false python-versions = ">=3.8" files = [ - {file = "mypy-1.11.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d42a6dd818ffce7be66cce644f1dff482f1d97c53ca70908dff0b9ddc120b77a"}, - {file = "mypy-1.11.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:801780c56d1cdb896eacd5619a83e427ce436d86a3bdf9112527f24a66618fef"}, - {file = "mypy-1.11.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:41ea707d036a5307ac674ea172875f40c9d55c5394f888b168033177fce47383"}, - {file = "mypy-1.11.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6e658bd2d20565ea86da7d91331b0eed6d2eee22dc031579e6297f3e12c758c8"}, - {file = "mypy-1.11.2-cp310-cp310-win_amd64.whl", hash = "sha256:478db5f5036817fe45adb7332d927daa62417159d49783041338921dcf646fc7"}, - {file = "mypy-1.11.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:75746e06d5fa1e91bfd5432448d00d34593b52e7e91a187d981d08d1f33d4385"}, - {file = "mypy-1.11.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a976775ab2256aadc6add633d44f100a2517d2388906ec4f13231fafbb0eccca"}, - {file = "mypy-1.11.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:cd953f221ac1379050a8a646585a29574488974f79d8082cedef62744f0a0104"}, - {file = "mypy-1.11.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:57555a7715c0a34421013144a33d280e73c08df70f3a18a552938587ce9274f4"}, - {file = "mypy-1.11.2-cp311-cp311-win_amd64.whl", hash = "sha256:36383a4fcbad95f2657642a07ba22ff797de26277158f1cc7bd234821468b1b6"}, - {file = "mypy-1.11.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:e8960dbbbf36906c5c0b7f4fbf2f0c7ffb20f4898e6a879fcf56a41a08b0d318"}, - {file = "mypy-1.11.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:06d26c277962f3fb50e13044674aa10553981ae514288cb7d0a738f495550b36"}, - {file = "mypy-1.11.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6e7184632d89d677973a14d00ae4d03214c8bc301ceefcdaf5c474866814c987"}, - {file = "mypy-1.11.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:3a66169b92452f72117e2da3a576087025449018afc2d8e9bfe5ffab865709ca"}, - {file = "mypy-1.11.2-cp312-cp312-win_amd64.whl", hash = "sha256:969ea3ef09617aff826885a22ece0ddef69d95852cdad2f60c8bb06bf1f71f70"}, - {file = "mypy-1.11.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:37c7fa6121c1cdfcaac97ce3d3b5588e847aa79b580c1e922bb5d5d2902df19b"}, - {file = "mypy-1.11.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4a8a53bc3ffbd161b5b2a4fff2f0f1e23a33b0168f1c0778ec70e1a3d66deb86"}, - {file = "mypy-1.11.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2ff93107f01968ed834f4256bc1fc4475e2fecf6c661260066a985b52741ddce"}, - {file = "mypy-1.11.2-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:edb91dded4df17eae4537668b23f0ff6baf3707683734b6a818d5b9d0c0c31a1"}, - {file = "mypy-1.11.2-cp38-cp38-win_amd64.whl", hash = "sha256:ee23de8530d99b6db0573c4ef4bd8f39a2a6f9b60655bf7a1357e585a3486f2b"}, - {file = "mypy-1.11.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:801ca29f43d5acce85f8e999b1e431fb479cb02d0e11deb7d2abb56bdaf24fd6"}, - {file = "mypy-1.11.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:af8d155170fcf87a2afb55b35dc1a0ac21df4431e7d96717621962e4b9192e70"}, - {file = "mypy-1.11.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f7821776e5c4286b6a13138cc935e2e9b6fde05e081bdebf5cdb2bb97c9df81d"}, - {file = "mypy-1.11.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:539c570477a96a4e6fb718b8d5c3e0c0eba1f485df13f86d2970c91f0673148d"}, - {file = "mypy-1.11.2-cp39-cp39-win_amd64.whl", hash = "sha256:3f14cd3d386ac4d05c5a39a51b84387403dadbd936e17cb35882134d4f8f0d24"}, - {file = "mypy-1.11.2-py3-none-any.whl", hash = "sha256:b499bc07dbdcd3de92b0a8b29fdf592c111276f6a12fe29c30f6c417dd546d12"}, - {file = "mypy-1.11.2.tar.gz", hash = "sha256:7f9993ad3e0ffdc95c2a14b66dee63729f021968bff8ad911867579c65d13a79"}, + {file = "mypy-1.13.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6607e0f1dd1fb7f0aca14d936d13fd19eba5e17e1cd2a14f808fa5f8f6d8f60a"}, + {file = "mypy-1.13.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8a21be69bd26fa81b1f80a61ee7ab05b076c674d9b18fb56239d72e21d9f4c80"}, + {file = "mypy-1.13.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7b2353a44d2179846a096e25691d54d59904559f4232519d420d64da6828a3a7"}, + {file = "mypy-1.13.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0730d1c6a2739d4511dc4253f8274cdd140c55c32dfb0a4cf8b7a43f40abfa6f"}, + {file = "mypy-1.13.0-cp310-cp310-win_amd64.whl", hash = "sha256:c5fc54dbb712ff5e5a0fca797e6e0aa25726c7e72c6a5850cfd2adbc1eb0a372"}, + {file = "mypy-1.13.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:581665e6f3a8a9078f28d5502f4c334c0c8d802ef55ea0e7276a6e409bc0d82d"}, + {file = "mypy-1.13.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3ddb5b9bf82e05cc9a627e84707b528e5c7caaa1c55c69e175abb15a761cec2d"}, + {file = "mypy-1.13.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:20c7ee0bc0d5a9595c46f38beb04201f2620065a93755704e141fcac9f59db2b"}, + {file = "mypy-1.13.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:3790ded76f0b34bc9c8ba4def8f919dd6a46db0f5a6610fb994fe8efdd447f73"}, + {file = "mypy-1.13.0-cp311-cp311-win_amd64.whl", hash = "sha256:51f869f4b6b538229c1d1bcc1dd7d119817206e2bc54e8e374b3dfa202defcca"}, + {file = "mypy-1.13.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:5c7051a3461ae84dfb5dd15eff5094640c61c5f22257c8b766794e6dd85e72d5"}, + {file = "mypy-1.13.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:39bb21c69a5d6342f4ce526e4584bc5c197fd20a60d14a8624d8743fffb9472e"}, + {file = "mypy-1.13.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:164f28cb9d6367439031f4c81e84d3ccaa1e19232d9d05d37cb0bd880d3f93c2"}, + {file = "mypy-1.13.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a4c1bfcdbce96ff5d96fc9b08e3831acb30dc44ab02671eca5953eadad07d6d0"}, + {file = "mypy-1.13.0-cp312-cp312-win_amd64.whl", hash = "sha256:a0affb3a79a256b4183ba09811e3577c5163ed06685e4d4b46429a271ba174d2"}, + {file = "mypy-1.13.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:a7b44178c9760ce1a43f544e595d35ed61ac2c3de306599fa59b38a6048e1aa7"}, + {file = "mypy-1.13.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:5d5092efb8516d08440e36626f0153b5006d4088c1d663d88bf79625af3d1d62"}, + {file = "mypy-1.13.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:de2904956dac40ced10931ac967ae63c5089bd498542194b436eb097a9f77bc8"}, + {file = "mypy-1.13.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:7bfd8836970d33c2105562650656b6846149374dc8ed77d98424b40b09340ba7"}, + {file = "mypy-1.13.0-cp313-cp313-win_amd64.whl", hash = "sha256:9f73dba9ec77acb86457a8fc04b5239822df0c14a082564737833d2963677dbc"}, + {file = "mypy-1.13.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:100fac22ce82925f676a734af0db922ecfea991e1d7ec0ceb1e115ebe501301a"}, + {file = "mypy-1.13.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:7bcb0bb7f42a978bb323a7c88f1081d1b5dee77ca86f4100735a6f541299d8fb"}, + {file = "mypy-1.13.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bde31fc887c213e223bbfc34328070996061b0833b0a4cfec53745ed61f3519b"}, + {file = "mypy-1.13.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:07de989f89786f62b937851295ed62e51774722e5444a27cecca993fc3f9cd74"}, + {file = "mypy-1.13.0-cp38-cp38-win_amd64.whl", hash = "sha256:4bde84334fbe19bad704b3f5b78c4abd35ff1026f8ba72b29de70dda0916beb6"}, + {file = "mypy-1.13.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0246bcb1b5de7f08f2826451abd947bf656945209b140d16ed317f65a17dc7dc"}, + {file = "mypy-1.13.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:7f5b7deae912cf8b77e990b9280f170381fdfbddf61b4ef80927edd813163732"}, + {file = "mypy-1.13.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7029881ec6ffb8bc233a4fa364736789582c738217b133f1b55967115288a2bc"}, + {file = "mypy-1.13.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:3e38b980e5681f28f033f3be86b099a247b13c491f14bb8b1e1e134d23bb599d"}, + {file = "mypy-1.13.0-cp39-cp39-win_amd64.whl", hash = "sha256:a6789be98a2017c912ae6ccb77ea553bbaf13d27605d2ca20a76dfbced631b24"}, + {file = "mypy-1.13.0-py3-none-any.whl", hash = "sha256:9c250883f9fd81d212e0952c92dbfcc96fc237f4b7c92f56ac81fd48460b3e5a"}, + {file = "mypy-1.13.0.tar.gz", hash = "sha256:0291a61b6fbf3e6673e3405cfcc0e7650bebc7939659fdca2702958038bd835e"}, ] [package.dependencies] @@ -821,6 +875,7 @@ typing-extensions = ">=4.6.0" [package.extras] dmypy = ["psutil (>=4.0)"] +faster-cache = ["orjson"] install-types = ["pip"] mypyc = ["setuptools (>=50)"] reports = ["lxml"] @@ -883,13 +938,13 @@ files = [ [[package]] name = "openai" -version = "1.53.0" +version = "1.56.0" description = "The official Python library for the openai API" optional = false -python-versions = ">=3.7.1" +python-versions = ">=3.8" files = [ - {file = "openai-1.53.0-py3-none-any.whl", hash = "sha256:20f408c32fc5cb66e60c6882c994cdca580a5648e10045cd840734194f033418"}, - {file = "openai-1.53.0.tar.gz", hash = "sha256:be2c4e77721b166cce8130e544178b7d579f751b4b074ffbaade3854b6f85ec5"}, + {file = "openai-1.56.0-py3-none-any.whl", hash = "sha256:0751a6e139a09fca2e9cbbe8a62bfdab901b5865249d2555d005decf966ef9c3"}, + {file = "openai-1.56.0.tar.gz", hash = "sha256:f7fa159c8e18e7f9a8d71ff4b8052452ae70a4edc6b76a6e97eda00d5364923f"}, ] [package.dependencies] @@ -907,96 +962,115 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"] [[package]] name = "orjson" -version = "3.10.7" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.7-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:74f4544f5a6405b90da8ea724d15ac9c36da4d72a738c64685003337401f5c12"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34a566f22c28222b08875b18b0dfbf8a947e69df21a9ed5c51a6bf91cfb944ac"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bf6ba8ebc8ef5792e2337fb0419f8009729335bb400ece005606336b7fd7bab7"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ac7cf6222b29fbda9e3a472b41e6a5538b48f2c8f99261eecd60aafbdb60690c"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de817e2f5fc75a9e7dd350c4b0f54617b280e26d1631811a43e7e968fa71e3e9"}, - {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:348bdd16b32556cf8d7257b17cf2bdb7ab7976af4af41ebe79f9796c218f7e91"}, - {file = "orjson-3.10.7-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:479fd0844ddc3ca77e0fd99644c7fe2de8e8be1efcd57705b5c92e5186e8a250"}, - {file = "orjson-3.10.7-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:fdf5197a21dd660cf19dfd2a3ce79574588f8f5e2dbf21bda9ee2d2b46924d84"}, - {file = "orjson-3.10.7-cp310-none-win32.whl", hash = "sha256:d374d36726746c81a49f3ff8daa2898dccab6596864ebe43d50733275c629175"}, - {file = "orjson-3.10.7-cp310-none-win_amd64.whl", hash = "sha256:cb61938aec8b0ffb6eef484d480188a1777e67b05d58e41b435c74b9d84e0b9c"}, - {file = "orjson-3.10.7-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7db8539039698ddfb9a524b4dd19508256107568cdad24f3682d5773e60504a2"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:480f455222cb7a1dea35c57a67578848537d2602b46c464472c995297117fa09"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8a9c9b168b3a19e37fe2778c0003359f07822c90fdff8f98d9d2a91b3144d8e0"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8de062de550f63185e4c1c54151bdddfc5625e37daf0aa1e75d2a1293e3b7d9a"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6b0dd04483499d1de9c8f6203f8975caf17a6000b9c0c54630cef02e44ee624e"}, - {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b58d3795dafa334fc8fd46f7c5dc013e6ad06fd5b9a4cc98cb1456e7d3558bd6"}, - {file = "orjson-3.10.7-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:33cfb96c24034a878d83d1a9415799a73dc77480e6c40417e5dda0710d559ee6"}, - {file = "orjson-3.10.7-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e724cebe1fadc2b23c6f7415bad5ee6239e00a69f30ee423f319c6af70e2a5c0"}, - {file = "orjson-3.10.7-cp311-none-win32.whl", hash = "sha256:82763b46053727a7168d29c772ed5c870fdae2f61aa8a25994c7984a19b1021f"}, - {file = "orjson-3.10.7-cp311-none-win_amd64.whl", hash = "sha256:eb8d384a24778abf29afb8e41d68fdd9a156cf6e5390c04cc07bbc24b89e98b5"}, - {file = "orjson-3.10.7-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:44a96f2d4c3af51bfac6bc4ef7b182aa33f2f054fd7f34cc0ee9a320d051d41f"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:76ac14cd57df0572453543f8f2575e2d01ae9e790c21f57627803f5e79b0d3c3"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bdbb61dcc365dd9be94e8f7df91975edc9364d6a78c8f7adb69c1cdff318ec93"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b48b3db6bb6e0a08fa8c83b47bc169623f801e5cc4f24442ab2b6617da3b5313"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23820a1563a1d386414fef15c249040042b8e5d07b40ab3fe3efbfbbcbcb8864"}, - {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0c6a008e91d10a2564edbb6ee5069a9e66df3fbe11c9a005cb411f441fd2c09"}, - {file = "orjson-3.10.7-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d352ee8ac1926d6193f602cbe36b1643bbd1bbcb25e3c1a657a4390f3000c9a5"}, - {file = "orjson-3.10.7-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:d2d9f990623f15c0ae7ac608103c33dfe1486d2ed974ac3f40b693bad1a22a7b"}, - {file = "orjson-3.10.7-cp312-none-win32.whl", hash = "sha256:7c4c17f8157bd520cdb7195f75ddbd31671997cbe10aee559c2d613592e7d7eb"}, - {file = "orjson-3.10.7-cp312-none-win_amd64.whl", hash = "sha256:1d9c0e733e02ada3ed6098a10a8ee0052dd55774de3d9110d29868d24b17faa1"}, - {file = "orjson-3.10.7-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:77d325ed866876c0fa6492598ec01fe30e803272a6e8b10e992288b009cbe149"}, - {file = "orjson-3.10.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ea2c232deedcb605e853ae1db2cc94f7390ac776743b699b50b071b02bea6fe"}, - {file = "orjson-3.10.7-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3dcfbede6737fdbef3ce9c37af3fb6142e8e1ebc10336daa05872bfb1d87839c"}, - {file = "orjson-3.10.7-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:11748c135f281203f4ee695b7f80bb1358a82a63905f9f0b794769483ea854ad"}, - {file = "orjson-3.10.7-cp313-none-win32.whl", hash = "sha256:a7e19150d215c7a13f39eb787d84db274298d3f83d85463e61d277bbd7f401d2"}, - {file = "orjson-3.10.7-cp313-none-win_amd64.whl", hash = "sha256:eef44224729e9525d5261cc8d28d6b11cafc90e6bd0be2157bde69a52ec83024"}, - {file = "orjson-3.10.7-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6ea2b2258eff652c82652d5e0f02bd5e0463a6a52abb78e49ac288827aaa1469"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:430ee4d85841e1483d487e7b81401785a5dfd69db5de01314538f31f8fbf7ee1"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4b6146e439af4c2472c56f8540d799a67a81226e11992008cb47e1267a9b3225"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:084e537806b458911137f76097e53ce7bf5806dda33ddf6aaa66a028f8d43a23"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4829cf2195838e3f93b70fd3b4292156fc5e097aac3739859ac0dcc722b27ac0"}, - {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1193b2416cbad1a769f868b1749535d5da47626ac29445803dae7cc64b3f5c98"}, - {file = "orjson-3.10.7-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:4e6c3da13e5a57e4b3dca2de059f243ebec705857522f188f0180ae88badd354"}, - {file = "orjson-3.10.7-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c31008598424dfbe52ce8c5b47e0752dca918a4fdc4a2a32004efd9fab41d866"}, - {file = "orjson-3.10.7-cp38-none-win32.whl", hash = "sha256:7122a99831f9e7fe977dc45784d3b2edc821c172d545e6420c375e5a935f5a1c"}, - {file = "orjson-3.10.7-cp38-none-win_amd64.whl", hash = "sha256:a763bc0e58504cc803739e7df040685816145a6f3c8a589787084b54ebc9f16e"}, - {file = "orjson-3.10.7-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:e76be12658a6fa376fcd331b1ea4e58f5a06fd0220653450f0d415b8fd0fbe20"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ed350d6978d28b92939bfeb1a0570c523f6170efc3f0a0ef1f1df287cd4f4960"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:144888c76f8520e39bfa121b31fd637e18d4cc2f115727865fdf9fa325b10412"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:09b2d92fd95ad2402188cf51573acde57eb269eddabaa60f69ea0d733e789fe9"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b24a579123fa884f3a3caadaed7b75eb5715ee2b17ab5c66ac97d29b18fe57f"}, - {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e72591bcfe7512353bd609875ab38050efe3d55e18934e2f18950c108334b4ff"}, - {file = "orjson-3.10.7-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:f4db56635b58cd1a200b0a23744ff44206ee6aa428185e2b6c4a65b3197abdcd"}, - {file = "orjson-3.10.7-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:0fa5886854673222618638c6df7718ea7fe2f3f2384c452c9ccedc70b4a510a5"}, - {file = "orjson-3.10.7-cp39-none-win32.whl", hash = "sha256:8272527d08450ab16eb405f47e0f4ef0e5ff5981c3d82afe0efd25dcbef2bcd2"}, - {file = "orjson-3.10.7-cp39-none-win_amd64.whl", hash = "sha256:974683d4618c0c7dbf4f69c95a979734bf183d0658611760017f6e70a145af58"}, - {file = "orjson-3.10.7.tar.gz", hash = "sha256:75ef0640403f945f3a1f9f6400686560dbfb0fb5b16589ad62cd477043c4eee3"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] name = "packaging" -version = "24.1" +version = "24.2" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" files = [ - {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"}, - {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"}, + {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, + {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, ] [[package]] -name = "pinecone-client" -version = "5.0.1" +name = "pinecone" +version = "5.4.1" description = "Pinecone client and SDK" optional = false python-versions = "<4.0,>=3.8" files = [ - {file = "pinecone_client-5.0.1-py3-none-any.whl", hash = "sha256:c8f7835e1045ba84e295f217a8e85573ffb80b41501bbc1af6d92c9631c567a7"}, - {file = "pinecone_client-5.0.1.tar.gz", hash = "sha256:11c33ff5d1c38a6ce69e69fe532c0f22f312fb28d761bb30b3767816d3181d64"}, + {file = "pinecone-5.4.1-py3-none-any.whl", hash = "sha256:10a79ce77727dfc4f9e16f36baead9062366bafb93d5c1d97338d8d7212e6e1c"}, + {file = "pinecone-5.4.1.tar.gz", hash = "sha256:daba837a66d2bbfce9e1330821982945c2315b773cfcbc42b06751ff631e632a"}, ] [package.dependencies] certifi = ">=2019.11.17" -pinecone-plugin-inference = ">=1.0.3,<2.0.0" +pinecone-plugin-inference = ">=2.0.0,<4.0.0" pinecone-plugin-interface = ">=0.0.7,<0.0.8" +python-dateutil = ">=2.5.3" tqdm = ">=4.64.1" typing-extensions = ">=3.7.4" urllib3 = [ @@ -1009,13 +1083,13 @@ grpc = ["googleapis-common-protos (>=1.53.0)", "grpcio (>=1.44.0)", "grpcio (>=1 [[package]] name = "pinecone-plugin-inference" -version = "1.1.0" +version = "3.0.0" description = "Embeddings plugin for Pinecone SDK" optional = false python-versions = "<4.0,>=3.8" files = [ - {file = "pinecone_plugin_inference-1.1.0-py3-none-any.whl", hash = "sha256:32c61aba21c9a28fdcd0e782204c1ca641aeb3fd6e42764fbf0de8186eb657ec"}, - {file = "pinecone_plugin_inference-1.1.0.tar.gz", hash = "sha256:283e5ae4590b901bf2179beb56fc3d1b715e63582f37ec7abb0708cf70912d1f"}, + {file = "pinecone_plugin_inference-3.0.0-py3-none-any.whl", hash = "sha256:57b31b51dbcb6b806b51ba24c1ec981eba0a4c52252f695f4ab1317fc1270f68"}, + {file = "pinecone_plugin_inference-3.0.0.tar.gz", hash = "sha256:1e25a0fb4e2fabef12654fc263ec26a0c1026d9a60ced71239edc1c7e95114e9"}, ] [package.dependencies] @@ -1047,21 +1121,112 @@ files = [ dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] +[[package]] +name = "propcache" +version = "0.2.1" +description = "Accelerated property cache" +optional = false +python-versions = ">=3.9" +files = [ + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6b3f39a85d671436ee3d12c017f8fdea38509e4f25b28eb25877293c98c243f6"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d51fbe4285d5db5d92a929e3e21536ea3dd43732c5b177c7ef03f918dff9f2"}, + {file = "propcache-0.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6445804cf4ec763dc70de65a3b0d9954e868609e83850a47ca4f0cb64bd79fea"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f9479aa06a793c5aeba49ce5c5692ffb51fcd9a7016e017d555d5e2b0045d212"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9631c5e8b5b3a0fda99cb0d29c18133bca1e18aea9effe55adb3da1adef80d3"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3156628250f46a0895f1f36e1d4fbe062a1af8718ec3ebeb746f1d23f0c5dc4d"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b6fb63ae352e13748289f04f37868099e69dba4c2b3e271c46061e82c745634"}, + {file = "propcache-0.2.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:887d9b0a65404929641a9fabb6452b07fe4572b269d901d622d8a34a4e9043b2"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:a96dc1fa45bd8c407a0af03b2d5218392729e1822b0c32e62c5bf7eeb5fb3958"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a7e65eb5c003a303b94aa2c3852ef130230ec79e349632d030e9571b87c4698c"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:999779addc413181912e984b942fbcc951be1f5b3663cd80b2687758f434c583"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:19a0f89a7bb9d8048d9c4370c9c543c396e894c76be5525f5e1ad287f1750ddf"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:1ac2f5fe02fa75f56e1ad473f1175e11f475606ec9bd0be2e78e4734ad575034"}, + {file = "propcache-0.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:574faa3b79e8ebac7cb1d7930f51184ba1ccf69adfdec53a12f319a06030a68b"}, + {file = "propcache-0.2.1-cp310-cp310-win32.whl", hash = "sha256:03ff9d3f665769b2a85e6157ac8b439644f2d7fd17615a82fa55739bc97863f4"}, + {file = "propcache-0.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:2d3af2e79991102678f53e0dbf4c35de99b6b8b58f29a27ca0325816364caaba"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ffc3cca89bb438fb9c95c13fc874012f7b9466b89328c3c8b1aa93cdcfadd16"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f174bbd484294ed9fdf09437f889f95807e5f229d5d93588d34e92106fbf6717"}, + {file = "propcache-0.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:70693319e0b8fd35dd863e3e29513875eb15c51945bf32519ef52927ca883bc3"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b480c6a4e1138e1aa137c0079b9b6305ec6dcc1098a8ca5196283e8a49df95a9"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d27b84d5880f6d8aa9ae3edb253c59d9f6642ffbb2c889b78b60361eed449787"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:857112b22acd417c40fa4595db2fe28ab900c8c5fe4670c7989b1c0230955465"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf6c4150f8c0e32d241436526f3c3f9cbd34429492abddbada2ffcff506c51af"}, + {file = "propcache-0.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66d4cfda1d8ed687daa4bc0274fcfd5267873db9a5bc0418c2da19273040eeb7"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c2f992c07c0fca81655066705beae35fc95a2fa7366467366db627d9f2ee097f"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:4a571d97dbe66ef38e472703067021b1467025ec85707d57e78711c085984e54"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:bb6178c241278d5fe853b3de743087be7f5f4c6f7d6d22a3b524d323eecec505"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:ad1af54a62ffe39cf34db1aa6ed1a1873bd548f6401db39d8e7cd060b9211f82"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e7048abd75fe40712005bcfc06bb44b9dfcd8e101dda2ecf2f5aa46115ad07ca"}, + {file = "propcache-0.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:160291c60081f23ee43d44b08a7e5fb76681221a8e10b3139618c5a9a291b84e"}, + {file = "propcache-0.2.1-cp311-cp311-win32.whl", hash = "sha256:819ce3b883b7576ca28da3861c7e1a88afd08cc8c96908e08a3f4dd64a228034"}, + {file = "propcache-0.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:edc9fc7051e3350643ad929df55c451899bb9ae6d24998a949d2e4c87fb596d3"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:081a430aa8d5e8876c6909b67bd2d937bfd531b0382d3fdedb82612c618bc41a"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d2ccec9ac47cf4e04897619c0e0c1a48c54a71bdf045117d3a26f80d38ab1fb0"}, + {file = "propcache-0.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:14d86fe14b7e04fa306e0c43cdbeebe6b2c2156a0c9ce56b815faacc193e320d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:049324ee97bb67285b49632132db351b41e77833678432be52bdd0289c0e05e4"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1cd9a1d071158de1cc1c71a26014dcdfa7dd3d5f4f88c298c7f90ad6f27bb46d"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:98110aa363f1bb4c073e8dcfaefd3a5cea0f0834c2aab23dda657e4dab2f53b5"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:647894f5ae99c4cf6bb82a1bb3a796f6e06af3caa3d32e26d2350d0e3e3faf24"}, + {file = "propcache-0.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bfd3223c15bebe26518d58ccf9a39b93948d3dcb3e57a20480dfdd315356baff"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d71264a80f3fcf512eb4f18f59423fe82d6e346ee97b90625f283df56aee103f"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:e73091191e4280403bde6c9a52a6999d69cdfde498f1fdf629105247599b57ec"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:3935bfa5fede35fb202c4b569bb9c042f337ca4ff7bd540a0aa5e37131659348"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f508b0491767bb1f2b87fdfacaba5f7eddc2f867740ec69ece6d1946d29029a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1672137af7c46662a1c2be1e8dc78cb6d224319aaa40271c9257d886be4363a6"}, + {file = "propcache-0.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b74c261802d3d2b85c9df2dfb2fa81b6f90deeef63c2db9f0e029a3cac50b518"}, + {file = "propcache-0.2.1-cp312-cp312-win32.whl", hash = "sha256:d09c333d36c1409d56a9d29b3a1b800a42c76a57a5a8907eacdbce3f18768246"}, + {file = "propcache-0.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:c214999039d4f2a5b2073ac506bba279945233da8c786e490d411dfc30f855c1"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:aca405706e0b0a44cc6bfd41fbe89919a6a56999157f6de7e182a990c36e37bc"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:12d1083f001ace206fe34b6bdc2cb94be66d57a850866f0b908972f90996b3e9"}, + {file = "propcache-0.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d93f3307ad32a27bda2e88ec81134b823c240aa3abb55821a8da553eed8d9439"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba278acf14471d36316159c94a802933d10b6a1e117b8554fe0d0d9b75c9d536"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4e6281aedfca15301c41f74d7005e6e3f4ca143584ba696ac69df4f02f40d629"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b750a8e5a1262434fb1517ddf64b5de58327f1adc3524a5e44c2ca43305eb0b"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf72af5e0fb40e9babf594308911436c8efde3cb5e75b6f206c34ad18be5c052"}, + {file = "propcache-0.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b2d0a12018b04f4cb820781ec0dffb5f7c7c1d2a5cd22bff7fb055a2cb19ebce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e800776a79a5aabdb17dcc2346a7d66d0777e942e4cd251defeb084762ecd17d"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:4160d9283bd382fa6c0c2b5e017acc95bc183570cd70968b9202ad6d8fc48dce"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:30b43e74f1359353341a7adb783c8f1b1c676367b011709f466f42fda2045e95"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:58791550b27d5488b1bb52bc96328456095d96206a250d28d874fafe11b3dfaf"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:0f022d381747f0dfe27e99d928e31bc51a18b65bb9e481ae0af1380a6725dd1f"}, + {file = "propcache-0.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:297878dc9d0a334358f9b608b56d02e72899f3b8499fc6044133f0d319e2ec30"}, + {file = "propcache-0.2.1-cp313-cp313-win32.whl", hash = "sha256:ddfab44e4489bd79bda09d84c430677fc7f0a4939a73d2bba3073036f487a0a6"}, + {file = "propcache-0.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:556fc6c10989f19a179e4321e5d678db8eb2924131e64652a51fe83e4c3db0e1"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:6a9a8c34fb7bb609419a211e59da8887eeca40d300b5ea8e56af98f6fbbb1541"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ae1aa1cd222c6d205853b3013c69cd04515f9d6ab6de4b0603e2e1c33221303e"}, + {file = "propcache-0.2.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:accb6150ce61c9c4b7738d45550806aa2b71c7668c6942f17b0ac182b6142fd4"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5eee736daafa7af6d0a2dc15cc75e05c64f37fc37bafef2e00d77c14171c2097"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f7a31fc1e1bd362874863fdeed71aed92d348f5336fd84f2197ba40c59f061bd"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cba4cfa1052819d16699e1d55d18c92b6e094d4517c41dd231a8b9f87b6fa681"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f089118d584e859c62b3da0892b88a83d611c2033ac410e929cb6754eec0ed16"}, + {file = "propcache-0.2.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:781e65134efaf88feb447e8c97a51772aa75e48b794352f94cb7ea717dedda0d"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:31f5af773530fd3c658b32b6bdc2d0838543de70eb9a2156c03e410f7b0d3aae"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:a7a078f5d37bee6690959c813977da5291b24286e7b962e62a94cec31aa5188b"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:cea7daf9fc7ae6687cf1e2c049752f19f146fdc37c2cc376e7d0032cf4f25347"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:8b3489ff1ed1e8315674d0775dc7d2195fb13ca17b3808721b54dbe9fd020faf"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9403db39be1393618dd80c746cb22ccda168efce239c73af13c3763ef56ffc04"}, + {file = "propcache-0.2.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5d97151bc92d2b2578ff7ce779cdb9174337390a535953cbb9452fb65164c587"}, + {file = "propcache-0.2.1-cp39-cp39-win32.whl", hash = "sha256:9caac6b54914bdf41bcc91e7eb9147d331d29235a7c967c150ef5df6464fd1bb"}, + {file = "propcache-0.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:92fc4500fcb33899b05ba73276dfb684a20d31caa567b7cb5252d48f896a91b1"}, + {file = "propcache-0.2.1-py3-none-any.whl", hash = "sha256:52277518d6aae65536e9cea52d4e7fd2f7a66f4aa2d30ed3f2fcea620ace3c54"}, + {file = "propcache-0.2.1.tar.gz", hash = "sha256:3f77ce728b19cb537714499928fe800c3dda29e8d9428778fc7c186da4c09a64"}, +] + [[package]] name = "pydantic" -version = "2.9.1" +version = "2.10.2" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.1-py3-none-any.whl", hash = "sha256:7aff4db5fdf3cf573d4b3c30926a510a10e19a0774d38fc4967f78beb6deb612"}, - {file = "pydantic-2.9.1.tar.gz", hash = "sha256:1363c7d975c7036df0db2b4a61f2e062fbc0aa5ab5f2772e0ffc7191a4f4bce2"}, + {file = "pydantic-2.10.2-py3-none-any.whl", hash = "sha256:cfb96e45951117c3024e6b67b25cdc33a3cb7b2fa62e239f7af1378358a1d99e"}, + {file = "pydantic-2.10.2.tar.gz", hash = "sha256:2bc2d7f17232e0841cbba4641e65ba1eb6fafb3a08de3a091ff3ce14a197c4fa"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.3" -typing-extensions = {version = ">=4.6.1", markers = "python_version < \"3.13\""} +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -1069,100 +1234,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.3" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:7f10a5d1b9281392f1bf507d16ac720e78285dfd635b05737c3911637601bae6"}, - {file = "pydantic_core-2.23.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3c09a7885dd33ee8c65266e5aa7fb7e2f23d49d8043f089989726391dd7350c5"}, - {file = "pydantic_core-2.23.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6470b5a1ec4d1c2e9afe928c6cb37eb33381cab99292a708b8cb9aa89e62429b"}, - {file = "pydantic_core-2.23.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9172d2088e27d9a185ea0a6c8cebe227a9139fd90295221d7d495944d2367700"}, - {file = "pydantic_core-2.23.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86fc6c762ca7ac8fbbdff80d61b2c59fb6b7d144aa46e2d54d9e1b7b0e780e01"}, - {file = "pydantic_core-2.23.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f0cb80fd5c2df4898693aa841425ea1727b1b6d2167448253077d2a49003e0ed"}, - {file = "pydantic_core-2.23.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03667cec5daf43ac4995cefa8aaf58f99de036204a37b889c24a80927b629cec"}, - {file = "pydantic_core-2.23.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:047531242f8e9c2db733599f1c612925de095e93c9cc0e599e96cf536aaf56ba"}, - {file = "pydantic_core-2.23.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:5499798317fff7f25dbef9347f4451b91ac2a4330c6669821c8202fd354c7bee"}, - {file = "pydantic_core-2.23.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bbb5e45eab7624440516ee3722a3044b83fff4c0372efe183fd6ba678ff681fe"}, - {file = "pydantic_core-2.23.3-cp310-none-win32.whl", hash = "sha256:8b5b3ed73abb147704a6e9f556d8c5cb078f8c095be4588e669d315e0d11893b"}, - {file = "pydantic_core-2.23.3-cp310-none-win_amd64.whl", hash = "sha256:2b603cde285322758a0279995b5796d64b63060bfbe214b50a3ca23b5cee3e83"}, - {file = "pydantic_core-2.23.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:c889fd87e1f1bbeb877c2ee56b63bb297de4636661cc9bbfcf4b34e5e925bc27"}, - {file = "pydantic_core-2.23.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ea85bda3189fb27503af4c45273735bcde3dd31c1ab17d11f37b04877859ef45"}, - {file = "pydantic_core-2.23.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a7f7f72f721223f33d3dc98a791666ebc6a91fa023ce63733709f4894a7dc611"}, - {file = "pydantic_core-2.23.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2b2b55b0448e9da68f56b696f313949cda1039e8ec7b5d294285335b53104b61"}, - {file = "pydantic_core-2.23.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c24574c7e92e2c56379706b9a3f07c1e0c7f2f87a41b6ee86653100c4ce343e5"}, - {file = "pydantic_core-2.23.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f2b05e6ccbee333a8f4b8f4d7c244fdb7a979e90977ad9c51ea31261e2085ce0"}, - {file = "pydantic_core-2.23.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e2c409ce1c219c091e47cb03feb3c4ed8c2b8e004efc940da0166aaee8f9d6c8"}, - {file = "pydantic_core-2.23.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d965e8b325f443ed3196db890d85dfebbb09f7384486a77461347f4adb1fa7f8"}, - {file = "pydantic_core-2.23.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:f56af3a420fb1ffaf43ece3ea09c2d27c444e7c40dcb7c6e7cf57aae764f2b48"}, - {file = "pydantic_core-2.23.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:5b01a078dd4f9a52494370af21aa52964e0a96d4862ac64ff7cea06e0f12d2c5"}, - {file = "pydantic_core-2.23.3-cp311-none-win32.whl", hash = "sha256:560e32f0df04ac69b3dd818f71339983f6d1f70eb99d4d1f8e9705fb6c34a5c1"}, - {file = "pydantic_core-2.23.3-cp311-none-win_amd64.whl", hash = "sha256:c744fa100fdea0d000d8bcddee95213d2de2e95b9c12be083370b2072333a0fa"}, - {file = "pydantic_core-2.23.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:e0ec50663feedf64d21bad0809f5857bac1ce91deded203efc4a84b31b2e4305"}, - {file = "pydantic_core-2.23.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:db6e6afcb95edbe6b357786684b71008499836e91f2a4a1e55b840955b341dbb"}, - {file = "pydantic_core-2.23.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:98ccd69edcf49f0875d86942f4418a4e83eb3047f20eb897bffa62a5d419c8fa"}, - {file = "pydantic_core-2.23.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a678c1ac5c5ec5685af0133262103defb427114e62eafeda12f1357a12140162"}, - {file = "pydantic_core-2.23.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:01491d8b4d8db9f3391d93b0df60701e644ff0894352947f31fff3e52bd5c801"}, - {file = "pydantic_core-2.23.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fcf31facf2796a2d3b7fe338fe8640aa0166e4e55b4cb108dbfd1058049bf4cb"}, - {file = "pydantic_core-2.23.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7200fd561fb3be06827340da066df4311d0b6b8eb0c2116a110be5245dceb326"}, - {file = "pydantic_core-2.23.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:dc1636770a809dee2bd44dd74b89cc80eb41172bcad8af75dd0bc182c2666d4c"}, - {file = "pydantic_core-2.23.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:67a5def279309f2e23014b608c4150b0c2d323bd7bccd27ff07b001c12c2415c"}, - {file = "pydantic_core-2.23.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:748bdf985014c6dd3e1e4cc3db90f1c3ecc7246ff5a3cd4ddab20c768b2f1dab"}, - {file = "pydantic_core-2.23.3-cp312-none-win32.whl", hash = "sha256:255ec6dcb899c115f1e2a64bc9ebc24cc0e3ab097775755244f77360d1f3c06c"}, - {file = "pydantic_core-2.23.3-cp312-none-win_amd64.whl", hash = "sha256:40b8441be16c1e940abebed83cd006ddb9e3737a279e339dbd6d31578b802f7b"}, - {file = "pydantic_core-2.23.3-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:6daaf5b1ba1369a22c8b050b643250e3e5efc6a78366d323294aee54953a4d5f"}, - {file = "pydantic_core-2.23.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d015e63b985a78a3d4ccffd3bdf22b7c20b3bbd4b8227809b3e8e75bc37f9cb2"}, - {file = "pydantic_core-2.23.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a3fc572d9b5b5cfe13f8e8a6e26271d5d13f80173724b738557a8c7f3a8a3791"}, - {file = "pydantic_core-2.23.3-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f6bd91345b5163ee7448bee201ed7dd601ca24f43f439109b0212e296eb5b423"}, - {file = "pydantic_core-2.23.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:fc379c73fd66606628b866f661e8785088afe2adaba78e6bbe80796baf708a63"}, - {file = "pydantic_core-2.23.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fbdce4b47592f9e296e19ac31667daed8753c8367ebb34b9a9bd89dacaa299c9"}, - {file = "pydantic_core-2.23.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc3cf31edf405a161a0adad83246568647c54404739b614b1ff43dad2b02e6d5"}, - {file = "pydantic_core-2.23.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8e22b477bf90db71c156f89a55bfe4d25177b81fce4aa09294d9e805eec13855"}, - {file = "pydantic_core-2.23.3-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:0a0137ddf462575d9bce863c4c95bac3493ba8e22f8c28ca94634b4a1d3e2bb4"}, - {file = "pydantic_core-2.23.3-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:203171e48946c3164fe7691fc349c79241ff8f28306abd4cad5f4f75ed80bc8d"}, - {file = "pydantic_core-2.23.3-cp313-none-win32.whl", hash = "sha256:76bdab0de4acb3f119c2a4bff740e0c7dc2e6de7692774620f7452ce11ca76c8"}, - {file = "pydantic_core-2.23.3-cp313-none-win_amd64.whl", hash = "sha256:37ba321ac2a46100c578a92e9a6aa33afe9ec99ffa084424291d84e456f490c1"}, - {file = "pydantic_core-2.23.3-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d063c6b9fed7d992bcbebfc9133f4c24b7a7f215d6b102f3e082b1117cddb72c"}, - {file = "pydantic_core-2.23.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:6cb968da9a0746a0cf521b2b5ef25fc5a0bee9b9a1a8214e0a1cfaea5be7e8a4"}, - {file = "pydantic_core-2.23.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:edbefe079a520c5984e30e1f1f29325054b59534729c25b874a16a5048028d16"}, - {file = "pydantic_core-2.23.3-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:cbaaf2ef20d282659093913da9d402108203f7cb5955020bd8d1ae5a2325d1c4"}, - {file = "pydantic_core-2.23.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:fb539d7e5dc4aac345846f290cf504d2fd3c1be26ac4e8b5e4c2b688069ff4cf"}, - {file = "pydantic_core-2.23.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7e6f33503c5495059148cc486867e1d24ca35df5fc064686e631e314d959ad5b"}, - {file = "pydantic_core-2.23.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:04b07490bc2f6f2717b10c3969e1b830f5720b632f8ae2f3b8b1542394c47a8e"}, - {file = "pydantic_core-2.23.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:03795b9e8a5d7fda05f3873efc3f59105e2dcff14231680296b87b80bb327295"}, - {file = "pydantic_core-2.23.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:c483dab0f14b8d3f0df0c6c18d70b21b086f74c87ab03c59250dbf6d3c89baba"}, - {file = "pydantic_core-2.23.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:8b2682038e255e94baf2c473dca914a7460069171ff5cdd4080be18ab8a7fd6e"}, - {file = "pydantic_core-2.23.3-cp38-none-win32.whl", hash = "sha256:f4a57db8966b3a1d1a350012839c6a0099f0898c56512dfade8a1fe5fb278710"}, - {file = "pydantic_core-2.23.3-cp38-none-win_amd64.whl", hash = "sha256:13dd45ba2561603681a2676ca56006d6dee94493f03d5cadc055d2055615c3ea"}, - {file = "pydantic_core-2.23.3-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:82da2f4703894134a9f000e24965df73cc103e31e8c31906cc1ee89fde72cbd8"}, - {file = "pydantic_core-2.23.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:dd9be0a42de08f4b58a3cc73a123f124f65c24698b95a54c1543065baca8cf0e"}, - {file = "pydantic_core-2.23.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:89b731f25c80830c76fdb13705c68fef6a2b6dc494402987c7ea9584fe189f5d"}, - {file = "pydantic_core-2.23.3-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c6de1ec30c4bb94f3a69c9f5f2182baeda5b809f806676675e9ef6b8dc936f28"}, - {file = "pydantic_core-2.23.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bb68b41c3fa64587412b104294b9cbb027509dc2f6958446c502638d481525ef"}, - {file = "pydantic_core-2.23.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1c3980f2843de5184656aab58698011b42763ccba11c4a8c35936c8dd6c7068c"}, - {file = "pydantic_core-2.23.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:94f85614f2cba13f62c3c6481716e4adeae48e1eaa7e8bac379b9d177d93947a"}, - {file = "pydantic_core-2.23.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:510b7fb0a86dc8f10a8bb43bd2f97beb63cffad1203071dc434dac26453955cd"}, - {file = "pydantic_core-2.23.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:1eba2f7ce3e30ee2170410e2171867ea73dbd692433b81a93758ab2de6c64835"}, - {file = "pydantic_core-2.23.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:4b259fd8409ab84b4041b7b3f24dcc41e4696f180b775961ca8142b5b21d0e70"}, - {file = "pydantic_core-2.23.3-cp39-none-win32.whl", hash = "sha256:40d9bd259538dba2f40963286009bf7caf18b5112b19d2b55b09c14dde6db6a7"}, - {file = "pydantic_core-2.23.3-cp39-none-win_amd64.whl", hash = "sha256:5a8cd3074a98ee70173a8633ad3c10e00dcb991ecec57263aacb4095c5efb958"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f399e8657c67313476a121a6944311fab377085ca7f490648c9af97fc732732d"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:6b5547d098c76e1694ba85f05b595720d7c60d342f24d5aad32c3049131fa5c4"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0dda0290a6f608504882d9f7650975b4651ff91c85673341789a476b1159f211"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65b6e5da855e9c55a0c67f4db8a492bf13d8d3316a59999cfbaf98cc6e401961"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:09e926397f392059ce0afdcac920df29d9c833256354d0c55f1584b0b70cf07e"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:87cfa0ed6b8c5bd6ae8b66de941cece179281239d482f363814d2b986b79cedc"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:e61328920154b6a44d98cabcb709f10e8b74276bc709c9a513a8c37a18786cc4"}, - {file = "pydantic_core-2.23.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:ce3317d155628301d649fe5e16a99528d5680af4ec7aa70b90b8dacd2d725c9b"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:e89513f014c6be0d17b00a9a7c81b1c426f4eb9224b15433f3d98c1a071f8433"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:4f62c1c953d7ee375df5eb2e44ad50ce2f5aff931723b398b8bc6f0ac159791a"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2718443bc671c7ac331de4eef9b673063b10af32a0bb385019ad61dcf2cc8f6c"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0d90e08b2727c5d01af1b5ef4121d2f0c99fbee692c762f4d9d0409c9da6541"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b676583fc459c64146debea14ba3af54e540b61762dfc0613dc4e98c3f66eeb"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:50e4661f3337977740fdbfbae084ae5693e505ca2b3130a6d4eb0f2281dc43b8"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:68f4cf373f0de6abfe599a38307f4417c1c867ca381c03df27c873a9069cda25"}, - {file = "pydantic_core-2.23.3-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:59d52cf01854cb26c46958552a21acb10dd78a52aa34c86f284e66b209db8cab"}, - {file = "pydantic_core-2.23.3.tar.gz", hash = "sha256:3cb0f65d8b4121c1b015c60104a685feb929a29d7cf204387c7f2688c7974690"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -1318,105 +1494,105 @@ files = [ [[package]] name = "regex" -version = "2024.9.11" +version = "2024.11.6" description = "Alternative regular expression module, to replace re." optional = false python-versions = ">=3.8" files = [ - {file = "regex-2024.9.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1494fa8725c285a81d01dc8c06b55287a1ee5e0e382d8413adc0a9197aac6408"}, - {file = "regex-2024.9.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0e12c481ad92d129c78f13a2a3662317e46ee7ef96c94fd332e1c29131875b7d"}, - {file = "regex-2024.9.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:16e13a7929791ac1216afde26f712802e3df7bf0360b32e4914dca3ab8baeea5"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:46989629904bad940bbec2106528140a218b4a36bb3042d8406980be1941429c"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a906ed5e47a0ce5f04b2c981af1c9acf9e8696066900bf03b9d7879a6f679fc8"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e9a091b0550b3b0207784a7d6d0f1a00d1d1c8a11699c1a4d93db3fbefc3ad35"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ddcd9a179c0a6fa8add279a4444015acddcd7f232a49071ae57fa6e278f1f71"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6b41e1adc61fa347662b09398e31ad446afadff932a24807d3ceb955ed865cc8"}, - {file = "regex-2024.9.11-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ced479f601cd2f8ca1fd7b23925a7e0ad512a56d6e9476f79b8f381d9d37090a"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:635a1d96665f84b292e401c3d62775851aedc31d4f8784117b3c68c4fcd4118d"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:c0256beda696edcf7d97ef16b2a33a8e5a875affd6fa6567b54f7c577b30a137"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:3ce4f1185db3fbde8ed8aa223fc9620f276c58de8b0d4f8cc86fd1360829edb6"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:09d77559e80dcc9d24570da3745ab859a9cf91953062e4ab126ba9d5993688ca"}, - {file = "regex-2024.9.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a22ccefd4db3f12b526eccb129390942fe874a3a9fdbdd24cf55773a1faab1a"}, - {file = "regex-2024.9.11-cp310-cp310-win32.whl", hash = "sha256:f745ec09bc1b0bd15cfc73df6fa4f726dcc26bb16c23a03f9e3367d357eeedd0"}, - {file = "regex-2024.9.11-cp310-cp310-win_amd64.whl", hash = "sha256:01c2acb51f8a7d6494c8c5eafe3d8e06d76563d8a8a4643b37e9b2dd8a2ff623"}, - {file = "regex-2024.9.11-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:2cce2449e5927a0bf084d346da6cd5eb016b2beca10d0013ab50e3c226ffc0df"}, - {file = "regex-2024.9.11-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3b37fa423beefa44919e009745ccbf353d8c981516e807995b2bd11c2c77d268"}, - {file = "regex-2024.9.11-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:64ce2799bd75039b480cc0360907c4fb2f50022f030bf9e7a8705b636e408fad"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a4cc92bb6db56ab0c1cbd17294e14f5e9224f0cc6521167ef388332604e92679"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d05ac6fa06959c4172eccd99a222e1fbf17b5670c4d596cb1e5cde99600674c4"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:040562757795eeea356394a7fb13076ad4f99d3c62ab0f8bdfb21f99a1f85664"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6113c008a7780792efc80f9dfe10ba0cd043cbf8dc9a76ef757850f51b4edc50"}, - {file = "regex-2024.9.11-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8e5fb5f77c8745a60105403a774fe2c1759b71d3e7b4ca237a5e67ad066c7199"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:54d9ff35d4515debf14bc27f1e3b38bfc453eff3220f5bce159642fa762fe5d4"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:df5cbb1fbc74a8305b6065d4ade43b993be03dbe0f8b30032cced0d7740994bd"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:7fb89ee5d106e4a7a51bce305ac4efb981536301895f7bdcf93ec92ae0d91c7f"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:a738b937d512b30bf75995c0159c0ddf9eec0775c9d72ac0202076c72f24aa96"}, - {file = "regex-2024.9.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e28f9faeb14b6f23ac55bfbbfd3643f5c7c18ede093977f1df249f73fd22c7b1"}, - {file = "regex-2024.9.11-cp311-cp311-win32.whl", hash = "sha256:18e707ce6c92d7282dfce370cd205098384b8ee21544e7cb29b8aab955b66fa9"}, - {file = "regex-2024.9.11-cp311-cp311-win_amd64.whl", hash = "sha256:313ea15e5ff2a8cbbad96ccef6be638393041b0a7863183c2d31e0c6116688cf"}, - {file = "regex-2024.9.11-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:b0d0a6c64fcc4ef9c69bd5b3b3626cc3776520a1637d8abaa62b9edc147a58f7"}, - {file = "regex-2024.9.11-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:49b0e06786ea663f933f3710a51e9385ce0cba0ea56b67107fd841a55d56a231"}, - {file = "regex-2024.9.11-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5b513b6997a0b2f10e4fd3a1313568e373926e8c252bd76c960f96fd039cd28d"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ee439691d8c23e76f9802c42a95cfeebf9d47cf4ffd06f18489122dbb0a7ad64"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a8f877c89719d759e52783f7fe6e1c67121076b87b40542966c02de5503ace42"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23b30c62d0f16827f2ae9f2bb87619bc4fba2044911e2e6c2eb1af0161cdb766"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:85ab7824093d8f10d44330fe1e6493f756f252d145323dd17ab6b48733ff6c0a"}, - {file = "regex-2024.9.11-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8dee5b4810a89447151999428fe096977346cf2f29f4d5e29609d2e19e0199c9"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:98eeee2f2e63edae2181c886d7911ce502e1292794f4c5ee71e60e23e8d26b5d"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:57fdd2e0b2694ce6fc2e5ccf189789c3e2962916fb38779d3e3521ff8fe7a822"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:d552c78411f60b1fdaafd117a1fca2f02e562e309223b9d44b7de8be451ec5e0"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a0b2b80321c2ed3fcf0385ec9e51a12253c50f146fddb2abbb10f033fe3d049a"}, - {file = "regex-2024.9.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:18406efb2f5a0e57e3a5881cd9354c1512d3bb4f5c45d96d110a66114d84d23a"}, - {file = "regex-2024.9.11-cp312-cp312-win32.whl", hash = "sha256:e464b467f1588e2c42d26814231edecbcfe77f5ac414d92cbf4e7b55b2c2a776"}, - {file = "regex-2024.9.11-cp312-cp312-win_amd64.whl", hash = "sha256:9e8719792ca63c6b8340380352c24dcb8cd7ec49dae36e963742a275dfae6009"}, - {file = "regex-2024.9.11-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:c157bb447303070f256e084668b702073db99bbb61d44f85d811025fcf38f784"}, - {file = "regex-2024.9.11-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:4db21ece84dfeefc5d8a3863f101995de646c6cb0536952c321a2650aa202c36"}, - {file = "regex-2024.9.11-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:220e92a30b426daf23bb67a7962900ed4613589bab80382be09b48896d211e92"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eb1ae19e64c14c7ec1995f40bd932448713d3c73509e82d8cd7744dc00e29e86"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f47cd43a5bfa48f86925fe26fbdd0a488ff15b62468abb5d2a1e092a4fb10e85"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9d4a76b96f398697fe01117093613166e6aa8195d63f1b4ec3f21ab637632963"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0ea51dcc0835eea2ea31d66456210a4e01a076d820e9039b04ae8d17ac11dee6"}, - {file = "regex-2024.9.11-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b7aaa315101c6567a9a45d2839322c51c8d6e81f67683d529512f5bcfb99c802"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c57d08ad67aba97af57a7263c2d9006d5c404d721c5f7542f077f109ec2a4a29"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f8404bf61298bb6f8224bb9176c1424548ee1181130818fcd2cbffddc768bed8"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:dd4490a33eb909ef5078ab20f5f000087afa2a4daa27b4c072ccb3cb3050ad84"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:eee9130eaad130649fd73e5cd92f60e55708952260ede70da64de420cdcad554"}, - {file = "regex-2024.9.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6a2644a93da36c784e546de579ec1806bfd2763ef47babc1b03d765fe560c9f8"}, - {file = "regex-2024.9.11-cp313-cp313-win32.whl", hash = "sha256:e997fd30430c57138adc06bba4c7c2968fb13d101e57dd5bb9355bf8ce3fa7e8"}, - {file = "regex-2024.9.11-cp313-cp313-win_amd64.whl", hash = "sha256:042c55879cfeb21a8adacc84ea347721d3d83a159da6acdf1116859e2427c43f"}, - {file = "regex-2024.9.11-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:35f4a6f96aa6cb3f2f7247027b07b15a374f0d5b912c0001418d1d55024d5cb4"}, - {file = "regex-2024.9.11-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:55b96e7ce3a69a8449a66984c268062fbaa0d8ae437b285428e12797baefce7e"}, - {file = "regex-2024.9.11-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:cb130fccd1a37ed894824b8c046321540263013da72745d755f2d35114b81a60"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:323c1f04be6b2968944d730e5c2091c8c89767903ecaa135203eec4565ed2b2b"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:be1c8ed48c4c4065ecb19d882a0ce1afe0745dfad8ce48c49586b90a55f02366"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b5b029322e6e7b94fff16cd120ab35a253236a5f99a79fb04fda7ae71ca20ae8"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f6fff13ef6b5f29221d6904aa816c34701462956aa72a77f1f151a8ec4f56aeb"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:587d4af3979376652010e400accc30404e6c16b7df574048ab1f581af82065e4"}, - {file = "regex-2024.9.11-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:079400a8269544b955ffa9e31f186f01d96829110a3bf79dc338e9910f794fca"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:f9268774428ec173654985ce55fc6caf4c6d11ade0f6f914d48ef4719eb05ebb"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:23f9985c8784e544d53fc2930fc1ac1a7319f5d5332d228437acc9f418f2f168"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:ae2941333154baff9838e88aa71c1d84f4438189ecc6021a12c7573728b5838e"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:e93f1c331ca8e86fe877a48ad64e77882c0c4da0097f2212873a69bbfea95d0c"}, - {file = "regex-2024.9.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:846bc79ee753acf93aef4184c040d709940c9d001029ceb7b7a52747b80ed2dd"}, - {file = "regex-2024.9.11-cp38-cp38-win32.whl", hash = "sha256:c94bb0a9f1db10a1d16c00880bdebd5f9faf267273b8f5bd1878126e0fbde771"}, - {file = "regex-2024.9.11-cp38-cp38-win_amd64.whl", hash = "sha256:2b08fce89fbd45664d3df6ad93e554b6c16933ffa9d55cb7e01182baaf971508"}, - {file = "regex-2024.9.11-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:07f45f287469039ffc2c53caf6803cd506eb5f5f637f1d4acb37a738f71dd066"}, - {file = "regex-2024.9.11-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4838e24ee015101d9f901988001038f7f0d90dc0c3b115541a1365fb439add62"}, - {file = "regex-2024.9.11-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:6edd623bae6a737f10ce853ea076f56f507fd7726bee96a41ee3d68d347e4d16"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c69ada171c2d0e97a4b5aa78fbb835e0ffbb6b13fc5da968c09811346564f0d3"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:02087ea0a03b4af1ed6ebab2c54d7118127fee8d71b26398e8e4b05b78963199"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:69dee6a020693d12a3cf892aba4808fe168d2a4cef368eb9bf74f5398bfd4ee8"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:297f54910247508e6e5cae669f2bc308985c60540a4edd1c77203ef19bfa63ca"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ecea58b43a67b1b79805f1a0255730edaf5191ecef84dbc4cc85eb30bc8b63b9"}, - {file = "regex-2024.9.11-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:eab4bb380f15e189d1313195b062a6aa908f5bd687a0ceccd47c8211e9cf0d4a"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:0cbff728659ce4bbf4c30b2a1be040faafaa9eca6ecde40aaff86f7889f4ab39"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:54c4a097b8bc5bb0dfc83ae498061d53ad7b5762e00f4adaa23bee22b012e6ba"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:73d6d2f64f4d894c96626a75578b0bf7d9e56dcda8c3d037a2118fdfe9b1c664"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:e53b5fbab5d675aec9f0c501274c467c0f9a5d23696cfc94247e1fb56501ed89"}, - {file = "regex-2024.9.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:0ffbcf9221e04502fc35e54d1ce9567541979c3fdfb93d2c554f0ca583a19b35"}, - {file = "regex-2024.9.11-cp39-cp39-win32.whl", hash = "sha256:e4c22e1ac1f1ec1e09f72e6c44d8f2244173db7eb9629cc3a346a8d7ccc31142"}, - {file = "regex-2024.9.11-cp39-cp39-win_amd64.whl", hash = "sha256:faa3c142464efec496967359ca99696c896c591c56c53506bac1ad465f66e919"}, - {file = "regex-2024.9.11.tar.gz", hash = "sha256:6c188c307e8433bcb63dc1915022deb553b4203a70722fc542c363bf120a01fd"}, + {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff590880083d60acc0433f9c3f713c51f7ac6ebb9adf889c79a261ecf541aa91"}, + {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:658f90550f38270639e83ce492f27d2c8d2cd63805c65a13a14d36ca126753f0"}, + {file = "regex-2024.11.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:164d8b7b3b4bcb2068b97428060b2a53be050085ef94eca7f240e7947f1b080e"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d3660c82f209655a06b587d55e723f0b813d3a7db2e32e5e7dc64ac2a9e86fde"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d22326fcdef5e08c154280b71163ced384b428343ae16a5ab2b3354aed12436e"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f1ac758ef6aebfc8943560194e9fd0fa18bcb34d89fd8bd2af18183afd8da3a2"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:997d6a487ff00807ba810e0f8332c18b4eb8d29463cfb7c820dc4b6e7562d0cf"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:02a02d2bb04fec86ad61f3ea7f49c015a0681bf76abb9857f945d26159d2968c"}, + {file = "regex-2024.11.6-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f02f93b92358ee3f78660e43b4b0091229260c5d5c408d17d60bf26b6c900e86"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:06eb1be98df10e81ebaded73fcd51989dcf534e3c753466e4b60c4697a003b67"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:040df6fe1a5504eb0f04f048e6d09cd7c7110fef851d7c567a6b6e09942feb7d"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fdabbfc59f2c6edba2a6622c647b716e34e8e3867e0ab975412c5c2f79b82da2"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8447d2d39b5abe381419319f942de20b7ecd60ce86f16a23b0698f22e1b70008"}, + {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:da8f5fc57d1933de22a9e23eec290a0d8a5927a5370d24bda9a6abe50683fe62"}, + {file = "regex-2024.11.6-cp310-cp310-win32.whl", hash = "sha256:b489578720afb782f6ccf2840920f3a32e31ba28a4b162e13900c3e6bd3f930e"}, + {file = "regex-2024.11.6-cp310-cp310-win_amd64.whl", hash = "sha256:5071b2093e793357c9d8b2929dfc13ac5f0a6c650559503bb81189d0a3814519"}, + {file = "regex-2024.11.6-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:5478c6962ad548b54a591778e93cd7c456a7a29f8eca9c49e4f9a806dcc5d638"}, + {file = "regex-2024.11.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2c89a8cc122b25ce6945f0423dc1352cb9593c68abd19223eebbd4e56612c5b7"}, + {file = "regex-2024.11.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:94d87b689cdd831934fa3ce16cc15cd65748e6d689f5d2b8f4f4df2065c9fa20"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1062b39a0a2b75a9c694f7a08e7183a80c63c0d62b301418ffd9c35f55aaa114"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:167ed4852351d8a750da48712c3930b031f6efdaa0f22fa1933716bfcd6bf4a3"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2d548dafee61f06ebdb584080621f3e0c23fff312f0de1afc776e2a2ba99a74f"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2a19f302cd1ce5dd01a9099aaa19cae6173306d1302a43b627f62e21cf18ac0"}, + {file = "regex-2024.11.6-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bec9931dfb61ddd8ef2ebc05646293812cb6b16b60cf7c9511a832b6f1854b55"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9714398225f299aa85267fd222f7142fcb5c769e73d7733344efc46f2ef5cf89"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:202eb32e89f60fc147a41e55cb086db2a3f8cb82f9a9a88440dcfc5d37faae8d"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:4181b814e56078e9b00427ca358ec44333765f5ca1b45597ec7446d3a1ef6e34"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:068376da5a7e4da51968ce4c122a7cd31afaaec4fccc7856c92f63876e57b51d"}, + {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ac10f2c4184420d881a3475fb2c6f4d95d53a8d50209a2500723d831036f7c45"}, + {file = "regex-2024.11.6-cp311-cp311-win32.whl", hash = "sha256:c36f9b6f5f8649bb251a5f3f66564438977b7ef8386a52460ae77e6070d309d9"}, + {file = "regex-2024.11.6-cp311-cp311-win_amd64.whl", hash = "sha256:02e28184be537f0e75c1f9b2f8847dc51e08e6e171c6bde130b2687e0c33cf60"}, + {file = "regex-2024.11.6-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:52fb28f528778f184f870b7cf8f225f5eef0a8f6e3778529bdd40c7b3920796a"}, + {file = "regex-2024.11.6-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fdd6028445d2460f33136c55eeb1f601ab06d74cb3347132e1c24250187500d9"}, + {file = "regex-2024.11.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:805e6b60c54bf766b251e94526ebad60b7de0c70f70a4e6210ee2891acb70bf2"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b85c2530be953a890eaffde05485238f07029600e8f098cdf1848d414a8b45e4"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bb26437975da7dc36b7efad18aa9dd4ea569d2357ae6b783bf1118dabd9ea577"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:abfa5080c374a76a251ba60683242bc17eeb2c9818d0d30117b4486be10c59d3"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70b7fa6606c2881c1db9479b0eaa11ed5dfa11c8d60a474ff0e095099f39d98e"}, + {file = "regex-2024.11.6-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0c32f75920cf99fe6b6c539c399a4a128452eaf1af27f39bce8909c9a3fd8cbe"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:982e6d21414e78e1f51cf595d7f321dcd14de1f2881c5dc6a6e23bbbbd68435e"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:a7c2155f790e2fb448faed6dd241386719802296ec588a8b9051c1f5c481bc29"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:149f5008d286636e48cd0b1dd65018548944e495b0265b45e1bffecce1ef7f39"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:e5364a4502efca094731680e80009632ad6624084aff9a23ce8c8c6820de3e51"}, + {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0a86e7eeca091c09e021db8eb72d54751e527fa47b8d5787caf96d9831bd02ad"}, + {file = "regex-2024.11.6-cp312-cp312-win32.whl", hash = "sha256:32f9a4c643baad4efa81d549c2aadefaeba12249b2adc5af541759237eee1c54"}, + {file = "regex-2024.11.6-cp312-cp312-win_amd64.whl", hash = "sha256:a93c194e2df18f7d264092dc8539b8ffb86b45b899ab976aa15d48214138e81b"}, + {file = "regex-2024.11.6-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:a6ba92c0bcdf96cbf43a12c717eae4bc98325ca3730f6b130ffa2e3c3c723d84"}, + {file = "regex-2024.11.6-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:525eab0b789891ac3be914d36893bdf972d483fe66551f79d3e27146191a37d4"}, + {file = "regex-2024.11.6-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:086a27a0b4ca227941700e0b31425e7a28ef1ae8e5e05a33826e17e47fbfdba0"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bde01f35767c4a7899b7eb6e823b125a64de314a8ee9791367c9a34d56af18d0"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b583904576650166b3d920d2bcce13971f6f9e9a396c673187f49811b2769dc7"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1c4de13f06a0d54fa0d5ab1b7138bfa0d883220965a29616e3ea61b35d5f5fc7"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3cde6e9f2580eb1665965ce9bf17ff4952f34f5b126beb509fee8f4e994f143c"}, + {file = "regex-2024.11.6-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d7f453dca13f40a02b79636a339c5b62b670141e63efd511d3f8f73fba162b3"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:59dfe1ed21aea057a65c6b586afd2a945de04fc7db3de0a6e3ed5397ad491b07"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:b97c1e0bd37c5cd7902e65f410779d39eeda155800b65fc4d04cc432efa9bc6e"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:f9d1e379028e0fc2ae3654bac3cbbef81bf3fd571272a42d56c24007979bafb6"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:13291b39131e2d002a7940fb176e120bec5145f3aeb7621be6534e46251912c4"}, + {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4f51f88c126370dcec4908576c5a627220da6c09d0bff31cfa89f2523843316d"}, + {file = "regex-2024.11.6-cp313-cp313-win32.whl", hash = "sha256:63b13cfd72e9601125027202cad74995ab26921d8cd935c25f09c630436348ff"}, + {file = "regex-2024.11.6-cp313-cp313-win_amd64.whl", hash = "sha256:2b3361af3198667e99927da8b84c1b010752fa4b1115ee30beaa332cabc3ef1a"}, + {file = "regex-2024.11.6-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:3a51ccc315653ba012774efca4f23d1d2a8a8f278a6072e29c7147eee7da446b"}, + {file = "regex-2024.11.6-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ad182d02e40de7459b73155deb8996bbd8e96852267879396fb274e8700190e3"}, + {file = "regex-2024.11.6-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:ba9b72e5643641b7d41fa1f6d5abda2c9a263ae835b917348fc3c928182ad467"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40291b1b89ca6ad8d3f2b82782cc33807f1406cf68c8d440861da6304d8ffbbd"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cdf58d0e516ee426a48f7b2c03a332a4114420716d55769ff7108c37a09951bf"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a36fdf2af13c2b14738f6e973aba563623cb77d753bbbd8d414d18bfaa3105dd"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d1cee317bfc014c2419a76bcc87f071405e3966da434e03e13beb45f8aced1a6"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:50153825ee016b91549962f970d6a4442fa106832e14c918acd1c8e479916c4f"}, + {file = "regex-2024.11.6-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ea1bfda2f7162605f6e8178223576856b3d791109f15ea99a9f95c16a7636fb5"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:df951c5f4a1b1910f1a99ff42c473ff60f8225baa1cdd3539fe2819d9543e9df"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:072623554418a9911446278f16ecb398fb3b540147a7828c06e2011fa531e773"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:f654882311409afb1d780b940234208a252322c24a93b442ca714d119e68086c"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:89d75e7293d2b3e674db7d4d9b1bee7f8f3d1609428e293771d1a962617150cc"}, + {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:f65557897fc977a44ab205ea871b690adaef6b9da6afda4790a2484b04293a5f"}, + {file = "regex-2024.11.6-cp38-cp38-win32.whl", hash = "sha256:6f44ec28b1f858c98d3036ad5d7d0bfc568bdd7a74f9c24e25f41ef1ebfd81a4"}, + {file = "regex-2024.11.6-cp38-cp38-win_amd64.whl", hash = "sha256:bb8f74f2f10dbf13a0be8de623ba4f9491faf58c24064f32b65679b021ed0001"}, + {file = "regex-2024.11.6-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:5704e174f8ccab2026bd2f1ab6c510345ae8eac818b613d7d73e785f1310f839"}, + {file = "regex-2024.11.6-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:220902c3c5cc6af55d4fe19ead504de80eb91f786dc102fbd74894b1551f095e"}, + {file = "regex-2024.11.6-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5e7e351589da0850c125f1600a4c4ba3c722efefe16b297de54300f08d734fbf"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5056b185ca113c88e18223183aa1a50e66507769c9640a6ff75859619d73957b"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2e34b51b650b23ed3354b5a07aab37034d9f923db2a40519139af34f485f77d0"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5670bce7b200273eee1840ef307bfa07cda90b38ae56e9a6ebcc9f50da9c469b"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:08986dce1339bc932923e7d1232ce9881499a0e02925f7402fb7c982515419ef"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:93c0b12d3d3bc25af4ebbf38f9ee780a487e8bf6954c115b9f015822d3bb8e48"}, + {file = "regex-2024.11.6-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:764e71f22ab3b305e7f4c21f1a97e1526a25ebdd22513e251cf376760213da13"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:f056bf21105c2515c32372bbc057f43eb02aae2fda61052e2f7622c801f0b4e2"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:69ab78f848845569401469da20df3e081e6b5a11cb086de3eed1d48f5ed57c95"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:86fddba590aad9208e2fa8b43b4c098bb0ec74f15718bb6a704e3c63e2cef3e9"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:684d7a212682996d21ca12ef3c17353c021fe9de6049e19ac8481ec35574a70f"}, + {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a03e02f48cd1abbd9f3b7e3586d97c8f7a9721c436f51a5245b3b9483044480b"}, + {file = "regex-2024.11.6-cp39-cp39-win32.whl", hash = "sha256:41758407fc32d5c3c5de163888068cfee69cb4c2be844e7ac517a52770f9af57"}, + {file = "regex-2024.11.6-cp39-cp39-win_amd64.whl", hash = "sha256:b2837718570f95dd41675328e111345f9b7095d821bac435aac173ac80b19983"}, + {file = "regex-2024.11.6.tar.gz", hash = "sha256:7ab159b063c52a0333c884e4679f8d7a85112ee3078fe3d9004b2dd875585519"}, ] [[package]] @@ -1483,104 +1659,110 @@ files = [ [[package]] name = "simsimd" -version = "5.2.1" -description = "Fastest SIMD-Accelerated Vector Similarity Functions for x86 and Arm" +version = "5.9.11" +description = "Portable mixed-precision BLAS-like vector math library for x86 and ARM" optional = false python-versions = "*" files = [ - {file = "simsimd-5.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c077d30656507812eb502b13da21d383f209729980e6f33775c005e54c834080"}, - {file = "simsimd-5.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:8a6489fd3251295e40ea646aef9bfd68488eef67f29f10acda185eca65cda48a"}, - {file = "simsimd-5.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:881401ab4aac969cfb1ba0301590fdf40cc53149dc0baa0556823b032a9213b6"}, - {file = "simsimd-5.2.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8f15689b58a79cd21d5975a4ce166d9fb01b59b8b509e76ef9f0eb77453cdaec"}, - {file = "simsimd-5.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2d249db978814a25a4c802c1eb24e82deca078d311da9952edd0e7cf28b8cb75"}, - {file = "simsimd-5.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:25cf244831e79ef4157fabf7e1390b7187f509850f3926fc7c49d16c0aa1a1f0"}, - {file = "simsimd-5.2.1-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:d7a146bc9271cef4a1543e9cdcabab0b0f5b8bccc3ef3d2277d5126ab285adca"}, - {file = "simsimd-5.2.1-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:8ce059db56c798f0647cd50fecac8f20f5ad609ad77ce644fc91373487dd3c37"}, - {file = "simsimd-5.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:face4052008d5c4b12dc6fc09d5ce0f39b81e6114c38b714695d52f4877e9953"}, - {file = "simsimd-5.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:cbc9774af40625033a5e6be90768154d1aef18f539b456e7691dc3576a31bcd5"}, - {file = "simsimd-5.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:6396ea925ae3fcaa6374684bff5049b87e76ad1888cf2e53d25767039144a360"}, - {file = "simsimd-5.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:9c802c21ca47072b7135ad5393af3231c6c15f27ee18fb7c9809f5251b5c478c"}, - {file = "simsimd-5.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:99f8e80d5758d1dba871d29adf9301e4d2d721902a8084e961247841fc4306a3"}, - {file = "simsimd-5.2.1-cp310-cp310-win32.whl", hash = "sha256:305ca88529a178dc2293337aa38ba733ad85f5e31e0c35111dabd77c45691718"}, - {file = "simsimd-5.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:305499b42baf559d0ddaaf5a8c14810ed9f11d248c19a16418ab88a6c7fb1c05"}, - {file = "simsimd-5.2.1-cp310-cp310-win_arm64.whl", hash = "sha256:a405c8bdaec9b9cd634a25e153994705fb22f4e2f674e0b3a1e349dd514d3b1e"}, - {file = "simsimd-5.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:9f342914fd54b90939a053d6ec6dde0b47131d39c2b2c3bfcf10acb9feac62be"}, - {file = "simsimd-5.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:44287add557bb4e78d249e3b076a37272c8ff62df379f4f837bf7d66534eae5d"}, - {file = "simsimd-5.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3cece60f867d54b15342aa421d561f26860fe70b93e0f13b9499718de3bf791b"}, - {file = "simsimd-5.2.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f02d7520b5f794ed1d8b1177214f263a06e334750fc6b4d8ba7bccfc0ea30d1d"}, - {file = "simsimd-5.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e3a288d5eac00a15df181354822f5714278d3b4123a5d8f1dcfc62fd1d2ffa9d"}, - {file = "simsimd-5.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c16dfc66f54b2ab95f74e3b1d886351ad65a69ab75041e069355b89f18e3ea36"}, - {file = "simsimd-5.2.1-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:78080b55b213117648038a657ad1437f465065077e79762ce04990b7cc4645dd"}, - {file = "simsimd-5.2.1-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:b7fb76b585194f040807aa40928515610d19ef0fb7d8bbb316dde17a05597b77"}, - {file = "simsimd-5.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a9f042fe6b8102b9e301c862aa655b1181cc73ebf589448ee2525c8c7023fd59"}, - {file = "simsimd-5.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:b5935ec1e4c62945972139f6ba6ca955e27d7781870fd89aab95c38e1614603c"}, - {file = "simsimd-5.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:07d77442a796b88ec984c2180f9c81ca912b11686f3e730a9648ff18644a136a"}, - {file = "simsimd-5.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e95dcbcd2931f51a449b664252746b1eba0dfc04715d14e9d79116000e13db3a"}, - {file = "simsimd-5.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:059c4b357d99757c8661d54141f4004fbb0ebbccf985cb39a1b630304af5fedf"}, - {file = "simsimd-5.2.1-cp311-cp311-win32.whl", hash = "sha256:0cf31a6fa6a62efd12d477f493411c1af1c64a7d61509ceebac593a83d1d4209"}, - {file = "simsimd-5.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:45d174f65ffe89020b01321a7f37404da8460c4800617fa5902ccc99b696ec9a"}, - {file = "simsimd-5.2.1-cp311-cp311-win_arm64.whl", hash = "sha256:6dc78085e112c0e36e6eeca546074cf8c56b2d80fba757bef8bebc444e61b72b"}, - {file = "simsimd-5.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:4936f92a6f25bf1b8cfd4069e850821e6ffe17addd997893d945994139cf1ec0"}, - {file = "simsimd-5.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:e16167789eb54c81ffdd0c1e185dd61df9a2fec6044067a047698b0af67865c0"}, - {file = "simsimd-5.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b04ba0570d9e258fd059a5f3964039e2fe6298d57363a9a9bb4ae0c000cd65a7"}, - {file = "simsimd-5.2.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5d4228bc8be42f9c9b6d59399303e9682f2edc9f2cc1550a3658ba8a9f0519a7"}, - {file = "simsimd-5.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9c3a80fdb3582d08f2da3d53daec73ea872fdac303529910aef71a774c1568bf"}, - {file = "simsimd-5.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5fbbc0068ef3daa85195508b25aa73562b07c3097fea1243aa2864e21dfd178d"}, - {file = "simsimd-5.2.1-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:3fe52c6b94f6777b0eca796a5751dbd4e55bae947d1906a00b31dd32f1a085f7"}, - {file = "simsimd-5.2.1-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:cdeda38843f4544e3cdc5687332ccd030ec9a3e10a47a7a63a9652ddc60f20ba"}, - {file = "simsimd-5.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8234b6a9308d5025a594413ca93b1e9dc4f9f9e2d4020af32529ed302570dacd"}, - {file = "simsimd-5.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:687725313925297aa36effac39013b1e31ed4d01764b5322bdc9eb0e73c51b6a"}, - {file = "simsimd-5.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:bb9aadd29b0def9d6d0811bd2e9fde1643e755aaf8d4010892c0e00f0e586477"}, - {file = "simsimd-5.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1df8520eac767584677367c598bd3c90abe0fa9ff49924eb289fea5b6fb6b2b3"}, - {file = "simsimd-5.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:f802b5435b9014fd2882641d45e279ff418c9bed83322957a99796fc6a9fae3d"}, - {file = "simsimd-5.2.1-cp312-cp312-win32.whl", hash = "sha256:271a5bb5daf3db37b4ca71c419ecc6c5c0d3a801cf4773907ae338aa34f18a1a"}, - {file = "simsimd-5.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:5d2a3ec2c3b90bd036823f16184d3fbfabc2a8fa9ba120f29cc3361ab3c68be8"}, - {file = "simsimd-5.2.1-cp312-cp312-win_arm64.whl", hash = "sha256:cf63293357013aa8d135d8f30443ce248223a53faf30e1e6d1464e559afd0b30"}, - {file = "simsimd-5.2.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:f95a7b56803e2ce952aa2476b7ed4ed5b8fe0f2c40daf14d6100bcd923282b99"}, - {file = "simsimd-5.2.1-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:01af17b95e1736f006177b3a84b6d25ec6068a2e0af97eed33f87c9d23684d0a"}, - {file = "simsimd-5.2.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bfef17e3a12f2c379d428bc4785637472b6a379e7122d3d227bbd5d9c20454ee"}, - {file = "simsimd-5.2.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ef288a2f89fe4b00c65f16895519da78c443d2e75080a8067b9d83196e911592"}, - {file = "simsimd-5.2.1-cp37-cp37m-manylinux_2_28_aarch64.whl", hash = "sha256:82fe3f4a70e79eb7a17cfac8b129fe0e0ea63408513091618703b85a6c90db00"}, - {file = "simsimd-5.2.1-cp37-cp37m-manylinux_2_28_x86_64.whl", hash = "sha256:035487a05b923541c3c524af56472f4121f14cb9a6761ae0d0d9101da077fe7a"}, - {file = "simsimd-5.2.1-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:0b1fe4154cb9622a3640b81d05d07276c785ada6ac59512160624f4f2225b8cc"}, - {file = "simsimd-5.2.1-cp37-cp37m-musllinux_1_2_i686.whl", hash = "sha256:b55bc8fd307f7cb8fa2bd76ae0bdd4a196b7e92ae592d08bc151991357aa636e"}, - {file = "simsimd-5.2.1-cp37-cp37m-musllinux_1_2_ppc64le.whl", hash = "sha256:d8e5075a8798b7641fd394dd7fbda5c7be349f5616780076d8a5cf826f29fc5f"}, - {file = "simsimd-5.2.1-cp37-cp37m-musllinux_1_2_s390x.whl", hash = "sha256:c310dda98e8cc56fc856f369fe6a925bbde72ca33c735808037cc7300edad5c9"}, - {file = "simsimd-5.2.1-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:81c052de76ccc31df39ee6a2929495fa386fcc2f8bd96512de50f10365c1434a"}, - {file = "simsimd-5.2.1-cp37-cp37m-win32.whl", hash = "sha256:b2dd417556d22be66a1f8bb8fe2a8222655c97382d2736802100ec2b658bf179"}, - {file = "simsimd-5.2.1-cp37-cp37m-win_amd64.whl", hash = "sha256:309a6a29e8213d7af603cdd0a30e7500f3ef3f5caafa17d1cb131f9a45faafb6"}, - {file = "simsimd-5.2.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:1500bf3e6728c98e01efd4e8b03ac27d5451a92c8cd00cd2c80314e0fef37f12"}, - {file = "simsimd-5.2.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:e2124f8928be3e63e253d349e0063d2e2e9c2959143425f383f7302d46e3588c"}, - {file = "simsimd-5.2.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:614828d03eca528cf0aebaa7aec24e774256f806c1feb4353bdeedaad8eb8b12"}, - {file = "simsimd-5.2.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4a983fef4c490c547babff1b99dbcc7ffac604157b5948b84532bbaf27e5359e"}, - {file = "simsimd-5.2.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:70eb039199b9c360ac7f081a1cccc34a1ef849653ea3dabe0c2a51cf014ae36e"}, - {file = "simsimd-5.2.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e77360121c0d3522d937c43a93ed5bc359ab05826c6b1443980536bf31966b90"}, - {file = "simsimd-5.2.1-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:72e7d2c04d8b66642558eaa09e36bbdcb2c818ad0b8116f318122635c0512493"}, - {file = "simsimd-5.2.1-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:510aa97c25ddae310a3ea6e818f161c5a9a178624a75f4d1c62d1898dba9537d"}, - {file = "simsimd-5.2.1-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:cf9d37d1dbd26e6e2c30d4410d007ecdb4a588ef316a50e257ada67fc1d7512b"}, - {file = "simsimd-5.2.1-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:9426ee74d6898f8cbd4ef6735216428c445367c2042a1573da9e0b327cbc0d7e"}, - {file = "simsimd-5.2.1-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:ce298323cf4b35cf652a11a45889df277a1e4ef58bc298baf6cccec938de4827"}, - {file = "simsimd-5.2.1-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:beb76cdb6a5442be351a4dcbaf35bc51e6e815e37b7cda3c27886c9de0112ed8"}, - {file = "simsimd-5.2.1-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:d9ba0b406a658053b9e4cc989881e055dbe419bfd0ef626a2f2d2d48ff9db879"}, - {file = "simsimd-5.2.1-cp38-cp38-win32.whl", hash = "sha256:7d465e56848ff733725dbc6e2f4c79ee7073f695006013c9d0aff6daa6a750cf"}, - {file = "simsimd-5.2.1-cp38-cp38-win_amd64.whl", hash = "sha256:c0f37b3c5963792925795f22ab90405df243e2738ec5b857ec5114a29facab38"}, - {file = "simsimd-5.2.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:095b143ff85fe57beec75783d48878a2c821fa249dd26c5f98521ecf6edfc77c"}, - {file = "simsimd-5.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b576df0679f5d92299f7b33ff28342cae154d46f3bfb0171253ad4cdcf8fc07a"}, - {file = "simsimd-5.2.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:9ba17ad2fdf6543f5b4091b4d94413d60760e44b1ebbff9c661d44c6ce642296"}, - {file = "simsimd-5.2.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:53cbb3b5202a06a5ffaef5d2a006b0a4f345f630951b9b2b9abada3cc279a532"}, - {file = "simsimd-5.2.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5fb49bb7cab159a625f9c2c1b0a236ce2d0c0bb217a63e36d46d6122c44d1b2f"}, - {file = "simsimd-5.2.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c8056abac0fd86e7d864bc59e75bd750e796e67aa55cb9a2f58b3f8ec3a71c6b"}, - {file = "simsimd-5.2.1-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:d02be0a65bbe5ead9fdfefd18f0babb27b4856ad02d3ff4b8b0126223288588a"}, - {file = "simsimd-5.2.1-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:2f1afeeedb6639628a94dcc4f7d01d670f43f4b10909c96876837c311b8f11d7"}, - {file = "simsimd-5.2.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:6f9ed03113216707f74381324b57105afad8fbd12323f474830c0929750631d1"}, - {file = "simsimd-5.2.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:818f3bd2893be61a5484a981ec262162ef480f06bfffd9686ddeab4b59d75d3f"}, - {file = "simsimd-5.2.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:c2cab5afce104f35cdb1b82c20b3c29e04f19d3ac73961316e6f065b7ef072e9"}, - {file = "simsimd-5.2.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:d20a5c7343e86daeb869ea5e2c9d5ca8c358bc7370288176ef04157fea5bad27"}, - {file = "simsimd-5.2.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:b23ffe97bb938803bf367f2de25ca971033be00774fbbf09426147a89fcc5dc4"}, - {file = "simsimd-5.2.1-cp39-cp39-win32.whl", hash = "sha256:8e942cc946b813937ae99ca3ea3d20ec68aaddc173904c298d65eee75d7d08a3"}, - {file = "simsimd-5.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:8d290c7361d9c8a87f6408d4ff7799c7df8278ac28d41e9ed68d252040854ca4"}, - {file = "simsimd-5.2.1-cp39-cp39-win_arm64.whl", hash = "sha256:6159540ba7ed5b9e8e34d340943e31f7791b2c49436d299969014be9869da350"}, - {file = "simsimd-5.2.1.tar.gz", hash = "sha256:716f607e06c9570288db42f2bb9661dadd79188874dba1c7df71d8efec4ecbb8"}, + {file = "simsimd-5.9.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:84a534ccd04d7aa5c4539817e09f94c5c5d4bfee9d72078b89b7e18c811100ac"}, + {file = "simsimd-5.9.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:323468e396f94eda2494df6b85214f6e4b16812e28cab5eab5ced507aa7221de"}, + {file = "simsimd-5.9.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f142bbefed325ac74d7209044b2fa777a6737a907fbd39359db6c72271204cfa"}, + {file = "simsimd-5.9.11-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:59a89ea757ef18014a56c16096cd80e85ec5f2d71d23068d751747e6154229d4"}, + {file = "simsimd-5.9.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f12d43eaab7bae5ae3e9f0fcbbbe8811eb1e28bb9b7bb68b8a78c8afdcca16f3"}, + {file = "simsimd-5.9.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ca73c0161f47681a2b5e266dfe5fee5b75bc0c0093b978641dd672f38c9c8abf"}, + {file = "simsimd-5.9.11-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:856d59a644e3208512895aa19c52d3fa28f7359ccc6a526c99ec40a0c94d014c"}, + {file = "simsimd-5.9.11-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:79a2a722ccce98375a3ff7033ad21a323b03f41032b004d43817a81baf873b53"}, + {file = "simsimd-5.9.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:de94d6457949888f17a94ddf165f179ca4f8b83cc9eaedf9a97daeddceae829d"}, + {file = "simsimd-5.9.11-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:ecec772486848ccf52e076781591f467c339c6b19dcf66720f8d5b0ede47717d"}, + {file = "simsimd-5.9.11-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:a8a211130e8499c60463b77208f51bee04ddb8d3dfece7371bb5e5b878105cdc"}, + {file = "simsimd-5.9.11-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fb7b5c3348a8ba2c4f8dbc16925e83ac4556ff7c98a086008c77d7ee192449b0"}, + {file = "simsimd-5.9.11-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:accaf43fdc9a32c5fb3cc501af91e8a6eb4443f871598f66282e83e705096627"}, + {file = "simsimd-5.9.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:a2b2113f6cee7882f58adab0a7b8939075938addb77df28f5c4f5f88a38a4150"}, + {file = "simsimd-5.9.11-cp310-cp310-win32.whl", hash = "sha256:3b9b112bd2d3f4579b7946463ccaa245cae21ac673c19401b8655ed0984b08dc"}, + {file = "simsimd-5.9.11-cp310-cp310-win_amd64.whl", hash = "sha256:b5030de0fa780e2f33b7b9fc176cea6455205c275bb23fba952c4f25a87fa30e"}, + {file = "simsimd-5.9.11-cp310-cp310-win_arm64.whl", hash = "sha256:a1429f7c48ac6743414e6877554ed18d62e03338162bcc506218869467790ed0"}, + {file = "simsimd-5.9.11-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:dc3161c6e2f966b06b407ca16a01157e4f62aeb54849102b2381c75afe96de63"}, + {file = "simsimd-5.9.11-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6a2e1b942270c0e13a242980f6ee28791cbef68842b1365510422e3f3b1108e5"}, + {file = "simsimd-5.9.11-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a77dd15b362f71ea95ff9a4eba895d34740261ff56092303e18c7b5584b86eb4"}, + {file = "simsimd-5.9.11-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:79f0f9a2aaea47b7feda669592d40c41a3c803d9207ecb96b551e2b10badeb61"}, + {file = "simsimd-5.9.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3976480e40074dd8ab2e327b0620791f37f88958e23659848d65e9eaee075d69"}, + {file = "simsimd-5.9.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7a925d2ced1d55bb994a77d563cc1cd9be6b628e555d55782ff4844fd2eff40e"}, + {file = "simsimd-5.9.11-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:2f08648184772dde6286a532f4034b56be62407d2240f0fa50e9896dd269fd9f"}, + {file = "simsimd-5.9.11-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:c9073d17f1ec774c3be6f3ae2bb6022cf329961ead6a53540a852f58a56d80f1"}, + {file = "simsimd-5.9.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:f318c4aaf8d8fbe168da6bab406a598e8a8710509bcfdb758d4f27ee66991d19"}, + {file = "simsimd-5.9.11-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:332c1abf09ffbc56e8ffa0d4fe91e6505dcc6fe8a4c3212922d7e45047b55210"}, + {file = "simsimd-5.9.11-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:f48db0b476dc4f3805cd83050483a3eda59b2c1e4861ca634382c0135d5848c3"}, + {file = "simsimd-5.9.11-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31f5e8b8210ac600910fa0631f094c54564e363ee72881194578ba2630721fce"}, + {file = "simsimd-5.9.11-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:32f0980848ca322fa81f8e9b73291ab780c24fdb23ad976668967830c99cfe09"}, + {file = "simsimd-5.9.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:866adcbfb93840e5b1915e834afda3b244fda8895aa3bdc96bbd0d51f24898f7"}, + {file = "simsimd-5.9.11-cp311-cp311-win32.whl", hash = "sha256:4b4f77da77016b8f7c2ccc8c2203d7f59112b471dc3ee047fdce72fb63f63647"}, + {file = "simsimd-5.9.11-cp311-cp311-win_amd64.whl", hash = "sha256:706e5db8f9b5d3fea9cbf549323c57ef8529d4536cf66784ab7926fb31c3f3d3"}, + {file = "simsimd-5.9.11-cp311-cp311-win_arm64.whl", hash = "sha256:605af1cf0d903f31dc488a94e2e6734d3047baa41d40b362fb3285144b383f63"}, + {file = "simsimd-5.9.11-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:b614a22531f35f9dc752c09da96cc3457f15c5d0ca3e2a12d13d54d2441a476d"}, + {file = "simsimd-5.9.11-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:95f984148040fd6ffec3bdd8ad68a1750c5bda16c226ff14ccdfc1439705a3b4"}, + {file = "simsimd-5.9.11-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:46afcd0b7b59fefffdfb91b0e83e881e56b536acb072343cf73d49fbad83bb8d"}, + {file = "simsimd-5.9.11-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:cc6286d20cf837d26a3943504eecb4db5b68046c06797ac125fbad6b5134ee3e"}, + {file = "simsimd-5.9.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7be158270caeb2e3daf616e052690a5bea41c81b9007d46d0746aee605001616"}, + {file = "simsimd-5.9.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e8d2e9f0e7d2b790ceaab1e6860de1026549a20995d93c55d81c590af4df8e82"}, + {file = "simsimd-5.9.11-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:d55e497ac4f30c31cb3046f81d18855e007d12ff1673437bac1e1a8c017f67d6"}, + {file = "simsimd-5.9.11-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:42c575afe5f9a8195ff86c4fc019972a373c1a3dd08b2263a3e4fc9f3dd9f3a0"}, + {file = "simsimd-5.9.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:c3467413ba3343d683f1f40ed48f424ecb1f4f21dcb4d4aa0fab93790a75f375"}, + {file = "simsimd-5.9.11-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:a65aad00bbae4a7c28383a925e61f5d43edfeed8afc494e1533e5670b6d74900"}, + {file = "simsimd-5.9.11-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:344d4e276d40eeaf6c724ce3aa309204c49bbc4d64c45e961861053d46557e3f"}, + {file = "simsimd-5.9.11-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:d4b7adf20cee0850937550faa1031fc6de5ab2a60d75242608e72809f308c98c"}, + {file = "simsimd-5.9.11-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:36bac4397b6d50dbc63be3fab6bb2d93256c892384b0bbb0ca7eeb9fc1386a60"}, + {file = "simsimd-5.9.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:32f52284c56ed1631054b679151663febeca4a0d265fb11b2d09450e51a80108"}, + {file = "simsimd-5.9.11-cp312-cp312-win32.whl", hash = "sha256:be5cf7833bebdb520fd2a81875ba8740921baba9e0d4ba123041f6b8c358c407"}, + {file = "simsimd-5.9.11-cp312-cp312-win_amd64.whl", hash = "sha256:845172ff6358b285c77311964170e7b50b4de953f8d9f760c8c641cac964966a"}, + {file = "simsimd-5.9.11-cp312-cp312-win_arm64.whl", hash = "sha256:e36a24f31553f86550f6fb3da622c083565d4de7c400bfa80032dd556ae0c2a3"}, + {file = "simsimd-5.9.11-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:db2134d102f5495a7af97e5544c243b8ea9d25ab1c9f4b5ad9145b9fb07f95c9"}, + {file = "simsimd-5.9.11-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b6e4803b336f787c45be7da6f28a39ce923b6a868271ea4037e7bd4bc8835478"}, + {file = "simsimd-5.9.11-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e8478b76b301da67cbdeb59b839f913461aa3321a1e56ea12c8cfa43277054d6"}, + {file = "simsimd-5.9.11-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1e46bd11836155f262797fb6e570e958b251ee7a9c6bc708150d1f4e7cd89721"}, + {file = "simsimd-5.9.11-cp37-cp37m-manylinux_2_28_aarch64.whl", hash = "sha256:2e8dc07459cf45447c2f23ba793125410af9925fdc5ef5ef2aff6f373bb60358"}, + {file = "simsimd-5.9.11-cp37-cp37m-manylinux_2_28_x86_64.whl", hash = "sha256:f69c0bf41e8b7782f7dbf1902a35f1c48a62c9bcb957755ad70ecc6a5ffac6a3"}, + {file = "simsimd-5.9.11-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:2d1e8610fe233a480cea6a5acf8b67d291cfe854cf5ead867b62e5569b57d849"}, + {file = "simsimd-5.9.11-cp37-cp37m-musllinux_1_2_armv7l.whl", hash = "sha256:574e6475b8632a1e19cff9f8bcf18ae0d7506f22b1a7640bd5ca0c4c86aa69d3"}, + {file = "simsimd-5.9.11-cp37-cp37m-musllinux_1_2_i686.whl", hash = "sha256:7624ebc619325aa9167476b2889fbee9edbbaf93d77608c1b79868029d82f222"}, + {file = "simsimd-5.9.11-cp37-cp37m-musllinux_1_2_ppc64le.whl", hash = "sha256:2c6fef446ed48d3d0d9a8f2d296f477c5f667bff38bcaa78247c4c7c5b3ce605"}, + {file = "simsimd-5.9.11-cp37-cp37m-musllinux_1_2_s390x.whl", hash = "sha256:d120fbb350ec7287c399583dec6c0483ed897bcc099f877b708588ecdbfa75e9"}, + {file = "simsimd-5.9.11-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:36317c91ae2703ba5415c76bf7a55f6d54a79dbc722f167789f652d5a6b0322e"}, + {file = "simsimd-5.9.11-cp37-cp37m-win32.whl", hash = "sha256:73c67472f8a052522e15fe4c1fe35cd7f37686193452a2cb5d5303780f21a340"}, + {file = "simsimd-5.9.11-cp37-cp37m-win_amd64.whl", hash = "sha256:2aee5a1a1b6528088fa18eeda9357de0b21f635c341f05af4ad684dfb601d2e3"}, + {file = "simsimd-5.9.11-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:d45725cc3797fd02be2bf8770dcfbd0c2eadef114c3960fb6924a765309549e0"}, + {file = "simsimd-5.9.11-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:a32b58753ff7956649253da75fc68382ddea99b19bef9df56d4b1726ff0a8d94"}, + {file = "simsimd-5.9.11-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:aa9fc6c397ba9f31320d8b9b30068b0bb2857c09a6a01cf2e70892ec18b8012b"}, + {file = "simsimd-5.9.11-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:825ad3c69e306ab35bff789acd2db5d6294852487a7ffa6179e14ecbed4c5316"}, + {file = "simsimd-5.9.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2dd1a635f6e6b682ac594c02eb683f14b2052fbcc0d4ccdf4307c24b1130252a"}, + {file = "simsimd-5.9.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2297b60d61af009118ff769bda4d778ee5dfb7b557f177396297a5cda998ee1b"}, + {file = "simsimd-5.9.11-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:db2c103ca7a07f2021157e621db113bf5a5f5a6d32b11702aedca4b4054ae18c"}, + {file = "simsimd-5.9.11-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:b9ec8271d3fa7f9b70ed39d3709a721fd5d94c2aa35767f06f7d908c7a55001e"}, + {file = "simsimd-5.9.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:230f0df6a887313dad4626e657c7e44e5bc7279eddbdaf74e2e94c5862ccdd43"}, + {file = "simsimd-5.9.11-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:aee92d573d54b9c985000cfbdcabda57cb0fe42ae678dd21f5475e1abd5b6739"}, + {file = "simsimd-5.9.11-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:e42e725b040b97f318f2bba489c583ef4ff872987018461ebc2284c8b32ea96a"}, + {file = "simsimd-5.9.11-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:587638a18d9ed36df03a3c728a7fe10b7e79785fc3ce866a35fd58dce9e1f22f"}, + {file = "simsimd-5.9.11-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:70788a80e399afcc787da4ff502f62e04339805b1f2e364f31d6529ee2de03da"}, + {file = "simsimd-5.9.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:9a4770ac29c2c02e5d02fbd7125bc7365f008d08f06933559a4c4286e20531a2"}, + {file = "simsimd-5.9.11-cp38-cp38-win32.whl", hash = "sha256:ab572de6a37435c475daa6e5deacc829cb79e028dd7269f463bf51c420e34bc0"}, + {file = "simsimd-5.9.11-cp38-cp38-win_amd64.whl", hash = "sha256:0f976b8e3341ee3099ff247a2bed8e82beec7e74ef634b99b51945e33fab28b7"}, + {file = "simsimd-5.9.11-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:8e4fef000c8bd3603f5e6884dba5aaf2909ca170be99f41516ef304fcbc9411e"}, + {file = "simsimd-5.9.11-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3b2bf459923688974ab090e5b67b595aa2d9074c6e3d5cc2e70ca57e2c325b01"}, + {file = "simsimd-5.9.11-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:d5b0a270566ec15d43ce43b1f2b913db3ddd16d230772c29ff2f0402ecffc3d7"}, + {file = "simsimd-5.9.11-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b4fba6dfba372229683b7f78b7ff6892601c2eacd861e66e4d84bfa638bd75ed"}, + {file = "simsimd-5.9.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:362ba4aa418460e8f1e3a2cd13b8dd274525dffc0b26c5a4e75cacf14e8af45b"}, + {file = "simsimd-5.9.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c6cb96639886e69cb1772579536d21204461b775f2383250f5ce5c1e575ad300"}, + {file = "simsimd-5.9.11-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:71ca186e4209e14b2c9ed856e7d831cacf53d6855993eef3417adb030604011b"}, + {file = "simsimd-5.9.11-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:75fca4eb8a0a8ba9058039c0ff30e77ad4d7d5d997340676a0c2c7c62e6d3bd7"}, + {file = "simsimd-5.9.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:f84adb867f09bea8cc30ca415b2d5716783645e9fb1607ac65492ed8e8efec22"}, + {file = "simsimd-5.9.11-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:d64e680c8bd3430f0d74f8f20e0e8e98c5c7631e0d31a3f5cb9700149d647300"}, + {file = "simsimd-5.9.11-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:841447f583b11045bfd4e1427aeeee00678d12f67ddd218cb7614f96898bee5f"}, + {file = "simsimd-5.9.11-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:ba227f65df3bed228843f6226d0a55682fc1c58bfb68c6dda4bad394dfbbf535"}, + {file = "simsimd-5.9.11-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:b7727c80524768548122eecd5107229e7c1958e97bc666057ce8356703c805a1"}, + {file = "simsimd-5.9.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:3244d8cbc12d2fbc0daf59df7160242871755daabd8cc01e0c905cbdfebbbb1b"}, + {file = "simsimd-5.9.11-cp39-cp39-win32.whl", hash = "sha256:2a1ffe93e781a292f1b1d34b47fbabe82414212e8cb97340428cfe4e800b72c8"}, + {file = "simsimd-5.9.11-cp39-cp39-win_amd64.whl", hash = "sha256:86f24a980c2ac10ad8e6341281c86bc769f84c30f633ba8213d7ee046bbe9599"}, + {file = "simsimd-5.9.11-cp39-cp39-win_arm64.whl", hash = "sha256:0c63ddf5ad90ae2c80309e7763a2d4306738e19f31b614f1cc6d0f784199350a"}, + {file = "simsimd-5.9.11.tar.gz", hash = "sha256:053c034c73aa291cc9189ce90f49ca6c5d4e0b30e4d990a25965c2f516d4a21a"}, ] [[package]] @@ -1607,13 +1789,13 @@ files = [ [[package]] name = "syrupy" -version = "4.7.1" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.1-py3-none-any.whl", hash = "sha256:be002267a512a4bedddfae2e026c93df1ea928ae10baadc09640516923376d41"}, - {file = "syrupy-4.7.1.tar.gz", hash = "sha256:f9d4485f3f27d0e5df6ed299cac6fa32eb40a441915d988e82be5a4bdda335c8"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -1621,13 +1803,13 @@ pytest = ">=7.0.0,<9.0.0" [[package]] name = "tenacity" -version = "8.5.0" +version = "9.0.0" description = "Retry code until it succeeds" optional = false python-versions = ">=3.8" files = [ - {file = "tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687"}, - {file = "tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78"}, + {file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"}, + {file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"}, ] [package.extras] @@ -1636,47 +1818,42 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tiktoken" -version = "0.7.0" +version = "0.8.0" description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "tiktoken-0.7.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:485f3cc6aba7c6b6ce388ba634fbba656d9ee27f766216f45146beb4ac18b25f"}, - {file = "tiktoken-0.7.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e54be9a2cd2f6d6ffa3517b064983fb695c9a9d8aa7d574d1ef3c3f931a99225"}, - {file = "tiktoken-0.7.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:79383a6e2c654c6040e5f8506f3750db9ddd71b550c724e673203b4f6b4b4590"}, - {file = "tiktoken-0.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5d4511c52caacf3c4981d1ae2df85908bd31853f33d30b345c8b6830763f769c"}, - {file = "tiktoken-0.7.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:13c94efacdd3de9aff824a788353aa5749c0faee1fbe3816df365ea450b82311"}, - {file = "tiktoken-0.7.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8e58c7eb29d2ab35a7a8929cbeea60216a4ccdf42efa8974d8e176d50c9a3df5"}, - {file = "tiktoken-0.7.0-cp310-cp310-win_amd64.whl", hash = "sha256:21a20c3bd1dd3e55b91c1331bf25f4af522c525e771691adbc9a69336fa7f702"}, - {file = "tiktoken-0.7.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:10c7674f81e6e350fcbed7c09a65bca9356eaab27fb2dac65a1e440f2bcfe30f"}, - {file = "tiktoken-0.7.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:084cec29713bc9d4189a937f8a35dbdfa785bd1235a34c1124fe2323821ee93f"}, - {file = "tiktoken-0.7.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:811229fde1652fedcca7c6dfe76724d0908775b353556d8a71ed74d866f73f7b"}, - {file = "tiktoken-0.7.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:86b6e7dc2e7ad1b3757e8a24597415bafcfb454cebf9a33a01f2e6ba2e663992"}, - {file = "tiktoken-0.7.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1063c5748be36344c7e18c7913c53e2cca116764c2080177e57d62c7ad4576d1"}, - {file = "tiktoken-0.7.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:20295d21419bfcca092644f7e2f2138ff947a6eb8cfc732c09cc7d76988d4a89"}, - {file = "tiktoken-0.7.0-cp311-cp311-win_amd64.whl", hash = "sha256:959d993749b083acc57a317cbc643fb85c014d055b2119b739487288f4e5d1cb"}, - {file = "tiktoken-0.7.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:71c55d066388c55a9c00f61d2c456a6086673ab7dec22dd739c23f77195b1908"}, - {file = "tiktoken-0.7.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:09ed925bccaa8043e34c519fbb2f99110bd07c6fd67714793c21ac298e449410"}, - {file = "tiktoken-0.7.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:03c6c40ff1db0f48a7b4d2dafeae73a5607aacb472fa11f125e7baf9dce73704"}, - {file = "tiktoken-0.7.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d20b5c6af30e621b4aca094ee61777a44118f52d886dbe4f02b70dfe05c15350"}, - {file = "tiktoken-0.7.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d427614c3e074004efa2f2411e16c826f9df427d3c70a54725cae860f09e4bf4"}, - {file = "tiktoken-0.7.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8c46d7af7b8c6987fac9b9f61041b452afe92eb087d29c9ce54951280f899a97"}, - {file = "tiktoken-0.7.0-cp312-cp312-win_amd64.whl", hash = "sha256:0bc603c30b9e371e7c4c7935aba02af5994a909fc3c0fe66e7004070858d3f8f"}, - {file = "tiktoken-0.7.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2398fecd38c921bcd68418675a6d155fad5f5e14c2e92fcf5fe566fa5485a858"}, - {file = "tiktoken-0.7.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:8f5f6afb52fb8a7ea1c811e435e4188f2bef81b5e0f7a8635cc79b0eef0193d6"}, - {file = "tiktoken-0.7.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:861f9ee616766d736be4147abac500732b505bf7013cfaf019b85892637f235e"}, - {file = "tiktoken-0.7.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:54031f95c6939f6b78122c0aa03a93273a96365103793a22e1793ee86da31685"}, - {file = "tiktoken-0.7.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:fffdcb319b614cf14f04d02a52e26b1d1ae14a570f90e9b55461a72672f7b13d"}, - {file = "tiktoken-0.7.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c72baaeaefa03ff9ba9688624143c858d1f6b755bb85d456d59e529e17234769"}, - {file = "tiktoken-0.7.0-cp38-cp38-win_amd64.whl", hash = "sha256:131b8aeb043a8f112aad9f46011dced25d62629091e51d9dc1adbf4a1cc6aa98"}, - {file = "tiktoken-0.7.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:cabc6dc77460df44ec5b879e68692c63551ae4fae7460dd4ff17181df75f1db7"}, - {file = "tiktoken-0.7.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8d57f29171255f74c0aeacd0651e29aa47dff6f070cb9f35ebc14c82278f3b25"}, - {file = "tiktoken-0.7.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2ee92776fdbb3efa02a83f968c19d4997a55c8e9ce7be821ceee04a1d1ee149c"}, - {file = "tiktoken-0.7.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e215292e99cb41fbc96988ef62ea63bb0ce1e15f2c147a61acc319f8b4cbe5bf"}, - {file = "tiktoken-0.7.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:8a81bac94769cab437dd3ab0b8a4bc4e0f9cf6835bcaa88de71f39af1791727a"}, - {file = "tiktoken-0.7.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:d6d73ea93e91d5ca771256dfc9d1d29f5a554b83821a1dc0891987636e0ae226"}, - {file = "tiktoken-0.7.0-cp39-cp39-win_amd64.whl", hash = "sha256:2bcb28ddf79ffa424f171dfeef9a4daff61a94c631ca6813f43967cb263b83b9"}, - {file = "tiktoken-0.7.0.tar.gz", hash = "sha256:1077266e949c24e0291f6c350433c6f0971365ece2b173a23bc3b9f9defef6b6"}, + {file = "tiktoken-0.8.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b07e33283463089c81ef1467180e3e00ab00d46c2c4bbcef0acab5f771d6695e"}, + {file = "tiktoken-0.8.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9269348cb650726f44dd3bbb3f9110ac19a8dcc8f54949ad3ef652ca22a38e21"}, + {file = "tiktoken-0.8.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25e13f37bc4ef2d012731e93e0fef21dc3b7aea5bb9009618de9a4026844e560"}, + {file = "tiktoken-0.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f13d13c981511331eac0d01a59b5df7c0d4060a8be1e378672822213da51e0a2"}, + {file = "tiktoken-0.8.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:6b2ddbc79a22621ce8b1166afa9f9a888a664a579350dc7c09346a3b5de837d9"}, + {file = "tiktoken-0.8.0-cp310-cp310-win_amd64.whl", hash = "sha256:d8c2d0e5ba6453a290b86cd65fc51fedf247e1ba170191715b049dac1f628005"}, + {file = "tiktoken-0.8.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d622d8011e6d6f239297efa42a2657043aaed06c4f68833550cac9e9bc723ef1"}, + {file = "tiktoken-0.8.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2efaf6199717b4485031b4d6edb94075e4d79177a172f38dd934d911b588d54a"}, + {file = "tiktoken-0.8.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5637e425ce1fc49cf716d88df3092048359a4b3bbb7da762840426e937ada06d"}, + {file = "tiktoken-0.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fb0e352d1dbe15aba082883058b3cce9e48d33101bdaac1eccf66424feb5b47"}, + {file = "tiktoken-0.8.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:56edfefe896c8f10aba372ab5706b9e3558e78db39dd497c940b47bf228bc419"}, + {file = "tiktoken-0.8.0-cp311-cp311-win_amd64.whl", hash = "sha256:326624128590def898775b722ccc327e90b073714227175ea8febbc920ac0a99"}, + {file = "tiktoken-0.8.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:881839cfeae051b3628d9823b2e56b5cc93a9e2efb435f4cf15f17dc45f21586"}, + {file = "tiktoken-0.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:fe9399bdc3f29d428f16a2f86c3c8ec20be3eac5f53693ce4980371c3245729b"}, + {file = "tiktoken-0.8.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9a58deb7075d5b69237a3ff4bb51a726670419db6ea62bdcd8bd80c78497d7ab"}, + {file = "tiktoken-0.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d2908c0d043a7d03ebd80347266b0e58440bdef5564f84f4d29fb235b5df3b04"}, + {file = "tiktoken-0.8.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:294440d21a2a51e12d4238e68a5972095534fe9878be57d905c476017bff99fc"}, + {file = "tiktoken-0.8.0-cp312-cp312-win_amd64.whl", hash = "sha256:d8f3192733ac4d77977432947d563d7e1b310b96497acd3c196c9bddb36ed9db"}, + {file = "tiktoken-0.8.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:02be1666096aff7da6cbd7cdaa8e7917bfed3467cd64b38b1f112e96d3b06a24"}, + {file = "tiktoken-0.8.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:c94ff53c5c74b535b2cbf431d907fc13c678bbd009ee633a2aca269a04389f9a"}, + {file = "tiktoken-0.8.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b231f5e8982c245ee3065cd84a4712d64692348bc609d84467c57b4b72dcbc5"}, + {file = "tiktoken-0.8.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4177faa809bd55f699e88c96d9bb4635d22e3f59d635ba6fd9ffedf7150b9953"}, + {file = "tiktoken-0.8.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5376b6f8dc4753cd81ead935c5f518fa0fbe7e133d9e25f648d8c4dabdd4bad7"}, + {file = "tiktoken-0.8.0-cp313-cp313-win_amd64.whl", hash = "sha256:18228d624807d66c87acd8f25fc135665617cab220671eb65b50f5d70fa51f69"}, + {file = "tiktoken-0.8.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:7e17807445f0cf1f25771c9d86496bd8b5c376f7419912519699f3cc4dc5c12e"}, + {file = "tiktoken-0.8.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:886f80bd339578bbdba6ed6d0567a0d5c6cfe198d9e587ba6c447654c65b8edc"}, + {file = "tiktoken-0.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6adc8323016d7758d6de7313527f755b0fc6c72985b7d9291be5d96d73ecd1e1"}, + {file = "tiktoken-0.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b591fb2b30d6a72121a80be24ec7a0e9eb51c5500ddc7e4c2496516dd5e3816b"}, + {file = "tiktoken-0.8.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:845287b9798e476b4d762c3ebda5102be87ca26e5d2c9854002825d60cdb815d"}, + {file = "tiktoken-0.8.0-cp39-cp39-win_amd64.whl", hash = "sha256:1473cfe584252dc3fa62adceb5b1c763c1874e04511b197da4e6de51d6ce5a02"}, + {file = "tiktoken-0.8.0.tar.gz", hash = "sha256:9ccbb2740f24542534369c5635cfd9b2b3c2490754a78ac8831d99f89f94eeb2"}, ] [package.dependencies] @@ -1688,31 +1865,62 @@ blobfile = ["blobfile (>=2)"] [[package]] name = "tomli" -version = "2.0.1" +version = "2.2.1" description = "A lil' TOML parser" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"}, - {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"}, + {file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"}, + {file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"}, + {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"}, + {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"}, + {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"}, + {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"}, + {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"}, + {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"}, ] [[package]] name = "tqdm" -version = "4.66.5" +version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = false python-versions = ">=3.7" files = [ - {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"}, - {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"}, + {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, + {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, ] [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} [package.extras] -dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"] +dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"] +discord = ["requests"] notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] telegram = ["requests"] @@ -1747,41 +1955,41 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "watchdog" -version = "5.0.2" +version = "6.0.0" description = "Filesystem events monitoring" optional = false python-versions = ">=3.9" files = [ - {file = "watchdog-5.0.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d961f4123bb3c447d9fcdcb67e1530c366f10ab3a0c7d1c0c9943050936d4877"}, - {file = "watchdog-5.0.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:72990192cb63872c47d5e5fefe230a401b87fd59d257ee577d61c9e5564c62e5"}, - {file = "watchdog-5.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6bec703ad90b35a848e05e1b40bf0050da7ca28ead7ac4be724ae5ac2653a1a0"}, - {file = "watchdog-5.0.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:dae7a1879918f6544201d33666909b040a46421054a50e0f773e0d870ed7438d"}, - {file = "watchdog-5.0.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c4a440f725f3b99133de610bfec93d570b13826f89616377715b9cd60424db6e"}, - {file = "watchdog-5.0.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f8b2918c19e0d48f5f20df458c84692e2a054f02d9df25e6c3c930063eca64c1"}, - {file = "watchdog-5.0.2-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:aa9cd6e24126d4afb3752a3e70fce39f92d0e1a58a236ddf6ee823ff7dba28ee"}, - {file = "watchdog-5.0.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:f627c5bf5759fdd90195b0c0431f99cff4867d212a67b384442c51136a098ed7"}, - {file = "watchdog-5.0.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:d7594a6d32cda2b49df3fd9abf9b37c8d2f3eab5df45c24056b4a671ac661619"}, - {file = "watchdog-5.0.2-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ba32efcccfe2c58f4d01115440d1672b4eb26cdd6fc5b5818f1fb41f7c3e1889"}, - {file = "watchdog-5.0.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:963f7c4c91e3f51c998eeff1b3fb24a52a8a34da4f956e470f4b068bb47b78ee"}, - {file = "watchdog-5.0.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:8c47150aa12f775e22efff1eee9f0f6beee542a7aa1a985c271b1997d340184f"}, - {file = "watchdog-5.0.2-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:14dd4ed023d79d1f670aa659f449bcd2733c33a35c8ffd88689d9d243885198b"}, - {file = "watchdog-5.0.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b84bff0391ad4abe25c2740c7aec0e3de316fdf7764007f41e248422a7760a7f"}, - {file = "watchdog-5.0.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3e8d5ff39f0a9968952cce548e8e08f849141a4fcc1290b1c17c032ba697b9d7"}, - {file = "watchdog-5.0.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:fb223456db6e5f7bd9bbd5cd969f05aae82ae21acc00643b60d81c770abd402b"}, - {file = "watchdog-5.0.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:9814adb768c23727a27792c77812cf4e2fd9853cd280eafa2bcfa62a99e8bd6e"}, - {file = "watchdog-5.0.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:901ee48c23f70193d1a7bc2d9ee297df66081dd5f46f0ca011be4f70dec80dab"}, - {file = "watchdog-5.0.2-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:638bcca3d5b1885c6ec47be67bf712b00a9ab3d4b22ec0881f4889ad870bc7e8"}, - {file = "watchdog-5.0.2-py3-none-manylinux2014_aarch64.whl", hash = "sha256:5597c051587f8757798216f2485e85eac583c3b343e9aa09127a3a6f82c65ee8"}, - {file = "watchdog-5.0.2-py3-none-manylinux2014_armv7l.whl", hash = "sha256:53ed1bf71fcb8475dd0ef4912ab139c294c87b903724b6f4a8bd98e026862e6d"}, - {file = "watchdog-5.0.2-py3-none-manylinux2014_i686.whl", hash = "sha256:29e4a2607bd407d9552c502d38b45a05ec26a8e40cc7e94db9bb48f861fa5abc"}, - {file = "watchdog-5.0.2-py3-none-manylinux2014_ppc64.whl", hash = "sha256:b6dc8f1d770a8280997e4beae7b9a75a33b268c59e033e72c8a10990097e5fde"}, - {file = "watchdog-5.0.2-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:d2ab34adc9bf1489452965cdb16a924e97d4452fcf88a50b21859068b50b5c3b"}, - {file = "watchdog-5.0.2-py3-none-manylinux2014_s390x.whl", hash = "sha256:7d1aa7e4bb0f0c65a1a91ba37c10e19dabf7eaaa282c5787e51371f090748f4b"}, - {file = "watchdog-5.0.2-py3-none-manylinux2014_x86_64.whl", hash = "sha256:726eef8f8c634ac6584f86c9c53353a010d9f311f6c15a034f3800a7a891d941"}, - {file = "watchdog-5.0.2-py3-none-win32.whl", hash = "sha256:bda40c57115684d0216556671875e008279dea2dc00fcd3dde126ac8e0d7a2fb"}, - {file = "watchdog-5.0.2-py3-none-win_amd64.whl", hash = "sha256:d010be060c996db725fbce7e3ef14687cdcc76f4ca0e4339a68cc4532c382a73"}, - {file = "watchdog-5.0.2-py3-none-win_ia64.whl", hash = "sha256:3960136b2b619510569b90f0cd96408591d6c251a75c97690f4553ca88889769"}, - {file = "watchdog-5.0.2.tar.gz", hash = "sha256:dcebf7e475001d2cdeb020be630dc5b687e9acdd60d16fea6bb4508e7b94cf76"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d1cdb490583ebd691c012b3d6dae011000fe42edb7a82ece80965b42abd61f26"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bc64ab3bdb6a04d69d4023b29422170b74681784ffb9463ed4870cf2f3e66112"}, + {file = "watchdog-6.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c897ac1b55c5a1461e16dae288d22bb2e412ba9807df8397a635d88f671d36c3"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6eb11feb5a0d452ee41f824e271ca311a09e250441c262ca2fd7ebcf2461a06c"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ef810fbf7b781a5a593894e4f439773830bdecb885e6880d957d5b9382a960d2"}, + {file = "watchdog-6.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:afd0fe1b2270917c5e23c2a65ce50c2a4abb63daafb0d419fde368e272a76b7c"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:bdd4e6f14b8b18c334febb9c4425a878a2ac20efd1e0b231978e7b150f92a948"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:c7c15dda13c4eb00d6fb6fc508b3c0ed88b9d5d374056b239c4ad1611125c860"}, + {file = "watchdog-6.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6f10cb2d5902447c7d0da897e2c6768bca89174d0c6e1e30abec5421af97a5b0"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:490ab2ef84f11129844c23fb14ecf30ef3d8a6abafd3754a6f75ca1e6654136c"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:76aae96b00ae814b181bb25b1b98076d5fc84e8a53cd8885a318b42b6d3a5134"}, + {file = "watchdog-6.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a175f755fc2279e0b7312c0035d52e27211a5bc39719dd529625b1930917345b"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:e6f0e77c9417e7cd62af82529b10563db3423625c5fce018430b249bf977f9e8"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:90c8e78f3b94014f7aaae121e6b909674df5b46ec24d6bebc45c44c56729af2a"}, + {file = "watchdog-6.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:e7631a77ffb1f7d2eefa4445ebbee491c720a5661ddf6df3498ebecae5ed375c"}, + {file = "watchdog-6.0.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:c7ac31a19f4545dd92fc25d200694098f42c9a8e391bc00bdd362c5736dbf881"}, + {file = "watchdog-6.0.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:9513f27a1a582d9808cf21a07dae516f0fab1cf2d7683a742c498b93eedabb11"}, + {file = "watchdog-6.0.0-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:7a0e56874cfbc4b9b05c60c8a1926fedf56324bb08cfbc188969777940aef3aa"}, + {file = "watchdog-6.0.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:e6439e374fc012255b4ec786ae3c4bc838cd7309a540e5fe0952d03687d8804e"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7607498efa04a3542ae3e05e64da8202e58159aa1fa4acddf7678d34a35d4f13"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_armv7l.whl", hash = "sha256:9041567ee8953024c83343288ccc458fd0a2d811d6a0fd68c4c22609e3490379"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_i686.whl", hash = "sha256:82dc3e3143c7e38ec49d61af98d6558288c415eac98486a5c581726e0737c00e"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_ppc64.whl", hash = "sha256:212ac9b8bf1161dc91bd09c048048a95ca3a4c4f5e5d4a7d1b1a7d5752a7f96f"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:e3df4cbb9a450c6d49318f6d14f4bbc80d763fa587ba46ec86f99f9e6876bb26"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_s390x.whl", hash = "sha256:2cce7cfc2008eb51feb6aab51251fd79b85d9894e98ba847408f662b3395ca3c"}, + {file = "watchdog-6.0.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:20ffe5b202af80ab4266dcd3e91aae72bf2da48c0d33bdb15c66658e685e94e2"}, + {file = "watchdog-6.0.0-py3-none-win32.whl", hash = "sha256:07df1fdd701c5d4c8e55ef6cf55b8f0120fe1aef7ef39a1c6fc6bc2e606d517a"}, + {file = "watchdog-6.0.0-py3-none-win_amd64.whl", hash = "sha256:cbafb470cf848d93b5d013e2ecb245d4aa1c8fd0504e863ccefa32445359d680"}, + {file = "watchdog-6.0.0-py3-none-win_ia64.whl", hash = "sha256:a1914259fa9e1454315171103c6a30961236f508b9b623eae470268bbcc6a22f"}, + {file = "watchdog-6.0.0.tar.gz", hash = "sha256:9ddf7c82fda3ae8e24decda1338ede66e1c99883db93711d8fb941eaa2d8c282"}, ] [package.extras] @@ -1789,110 +1997,101 @@ watchmedo = ["PyYAML (>=3.10)"] [[package]] name = "yarl" -version = "1.11.1" +version = "1.18.3" description = "Yet another URL library" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "yarl-1.11.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:400cd42185f92de559d29eeb529e71d80dfbd2f45c36844914a4a34297ca6f00"}, - {file = "yarl-1.11.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:8258c86f47e080a258993eed877d579c71da7bda26af86ce6c2d2d072c11320d"}, - {file = "yarl-1.11.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2164cd9725092761fed26f299e3f276bb4b537ca58e6ff6b252eae9631b5c96e"}, - {file = "yarl-1.11.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a08ea567c16f140af8ddc7cb58e27e9138a1386e3e6e53982abaa6f2377b38cc"}, - {file = "yarl-1.11.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:768ecc550096b028754ea28bf90fde071c379c62c43afa574edc6f33ee5daaec"}, - {file = "yarl-1.11.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2909fa3a7d249ef64eeb2faa04b7957e34fefb6ec9966506312349ed8a7e77bf"}, - {file = "yarl-1.11.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:01a8697ec24f17c349c4f655763c4db70eebc56a5f82995e5e26e837c6eb0e49"}, - {file = "yarl-1.11.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e286580b6511aac7c3268a78cdb861ec739d3e5a2a53b4809faef6b49778eaff"}, - {file = "yarl-1.11.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:4179522dc0305c3fc9782549175c8e8849252fefeb077c92a73889ccbcd508ad"}, - {file = "yarl-1.11.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:27fcb271a41b746bd0e2a92182df507e1c204759f460ff784ca614e12dd85145"}, - {file = "yarl-1.11.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:f61db3b7e870914dbd9434b560075e0366771eecbe6d2b5561f5bc7485f39efd"}, - {file = "yarl-1.11.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:c92261eb2ad367629dc437536463dc934030c9e7caca861cc51990fe6c565f26"}, - {file = "yarl-1.11.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:d95b52fbef190ca87d8c42f49e314eace4fc52070f3dfa5f87a6594b0c1c6e46"}, - {file = "yarl-1.11.1-cp310-cp310-win32.whl", hash = "sha256:489fa8bde4f1244ad6c5f6d11bb33e09cf0d1d0367edb197619c3e3fc06f3d91"}, - {file = "yarl-1.11.1-cp310-cp310-win_amd64.whl", hash = "sha256:476e20c433b356e16e9a141449f25161e6b69984fb4cdbd7cd4bd54c17844998"}, - {file = "yarl-1.11.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:946eedc12895873891aaceb39bceb484b4977f70373e0122da483f6c38faaa68"}, - {file = "yarl-1.11.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:21a7c12321436b066c11ec19c7e3cb9aec18884fe0d5b25d03d756a9e654edfe"}, - {file = "yarl-1.11.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c35f493b867912f6fda721a59cc7c4766d382040bdf1ddaeeaa7fa4d072f4675"}, - {file = "yarl-1.11.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25861303e0be76b60fddc1250ec5986c42f0a5c0c50ff57cc30b1be199c00e63"}, - {file = "yarl-1.11.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e4b53f73077e839b3f89c992223f15b1d2ab314bdbdf502afdc7bb18e95eae27"}, - {file = "yarl-1.11.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:327c724b01b8641a1bf1ab3b232fb638706e50f76c0b5bf16051ab65c868fac5"}, - {file = "yarl-1.11.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4307d9a3417eea87715c9736d050c83e8c1904e9b7aada6ce61b46361b733d92"}, - {file = "yarl-1.11.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:48a28bed68ab8fb7e380775f0029a079f08a17799cb3387a65d14ace16c12e2b"}, - {file = "yarl-1.11.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:067b961853c8e62725ff2893226fef3d0da060656a9827f3f520fb1d19b2b68a"}, - {file = "yarl-1.11.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:8215f6f21394d1f46e222abeb06316e77ef328d628f593502d8fc2a9117bde83"}, - {file = "yarl-1.11.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:498442e3af2a860a663baa14fbf23fb04b0dd758039c0e7c8f91cb9279799bff"}, - {file = "yarl-1.11.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:69721b8effdb588cb055cc22f7c5105ca6fdaa5aeb3ea09021d517882c4a904c"}, - {file = "yarl-1.11.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1e969fa4c1e0b1a391f3fcbcb9ec31e84440253325b534519be0d28f4b6b533e"}, - {file = "yarl-1.11.1-cp311-cp311-win32.whl", hash = "sha256:7d51324a04fc4b0e097ff8a153e9276c2593106a811704025bbc1d6916f45ca6"}, - {file = "yarl-1.11.1-cp311-cp311-win_amd64.whl", hash = "sha256:15061ce6584ece023457fb8b7a7a69ec40bf7114d781a8c4f5dcd68e28b5c53b"}, - {file = "yarl-1.11.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:a4264515f9117be204935cd230fb2a052dd3792789cc94c101c535d349b3dab0"}, - {file = "yarl-1.11.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:f41fa79114a1d2eddb5eea7b912d6160508f57440bd302ce96eaa384914cd265"}, - {file = "yarl-1.11.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:02da8759b47d964f9173c8675710720b468aa1c1693be0c9c64abb9d8d9a4867"}, - {file = "yarl-1.11.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9361628f28f48dcf8b2f528420d4d68102f593f9c2e592bfc842f5fb337e44fd"}, - {file = "yarl-1.11.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b91044952da03b6f95fdba398d7993dd983b64d3c31c358a4c89e3c19b6f7aef"}, - {file = "yarl-1.11.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:74db2ef03b442276d25951749a803ddb6e270d02dda1d1c556f6ae595a0d76a8"}, - {file = "yarl-1.11.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e975a2211952a8a083d1b9d9ba26472981ae338e720b419eb50535de3c02870"}, - {file = "yarl-1.11.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8aef97ba1dd2138112890ef848e17d8526fe80b21f743b4ee65947ea184f07a2"}, - {file = "yarl-1.11.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:a7915ea49b0c113641dc4d9338efa9bd66b6a9a485ffe75b9907e8573ca94b84"}, - {file = "yarl-1.11.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:504cf0d4c5e4579a51261d6091267f9fd997ef58558c4ffa7a3e1460bd2336fa"}, - {file = "yarl-1.11.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:3de5292f9f0ee285e6bd168b2a77b2a00d74cbcfa420ed078456d3023d2f6dff"}, - {file = "yarl-1.11.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a34e1e30f1774fa35d37202bbeae62423e9a79d78d0874e5556a593479fdf239"}, - {file = "yarl-1.11.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:66b63c504d2ca43bf7221a1f72fbe981ff56ecb39004c70a94485d13e37ebf45"}, - {file = "yarl-1.11.1-cp312-cp312-win32.whl", hash = "sha256:a28b70c9e2213de425d9cba5ab2e7f7a1c8ca23a99c4b5159bf77b9c31251447"}, - {file = "yarl-1.11.1-cp312-cp312-win_amd64.whl", hash = "sha256:17b5a386d0d36fb828e2fb3ef08c8829c1ebf977eef88e5367d1c8c94b454639"}, - {file = "yarl-1.11.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:1fa2e7a406fbd45b61b4433e3aa254a2c3e14c4b3186f6e952d08a730807fa0c"}, - {file = "yarl-1.11.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:750f656832d7d3cb0c76be137ee79405cc17e792f31e0a01eee390e383b2936e"}, - {file = "yarl-1.11.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0b8486f322d8f6a38539136a22c55f94d269addb24db5cb6f61adc61eabc9d93"}, - {file = "yarl-1.11.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3fce4da3703ee6048ad4138fe74619c50874afe98b1ad87b2698ef95bf92c96d"}, - {file = "yarl-1.11.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8ed653638ef669e0efc6fe2acb792275cb419bf9cb5c5049399f3556995f23c7"}, - {file = "yarl-1.11.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:18ac56c9dd70941ecad42b5a906820824ca72ff84ad6fa18db33c2537ae2e089"}, - {file = "yarl-1.11.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:688654f8507464745ab563b041d1fb7dab5d9912ca6b06e61d1c4708366832f5"}, - {file = "yarl-1.11.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4973eac1e2ff63cf187073cd4e1f1148dcd119314ab79b88e1b3fad74a18c9d5"}, - {file = "yarl-1.11.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:964a428132227edff96d6f3cf261573cb0f1a60c9a764ce28cda9525f18f7786"}, - {file = "yarl-1.11.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:6d23754b9939cbab02c63434776df1170e43b09c6a517585c7ce2b3d449b7318"}, - {file = "yarl-1.11.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:c2dc4250fe94d8cd864d66018f8344d4af50e3758e9d725e94fecfa27588ff82"}, - {file = "yarl-1.11.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:09696438cb43ea6f9492ef237761b043f9179f455f405279e609f2bc9100212a"}, - {file = "yarl-1.11.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:999bfee0a5b7385a0af5ffb606393509cfde70ecca4f01c36985be6d33e336da"}, - {file = "yarl-1.11.1-cp313-cp313-win32.whl", hash = "sha256:ce928c9c6409c79e10f39604a7e214b3cb69552952fbda8d836c052832e6a979"}, - {file = "yarl-1.11.1-cp313-cp313-win_amd64.whl", hash = "sha256:501c503eed2bb306638ccb60c174f856cc3246c861829ff40eaa80e2f0330367"}, - {file = "yarl-1.11.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:dae7bd0daeb33aa3e79e72877d3d51052e8b19c9025ecf0374f542ea8ec120e4"}, - {file = "yarl-1.11.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:3ff6b1617aa39279fe18a76c8d165469c48b159931d9b48239065767ee455b2b"}, - {file = "yarl-1.11.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:3257978c870728a52dcce8c2902bf01f6c53b65094b457bf87b2644ee6238ddc"}, - {file = "yarl-1.11.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f351fa31234699d6084ff98283cb1e852270fe9e250a3b3bf7804eb493bd937"}, - {file = "yarl-1.11.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8aef1b64da41d18026632d99a06b3fefe1d08e85dd81d849fa7c96301ed22f1b"}, - {file = "yarl-1.11.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7175a87ab8f7fbde37160a15e58e138ba3b2b0e05492d7351314a250d61b1591"}, - {file = "yarl-1.11.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba444bdd4caa2a94456ef67a2f383710928820dd0117aae6650a4d17029fa25e"}, - {file = "yarl-1.11.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0ea9682124fc062e3d931c6911934a678cb28453f957ddccf51f568c2f2b5e05"}, - {file = "yarl-1.11.1-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:8418c053aeb236b20b0ab8fa6bacfc2feaaf7d4683dd96528610989c99723d5f"}, - {file = "yarl-1.11.1-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:61a5f2c14d0a1adfdd82258f756b23a550c13ba4c86c84106be4c111a3a4e413"}, - {file = "yarl-1.11.1-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:f3a6d90cab0bdf07df8f176eae3a07127daafcf7457b997b2bf46776da2c7eb7"}, - {file = "yarl-1.11.1-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:077da604852be488c9a05a524068cdae1e972b7dc02438161c32420fb4ec5e14"}, - {file = "yarl-1.11.1-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:15439f3c5c72686b6c3ff235279630d08936ace67d0fe5c8d5bbc3ef06f5a420"}, - {file = "yarl-1.11.1-cp38-cp38-win32.whl", hash = "sha256:238a21849dd7554cb4d25a14ffbfa0ef380bb7ba201f45b144a14454a72ffa5a"}, - {file = "yarl-1.11.1-cp38-cp38-win_amd64.whl", hash = "sha256:67459cf8cf31da0e2cbdb4b040507e535d25cfbb1604ca76396a3a66b8ba37a6"}, - {file = "yarl-1.11.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:884eab2ce97cbaf89f264372eae58388862c33c4f551c15680dd80f53c89a269"}, - {file = "yarl-1.11.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8a336eaa7ee7e87cdece3cedb395c9657d227bfceb6781295cf56abcd3386a26"}, - {file = "yarl-1.11.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:87f020d010ba80a247c4abc335fc13421037800ca20b42af5ae40e5fd75e7909"}, - {file = "yarl-1.11.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:637c7ddb585a62d4469f843dac221f23eec3cbad31693b23abbc2c366ad41ff4"}, - {file = "yarl-1.11.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:48dfd117ab93f0129084577a07287376cc69c08138694396f305636e229caa1a"}, - {file = "yarl-1.11.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:75e0ae31fb5ccab6eda09ba1494e87eb226dcbd2372dae96b87800e1dcc98804"}, - {file = "yarl-1.11.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f46f81501160c28d0c0b7333b4f7be8983dbbc161983b6fb814024d1b4952f79"}, - {file = "yarl-1.11.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:04293941646647b3bfb1719d1d11ff1028e9c30199509a844da3c0f5919dc520"}, - {file = "yarl-1.11.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:250e888fa62d73e721f3041e3a9abf427788a1934b426b45e1b92f62c1f68366"}, - {file = "yarl-1.11.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:e8f63904df26d1a66aabc141bfd258bf738b9bc7bc6bdef22713b4f5ef789a4c"}, - {file = "yarl-1.11.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:aac44097d838dda26526cffb63bdd8737a2dbdf5f2c68efb72ad83aec6673c7e"}, - {file = "yarl-1.11.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:267b24f891e74eccbdff42241c5fb4f974de2d6271dcc7d7e0c9ae1079a560d9"}, - {file = "yarl-1.11.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:6907daa4b9d7a688063ed098c472f96e8181733c525e03e866fb5db480a424df"}, - {file = "yarl-1.11.1-cp39-cp39-win32.whl", hash = "sha256:14438dfc5015661f75f85bc5adad0743678eefee266ff0c9a8e32969d5d69f74"}, - {file = "yarl-1.11.1-cp39-cp39-win_amd64.whl", hash = "sha256:94d0caaa912bfcdc702a4204cd5e2bb01eb917fc4f5ea2315aa23962549561b0"}, - {file = "yarl-1.11.1-py3-none-any.whl", hash = "sha256:72bf26f66456baa0584eff63e44545c9f0eaed9b73cb6601b647c91f14c11f38"}, - {file = "yarl-1.11.1.tar.gz", hash = "sha256:1bb2d9e212fb7449b8fb73bc461b51eaa17cc8430b4a87d87be7b25052d92f53"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7"}, + {file = "yarl-1.18.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:602d98f2c2d929f8e697ed274fbadc09902c4025c5a9963bf4e9edfc3ab6f7ed"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c654d5207c78e0bd6d749f6dae1dcbbfde3403ad3a4b11f3c5544d9906969dde"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5094d9206c64181d0f6e76ebd8fb2f8fe274950a63890ee9e0ebfd58bf9d787b"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35098b24e0327fc4ebdc8ffe336cee0a87a700c24ffed13161af80124b7dc8e5"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3236da9272872443f81fedc389bace88408f64f89f75d1bdb2256069a8730ccc"}, + {file = "yarl-1.18.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e2c08cc9b16f4f4bc522771d96734c7901e7ebef70c6c5c35dd0f10845270bcd"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:80316a8bd5109320d38eef8833ccf5f89608c9107d02d2a7f985f98ed6876990"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c1e1cc06da1491e6734f0ea1e6294ce00792193c463350626571c287c9a704db"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fea09ca13323376a2fdfb353a5fa2e59f90cd18d7ca4eaa1fd31f0a8b4f91e62"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e3b9fd71836999aad54084906f8663dffcd2a7fb5cdafd6c37713b2e72be1760"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:757e81cae69244257d125ff31663249b3013b5dc0a8520d73694aed497fb195b"}, + {file = "yarl-1.18.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b1771de9944d875f1b98a745bc547e684b863abf8f8287da8466cf470ef52690"}, + {file = "yarl-1.18.3-cp310-cp310-win32.whl", hash = "sha256:8874027a53e3aea659a6d62751800cf6e63314c160fd607489ba5c2edd753cf6"}, + {file = "yarl-1.18.3-cp310-cp310-win_amd64.whl", hash = "sha256:93b2e109287f93db79210f86deb6b9bbb81ac32fc97236b16f7433db7fc437d8"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8503ad47387b8ebd39cbbbdf0bf113e17330ffd339ba1144074da24c545f0069"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02ddb6756f8f4517a2d5e99d8b2f272488e18dd0bfbc802f31c16c6c20f22193"}, + {file = "yarl-1.18.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:67a283dd2882ac98cc6318384f565bffc751ab564605959df4752d42483ad889"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d980e0325b6eddc81331d3f4551e2a333999fb176fd153e075c6d1c2530aa8a8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b643562c12680b01e17239be267bc306bbc6aac1f34f6444d1bded0c5ce438ca"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c017a3b6df3a1bd45b9fa49a0f54005e53fbcad16633870104b66fa1a30a29d8"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75674776d96d7b851b6498f17824ba17849d790a44d282929c42dbb77d4f17ae"}, + {file = "yarl-1.18.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ccaa3a4b521b780a7e771cc336a2dba389a0861592bbce09a476190bb0c8b4b3"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d06d3005e668744e11ed80812e61efd77d70bb7f03e33c1598c301eea20efbb"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:9d41beda9dc97ca9ab0b9888cb71f7539124bc05df02c0cff6e5acc5a19dcc6e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:ba23302c0c61a9999784e73809427c9dbedd79f66a13d84ad1b1943802eaaf59"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:6748dbf9bfa5ba1afcc7556b71cda0d7ce5f24768043a02a58846e4a443d808d"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:0b0cad37311123211dc91eadcb322ef4d4a66008d3e1bdc404808992260e1a0e"}, + {file = "yarl-1.18.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0fb2171a4486bb075316ee754c6d8382ea6eb8b399d4ec62fde2b591f879778a"}, + {file = "yarl-1.18.3-cp311-cp311-win32.whl", hash = "sha256:61b1a825a13bef4a5f10b1885245377d3cd0bf87cba068e1d9a88c2ae36880e1"}, + {file = "yarl-1.18.3-cp311-cp311-win_amd64.whl", hash = "sha256:b9d60031cf568c627d028239693fd718025719c02c9f55df0a53e587aab951b5"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1dd4bdd05407ced96fed3d7f25dbbf88d2ffb045a0db60dbc247f5b3c5c25d50"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7c33dd1931a95e5d9a772d0ac5e44cac8957eaf58e3c8da8c1414de7dd27c576"}, + {file = "yarl-1.18.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:25b411eddcfd56a2f0cd6a384e9f4f7aa3efee14b188de13048c25b5e91f1640"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:436c4fc0a4d66b2badc6c5fc5ef4e47bb10e4fd9bf0c79524ac719a01f3607c2"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e35ef8683211db69ffe129a25d5634319a677570ab6b2eba4afa860f54eeaf75"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84b2deecba4a3f1a398df819151eb72d29bfeb3b69abb145a00ddc8d30094512"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e5a1fea0fd4f5bfa7440a47eff01d9822a65b4488f7cff83155a0f31a2ecba"}, + {file = "yarl-1.18.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0e883008013c0e4aef84dcfe2a0b172c4d23c2669412cf5b3371003941f72bb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5a3f356548e34a70b0172d8890006c37be92995f62d95a07b4a42e90fba54272"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ccd17349166b1bee6e529b4add61727d3f55edb7babbe4069b5764c9587a8cc6"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b958ddd075ddba5b09bb0be8a6d9906d2ce933aee81100db289badbeb966f54e"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c7d79f7d9aabd6011004e33b22bc13056a3e3fb54794d138af57f5ee9d9032cb"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:4891ed92157e5430874dad17b15eb1fda57627710756c27422200c52d8a4e393"}, + {file = "yarl-1.18.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ce1af883b94304f493698b00d0f006d56aea98aeb49d75ec7d98cd4a777e9285"}, + {file = "yarl-1.18.3-cp312-cp312-win32.whl", hash = "sha256:f91c4803173928a25e1a55b943c81f55b8872f0018be83e3ad4938adffb77dd2"}, + {file = "yarl-1.18.3-cp312-cp312-win_amd64.whl", hash = "sha256:7e2ee16578af3b52ac2f334c3b1f92262f47e02cc6193c598502bd46f5cd1477"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:90adb47ad432332d4f0bc28f83a5963f426ce9a1a8809f5e584e704b82685dcb"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:913829534200eb0f789d45349e55203a091f45c37a2674678744ae52fae23efa"}, + {file = "yarl-1.18.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ef9f7768395923c3039055c14334ba4d926f3baf7b776c923c93d80195624782"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88a19f62ff30117e706ebc9090b8ecc79aeb77d0b1f5ec10d2d27a12bc9f66d0"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e17c9361d46a4d5addf777c6dd5eab0715a7684c2f11b88c67ac37edfba6c482"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a74a13a4c857a84a845505fd2d68e54826a2cd01935a96efb1e9d86c728e186"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41f7ce59d6ee7741af71d82020346af364949314ed3d87553763a2df1829cc58"}, + {file = "yarl-1.18.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f52a265001d830bc425f82ca9eabda94a64a4d753b07d623a9f2863fde532b53"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:82123d0c954dc58db301f5021a01854a85bf1f3bb7d12ae0c01afc414a882ca2"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:2ec9bbba33b2d00999af4631a3397d1fd78290c48e2a3e52d8dd72db3a067ac8"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:fbd6748e8ab9b41171bb95c6142faf068f5ef1511935a0aa07025438dd9a9bc1"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:877d209b6aebeb5b16c42cbb377f5f94d9e556626b1bfff66d7b0d115be88d0a"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:b464c4ab4bfcb41e3bfd3f1c26600d038376c2de3297760dfe064d2cb7ea8e10"}, + {file = "yarl-1.18.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8d39d351e7faf01483cc7ff7c0213c412e38e5a340238826be7e0e4da450fdc8"}, + {file = "yarl-1.18.3-cp313-cp313-win32.whl", hash = "sha256:61ee62ead9b68b9123ec24bc866cbef297dd266175d53296e2db5e7f797f902d"}, + {file = "yarl-1.18.3-cp313-cp313-win_amd64.whl", hash = "sha256:578e281c393af575879990861823ef19d66e2b1d0098414855dd367e234f5b3c"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:61e5e68cb65ac8f547f6b5ef933f510134a6bf31bb178be428994b0cb46c2a04"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:fe57328fbc1bfd0bd0514470ac692630f3901c0ee39052ae47acd1d90a436719"}, + {file = "yarl-1.18.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a440a2a624683108a1b454705ecd7afc1c3438a08e890a1513d468671d90a04e"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:09c7907c8548bcd6ab860e5f513e727c53b4a714f459b084f6580b49fa1b9cee"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b4f6450109834af88cb4cc5ecddfc5380ebb9c228695afc11915a0bf82116789"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9ca04806f3be0ac6d558fffc2fdf8fcef767e0489d2684a21912cc4ed0cd1b8"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77a6e85b90a7641d2e07184df5557132a337f136250caafc9ccaa4a2a998ca2c"}, + {file = "yarl-1.18.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6333c5a377c8e2f5fae35e7b8f145c617b02c939d04110c76f29ee3676b5f9a5"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:0b3c92fa08759dbf12b3a59579a4096ba9af8dd344d9a813fc7f5070d86bbab1"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:4ac515b860c36becb81bb84b667466885096b5fc85596948548b667da3bf9f24"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:045b8482ce9483ada4f3f23b3774f4e1bf4f23a2d5c912ed5170f68efb053318"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:a4bb030cf46a434ec0225bddbebd4b89e6471814ca851abb8696170adb163985"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:54d6921f07555713b9300bee9c50fb46e57e2e639027089b1d795ecd9f7fa910"}, + {file = "yarl-1.18.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1d407181cfa6e70077df3377938c08012d18893f9f20e92f7d2f314a437c30b1"}, + {file = "yarl-1.18.3-cp39-cp39-win32.whl", hash = "sha256:ac36703a585e0929b032fbaab0707b75dc12703766d0b53486eabd5139ebadd5"}, + {file = "yarl-1.18.3-cp39-cp39-win_amd64.whl", hash = "sha256:ba87babd629f8af77f557b61e49e7c7cac36f22f871156b91e10a6e9d4f829e9"}, + {file = "yarl-1.18.3-py3-none-any.whl", hash = "sha256:b57f4f58099328dfb26c6a771d09fb20dbbae81d20cfb66141251ea063bd101b"}, + {file = "yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1"}, ] [package.dependencies] idna = ">=2.0" multidict = ">=4.0" +propcache = ">=0.2.0" [metadata] lock-version = "2.0" python-versions = ">=3.9,<3.13" -content-hash = "899f0a0ae7877b0b3724a4799907b3ff6d3809412f6dbfaab9434919d6216d8c" +content-hash = "b19080a915cafa4786cc8238c11e89b05e496912674d8915d22fe1fe85604b22" diff --git a/libs/partners/pinecone/pyproject.toml b/libs/partners/pinecone/pyproject.toml index 7905ee41c8eba..7c33a4502f861 100644 --- a/libs/partners/pinecone/pyproject.toml +++ b/libs/partners/pinecone/pyproject.toml @@ -20,16 +20,10 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<3.13" -langchain-core = "^0.3.15" -pinecone-client = "^5.0.0" +langchain-core = "^0.3.21" +pinecone = "^5.4.0" aiohttp = ">=3.9.5,<3.10" -[[tool.poetry.dependencies.numpy]] -version = "^1" -python = "<3.12" - -[[tool.poetry.dependencies.numpy]] -version = "^1.26.0" -python = ">=3.12" +numpy = ">=1.26.0,<2.0.0" [tool.ruff.lint] select = [ "E", "F", "I", "T201",] diff --git a/libs/partners/qdrant/poetry.lock b/libs/partners/qdrant/poetry.lock index 56c3a7f971813..41fd237e2b117 100644 --- a/libs/partners/qdrant/poetry.lock +++ b/libs/partners/qdrant/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. [[package]] name = "annotated-types" @@ -327,137 +327,137 @@ tqdm = ["tqdm"] [[package]] name = "grpcio" -version = "1.67.1" +version = "1.68.0" description = "HTTP/2-based RPC framework" optional = false python-versions = ">=3.8" files = [ - {file = "grpcio-1.67.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:8b0341d66a57f8a3119b77ab32207072be60c9bf79760fa609c5609f2deb1f3f"}, - {file = "grpcio-1.67.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:f5a27dddefe0e2357d3e617b9079b4bfdc91341a91565111a21ed6ebbc51b22d"}, - {file = "grpcio-1.67.1-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:43112046864317498a33bdc4797ae6a268c36345a910de9b9c17159d8346602f"}, - {file = "grpcio-1.67.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c9b929f13677b10f63124c1a410994a401cdd85214ad83ab67cc077fc7e480f0"}, - {file = "grpcio-1.67.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7d1797a8a3845437d327145959a2c0c47c05947c9eef5ff1a4c80e499dcc6fa"}, - {file = "grpcio-1.67.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:0489063974d1452436139501bf6b180f63d4977223ee87488fe36858c5725292"}, - {file = "grpcio-1.67.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:9fd042de4a82e3e7aca44008ee2fb5da01b3e5adb316348c21980f7f58adc311"}, - {file = "grpcio-1.67.1-cp310-cp310-win32.whl", hash = "sha256:638354e698fd0c6c76b04540a850bf1db27b4d2515a19fcd5cf645c48d3eb1ed"}, - {file = "grpcio-1.67.1-cp310-cp310-win_amd64.whl", hash = "sha256:608d87d1bdabf9e2868b12338cd38a79969eaf920c89d698ead08f48de9c0f9e"}, - {file = "grpcio-1.67.1-cp311-cp311-linux_armv7l.whl", hash = "sha256:7818c0454027ae3384235a65210bbf5464bd715450e30a3d40385453a85a70cb"}, - {file = "grpcio-1.67.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ea33986b70f83844cd00814cee4451055cd8cab36f00ac64a31f5bb09b31919e"}, - {file = "grpcio-1.67.1-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:c7a01337407dd89005527623a4a72c5c8e2894d22bead0895306b23c6695698f"}, - {file = "grpcio-1.67.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:80b866f73224b0634f4312a4674c1be21b2b4afa73cb20953cbbb73a6b36c3cc"}, - {file = "grpcio-1.67.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9fff78ba10d4250bfc07a01bd6254a6d87dc67f9627adece85c0b2ed754fa96"}, - {file = "grpcio-1.67.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:8a23cbcc5bb11ea7dc6163078be36c065db68d915c24f5faa4f872c573bb400f"}, - {file = "grpcio-1.67.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:1a65b503d008f066e994f34f456e0647e5ceb34cfcec5ad180b1b44020ad4970"}, - {file = "grpcio-1.67.1-cp311-cp311-win32.whl", hash = "sha256:e29ca27bec8e163dca0c98084040edec3bc49afd10f18b412f483cc68c712744"}, - {file = "grpcio-1.67.1-cp311-cp311-win_amd64.whl", hash = "sha256:786a5b18544622bfb1e25cc08402bd44ea83edfb04b93798d85dca4d1a0b5be5"}, - {file = "grpcio-1.67.1-cp312-cp312-linux_armv7l.whl", hash = "sha256:267d1745894200e4c604958da5f856da6293f063327cb049a51fe67348e4f953"}, - {file = "grpcio-1.67.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:85f69fdc1d28ce7cff8de3f9c67db2b0ca9ba4449644488c1e0303c146135ddb"}, - {file = "grpcio-1.67.1-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:f26b0b547eb8d00e195274cdfc63ce64c8fc2d3e2d00b12bf468ece41a0423a0"}, - {file = "grpcio-1.67.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4422581cdc628f77302270ff839a44f4c24fdc57887dc2a45b7e53d8fc2376af"}, - {file = "grpcio-1.67.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1d7616d2ded471231c701489190379e0c311ee0a6c756f3c03e6a62b95a7146e"}, - {file = "grpcio-1.67.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:8a00efecde9d6fcc3ab00c13f816313c040a28450e5e25739c24f432fc6d3c75"}, - {file = "grpcio-1.67.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:699e964923b70f3101393710793289e42845791ea07565654ada0969522d0a38"}, - {file = "grpcio-1.67.1-cp312-cp312-win32.whl", hash = "sha256:4e7b904484a634a0fff132958dabdb10d63e0927398273917da3ee103e8d1f78"}, - {file = "grpcio-1.67.1-cp312-cp312-win_amd64.whl", hash = "sha256:5721e66a594a6c4204458004852719b38f3d5522082be9061d6510b455c90afc"}, - {file = "grpcio-1.67.1-cp313-cp313-linux_armv7l.whl", hash = "sha256:aa0162e56fd10a5547fac8774c4899fc3e18c1aa4a4759d0ce2cd00d3696ea6b"}, - {file = "grpcio-1.67.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:beee96c8c0b1a75d556fe57b92b58b4347c77a65781ee2ac749d550f2a365dc1"}, - {file = "grpcio-1.67.1-cp313-cp313-manylinux_2_17_aarch64.whl", hash = "sha256:a93deda571a1bf94ec1f6fcda2872dad3ae538700d94dc283c672a3b508ba3af"}, - {file = "grpcio-1.67.1-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0e6f255980afef598a9e64a24efce87b625e3e3c80a45162d111a461a9f92955"}, - {file = "grpcio-1.67.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9e838cad2176ebd5d4a8bb03955138d6589ce9e2ce5d51c3ada34396dbd2dba8"}, - {file = "grpcio-1.67.1-cp313-cp313-musllinux_1_1_i686.whl", hash = "sha256:a6703916c43b1d468d0756c8077b12017a9fcb6a1ef13faf49e67d20d7ebda62"}, - {file = "grpcio-1.67.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:917e8d8994eed1d86b907ba2a61b9f0aef27a2155bca6cbb322430fc7135b7bb"}, - {file = "grpcio-1.67.1-cp313-cp313-win32.whl", hash = "sha256:e279330bef1744040db8fc432becc8a727b84f456ab62b744d3fdb83f327e121"}, - {file = "grpcio-1.67.1-cp313-cp313-win_amd64.whl", hash = "sha256:fa0c739ad8b1996bd24823950e3cb5152ae91fca1c09cc791190bf1627ffefba"}, - {file = "grpcio-1.67.1-cp38-cp38-linux_armv7l.whl", hash = "sha256:178f5db771c4f9a9facb2ab37a434c46cb9be1a75e820f187ee3d1e7805c4f65"}, - {file = "grpcio-1.67.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:0f3e49c738396e93b7ba9016e153eb09e0778e776df6090c1b8c91877cc1c426"}, - {file = "grpcio-1.67.1-cp38-cp38-manylinux_2_17_aarch64.whl", hash = "sha256:24e8a26dbfc5274d7474c27759b54486b8de23c709d76695237515bc8b5baeab"}, - {file = "grpcio-1.67.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3b6c16489326d79ead41689c4b84bc40d522c9a7617219f4ad94bc7f448c5085"}, - {file = "grpcio-1.67.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:60e6a4dcf5af7bbc36fd9f81c9f372e8ae580870a9e4b6eafe948cd334b81cf3"}, - {file = "grpcio-1.67.1-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:95b5f2b857856ed78d72da93cd7d09b6db8ef30102e5e7fe0961fe4d9f7d48e8"}, - {file = "grpcio-1.67.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b49359977c6ec9f5d0573ea4e0071ad278ef905aa74e420acc73fd28ce39e9ce"}, - {file = "grpcio-1.67.1-cp38-cp38-win32.whl", hash = "sha256:f5b76ff64aaac53fede0cc93abf57894ab2a7362986ba22243d06218b93efe46"}, - {file = "grpcio-1.67.1-cp38-cp38-win_amd64.whl", hash = "sha256:804c6457c3cd3ec04fe6006c739579b8d35c86ae3298ffca8de57b493524b771"}, - {file = "grpcio-1.67.1-cp39-cp39-linux_armv7l.whl", hash = "sha256:a25bdea92b13ff4d7790962190bf6bf5c4639876e01c0f3dda70fc2769616335"}, - {file = "grpcio-1.67.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:cdc491ae35a13535fd9196acb5afe1af37c8237df2e54427be3eecda3653127e"}, - {file = "grpcio-1.67.1-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:85f862069b86a305497e74d0dc43c02de3d1d184fc2c180993aa8aa86fbd19b8"}, - {file = "grpcio-1.67.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ec74ef02010186185de82cc594058a3ccd8d86821842bbac9873fd4a2cf8be8d"}, - {file = "grpcio-1.67.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:01f616a964e540638af5130469451cf580ba8c7329f45ca998ab66e0c7dcdb04"}, - {file = "grpcio-1.67.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:299b3d8c4f790c6bcca485f9963b4846dd92cf6f1b65d3697145d005c80f9fe8"}, - {file = "grpcio-1.67.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:60336bff760fbb47d7e86165408126f1dded184448e9a4c892189eb7c9d3f90f"}, - {file = "grpcio-1.67.1-cp39-cp39-win32.whl", hash = "sha256:5ed601c4c6008429e3d247ddb367fe8c7259c355757448d7c1ef7bd4a6739e8e"}, - {file = "grpcio-1.67.1-cp39-cp39-win_amd64.whl", hash = "sha256:5db70d32d6703b89912af16d6d45d78406374a8b8ef0d28140351dd0ec610e98"}, - {file = "grpcio-1.67.1.tar.gz", hash = "sha256:3dc2ed4cabea4dc14d5e708c2b426205956077cc5de419b4d4079315017e9732"}, + {file = "grpcio-1.68.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:619b5d0f29f4f5351440e9343224c3e19912c21aeda44e0c49d0d147a8d01544"}, + {file = "grpcio-1.68.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:a59f5822f9459bed098ffbceb2713abbf7c6fd13f2b9243461da5c338d0cd6c3"}, + {file = "grpcio-1.68.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:c03d89df516128febc5a7e760d675b478ba25802447624edf7aa13b1e7b11e2a"}, + {file = "grpcio-1.68.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:44bcbebb24363d587472089b89e2ea0ab2e2b4df0e4856ba4c0b087c82412121"}, + {file = "grpcio-1.68.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:79f81b7fbfb136247b70465bd836fa1733043fdee539cd6031cb499e9608a110"}, + {file = "grpcio-1.68.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:88fb2925789cfe6daa20900260ef0a1d0a61283dfb2d2fffe6194396a354c618"}, + {file = "grpcio-1.68.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:99f06232b5c9138593ae6f2e355054318717d32a9c09cdc5a2885540835067a1"}, + {file = "grpcio-1.68.0-cp310-cp310-win32.whl", hash = "sha256:a6213d2f7a22c3c30a479fb5e249b6b7e648e17f364598ff64d08a5136fe488b"}, + {file = "grpcio-1.68.0-cp310-cp310-win_amd64.whl", hash = "sha256:15327ab81131ef9b94cb9f45b5bd98803a179c7c61205c8c0ac9aff9d6c4e82a"}, + {file = "grpcio-1.68.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:3b2b559beb2d433129441783e5f42e3be40a9e1a89ec906efabf26591c5cd415"}, + {file = "grpcio-1.68.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e46541de8425a4d6829ac6c5d9b16c03c292105fe9ebf78cb1c31e8d242f9155"}, + {file = "grpcio-1.68.0-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:c1245651f3c9ea92a2db4f95d37b7597db6b246d5892bca6ee8c0e90d76fb73c"}, + {file = "grpcio-1.68.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4f1931c7aa85be0fa6cea6af388e576f3bf6baee9e5d481c586980c774debcb4"}, + {file = "grpcio-1.68.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8b0ff09c81e3aded7a183bc6473639b46b6caa9c1901d6f5e2cba24b95e59e30"}, + {file = "grpcio-1.68.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:8c73f9fbbaee1a132487e31585aa83987ddf626426d703ebcb9a528cf231c9b1"}, + {file = "grpcio-1.68.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:6b2f98165ea2790ea159393a2246b56f580d24d7da0d0342c18a085299c40a75"}, + {file = "grpcio-1.68.0-cp311-cp311-win32.whl", hash = "sha256:e1e7ed311afb351ff0d0e583a66fcb39675be112d61e7cfd6c8269884a98afbc"}, + {file = "grpcio-1.68.0-cp311-cp311-win_amd64.whl", hash = "sha256:e0d2f68eaa0a755edd9a47d40e50dba6df2bceda66960dee1218da81a2834d27"}, + {file = "grpcio-1.68.0-cp312-cp312-linux_armv7l.whl", hash = "sha256:8af6137cc4ae8e421690d276e7627cfc726d4293f6607acf9ea7260bd8fc3d7d"}, + {file = "grpcio-1.68.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:4028b8e9a3bff6f377698587d642e24bd221810c06579a18420a17688e421af7"}, + {file = "grpcio-1.68.0-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:f60fa2adf281fd73ae3a50677572521edca34ba373a45b457b5ebe87c2d01e1d"}, + {file = "grpcio-1.68.0-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e18589e747c1e70b60fab6767ff99b2d0c359ea1db8a2cb524477f93cdbedf5b"}, + {file = "grpcio-1.68.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0d30f3fee9372796f54d3100b31ee70972eaadcc87314be369360248a3dcffe"}, + {file = "grpcio-1.68.0-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:7e0a3e72c0e9a1acab77bef14a73a416630b7fd2cbd893c0a873edc47c42c8cd"}, + {file = "grpcio-1.68.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a831dcc343440969aaa812004685ed322cdb526cd197112d0db303b0da1e8659"}, + {file = "grpcio-1.68.0-cp312-cp312-win32.whl", hash = "sha256:5a180328e92b9a0050958ced34dddcb86fec5a8b332f5a229e353dafc16cd332"}, + {file = "grpcio-1.68.0-cp312-cp312-win_amd64.whl", hash = "sha256:2bddd04a790b69f7a7385f6a112f46ea0b34c4746f361ebafe9ca0be567c78e9"}, + {file = "grpcio-1.68.0-cp313-cp313-linux_armv7l.whl", hash = "sha256:fc05759ffbd7875e0ff2bd877be1438dfe97c9312bbc558c8284a9afa1d0f40e"}, + {file = "grpcio-1.68.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:15fa1fe25d365a13bc6d52fcac0e3ee1f9baebdde2c9b3b2425f8a4979fccea1"}, + {file = "grpcio-1.68.0-cp313-cp313-manylinux_2_17_aarch64.whl", hash = "sha256:32a9cb4686eb2e89d97022ecb9e1606d132f85c444354c17a7dbde4a455e4a3b"}, + {file = "grpcio-1.68.0-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:dba037ff8d284c8e7ea9a510c8ae0f5b016004f13c3648f72411c464b67ff2fb"}, + {file = "grpcio-1.68.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0efbbd849867e0e569af09e165363ade75cf84f5229b2698d53cf22c7a4f9e21"}, + {file = "grpcio-1.68.0-cp313-cp313-musllinux_1_1_i686.whl", hash = "sha256:4e300e6978df0b65cc2d100c54e097c10dfc7018b9bd890bbbf08022d47f766d"}, + {file = "grpcio-1.68.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:6f9c7ad1a23e1047f827385f4713b5b8c6c7d325705be1dd3e31fb00dcb2f665"}, + {file = "grpcio-1.68.0-cp313-cp313-win32.whl", hash = "sha256:3ac7f10850fd0487fcce169c3c55509101c3bde2a3b454869639df2176b60a03"}, + {file = "grpcio-1.68.0-cp313-cp313-win_amd64.whl", hash = "sha256:afbf45a62ba85a720491bfe9b2642f8761ff348006f5ef67e4622621f116b04a"}, + {file = "grpcio-1.68.0-cp38-cp38-linux_armv7l.whl", hash = "sha256:f8f695d9576ce836eab27ba7401c60acaf9ef6cf2f70dfe5462055ba3df02cc3"}, + {file = "grpcio-1.68.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:9fe1b141cda52f2ca73e17d2d3c6a9f3f3a0c255c216b50ce616e9dca7e3441d"}, + {file = "grpcio-1.68.0-cp38-cp38-manylinux_2_17_aarch64.whl", hash = "sha256:4df81d78fd1646bf94ced4fb4cd0a7fe2e91608089c522ef17bc7db26e64effd"}, + {file = "grpcio-1.68.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:46a2d74d4dd8993151c6cd585594c082abe74112c8e4175ddda4106f2ceb022f"}, + {file = "grpcio-1.68.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a17278d977746472698460c63abf333e1d806bd41f2224f90dbe9460101c9796"}, + {file = "grpcio-1.68.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:15377bce516b1c861c35e18eaa1c280692bf563264836cece693c0f169b48829"}, + {file = "grpcio-1.68.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:cc5f0a4f5904b8c25729a0498886b797feb817d1fd3812554ffa39551112c161"}, + {file = "grpcio-1.68.0-cp38-cp38-win32.whl", hash = "sha256:def1a60a111d24376e4b753db39705adbe9483ef4ca4761f825639d884d5da78"}, + {file = "grpcio-1.68.0-cp38-cp38-win_amd64.whl", hash = "sha256:55d3b52fd41ec5772a953612db4e70ae741a6d6ed640c4c89a64f017a1ac02b5"}, + {file = "grpcio-1.68.0-cp39-cp39-linux_armv7l.whl", hash = "sha256:0d230852ba97654453d290e98d6aa61cb48fa5fafb474fb4c4298d8721809354"}, + {file = "grpcio-1.68.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:50992f214264e207e07222703c17d9cfdcc2c46ed5a1ea86843d440148ebbe10"}, + {file = "grpcio-1.68.0-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:14331e5c27ed3545360464a139ed279aa09db088f6e9502e95ad4bfa852bb116"}, + {file = "grpcio-1.68.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f84890b205692ea813653ece4ac9afa2139eae136e419231b0eec7c39fdbe4c2"}, + {file = "grpcio-1.68.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b0cf343c6f4f6aa44863e13ec9ddfe299e0be68f87d68e777328bff785897b05"}, + {file = "grpcio-1.68.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:fd2c2d47969daa0e27eadaf15c13b5e92605c5e5953d23c06d0b5239a2f176d3"}, + {file = "grpcio-1.68.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:18668e36e7f4045820f069997834e94e8275910b1f03e078a6020bd464cb2363"}, + {file = "grpcio-1.68.0-cp39-cp39-win32.whl", hash = "sha256:2af76ab7c427aaa26aa9187c3e3c42f38d3771f91a20f99657d992afada2294a"}, + {file = "grpcio-1.68.0-cp39-cp39-win_amd64.whl", hash = "sha256:e694b5928b7b33ca2d3b4d5f9bf8b5888906f181daff6b406f4938f3a997a490"}, + {file = "grpcio-1.68.0.tar.gz", hash = "sha256:7e7483d39b4a4fddb9906671e9ea21aaad4f031cdfc349fec76bdfa1e404543a"}, ] [package.extras] -protobuf = ["grpcio-tools (>=1.67.1)"] +protobuf = ["grpcio-tools (>=1.68.0)"] [[package]] name = "grpcio-tools" -version = "1.67.1" +version = "1.68.0" description = "Protobuf code generator for gRPC" optional = false python-versions = ">=3.8" files = [ - {file = "grpcio_tools-1.67.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:c701aaa51fde1f2644bd94941aa94c337adb86f25cd03cf05e37387aaea25800"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:6a722bba714392de2386569c40942566b83725fa5c5450b8910e3832a5379469"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:0c7415235cb154e40b5ae90e2a172a0eb8c774b6876f53947cf0af05c983d549"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6a4c459098c4934f9470280baf9ff8b38c365e147f33c8abc26039a948a664a5"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e89bf53a268f55c16989dab1cf0b32a5bff910762f138136ffad4146129b7a10"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:f09cb3e6bcb140f57b878580cf3b848976f67faaf53d850a7da9bfac12437068"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:616dd0c6686212ca90ff899bb37eb774798677e43dc6f78c6954470782d37399"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-win32.whl", hash = "sha256:58a66dbb3f0fef0396737ac09d6571a7f8d96a544ce3ed04c161f3d4fa8d51cc"}, - {file = "grpcio_tools-1.67.1-cp310-cp310-win_amd64.whl", hash = "sha256:89ee7c505bdf152e67c2cced6055aed4c2d4170f53a2b46a7e543d3b90e7b977"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-linux_armv7l.whl", hash = "sha256:6d80ddd87a2fb7131d242f7d720222ef4f0f86f53ec87b0a6198c343d8e4a86e"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:b655425b82df51f3bd9fd3ba1a6282d5c9ce1937709f059cb3d419b224532d89"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:250241e6f9d20d0910a46887dfcbf2ec9108efd3b48f3fb95bb42d50d09d03f8"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6008f5a5add0b6f03082edb597acf20d5a9e4e7c55ea1edac8296c19e6a0ec8d"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5eff9818c3831fa23735db1fa39aeff65e790044d0a312260a0c41ae29cc2d9e"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:262ab7c40113f8c3c246e28e369661ddf616a351cb34169b8ba470c9a9c3b56f"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:1eebd8c746adf5786fa4c3056258c21cc470e1eca51d3ed23a7fb6a697fe4e81"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-win32.whl", hash = "sha256:3eff92fb8ca1dd55e3af0ef02236c648921fb7d0e8ca206b889585804b3659ae"}, - {file = "grpcio_tools-1.67.1-cp311-cp311-win_amd64.whl", hash = "sha256:1ed18281ee17e5e0f9f6ce0c6eb3825ca9b5a0866fc1db2e17fab8aca28b8d9f"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-linux_armv7l.whl", hash = "sha256:bd5caef3a484e226d05a3f72b2d69af500dca972cf434bf6b08b150880166f0b"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:48a2d63d1010e5b218e8e758ecb2a8d63c0c6016434e9f973df1c3558917020a"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:baa64a6aa009bffe86309e236c81b02cd4a88c1ebd66f2d92e84e9b97a9ae857"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4ab318c40b5e3c097a159035fc3e4ecfbe9b3d2c9de189e55468b2c27639a6ab"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:50eba3e31f9ac1149463ad9182a37349850904f142cffbd957cd7f54ec320b8e"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:de6fbc071ecc4fe6e354a7939202191c1f1abffe37fbce9b08e7e9a5b93eba3d"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:db9e87f6ea4b0ce99b2651203480585fd9e8dd0dd122a19e46836e93e3a1b749"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-win32.whl", hash = "sha256:6a595a872fb720dde924c4e8200f41d5418dd6baab8cc1a3c1e540f8f4596351"}, - {file = "grpcio_tools-1.67.1-cp312-cp312-win_amd64.whl", hash = "sha256:92eebb9b31031604ae97ea7657ae2e43149b0394af7117ad7e15894b6cc136dc"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-linux_armv7l.whl", hash = "sha256:9a3b9510cc87b6458b05ad49a6dee38df6af37f9ee6aa027aa086537798c3d4a"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:9e4c9b9fa9b905f15d414cb7bd007ba7499f8907bdd21231ab287a86b27da81a"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-manylinux_2_17_aarch64.whl", hash = "sha256:e11a98b41af4bc88b7a738232b8fa0306ad82c79fa5d7090bb607f183a57856f"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de0fcfe61c26679d64b1710746f2891f359593f76894fcf492c37148d5694f00"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7ae3b3e2ee5aad59dece65a613624c46a84c9582fc3642686537c6dfae8e47dc"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-musllinux_1_1_i686.whl", hash = "sha256:9a630f83505b6471a3094a7a372a1240de18d0cd3e64f4fbf46b361bac2be65b"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:d85a1fcbacd3e08dc2b3d1d46b749351a9a50899fa35cf2ff040e1faf7d405ad"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-win32.whl", hash = "sha256:778470f025f25a1fca5a48c93c0a18af395b46b12dd8df7fca63736b85181f41"}, - {file = "grpcio_tools-1.67.1-cp313-cp313-win_amd64.whl", hash = "sha256:6961da86e9856b4ddee0bf51ef6636b4bf9c29c0715aa71f3c8f027c45d42654"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-linux_armv7l.whl", hash = "sha256:c088dfbbe289bb171ca9c98fabbf7ecc8c1c51af2ba384ef32a4fdcb784b17e9"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:11ce546daf8f8c04ee8d4a1673b4754cda4a0a9d505d820efd636e37f46b50c5"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-manylinux_2_17_aarch64.whl", hash = "sha256:83fecb2f6119ef0eea68a091964898418c1969375d399956ff8d1741beb7b081"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d39c1aa6b26e2602d815b9cfa37faba48b2889680ae6baa002560cf0f0c69fac"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e975dc9fb61a77d88e739eb17b3361f369d03cc754217f02dd83ec7cfac32e38"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:6c6e5c5b15f2eedc2a81268d588d14a79a52020383bf87b3c7595df7b571504a"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:a974e0ce01806adba718e6eb8c385defe6805b18969b6914da7db55fb055ae45"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-win32.whl", hash = "sha256:35e9b0a82be9f425aa67ee1dc69ba02cf135aeee3f22c0455c5d1b01769bbdb4"}, - {file = "grpcio_tools-1.67.1-cp38-cp38-win_amd64.whl", hash = "sha256:0436c97f29e654d2eccd7419907ee019caf7eea6bdc6ae91d98011f6c5f44f17"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-linux_armv7l.whl", hash = "sha256:718fbb6d68a3d000cb3cf381642660eade0e8c1b0bf7472b84b3367f5b56171d"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:062887d2e9cb8bc261c21a2b8da714092893ce62b4e072775eaa9b24dcbf3b31"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:59dbf14a1ce928bf03a58fa157034374411159ab5d32ad83cf146d9400eed618"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ac552fc9c76d50408d7141e1fd1eae69d85fbf7ae71da4d8877eaa07127fbe74"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5c6583773400e441dc62d08b5a32357babef1a9f9f73c3ac328a75af550815a9"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:862108f90f2f6408908e5ea4584c5104f7caf419c6d73aa3ff36bf8284cca224"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:587c6326425f37dca2291f46b93e446c07ee781cea27725865b806b7a049ec56"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-win32.whl", hash = "sha256:d7d46a4405bd763525215b6e073888386587aef9b4a5ec125bf97ba897ac757d"}, - {file = "grpcio_tools-1.67.1-cp39-cp39-win_amd64.whl", hash = "sha256:e2fc7980e8bab3ee5ab98b6fdc2a8fbaa4785f196d897531346176fda49a605c"}, - {file = "grpcio_tools-1.67.1.tar.gz", hash = "sha256:d9657f5ddc62b52f58904e6054b7d8a8909ed08a1e28b734be3a707087bcf004"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:9509a5c3ed3d54fa7ac20748d501cb86668f764605a0a68f275339ee0f1dc1a6"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:59a885091bf29700ba0e14a954d156a18714caaa2006a7f328b18e1ac4b1e721"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:d3e678162e1d7a8720dc05fdd537fc8df082a50831791f7bb1c6f90095f8368b"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:10d03e3ad4af6284fd27cb14f5a3d52045913c1253e3e24a384ed91bc8adbfcd"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1769d7f529de1cc102f7fb900611e3c0b69bdb244fca1075b24d6e5b49024586"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:88640d95ee41921ac7352fa5fadca52a06d7e21fbe53e6a706a9a494f756be7d"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:e903d07bc65232aa9e7704c829aec263e1e139442608e473d7912417a9908e29"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-win32.whl", hash = "sha256:66b70b37184d40806844f51c2757c6b852511d4ea46a3bf2c7e931a47b455bc6"}, + {file = "grpcio_tools-1.68.0-cp310-cp310-win_amd64.whl", hash = "sha256:b47ae076ffb29a68e517bc03552bef0d9c973f8e18adadff180b123e973a26ea"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:f65942fab440e99113ce14436deace7554d5aa554ea18358e3a5f3fc47efe322"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8fefc6d000e169a97336feded23ce614df3fb9926fc48c7a9ff8ea459d93b5b0"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:6dd69c9f3ff85eee8d1f71adf7023c638ca8d465633244ac1b7f19bc3668612d"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7dc5195dc02057668cc22da1ff1aea1811f6fa0deb801b3194dec1fe0bab1cf0"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:849b12bec2320e49e988df104c92217d533e01febac172a4495caab36d9f0edc"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:766c2cd2e365e0fc0e559af56f2c2d144d95fd7cb8668a34d533e66d6435eb34"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:2ec3a2e0afa4866ccc5ba33c071aebaa619245dfdd840cbb74f2b0591868d085"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-win32.whl", hash = "sha256:80b733014eb40d920d836d782e5cdea0dcc90d251a2ffb35ab378ef4f8a42c14"}, + {file = "grpcio_tools-1.68.0-cp311-cp311-win_amd64.whl", hash = "sha256:f95103e3e4e7fee7c6123bc9e4e925e07ad24d8d09d7c1c916fb6c8d1cb9e726"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-linux_armv7l.whl", hash = "sha256:dd9a654af8536b3de8525bff72a245fef62d572eabf96ac946fe850e707cb27d"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:0f77957e3a0916a0dd18d57ce6b49d95fc9a5cfed92310f226339c0fda5394f6"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:92a09afe64fe26696595de2036e10967876d26b12c894cc9160f00152cacebe7"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:28ebdbad2ef16699d07400b65260240851049a75502eff69a59b127d3ab960f1"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5d3150d784d8050b10dcf5eb06e04fb90747a1547fed3a062a608d940fe57066"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:261d98fd635595de42aadee848f9af46da6654d63791c888891e94f66c5d0682"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:061345c0079b9471f32230186ab01acb908ea0e577bc1699a8cf47acef8be4af"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-win32.whl", hash = "sha256:533ce6791a5ba21e35d74c6c25caf4776f5692785a170c01ea1153783ad5af31"}, + {file = "grpcio_tools-1.68.0-cp312-cp312-win_amd64.whl", hash = "sha256:56842a0ce74b4b92eb62cd5ee00181b2d3acc58ba0c4fd20d15a5db51f891ba6"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-linux_armv7l.whl", hash = "sha256:1117a81592542f0c36575082daa6413c57ca39188b18a4c50ec7332616f4b97e"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:51e5a090849b30c99a2396d42140b8a3e558eff6cdfa12603f9582e2cd07724e"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-manylinux_2_17_aarch64.whl", hash = "sha256:4fe611d89a1836df8936f066d39c7eb03d4241806449ec45d4b8e1c843ae8011"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c10f3faa0cc4d89eb546f53b623837af23e86dc495d3b89510bcc0e0a6c0b8b2"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:46b537480b8fd2195d988120a28467601a2a3de2e504043b89fb90318e1eb754"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-musllinux_1_1_i686.whl", hash = "sha256:17d0c9004ea82b4213955a585401e80c30d4b37a1d4ace32ccdea8db4d3b7d43"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:2919faae04fe47bad57fc9b578aeaab527da260e851f321a253b6b11862254a8"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-win32.whl", hash = "sha256:ee86157ef899f58ba2fe1055cce0d33bd703e99aa6d5a0895581ac3969f06bfa"}, + {file = "grpcio_tools-1.68.0-cp313-cp313-win_amd64.whl", hash = "sha256:d0470ffc6a93c86cdda48edd428d22e2fef17d854788d60d0d5f291038873157"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-linux_armv7l.whl", hash = "sha256:795f2cd76f68a12b0b5541b98187ba367dd69b49d359cf98b781ead742961370"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:57e29e78c33fb1b1d557fbe7650d722d1f2b0a9f53ea73beb8ea47e627b6000b"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-manylinux_2_17_aarch64.whl", hash = "sha256:700f171cd3293ee8d50cd43171562ff07b14fa8e49ee471cd91c6924c7da8644"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:196cd8a3a5963a4c9e424314df9eb573b305e6f958fe6508d26580ce01e7aa56"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cad40c3164ee9cef62524dea509449ea581b17ea493178beef051bf79b5103ca"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:ab93fab49fa1e699e577ff5fbb99aba660164d710d4c33cfe0aa9d06f585539f"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:511224a99726eb84db9ddb84dc8a75377c3eae797d835f99e80128ec618376d5"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-win32.whl", hash = "sha256:b4ca81770cd729a9ea536d871aacedbde2b732bb9bb83c9d993d63f58502153d"}, + {file = "grpcio_tools-1.68.0-cp38-cp38-win_amd64.whl", hash = "sha256:6950725bf7a496f81d3ec3324334ffc9dbec743b510dd0e897f51f8627eeb6ac"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-linux_armv7l.whl", hash = "sha256:01ace351a51d7ee120963a4612b1f00e964462ec548db20d17f8902e238592c8"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:5afd2f3f7257b52228a7808a2b4a765893d4d802d7a2377d9284853e67d045c6"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:453ee3193d59c974c678d91f08786f43c25ef753651b0825dc3d008c31baf68d"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b094b22919b786ad73c20372ef5e546330e7cd2c6dc12293b7ed586975f35d38"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:26335eea976dfc1ff5d90b19c309a9425bd53868112a0507ad20f297f2c21d3e"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:c77ecc5164bb413a613bdac9091dcc29d26834a2ac42fcd1afdfcda9e3003e68"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:e31be6dc61496a59c1079b0a669f93dfcc2cdc4b1dbdc4374247cd09cee1329b"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-win32.whl", hash = "sha256:3aa40958355920ae2846c6fb5cadac4f2c8e33234a2982fef8101da0990e3968"}, + {file = "grpcio_tools-1.68.0-cp39-cp39-win_amd64.whl", hash = "sha256:19bafb80948eda979b1b3a63c1567162d06249f43068a0e46a028a448e6f72d4"}, + {file = "grpcio_tools-1.68.0.tar.gz", hash = "sha256:737804ec2225dd4cc27e633b4ca0e963b0795161bf678285fab6586e917fd867"}, ] [package.dependencies] -grpcio = ">=1.67.1" +grpcio = ">=1.68.0" protobuf = ">=5.26.1,<6.0dev" setuptools = "*" @@ -500,13 +500,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.6" +version = "1.0.7" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"}, - {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"}, + {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, + {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, ] [package.dependencies] @@ -656,7 +656,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.15" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -681,18 +681,18 @@ url = "../../core" [[package]] name = "langsmith" -version = "0.1.139" +version = "0.1.146" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, - {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, + {file = "langsmith-0.1.146-py3-none-any.whl", hash = "sha256:9d062222f1a32c9b047dab0149b24958f988989cd8d4a5f9139ff959a51e59d8"}, + {file = "langsmith-0.1.146.tar.gz", hash = "sha256:ead8b0b9d5b6cd3ac42937ec48bdf09d4afe7ca1bba22dc05eb65591a18106f8"}, ] [package.dependencies] httpx = ">=0.23.0,<1" -orjson = ">=3.9.14,<4.0.0" +orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""} pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, @@ -980,32 +980,32 @@ reference = ["Pillow", "google-re2"] [[package]] name = "onnxruntime" -version = "1.20.0" +version = "1.20.1" description = "ONNX Runtime is a runtime accelerator for Machine Learning models" optional = true python-versions = "*" files = [ - {file = "onnxruntime-1.20.0-cp310-cp310-macosx_13_0_universal2.whl", hash = "sha256:2ac38bc6cbf7bb8527ded58711af6ef2c8c59d070f0fde58f83824422526922a"}, - {file = "onnxruntime-1.20.0-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5cfd5a22abc11b273ec76fa773e22db19b749e27bf1ed05dd50d207f1817aae1"}, - {file = "onnxruntime-1.20.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6b5daee2d03909b589f1a9ab24c325cc3c33ab7f736228158784fb1a97a92308"}, - {file = "onnxruntime-1.20.0-cp310-cp310-win32.whl", hash = "sha256:e1eb08c13f91f830eb8df4f4e17a2a2652d1165f50bbed4f28f2afbf425c55d7"}, - {file = "onnxruntime-1.20.0-cp310-cp310-win_amd64.whl", hash = "sha256:cfcc1d21a12076bcc213441b405c48e1f21dedb36943e31eb93cb7a12b34678e"}, - {file = "onnxruntime-1.20.0-cp311-cp311-macosx_13_0_universal2.whl", hash = "sha256:3398354e9145c68edc09dbc72265401150027e76716ae758e8d9b52e6a7ddca0"}, - {file = "onnxruntime-1.20.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8a831b720d0a7be8241a230cb06f592e8bb66652d7cea54ce02d83769651fdee"}, - {file = "onnxruntime-1.20.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:041fefe60af844ebd90f344c84f908201490555cd0a6d78dd0a7acdc27b59972"}, - {file = "onnxruntime-1.20.0-cp311-cp311-win32.whl", hash = "sha256:83da64d2824809d0f6977db8bfc5091f742c26f09dfd66a3934e673780f5f87a"}, - {file = "onnxruntime-1.20.0-cp311-cp311-win_amd64.whl", hash = "sha256:bfa390046332f5fca6f8af8c9d17164621ac52e66b11518e187278b19364800c"}, - {file = "onnxruntime-1.20.0-cp312-cp312-macosx_13_0_universal2.whl", hash = "sha256:97c2b91bfea063f9c3457422d28a336bfd2859001cd880645adfa7184e29dd79"}, - {file = "onnxruntime-1.20.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:51e7b34e398089c4ed8d0f50722d7a64a4d5f11b38c4a42576458a03c6dbc72e"}, - {file = "onnxruntime-1.20.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0e259378ff2843321e0bf4552adcbee48822c91d77d42dde78b87dcdf10ad01f"}, - {file = "onnxruntime-1.20.0-cp312-cp312-win32.whl", hash = "sha256:428abc1f7d8eb425887e2b7726044f2af7b5a098359455e7d2d92343f04ad0ff"}, - {file = "onnxruntime-1.20.0-cp312-cp312-win_amd64.whl", hash = "sha256:d5f23cbfeb546e16ffea81c28d2e796a53197fdc6c92540648e2aa53a7c7a637"}, - {file = "onnxruntime-1.20.0-cp313-cp313-macosx_13_0_universal2.whl", hash = "sha256:95b91126bc3e1754868da1d3d2d08a7a10279b8ff5cea5e34e92fbe3fd691dcf"}, - {file = "onnxruntime-1.20.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d57c10d7729347d6663f32b3f569f33d69a95e150d37ff6af4be9b9ab1ffdc25"}, - {file = "onnxruntime-1.20.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b9c38735dac127d0eeb957ec312c8f1ae90ecae2779a55b2fa279aa7bd116cbd"}, - {file = "onnxruntime-1.20.0-cp313-cp313-win_amd64.whl", hash = "sha256:25514cec4ea251d492aa1e38a7395d8801e64a4c940a154aef84cfad97ae4628"}, - {file = "onnxruntime-1.20.0-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:640ad9ea72d322f0325a51544eddb54f4fa843c4348573c88a9cb44f46678f3f"}, - {file = "onnxruntime-1.20.0-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:dc4e7c10c98c1f407835448c26a7e14ebff3234f131e1fbc53bd9500c828df89"}, + {file = "onnxruntime-1.20.1-cp310-cp310-macosx_13_0_universal2.whl", hash = "sha256:e50ba5ff7fed4f7d9253a6baf801ca2883cc08491f9d32d78a80da57256a5439"}, + {file = "onnxruntime-1.20.1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7b2908b50101a19e99c4d4e97ebb9905561daf61829403061c1adc1b588bc0de"}, + {file = "onnxruntime-1.20.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d82daaec24045a2e87598b8ac2b417b1cce623244e80e663882e9fe1aae86410"}, + {file = "onnxruntime-1.20.1-cp310-cp310-win32.whl", hash = "sha256:4c4b251a725a3b8cf2aab284f7d940c26094ecd9d442f07dd81ab5470e99b83f"}, + {file = "onnxruntime-1.20.1-cp310-cp310-win_amd64.whl", hash = "sha256:d3b616bb53a77a9463707bb313637223380fc327f5064c9a782e8ec69c22e6a2"}, + {file = "onnxruntime-1.20.1-cp311-cp311-macosx_13_0_universal2.whl", hash = "sha256:06bfbf02ca9ab5f28946e0f912a562a5f005301d0c419283dc57b3ed7969bb7b"}, + {file = "onnxruntime-1.20.1-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f6243e34d74423bdd1edf0ae9596dd61023b260f546ee17d701723915f06a9f7"}, + {file = "onnxruntime-1.20.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5eec64c0269dcdb8d9a9a53dc4d64f87b9e0c19801d9321246a53b7eb5a7d1bc"}, + {file = "onnxruntime-1.20.1-cp311-cp311-win32.whl", hash = "sha256:a19bc6e8c70e2485a1725b3d517a2319603acc14c1f1a017dda0afe6d4665b41"}, + {file = "onnxruntime-1.20.1-cp311-cp311-win_amd64.whl", hash = "sha256:8508887eb1c5f9537a4071768723ec7c30c28eb2518a00d0adcd32c89dea3221"}, + {file = "onnxruntime-1.20.1-cp312-cp312-macosx_13_0_universal2.whl", hash = "sha256:22b0655e2bf4f2161d52706e31f517a0e54939dc393e92577df51808a7edc8c9"}, + {file = "onnxruntime-1.20.1-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f1f56e898815963d6dc4ee1c35fc6c36506466eff6d16f3cb9848cea4e8c8172"}, + {file = "onnxruntime-1.20.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bb71a814f66517a65628c9e4a2bb530a6edd2cd5d87ffa0af0f6f773a027d99e"}, + {file = "onnxruntime-1.20.1-cp312-cp312-win32.whl", hash = "sha256:bd386cc9ee5f686ee8a75ba74037750aca55183085bf1941da8efcfe12d5b120"}, + {file = "onnxruntime-1.20.1-cp312-cp312-win_amd64.whl", hash = "sha256:19c2d843eb074f385e8bbb753a40df780511061a63f9def1b216bf53860223fb"}, + {file = "onnxruntime-1.20.1-cp313-cp313-macosx_13_0_universal2.whl", hash = "sha256:cc01437a32d0042b606f462245c8bbae269e5442797f6213e36ce61d5abdd8cc"}, + {file = "onnxruntime-1.20.1-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:fb44b08e017a648924dbe91b82d89b0c105b1adcfe31e90d1dc06b8677ad37be"}, + {file = "onnxruntime-1.20.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bda6aebdf7917c1d811f21d41633df00c58aff2bef2f598f69289c1f1dabc4b3"}, + {file = "onnxruntime-1.20.1-cp313-cp313-win_amd64.whl", hash = "sha256:d30367df7e70f1d9fc5a6a68106f5961686d39b54d3221f760085524e8d38e16"}, + {file = "onnxruntime-1.20.1-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c9158465745423b2b5d97ed25aa7740c7d38d2993ee2e5c3bfacb0c4145c49d8"}, + {file = "onnxruntime-1.20.1-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0df6f2df83d61f46e842dbcde610ede27218947c33e994545a22333491e72a3b"}, ] [package.dependencies] @@ -1018,80 +1018,97 @@ sympy = "*" [[package]] name = "orjson" -version = "3.10.10" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.10-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:b788a579b113acf1c57e0a68e558be71d5d09aa67f62ca1f68e01117e550a998"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:804b18e2b88022c8905bb79bd2cbe59c0cd014b9328f43da8d3b28441995cda4"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9972572a1d042ec9ee421b6da69f7cc823da5962237563fa548ab17f152f0b9b"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc6993ab1c2ae7dd0711161e303f1db69062955ac2668181bfdf2dd410e65258"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d78e4cacced5781b01d9bc0f0cd8b70b906a0e109825cb41c1b03f9c41e4ce86"}, - {file = "orjson-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e6eb2598df518281ba0cbc30d24c5b06124ccf7e19169e883c14e0831217a0bc"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:23776265c5215ec532de6238a52707048401a568f0fa0d938008e92a147fe2c7"}, - {file = "orjson-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8cc2a654c08755cef90b468ff17c102e2def0edd62898b2486767204a7f5cc9c"}, - {file = "orjson-3.10.10-cp310-none-win32.whl", hash = "sha256:081b3fc6a86d72efeb67c13d0ea7c030017bd95f9868b1e329a376edc456153b"}, - {file = "orjson-3.10.10-cp310-none-win_amd64.whl", hash = "sha256:ff38c5fb749347768a603be1fb8a31856458af839f31f064c5aa74aca5be9efe"}, - {file = "orjson-3.10.10-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:879e99486c0fbb256266c7c6a67ff84f46035e4f8749ac6317cc83dacd7f993a"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:019481fa9ea5ff13b5d5d95e6fd5ab25ded0810c80b150c2c7b1cc8660b662a7"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0dd57eff09894938b4c86d4b871a479260f9e156fa7f12f8cad4b39ea8028bb5"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dbde6d70cd95ab4d11ea8ac5e738e30764e510fc54d777336eec09bb93b8576c"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b2625cb37b8fb42e2147404e5ff7ef08712099197a9cd38895006d7053e69d6"}, - {file = "orjson-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dbf3c20c6a7db69df58672a0d5815647ecf78c8e62a4d9bd284e8621c1fe5ccb"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:75c38f5647e02d423807d252ce4528bf6a95bd776af999cb1fb48867ed01d1f6"}, - {file = "orjson-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:23458d31fa50ec18e0ec4b0b4343730928296b11111df5f547c75913714116b2"}, - {file = "orjson-3.10.10-cp311-none-win32.whl", hash = "sha256:2787cd9dedc591c989f3facd7e3e86508eafdc9536a26ec277699c0aa63c685b"}, - {file = "orjson-3.10.10-cp311-none-win_amd64.whl", hash = "sha256:6514449d2c202a75183f807bc755167713297c69f1db57a89a1ef4a0170ee269"}, - {file = "orjson-3.10.10-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:8564f48f3620861f5ef1e080ce7cd122ee89d7d6dacf25fcae675ff63b4d6e05"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5bf161a32b479034098c5b81f2608f09167ad2fa1c06abd4e527ea6bf4837a9"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:68b65c93617bcafa7f04b74ae8bc2cc214bd5cb45168a953256ff83015c6747d"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e8e28406f97fc2ea0c6150f4c1b6e8261453318930b334abc419214c82314f85"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e4d0d9fe174cc7a5bdce2e6c378bcdb4c49b2bf522a8f996aa586020e1b96cee"}, - {file = "orjson-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b3be81c42f1242cbed03cbb3973501fcaa2675a0af638f8be494eaf37143d999"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:65f9886d3bae65be026219c0a5f32dbbe91a9e6272f56d092ab22561ad0ea33b"}, - {file = "orjson-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:730ed5350147db7beb23ddaf072f490329e90a1d059711d364b49fe352ec987b"}, - {file = "orjson-3.10.10-cp312-none-win32.whl", hash = "sha256:a8f4bf5f1c85bea2170800020d53a8877812892697f9c2de73d576c9307a8a5f"}, - {file = "orjson-3.10.10-cp312-none-win_amd64.whl", hash = "sha256:384cd13579a1b4cd689d218e329f459eb9ddc504fa48c5a83ef4889db7fd7a4f"}, - {file = "orjson-3.10.10-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:44bffae68c291f94ff5a9b4149fe9d1bdd4cd0ff0fb575bcea8351d48db629a1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e27b4c6437315df3024f0835887127dac2a0a3ff643500ec27088d2588fa5ae1"}, - {file = "orjson-3.10.10-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca84df16d6b49325a4084fd8b2fe2229cb415e15c46c529f868c3387bb1339d"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c14ce70e8f39bd71f9f80423801b5d10bf93d1dceffdecd04df0f64d2c69bc01"}, - {file = "orjson-3.10.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:24ac62336da9bda1bd93c0491eff0613003b48d3cb5d01470842e7b52a40d5b4"}, - {file = "orjson-3.10.10-cp313-none-win32.whl", hash = "sha256:eb0a42831372ec2b05acc9ee45af77bcaccbd91257345f93780a8e654efc75db"}, - {file = "orjson-3.10.10-cp313-none-win_amd64.whl", hash = "sha256:f0c4f37f8bf3f1075c6cc8dd8a9f843689a4b618628f8812d0a71e6968b95ffd"}, - {file = "orjson-3.10.10-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:829700cc18503efc0cf502d630f612884258020d98a317679cd2054af0259568"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e0ceb5e0e8c4f010ac787d29ae6299846935044686509e2f0f06ed441c1ca949"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0c25908eb86968613216f3db4d3003f1c45d78eb9046b71056ca327ff92bdbd4"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:218cb0bc03340144b6328a9ff78f0932e642199ac184dd74b01ad691f42f93ff"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e2277ec2cea3775640dc81ab5195bb5b2ada2fe0ea6eee4677474edc75ea6785"}, - {file = "orjson-3.10.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:848ea3b55ab5ccc9d7bbd420d69432628b691fba3ca8ae3148c35156cbd282aa"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:e3e67b537ac0c835b25b5f7d40d83816abd2d3f4c0b0866ee981a045287a54f3"}, - {file = "orjson-3.10.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:7948cfb909353fce2135dcdbe4521a5e7e1159484e0bb024c1722f272488f2b8"}, - {file = "orjson-3.10.10-cp38-none-win32.whl", hash = "sha256:78bee66a988f1a333dc0b6257503d63553b1957889c17b2c4ed72385cd1b96ae"}, - {file = "orjson-3.10.10-cp38-none-win_amd64.whl", hash = "sha256:f1d647ca8d62afeb774340a343c7fc023efacfd3a39f70c798991063f0c681dd"}, - {file = "orjson-3.10.10-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:5a059afddbaa6dd733b5a2d76a90dbc8af790b993b1b5cb97a1176ca713b5df8"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6f9b5c59f7e2a1a410f971c5ebc68f1995822837cd10905ee255f96074537ee6"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d5ef198bafdef4aa9d49a4165ba53ffdc0a9e1c7b6f76178572ab33118afea25"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:aaf29ce0bb5d3320824ec3d1508652421000ba466abd63bdd52c64bcce9eb1fa"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dddd5516bcc93e723d029c1633ae79c4417477b4f57dad9bfeeb6bc0315e654a"}, - {file = "orjson-3.10.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a12f2003695b10817f0fa8b8fca982ed7f5761dcb0d93cff4f2f9f6709903fd7"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:672f9874a8a8fb9bb1b771331d31ba27f57702c8106cdbadad8bda5d10bc1019"}, - {file = "orjson-3.10.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1dcbb0ca5fafb2b378b2c74419480ab2486326974826bbf6588f4dc62137570a"}, - {file = "orjson-3.10.10-cp39-none-win32.whl", hash = "sha256:d9bbd3a4b92256875cb058c3381b782649b9a3c68a4aa9a2fff020c2f9cfc1be"}, - {file = "orjson-3.10.10-cp39-none-win_amd64.whl", hash = "sha256:766f21487a53aee8524b97ca9582d5c6541b03ab6210fbaf10142ae2f3ced2aa"}, - {file = "orjson-3.10.10.tar.gz", hash = "sha256:37949383c4df7b4337ce82ee35b6d7471e55195efa7dcb45ab8226ceadb0fe3b"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] name = "packaging" -version = "24.1" +version = "24.2" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" files = [ - {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"}, - {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"}, + {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, + {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, ] [[package]] @@ -1247,22 +1264,19 @@ files = [ [[package]] name = "pydantic" -version = "2.9.2" +version = "2.10.2" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"}, - {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"}, + {file = "pydantic-2.10.2-py3-none-any.whl", hash = "sha256:cfb96e45951117c3024e6b67b25cdc33a3cb7b2fa62e239f7af1378358a1d99e"}, + {file = "pydantic-2.10.2.tar.gz", hash = "sha256:2bc2d7f17232e0841cbba4641e65ba1eb6fafb3a08de3a091ff3ce14a197c4fa"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.23.4" -typing-extensions = [ - {version = ">=4.6.1", markers = "python_version < \"3.13\""}, - {version = ">=4.12.2", markers = "python_version >= \"3.13\""}, -] +pydantic-core = "2.27.1" +typing-extensions = ">=4.12.2" [package.extras] email = ["email-validator (>=2.0.0)"] @@ -1270,100 +1284,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.23.4" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"}, - {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2"}, - {file = "pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3"}, - {file = "pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071"}, - {file = "pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119"}, - {file = "pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8"}, - {file = "pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e"}, - {file = "pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0"}, - {file = "pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64"}, - {file = "pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f"}, - {file = "pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231"}, - {file = "pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36"}, - {file = "pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e"}, - {file = "pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24"}, - {file = "pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84"}, - {file = "pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:7530e201d10d7d14abce4fb54cfe5b94a0aefc87da539d0346a484ead376c3cc"}, - {file = "pydantic_core-2.23.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cb3da3fd1b6a5d0279a01877713dbda118a2a4fc6f0d821a57da2e464793f05"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:42c6dcb030aefb668a2b7009c85b27f90e51e6a3b4d5c9bc4c57631292015b0d"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:696dd8d674d6ce621ab9d45b205df149399e4bb9aa34102c970b721554828510"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2971bb5ffe72cc0f555c13e19b23c85b654dd2a8f7ab493c262071377bfce9f6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8394d940e5d400d04cad4f75c0598665cbb81aecefaca82ca85bd28264af7f9b"}, - {file = "pydantic_core-2.23.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0dff76e0602ca7d4cdaacc1ac4c005e0ce0dcfe095d5b5259163a80d3a10d327"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7d32706badfe136888bdea71c0def994644e09fff0bfe47441deaed8e96fdbc6"}, - {file = "pydantic_core-2.23.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f"}, - {file = "pydantic_core-2.23.4-cp313-none-win32.whl", hash = "sha256:3d5639516376dce1940ea36edf408c554475369f5da2abd45d44621cb616f769"}, - {file = "pydantic_core-2.23.4-cp313-none-win_amd64.whl", hash = "sha256:5a1504ad17ba4210df3a045132a7baeeba5a200e930f57512ee02909fc5c4cb5"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555"}, - {file = "pydantic_core-2.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:81965a16b675b35e1d09dd14df53f190f9129c0202356ed44ab2728b1c905658"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ffa2ebd4c8530079140dd2d7f794a9d9a73cbb8e9d59ffe24c63436efa8f271"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:61817945f2fe7d166e75fbfb28004034b48e44878177fc54d81688e7b85a3665"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29d2c342c4bc01b88402d60189f3df065fb0dda3654744d5a165a5288a657368"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5e11661ce0fd30a6790e8bcdf263b9ec5988e95e63cf901972107efc49218b13"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad"}, - {file = "pydantic_core-2.23.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:374a5e5049eda9e0a44c696c7ade3ff355f06b1fe0bb945ea3cac2bc336478a2"}, - {file = "pydantic_core-2.23.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5c364564d17da23db1106787675fc7af45f2f7b58b4173bfdd105564e132e6fb"}, - {file = "pydantic_core-2.23.4-cp38-none-win32.whl", hash = "sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6"}, - {file = "pydantic_core-2.23.4-cp38-none-win_amd64.whl", hash = "sha256:5f5ff8d839f4566a474a969508fe1c5e59c31c80d9e140566f9a37bba7b8d556"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a"}, - {file = "pydantic_core-2.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f54b118ce5de9ac21c363d9b3caa6c800341e8c47a508787e5868c6b79c9323"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:86d2f57d3e1379a9525c5ab067b27dbb8a0642fb5d454e17a9ac434f9ce523e3"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1278e0d324f6908e872730c9102b0112477a7f7cf88b308e4fc36ce1bdb6d58c"}, - {file = "pydantic_core-2.23.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a6b5099eeec78827553827f4c6b8615978bb4b6a88e5d9b93eddf8bb6790f55"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040"}, - {file = "pydantic_core-2.23.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605"}, - {file = "pydantic_core-2.23.4-cp39-none-win32.whl", hash = "sha256:37b0fe330e4a58d3c58b24d91d1eb102aeec675a3db4c292ec3928ecd892a9a6"}, - {file = "pydantic_core-2.23.4-cp39-none-win_amd64.whl", hash = "sha256:1498bec4c05c9c787bde9125cfdcc63a41004ff167f495063191b863399b1a29"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433"}, - {file = "pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:78ddaaa81421a29574a682b3179d4cf9e6d405a09b99d93ddcf7e5239c742e21"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:883a91b5dd7d26492ff2f04f40fbb652de40fcc0afe07e8129e8ae779c2110eb"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88ad334a15b32a791ea935af224b9de1bf99bcd62fabf745d5f3442199d86d59"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:233710f069d251feb12a56da21e14cca67994eab08362207785cf8c598e74577"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:19442362866a753485ba5e4be408964644dd6a09123d9416c54cd49171f50744"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:624e278a7d29b6445e4e813af92af37820fafb6dcc55c012c834f9e26f9aaaef"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8"}, - {file = "pydantic_core-2.23.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e"}, - {file = "pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -1740,130 +1765,147 @@ files = [ [[package]] name = "setuptools" -version = "75.3.0" +version = "75.6.0" description = "Easily download, build, install, upgrade, and uninstall Python packages" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "setuptools-75.3.0-py3-none-any.whl", hash = "sha256:f2504966861356aa38616760c0f66568e535562374995367b4e69c7143cf6bcd"}, - {file = "setuptools-75.3.0.tar.gz", hash = "sha256:fba5dd4d766e97be1b1681d98712680ae8f2f26d7881245f2ce9e40714f1a686"}, + {file = "setuptools-75.6.0-py3-none-any.whl", hash = "sha256:ce74b49e8f7110f9bf04883b730f4765b774ef3ef28f722cce7c273d253aaf7d"}, + {file = "setuptools-75.6.0.tar.gz", hash = "sha256:8199222558df7c86216af4f84c30e9b34a61d8ba19366cc914424cdbd28252f6"}, ] [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.5.2)"] -core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.collections", "jaraco.functools", "jaraco.text (>=3.7)", "more-itertools", "more-itertools (>=8.8)", "packaging", "packaging (>=24)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.7.0)"] +core = ["importlib_metadata (>=6)", "jaraco.collections", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"] enabler = ["pytest-enabler (>=2.2)"] -test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test (>=5.5)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"] -type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.12.*)", "pytest-mypy"] +test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"] +type = ["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (>=1.12,<1.14)", "pytest-mypy"] [[package]] name = "simsimd" -version = "5.9.10" +version = "6.2.1" description = "Portable mixed-precision BLAS-like vector math library for x86 and ARM" optional = false python-versions = "*" files = [ - {file = "simsimd-5.9.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:50ef517a656aa658278028e93429829240b449160abbb21ac9fd6d70f7e549cf"}, - {file = "simsimd-5.9.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:519a699c210d27a407c34b037f3be9d0832f3b2d270355380fa46096ae9382e5"}, - {file = "simsimd-5.9.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d305b55fea2b9f4eed2d9b04adfc51e739dc529035d10a006919e5718987a34e"}, - {file = "simsimd-5.9.10-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:862f1e673b18bb33b895a438da459c2a5b4ae71e4835ae3fb8f299325921a86b"}, - {file = "simsimd-5.9.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:558eb9cdb6900bda5e624b658519d9a441aeefa1ff019e45cf290b0854e87092"}, - {file = "simsimd-5.9.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28f597142fe2a5dae7a19dc36d6c60676ba9ecba645c3c59d671e892e104ed2e"}, - {file = "simsimd-5.9.10-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:6f8abe8c3c3bcac402d0ee10eaacfff117b4cdab6c6948611f1eeefd94a10d29"}, - {file = "simsimd-5.9.10-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:4364a7baf27a42d7be73ed563d3283aad2c7b1b093f0039cd86cfe5499396fa8"}, - {file = "simsimd-5.9.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c286931e0b580f98de7c5ce4cd9cc3063b6ad866c36bc30dd493cf1dc30f3861"}, - {file = "simsimd-5.9.10-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:3d0c77a98e843fd85164a6fd2210967ba1b1da6035cabefb0f162b646c418afb"}, - {file = "simsimd-5.9.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:942a778b165180c0344e02516617d0f5d9209936fb3cbe096e3c7993f7fbefbf"}, - {file = "simsimd-5.9.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e7c61c4999743084917162887b37e0b71323ae4a4348ea9dba805c4ece49b4f2"}, - {file = "simsimd-5.9.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:5d42080da1d41f64115715de713a8cad90363f9046c7930429d0a94459033b79"}, - {file = "simsimd-5.9.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:83f897b12707c86fbedd87ab002f069e3ce4e98074f0008749e09e44651738e5"}, - {file = "simsimd-5.9.10-cp310-cp310-win32.whl", hash = "sha256:7947c76327031ec7c76e5b24fccd8d9c0525f44de70956c1def580d33ec49dd0"}, - {file = "simsimd-5.9.10-cp310-cp310-win_amd64.whl", hash = "sha256:35ad466a6a3543da4164e9c6a1b1b988148b127110595493ce1d1565e78ab9e4"}, - {file = "simsimd-5.9.10-cp310-cp310-win_arm64.whl", hash = "sha256:7000c23583637a5228df8c3d03fdde115e6540ffa300017cf85bef241665ce71"}, - {file = "simsimd-5.9.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:81d2b9dd6680bdd1dd9350116b550d4ae3e36a88a1ab49d853a3416d1b3631ba"}, - {file = "simsimd-5.9.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b4b2f01c33f6e6e37491191a114f1e6d894869e5635b73e1e62fcebc87d05339"}, - {file = "simsimd-5.9.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5868aa2a191cb58d8f5cfb0a74467e78c630a45dd9cada287b6948233acaf5ab"}, - {file = "simsimd-5.9.10-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3d90d7ab1e04f89deeaaca3c2a276bfbd9a957d5f72a2aaa267e6172f0b81c13"}, - {file = "simsimd-5.9.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:fdafb27d0956d51ffe6161a5354cb456f0c418e5d8a22a59e273afa0b16509c2"}, - {file = "simsimd-5.9.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9ab22a14a0931c01471cbb5fbc454dacc3cfb39c31fba2c463620b50ea113db8"}, - {file = "simsimd-5.9.10-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:a1cff519512cbd5416d990ab20460dd3f6f957fcd8ca42b1c5b8f9a3f841217c"}, - {file = "simsimd-5.9.10-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:1a5d05b125efd097f4503f927eedaf13a0bba363584a23cf9559b363d0ea73c4"}, - {file = "simsimd-5.9.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:4ee55151df12ef5d97f8bf78bba0eae6617b068a55e4bdde213039e45b9f556c"}, - {file = "simsimd-5.9.10-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:4f9e1279b4e017bd35c98db40dd71514e346bce28c18cd646e465218afe6c83c"}, - {file = "simsimd-5.9.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:07c17f078079953b02765148fe62d7cceac2cc6f6301f1462b8567b6e2107510"}, - {file = "simsimd-5.9.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:e6528244b99483ecf74b797e2890c6976da9e62bff30ea6c47af63cfe8c199a8"}, - {file = "simsimd-5.9.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:915729dd73a4ea0f9251146957b3247b64a0f12e9fb0b7f4a27a845af7e7e9bc"}, - {file = "simsimd-5.9.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:48eb28c0c44e13ad3e6ee9d1421f2a8b5ca707599a655c4e89e1b781e1c30db0"}, - {file = "simsimd-5.9.10-cp311-cp311-win32.whl", hash = "sha256:8d62f82d7ffbb911bf6d2ead7df2f6204d1061bec789185a7afd2df700d57202"}, - {file = "simsimd-5.9.10-cp311-cp311-win_amd64.whl", hash = "sha256:08f02f34b11bc7fc5f38f73c779d2963b5980abe014d216ac83299ced926d8b4"}, - {file = "simsimd-5.9.10-cp311-cp311-win_arm64.whl", hash = "sha256:9897f52eb9bd238ef8f63aa0b1262cc66637f11454950e762d53c4ffacea9f8a"}, - {file = "simsimd-5.9.10-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:a739c73b0b8526f905d0902c8e48404552115eed66af7bfc3eaaf3cdf76fb000"}, - {file = "simsimd-5.9.10-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7d8f499ad51beeb5530ddb3055a6e38dc9f81356db3d6cb2eb431be125754acf"}, - {file = "simsimd-5.9.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:ccd9958250d38fb393f8d4a5f26fde641f13cc8d86674badf120500e6a49ebc9"}, - {file = "simsimd-5.9.10-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:30ca3530a979b94da6758fcca045d3255c1c376594e379a990702b760292eebd"}, - {file = "simsimd-5.9.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:70b117e0b8b2119e595976105a37eb8c65f16a0cbc60d1fa9aaddad0d96b0567"}, - {file = "simsimd-5.9.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d9902b2dad0619b18ebaa259d6ca1865fa2e05284e9e6c28fbc1b25ed3e387a5"}, - {file = "simsimd-5.9.10-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:6c614f212dc074df0ec7e1ac8126d28327e66417c4e8767fc3a82ba639fc7c6f"}, - {file = "simsimd-5.9.10-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:af3bcf5b4b14184f60a90849495985be9b93e7b773e562b383d07156e651ed62"}, - {file = "simsimd-5.9.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e9c3acadb575610d6b53b4cf25e00fa50154ef4ba72f280e35b73666d6db8fd2"}, - {file = "simsimd-5.9.10-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff54621f44b0d147dfd1466f01b9671aaff7dd8b409f0841eedaafe047fdfd9b"}, - {file = "simsimd-5.9.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:904c9952a64a8a2d88a23525fa515b26e22c63e48f0b51650d2e626e98ec3826"}, - {file = "simsimd-5.9.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:439f9b8d9b0beed11d5d5f6c714b53fe7cf89cec221e8cedbcce4d472bbc0add"}, - {file = "simsimd-5.9.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:c577dc019847c08b6a79878d5c6962eab20393c816669707db2c172521a8b94a"}, - {file = "simsimd-5.9.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:1903b7e88a92146ffe1c65ff7aa03ff80723234815fa2905f00e48aeaa2e71ee"}, - {file = "simsimd-5.9.10-cp312-cp312-win32.whl", hash = "sha256:c7a6aba59871ce360742cafd3ac22d83b19dd4edaf6fc4f2bb0f6a9d45a3740b"}, - {file = "simsimd-5.9.10-cp312-cp312-win_amd64.whl", hash = "sha256:32352b3836bc79e6d5799bd53bb04ba6caad3359f8875a764a79c37276472c85"}, - {file = "simsimd-5.9.10-cp312-cp312-win_arm64.whl", hash = "sha256:091bf83c3d0aed9b73e7c6d599e070633a75d651bb11c93a4f5a4cbb9553ca48"}, - {file = "simsimd-5.9.10-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:c40111f7c65c11510cb3d97d9613f9079e287955f8767a7335903c717204f41f"}, - {file = "simsimd-5.9.10-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ae1daec7d6f14f3ba7fb80516eaef090e5f6e264e9298945f8745b1019ee4e78"}, - {file = "simsimd-5.9.10-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8512287f478a7312568f3f3a79460435eff325924675d02577f825847eed8d52"}, - {file = "simsimd-5.9.10-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:34d27a6a0e82c2d0baf06a71be9fd9f9118f48541807182015affdb997acc28d"}, - {file = "simsimd-5.9.10-cp37-cp37m-manylinux_2_28_aarch64.whl", hash = "sha256:4fa02f9858afd2bb2ed5f532d9e5da66d8b978323496e92b2d26586646e10395"}, - {file = "simsimd-5.9.10-cp37-cp37m-manylinux_2_28_x86_64.whl", hash = "sha256:538049f17be6c3c71d92077556a9a3653f94c4ce715ae88b22c0cec36b5890e8"}, - {file = "simsimd-5.9.10-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:72ad1d90686281d5aed310f16212ff72c93b75f76121400b448910d8ccc37625"}, - {file = "simsimd-5.9.10-cp37-cp37m-musllinux_1_2_armv7l.whl", hash = "sha256:d98f4f38b72c5f4e101d65f070e6be12cd25815d9f8a8c79236140ac8cbc6e1f"}, - {file = "simsimd-5.9.10-cp37-cp37m-musllinux_1_2_i686.whl", hash = "sha256:99df4222c3dc56d035c42dccc1bfce10efefae9db255ed900c1cb1b5cfe16cf0"}, - {file = "simsimd-5.9.10-cp37-cp37m-musllinux_1_2_ppc64le.whl", hash = "sha256:563e497867309a7b5877d5485348a67ed235f4b7cbe54fe4b4e7a4f464906c6c"}, - {file = "simsimd-5.9.10-cp37-cp37m-musllinux_1_2_s390x.whl", hash = "sha256:06be2760106aeaa0dce2aa89d0f143fbeffce3cfc3fd4a05c49737091610e8d3"}, - {file = "simsimd-5.9.10-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:399530090842a6afb8f43692fa5912c0f2f59294284f561b52a757e66283e368"}, - {file = "simsimd-5.9.10-cp37-cp37m-win32.whl", hash = "sha256:2574eb79da5c19152c844e1cd7ae7bf25c5a7feda8aecfb05f1dfa6ce294e3c1"}, - {file = "simsimd-5.9.10-cp37-cp37m-win_amd64.whl", hash = "sha256:e72a7cd7b61d7dd6c70ba7df3d856f56fe6217a29a21f9aeef34908022432d3b"}, - {file = "simsimd-5.9.10-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:70588e625fd495a7e5484b5ddb2a37a22979acc11031a8cee757e2c34c1985f8"}, - {file = "simsimd-5.9.10-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2db4140f6782cce03ef1b6558f486599655f87238ba12bf97f4f2cbbabe0757c"}, - {file = "simsimd-5.9.10-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:94b84f7aef7843116cf2773c487362f62ef124f76c6bbf52407ce84b5ec80ddc"}, - {file = "simsimd-5.9.10-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4a627ca323f155eb4e98472193fe6a18436a888434ae70457e855b8707612b75"}, - {file = "simsimd-5.9.10-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0048afa3eaed4ce18379242b08051fb641c4983b02f35da05b9de56a85a0f444"}, - {file = "simsimd-5.9.10-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4bcc49d7455eed591c6cb1132662a49442eba3f44a58bf4f393a45ac1e83ef5f"}, - {file = "simsimd-5.9.10-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:b3a5cdc53d816bad747e92afde771116180e9a8cc0e55e1ff56f798967df126b"}, - {file = "simsimd-5.9.10-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:d16c1f8a314b76122cc485fb2ba581de31791928a280810153c567d029f3ddc3"}, - {file = "simsimd-5.9.10-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:9d3551249c78c39db5badefd2fc08022105f320a9d6135573d95676e0962e1b0"}, - {file = "simsimd-5.9.10-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:518c5afb12b82f353075355283fb59a5dc5fb373ff4602f1af974072dd988eaa"}, - {file = "simsimd-5.9.10-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:7d636fbef37b1660499572cb1e210085ff8c0ad815e8d59cc59dab9e21ce1818"}, - {file = "simsimd-5.9.10-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:37b0e01b1053aa8a13f586d023b8cc2876aec404ab9590db2070bfce36d9d6fd"}, - {file = "simsimd-5.9.10-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:64f04e8dc24e7fcb1be85adb1ebc70fe082fe94974e1066e89957d7b9d3f7696"}, - {file = "simsimd-5.9.10-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:447ea692083b2e8656d22877aa346733a792ed79af74c46c365c0527f23919bc"}, - {file = "simsimd-5.9.10-cp38-cp38-win32.whl", hash = "sha256:d94c103e4dbdc667a80f209361512caac1576feea994c3de61989a038fe4be3b"}, - {file = "simsimd-5.9.10-cp38-cp38-win_amd64.whl", hash = "sha256:3f5c2626c347b75a5fa20fce4ff6a48b6054b5b2445cb3c4a2fe7f3b85956104"}, - {file = "simsimd-5.9.10-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:428859c2039be07ebae2e993aaab88eb5e3310c244de8d6070280cb77e0801fc"}, - {file = "simsimd-5.9.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f949106671905cc875e6c947d9f58c5473b0a143d47ba5a2e2759254b371240e"}, - {file = "simsimd-5.9.10-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3c00096923e3462cb74f82455b6312d498ff6952fe3dc5c30e1171f2a0fc6ea3"}, - {file = "simsimd-5.9.10-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:687229a77e1ce2b229d3d9ac74dfd167808db261d8271573d10b57bc11461188"}, - {file = "simsimd-5.9.10-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:47528cc08c1fdddd020598a51843aa5f59dacf1667e97415d75e6276297a7684"}, - {file = "simsimd-5.9.10-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fc0aa52270606da2d9e5e37e9158a02e685f3402da639b21a803cf02d5c7f56d"}, - {file = "simsimd-5.9.10-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:f496f522f2ad1fe06db569d6002829db7c302e7dc795bb1b7c50166a5fe194d8"}, - {file = "simsimd-5.9.10-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:3a9918cd1c6119bf0fac5b3d75f1e6af982f3faa3702239e1abf8dfb9af0fe33"}, - {file = "simsimd-5.9.10-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:362297c7e48f9ddd32a252b8bdc3034f05cfda0047788178a3488be97c150faa"}, - {file = "simsimd-5.9.10-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:3dc2d5d5310d995da124f30ad33f934be6a6829cab38a58b477478c02a5fa4b8"}, - {file = "simsimd-5.9.10-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:07d6266aca8de0d1b112776ba1322cb8ea158bcbc432bf7bc78b889806502bbe"}, - {file = "simsimd-5.9.10-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:606b8c44caf34357841ae387ca21012ce824436bf3a223ba1712433ae807c824"}, - {file = "simsimd-5.9.10-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9f254433c48cf1b99cbd5e0d0cd2eb2da02312254e260fdf8e3f0e5d8ab817af"}, - {file = "simsimd-5.9.10-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:f43aa14f8e92813894a3d38da771c48500cc27ea0360858309f51f9e313a2857"}, - {file = "simsimd-5.9.10-cp39-cp39-win32.whl", hash = "sha256:a70ee09870aa86a8d8c9a51901ba22e9980c24bc7cd3c57409524f386ce624df"}, - {file = "simsimd-5.9.10-cp39-cp39-win_amd64.whl", hash = "sha256:62e8b06a7cff740c6491f2285e5de0fdf6a2fbe26e3e3fa849ee6095423805bd"}, - {file = "simsimd-5.9.10-cp39-cp39-win_arm64.whl", hash = "sha256:4893c0f396a1b18756f1011e1ab742f51bf6f6b445d0df99f80ff75ce933e0aa"}, - {file = "simsimd-5.9.10.tar.gz", hash = "sha256:b1bb95837f8ab18ee26e7e770025db4148065138aa08b3118b97b0087bf093e1"}, + {file = "simsimd-6.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:9c79486cf75eb06c5e1f623e8315f9fb73620ac63b846d5a6c843f14905de43f"}, + {file = "simsimd-6.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:104d53f2489dcbf569b8260d678e2183af605510115dc2b22ed0340aa47fe892"}, + {file = "simsimd-6.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fef886c8220d3566b9f43d441226ca267a11682dea5496bb6e007f655eee1fd1"}, + {file = "simsimd-6.2.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:522e56451481bff3468653c2818ad1240b4cb13cff0ec76bc88d8860bfc775c9"}, + {file = "simsimd-6.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a5dfb02fa141a6e039803044930753aef1df5ed05cae8b14fe348cdc160cef1e"}, + {file = "simsimd-6.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:39eb6abdd44adfddec181a713e9cfad8742d03abbc6247c4e5ca2caee38e4775"}, + {file = "simsimd-6.2.1-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:9ca68b9d2cc1c19af6afe6f01a764861fc8bb919d688a64cf0b0ac0abae7e0fa"}, + {file = "simsimd-6.2.1-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:2b56b1ca7b76c0d4515938a036e688b73a866b19e6f6eb743596144fdf498a0c"}, + {file = "simsimd-6.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:02d7b7c7afecc63ddf501460f09c1da90625bfd59b4da5fda126c1aa5c54bb95"}, + {file = "simsimd-6.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:8abc529daf0a61649ca4a237cd9e63723f3355394686898654c643bd63846cf5"}, + {file = "simsimd-6.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9ea60422d0f45d3a1899984c3fc3a14dbd248cfca8f67c24751029441464a806"}, + {file = "simsimd-6.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:98e38a0ca4805c1de2882d0641b54e249eabca4ed2980c82465822130d7f8c98"}, + {file = "simsimd-6.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:cbbc2434286493b88f3b8211e922d37b46588b34d4cc28f3262f154c8ca1141c"}, + {file = "simsimd-6.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:4f2ecd459f4917facdb287c42c5e68030b21cb98edac0fec9919a7215968e38a"}, + {file = "simsimd-6.2.1-cp310-cp310-win32.whl", hash = "sha256:4ec31c076dc839114bff5d83526ddf46551d4720cc8cd0f16516896809a4fca6"}, + {file = "simsimd-6.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:94282e040be985c993d415290371f6b22bec3eeadafe747a6d8dfbd2c317f35e"}, + {file = "simsimd-6.2.1-cp310-cp310-win_arm64.whl", hash = "sha256:0784e98ca48a0075fb0cbd7782df11eaa17ce15c60f09a65e8477864208afb8a"}, + {file = "simsimd-6.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e9614309af75be4d08a051dc61ed5cf41b5239b8303b37dc2f9c8a7223534392"}, + {file = "simsimd-6.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ea4f0f68be5f85bbcf4322bfdd1b449176cf5fdd99960c546514457635632443"}, + {file = "simsimd-6.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:12a8d60ccc8991dfbbf056c221ce4f02135f5892492894972f421a6f155015d9"}, + {file = "simsimd-6.2.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a74142ea21a6fd3ec5c64e4d4acf1ec6f4d80c0bb1a5989d68af6e84f7ac612e"}, + {file = "simsimd-6.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:298f7c793fc2a1eeedcefa1278eb2ef6f52ce0b36aaa8780885f96a39ce1a4e8"}, + {file = "simsimd-6.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4025ebad36fb3fa5cffcd48d33375d5e5decc59c1129a259b74fed097eab1ab5"}, + {file = "simsimd-6.2.1-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:f486682aa7a8918d86df411d3c11c635db4b67d514cb6bb499c0edab7fb8ec58"}, + {file = "simsimd-6.2.1-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:173e66699597a4fcf6fa50b52cced40216fdcfba15f60b761a2bd9cb1d98a444"}, + {file = "simsimd-6.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:5b5c6f79f797cc020a2ff64950162dfb6d130c51a07cdac5ad97ec836e85ce50"}, + {file = "simsimd-6.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:25812637f43feaef1a33ae00b81a4d2b0116aadae3a08267486c1e57236fc368"}, + {file = "simsimd-6.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:592a578c788a9cb7877eff41487cc7f50474e00f774de74bea8590fa95c804ae"}, + {file = "simsimd-6.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:191c020f312350ac06eee829376b11d8c1282da8fefb4381fe0625edfb678d8d"}, + {file = "simsimd-6.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e9ad2c247ed58ba9bb170a01295cb315a45c817775cc7e51ad342f70978a1057"}, + {file = "simsimd-6.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0ff603134600da12175e66b842b7a7331c827fa070d1d8b63386a40bc8d09fcd"}, + {file = "simsimd-6.2.1-cp311-cp311-win32.whl", hash = "sha256:99dff4e04663c82284152ecc2e8bf76b2825f3f17e179abf7892e06196061056"}, + {file = "simsimd-6.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:0efc6343c440a26cf16463c4c667655af9597bcbd55ad66f33a80b2b84de7412"}, + {file = "simsimd-6.2.1-cp311-cp311-win_arm64.whl", hash = "sha256:2d364f2c24dd38578bf0eec436c4b901c900ae1893680f46eb5632e01330d814"}, + {file = "simsimd-6.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:9b3315e41bb759dc038ecd6f4fa7bcf278bf72ee7d982f752482cdc732aea271"}, + {file = "simsimd-6.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:8d476c874bafa0d12d4c8c5c47faf17407f3c96140616384421c2aa980342b6f"}, + {file = "simsimd-6.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:e9d4f15c06cc221d29e181197c7bbf92c5e829220cbeb3cd1cf080de78b04f2a"}, + {file = "simsimd-6.2.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d286fd4538cb1a1c70e69da00a3acee301519d578931b41161f4f1379d1195c6"}, + {file = "simsimd-6.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:050f68cfa85f1fb2cfa156280928e42926e3977034b755023ce1315bf59e87ff"}, + {file = "simsimd-6.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:67bb4b17e04919545f29c7b708faaccbe027f164f8b5c9f4328604fa8f5560ea"}, + {file = "simsimd-6.2.1-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:3d6bffd999dbb36e606b065e0180365efac2606049c4f7818e4cba2d34c3678f"}, + {file = "simsimd-6.2.1-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:25adb244fb75dbf49af0d1bcac4ed4a3fef8e847d78449faa5595af0a3e20d61"}, + {file = "simsimd-6.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:b4542cee77e801a9c27370fc36ae271514fc0fb2ce14a35f8b25f47989e3d267"}, + {file = "simsimd-6.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:4f665228f8ff4911790b485e74b00fa9586a141dde6011970be71bb303b5a22f"}, + {file = "simsimd-6.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:783b4308f80ae00763b0eaa0dac26196958f9c2df60d35a0347ebd2f82ece46d"}, + {file = "simsimd-6.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:95055e72cfe313c1c8694783bf8a631cc15673b3b775abef367e396d931db0b8"}, + {file = "simsimd-6.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a98f2b383f51b4f4ee568a637fc7958a347fdae0bd184cff8faa8030b6454a39"}, + {file = "simsimd-6.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2e474fd10ceb38e2c9f826108a7762f8ff7912974846d86f08c4e7b19cd35ed4"}, + {file = "simsimd-6.2.1-cp312-cp312-win32.whl", hash = "sha256:b2530ea44fffeab25e5752bec6a5991f30fbc430b04647980db5b195c0971d48"}, + {file = "simsimd-6.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:dc23283235d5b8f0373b95a547e26da2d7785647a5d0fa15c282fc8c49c0dcb0"}, + {file = "simsimd-6.2.1-cp312-cp312-win_arm64.whl", hash = "sha256:5692ce7e56253178eea9dbd58191734918409b83d54b07cfdcecf868d0150a73"}, + {file = "simsimd-6.2.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:76b32fdc7142c9714e94651ece8bc00dd5139c554813211552aa358e44af0e07"}, + {file = "simsimd-6.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f44e5e2319427f94db658c6f75caae78850da505902874a1664a83ef5713f333"}, + {file = "simsimd-6.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:05323cbad7200592c2e53fbcc759e615594e8ca444ef5eddf9f3fb196ad4de9c"}, + {file = "simsimd-6.2.1-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b1f3cbe5c39db2bb64f30999104de1215ba3805d6059af7bc5a9d662d50f4707"}, + {file = "simsimd-6.2.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eaa94e0932ae2a48b7e4df8c29204dc9fe59f72b1faeb08e9d5015bf51fb9f21"}, + {file = "simsimd-6.2.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:508465f8d4e3e0fff07c939921aeedf55b0ade9f56f64e938c350c283dea42fb"}, + {file = "simsimd-6.2.1-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:ca67f6273ef544c74c48b134af756de7c98a711ccf69cd0791225f26dd449281"}, + {file = "simsimd-6.2.1-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:d470b43ce606f21f54a23fc19ad6928333e17d0956b02eb27b7b112edc156a10"}, + {file = "simsimd-6.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:59518b9834c167a1dd8900600718e95cdadc9d74525452f426aa8455a38c55ef"}, + {file = "simsimd-6.2.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:59c2978c4e402097d8a4b38f076ff98cc43e6b059d53f89736404f26e9a9bd5a"}, + {file = "simsimd-6.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:edc68e727d53ed2866dcfb625f15e52be8f1e6809f4be2147bf8d2115a2542b7"}, + {file = "simsimd-6.2.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:9e5e82551d75c0e2cd0d4b8af8db1cae7b5ac6dcc076c0c760870ff81f78135b"}, + {file = "simsimd-6.2.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:2fa19f8c9786757d19afcbda9f8fb68de55e4f5562725ae8727f887d01bf0e4d"}, + {file = "simsimd-6.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5b0748aa6bd4df4c5a3f5e979aec14b26588f1b2e0d44075dcc9eaf4d555e15b"}, + {file = "simsimd-6.2.1-cp313-cp313-win32.whl", hash = "sha256:7f43721e1a4ebe8d2245b0e85dd7de7153d1bf22839579d5f69a345909c68d9e"}, + {file = "simsimd-6.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:6af1565e0ef7060bc52a38e3273a8e6e92aff47835965dc5311298563475935e"}, + {file = "simsimd-6.2.1-cp313-cp313-win_arm64.whl", hash = "sha256:e690b41377c8dd157d585713b0bc35c845aee7742334bf12d1f087fc8a65b6c3"}, + {file = "simsimd-6.2.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:9264abf5dabe046d3951d162dbba21c7a3c3f491587c84038df1b94de0b6742a"}, + {file = "simsimd-6.2.1-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e93ffe6ea7417bffdee9a1b9ebb682f35f41e3e75b7e51f0f3a2fb5f7dd4c079"}, + {file = "simsimd-6.2.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d09ea4d3c0224bedf9f72881d1e5896a265fc89311abba078e615b0c06d989da"}, + {file = "simsimd-6.2.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dae5f7c37ffd0313ea59aa0a20203e7624bc5a39065fc5505991268689f2b6a2"}, + {file = "simsimd-6.2.1-cp37-cp37m-manylinux_2_28_aarch64.whl", hash = "sha256:2f573d706e44018cba63a6ff44f4a1a7733fb55ee504a12b345c012bc114f7d5"}, + {file = "simsimd-6.2.1-cp37-cp37m-manylinux_2_28_x86_64.whl", hash = "sha256:63a48c50c0ff44ac4d463f8c963f718de5aff54e1c4a6ce8363e291ac2f1fc14"}, + {file = "simsimd-6.2.1-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:77912f9b4c230eea2bca7ba35c33dfd5590b41a867abba9fe7e152a7ae976307"}, + {file = "simsimd-6.2.1-cp37-cp37m-musllinux_1_2_armv7l.whl", hash = "sha256:731635de9e771571fbf61edb81cfa466fed37845fbfb35d719afb7c6ea3d4bce"}, + {file = "simsimd-6.2.1-cp37-cp37m-musllinux_1_2_i686.whl", hash = "sha256:03c94c9dcf80c93c58c9435f295fd35399d88097464d1a0a5995372868d852e3"}, + {file = "simsimd-6.2.1-cp37-cp37m-musllinux_1_2_ppc64le.whl", hash = "sha256:bbcfc905d90343c7b7e07f7b80385abc017405125246908181f6841c5f3cbde3"}, + {file = "simsimd-6.2.1-cp37-cp37m-musllinux_1_2_s390x.whl", hash = "sha256:4cf0180f4b17ea3758523f644eddc38124ac98c4aac1c5572f44fd04c3bcb2f3"}, + {file = "simsimd-6.2.1-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:31163917ce2848f7896e633b8d1ae0db9004dc8eb6605cf959f6319e31cd569c"}, + {file = "simsimd-6.2.1-cp37-cp37m-win32.whl", hash = "sha256:c7af7da114f81af0bcfbf9563ea109479550e62dd5dde39ea2e93bc5f1e306ca"}, + {file = "simsimd-6.2.1-cp37-cp37m-win_amd64.whl", hash = "sha256:cad9b5503d35b7be3e704594bcdf3883bbcdb9987086d942a2a52e7b0927288e"}, + {file = "simsimd-6.2.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:5b62fcf02e33a88e4c4a93da9d682e475bb08979d7d18f91a76bee2fe2f9d335"}, + {file = "simsimd-6.2.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0d7eeed41600bb229c34d822e0011c80019c16c689f16c82b875012e7116b2d5"}, + {file = "simsimd-6.2.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:0da7f30f11cbe7c6ced372af3f5da24b7df1038bad82cfd0032667024622b794"}, + {file = "simsimd-6.2.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ae496f16f2d759dc103ed8b8a5533c0a52e5c96c88e5d6a9e26eff24f174537b"}, + {file = "simsimd-6.2.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9046d108b3fc7cd1808df53083b3a2e26f70a1efb4f378971fefe76c27d64488"}, + {file = "simsimd-6.2.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1919957071b6d19e337ebba9c04f4b48604f927fc9118ce877b1fbcec1975f57"}, + {file = "simsimd-6.2.1-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:ef6d998496e5569ce9b5ce21a9ecbe3b59f9426ce27e6bf1db0eae67613d8d9e"}, + {file = "simsimd-6.2.1-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:3cb54ec20235d81dd9596c8fe8b2bd35fad027d3f5cd52e23a17a71b3ac44d3f"}, + {file = "simsimd-6.2.1-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:598330828b922700aac8a7939c562f80e4ee9000671081ff264c8daae4692d76"}, + {file = "simsimd-6.2.1-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:1b45987216a5d5b9b1441ea8acbf5d731e5ee60c0727999f10438827d201b40d"}, + {file = "simsimd-6.2.1-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:8c9b79c189ab40e1633c4cecba1a58133a8454662c40af8abdf18f0766a1cf94"}, + {file = "simsimd-6.2.1-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:1324d7433f0cefd29a55716197112d22b259c49d7c62425517dc37d0c6494b69"}, + {file = "simsimd-6.2.1-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:c5101d1204e42b15c1e3772ec8b357cec9bce5eea0ccb76ec8faff5104233241"}, + {file = "simsimd-6.2.1-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:d8c7b7b286d7be1756fb837b9f3330f7d03eb6a7329cd717c88d635e441a8eb0"}, + {file = "simsimd-6.2.1-cp38-cp38-win32.whl", hash = "sha256:2e07e5b4abbb5561a62acfc4d1f2c4fb9051cc0f6919b0456d0bb37dc6749f0a"}, + {file = "simsimd-6.2.1-cp38-cp38-win_amd64.whl", hash = "sha256:87b963f862ba50a61527af281a66e1d6cee34c535b621718e45de1df8f277cba"}, + {file = "simsimd-6.2.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:45010111c39117af851a323e78bd43e6a344349b4ed7b1f5ca4c4ebb2284c7e5"}, + {file = "simsimd-6.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:dd6ecae57a481f9fc0bceb331cba7b18a0b23a71f15af7d06cdf8aa8aac38645"}, + {file = "simsimd-6.2.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ffbb874d4c3ed53443468f9c20704845cc8736d5717817c35d5cb12ad5548c7a"}, + {file = "simsimd-6.2.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7b6147ddc390c08a802af258ad204b1d775bb3d180ec6f6fcea82f4fd71fb447"}, + {file = "simsimd-6.2.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0048df2245d239ed016e5f4b5d75e96987149bf7245e90713e1fe3b53e321a74"}, + {file = "simsimd-6.2.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fc087d9dacab1eb4abc2f3d9f33047fc601db501cb43165e658973fe5fd50c9b"}, + {file = "simsimd-6.2.1-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:d1d2e6c3d655a34b42c6e0d0c28ac7b86498858ffb68c58733893fc538bd26a9"}, + {file = "simsimd-6.2.1-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:d063beb7a53d8525af56c4247e1e43a7fa161b70bcbacf30daab639b32ad4a10"}, + {file = "simsimd-6.2.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:4a517ae74d18a8b7d4d349cf4afed45f33cd660cb44d0ae34c95d00c1f7fa760"}, + {file = "simsimd-6.2.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:a79a2bd32ba0f90f70c22accf4b441846049b55aeae73556f4b5c6e9fe6e024f"}, + {file = "simsimd-6.2.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:4c9487acdae92b4089a0142cd3691328bfdcaaebf2587a0c11df4039ff7005e8"}, + {file = "simsimd-6.2.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:1c4760dee8f65a890b82a6175d5294d30271637495a9e4195969fc1ad38ec056"}, + {file = "simsimd-6.2.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:abee753fbb8584373218bf78396ae3d2b2a1202c7284cd9c70695535c62cdc31"}, + {file = "simsimd-6.2.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:300042eeab379923d77bca328fdc2ac1df8adfdffa9a6939f28ba6b196f02002"}, + {file = "simsimd-6.2.1-cp39-cp39-win32.whl", hash = "sha256:2eed0ad770b18a3b74b19ad744ee3224dae9bf1a86bd9126eae0636ada53eebd"}, + {file = "simsimd-6.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:e99cc8aa19af5ca3574aa72e1d0e959c4859345fdf553a887ce22e469c1145a8"}, + {file = "simsimd-6.2.1-cp39-cp39-win_arm64.whl", hash = "sha256:37b0db92ca0fec835ec1256d6dd167d7c9f727d3372b98bf27b1fd59ad299768"}, + {file = "simsimd-6.2.1.tar.gz", hash = "sha256:5e202c5386a4141946b7aee05faac8ebc2e36bca0a360b24080e57b59bc4ef6a"}, ] [[package]] @@ -1918,13 +1960,13 @@ dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"] [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -1947,111 +1989,26 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tokenizers" -version = "0.20.1" +version = "0.21.0" description = "" optional = true python-versions = ">=3.7" files = [ - {file = "tokenizers-0.20.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:439261da7c0a5c88bda97acb284d49fbdaf67e9d3b623c0bfd107512d22787a9"}, - {file = "tokenizers-0.20.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:03dae629d99068b1ea5416d50de0fea13008f04129cc79af77a2a6392792d93c"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b61f561f329ffe4b28367798b89d60c4abf3f815d37413b6352bc6412a359867"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ec870fce1ee5248a10be69f7a8408a234d6f2109f8ea827b4f7ecdbf08c9fd15"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d388d1ea8b7447da784e32e3b86a75cce55887e3b22b31c19d0b186b1c677800"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:299c85c1d21135bc01542237979bf25c32efa0d66595dd0069ae259b97fb2dbe"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e96f6c14c9752bb82145636b614d5a78e9cde95edfbe0a85dad0dd5ddd6ec95c"}, - {file = "tokenizers-0.20.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc9e95ad49c932b80abfbfeaf63b155761e695ad9f8a58c52a47d962d76e310f"}, - {file = "tokenizers-0.20.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:f22dee205329a636148c325921c73cf3e412e87d31f4d9c3153b302a0200057b"}, - {file = "tokenizers-0.20.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a2ffd9a8895575ac636d44500c66dffaef133823b6b25067604fa73bbc5ec09d"}, - {file = "tokenizers-0.20.1-cp310-none-win32.whl", hash = "sha256:2847843c53f445e0f19ea842a4e48b89dd0db4e62ba6e1e47a2749d6ec11f50d"}, - {file = "tokenizers-0.20.1-cp310-none-win_amd64.whl", hash = "sha256:f9aa93eacd865f2798b9e62f7ce4533cfff4f5fbd50c02926a78e81c74e432cd"}, - {file = "tokenizers-0.20.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4a717dcb08f2dabbf27ae4b6b20cbbb2ad7ed78ce05a829fae100ff4b3c7ff15"}, - {file = "tokenizers-0.20.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3f84dad1ff1863c648d80628b1b55353d16303431283e4efbb6ab1af56a75832"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:929c8f3afa16a5130a81ab5079c589226273ec618949cce79b46d96e59a84f61"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d10766473954397e2d370f215ebed1cc46dcf6fd3906a2a116aa1d6219bfedc3"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9300fac73ddc7e4b0330acbdda4efaabf74929a4a61e119a32a181f534a11b47"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0ecaf7b0e39caeb1aa6dd6e0975c405716c82c1312b55ac4f716ef563a906969"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5170be9ec942f3d1d317817ced8d749b3e1202670865e4fd465e35d8c259de83"}, - {file = "tokenizers-0.20.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ef3f1ae08fa9aea5891cbd69df29913e11d3841798e0bfb1ff78b78e4e7ea0a4"}, - {file = "tokenizers-0.20.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:ee86d4095d3542d73579e953c2e5e07d9321af2ffea6ecc097d16d538a2dea16"}, - {file = "tokenizers-0.20.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:86dcd08da163912e17b27bbaba5efdc71b4fbffb841530fdb74c5707f3c49216"}, - {file = "tokenizers-0.20.1-cp311-none-win32.whl", hash = "sha256:9af2dc4ee97d037bc6b05fa4429ddc87532c706316c5e11ce2f0596dfcfa77af"}, - {file = "tokenizers-0.20.1-cp311-none-win_amd64.whl", hash = "sha256:899152a78b095559c287b4c6d0099469573bb2055347bb8154db106651296f39"}, - {file = "tokenizers-0.20.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:407ab666b38e02228fa785e81f7cf79ef929f104bcccf68a64525a54a93ceac9"}, - {file = "tokenizers-0.20.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2f13a2d16032ebc8bd812eb8099b035ac65887d8f0c207261472803b9633cf3e"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e98eee4dca22849fbb56a80acaa899eec5b72055d79637dd6aa15d5e4b8628c9"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:47c1bcdd61e61136087459cb9e0b069ff23b5568b008265e5cbc927eae3387ce"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:128c1110e950534426e2274837fc06b118ab5f2fa61c3436e60e0aada0ccfd67"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e2e2d47a819d2954f2c1cd0ad51bb58ffac6f53a872d5d82d65d79bf76b9896d"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bdd67a0e3503a9a7cf8bc5a4a49cdde5fa5bada09a51e4c7e1c73900297539bd"}, - {file = "tokenizers-0.20.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:689b93d2e26d04da337ac407acec8b5d081d8d135e3e5066a88edd5bdb5aff89"}, - {file = "tokenizers-0.20.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:0c6a796ddcd9a19ad13cf146997cd5895a421fe6aec8fd970d69f9117bddb45c"}, - {file = "tokenizers-0.20.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:3ea919687aa7001a8ff1ba36ac64f165c4e89035f57998fa6cedcfd877be619d"}, - {file = "tokenizers-0.20.1-cp312-none-win32.whl", hash = "sha256:6d3ac5c1f48358ffe20086bf065e843c0d0a9fce0d7f0f45d5f2f9fba3609ca5"}, - {file = "tokenizers-0.20.1-cp312-none-win_amd64.whl", hash = "sha256:b0874481aea54a178f2bccc45aa2d0c99cd3f79143a0948af6a9a21dcc49173b"}, - {file = "tokenizers-0.20.1-cp37-cp37m-macosx_10_12_x86_64.whl", hash = "sha256:96af92e833bd44760fb17f23f402e07a66339c1dcbe17d79a9b55bb0cc4f038e"}, - {file = "tokenizers-0.20.1-cp37-cp37m-macosx_11_0_arm64.whl", hash = "sha256:65f34e5b731a262dfa562820818533c38ce32a45864437f3d9c82f26c139ca7f"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:17f98fccb5c12ab1ce1f471731a9cd86df5d4bd2cf2880c5a66b229802d96145"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b8c0fc3542cf9370bf92c932eb71bdeb33d2d4aeeb4126d9fd567b60bd04cb30"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4b39356df4575d37f9b187bb623aab5abb7b62c8cb702867a1768002f814800c"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bfdad27b0e50544f6b838895a373db6114b85112ba5c0cefadffa78d6daae563"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:094663dd0e85ee2e573126918747bdb40044a848fde388efb5b09d57bc74c680"}, - {file = "tokenizers-0.20.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:14e4cf033a2aa207d7ac790e91adca598b679999710a632c4a494aab0fc3a1b2"}, - {file = "tokenizers-0.20.1-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:9310951c92c9fb91660de0c19a923c432f110dbfad1a2d429fbc44fa956bf64f"}, - {file = "tokenizers-0.20.1-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:05e41e302c315bd2ed86c02e917bf03a6cf7d2f652c9cee1a0eb0d0f1ca0d32c"}, - {file = "tokenizers-0.20.1-cp37-none-win32.whl", hash = "sha256:212231ab7dfcdc879baf4892ca87c726259fa7c887e1688e3f3cead384d8c305"}, - {file = "tokenizers-0.20.1-cp37-none-win_amd64.whl", hash = "sha256:896195eb9dfdc85c8c052e29947169c1fcbe75a254c4b5792cdbd451587bce85"}, - {file = "tokenizers-0.20.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:741fb22788482d09d68e73ece1495cfc6d9b29a06c37b3df90564a9cfa688e6d"}, - {file = "tokenizers-0.20.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:10be14ebd8082086a342d969e17fc2d6edc856c59dbdbddd25f158fa40eaf043"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:514cf279b22fa1ae0bc08e143458c74ad3b56cd078b319464959685a35c53d5e"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a647c5b7cb896d6430cf3e01b4e9a2d77f719c84cefcef825d404830c2071da2"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7cdf379219e1e1dd432091058dab325a2e6235ebb23e0aec8d0508567c90cd01"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ba72260449e16c4c2f6f3252823b059fbf2d31b32617e582003f2b18b415c39"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:910b96ed87316e4277b23c7bcaf667ce849c7cc379a453fa179e7e09290eeb25"}, - {file = "tokenizers-0.20.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e53975a6694428a0586534cc1354b2408d4e010a3103117f617cbb550299797c"}, - {file = "tokenizers-0.20.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:07c4b7be58da142b0730cc4e5fd66bb7bf6f57f4986ddda73833cd39efef8a01"}, - {file = "tokenizers-0.20.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b605c540753e62199bf15cf69c333e934077ef2350262af2ccada46026f83d1c"}, - {file = "tokenizers-0.20.1-cp38-none-win32.whl", hash = "sha256:88b3bc76ab4db1ab95ead623d49c95205411e26302cf9f74203e762ac7e85685"}, - {file = "tokenizers-0.20.1-cp38-none-win_amd64.whl", hash = "sha256:d412a74cf5b3f68a90c615611a5aa4478bb303d1c65961d22db45001df68afcb"}, - {file = "tokenizers-0.20.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:a25dcb2f41a0a6aac31999e6c96a75e9152fa0127af8ece46c2f784f23b8197a"}, - {file = "tokenizers-0.20.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a12c3cebb8c92e9c35a23ab10d3852aee522f385c28d0b4fe48c0b7527d59762"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:02e18da58cf115b7c40de973609c35bde95856012ba42a41ee919c77935af251"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f326a1ac51ae909b9760e34671c26cd0dfe15662f447302a9d5bb2d872bab8ab"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0b4872647ea6f25224e2833b044b0b19084e39400e8ead3cfe751238b0802140"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ce6238a3311bb8e4c15b12600927d35c267b92a52c881ef5717a900ca14793f7"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:57b7a8880b208866508b06ce365dc631e7a2472a3faa24daa430d046fb56c885"}, - {file = "tokenizers-0.20.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a908c69c2897a68f412aa05ba38bfa87a02980df70f5a72fa8490479308b1f2d"}, - {file = "tokenizers-0.20.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:da1001aa46f4490099c82e2facc4fbc06a6a32bf7de3918ba798010954b775e0"}, - {file = "tokenizers-0.20.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:42c097390e2f0ed0a5c5d569e6669dd4e9fff7b31c6a5ce6e9c66a61687197de"}, - {file = "tokenizers-0.20.1-cp39-none-win32.whl", hash = "sha256:3d4d218573a3d8b121a1f8c801029d70444ffb6d8f129d4cca1c7b672ee4a24c"}, - {file = "tokenizers-0.20.1-cp39-none-win_amd64.whl", hash = "sha256:37d1e6f616c84fceefa7c6484a01df05caf1e207669121c66213cb5b2911d653"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:48689da7a395df41114f516208d6550e3e905e1239cc5ad386686d9358e9cef0"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:712f90ea33f9bd2586b4a90d697c26d56d0a22fd3c91104c5858c4b5b6489a79"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:359eceb6a620c965988fc559cebc0a98db26713758ec4df43fb76d41486a8ed5"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d3caf244ce89d24c87545aafc3448be15870096e796c703a0d68547187192e1"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03b03cf8b9a32254b1bf8a305fb95c6daf1baae0c1f93b27f2b08c9759f41dee"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:218e5a3561561ea0f0ef1559c6d95b825308dbec23fb55b70b92589e7ff2e1e8"}, - {file = "tokenizers-0.20.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f40df5e0294a95131cc5f0e0eb91fe86d88837abfbee46b9b3610b09860195a7"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-macosx_10_12_x86_64.whl", hash = "sha256:08aaa0d72bb65058e8c4b0455f61b840b156c557e2aca57627056624c3a93976"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:998700177b45f70afeb206ad22c08d9e5f3a80639dae1032bf41e8cbc4dada4b"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:62f7fbd3c2c38b179556d879edae442b45f68312019c3a6013e56c3947a4e648"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:31e87fca4f6bbf5cc67481b562147fe932f73d5602734de7dd18a8f2eee9c6dd"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:956f21d359ae29dd51ca5726d2c9a44ffafa041c623f5aa33749da87cfa809b9"}, - {file = "tokenizers-0.20.1-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:1fbbaf17a393c78d8aedb6a334097c91cb4119a9ced4764ab8cfdc8d254dc9f9"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-macosx_10_12_x86_64.whl", hash = "sha256:ebe63e31f9c1a970c53866d814e35ec2ec26fda03097c486f82f3891cee60830"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-macosx_11_0_arm64.whl", hash = "sha256:81970b80b8ac126910295f8aab2d7ef962009ea39e0d86d304769493f69aaa1e"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:130e35e76f9337ed6c31be386e75d4925ea807055acf18ca1a9b0eec03d8fe23"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:cd28a8614f5c82a54ab2463554e84ad79526c5184cf4573bbac2efbbbcead457"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9041ee665d0fa7f5c4ccf0f81f5e6b7087f797f85b143c094126fc2611fec9d0"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:62eb9daea2a2c06bcd8113a5824af8ef8ee7405d3a71123ba4d52c79bb3d9f1a"}, - {file = "tokenizers-0.20.1-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f861889707b54a9ab1204030b65fd6c22bdd4a95205deec7994dc22a8baa2ea4"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:89d5c337d74ea6e5e7dc8af124cf177be843bbb9ca6e58c01f75ea103c12c8a9"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:0b7f515c83397e73292accdbbbedc62264e070bae9682f06061e2ddce67cacaf"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3e0305fc1ec6b1e5052d30d9c1d5c807081a7bd0cae46a33d03117082e91908c"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5dc611e6ac0fa00a41de19c3bf6391a05ea201d2d22b757d63f5491ec0e67faa"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c5ffe0d7f7bfcfa3b2585776ecf11da2e01c317027c8573c78ebcb8985279e23"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:e7edb8ec12c100d5458d15b1e47c0eb30ad606a05641f19af7563bc3d1608c14"}, - {file = "tokenizers-0.20.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:de291633fb9303555793cc544d4a86e858da529b7d0b752bcaf721ae1d74b2c9"}, - {file = "tokenizers-0.20.1.tar.gz", hash = "sha256:84edcc7cdeeee45ceedb65d518fffb77aec69311c9c8e30f77ad84da3025f002"}, + {file = "tokenizers-0.21.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:3c4c93eae637e7d2aaae3d376f06085164e1660f89304c0ab2b1d08a406636b2"}, + {file = "tokenizers-0.21.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:f53ea537c925422a2e0e92a24cce96f6bc5046bbef24a1652a5edc8ba975f62e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b177fb54c4702ef611de0c069d9169f0004233890e0c4c5bd5508ae05abf193"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6b43779a269f4629bebb114e19c3fca0223296ae9fea8bb9a7a6c6fb0657ff8e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9aeb255802be90acfd363626753fda0064a8df06031012fe7d52fd9a905eb00e"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d8b09dbeb7a8d73ee204a70f94fc06ea0f17dcf0844f16102b9f414f0b7463ba"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:400832c0904f77ce87c40f1a8a27493071282f785724ae62144324f171377273"}, + {file = "tokenizers-0.21.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e84ca973b3a96894d1707e189c14a774b701596d579ffc7e69debfc036a61a04"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:eb7202d231b273c34ec67767378cd04c767e967fda12d4a9e36208a34e2f137e"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:089d56db6782a73a27fd8abf3ba21779f5b85d4a9f35e3b493c7bbcbbf0d539b"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:c87ca3dc48b9b1222d984b6b7490355a6fdb411a2d810f6f05977258400ddb74"}, + {file = "tokenizers-0.21.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:4145505a973116f91bc3ac45988a92e618a6f83eb458f49ea0790df94ee243ff"}, + {file = "tokenizers-0.21.0-cp39-abi3-win32.whl", hash = "sha256:eb1702c2f27d25d9dd5b389cc1f2f51813e99f8ca30d9e25348db6585a97e24a"}, + {file = "tokenizers-0.21.0-cp39-abi3-win_amd64.whl", hash = "sha256:87841da5a25a3a5f70c102de371db120f41873b854ba65e52bccd57df5a3780c"}, + {file = "tokenizers-0.21.0.tar.gz", hash = "sha256:ee0894bf311b75b0c03079f33859ae4b2334d675d4e93f5a4132e1eae2834fe4"}, ] [package.dependencies] @@ -2064,31 +2021,32 @@ testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"] [[package]] name = "tomli" -version = "2.0.2" +version = "2.1.0" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"}, - {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"}, + {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, + {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, ] [[package]] name = "tqdm" -version = "4.66.6" +version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = true python-versions = ">=3.7" files = [ - {file = "tqdm-4.66.6-py3-none-any.whl", hash = "sha256:223e8b5359c2efc4b30555531f09e9f2f3589bcd7fdd389271191031b49b7a63"}, - {file = "tqdm-4.66.6.tar.gz", hash = "sha256:4bdd694238bef1485ce839d67967ab50af8f9272aab687c0d7702a01da0be090"}, + {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, + {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, ] [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} [package.extras] -dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"] +dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"] +discord = ["requests"] notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] telegram = ["requests"] @@ -2183,4 +2141,4 @@ fastembed = ["fastembed"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4" -content-hash = "9f07b1ef4a49c5ab9ca9d1b736cc94e9c3ff1ef0144ad478b5ff5147bcef19ff" +content-hash = "2a325d2b9028b0f32aa3cc7a15c22fe32568452e8c91cfc5b68642faed09a013" diff --git a/libs/partners/qdrant/pyproject.toml b/libs/partners/qdrant/pyproject.toml index a19b3d8523dfc..13e9dc8236bd0 100644 --- a/libs/partners/qdrant/pyproject.toml +++ b/libs/partners/qdrant/pyproject.toml @@ -96,7 +96,7 @@ ruff = "^0.5" [tool.poetry.group.typing.dependencies] mypy = "^1.10" -simsimd = "^5.0.0" +simsimd = "^6.0.0" [[tool.poetry.group.typing.dependencies.langchain-core]] path = "../../core" develop = true diff --git a/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py b/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py index 1152fe44946f7..edcaf93eebf02 100644 --- a/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py +++ b/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py @@ -5,6 +5,7 @@ import pytest # type: ignore[import-not-found] from langchain_core.language_models import BaseChatModel from langchain_core.rate_limiters import InMemoryRateLimiter +from langchain_core.tools import BaseTool from langchain_tests.integration_tests import ( # type: ignore[import-not-found] ChatModelIntegrationTests, # type: ignore[import-not-found] ) @@ -40,13 +41,19 @@ def test_usage_metadata_streaming(self, model: BaseChatModel) -> None: super().test_usage_metadata_streaming(model) @pytest.mark.xfail(reason="Can't handle AIMessage with empty content.") - def test_tool_message_error_status(self, model: BaseChatModel) -> None: - super().test_tool_message_error_status(model) + def test_tool_message_error_status( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_error_status(model, my_adder_tool) @pytest.mark.xfail(reason="Can't handle AIMessage with empty content.") - def test_structured_few_shot_examples(self, model: BaseChatModel) -> None: - super().test_structured_few_shot_examples(model) + def test_structured_few_shot_examples( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_structured_few_shot_examples(model, my_adder_tool) @pytest.mark.xfail(reason="Can't handle AIMessage with empty content.") - def test_tool_message_histories_string_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_string_content(model) + def test_tool_message_histories_string_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_string_content(model, my_adder_tool) diff --git a/libs/standard-tests/langchain_tests/__init__.py b/libs/standard-tests/langchain_tests/__init__.py index e69de29bb2d1d..0f41b67980ccc 100644 --- a/libs/standard-tests/langchain_tests/__init__.py +++ b/libs/standard-tests/langchain_tests/__init__.py @@ -0,0 +1,7 @@ +""" +Base Test classes for standard testing. + +To learn how to use these classes, see the +`Integration standard testing `_ +guide. +""" diff --git a/libs/standard-tests/langchain_tests/base.py b/libs/standard-tests/langchain_tests/base.py index f2b7ca1f7e92d..df99a39b71d62 100644 --- a/libs/standard-tests/langchain_tests/base.py +++ b/libs/standard-tests/langchain_tests/base.py @@ -3,9 +3,15 @@ class BaseStandardTests(ABC): + """ + :private: + """ + def test_no_overrides_DO_NOT_OVERRIDE(self) -> None: """ Test that no standard tests are overridden. + + :private: """ # find path to standard test implementations comparison_class = None diff --git a/libs/standard-tests/langchain_tests/integration_tests/__init__.py b/libs/standard-tests/langchain_tests/integration_tests/__init__.py index 67ccb38f29e94..b6f0a1b0f2a23 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/__init__.py +++ b/libs/standard-tests/langchain_tests/integration_tests/__init__.py @@ -11,6 +11,7 @@ "vectorstores", "embeddings", "tools", + "retrievers", ] for module in modules: @@ -20,8 +21,9 @@ from .cache import AsyncCacheTestSuite, SyncCacheTestSuite from .chat_models import ChatModelIntegrationTests from .embeddings import EmbeddingsIntegrationTests +from .retrievers import RetrieversIntegrationTests from .tools import ToolsIntegrationTests -from .vectorstores import AsyncReadWriteTestSuite, ReadWriteTestSuite +from .vectorstores import VectorStoreIntegrationTests __all__ = [ "ChatModelIntegrationTests", @@ -31,6 +33,6 @@ "BaseStoreSyncTests", "AsyncCacheTestSuite", "SyncCacheTestSuite", - "AsyncReadWriteTestSuite", - "ReadWriteTestSuite", + "VectorStoreIntegrationTests", + "RetrieversIntegrationTests", ] diff --git a/libs/standard-tests/langchain_tests/integration_tests/base_store.py b/libs/standard-tests/langchain_tests/integration_tests/base_store.py index cc5fab8bcf7a4..ff9e178aea903 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/base_store.py +++ b/libs/standard-tests/langchain_tests/integration_tests/base_store.py @@ -1,3 +1,11 @@ +""" +Standard tests for the BaseStore abstraction + +We don't recommend implementing externally managed BaseStore abstractions at this time. + +:private: +""" + from abc import abstractmethod from typing import AsyncGenerator, Generator, Generic, Tuple, TypeVar diff --git a/libs/standard-tests/langchain_tests/integration_tests/cache.py b/libs/standard-tests/langchain_tests/integration_tests/cache.py index 7087da8ea07b3..3d04731d16a74 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/cache.py +++ b/libs/standard-tests/langchain_tests/integration_tests/cache.py @@ -1,3 +1,11 @@ +""" +Standard tests for the BaseCache abstraction + +We don't recommend implementing externally managed BaseCache abstractions at this time. + +:private: +""" + from abc import abstractmethod import pytest diff --git a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py index 61f45e63b9bee..7a787563b267b 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py @@ -16,23 +16,37 @@ ) from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import ChatPromptTemplate -from langchain_core.tools import tool +from langchain_core.tools import BaseTool, tool +from langchain_core.utils.function_calling import tool_example_to_messages from pydantic import BaseModel, Field from pydantic.v1 import BaseModel as BaseModelV1 from pydantic.v1 import Field as FieldV1 from langchain_tests.unit_tests.chat_models import ( ChatModelTests, - my_adder_tool, ) from langchain_tests.utils.pydantic import PYDANTIC_MAJOR_VERSION -class MagicFunctionSchema(BaseModel): +def _get_joke_class() -> type[BaseModel]: + """ + :private: + """ + + class Joke(BaseModel): + """Joke to tell user.""" + + setup: str = Field(description="question to set up a joke") + punchline: str = Field(description="answer to resolve the joke") + + return Joke + + +class _MagicFunctionSchema(BaseModel): input: int = Field(..., gt=-1000, lt=1000) -@tool(args_schema=MagicFunctionSchema) +@tool(args_schema=_MagicFunctionSchema) def magic_function(input: int) -> int: """Applies a magic function to an input.""" return input + 2 @@ -44,13 +58,6 @@ def magic_function_no_args() -> int: return 5 -class Joke(BaseModel): - """Joke to tell user.""" - - setup: str = Field(description="question to set up a joke") - punchline: str = Field(description="answer to resolve the joke") - - def _validate_tool_call_message(message: BaseMessage) -> None: assert isinstance(message, AIMessage) assert len(message.tool_calls) == 1 @@ -72,8 +79,244 @@ def _validate_tool_call_message_no_args(message: BaseMessage) -> None: class ChatModelIntegrationTests(ChatModelTests): + """Base class for chat model integration tests. + + Test subclasses must implement the ``chat_model_class`` and + ``chat_model_params`` properties to specify what model to test and its + initialization parameters. + + Example: + + .. code-block:: python + + from typing import Type + + from langchain_tests.integration_tests import ChatModelIntegrationTests + from my_package.chat_models import MyChatModel + + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def chat_model_class(self) -> Type[MyChatModel]: + # Return the chat model class to test here + return MyChatModel + + @property + def chat_model_params(self) -> dict: + # Return initialization parameters for the model. + return {"model": "model-001", "temperature": 0} + + .. note:: + API references for individual test methods include troubleshooting tips. + + + Test subclasses must implement the following two properties: + + chat_model_class + The chat model class to test, e.g., ``ChatParrotLink``. + + Example: + + .. code-block:: python + + @property + def chat_model_class(self) -> Type[ChatParrotLink]: + return ChatParrotLink + + chat_model_params + Initialization parameters for the chat model. + + Example: + + .. code-block:: python + + @property + def chat_model_params(self) -> dict: + return {"model": "bird-brain-001", "temperature": 0} + + In addition, test subclasses can control what features are tested (such as tool + calling or multi-modality) by selectively overriding the following properties. + Expand to see details: + + .. dropdown:: has_tool_calling + + Boolean property indicating whether the chat model supports tool calling. + + By default, this is determined by whether the chat model's `bind_tools` method + is overridden. It typically does not need to be overridden on the test class. + + Example override: + + .. code-block:: python + + @property + def has_tool_calling(self) -> bool: + return True + + .. dropdown:: tool_choice_value + + Value to use for tool choice when used in tests. + + Some tests for tool calling features attempt to force tool calling via a + `tool_choice` parameter. A common value for this parameter is "any". Defaults + to `None`. + + Note: if the value is set to "tool_name", the name of the tool used in each + test will be set as the value for `tool_choice`. + + Example: + + .. code-block:: python + + @property + def tool_choice_value(self) -> Optional[str]: + return "any" + + .. dropdown:: has_structured_output + + Boolean property indicating whether the chat model supports structured + output. + + By default, this is determined by whether the chat model's + `with_structured_output` method is overridden. If the base implementation is + intended to be used, this method should be overridden. + + See: https://python.langchain.com/docs/concepts/structured_outputs/ + + Example: + + .. code-block:: python + + @property + def has_structured_output(self) -> bool: + return True + + .. dropdown:: supports_image_inputs + + Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``. + + If set to ``True``, the chat model will be tested using content blocks of the + form + + .. code-block:: python + + [ + {"type": "text", "text": "describe the weather in this image"}, + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ] + + See https://python.langchain.com/docs/concepts/multimodality/ + + Example: + + .. code-block:: python + + @property + def supports_image_inputs(self) -> bool: + return True + + .. dropdown:: supports_video_inputs + + Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``. No current tests are written for this feature. + + .. dropdown:: returns_usage_metadata + + Boolean property indicating whether the chat model returns usage metadata + on invoke and streaming responses. + + ``usage_metadata`` is an optional dict attribute on AIMessages that track input + and output tokens: https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.UsageMetadata.html + + Example: + + .. code-block:: python + + @property + def returns_usage_metadata(self) -> bool: + return False + + .. dropdown:: supports_anthropic_inputs + + Boolean property indicating whether the chat model supports Anthropic-style + inputs. + + These inputs might feature "tool use" and "tool result" content blocks, e.g., + + .. code-block:: python + + [ + {"type": "text", "text": "Hmm let me think about that"}, + { + "type": "tool_use", + "input": {"fav_color": "green"}, + "id": "foo", + "name": "color_picker", + }, + ] + + If set to ``True``, the chat model will be tested using content blocks of this + form. + + Example: + + .. code-block:: python + + @property + def supports_anthropic_inputs(self) -> bool: + return False + + .. dropdown:: supports_image_tool_message + + Boolean property indicating whether the chat model supports ToolMessages + that include image content, e.g., + + .. code-block:: python + + ToolMessage( + content=[ + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ], + tool_call_id="1", + name="random_image", + ) + + If set to ``True``, the chat model will be tested with message sequences that + include ToolMessages of this form. + + Example: + + .. code-block:: python + + @property + def supports_image_tool_message(self) -> bool: + return False + + .. dropdown:: supported_usage_metadata_details + + Property controlling what usage metadata details are emitted in both invoke + and stream. + + ``usage_metadata`` is an optional dict attribute on AIMessages that track input + and output tokens: https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.UsageMetadata.html + + It includes optional keys ``input_token_details`` and ``output_token_details`` + that can track usage details associated with special types of tokens, such as + cached, audio, or reasoning. + + Only needs to be overridden if these details are supplied. + """ + @property def standard_chat_model_params(self) -> dict: + """:private:""" return {} def test_invoke(self, model: BaseChatModel) -> None: @@ -294,8 +537,8 @@ def test_usage_metadata(self, model: BaseChatModel) -> None: .. dropdown:: Configuration By default, this test is run. - To disable this feature, set `returns_usage_metadata` to False in your test - class: + To disable this feature, set `returns_usage_metadata` to False in your + test class: .. code-block:: python @@ -434,8 +677,8 @@ def test_usage_metadata_streaming(self, model: BaseChatModel) -> None: .. dropdown:: Configuration By default, this test is run. - To disable this feature, set `returns_usage_metadata` to False in your test - class: + To disable this feature, set `returns_usage_metadata` to False in your + test class: .. code-block:: python @@ -563,6 +806,28 @@ def supported_usage_metadata_details(self) -> dict: ) def test_stop_sequence(self, model: BaseChatModel) -> None: + """Test that model does not fail when invoked with the ``stop`` parameter, + which is a standard parameter for stopping generation at a certain token. + + More on standard parameters here: https://python.langchain.com/docs/concepts/chat_models/#standard-parameters + + This should pass for all integrations. + + .. dropdown:: Troubleshooting + + If this test fails, check that the function signature for ``_generate`` + (as well as ``_stream`` and async variants) accepts the ``stop`` parameter: + + .. code-block:: python + + def _generate( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[CallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> ChatResult: + """ # noqa: E501 result = model.invoke("hi", stop=["you"]) assert isinstance(result, AIMessage) @@ -573,6 +838,44 @@ def test_stop_sequence(self, model: BaseChatModel) -> None: assert isinstance(result, AIMessage) def test_tool_calling(self, model: BaseChatModel) -> None: + """Test that the model generates tool calls. This test is skipped if the + ``has_tool_calling`` property on the test class is set to False. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that ``bind_tools`` is implemented to correctly + translate LangChain tool objects into the appropriate schema for your + chat model. + + This test may fail if the chat model does not support a ``tool_choice`` + parameter. This parameter can be used to force a tool call. If + ``tool_choice`` is not supported and the model consistently fails this + test, you can ``xfail`` the test: + + .. code-block:: python + + @pytest.mark.xfail(reason=("Does not support tool_choice.")) + def test_tool_calling(self, model: BaseChatModel) -> None: + super().test_tool_calling(model) + + Otherwise, ensure that the ``tool_choice_value`` property is correctly + specified on the test class. + """ if not self.has_tool_calling: pytest.skip("Test requires tool calling.") if self.tool_choice_value == "tool_name": @@ -594,6 +897,44 @@ def test_tool_calling(self, model: BaseChatModel) -> None: _validate_tool_call_message(full) async def test_tool_calling_async(self, model: BaseChatModel) -> None: + """Test that the model generates tool calls. This test is skipped if the + ``has_tool_calling`` property on the test class is set to False. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that ``bind_tools`` is implemented to correctly + translate LangChain tool objects into the appropriate schema for your + chat model. + + This test may fail if the chat model does not support a ``tool_choice`` + parameter. This parameter can be used to force a tool call. If + ``tool_choice`` is not supported and the model consistently fails this + test, you can ``xfail`` the test: + + .. code-block:: python + + @pytest.mark.xfail(reason=("Does not support tool_choice.")) + async def test_tool_calling_async(self, model: BaseChatModel) -> None: + await super().test_tool_calling_async(model) + + Otherwise, ensure that the ``tool_choice_value`` property is correctly + specified on the test class. + """ if not self.has_tool_calling: pytest.skip("Test requires tool calling.") if self.tool_choice_value == "tool_name": @@ -615,6 +956,46 @@ async def test_tool_calling_async(self, model: BaseChatModel) -> None: _validate_tool_call_message(full) def test_tool_calling_with_no_arguments(self, model: BaseChatModel) -> None: + """Test that the model generates tool calls for tools with no arguments. + This test is skipped if the ``has_tool_calling`` property on the test class + is set to False. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that ``bind_tools`` is implemented to correctly + translate LangChain tool objects into the appropriate schema for your + chat model. It should correctly handle the case where a tool has no + arguments. + + This test may fail if the chat model does not support a ``tool_choice`` + parameter. This parameter can be used to force a tool call. It may also + fail if a provider does not support this form of tool. In these cases, + you can ``xfail`` the test: + + .. code-block:: python + + @pytest.mark.xfail(reason=("Does not support tool_choice.")) + def test_tool_calling_with_no_arguments(self, model: BaseChatModel) -> None: + super().test_tool_calling_with_no_arguments(model) + + Otherwise, ensure that the ``tool_choice_value`` property is correctly + specified on the test class. + """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") @@ -636,6 +1017,45 @@ def test_tool_calling_with_no_arguments(self, model: BaseChatModel) -> None: _validate_tool_call_message_no_args(full) def test_bind_runnables_as_tools(self, model: BaseChatModel) -> None: + """Test that the model generates tool calls for tools that are derived from + LangChain runnables. This test is skipped if the ``has_tool_calling`` property + on the test class is set to False. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that ``bind_tools`` is implemented to correctly + translate LangChain tool objects into the appropriate schema for your + chat model. + + This test may fail if the chat model does not support a ``tool_choice`` + parameter. This parameter can be used to force a tool call. If + ``tool_choice`` is not supported and the model consistently fails this + test, you can ``xfail`` the test: + + .. code-block:: python + + @pytest.mark.xfail(reason=("Does not support tool_choice.")) + def test_bind_runnables_as_tools(self, model: BaseChatModel) -> None: + super().test_bind_runnables_as_tools(model) + + Otherwise, ensure that the ``tool_choice_value`` property is correctly + specified on the test class. + """ if not self.has_tool_calling: pytest.skip("Test requires tool calling.") @@ -662,10 +1082,36 @@ def test_bind_runnables_as_tools(self, model: BaseChatModel) -> None: assert tool_call["type"] == "tool_call" def test_structured_output(self, model: BaseChatModel) -> None: - """Test to verify structured output with a Pydantic model.""" + """Test to verify structured output is generated both on invoke and stream. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, ensure that the model's ``bind_tools`` method + properly handles both JSON Schema and Pydantic V2 models. + ``langchain_core`` implements a utility function that will accommodate + most formats: https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.convert_to_openai_tool.html + + See example implementation of ``with_structured_output`` here: https://python.langchain.com/api_reference/_modules/langchain_openai/chat_models/base.html#BaseChatOpenAI.with_structured_output + """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") + Joke = _get_joke_class() # Pydantic class # Type ignoring since the interface only officially supports pydantic 1 # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2. @@ -689,10 +1135,37 @@ def test_structured_output(self, model: BaseChatModel) -> None: assert set(chunk.keys()) == {"setup", "punchline"} async def test_structured_output_async(self, model: BaseChatModel) -> None: - """Test to verify structured output with a Pydantic model.""" + """Test to verify structured output is generated both on invoke and stream. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, ensure that the model's ``bind_tools`` method + properly handles both JSON Schema and Pydantic V2 models. + ``langchain_core`` implements a utility function that will accommodate + most formats: https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.convert_to_openai_tool.html + + See example implementation of ``with_structured_output`` here: https://python.langchain.com/api_reference/_modules/langchain_openai/chat_models/base.html#BaseChatOpenAI.with_structured_output + """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") + Joke = _get_joke_class() + # Pydantic class # Type ignoring since the interface only officially supports pydantic 1 # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2. @@ -717,9 +1190,34 @@ async def test_structured_output_async(self, model: BaseChatModel) -> None: @pytest.mark.skipif(PYDANTIC_MAJOR_VERSION != 2, reason="Test requires pydantic 2.") def test_structured_output_pydantic_2_v1(self, model: BaseChatModel) -> None: - """Test to verify compatibility with pydantic.v1.BaseModel. + """Test to verify we can generate structured output using + pydantic.v1.BaseModel. pydantic.v1.BaseModel is available in the pydantic 2 package. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, ensure that the model's ``bind_tools`` method + properly handles both JSON Schema and Pydantic V1 models. + ``langchain_core`` implements a utility function that will accommodate + most formats: https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.convert_to_openai_tool.html + + See example implementation of ``with_structured_output`` here: https://python.langchain.com/api_reference/_modules/langchain_openai/chat_models/base.html#BaseChatOpenAI.with_structured_output """ if not self.has_tool_calling: pytest.skip("Test requires tool calling.") @@ -750,7 +1248,33 @@ class Joke(BaseModelV1): # Uses langchain_core.pydantic_v1.BaseModel assert set(chunk.keys()) == {"setup", "punchline"} def test_structured_output_optional_param(self, model: BaseChatModel) -> None: - """Test to verify structured output with an optional param.""" + """Test to verify we can generate structured output that includes optional + parameters. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, ensure that the model's ``bind_tools`` method + properly handles Pydantic V2 models with optional parameters. + ``langchain_core`` implements a utility function that will accommodate + most formats: https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.convert_to_openai_tool.html + + See example implementation of ``with_structured_output`` here: https://python.langchain.com/api_reference/_modules/langchain_openai/chat_models/base.html#BaseChatOpenAI.with_structured_output + """ if not self.has_tool_calling: pytest.skip("Test requires tool calling.") @@ -771,11 +1295,45 @@ class Joke(BaseModel): joke_result = chat.invoke("Give me a joke about cats, include the punchline.") assert isinstance(joke_result, Joke) - def test_tool_message_histories_string_content(self, model: BaseChatModel) -> None: - """ - Test that message histories are compatible with string tool contents - (e.g. OpenAI). - """ + def test_tool_message_histories_string_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + """Test that message histories are compatible with string tool contents + (e.g. OpenAI format). If a model passes this test, it should be compatible + with messages generated from providers following OpenAI format. + + This test should be skipped if the model does not support tool calling + (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model can correctly handle message histories that include AIMessage objects with ``""`` content. + 2. The ``tool_calls`` attribute on AIMessage objects is correctly handled and passed to the model in an appropriate format. + 3. The model can correctly handle ToolMessage objects with string content and arbitrary string values for ``tool_call_id``. + + You can ``xfail`` the test if tool calling is implemented but this format + is not supported. + + .. code-block:: python + + @pytest.mark.xfail(reason=("Not implemented.")) + def test_tool_message_histories_string_content(self, *args: Any) -> None: + super().test_tool_message_histories_string_content(*args) + """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") model_with_tools = model.bind_tools([my_adder_tool]) @@ -808,11 +1366,58 @@ def test_tool_message_histories_string_content(self, model: BaseChatModel) -> No def test_tool_message_histories_list_content( self, model: BaseChatModel, + my_adder_tool: BaseTool, ) -> None: - """ - Test that message histories are compatible with list tool contents - (e.g. Anthropic). - """ + """Test that message histories are compatible with list tool contents + (e.g. Anthropic format). + + These message histories will include AIMessage objects with "tool use" and + content blocks, e.g., + + .. code-block:: python + + [ + {"type": "text", "text": "Hmm let me think about that"}, + { + "type": "tool_use", + "input": {"fav_color": "green"}, + "id": "foo", + "name": "color_picker", + }, + ] + + This test should be skipped if the model does not support tool calling + (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model can correctly handle message histories that include AIMessage objects with list content. + 2. The ``tool_calls`` attribute on AIMessage objects is correctly handled and passed to the model in an appropriate format. + 3. The model can correctly handle ToolMessage objects with string content and arbitrary string values for ``tool_call_id``. + + You can ``xfail`` the test if tool calling is implemented but this format + is not supported. + + .. code-block:: python + + @pytest.mark.xfail(reason=("Not implemented.")) + def test_tool_message_histories_list_content(self, *args: Any) -> None: + super().test_tool_message_histories_list_content(*args) + """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") model_with_tools = model.bind_tools([my_adder_tool]) @@ -850,42 +1455,106 @@ def test_tool_message_histories_list_content( result_list_content = model_with_tools.invoke(messages_list_content) assert isinstance(result_list_content, AIMessage) - def test_structured_few_shot_examples(self, model: BaseChatModel) -> None: - """ - Test that model can process few-shot examples with tool calls. - """ + def test_structured_few_shot_examples( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + """Test that the model can process few-shot examples with tool calls. + + These are represented as a sequence of messages of the following form: + + - ``HumanMessage`` with string content; + - ``AIMessage`` with the ``tool_calls`` attribute populated; + - ``ToolMessage`` with string content; + - ``AIMessage`` with string content (an answer); + - ``HuamnMessage`` with string content (a follow-up question). + + This test should be skipped if the model does not support tool calling + (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + This test uses a utility function in ``langchain_core`` to generate a + sequence of messages representing "few-shot" examples: https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.tool_example_to_messages.html + + If this test fails, check that the model can correctly handle this + sequence of messages. + + You can ``xfail`` the test if tool calling is implemented but this format + is not supported. + + .. code-block:: python + + @pytest.mark.xfail(reason=("Not implemented.")) + def test_structured_few_shot_examples(self, *args: Any) -> None: + super().test_structured_few_shot_examples(*args) + """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") model_with_tools = model.bind_tools([my_adder_tool], tool_choice="any") - function_name = "my_adder_tool" - function_args = {"a": 1, "b": 2} function_result = json.dumps({"result": 3}) - messages_string_content = [ - HumanMessage("What is 1 + 2"), - AIMessage( - "", - tool_calls=[ - { - "name": function_name, - "args": function_args, - "id": "abc123", - "type": "tool_call", - }, - ], - ), - ToolMessage( - function_result, - name=function_name, - tool_call_id="abc123", - ), - AIMessage(function_result), - HumanMessage("What is 3 + 4"), - ] - result_string_content = model_with_tools.invoke(messages_string_content) - assert isinstance(result_string_content, AIMessage) + tool_schema = my_adder_tool.args_schema + assert tool_schema is not None + few_shot_messages = tool_example_to_messages( + "What is 1 + 2", + [tool_schema(a=1, b=2)], + tool_outputs=[function_result], + ai_response=function_result, + ) + + messages = few_shot_messages + [HumanMessage("What is 3 + 4")] + result = model_with_tools.invoke(messages) + assert isinstance(result, AIMessage) def test_image_inputs(self, model: BaseChatModel) -> None: + """Test that the model can process image inputs. + + This test should be skipped (see Configuration below) if the model does not + support image inputs These will take the form of messages with OpenAI-style + image content blocks: + + .. code-block:: python + + [ + {"type": "text", "text": "describe the weather in this image"}, + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ] + + See https://python.langchain.com/docs/concepts/multimodality/ + + .. dropdown:: Configuration + + To disable this test, set ``supports_image_inputs`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def supports_image_inputs(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that the model can correctly handle messages + with image content blocks in OpenAI format, including base64-encoded + images. Otherwise, set the ``supports_image_inputs`` property to False. + """ if not self.supports_image_inputs: return image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" @@ -902,6 +1571,46 @@ def test_image_inputs(self, model: BaseChatModel) -> None: model.invoke([message]) def test_image_tool_message(self, model: BaseChatModel) -> None: + """Test that the model can process ToolMessages with image inputs. + + This test should be skipped if the model does not support messages of the + form: + + .. code-block:: python + + ToolMessage( + content=[ + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ], + tool_call_id="1", + name="random_image", + ) + + This test can be skipped by setting the ``supports_image_tool_message`` property + to False (see Configuration below). + + .. dropdown:: Configuration + + To disable this test, set ``supports_image_tool_message`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def supports_image_tool_message(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that the model can correctly handle messages + with image content blocks in ToolMessages, including base64-encoded + images. Otherwise, set the ``supports_image_tool_message`` property to + False. + """ if not self.supports_image_tool_message: return image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" @@ -933,6 +1642,72 @@ def random_image() -> str: model.bind_tools([random_image]).invoke(messages) def test_anthropic_inputs(self, model: BaseChatModel) -> None: + """Test that model can process Anthropic-style message histories. + + These message histories will include ``AIMessage`` objects with ``tool_use`` + content blocks, e.g., + + .. code-block:: python + + AIMessage( + [ + {"type": "text", "text": "Hmm let me think about that"}, + { + "type": "tool_use", + "input": {"fav_color": "green"}, + "id": "foo", + "name": "color_picker", + }, + ] + ) + + as well as ``HumanMessage`` objects containing ``tool_result`` content blocks: + + .. code-block:: python + + HumanMessage( + [ + { + "type": "tool_result", + "tool_use_id": "foo", + "content": [ + { + "type": "text", + "text": "green is a great pick! that's my sister's favorite color", # noqa: E501 + } + ], + "is_error": False, + }, + {"type": "text", "text": "what's my sister's favorite color"}, + ] + ) + + This test should be skipped if the model does not support messages of this + form (or doesn't support tool calling generally). See Configuration below. + + .. dropdown:: Configuration + + To disable this test, set ``supports_anthropic_inputs`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def supports_anthropic_inputs(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model can correctly handle message histories that include message objects with list content. + 2. The ``tool_calls`` attribute on AIMessage objects is correctly handled and passed to the model in an appropriate format. + 3. HumanMessages with "tool_result" content blocks are correctly handled. + + Otherwise, if Anthropic tool call and result formats are not supported, + set the ``supports_anthropic_inputs`` property to False. + """ # noqa: E501 if not self.supports_anthropic_inputs: return @@ -993,8 +1768,48 @@ class color_picker(BaseModelV1): ] model.bind_tools([color_picker]).invoke(messages) - def test_tool_message_error_status(self, model: BaseChatModel) -> None: - """Test that ToolMessage with status='error' can be handled.""" + def test_tool_message_error_status( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + """Test that ToolMessage with ``status="error"`` can be handled. + + These messages may take the form: + + .. code-block:: python + + ToolMessage( + "Error: Missing required argument 'b'.", + name="my_adder_tool", + tool_call_id="abc123", + status="error", + ) + + If possible, the ``status`` field should be parsed and passed appropriately + to the model. + + This test is optional and should be skipped if the model does not support + tool calling (see Configuration below). + + .. dropdown:: Configuration + + To disable tool calling tests, set ``has_tool_calling`` to False in your + test class: + + .. code-block:: python + + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def has_tool_calling(self) -> bool: + return False + + .. dropdown:: Troubleshooting + + If this test fails, check that the ``status`` field on ``ToolMessage`` + objects is either ignored or passed to the model appropriately. + + Otherwise, ensure that the ``tool_choice_value`` property is correctly + specified on the test class. + """ if not self.has_tool_calling: pytest.skip("Test requires tool calling.") model_with_tools = model.bind_tools([my_adder_tool]) @@ -1022,6 +1837,22 @@ def test_tool_message_error_status(self, model: BaseChatModel) -> None: assert isinstance(result, AIMessage) def test_message_with_name(self, model: BaseChatModel) -> None: + """Test that HumanMessage with values for the ``name`` field can be handled. + + These messages may take the form: + + .. code-block:: python + + HumanMessage("hello", name="example_user") + + If possible, the ``name`` field should be parsed and passed appropriately + to the model. Otherwise, it should be ignored. + + .. dropdown:: Troubleshooting + + If this test fails, check that the ``name`` field on ``HumanMessage`` + objects is either ignored or passed to the model appropriately. + """ result = model.invoke([HumanMessage("hello", name="example_user")]) assert result is not None assert isinstance(result, AIMessage) @@ -1029,16 +1860,21 @@ def test_message_with_name(self, model: BaseChatModel) -> None: assert len(result.content) > 0 def invoke_with_audio_input(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_audio_output(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_reasoning_output(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_cache_read_input(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_cache_creation_input(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() diff --git a/libs/standard-tests/langchain_tests/integration_tests/embeddings.py b/libs/standard-tests/langchain_tests/integration_tests/embeddings.py index 7e3689d0f5429..8b4f20bb4a5e7 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/embeddings.py +++ b/libs/standard-tests/langchain_tests/integration_tests/embeddings.py @@ -6,7 +6,47 @@ class EmbeddingsIntegrationTests(EmbeddingsTests): + """Base class for embeddings integration tests. + + Test subclasses must implement the ``embeddings_class`` property to specify the + embeddings model to be tested. You can also override the + ``embedding_model_params`` property to specify initialization parameters. + + Example: + + .. code-block:: python + + from typing import Type + + from langchain_tests.integration_tests import EmbeddingsIntegrationTests + from my_package.embeddings import MyEmbeddingsModel + + + class TestMyEmbeddingsModelIntegration(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[MyEmbeddingsModel]: + # Return the embeddings model class to test here + return MyEmbeddingsModel + + @property + def embedding_model_params(self) -> dict: + # Return initialization parameters for the model. + return {"model": "model-001"} + + .. note:: + API references for individual test methods include troubleshooting tips. + """ + def test_embed_query(self, model: Embeddings) -> None: + """Test embedding a string query. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of floats when calling ``.embed_query`` on a string. + 2. The length of the list is consistent across different inputs. + """ # noqa: E501 embedding_1 = model.embed_query("foo") assert isinstance(embedding_1, List) @@ -18,6 +58,15 @@ def test_embed_query(self, model: Embeddings) -> None: assert len(embedding_1) == len(embedding_2) def test_embed_documents(self, model: Embeddings) -> None: + """Test embedding a list of strings. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of lists of floats when calling ``.embed_documents`` on a list of strings. + 2. The length of each list is the same. + """ # noqa: E501 documents = ["foo", "bar", "baz"] embeddings = model.embed_documents(documents) @@ -28,6 +77,15 @@ def test_embed_documents(self, model: Embeddings) -> None: assert all(len(embedding) == len(embeddings[0]) for embedding in embeddings) async def test_aembed_query(self, model: Embeddings) -> None: + """Test embedding a string query async. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of floats when calling ``.aembed_query`` on a string. + 2. The length of the list is consistent across different inputs. + """ # noqa: E501 embedding_1 = await model.aembed_query("foo") assert isinstance(embedding_1, List) @@ -39,6 +97,15 @@ async def test_aembed_query(self, model: Embeddings) -> None: assert len(embedding_1) == len(embedding_2) async def test_aembed_documents(self, model: Embeddings) -> None: + """Test embedding a list of strings async. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of lists of floats when calling ``.aembed_documents`` on a list of strings. + 2. The length of each list is the same. + """ # noqa: E501 documents = ["foo", "bar", "baz"] embeddings = await model.aembed_documents(documents) diff --git a/libs/standard-tests/langchain_tests/integration_tests/indexer.py b/libs/standard-tests/langchain_tests/integration_tests/indexer.py index f1e5d9eee0a43..bdc0fc2e6b408 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/indexer.py +++ b/libs/standard-tests/langchain_tests/integration_tests/indexer.py @@ -1,4 +1,12 @@ -"""Test suite to check index implementations.""" +"""Test suite to check index implementations. + +Standard tests for the DocumentIndex abstraction + +We don't recommend implementing externally managed DocumentIndex abstractions at this +time. + +:private: +""" import inspect import uuid diff --git a/libs/standard-tests/langchain_tests/integration_tests/retrievers.py b/libs/standard-tests/langchain_tests/integration_tests/retrievers.py new file mode 100644 index 0000000000000..72425f30c7cab --- /dev/null +++ b/libs/standard-tests/langchain_tests/integration_tests/retrievers.py @@ -0,0 +1,134 @@ +from abc import abstractmethod +from typing import Type + +import pytest +from langchain_core.documents import Document +from langchain_core.retrievers import BaseRetriever + +from langchain_tests.base import BaseStandardTests + + +class RetrieversIntegrationTests(BaseStandardTests): + """ + Base class for retrievers integration tests. + """ + + @property + @abstractmethod + def retriever_constructor(self) -> Type[BaseRetriever]: + """ + A BaseRetriever subclass to be tested. + """ + ... + + @property + def retriever_constructor_params(self) -> dict: + """ + Returns a dictionary of parameters to pass to the retriever constructor. + """ + return {} + + @property + @abstractmethod + def retriever_query_example(self) -> str: + """ + Returns a str representing the "query" of an example retriever call. + """ + ... + + @pytest.fixture + def retriever(self) -> BaseRetriever: + """ + :private: + """ + return self.retriever_constructor(**self.retriever_constructor_params) + + def test_k_constructor_param(self) -> None: + """ + Test that the retriever constructor accepts a k parameter, representing + the number of documents to return. + + .. dropdown:: Troubleshooting + + If this test fails, either the retriever constructor does not accept a k + parameter, or the retriever does not return the correct number of documents + (`k`) when it is set. + + For example, a retriever like + + .. code-block:: python + + MyRetriever(k=3).invoke("query") + + should return 3 documents when invoked with a query. + """ + params = { + k: v for k, v in self.retriever_constructor_params.items() if k != "k" + } + params_3 = {**params, "k": 3} + retriever_3 = self.retriever_constructor(**params_3) + result_3 = retriever_3.invoke(self.retriever_query_example) + assert len(result_3) == 3 + assert all(isinstance(doc, Document) for doc in result_3) + + params_1 = {**params, "k": 1} + retriever_1 = self.retriever_constructor(**params_1) + result_1 = retriever_1.invoke(self.retriever_query_example) + assert len(result_1) == 1 + assert all(isinstance(doc, Document) for doc in result_1) + + def test_invoke_with_k_kwarg(self, retriever: BaseRetriever) -> None: + """ + Test that the invoke method accepts a k parameter, representing the number of + documents to return. + + .. dropdown:: Troubleshooting + + If this test fails, the retriever's invoke method does not accept a k + parameter, or the retriever does not return the correct number of documents + (`k`) when it is set. + + For example, a retriever like + + .. code-block:: python + + MyRetriever().invoke("query", k=3) + + should return 3 documents when invoked with a query. + """ + result_1 = retriever.invoke(self.retriever_query_example, k=1) + assert len(result_1) == 1 + assert all(isinstance(doc, Document) for doc in result_1) + + result_3 = retriever.invoke(self.retriever_query_example, k=3) + assert len(result_3) == 3 + assert all(isinstance(doc, Document) for doc in result_3) + + def test_invoke_returns_documents(self, retriever: BaseRetriever) -> None: + """ + If invoked with the example params, the retriever should return a list of + Documents. + + .. dropdown:: Troubleshooting + + If this test fails, the retriever's invoke method does not return a list of + `langchain_core.document.Document` objects. Please confirm that your + `_get_relevant_documents` method returns a list of `Document` objects. + """ + result = retriever.invoke(self.retriever_query_example) + + assert isinstance(result, list) + assert all(isinstance(doc, Document) for doc in result) + + async def test_ainvoke_returns_documents(self, retriever: BaseRetriever) -> None: + """ + If ainvoked with the example params, the retriever should return a list of + Documents. + + See :meth:`test_invoke_returns_documents` for more information on + troubleshooting. + """ + result = await retriever.ainvoke(self.retriever_query_example) + + assert isinstance(result, list) + assert all(isinstance(doc, Document) for doc in result) diff --git a/libs/standard-tests/langchain_tests/integration_tests/tools.py b/libs/standard-tests/langchain_tests/integration_tests/tools.py index 4987626037863..2fcd610ccc052 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/tools.py +++ b/libs/standard-tests/langchain_tests/integration_tests/tools.py @@ -5,9 +5,21 @@ class ToolsIntegrationTests(ToolsTests): + """ + Base class for tools integration tests. + """ + def test_invoke_matches_output_schema(self, tool: BaseTool) -> None: """ If invoked with a ToolCall, the tool should return a valid ToolMessage content. + + If you have followed the `custom tool guide `_, + this test should always pass because ToolCall inputs are handled by the + :class:`langchain_core.tools.BaseTool` class. + + If you have not followed this guide, you should ensure that your tool's + `invoke` method returns a valid ToolMessage content when it receives + a dict representing a ToolCall as input (as opposed to distinct args). """ tool_call = ToolCall( name=tool.name, @@ -36,6 +48,8 @@ def test_invoke_matches_output_schema(self, tool: BaseTool) -> None: async def test_async_invoke_matches_output_schema(self, tool: BaseTool) -> None: """ If ainvoked with a ToolCall, the tool should return a valid ToolMessage content. + + For debugging tips, see :meth:`test_invoke_matches_output_schema`. """ tool_call = ToolCall( name=tool.name, @@ -65,12 +79,20 @@ def test_invoke_no_tool_call(self, tool: BaseTool) -> None: """ If invoked without a ToolCall, the tool can return anything but it shouldn't throw an error + + If this test fails, your tool may not be handling the input you defined + in `tool_invoke_params_example` correctly, and it's throwing an error. + + This test doesn't have any checks. It's just to ensure that the tool + doesn't throw an error when invoked with a dictionary of kwargs. """ tool.invoke(self.tool_invoke_params_example) async def test_async_invoke_no_tool_call(self, tool: BaseTool) -> None: """ - If invoked without a ToolCall, the tool can return anything + If ainvoked without a ToolCall, the tool can return anything but it shouldn't throw an error + + For debugging tips, see :meth:`test_invoke_no_tool_call`. """ await tool.ainvoke(self.tool_invoke_params_example) diff --git a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py index 08b0358dcfb9e..6b8d8d1d565d6 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py +++ b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py @@ -14,19 +14,86 @@ EMBEDDING_SIZE = 6 -class ReadWriteTestSuite(BaseStandardTests): - """Test suite for checking the read-write API of a vectorstore. - - This test suite verifies the basic read-write API of a vectorstore. - - The test suite is designed for synchronous vectorstores. +class VectorStoreIntegrationTests(BaseStandardTests): + """Base class for vector store integration tests. Implementers should subclass this test suite and provide a fixture - that returns an empty vectorstore for each test. + that returns an empty vector store for each test. - The fixture should use the `get_embeddings` method to get a pre-defined + The fixture should use the ``get_embeddings`` method to get a pre-defined embeddings model that should be used for this test suite. - """ + + Here is a template: + + .. code-block:: python + + from typing import Generator + + import pytest + from langchain_core.vectorstores import VectorStore + from langchain_parrot_link.vectorstores import ParrotVectorStore + from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests + + + class TestParrotVectorStore(VectorStoreIntegrationTests): + @pytest.fixture() + def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore + \"\"\"Get an empty vectorstore.\"\"\" + store = ParrotVectorStore(self.get_embeddings()) + # note: store should be EMPTY at this point + # if you need to delete data, you may do so here + try: + yield store + finally: + # cleanup operations, or deleting data + pass + + In the fixture, before the ``yield`` we instantiate an empty vector store. In the + ``finally`` block, we call whatever logic is necessary to bring the vector store + to a clean state. + + Example: + + .. code-block:: python + + from typing import Generator + + import pytest + from langchain_core.vectorstores import VectorStore + from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests + + from langchain_chroma import Chroma + + + class TestChromaStandard(VectorStoreIntegrationTests): + @pytest.fixture() + def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore + \"\"\"Get an empty vectorstore for unit tests.\"\"\" + store = Chroma(embedding_function=self.get_embeddings()) + try: + yield store + finally: + store.delete_collection() + pass + + Note that by default we enable both sync and async tests. To disable either, + override the ``has_sync`` or ``has_async`` properties to ``False`` in the + subclass. For example: + + .. code-block:: python + + class TestParrotVectorStore(VectorStoreIntegrationTests): + @pytest.fixture() + def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore + ... + + @property + def has_async(self) -> bool: + return False + + .. note:: + API references for individual test methods include troubleshooting tips. + """ # noqa: E501 @abstractmethod @pytest.fixture @@ -36,19 +103,61 @@ def vectorstore(self) -> VectorStore: The returned vectorstore should be EMPTY. """ + @property + def has_sync(self) -> bool: + """ + Configurable property to enable or disable sync tests. + """ + return True + + @property + def has_async(self) -> bool: + """ + Configurable property to enable or disable async tests. + """ + return True + @staticmethod def get_embeddings() -> Embeddings: - """A pre-defined embeddings model that should be used for this test.""" + """A pre-defined embeddings model that should be used for this test. + + This currently uses ``DeterministicFakeEmbedding`` from ``langchain-core``, + which uses numpy to generate random numbers based on a hash of the input text. + + The resulting embeddings are not meaningful, but they are deterministic. + """ return DeterministicFakeEmbedding( size=EMBEDDING_SIZE, ) def test_vectorstore_is_empty(self, vectorstore: VectorStore) -> None: - """Test that the vectorstore is empty.""" + """Test that the vectorstore is empty. + + .. dropdown:: Troubleshooting + + If this test fails, check that the test class (i.e., sub class of + ``VectorStoreIntegrationTests``) initializes an empty vector store in the + ``vectorestore`` fixture. + """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + assert vectorstore.similarity_search("foo", k=1) == [] def test_add_documents(self, vectorstore: VectorStore) -> None: - """Test adding documents into the vectorstore.""" + """Test adding documents into the vectorstore. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. We correctly initialize an empty vector store in the ``vectorestore`` fixture. + 2. Calling ``.similarity_search`` for the top ``k`` similar documents does not threshold by score. + 3. We do not mutate the original document object when adding it to the vector store (e.g., by adding an ID). + """ # noqa: E501 + if not self.has_sync: + pytest.skip("Sync tests not supported.") + original_documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -71,11 +180,30 @@ def test_vectorstore_still_empty(self, vectorstore: VectorStore) -> None: This just verifies that the fixture is set up properly to be empty after each test. + + .. dropdown:: Troubleshooting + + If this test fails, check that the test class (i.e., sub class of + ``VectorStoreIntegrationTests``) correctly clears the vector store in the + ``finally`` block. """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + assert vectorstore.similarity_search("foo", k=1) == [] def test_deleting_documents(self, vectorstore: VectorStore) -> None: - """Test deleting documents from the vectorstore.""" + """Test deleting documents from the vectorstore. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``add_documents`` preserves identifiers + passed in through ``ids``, and that ``delete`` correctly removes + documents. + """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -87,7 +215,16 @@ def test_deleting_documents(self, vectorstore: VectorStore) -> None: assert documents == [Document(page_content="bar", metadata={"id": 2}, id="2")] def test_deleting_bulk_documents(self, vectorstore: VectorStore) -> None: - """Test that we can delete several documents at once.""" + """Test that we can delete several documents at once. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``delete`` correctly removes multiple + documents when given a list of IDs. + """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -100,14 +237,33 @@ def test_deleting_bulk_documents(self, vectorstore: VectorStore) -> None: assert documents == [Document(page_content="baz", metadata={"id": 3}, id="3")] def test_delete_missing_content(self, vectorstore: VectorStore) -> None: - """Deleting missing content should not raise an exception.""" + """Deleting missing content should not raise an exception. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``delete`` does not raise an exception + when deleting IDs that do not exist. + """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + vectorstore.delete(["1"]) vectorstore.delete(["1", "2", "3"]) def test_add_documents_with_ids_is_idempotent( self, vectorstore: VectorStore ) -> None: - """Adding by ID should be idempotent.""" + """Adding by ID should be idempotent. + + .. dropdown:: Troubleshooting + + If this test fails, check that adding the same document twice with the + same IDs has the same effect as adding it once (i.e., it does not + duplicate the documents). + """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -121,7 +277,17 @@ def test_add_documents_with_ids_is_idempotent( ] def test_add_documents_by_id_with_mutation(self, vectorstore: VectorStore) -> None: - """Test that we can overwrite by ID using add_documents.""" + """Test that we can overwrite by ID using add_documents. + + .. dropdown:: Troubleshooting + + If this test fails, check that when ``add_documents`` is called with an + ID that already exists in the vector store, the content is updated + rather than duplicated. + """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -150,7 +316,29 @@ def test_add_documents_by_id_with_mutation(self, vectorstore: VectorStore) -> No ] def test_get_by_ids(self, vectorstore: VectorStore) -> None: - """Test get by IDs.""" + """Test get by IDs. + + This test requires that ``get_by_ids`` be implemented on the vector store. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and returns + documents in the same order as the IDs passed in. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + def test_get_by_ids(self, vectorstore: VectorStore) -> None: + super().test_get_by_ids(vectorstore) + """ + if not self.has_sync: + pytest.skip("Sync tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -163,13 +351,56 @@ def test_get_by_ids(self, vectorstore: VectorStore) -> None: ] def test_get_by_ids_missing(self, vectorstore: VectorStore) -> None: - """Test get by IDs with missing IDs.""" + """Test get by IDs with missing IDs. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and does not + raise an exception when given IDs that do not exist. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + def test_get_by_ids_missing(self, vectorstore: VectorStore) -> None: + super().test_get_by_ids_missing(vectorstore) + """ # noqa: E501 + if not self.has_sync: + pytest.skip("Sync tests not supported.") + # This should not raise an exception documents = vectorstore.get_by_ids(["1", "2", "3"]) assert documents == [] def test_add_documents_documents(self, vectorstore: VectorStore) -> None: - """Run add_documents tests.""" + """Run add_documents tests. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and returns + documents in the same order as the IDs passed in. + + Check also that ``add_documents`` will correctly generate string IDs if + none are provided. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + def test_add_documents_documents(self, vectorstore: VectorStore) -> None: + super().test_add_documents_documents(vectorstore) + """ # noqa: E501 + if not self.has_sync: + pytest.skip("Sync tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -181,7 +412,32 @@ def test_add_documents_documents(self, vectorstore: VectorStore) -> None: ] def test_add_documents_with_existing_ids(self, vectorstore: VectorStore) -> None: - """Test that add_documentsing with existing IDs is idempotent.""" + """Test that add_documents with existing IDs is idempotent. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and returns + documents in the same order as the IDs passed in. + + This test also verifies that: + + 1. IDs specified in the ``Document.id`` field are assigned when adding documents. + 2. If some documents include IDs and others don't string IDs are generated for the latter. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + def test_add_documents_with_existing_ids(self, vectorstore: VectorStore) -> None: + super().test_add_documents_with_existing_ids(vectorstore) + """ # noqa: E501 + if not self.has_sync: + pytest.skip("Sync tests not supported.") + documents = [ Document(id="foo", page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -193,42 +449,34 @@ def test_add_documents_with_existing_ids(self, vectorstore: VectorStore) -> None Document(page_content="bar", metadata={"id": 2}, id=ids[1]), ] + async def test_vectorstore_is_empty_async(self, vectorstore: VectorStore) -> None: + """Test that the vectorstore is empty. -class AsyncReadWriteTestSuite(BaseStandardTests): - """Test suite for checking the **async** read-write API of a vectorstore. + .. dropdown:: Troubleshooting - This test suite verifies the basic read-write API of a vectorstore. + If this test fails, check that the test class (i.e., sub class of + ``VectorStoreIntegrationTests``) initializes an empty vector store in the + ``vectorestore`` fixture. + """ + if not self.has_async: + pytest.skip("Async tests not supported.") - The test suite is designed for asynchronous vectorstores. + assert await vectorstore.asimilarity_search("foo", k=1) == [] - Implementers should subclass this test suite and provide a fixture - that returns an empty vectorstore for each test. + async def test_add_documents_async(self, vectorstore: VectorStore) -> None: + """Test adding documents into the vectorstore. - The fixture should use the `get_embeddings` method to get a pre-defined - embeddings model that should be used for this test suite. - """ + .. dropdown:: Troubleshooting - @abstractmethod - @pytest.fixture - async def vectorstore(self) -> VectorStore: - """Get the vectorstore class to test. + If this test fails, check that: - The returned vectorstore should be EMPTY. - """ + 1. We correctly initialize an empty vector store in the ``vectorestore`` fixture. + 2. Calling ``.asimilarity_search`` for the top ``k`` similar documents does not threshold by score. + 3. We do not mutate the original document object when adding it to the vector store (e.g., by adding an ID). + """ # noqa: E501 + if not self.has_async: + pytest.skip("Async tests not supported.") - @staticmethod - def get_embeddings() -> Embeddings: - """A pre-defined embeddings model that should be used for this test.""" - return DeterministicFakeEmbedding( - size=EMBEDDING_SIZE, - ) - - async def test_vectorstore_is_empty(self, vectorstore: VectorStore) -> None: - """Test that the vectorstore is empty.""" - assert await vectorstore.asimilarity_search("foo", k=1) == [] - - async def test_add_documents(self, vectorstore: VectorStore) -> None: - """Test adding documents into the vectorstore.""" original_documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -247,16 +495,37 @@ async def test_add_documents(self, vectorstore: VectorStore) -> None: Document(page_content="bar", metadata={"id": 2}), ] - async def test_vectorstore_still_empty(self, vectorstore: VectorStore) -> None: + async def test_vectorstore_still_empty_async( + self, vectorstore: VectorStore + ) -> None: """This test should follow a test that adds documents. This just verifies that the fixture is set up properly to be empty after each test. + + .. dropdown:: Troubleshooting + + If this test fails, check that the test class (i.e., sub class of + ``VectorStoreIntegrationTests``) correctly clears the vector store in the + ``finally`` block. """ + if not self.has_async: + pytest.skip("Async tests not supported.") + assert await vectorstore.asimilarity_search("foo", k=1) == [] - async def test_deleting_documents(self, vectorstore: VectorStore) -> None: - """Test deleting documents from the vectorstore.""" + async def test_deleting_documents_async(self, vectorstore: VectorStore) -> None: + """Test deleting documents from the vectorstore. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``aadd_documents`` preserves identifiers + passed in through ``ids``, and that ``delete`` correctly removes + documents. + """ + if not self.has_async: + pytest.skip("Async tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -267,8 +536,19 @@ async def test_deleting_documents(self, vectorstore: VectorStore) -> None: documents = await vectorstore.asimilarity_search("foo", k=1) assert documents == [Document(page_content="bar", metadata={"id": 2}, id="2")] - async def test_deleting_bulk_documents(self, vectorstore: VectorStore) -> None: - """Test that we can delete several documents at once.""" + async def test_deleting_bulk_documents_async( + self, vectorstore: VectorStore + ) -> None: + """Test that we can delete several documents at once. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``adelete`` correctly removes multiple + documents when given a list of IDs. + """ + if not self.has_async: + pytest.skip("Async tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -280,15 +560,34 @@ async def test_deleting_bulk_documents(self, vectorstore: VectorStore) -> None: documents = await vectorstore.asimilarity_search("foo", k=1) assert documents == [Document(page_content="baz", metadata={"id": 3}, id="3")] - async def test_delete_missing_content(self, vectorstore: VectorStore) -> None: - """Deleting missing content should not raise an exception.""" + async def test_delete_missing_content_async(self, vectorstore: VectorStore) -> None: + """Deleting missing content should not raise an exception. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``adelete`` does not raise an exception + when deleting IDs that do not exist. + """ + if not self.has_async: + pytest.skip("Async tests not supported.") + await vectorstore.adelete(["1"]) await vectorstore.adelete(["1", "2", "3"]) - async def test_add_documents_with_ids_is_idempotent( + async def test_add_documents_with_ids_is_idempotent_async( self, vectorstore: VectorStore ) -> None: - """Adding by ID should be idempotent.""" + """Adding by ID should be idempotent. + + .. dropdown:: Troubleshooting + + If this test fails, check that adding the same document twice with the + same IDs has the same effect as adding it once (i.e., it does not + duplicate the documents). + """ + if not self.has_async: + pytest.skip("Async tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -301,10 +600,20 @@ async def test_add_documents_with_ids_is_idempotent( Document(page_content="foo", metadata={"id": 1}, id="1"), ] - async def test_add_documents_by_id_with_mutation( + async def test_add_documents_by_id_with_mutation_async( self, vectorstore: VectorStore ) -> None: - """Test that we can overwrite by ID using add_documents.""" + """Test that we can overwrite by ID using add_documents. + + .. dropdown:: Troubleshooting + + If this test fails, check that when ``aadd_documents`` is called with an + ID that already exists in the vector store, the content is updated + rather than duplicated. + """ + if not self.has_async: + pytest.skip("Async tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -332,8 +641,30 @@ async def test_add_documents_by_id_with_mutation( Document(id="2", page_content="bar", metadata={"id": 2}), ] - async def test_get_by_ids(self, vectorstore: VectorStore) -> None: - """Test get by IDs.""" + async def test_get_by_ids_async(self, vectorstore: VectorStore) -> None: + """Test get by IDs. + + This test requires that ``get_by_ids`` be implemented on the vector store. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and returns + documents in the same order as the IDs passed in. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + async def test_get_by_ids(self, vectorstore: VectorStore) -> None: + await super().test_get_by_ids(vectorstore) + """ + if not self.has_async: + pytest.skip("Async tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -345,13 +676,58 @@ async def test_get_by_ids(self, vectorstore: VectorStore) -> None: Document(page_content="bar", metadata={"id": 2}, id=ids[1]), ] - async def test_get_by_ids_missing(self, vectorstore: VectorStore) -> None: - """Test get by IDs with missing IDs.""" + async def test_get_by_ids_missing_async(self, vectorstore: VectorStore) -> None: + """Test get by IDs with missing IDs. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and does not + raise an exception when given IDs that do not exist. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + async def test_get_by_ids_missing(self, vectorstore: VectorStore) -> None: + await super().test_get_by_ids_missing(vectorstore) + """ # noqa: E501 + if not self.has_async: + pytest.skip("Async tests not supported.") + # This should not raise an exception assert await vectorstore.aget_by_ids(["1", "2", "3"]) == [] - async def test_add_documents_documents(self, vectorstore: VectorStore) -> None: - """Run add_documents tests.""" + async def test_add_documents_documents_async( + self, vectorstore: VectorStore + ) -> None: + """Run add_documents tests. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and returns + documents in the same order as the IDs passed in. + + Check also that ``aadd_documents`` will correctly generate string IDs if + none are provided. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + async def test_add_documents_documents(self, vectorstore: VectorStore) -> None: + await super().test_add_documents_documents(vectorstore) + """ # noqa: E501 + if not self.has_async: + pytest.skip("Async tests not supported.") + documents = [ Document(page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), @@ -362,10 +738,35 @@ async def test_add_documents_documents(self, vectorstore: VectorStore) -> None: Document(page_content="bar", metadata={"id": 2}, id=ids[1]), ] - async def test_add_documents_with_existing_ids( + async def test_add_documents_with_existing_ids_async( self, vectorstore: VectorStore ) -> None: - """Test that add_documentsing with existing IDs is idempotent.""" + """Test that add_documents with existing IDs is idempotent. + + .. dropdown:: Troubleshooting + + If this test fails, check that ``get_by_ids`` is implemented and returns + documents in the same order as the IDs passed in. + + This test also verifies that: + + 1. IDs specified in the ``Document.id`` field are assigned when adding documents. + 2. If some documents include IDs and others don't string IDs are generated for the latter. + + .. note:: + ``get_by_ids`` was added to the ``VectorStore`` interface in + ``langchain-core`` version 0.2.11. If difficult to implement, this + test can be skipped using a pytest ``xfail`` on the test class: + + .. code-block:: python + + @pytest.mark.xfail(reason=("get_by_ids not implemented.")) + async def test_add_documents_with_existing_ids(self, vectorstore: VectorStore) -> None: + await super().test_add_documents_with_existing_ids(vectorstore) + """ # noqa: E501 + if not self.has_async: + pytest.skip("Async tests not supported.") + documents = [ Document(id="foo", page_content="foo", metadata={"id": 1}), Document(page_content="bar", metadata={"id": 2}), diff --git a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py index f5e5fe54f6e76..9d3b20de4ceb9 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py @@ -1,4 +1,6 @@ -"""Unit tests for chat models.""" +""" +:autodoc-options: autoproperty +""" import os from abc import abstractmethod @@ -9,7 +11,7 @@ from langchain_core.language_models import BaseChatModel from langchain_core.load import dumpd, load from langchain_core.runnables import RunnableBinding -from langchain_core.tools import tool +from langchain_core.tools import BaseTool, tool from pydantic import BaseModel, Field, SecretStr from pydantic.v1 import ( BaseModel as BaseModelV1, @@ -26,15 +28,12 @@ from langchain_tests.utils.pydantic import PYDANTIC_MAJOR_VERSION -class Person(BaseModel): # Used by some dependent tests. Should be deprecated. - """Record attributes of a person.""" - - name: str = Field(..., description="The name of the person.") - age: int = Field(..., description="The age of the person.") - - def generate_schema_pydantic_v1_from_2() -> Any: - """Use to generate a schema from v1 namespace in pydantic 2.""" + """ + Use to generate a schema from v1 namespace in pydantic 2. + + :private: + """ if PYDANTIC_MAJOR_VERSION != 2: raise AssertionError("This function is only compatible with Pydantic v2.") @@ -48,7 +47,11 @@ class PersonB(BaseModelV1): def generate_schema_pydantic() -> Any: - """Works with either pydantic 1 or 2""" + """ + Works with either pydantic 1 or 2 + + :private: + """ class PersonA(BaseModel): """Record attributes of a person.""" @@ -65,28 +68,26 @@ class PersonA(BaseModel): TEST_PYDANTIC_MODELS.append(generate_schema_pydantic_v1_from_2()) -@tool -def my_adder_tool(a: int, b: int) -> int: - """Takes two integers, a and b, and returns their sum.""" - return a + b - - -def my_adder(a: int, b: int) -> int: - """Takes two integers, a and b, and returns their sum.""" - return a + b +class ChatModelTests(BaseStandardTests): + """Base class for chat model tests. + :private: + """ # noqa: E501 -class ChatModelTests(BaseStandardTests): @property @abstractmethod - def chat_model_class(self) -> Type[BaseChatModel]: ... + def chat_model_class(self) -> Type[BaseChatModel]: + """The chat model class to test, e.g., ``ChatParrotLink``.""" + ... @property def chat_model_params(self) -> dict: + """Initialization parameters for the chat model.""" return {} @property def standard_chat_model_params(self) -> dict: + """:private:""" return { "temperature": 0, "max_tokens": 100, @@ -97,21 +98,35 @@ def standard_chat_model_params(self) -> dict: @pytest.fixture def model(self) -> BaseChatModel: + """:private:""" return self.chat_model_class( **{**self.standard_chat_model_params, **self.chat_model_params} ) + @pytest.fixture + def my_adder_tool(self) -> BaseTool: + """:private:""" + + @tool + def my_adder_tool(a: int, b: int) -> int: + """Takes two integers, a and b, and returns their sum.""" + return a + b + + return my_adder_tool + @property def has_tool_calling(self) -> bool: + """(bool) whether the model supports tool calling.""" return self.chat_model_class.bind_tools is not BaseChatModel.bind_tools @property def tool_choice_value(self) -> Optional[str]: - """Value to use for tool choice when used in tests.""" + """(None or str) to use for tool choice when used in tests.""" return None @property def has_structured_output(self) -> bool: + """(bool) whether the chat model supports structured output.""" return ( self.chat_model_class.with_structured_output is not BaseChatModel.with_structured_output @@ -119,22 +134,31 @@ def has_structured_output(self) -> bool: @property def supports_image_inputs(self) -> bool: + """(bool) whether the chat model supports image inputs, defaults to + ``False``.""" return False @property def supports_video_inputs(self) -> bool: + """(bool) whether the chat model supports video inputs, efaults to ``False``. + No current tests are written for this feature.""" return False @property def returns_usage_metadata(self) -> bool: + """(bool) whether the chat model returns usage metadata on invoke and streaming + responses.""" return True @property def supports_anthropic_inputs(self) -> bool: + """(bool) whether the chat model supports Anthropic-style inputs.""" return False @property def supports_image_tool_message(self) -> bool: + """(bool) whether the chat model supports ToolMessages that include image + content.""" return False @property @@ -152,31 +176,322 @@ def supported_usage_metadata_details( ] ], ]: + """(dict) what usage metadata details are emitted in invoke and stream. Only + needs to be overridden if these details are returned by the model.""" return {"invoke": [], "stream": []} class ChatModelUnitTests(ChatModelTests): + """Base class for chat model unit tests. + + Test subclasses must implement the ``chat_model_class`` and + ``chat_model_params`` properties to specify what model to test and its + initialization parameters. + + Example: + + .. code-block:: python + + from typing import Type + + from langchain_tests.unit_tests import ChatModelUnitTests + from my_package.chat_models import MyChatModel + + + class TestMyChatModelUnit(ChatModelUnitTests): + @property + def chat_model_class(self) -> Type[MyChatModel]: + # Return the chat model class to test here + return MyChatModel + + @property + def chat_model_params(self) -> dict: + # Return initialization parameters for the model. + return {"model": "model-001", "temperature": 0} + + .. note:: + API references for individual test methods include troubleshooting tips. + + + Test subclasses must implement the following two properties: + + chat_model_class + The chat model class to test, e.g., ``ChatParrotLink``. + + Example: + + .. code-block:: python + + @property + def chat_model_class(self) -> Type[ChatParrotLink]: + return ChatParrotLink + + chat_model_params + Initialization parameters for the chat model. + + Example: + + .. code-block:: python + + @property + def chat_model_params(self) -> dict: + return {"model": "bird-brain-001", "temperature": 0} + + In addition, test subclasses can control what features are tested (such as tool + calling or multi-modality) by selectively overriding the following properties. + Expand to see details: + + .. dropdown:: has_tool_calling + + Boolean property indicating whether the chat model supports tool calling. + + By default, this is determined by whether the chat model's `bind_tools` method + is overridden. It typically does not need to be overridden on the test class. + + Example override: + + .. code-block:: python + + @property + def has_tool_calling(self) -> bool: + return True + + .. dropdown:: tool_choice_value + + Value to use for tool choice when used in tests. + + Some tests for tool calling features attempt to force tool calling via a + `tool_choice` parameter. A common value for this parameter is "any". Defaults + to `None`. + + Note: if the value is set to "tool_name", the name of the tool used in each + test will be set as the value for `tool_choice`. + + Example: + + .. code-block:: python + + @property + def tool_choice_value(self) -> Optional[str]: + return "any" + + .. dropdown:: has_structured_output + + Boolean property indicating whether the chat model supports structured + output. + + By default, this is determined by whether the chat model's + `with_structured_output` method is overridden. If the base implementation is + intended to be used, this method should be overridden. + + See: https://python.langchain.com/docs/concepts/structured_outputs/ + + Example: + + .. code-block:: python + + @property + def has_structured_output(self) -> bool: + return True + + .. dropdown:: supports_image_inputs + + Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``. + + If set to ``True``, the chat model will be tested using content blocks of the + form + + .. code-block:: python + + [ + {"type": "text", "text": "describe the weather in this image"}, + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ] + + See https://python.langchain.com/docs/concepts/multimodality/ + + Example: + + .. code-block:: python + + @property + def supports_image_inputs(self) -> bool: + return True + + .. dropdown:: supports_video_inputs + + Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``. No current tests are written for this feature. + + .. dropdown:: returns_usage_metadata + + Boolean property indicating whether the chat model returns usage metadata + on invoke and streaming responses. + + ``usage_metadata`` is an optional dict attribute on AIMessages that track input + and output tokens: https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.UsageMetadata.html + + Example: + + .. code-block:: python + + @property + def returns_usage_metadata(self) -> bool: + return False + + .. dropdown:: supports_anthropic_inputs + + Boolean property indicating whether the chat model supports Anthropic-style + inputs. + + These inputs might feature "tool use" and "tool result" content blocks, e.g., + + .. code-block:: python + + [ + {"type": "text", "text": "Hmm let me think about that"}, + { + "type": "tool_use", + "input": {"fav_color": "green"}, + "id": "foo", + "name": "color_picker", + }, + ] + + If set to ``True``, the chat model will be tested using content blocks of this + form. + + Example: + + .. code-block:: python + + @property + def supports_anthropic_inputs(self) -> bool: + return False + + .. dropdown:: supports_image_tool_message + + Boolean property indicating whether the chat model supports ToolMessages + that include image content, e.g., + + .. code-block:: python + + ToolMessage( + content=[ + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ], + tool_call_id="1", + name="random_image", + ) + + If set to ``True``, the chat model will be tested with message sequences that + include ToolMessages of this form. + + Example: + + .. code-block:: python + + @property + def supports_image_tool_message(self) -> bool: + return False + + .. dropdown:: supported_usage_metadata_details + + Property controlling what usage metadata details are emitted in both invoke + and stream. + + ``usage_metadata`` is an optional dict attribute on AIMessages that track input + and output tokens: https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.UsageMetadata.html + + It includes optional keys ``input_token_details`` and ``output_token_details`` + that can track usage details associated with special types of tokens, such as + cached, audio, or reasoning. + + Only needs to be overridden if these details are supplied. + + Testing initialization from environment variables + Some unit tests may require testing initialization from environment variables. + These tests can be enabled by overriding the ``init_from_env_params`` + property (see below): + + .. dropdown:: init_from_env_params + + This property is used in unit tests to test initialization from + environment variables. It should return a tuple of three dictionaries + that specify the environment variables, additional initialization args, + and expected instance attributes to check. + + Defaults to empty dicts. If not overridden, the test is skipped. + + Example: + + .. code-block:: python + + @property + def init_from_env_params(self) -> Tuple[dict, dict, dict]: + return ( + { + "MY_API_KEY": "api_key", + }, + { + "model": "bird-brain-001", + }, + { + "my_api_key": "api_key", + }, + ) + """ # noqa: E501 + @property def standard_chat_model_params(self) -> dict: + """:private:""" params = super().standard_chat_model_params params["api_key"] = "test" return params @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: - """Return env vars, init args, and expected instance attrs for initializing - from env vars.""" + """(tuple) environment variables, additional initialization args, and expected + instance attributes for testing initialization from environment variables.""" return {}, {}, {} def test_init(self) -> None: + """Test model initialization. This should pass for all integrations. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that: + + 1. ``chat_model_params`` is specified and the model can be initialized from those params; + 2. The model accommodates standard parameters: https://python.langchain.com/docs/concepts/chat_models/#standard-parameters + """ # noqa: E501 model = self.chat_model_class( **{**self.standard_chat_model_params, **self.chat_model_params} ) assert model is not None def test_init_from_env(self) -> None: + """Test initialization from environment variables. Relies on the + ``init_from_env_params`` property. Test is skipped if that property is not + set. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that ``init_from_env_params`` is specified + correctly and that model parameters are properly set from environment + variables during initialization. + """ env_params, model_params, expected_attrs = self.init_from_env_params - if env_params: + if not env_params: + pytest.skip("init_from_env_params not specified.") + else: with mock.patch.dict(os.environ, env_params): model = self.chat_model_class(**model_params) assert model is not None @@ -189,6 +504,14 @@ def test_init_from_env(self) -> None: def test_init_streaming( self, ) -> None: + """Test that model can be initialized with ``streaming=True``. This is for + backward-compatibility purposes. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that the model can be initialized with a + boolean ``streaming`` parameter. + """ model = self.chat_model_class( **{ **self.standard_chat_model_params, @@ -201,10 +524,27 @@ def test_init_streaming( def test_bind_tool_pydantic( self, model: BaseChatModel, + my_adder_tool: BaseTool, ) -> None: + """Test that chat model correctly handles Pydantic models that are passed + into ``bind_tools``. Test is skipped if the ``has_tool_calling`` property + on the test class is False. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that the model's ``bind_tools`` method + properly handles Pydantic V2 models. ``langchain_core`` implements + a utility function that will accommodate most formats: https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.convert_to_openai_tool.html + + See example implementation of ``bind_tools`` here: https://python.langchain.com/api_reference/_modules/langchain_openai/chat_models/base.html#BaseChatOpenAI.bind_tools + """ # noqa: E501 if not self.has_tool_calling: return + def my_adder(a: int, b: int) -> int: + """Takes two integers, a and b, and returns their sum.""" + return a + b + tools = [my_adder_tool, my_adder] for pydantic_model in TEST_PYDANTIC_MODELS: @@ -227,12 +567,35 @@ def test_with_structured_output( model: BaseChatModel, schema: Any, ) -> None: + """Test ``with_structured_output`` method. Test is skipped if the + ``has_structured_output`` property on the test class is False. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that the model's ``bind_tools`` method + properly handles Pydantic V2 models. ``langchain_core`` implements + a utility function that will accommodate most formats: https://python.langchain.com/api_reference/core/utils/langchain_core.utils.function_calling.convert_to_openai_tool.html + + See example implementation of ``with_structured_output`` here: https://python.langchain.com/api_reference/_modules/langchain_openai/chat_models/base.html#BaseChatOpenAI.with_structured_output + """ # noqa: E501 if not self.has_structured_output: return assert model.with_structured_output(schema) is not None def test_standard_params(self, model: BaseChatModel) -> None: + """Test that model properly generates standard parameters. These are used + for tracing purposes. + + .. dropdown:: Troubleshooting + + If this test fails, check that the model accommodates standard parameters: + https://python.langchain.com/docs/concepts/chat_models/#standard-parameters + + Check also that the model class is named according to convention + (e.g., ``ChatProviderName``). + """ + class ExpectedParams(BaseModelV1): ls_provider: str ls_model_name: str @@ -260,10 +623,20 @@ class ExpectedParams(BaseModelV1): pytest.fail(f"Validation error: {e}") def test_serdes(self, model: BaseChatModel, snapshot: SnapshotAssertion) -> None: + """Test serialization and deserialization of the model. Test is skipped if the + ``is_lc_serializable`` property on the chat model class is not overwritten + to return ``True``. + + .. dropdown:: Troubleshooting + + If this test fails, check that the ``init_from_env_params`` property is + correctly set on the test class. + """ if not self.chat_model_class.is_lc_serializable(): - return - env_params, model_params, expected_attrs = self.init_from_env_params - with mock.patch.dict(os.environ, env_params): - ser = dumpd(model) - assert ser == snapshot(name="serialized") - assert model.dict() == load(dumpd(model)).dict() + pytest.skip("Model is not serializable.") + else: + env_params, model_params, expected_attrs = self.init_from_env_params + with mock.patch.dict(os.environ, env_params): + ser = dumpd(model) + assert ser == snapshot(name="serialized") + assert model.dict() == load(dumpd(model)).dict() diff --git a/libs/standard-tests/langchain_tests/unit_tests/embeddings.py b/libs/standard-tests/langchain_tests/unit_tests/embeddings.py index da7b78513844b..527be61e8be98 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/embeddings.py +++ b/libs/standard-tests/langchain_tests/unit_tests/embeddings.py @@ -11,6 +11,10 @@ class EmbeddingsTests(BaseStandardTests): + """ + :private: + """ + @property @abstractmethod def embeddings_class(self) -> Type[Embeddings]: ... @@ -25,17 +29,98 @@ def model(self) -> Embeddings: class EmbeddingsUnitTests(EmbeddingsTests): + """Base class for embeddings unit tests. + + Test subclasses must implement the ``embeddings_class`` property to specify the + embeddings model to be tested. You can also override the + ``embedding_model_params`` property to specify initialization parameters. + + Example: + + .. code-block:: python + + from typing import Type + + from langchain_tests.unit_tests import EmbeddingsUnitTests + from my_package.embeddings import MyEmbeddingsModel + + + class TestMyEmbeddingsModelUnit(EmbeddingsUnitTests): + @property + def embeddings_class(self) -> Type[MyEmbeddingsModel]: + # Return the embeddings model class to test here + return MyEmbeddingsModel + + @property + def embedding_model_params(self) -> dict: + # Return initialization parameters for the model. + return {"model": "model-001"} + + .. note:: + API references for individual test methods include troubleshooting tips. + + Testing initialization from environment variables + Overriding the ``init_from_env_params`` property will enable additional tests + for initialization from environment variables. See below for details. + + .. dropdown:: init_from_env_params + + This property is used in unit tests to test initialization from + environment variables. It should return a tuple of three dictionaries + that specify the environment variables, additional initialization args, + and expected instance attributes to check. + + Defaults to empty dicts. If not overridden, the test is skipped. + + Example: + + .. code-block:: python + + @property + def init_from_env_params(self) -> Tuple[dict, dict, dict]: + return ( + { + "MY_API_KEY": "api_key", + }, + { + "model": "model-001", + }, + { + "my_api_key": "api_key", + }, + ) + """ # noqa: E501 + def test_init(self) -> None: + """Test model initialization. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that ``embedding_model_params`` is specified + and the model can be initialized from those params. + """ model = self.embeddings_class(**self.embedding_model_params) assert model is not None @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: - """Return env vars, init args, and expected instance attrs for initializing - from env vars.""" + """This property is used in unit tests to test initialization from environment + variables. It should return a tuple of three dictionaries that specify the + environment variables, additional initialization args, and expected instance + attributes to check.""" return {}, {}, {} def test_init_from_env(self) -> None: + """Test initialization from environment variables. Relies on the + ``init_from_env_params`` property. Test is skipped if that property is not + set. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that ``init_from_env_params`` is specified + correctly and that model parameters are properly set from environment + variables during initialization. + """ env_params, embeddings_params, expected_attrs = self.init_from_env_params if env_params: with mock.patch.dict(os.environ, env_params): diff --git a/libs/standard-tests/langchain_tests/unit_tests/tools.py b/libs/standard-tests/langchain_tests/unit_tests/tools.py index 93701437da340..bdc2df1c9fb62 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/tools.py +++ b/libs/standard-tests/langchain_tests/unit_tests/tools.py @@ -11,12 +11,25 @@ class ToolsTests(BaseStandardTests): + """ + :private: + Base class for testing tools. This won't show in the documentation, but + the docstrings will be inherited by subclasses. + """ + @property @abstractmethod - def tool_constructor(self) -> Union[Type[BaseTool], BaseTool]: ... + def tool_constructor(self) -> Union[Type[BaseTool], BaseTool]: + """ + Returns a class or instance of a tool to be tested. + """ + ... @property def tool_constructor_params(self) -> dict: + """ + Returns a dictionary of parameters to pass to the tool constructor. + """ return {} @property @@ -24,13 +37,16 @@ def tool_invoke_params_example(self) -> dict: """ Returns a dictionary representing the "args" of an example tool call. - This should NOT be a ToolCall dict - i.e. it should not + This should NOT be a ToolCall dict - it should not have {"name", "id", "args"} keys. """ return {} @pytest.fixture def tool(self) -> BaseTool: + """ + :private: + """ if isinstance(self.tool_constructor, BaseTool): if self.tool_constructor_params != {}: msg = ( @@ -43,12 +59,9 @@ def tool(self) -> BaseTool: class ToolsUnitTests(ToolsTests): - def test_init(self) -> None: - if isinstance(self.tool_constructor, BaseTool): - tool = self.tool_constructor - else: - tool = self.tool_constructor(**self.tool_constructor_params) - assert tool is not None + """ + Base class for tools unit tests. + """ @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: @@ -56,6 +69,18 @@ def init_from_env_params(self) -> Tuple[dict, dict, dict]: from env vars.""" return {}, {}, {} + def test_init(self) -> None: + """ + Test that the tool can be initialized with :attr:`tool_constructor` and + :attr:`tool_constructor_params`. If this fails, check that the + keyword args defined in :attr:`tool_constructor_params` are valid. + """ + if isinstance(self.tool_constructor, BaseTool): + tool = self.tool_constructor + else: + tool = self.tool_constructor(**self.tool_constructor_params) + assert tool is not None + def test_init_from_env(self) -> None: env_params, tools_params, expected_attrs = self.init_from_env_params if env_params: @@ -69,14 +94,32 @@ def test_init_from_env(self) -> None: assert actual == expected def test_has_name(self, tool: BaseTool) -> None: + """ + Tests that the tool has a name attribute to pass to chat models. + + If this fails, add a `name` parameter to your tool. + """ assert tool.name def test_has_input_schema(self, tool: BaseTool) -> None: + """ + Tests that the tool has an input schema. + + If this fails, add an `args_schema` to your tool. + + See + `this guide `_ + and see how `CalculatorInput` is configured in the + `CustomCalculatorTool.args_schema` attribute + """ assert tool.get_input_schema() def test_input_schema_matches_invoke_params(self, tool: BaseTool) -> None: """ - Tests that the provided example params match the declared input schema + Tests that the provided example params match the declared input schema. + + If this fails, update the `tool_invoke_params_example` attribute to match + the input schema (`args_schema`) of the tool. """ # this will be a pydantic object input_schema = tool.get_input_schema() diff --git a/libs/standard-tests/langchain_tests/utils/pydantic.py b/libs/standard-tests/langchain_tests/utils/pydantic.py index 6aa0408a092d7..52720bbd081b2 100644 --- a/libs/standard-tests/langchain_tests/utils/pydantic.py +++ b/libs/standard-tests/langchain_tests/utils/pydantic.py @@ -1,4 +1,8 @@ -"""Utilities for working with pydantic models.""" +""" +Utilities for working with pydantic models. + +:private: +""" def get_pydantic_major_version() -> int: diff --git a/libs/standard-tests/poetry.lock b/libs/standard-tests/poetry.lock index a10861100dffc..316059246f762 100644 --- a/libs/standard-tests/poetry.lock +++ b/libs/standard-tests/poetry.lock @@ -13,24 +13,24 @@ files = [ [[package]] name = "anyio" -version = "4.6.2.post1" +version = "4.7.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.9" files = [ - {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"}, - {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"}, + {file = "anyio-4.7.0-py3-none-any.whl", hash = "sha256:ea60c3723ab42ba6fff7e8ccb0488c898ec538ff4df1f1d5e642c3601d07e352"}, + {file = "anyio-4.7.0.tar.gz", hash = "sha256:2f834749c602966b7d456a7567cafcb309f96482b5081d14ac93ccd457f9dd48"}, ] [package.dependencies] exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} idna = ">=2.8" sniffio = ">=1.1" -typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} +typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] -doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"] +doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"] trio = ["trio (>=0.26.1)"] [[package]] @@ -234,13 +234,13 @@ trio = ["trio (>=0.22.0,<1.0)"] [[package]] name = "httpx" -version = "0.27.2" +version = "0.28.1" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"}, - {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"}, + {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"}, + {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"}, ] [package.dependencies] @@ -248,7 +248,6 @@ anyio = "*" certifi = "*" httpcore = "==1.*" idna = "*" -sniffio = "*" [package.extras] brotli = ["brotli", "brotlicffi"] @@ -309,7 +308,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.22" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -334,13 +333,13 @@ url = "../core" [[package]] name = "langsmith" -version = "0.1.144" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.144-py3-none-any.whl", hash = "sha256:08ffb975bff2e82fc6f5428837c64c074ea25102d08a25e256361a80812c6100"}, - {file = "langsmith-0.1.144.tar.gz", hash = "sha256:b621f358d5a33441d7b5e7264c376bf4ea82bfc62d7e41aafc0f8094e3bd6369"}, + {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"}, + {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"}, ] [package.dependencies] @@ -353,6 +352,9 @@ pydantic = [ requests = ">=2,<3" requests-toolbelt = ">=1.0.0,<2.0.0" +[package.extras] +langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"] + [[package]] name = "mypy" version = "1.13.0" @@ -462,71 +464,152 @@ files = [ {file = "numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010"}, ] +[[package]] +name = "numpy" +version = "2.2.0" +description = "Fundamental package for array computing in Python" +optional = false +python-versions = ">=3.10" +files = [ + {file = "numpy-2.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1e25507d85da11ff5066269d0bd25d06e0a0f2e908415534f3e603d2a78e4ffa"}, + {file = "numpy-2.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a62eb442011776e4036af5c8b1a00b706c5bc02dc15eb5344b0c750428c94219"}, + {file = "numpy-2.2.0-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:b606b1aaf802e6468c2608c65ff7ece53eae1a6874b3765f69b8ceb20c5fa78e"}, + {file = "numpy-2.2.0-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:36b2b43146f646642b425dd2027730f99bac962618ec2052932157e213a040e9"}, + {file = "numpy-2.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7fe8f3583e0607ad4e43a954e35c1748b553bfe9fdac8635c02058023277d1b3"}, + {file = "numpy-2.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:122fd2fcfafdefc889c64ad99c228d5a1f9692c3a83f56c292618a59aa60ae83"}, + {file = "numpy-2.2.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3f2f5cddeaa4424a0a118924b988746db6ffa8565e5829b1841a8a3bd73eb59a"}, + {file = "numpy-2.2.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7fe4bb0695fe986a9e4deec3b6857003b4cfe5c5e4aac0b95f6a658c14635e31"}, + {file = "numpy-2.2.0-cp310-cp310-win32.whl", hash = "sha256:b30042fe92dbd79f1ba7f6898fada10bdaad1847c44f2dff9a16147e00a93661"}, + {file = "numpy-2.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:54dc1d6d66f8d37843ed281773c7174f03bf7ad826523f73435deb88ba60d2d4"}, + {file = "numpy-2.2.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:9874bc2ff574c40ab7a5cbb7464bf9b045d617e36754a7bc93f933d52bd9ffc6"}, + {file = "numpy-2.2.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:0da8495970f6b101ddd0c38ace92edea30e7e12b9a926b57f5fabb1ecc25bb90"}, + {file = "numpy-2.2.0-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:0557eebc699c1c34cccdd8c3778c9294e8196df27d713706895edc6f57d29608"}, + {file = "numpy-2.2.0-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:3579eaeb5e07f3ded59298ce22b65f877a86ba8e9fe701f5576c99bb17c283da"}, + {file = "numpy-2.2.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40deb10198bbaa531509aad0cd2f9fadb26c8b94070831e2208e7df543562b74"}, + {file = "numpy-2.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c2aed8fcf8abc3020d6a9ccb31dbc9e7d7819c56a348cc88fd44be269b37427e"}, + {file = "numpy-2.2.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a222d764352c773aa5ebde02dd84dba3279c81c6db2e482d62a3fa54e5ece69b"}, + {file = "numpy-2.2.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:4e58666988605e251d42c2818c7d3d8991555381be26399303053b58a5bbf30d"}, + {file = "numpy-2.2.0-cp311-cp311-win32.whl", hash = "sha256:4723a50e1523e1de4fccd1b9a6dcea750c2102461e9a02b2ac55ffeae09a4410"}, + {file = "numpy-2.2.0-cp311-cp311-win_amd64.whl", hash = "sha256:16757cf28621e43e252c560d25b15f18a2f11da94fea344bf26c599b9cf54b73"}, + {file = "numpy-2.2.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:cff210198bb4cae3f3c100444c5eaa573a823f05c253e7188e1362a5555235b3"}, + {file = "numpy-2.2.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:58b92a5828bd4d9aa0952492b7de803135038de47343b2aa3cc23f3b71a3dc4e"}, + {file = "numpy-2.2.0-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:ebe5e59545401fbb1b24da76f006ab19734ae71e703cdb4a8b347e84a0cece67"}, + {file = "numpy-2.2.0-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:e2b8cd48a9942ed3f85b95ca4105c45758438c7ed28fff1e4ce3e57c3b589d8e"}, + {file = "numpy-2.2.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:57fcc997ffc0bef234b8875a54d4058afa92b0b0c4223fc1f62f24b3b5e86038"}, + {file = "numpy-2.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:85ad7d11b309bd132d74397fcf2920933c9d1dc865487128f5c03d580f2c3d03"}, + {file = "numpy-2.2.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:cb24cca1968b21355cc6f3da1a20cd1cebd8a023e3c5b09b432444617949085a"}, + {file = "numpy-2.2.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0798b138c291d792f8ea40fe3768610f3c7dd2574389e37c3f26573757c8f7ef"}, + {file = "numpy-2.2.0-cp312-cp312-win32.whl", hash = "sha256:afe8fb968743d40435c3827632fd36c5fbde633b0423da7692e426529b1759b1"}, + {file = "numpy-2.2.0-cp312-cp312-win_amd64.whl", hash = "sha256:3a4199f519e57d517ebd48cb76b36c82da0360781c6a0353e64c0cac30ecaad3"}, + {file = "numpy-2.2.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f8c8b141ef9699ae777c6278b52c706b653bf15d135d302754f6b2e90eb30367"}, + {file = "numpy-2.2.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0f0986e917aca18f7a567b812ef7ca9391288e2acb7a4308aa9d265bd724bdae"}, + {file = "numpy-2.2.0-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:1c92113619f7b272838b8d6702a7f8ebe5edea0df48166c47929611d0b4dea69"}, + {file = "numpy-2.2.0-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:5a145e956b374e72ad1dff82779177d4a3c62bc8248f41b80cb5122e68f22d13"}, + {file = "numpy-2.2.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:18142b497d70a34b01642b9feabb70156311b326fdddd875a9981f34a369b671"}, + {file = "numpy-2.2.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a7d41d1612c1a82b64697e894b75db6758d4f21c3ec069d841e60ebe54b5b571"}, + {file = "numpy-2.2.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a98f6f20465e7618c83252c02041517bd2f7ea29be5378f09667a8f654a5918d"}, + {file = "numpy-2.2.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e09d40edfdb4e260cb1567d8ae770ccf3b8b7e9f0d9b5c2a9992696b30ce2742"}, + {file = "numpy-2.2.0-cp313-cp313-win32.whl", hash = "sha256:3905a5fffcc23e597ee4d9fb3fcd209bd658c352657548db7316e810ca80458e"}, + {file = "numpy-2.2.0-cp313-cp313-win_amd64.whl", hash = "sha256:a184288538e6ad699cbe6b24859206e38ce5fba28f3bcfa51c90d0502c1582b2"}, + {file = "numpy-2.2.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:7832f9e8eb00be32f15fdfb9a981d6955ea9adc8574c521d48710171b6c55e95"}, + {file = "numpy-2.2.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:f0dd071b95bbca244f4cb7f70b77d2ff3aaaba7fa16dc41f58d14854a6204e6c"}, + {file = "numpy-2.2.0-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:b0b227dcff8cdc3efbce66d4e50891f04d0a387cce282fe1e66199146a6a8fca"}, + {file = "numpy-2.2.0-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:6ab153263a7c5ccaf6dfe7e53447b74f77789f28ecb278c3b5d49db7ece10d6d"}, + {file = "numpy-2.2.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e500aba968a48e9019e42c0c199b7ec0696a97fa69037bea163b55398e390529"}, + {file = "numpy-2.2.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:440cfb3db4c5029775803794f8638fbdbf71ec702caf32735f53b008e1eaece3"}, + {file = "numpy-2.2.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:a55dc7a7f0b6198b07ec0cd445fbb98b05234e8b00c5ac4874a63372ba98d4ab"}, + {file = "numpy-2.2.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:4bddbaa30d78c86329b26bd6aaaea06b1e47444da99eddac7bf1e2fab717bd72"}, + {file = "numpy-2.2.0-cp313-cp313t-win32.whl", hash = "sha256:30bf971c12e4365153afb31fc73f441d4da157153f3400b82db32d04de1e4066"}, + {file = "numpy-2.2.0-cp313-cp313t-win_amd64.whl", hash = "sha256:d35717333b39d1b6bb8433fa758a55f1081543de527171543a2b710551d40881"}, + {file = "numpy-2.2.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:e12c6c1ce84628c52d6367863773f7c8c8241be554e8b79686e91a43f1733773"}, + {file = "numpy-2.2.0-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:b6207dc8fb3c8cb5668e885cef9ec7f70189bec4e276f0ff70d5aa078d32c88e"}, + {file = "numpy-2.2.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a50aeff71d0f97b6450d33940c7181b08be1441c6c193e678211bff11aa725e7"}, + {file = "numpy-2.2.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:df12a1f99b99f569a7c2ae59aa2d31724e8d835fc7f33e14f4792e3071d11221"}, + {file = "numpy-2.2.0.tar.gz", hash = "sha256:140dd80ff8981a583a60980be1a655068f8adebf7a45a06a6858c873fcdcd4a0"}, +] + [[package]] name = "orjson" -version = "3.10.11" +version = "3.10.12" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.11-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6dade64687f2bd7c090281652fe18f1151292d567a9302b34c2dbb92a3872f1f"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82f07c550a6ccd2b9290849b22316a609023ed851a87ea888c0456485a7d196a"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd9a187742d3ead9df2e49240234d728c67c356516cf4db018833a86f20ec18c"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:77b0fed6f209d76c1c39f032a70df2d7acf24b1812ca3e6078fd04e8972685a3"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:63fc9d5fe1d4e8868f6aae547a7b8ba0a2e592929245fff61d633f4caccdcdd6"}, - {file = "orjson-3.10.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65cd3e3bb4fbb4eddc3c1e8dce10dc0b73e808fcb875f9fab40c81903dd9323e"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6f67c570602300c4befbda12d153113b8974a3340fdcf3d6de095ede86c06d92"}, - {file = "orjson-3.10.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:1f39728c7f7d766f1f5a769ce4d54b5aaa4c3f92d5b84817053cc9995b977acc"}, - {file = "orjson-3.10.11-cp310-none-win32.whl", hash = "sha256:1789d9db7968d805f3d94aae2c25d04014aae3a2fa65b1443117cd462c6da647"}, - {file = "orjson-3.10.11-cp310-none-win_amd64.whl", hash = "sha256:5576b1e5a53a5ba8f8df81872bb0878a112b3ebb1d392155f00f54dd86c83ff6"}, - {file = "orjson-3.10.11-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1444f9cb7c14055d595de1036f74ecd6ce15f04a715e73f33bb6326c9cef01b6"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdec57fe3b4bdebcc08a946db3365630332dbe575125ff3d80a3272ebd0ddafe"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4eed32f33a0ea6ef36ccc1d37f8d17f28a1d6e8eefae5928f76aff8f1df85e67"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:80df27dd8697242b904f4ea54820e2d98d3f51f91e97e358fc13359721233e4b"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:705f03cee0cb797256d54de6695ef219e5bc8c8120b6654dd460848d57a9af3d"}, - {file = "orjson-3.10.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03246774131701de8e7059b2e382597da43144a9a7400f178b2a32feafc54bd5"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8b5759063a6c940a69c728ea70d7c33583991c6982915a839c8da5f957e0103a"}, - {file = "orjson-3.10.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:677f23e32491520eebb19c99bb34675daf5410c449c13416f7f0d93e2cf5f981"}, - {file = "orjson-3.10.11-cp311-none-win32.whl", hash = "sha256:a11225d7b30468dcb099498296ffac36b4673a8398ca30fdaec1e6c20df6aa55"}, - {file = "orjson-3.10.11-cp311-none-win_amd64.whl", hash = "sha256:df8c677df2f9f385fcc85ab859704045fa88d4668bc9991a527c86e710392bec"}, - {file = "orjson-3.10.11-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:360a4e2c0943da7c21505e47cf6bd725588962ff1d739b99b14e2f7f3545ba51"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:496e2cb45de21c369079ef2d662670a4892c81573bcc143c4205cae98282ba97"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7dfa8db55c9792d53c5952900c6a919cfa377b4f4534c7a786484a6a4a350c19"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:51f3382415747e0dbda9dade6f1e1a01a9d37f630d8c9049a8ed0e385b7a90c0"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f35a1b9f50a219f470e0e497ca30b285c9f34948d3c8160d5ad3a755d9299433"}, - {file = "orjson-3.10.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e2f3b7c5803138e67028dde33450e054c87e0703afbe730c105f1fcd873496d5"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f91d9eb554310472bd09f5347950b24442600594c2edc1421403d7610a0998fd"}, - {file = "orjson-3.10.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dfbb2d460a855c9744bbc8e36f9c3a997c4b27d842f3d5559ed54326e6911f9b"}, - {file = "orjson-3.10.11-cp312-none-win32.whl", hash = "sha256:d4a62c49c506d4d73f59514986cadebb7e8d186ad510c518f439176cf8d5359d"}, - {file = "orjson-3.10.11-cp312-none-win_amd64.whl", hash = "sha256:f1eec3421a558ff7a9b010a6c7effcfa0ade65327a71bb9b02a1c3b77a247284"}, - {file = "orjson-3.10.11-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c46294faa4e4d0eb73ab68f1a794d2cbf7bab33b1dda2ac2959ffb7c61591899"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:52e5834d7d6e58a36846e059d00559cb9ed20410664f3ad156cd2cc239a11230"}, - {file = "orjson-3.10.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2fc947e5350fdce548bfc94f434e8760d5cafa97fb9c495d2fef6757aa02ec0"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0efabbf839388a1dab5b72b5d3baedbd6039ac83f3b55736eb9934ea5494d258"}, - {file = "orjson-3.10.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a3f29634260708c200c4fe148e42b4aae97d7b9fee417fbdd74f8cfc265f15b0"}, - {file = "orjson-3.10.11-cp313-none-win32.whl", hash = "sha256:1a1222ffcee8a09476bbdd5d4f6f33d06d0d6642df2a3d78b7a195ca880d669b"}, - {file = "orjson-3.10.11-cp313-none-win_amd64.whl", hash = "sha256:bc274ac261cc69260913b2d1610760e55d3c0801bb3457ba7b9004420b6b4270"}, - {file = "orjson-3.10.11-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:19b3763e8bbf8ad797df6b6b5e0fc7c843ec2e2fc0621398534e0c6400098f87"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1be83a13312e5e58d633580c5eb8d0495ae61f180da2722f20562974188af205"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:afacfd1ab81f46dedd7f6001b6d4e8de23396e4884cd3c3436bd05defb1a6446"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb4d0bea56bba596723d73f074c420aec3b2e5d7d30698bc56e6048066bd560c"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96ed1de70fcb15d5fed529a656df29f768187628727ee2788344e8a51e1c1350"}, - {file = "orjson-3.10.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4bfb30c891b530f3f80e801e3ad82ef150b964e5c38e1fb8482441c69c35c61c"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:d496c74fc2b61341e3cefda7eec21b7854c5f672ee350bc55d9a4997a8a95204"}, - {file = "orjson-3.10.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:655a493bac606655db9a47fe94d3d84fc7f3ad766d894197c94ccf0c5408e7d3"}, - {file = "orjson-3.10.11-cp38-none-win32.whl", hash = "sha256:b9546b278c9fb5d45380f4809e11b4dd9844ca7aaf1134024503e134ed226161"}, - {file = "orjson-3.10.11-cp38-none-win_amd64.whl", hash = "sha256:b592597fe551d518f42c5a2eb07422eb475aa8cfdc8c51e6da7054b836b26782"}, - {file = "orjson-3.10.11-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:c95f2ecafe709b4e5c733b5e2768ac569bed308623c85806c395d9cca00e08af"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:80c00d4acded0c51c98754fe8218cb49cb854f0f7eb39ea4641b7f71732d2cb7"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:461311b693d3d0a060439aa669c74f3603264d4e7a08faa68c47ae5a863f352d"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52ca832f17d86a78cbab86cdc25f8c13756ebe182b6fc1a97d534051c18a08de"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c57ea78a753812f528178aa2f1c57da633754c91d2124cb28991dab4c79a54"}, - {file = "orjson-3.10.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7fcfc6f7ca046383fb954ba528587e0f9336828b568282b27579c49f8e16aad"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:86b9dd983857970c29e4c71bb3e95ff085c07d3e83e7c46ebe959bac07ebd80b"}, - {file = "orjson-3.10.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:4d83f87582d223e54efb2242a79547611ba4ebae3af8bae1e80fa9a0af83bb7f"}, - {file = "orjson-3.10.11-cp39-none-win32.whl", hash = "sha256:9fd0ad1c129bc9beb1154c2655f177620b5beaf9a11e0d10bac63ef3fce96950"}, - {file = "orjson-3.10.11-cp39-none-win_amd64.whl", hash = "sha256:10f416b2a017c8bd17f325fb9dee1fb5cdd7a54e814284896b7c3f2763faa017"}, - {file = "orjson-3.10.11.tar.gz", hash = "sha256:e35b6d730de6384d5b2dab5fd23f0d76fae8bbc8c353c2f78210aa5fa4beb3ef"}, + {file = "orjson-3.10.12-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ece01a7ec71d9940cc654c482907a6b65df27251255097629d0dea781f255c6d"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c34ec9aebc04f11f4b978dd6caf697a2df2dd9b47d35aa4cc606cabcb9df69d7"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fd6ec8658da3480939c79b9e9e27e0db31dffcd4ba69c334e98c9976ac29140e"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f17e6baf4cf01534c9de8a16c0c611f3d94925d1701bf5f4aff17003677d8ced"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6402ebb74a14ef96f94a868569f5dccf70d791de49feb73180eb3c6fda2ade56"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0000758ae7c7853e0a4a6063f534c61656ebff644391e1f81698c1b2d2fc8cd2"}, + {file = "orjson-3.10.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:888442dcee99fd1e5bd37a4abb94930915ca6af4db50e23e746cdf4d1e63db13"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c1f7a3ce79246aa0e92f5458d86c54f257fb5dfdc14a192651ba7ec2c00f8a05"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:802a3935f45605c66fb4a586488a38af63cb37aaad1c1d94c982c40dcc452e85"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:1da1ef0113a2be19bb6c557fb0ec2d79c92ebd2fed4cfb1b26bab93f021fb885"}, + {file = "orjson-3.10.12-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a3273e99f367f137d5b3fecb5e9f45bcdbfac2a8b2f32fbc72129bbd48789c2"}, + {file = "orjson-3.10.12-cp310-none-win32.whl", hash = "sha256:475661bf249fd7907d9b0a2a2421b4e684355a77ceef85b8352439a9163418c3"}, + {file = "orjson-3.10.12-cp310-none-win_amd64.whl", hash = "sha256:87251dc1fb2b9e5ab91ce65d8f4caf21910d99ba8fb24b49fd0c118b2362d509"}, + {file = "orjson-3.10.12-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a734c62efa42e7df94926d70fe7d37621c783dea9f707a98cdea796964d4cf74"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:750f8b27259d3409eda8350c2919a58b0cfcd2054ddc1bd317a643afc646ef23"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb52c22bfffe2857e7aa13b4622afd0dd9d16ea7cc65fd2bf318d3223b1b6252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:440d9a337ac8c199ff8251e100c62e9488924c92852362cd27af0e67308c16ef"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9e15c06491c69997dfa067369baab3bf094ecb74be9912bdc4339972323f252"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:362d204ad4b0b8724cf370d0cd917bb2dc913c394030da748a3bb632445ce7c4"}, + {file = "orjson-3.10.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2b57cbb4031153db37b41622eac67329c7810e5f480fda4cfd30542186f006ae"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:165c89b53ef03ce0d7c59ca5c82fa65fe13ddf52eeb22e859e58c237d4e33b9b"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:5dee91b8dfd54557c1a1596eb90bcd47dbcd26b0baaed919e6861f076583e9da"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:77a4e1cfb72de6f905bdff061172adfb3caf7a4578ebf481d8f0530879476c07"}, + {file = "orjson-3.10.12-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:038d42c7bc0606443459b8fe2d1f121db474c49067d8d14c6a075bbea8bf14dd"}, + {file = "orjson-3.10.12-cp311-none-win32.whl", hash = "sha256:03b553c02ab39bed249bedd4abe37b2118324d1674e639b33fab3d1dafdf4d79"}, + {file = "orjson-3.10.12-cp311-none-win_amd64.whl", hash = "sha256:8b8713b9e46a45b2af6b96f559bfb13b1e02006f4242c156cbadef27800a55a8"}, + {file = "orjson-3.10.12-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:53206d72eb656ca5ac7d3a7141e83c5bbd3ac30d5eccfe019409177a57634b0d"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac8010afc2150d417ebda810e8df08dd3f544e0dd2acab5370cfa6bcc0662f8f"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed459b46012ae950dd2e17150e838ab08215421487371fa79d0eced8d1461d70"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8dcb9673f108a93c1b52bfc51b0af422c2d08d4fc710ce9c839faad25020bb69"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:22a51ae77680c5c4652ebc63a83d5255ac7d65582891d9424b566fb3b5375ee9"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:910fdf2ac0637b9a77d1aad65f803bac414f0b06f720073438a7bd8906298192"}, + {file = "orjson-3.10.12-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:24ce85f7100160936bc2116c09d1a8492639418633119a2224114f67f63a4559"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8a76ba5fc8dd9c913640292df27bff80a685bed3a3c990d59aa6ce24c352f8fc"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ff70ef093895fd53f4055ca75f93f047e088d1430888ca1229393a7c0521100f"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f4244b7018b5753ecd10a6d324ec1f347da130c953a9c88432c7fbc8875d13be"}, + {file = "orjson-3.10.12-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:16135ccca03445f37921fa4b585cff9a58aa8d81ebcb27622e69bfadd220b32c"}, + {file = "orjson-3.10.12-cp312-none-win32.whl", hash = "sha256:2d879c81172d583e34153d524fcba5d4adafbab8349a7b9f16ae511c2cee8708"}, + {file = "orjson-3.10.12-cp312-none-win_amd64.whl", hash = "sha256:fc23f691fa0f5c140576b8c365bc942d577d861a9ee1142e4db468e4e17094fb"}, + {file = "orjson-3.10.12-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:47962841b2a8aa9a258b377f5188db31ba49af47d4003a32f55d6f8b19006543"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6334730e2532e77b6054e87ca84f3072bee308a45a452ea0bffbbbc40a67e296"}, + {file = "orjson-3.10.12-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:accfe93f42713c899fdac2747e8d0d5c659592df2792888c6c5f829472e4f85e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a7974c490c014c48810d1dede6c754c3cc46598da758c25ca3b4001ac45b703f"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:3f250ce7727b0b2682f834a3facff88e310f52f07a5dcfd852d99637d386e79e"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f31422ff9486ae484f10ffc51b5ab2a60359e92d0716fcce1b3593d7bb8a9af6"}, + {file = "orjson-3.10.12-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5f29c5d282bb2d577c2a6bbde88d8fdcc4919c593f806aac50133f01b733846e"}, + {file = "orjson-3.10.12-cp313-none-win32.whl", hash = "sha256:f45653775f38f63dc0e6cd4f14323984c3149c05d6007b58cb154dd080ddc0dc"}, + {file = "orjson-3.10.12-cp313-none-win_amd64.whl", hash = "sha256:229994d0c376d5bdc91d92b3c9e6be2f1fbabd4cc1b59daae1443a46ee5e9825"}, + {file = "orjson-3.10.12-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7d69af5b54617a5fac5c8e5ed0859eb798e2ce8913262eb522590239db6c6763"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ed119ea7d2953365724a7059231a44830eb6bbb0cfead33fcbc562f5fd8f935"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:9c5fc1238ef197e7cad5c91415f524aaa51e004be5a9b35a1b8a84ade196f73f"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:43509843990439b05f848539d6f6198d4ac86ff01dd024b2f9a795c0daeeab60"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f72e27a62041cfb37a3de512247ece9f240a561e6c8662276beaf4d53d406db4"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a904f9572092bb6742ab7c16c623f0cdccbad9eeb2d14d4aa06284867bddd31"}, + {file = "orjson-3.10.12-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:855c0833999ed5dc62f64552db26f9be767434917d8348d77bacaab84f787d7b"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:897830244e2320f6184699f598df7fb9db9f5087d6f3f03666ae89d607e4f8ed"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_armv7l.whl", hash = "sha256:0b32652eaa4a7539f6f04abc6243619c56f8530c53bf9b023e1269df5f7816dd"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:36b4aa31e0f6a1aeeb6f8377769ca5d125db000f05c20e54163aef1d3fe8e833"}, + {file = "orjson-3.10.12-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:5535163054d6cbf2796f93e4f0dbc800f61914c0e3c4ed8499cf6ece22b4a3da"}, + {file = "orjson-3.10.12-cp38-none-win32.whl", hash = "sha256:90a5551f6f5a5fa07010bf3d0b4ca2de21adafbbc0af6cb700b63cd767266cb9"}, + {file = "orjson-3.10.12-cp38-none-win_amd64.whl", hash = "sha256:703a2fb35a06cdd45adf5d733cf613cbc0cb3ae57643472b16bc22d325b5fb6c"}, + {file = "orjson-3.10.12-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:f29de3ef71a42a5822765def1febfb36e0859d33abf5c2ad240acad5c6a1b78d"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de365a42acc65d74953f05e4772c974dad6c51cfc13c3240899f534d611be967"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:91a5a0158648a67ff0004cb0df5df7dcc55bfc9ca154d9c01597a23ad54c8d0c"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c47ce6b8d90fe9646a25b6fb52284a14ff215c9595914af63a5933a49972ce36"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0eee4c2c5bfb5c1b47a5db80d2ac7aaa7e938956ae88089f098aff2c0f35d5d8"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35d3081bbe8b86587eb5c98a73b97f13d8f9fea685cf91a579beddacc0d10566"}, + {file = "orjson-3.10.12-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:73c23a6e90383884068bc2dba83d5222c9fcc3b99a0ed2411d38150734236755"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5472be7dc3269b4b52acba1433dac239215366f89dc1d8d0e64029abac4e714e"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:7319cda750fca96ae5973efb31b17d97a5c5225ae0bc79bf5bf84df9e1ec2ab6"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:74d5ca5a255bf20b8def6a2b96b1e18ad37b4a122d59b154c458ee9494377f80"}, + {file = "orjson-3.10.12-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ff31d22ecc5fb85ef62c7d4afe8301d10c558d00dd24274d4bbe464380d3cd69"}, + {file = "orjson-3.10.12-cp39-none-win32.whl", hash = "sha256:c22c3ea6fba91d84fcb4cda30e64aff548fcf0c44c876e681f47d61d24b12e6b"}, + {file = "orjson-3.10.12-cp39-none-win_amd64.whl", hash = "sha256:be604f60d45ace6b0b33dd990a66b4526f1a7a186ac411c942674625456ca548"}, + {file = "orjson-3.10.12.tar.gz", hash = "sha256:0a78bbda3aea0f9f079057ee1ee8a1ecf790d4f1af88dd67493c6b8ee52506ff"}, ] [[package]] @@ -557,18 +640,18 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "pydantic" -version = "2.10.0" +version = "2.10.3" description = "Data validation using Python type hints" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic-2.10.0-py3-none-any.whl", hash = "sha256:5e7807ba9201bdf61b1b58aa6eb690916c40a47acfb114b1b4fef3e7fd5b30fc"}, - {file = "pydantic-2.10.0.tar.gz", hash = "sha256:0aca0f045ff6e2f097f1fe89521115335f15049eeb8a7bef3dafe4b19a74e289"}, + {file = "pydantic-2.10.3-py3-none-any.whl", hash = "sha256:be04d85bbc7b65651c5f8e6b9976ed9c6f41782a55524cef079a34a0bb82144d"}, + {file = "pydantic-2.10.3.tar.gz", hash = "sha256:cb5ac360ce894ceacd69c403187900a02c4b20b693a9dd1d643e1effab9eadf9"}, ] [package.dependencies] annotated-types = ">=0.6.0" -pydantic-core = "2.27.0" +pydantic-core = "2.27.1" typing-extensions = ">=4.12.2" [package.extras] @@ -577,111 +660,111 @@ timezone = ["tzdata"] [[package]] name = "pydantic-core" -version = "2.27.0" +version = "2.27.1" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_core-2.27.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:cd2ac6b919f7fed71b17fe0b4603c092a4c9b5bae414817c9c81d3c22d1e1bcc"}, - {file = "pydantic_core-2.27.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e015833384ca3e1a0565a79f5d953b0629d9138021c27ad37c92a9fa1af7623c"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:db72e40628967f6dc572020d04b5f800d71264e0531c6da35097e73bdf38b003"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:df45c4073bed486ea2f18757057953afed8dd77add7276ff01bccb79982cf46c"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:836a4bfe0cc6d36dc9a9cc1a7b391265bf6ce9d1eb1eac62ac5139f5d8d9a6fa"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4bf1340ae507f6da6360b24179c2083857c8ca7644aab65807023cf35404ea8d"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ab325fc86fbc077284c8d7f996d904d30e97904a87d6fb303dce6b3de7ebba9"}, - {file = "pydantic_core-2.27.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1da0c98a85a6c6ed702d5556db3b09c91f9b0b78de37b7593e2de8d03238807a"}, - {file = "pydantic_core-2.27.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:7b0202ebf2268954090209a84f9897345719e46a57c5f2c9b7b250ca0a9d3e63"}, - {file = "pydantic_core-2.27.0-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:35380671c3c921fe8adf31ad349dc6f7588b7e928dbe44e1093789734f607399"}, - {file = "pydantic_core-2.27.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6b4c19525c3538fbc0bbda6229f9682fb8199ce9ac37395880e6952798e00373"}, - {file = "pydantic_core-2.27.0-cp310-none-win32.whl", hash = "sha256:333c840a1303d1474f491e7be0b718226c730a39ead0f7dab2c7e6a2f3855555"}, - {file = "pydantic_core-2.27.0-cp310-none-win_amd64.whl", hash = "sha256:99b2863c1365f43f74199c980a3d40f18a218fbe683dd64e470199db426c4d6a"}, - {file = "pydantic_core-2.27.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4523c4009c3f39d948e01962223c9f5538602e7087a628479b723c939fab262d"}, - {file = "pydantic_core-2.27.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:84af1cf7bfdcbc6fcf5a5f70cc9896205e0350306e4dd73d54b6a18894f79386"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e65466b31be1070b4a5b7dbfbd14b247884cb8e8b79c64fb0f36b472912dbaea"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a5c022bb0d453192426221605efc865373dde43b17822a264671c53b068ac20c"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6bb69bf3b6500f195c3deb69c1205ba8fc3cb21d1915f1f158a10d6b1ef29b6a"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0aa4d1b2eba9a325897308b3124014a142cdccb9f3e016f31d3ebee6b5ea5e75"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8e96ca781e0c01e32115912ebdf7b3fb0780ce748b80d7d28a0802fa9fbaf44e"}, - {file = "pydantic_core-2.27.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b872c86d8d71827235c7077461c502feb2db3f87d9d6d5a9daa64287d75e4fa0"}, - {file = "pydantic_core-2.27.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:82e1ad4ca170e8af4c928b67cff731b6296e6a0a0981b97b2eb7c275cc4e15bd"}, - {file = "pydantic_core-2.27.0-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:eb40f828bc2f73f777d1eb8fee2e86cd9692a4518b63b6b5aa8af915dfd3207b"}, - {file = "pydantic_core-2.27.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:9a8fbf506fde1529a1e3698198fe64bfbe2e0c09557bc6a7dcf872e7c01fec40"}, - {file = "pydantic_core-2.27.0-cp311-none-win32.whl", hash = "sha256:24f984fc7762ed5f806d9e8c4c77ea69fdb2afd987b4fd319ef06c87595a8c55"}, - {file = "pydantic_core-2.27.0-cp311-none-win_amd64.whl", hash = "sha256:68950bc08f9735306322bfc16a18391fcaac99ded2509e1cc41d03ccb6013cfe"}, - {file = "pydantic_core-2.27.0-cp311-none-win_arm64.whl", hash = "sha256:3eb8849445c26b41c5a474061032c53e14fe92a11a5db969f722a2716cd12206"}, - {file = "pydantic_core-2.27.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:8117839a9bdbba86e7f9df57018fe3b96cec934c3940b591b0fd3fbfb485864a"}, - {file = "pydantic_core-2.27.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a291d0b4243a259c8ea7e2b84eb9ccb76370e569298875a7c5e3e71baf49057a"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:84e35afd9e10b2698e6f2f32256678cb23ca6c1568d02628033a837638b3ed12"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:58ab0d979c969983cdb97374698d847a4acffb217d543e172838864636ef10d9"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0d06b667e53320332be2bf6f9461f4a9b78092a079b8ce8634c9afaa7e10cd9f"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:78f841523729e43e3928a364ec46e2e3f80e6625a4f62aca5c345f3f626c6e8a"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:400bf470e4327e920883b51e255617dfe4496d4e80c3fea0b5a5d0bf2c404dd4"}, - {file = "pydantic_core-2.27.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:951e71da6c89d354572098bada5ba5b5dc3a9390c933af8a614e37755d3d1840"}, - {file = "pydantic_core-2.27.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:2a51ce96224eadd1845150b204389623c8e129fde5a67a84b972bd83a85c6c40"}, - {file = "pydantic_core-2.27.0-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:483c2213a609e7db2c592bbc015da58b6c75af7360ca3c981f178110d9787bcf"}, - {file = "pydantic_core-2.27.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:359e7951f04ad35111b5ddce184db3391442345d0ab073aa63a95eb8af25a5ef"}, - {file = "pydantic_core-2.27.0-cp312-none-win32.whl", hash = "sha256:ee7d9d5537daf6d5c74a83b38a638cc001b648096c1cae8ef695b0c919d9d379"}, - {file = "pydantic_core-2.27.0-cp312-none-win_amd64.whl", hash = "sha256:2be0ad541bb9f059954ccf8877a49ed73877f862529575ff3d54bf4223e4dd61"}, - {file = "pydantic_core-2.27.0-cp312-none-win_arm64.whl", hash = "sha256:6e19401742ed7b69e51d8e4df3c03ad5ec65a83b36244479fd70edde2828a5d9"}, - {file = "pydantic_core-2.27.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:5f2b19b8d6fca432cb3acf48cf5243a7bf512988029b6e6fd27e9e8c0a204d85"}, - {file = "pydantic_core-2.27.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:c86679f443e7085ea55a7376462553996c688395d18ef3f0d3dbad7838f857a2"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:510b11e9c3b1a852876d1ccd8d5903684336d635214148637ceb27366c75a467"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eb704155e73b833801c247f39d562229c0303f54770ca14fb1c053acb376cf10"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9ce048deb1e033e7a865ca384770bccc11d44179cf09e5193a535c4c2f497bdc"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:58560828ee0951bb125c6f2862fbc37f039996d19ceb6d8ff1905abf7da0bf3d"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:abb4785894936d7682635726613c44578c420a096729f1978cd061a7e72d5275"}, - {file = "pydantic_core-2.27.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2883b260f7a93235488699d39cbbd94fa7b175d3a8063fbfddd3e81ad9988cb2"}, - {file = "pydantic_core-2.27.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:c6fcb3fa3855d583aa57b94cf146f7781d5d5bc06cb95cb3afece33d31aac39b"}, - {file = "pydantic_core-2.27.0-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:e851a051f7260e6d688267eb039c81f05f23a19431bd7dfa4bf5e3cb34c108cd"}, - {file = "pydantic_core-2.27.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:edb1bfd45227dec8d50bc7c7d86463cd8728bcc574f9b07de7369880de4626a3"}, - {file = "pydantic_core-2.27.0-cp313-none-win32.whl", hash = "sha256:678f66462058dd978702db17eb6a3633d634f7aa0deaea61e0a674152766d3fc"}, - {file = "pydantic_core-2.27.0-cp313-none-win_amd64.whl", hash = "sha256:d28ca7066d6cdd347a50d8b725dc10d9a1d6a1cce09836cf071ea6a2d4908be0"}, - {file = "pydantic_core-2.27.0-cp313-none-win_arm64.whl", hash = "sha256:6f4a53af9e81d757756508b57cae1cf28293f0f31b9fa2bfcb416cc7fb230f9d"}, - {file = "pydantic_core-2.27.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:e9f9feee7f334b72ceae46313333d002b56f325b5f04271b4ae2aadd9e993ae4"}, - {file = "pydantic_core-2.27.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:225bfff5d425c34e1fd562cef52d673579d59b967d9de06178850c4802af9039"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c921ad596ff1a82f9c692b0758c944355abc9f0de97a4c13ca60ffc6d8dc15d4"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6354e18a9be37bfa124d6b288a87fb30c673745806c92956f1a25e3ae6e76b96"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8ee4c2a75af9fe21269a4a0898c5425afb01af1f5d276063f57e2ae1bc64e191"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c91e3c04f5191fd3fb68764bddeaf02025492d5d9f23343b283870f6ace69708"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7a6ebfac28fd51890a61df36ef202adbd77d00ee5aca4a3dadb3d9ed49cfb929"}, - {file = "pydantic_core-2.27.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:36aa167f69d8807ba7e341d67ea93e50fcaaf6bc433bb04939430fa3dab06f31"}, - {file = "pydantic_core-2.27.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:3e8d89c276234579cd3d095d5fa2a44eb10db9a218664a17b56363cddf226ff3"}, - {file = "pydantic_core-2.27.0-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:5cc822ab90a70ea3a91e6aed3afac570b276b1278c6909b1d384f745bd09c714"}, - {file = "pydantic_core-2.27.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:e15315691fe2253eb447503153acef4d7223dfe7e7702f9ed66539fcd0c43801"}, - {file = "pydantic_core-2.27.0-cp38-none-win32.whl", hash = "sha256:dfa5f5c0a4c8fced1422dc2ca7eefd872d5d13eb33cf324361dbf1dbfba0a9fe"}, - {file = "pydantic_core-2.27.0-cp38-none-win_amd64.whl", hash = "sha256:513cb14c0cc31a4dfd849a4674b20c46d87b364f997bbcb02282306f5e187abf"}, - {file = "pydantic_core-2.27.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:4148dc9184ab79e356dc00a4199dc0ee8647973332cb385fc29a7cced49b9f9c"}, - {file = "pydantic_core-2.27.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5fc72fbfebbf42c0856a824b8b0dc2b5cd2e4a896050281a21cfa6fed8879cb1"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:185ef205256cd8b38431205698531026979db89a79587725c1e55c59101d64e9"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:395e3e1148fa7809016231f8065f30bb0dc285a97b4dc4360cd86e17bab58af7"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:33d14369739c5d07e2e7102cdb0081a1fa46ed03215e07f097b34e020b83b1ae"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e7820bb0d65e3ce1e3e70b6708c2f66143f55912fa02f4b618d0f08b61575f12"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:43b61989068de9ce62296cde02beffabcadb65672207fc51e7af76dca75e6636"}, - {file = "pydantic_core-2.27.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:15e350efb67b855cd014c218716feea4986a149ed1f42a539edd271ee074a196"}, - {file = "pydantic_core-2.27.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:433689845288f9a1ee5714444e65957be26d30915f7745091ede4a83cfb2d7bb"}, - {file = "pydantic_core-2.27.0-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:3fd8bc2690e7c39eecdf9071b6a889ce7b22b72073863940edc2a0a23750ca90"}, - {file = "pydantic_core-2.27.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:884f1806609c2c66564082540cffc96868c5571c7c3cf3a783f63f2fb49bd3cd"}, - {file = "pydantic_core-2.27.0-cp39-none-win32.whl", hash = "sha256:bf37b72834e7239cf84d4a0b2c050e7f9e48bced97bad9bdf98d26b8eb72e846"}, - {file = "pydantic_core-2.27.0-cp39-none-win_amd64.whl", hash = "sha256:31a2cae5f059329f9cfe3d8d266d3da1543b60b60130d186d9b6a3c20a346361"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:4fb49cfdb53af5041aba909be00cccfb2c0d0a2e09281bf542371c5fd36ad04c"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:49633583eb7dc5cba61aaf7cdb2e9e662323ad394e543ee77af265736bcd3eaa"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:153017e3d6cd3ce979de06d84343ca424bb6092727375eba1968c8b4693c6ecb"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ff63a92f6e249514ef35bc795de10745be0226eaea06eb48b4bbeaa0c8850a4a"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5982048129f40b082c2654de10c0f37c67a14f5ff9d37cf35be028ae982f26df"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:91bc66f878557313c2a6bcf396e7befcffe5ab4354cfe4427318968af31143c3"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:68ef5377eb582fa4343c9d0b57a5b094046d447b4c73dd9fbd9ffb216f829e7d"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:c5726eec789ee38f2c53b10b1821457b82274f81f4f746bb1e666d8741fcfadb"}, - {file = "pydantic_core-2.27.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:c0c431e4be5c1a0c6654e0c31c661cd89e0ca956ef65305c3c3fd96f4e72ca39"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:8e21d927469d04b39386255bf00d0feedead16f6253dcc85e9e10ddebc334084"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:4b51f964fcbb02949fc546022e56cdb16cda457af485e9a3e8b78ac2ecf5d77e"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25a7fd4de38f7ff99a37e18fa0098c3140286451bc823d1746ba80cec5b433a1"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6fda87808429c520a002a85d6e7cdadbf58231d60e96260976c5b8f9a12a8e13"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8a150392102c402c538190730fda06f3bce654fc498865579a9f2c1d2b425833"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:c9ed88b398ba7e3bad7bd64d66cc01dcde9cfcb7ec629a6fd78a82fa0b559d78"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:9fe94d9d2a2b4edd7a4b22adcd45814b1b59b03feb00e56deb2e89747aec7bfe"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:d8b5ee4ae9170e2775d495b81f414cc20268041c42571530513496ba61e94ba3"}, - {file = "pydantic_core-2.27.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:d29e235ce13c91902ef3efc3d883a677655b3908b1cbc73dee816e5e1f8f7739"}, - {file = "pydantic_core-2.27.0.tar.gz", hash = "sha256:f57783fbaf648205ac50ae7d646f27582fc706be3977e87c3c124e7a92407b10"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"}, + {file = "pydantic_core-2.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f82d068a2d6ecfc6e054726080af69a6764a10015467d7d7b9f66d6ed5afa23b"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:121ceb0e822f79163dd4699e4c54f5ad38b157084d97b34de8b232bcaad70278"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4603137322c18eaf2e06a4495f426aa8d8388940f3c457e7548145011bb68e05"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a33cd6ad9017bbeaa9ed78a2e0752c5e250eafb9534f308e7a5f7849b0b1bfb4"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:15cc53a3179ba0fcefe1e3ae50beb2784dede4003ad2dfd24f81bba4b23a454f"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:45d9c5eb9273aa50999ad6adc6be5e0ecea7e09dbd0d31bd0c65a55a2592ca08"}, + {file = "pydantic_core-2.27.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8bf7b66ce12a2ac52d16f776b31d16d91033150266eb796967a7e4621707e4f6"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:655d7dd86f26cb15ce8a431036f66ce0318648f8853d709b4167786ec2fa4807"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:5556470f1a2157031e676f776c2bc20acd34c1990ca5f7e56f1ebf938b9ab57c"}, + {file = "pydantic_core-2.27.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f69ed81ab24d5a3bd93861c8c4436f54afdf8e8cc421562b0c7504cf3be58206"}, + {file = "pydantic_core-2.27.1-cp310-none-win32.whl", hash = "sha256:f5a823165e6d04ccea61a9f0576f345f8ce40ed533013580e087bd4d7442b52c"}, + {file = "pydantic_core-2.27.1-cp310-none-win_amd64.whl", hash = "sha256:57866a76e0b3823e0b56692d1a0bf722bffb324839bb5b7226a7dbd6c9a40b17"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac3b20653bdbe160febbea8aa6c079d3df19310d50ac314911ed8cc4eb7f8cb8"}, + {file = "pydantic_core-2.27.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a5a8e19d7c707c4cadb8c18f5f60c843052ae83c20fa7d44f41594c644a1d330"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f7059ca8d64fea7f238994c97d91f75965216bcbe5f695bb44f354893f11d52"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bed0f8a0eeea9fb72937ba118f9db0cb7e90773462af7962d382445f3005e5a4"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a3cb37038123447cf0f3ea4c74751f6a9d7afef0eb71aa07bf5f652b5e6a132c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84286494f6c5d05243456e04223d5a9417d7f443c3b76065e75001beb26f88de"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:acc07b2cfc5b835444b44a9956846b578d27beeacd4b52e45489e93276241025"}, + {file = "pydantic_core-2.27.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4fefee876e07a6e9aad7a8c8c9f85b0cdbe7df52b8a9552307b09050f7512c7e"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:258c57abf1188926c774a4c94dd29237e77eda19462e5bb901d88adcab6af919"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:35c14ac45fcfdf7167ca76cc80b2001205a8d5d16d80524e13508371fb8cdd9c"}, + {file = "pydantic_core-2.27.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d1b26e1dff225c31897696cab7d4f0a315d4c0d9e8666dbffdb28216f3b17fdc"}, + {file = "pydantic_core-2.27.1-cp311-none-win32.whl", hash = "sha256:2cdf7d86886bc6982354862204ae3b2f7f96f21a3eb0ba5ca0ac42c7b38598b9"}, + {file = "pydantic_core-2.27.1-cp311-none-win_amd64.whl", hash = "sha256:3af385b0cee8df3746c3f406f38bcbfdc9041b5c2d5ce3e5fc6637256e60bbc5"}, + {file = "pydantic_core-2.27.1-cp311-none-win_arm64.whl", hash = "sha256:81f2ec23ddc1b476ff96563f2e8d723830b06dceae348ce02914a37cb4e74b89"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9cbd94fc661d2bab2bc702cddd2d3370bbdcc4cd0f8f57488a81bcce90c7a54f"}, + {file = "pydantic_core-2.27.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5f8c4718cd44ec1580e180cb739713ecda2bdee1341084c1467802a417fe0f02"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:15aae984e46de8d376df515f00450d1522077254ef6b7ce189b38ecee7c9677c"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1ba5e3963344ff25fc8c40da90f44b0afca8cfd89d12964feb79ac1411a260ac"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:992cea5f4f3b29d6b4f7f1726ed8ee46c8331c6b4eed6db5b40134c6fe1768bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0325336f348dbee6550d129b1627cb8f5351a9dc91aad141ffb96d4937bd9529"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7597c07fbd11515f654d6ece3d0e4e5093edc30a436c63142d9a4b8e22f19c35"}, + {file = "pydantic_core-2.27.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3bbd5d8cc692616d5ef6fbbbd50dbec142c7e6ad9beb66b78a96e9c16729b089"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:dc61505e73298a84a2f317255fcc72b710b72980f3a1f670447a21efc88f8381"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:e1f735dc43da318cad19b4173dd1ffce1d84aafd6c9b782b3abc04a0d5a6f5bb"}, + {file = "pydantic_core-2.27.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f4e5658dbffe8843a0f12366a4c2d1c316dbe09bb4dfbdc9d2d9cd6031de8aae"}, + {file = "pydantic_core-2.27.1-cp312-none-win32.whl", hash = "sha256:672ebbe820bb37988c4d136eca2652ee114992d5d41c7e4858cdd90ea94ffe5c"}, + {file = "pydantic_core-2.27.1-cp312-none-win_amd64.whl", hash = "sha256:66ff044fd0bb1768688aecbe28b6190f6e799349221fb0de0e6f4048eca14c16"}, + {file = "pydantic_core-2.27.1-cp312-none-win_arm64.whl", hash = "sha256:9a3b0793b1bbfd4146304e23d90045f2a9b5fd5823aa682665fbdaf2a6c28f3e"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f216dbce0e60e4d03e0c4353c7023b202d95cbaeff12e5fd2e82ea0a66905073"}, + {file = "pydantic_core-2.27.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a2e02889071850bbfd36b56fd6bc98945e23670773bc7a76657e90e6b6603c08"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42b0e23f119b2b456d07ca91b307ae167cc3f6c846a7b169fca5326e32fdc6cf"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:764be71193f87d460a03f1f7385a82e226639732214b402f9aa61f0d025f0737"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1c00666a3bd2f84920a4e94434f5974d7bbc57e461318d6bb34ce9cdbbc1f6b2"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3ccaa88b24eebc0f849ce0a4d09e8a408ec5a94afff395eb69baf868f5183107"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c65af9088ac534313e1963443d0ec360bb2b9cba6c2909478d22c2e363d98a51"}, + {file = "pydantic_core-2.27.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:206b5cf6f0c513baffaeae7bd817717140770c74528f3e4c3e1cec7871ddd61a"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:062f60e512fc7fff8b8a9d680ff0ddaaef0193dba9fa83e679c0c5f5fbd018bc"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:a0697803ed7d4af5e4c1adf1670af078f8fcab7a86350e969f454daf598c4960"}, + {file = "pydantic_core-2.27.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:58ca98a950171f3151c603aeea9303ef6c235f692fe555e883591103da709b23"}, + {file = "pydantic_core-2.27.1-cp313-none-win32.whl", hash = "sha256:8065914ff79f7eab1599bd80406681f0ad08f8e47c880f17b416c9f8f7a26d05"}, + {file = "pydantic_core-2.27.1-cp313-none-win_amd64.whl", hash = "sha256:ba630d5e3db74c79300d9a5bdaaf6200172b107f263c98a0539eeecb857b2337"}, + {file = "pydantic_core-2.27.1-cp313-none-win_arm64.whl", hash = "sha256:45cf8588c066860b623cd11c4ba687f8d7175d5f7ef65f7129df8a394c502de5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:5897bec80a09b4084aee23f9b73a9477a46c3304ad1d2d07acca19723fb1de62"}, + {file = "pydantic_core-2.27.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d0165ab2914379bd56908c02294ed8405c252250668ebcb438a55494c69f44ab"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b9af86e1d8e4cfc82c2022bfaa6f459381a50b94a29e95dcdda8442d6d83864"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f6c8a66741c5f5447e047ab0ba7a1c61d1e95580d64bce852e3df1f895c4067"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a42d6a8156ff78981f8aa56eb6394114e0dedb217cf8b729f438f643608cbcd"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64c65f40b4cd8b0e049a8edde07e38b476da7e3aaebe63287c899d2cff253fa5"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdcf339322a3fae5cbd504edcefddd5a50d9ee00d968696846f089b4432cf78"}, + {file = "pydantic_core-2.27.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bf99c8404f008750c846cb4ac4667b798a9f7de673ff719d705d9b2d6de49c5f"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8f1edcea27918d748c7e5e4d917297b2a0ab80cad10f86631e488b7cddf76a36"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_armv7l.whl", hash = "sha256:159cac0a3d096f79ab6a44d77a961917219707e2a130739c64d4dd46281f5c2a"}, + {file = "pydantic_core-2.27.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:029d9757eb621cc6e1848fa0b0310310de7301057f623985698ed7ebb014391b"}, + {file = "pydantic_core-2.27.1-cp38-none-win32.whl", hash = "sha256:a28af0695a45f7060e6f9b7092558a928a28553366519f64083c63a44f70e618"}, + {file = "pydantic_core-2.27.1-cp38-none-win_amd64.whl", hash = "sha256:2d4567c850905d5eaaed2f7a404e61012a51caf288292e016360aa2b96ff38d4"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:e9386266798d64eeb19dd3677051f5705bf873e98e15897ddb7d76f477131967"}, + {file = "pydantic_core-2.27.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4228b5b646caa73f119b1ae756216b59cc6e2267201c27d3912b592c5e323b60"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b3dfe500de26c52abe0477dde16192ac39c98f05bf2d80e76102d394bd13854"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:aee66be87825cdf72ac64cb03ad4c15ffef4143dbf5c113f64a5ff4f81477bf9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b748c44bb9f53031c8cbc99a8a061bc181c1000c60a30f55393b6e9c45cc5bd"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ca038c7f6a0afd0b2448941b6ef9d5e1949e999f9e5517692eb6da58e9d44be"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e0bd57539da59a3e4671b90a502da9a28c72322a4f17866ba3ac63a82c4498e"}, + {file = "pydantic_core-2.27.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ac6c2c45c847bbf8f91930d88716a0fb924b51e0c6dad329b793d670ec5db792"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b94d4ba43739bbe8b0ce4262bcc3b7b9f31459ad120fb595627eaeb7f9b9ca01"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_armv7l.whl", hash = "sha256:00e6424f4b26fe82d44577b4c842d7df97c20be6439e8e685d0d715feceb9fb9"}, + {file = "pydantic_core-2.27.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:38de0a70160dd97540335b7ad3a74571b24f1dc3ed33f815f0880682e6880131"}, + {file = "pydantic_core-2.27.1-cp39-none-win32.whl", hash = "sha256:7ccebf51efc61634f6c2344da73e366c75e735960b5654b63d7e6f69a5885fa3"}, + {file = "pydantic_core-2.27.1-cp39-none-win_amd64.whl", hash = "sha256:a57847b090d7892f123726202b7daa20df6694cbd583b67a592e856bff603d6c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3fa80ac2bd5856580e242dbc202db873c60a01b20309c8319b5c5986fbe53ce6"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d950caa237bb1954f1b8c9227b5065ba6875ac9771bb8ec790d956a699b78676"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e4216e64d203e39c62df627aa882f02a2438d18a5f21d7f721621f7a5d3611d"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02a3d637bd387c41d46b002f0e49c52642281edacd2740e5a42f7017feea3f2c"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:161c27ccce13b6b0c8689418da3885d3220ed2eae2ea5e9b2f7f3d48f1d52c27"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:19910754e4cc9c63bc1c7f6d73aa1cfee82f42007e407c0f413695c2f7ed777f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e173486019cc283dc9778315fa29a363579372fe67045e971e89b6365cc035ed"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:af52d26579b308921b73b956153066481f064875140ccd1dfd4e77db89dbb12f"}, + {file = "pydantic_core-2.27.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:981fb88516bd1ae8b0cbbd2034678a39dedc98752f264ac9bc5839d3923fa04c"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5fde892e6c697ce3e30c61b239330fc5d569a71fefd4eb6512fc6caec9dd9e2f"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:816f5aa087094099fff7edabb5e01cc370eb21aa1a1d44fe2d2aefdfb5599b31"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c10c309e18e443ddb108f0ef64e8729363adbfd92d6d57beec680f6261556f3"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98476c98b02c8e9b2eec76ac4156fd006628b1b2d0ef27e548ffa978393fd154"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c3027001c28434e7ca5a6e1e527487051136aa81803ac812be51802150d880dd"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:7699b1df36a48169cdebda7ab5a2bac265204003f153b4bd17276153d997670a"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1c39b07d90be6b48968ddc8c19e7585052088fd7ec8d568bb31ff64c70ae3c97"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:46ccfe3032b3915586e469d4972973f893c0a2bb65669194a5bdea9bacc088c2"}, + {file = "pydantic_core-2.27.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:62ba45e21cf6571d7f716d903b5b7b6d2617e2d5d67c0923dc47b9d41369f840"}, + {file = "pydantic_core-2.27.1.tar.gz", hash = "sha256:62a763352879b84aa31058fc931884055fd75089cccbd9d58bb6afd01141b235"}, ] [package.dependencies] @@ -689,13 +772,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0" [[package]] name = "pytest" -version = "8.3.3" +version = "8.3.4" description = "pytest: simple powerful testing with Python" optional = false python-versions = ">=3.8" files = [ - {file = "pytest-8.3.3-py3-none-any.whl", hash = "sha256:a6853c7375b2663155079443d2e45de913a911a11d669df02a50814944db57b2"}, - {file = "pytest-8.3.3.tar.gz", hash = "sha256:70b98107bd648308a7952b06e6ca9a50bc660be218d53c257cc1fc94fda10181"}, + {file = "pytest-8.3.4-py3-none-any.whl", hash = "sha256:50e16d954148559c9a74109af1eaf0c945ba2d8f30f0a3d3335edde19788b6f6"}, + {file = "pytest-8.3.4.tar.gz", hash = "sha256:965370d062bce11e73868e0335abac31b4d3de0e82f4007408d242b4f8610761"}, ] [package.dependencies] @@ -711,22 +794,36 @@ dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments [[package]] name = "pytest-asyncio" -version = "0.23.8" +version = "0.24.0" description = "Pytest support for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "pytest_asyncio-0.23.8-py3-none-any.whl", hash = "sha256:50265d892689a5faefb84df80819d1ecef566eb3549cf915dfb33569359d1ce2"}, - {file = "pytest_asyncio-0.23.8.tar.gz", hash = "sha256:759b10b33a6dc61cce40a8bd5205e302978bbbcc00e279a8b61d9a6a3c82e4d3"}, + {file = "pytest_asyncio-0.24.0-py3-none-any.whl", hash = "sha256:a811296ed596b69bf0b6f3dc40f83bcaf341b155a269052d82efa2b25ac7037b"}, + {file = "pytest_asyncio-0.24.0.tar.gz", hash = "sha256:d081d828e576d85f875399194281e92bf8a68d60d72d1a2faf2feddb6c46b276"}, ] [package.dependencies] -pytest = ">=7.0.0,<9" +pytest = ">=8.2,<9" [package.extras] docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"] testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"] +[[package]] +name = "pytest-socket" +version = "0.7.0" +description = "Pytest Plugin to disable socket calls during tests" +optional = false +python-versions = ">=3.8,<4.0" +files = [ + {file = "pytest_socket-0.7.0-py3-none-any.whl", hash = "sha256:7e0f4642177d55d317bbd58fc68c6bd9048d6eadb2d46a89307fa9221336ce45"}, + {file = "pytest_socket-0.7.0.tar.gz", hash = "sha256:71ab048cbbcb085c15a4423b73b619a8b35d6a307f46f78ea46be51b1b7e11b3"}, +] + +[package.dependencies] +pytest = ">=6.2.5" + [[package]] name = "pyyaml" version = "6.0.2" @@ -826,29 +923,29 @@ requests = ">=2.0.1,<3.0.0" [[package]] name = "ruff" -version = "0.7.4" +version = "0.8.2" description = "An extremely fast Python linter and code formatter, written in Rust." optional = false python-versions = ">=3.7" files = [ - {file = "ruff-0.7.4-py3-none-linux_armv6l.whl", hash = "sha256:a4919925e7684a3f18e18243cd6bea7cfb8e968a6eaa8437971f681b7ec51478"}, - {file = "ruff-0.7.4-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:cfb365c135b830778dda8c04fb7d4280ed0b984e1aec27f574445231e20d6c63"}, - {file = "ruff-0.7.4-py3-none-macosx_11_0_arm64.whl", hash = "sha256:63a569b36bc66fbadec5beaa539dd81e0527cb258b94e29e0531ce41bacc1f20"}, - {file = "ruff-0.7.4-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d06218747d361d06fd2fdac734e7fa92df36df93035db3dc2ad7aa9852cb109"}, - {file = "ruff-0.7.4-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e0cea28d0944f74ebc33e9f934238f15c758841f9f5edd180b5315c203293452"}, - {file = "ruff-0.7.4-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:80094ecd4793c68b2571b128f91754d60f692d64bc0d7272ec9197fdd09bf9ea"}, - {file = "ruff-0.7.4-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:997512325c6620d1c4c2b15db49ef59543ef9cd0f4aa8065ec2ae5103cedc7e7"}, - {file = "ruff-0.7.4-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:00b4cf3a6b5fad6d1a66e7574d78956bbd09abfd6c8a997798f01f5da3d46a05"}, - {file = "ruff-0.7.4-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7dbdc7d8274e1422722933d1edddfdc65b4336abf0b16dfcb9dedd6e6a517d06"}, - {file = "ruff-0.7.4-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0e92dfb5f00eaedb1501b2f906ccabfd67b2355bdf117fea9719fc99ac2145bc"}, - {file = "ruff-0.7.4-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:3bd726099f277d735dc38900b6a8d6cf070f80828877941983a57bca1cd92172"}, - {file = "ruff-0.7.4-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:2e32829c429dd081ee5ba39aef436603e5b22335c3d3fff013cd585806a6486a"}, - {file = "ruff-0.7.4-py3-none-musllinux_1_2_i686.whl", hash = "sha256:662a63b4971807623f6f90c1fb664613f67cc182dc4d991471c23c541fee62dd"}, - {file = "ruff-0.7.4-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:876f5e09eaae3eb76814c1d3b68879891d6fde4824c015d48e7a7da4cf066a3a"}, - {file = "ruff-0.7.4-py3-none-win32.whl", hash = "sha256:75c53f54904be42dd52a548728a5b572344b50d9b2873d13a3f8c5e3b91f5cac"}, - {file = "ruff-0.7.4-py3-none-win_amd64.whl", hash = "sha256:745775c7b39f914238ed1f1b0bebed0b9155a17cd8bc0b08d3c87e4703b990d6"}, - {file = "ruff-0.7.4-py3-none-win_arm64.whl", hash = "sha256:11bff065102c3ae9d3ea4dc9ecdfe5a5171349cdd0787c1fc64761212fc9cf1f"}, - {file = "ruff-0.7.4.tar.gz", hash = "sha256:cd12e35031f5af6b9b93715d8c4f40360070b2041f81273d0527683d5708fce2"}, + {file = "ruff-0.8.2-py3-none-linux_armv6l.whl", hash = "sha256:c49ab4da37e7c457105aadfd2725e24305ff9bc908487a9bf8d548c6dad8bb3d"}, + {file = "ruff-0.8.2-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:ec016beb69ac16be416c435828be702ee694c0d722505f9c1f35e1b9c0cc1bf5"}, + {file = "ruff-0.8.2-py3-none-macosx_11_0_arm64.whl", hash = "sha256:f05cdf8d050b30e2ba55c9b09330b51f9f97d36d4673213679b965d25a785f3c"}, + {file = "ruff-0.8.2-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:60f578c11feb1d3d257b2fb043ddb47501ab4816e7e221fbb0077f0d5d4e7b6f"}, + {file = "ruff-0.8.2-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:cbd5cf9b0ae8f30eebc7b360171bd50f59ab29d39f06a670b3e4501a36ba5897"}, + {file = "ruff-0.8.2-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b402ddee3d777683de60ff76da801fa7e5e8a71038f57ee53e903afbcefdaa58"}, + {file = "ruff-0.8.2-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:705832cd7d85605cb7858d8a13d75993c8f3ef1397b0831289109e953d833d29"}, + {file = "ruff-0.8.2-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:32096b41aaf7a5cc095fa45b4167b890e4c8d3fd217603f3634c92a541de7248"}, + {file = "ruff-0.8.2-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e769083da9439508833cfc7c23e351e1809e67f47c50248250ce1ac52c21fb93"}, + {file = "ruff-0.8.2-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5fe716592ae8a376c2673fdfc1f5c0c193a6d0411f90a496863c99cd9e2ae25d"}, + {file = "ruff-0.8.2-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:81c148825277e737493242b44c5388a300584d73d5774defa9245aaef55448b0"}, + {file = "ruff-0.8.2-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:d261d7850c8367704874847d95febc698a950bf061c9475d4a8b7689adc4f7fa"}, + {file = "ruff-0.8.2-py3-none-musllinux_1_2_i686.whl", hash = "sha256:1ca4e3a87496dc07d2427b7dd7ffa88a1e597c28dad65ae6433ecb9f2e4f022f"}, + {file = "ruff-0.8.2-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:729850feed82ef2440aa27946ab39c18cb4a8889c1128a6d589ffa028ddcfc22"}, + {file = "ruff-0.8.2-py3-none-win32.whl", hash = "sha256:ac42caaa0411d6a7d9594363294416e0e48fc1279e1b0e948391695db2b3d5b1"}, + {file = "ruff-0.8.2-py3-none-win_amd64.whl", hash = "sha256:2aae99ec70abf43372612a838d97bfe77d45146254568d94926e8ed5bbb409ea"}, + {file = "ruff-0.8.2-py3-none-win_arm64.whl", hash = "sha256:fb88e2a506b70cfbc2de6fae6681c4f944f7dd5f2fe87233a7233d888bad73e8"}, + {file = "ruff-0.8.2.tar.gz", hash = "sha256:b84f4f414dda8ac7f75075c1fa0b905ac0ff25361f42e6d5da681a465e0f78e5"}, ] [[package]] @@ -864,13 +961,13 @@ files = [ [[package]] name = "syrupy" -version = "4.7.2" +version = "4.8.0" description = "Pytest Snapshot Test Utility" optional = false python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.7.2-py3-none-any.whl", hash = "sha256:eae7ba6be5aed190237caa93be288e97ca1eec5ca58760e4818972a10c4acc64"}, - {file = "syrupy-4.7.2.tar.gz", hash = "sha256:ea45e099f242de1bb53018c238f408a5bb6c82007bc687aefcbeaa0e1c2e935a"}, + {file = "syrupy-4.8.0-py3-none-any.whl", hash = "sha256:544f4ec6306f4b1c460fdab48fd60b2c7fe54a6c0a8243aeea15f9ad9c638c3f"}, + {file = "syrupy-4.8.0.tar.gz", hash = "sha256:648f0e9303aaa8387c8365d7314784c09a6bab0a407455c6a01d6a4f5c6a8ede"}, ] [package.dependencies] @@ -893,13 +990,43 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"] [[package]] name = "tomli" -version = "2.1.0" +version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" files = [ - {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, - {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, + {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"}, + {file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"}, + {file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"}, + {file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"}, + {file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"}, + {file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"}, + {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"}, + {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"}, + {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"}, + {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"}, + {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"}, + {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"}, + {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"}, + {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"}, + {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"}, + {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"}, + {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"}, ] [[package]] @@ -933,4 +1060,4 @@ zstd = ["zstandard (>=0.18.0)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "f92550d052b48eb60c41c6baa12c158391f7c1e5453b824ac212aa1e75260b1f" +content-hash = "c7788100e716b6bb0a93ff547aaa451f70b435b0c0405c7a06581ddb7fac6f20" diff --git a/libs/standard-tests/pyproject.toml b/libs/standard-tests/pyproject.toml index cb15fa4968312..2a44bc3b7bf83 100644 --- a/libs/standard-tests/pyproject.toml +++ b/libs/standard-tests/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-tests" -version = "0.3.4" +version = "0.3.7" description = "Standard tests for LangChain implementations" authors = ["Erick Friis "] readme = "README.md" @@ -19,10 +19,20 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.19" +langchain-core = "^0.3.22" pytest = ">=7,<9" -httpx = "^0.27.0" +pytest-asyncio = ">=0.20,<1" +httpx = ">=0.25.0,<1" syrupy = "^4" +pytest-socket = ">=0.6.0,<1" + +[[tool.poetry.dependencies.numpy]] +version = "^1.24.0" +python = "<3.12" + +[[tool.poetry.dependencies.numpy]] +version = ">=1.26.2,<3" +python = ">=3.12" [tool.ruff.lint] select = ["E", "F", "I", "T201"] @@ -52,15 +62,6 @@ optional = true optional = true [tool.poetry.group.test.dependencies] -pytest-asyncio = "^0.23.7" - -[[tool.poetry.group.test.dependencies.numpy]] -version = "^1.24.0" -python = "<3.12" - -[[tool.poetry.group.test.dependencies.numpy]] -version = "^1.26.0" -python = ">=3.12" [tool.poetry.group.test_integration.dependencies] diff --git a/libs/standard-tests/tests/unit_tests/test_basic_retriever.py b/libs/standard-tests/tests/unit_tests/test_basic_retriever.py new file mode 100644 index 0000000000000..fb7999a09fb5c --- /dev/null +++ b/libs/standard-tests/tests/unit_tests/test_basic_retriever.py @@ -0,0 +1,29 @@ +from typing import Any, Type + +from langchain_core.documents import Document +from langchain_core.retrievers import BaseRetriever + +from langchain_tests.integration_tests import RetrieversIntegrationTests + + +class ParrotRetriever(BaseRetriever): + parrot_name: str + k: int = 3 + + def _get_relevant_documents(self, query: str, **kwargs: Any) -> list[Document]: + k = kwargs.get("k", self.k) + return [Document(page_content=f"{self.parrot_name} says: {query}")] * k + + +class TestParrotRetrieverIntegration(RetrieversIntegrationTests): + @property + def retriever_constructor(self) -> Type[ParrotRetriever]: + return ParrotRetriever + + @property + def retriever_constructor_params(self) -> dict: + return {"parrot_name": "Polly"} + + @property + def retriever_query_example(self) -> str: + return "parrot" diff --git a/libs/standard-tests/tests/unit_tests/test_embeddings.py b/libs/standard-tests/tests/unit_tests/test_embeddings.py new file mode 100644 index 0000000000000..d2a551deccafe --- /dev/null +++ b/libs/standard-tests/tests/unit_tests/test_embeddings.py @@ -0,0 +1,26 @@ +from typing import Type + +from langchain_core.embeddings import DeterministicFakeEmbedding, Embeddings + +from langchain_tests.integration_tests import EmbeddingsIntegrationTests +from langchain_tests.unit_tests import EmbeddingsUnitTests + + +class TestFakeEmbeddingsUnit(EmbeddingsUnitTests): + @property + def embeddings_class(self) -> Type[Embeddings]: + return DeterministicFakeEmbedding + + @property + def embedding_model_params(self) -> dict: + return {"size": 6} # embedding dimension + + +class TestFakeEmbeddingsIntegration(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[Embeddings]: + return DeterministicFakeEmbedding + + @property + def embedding_model_params(self) -> dict: + return {"size": 6} diff --git a/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py b/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py index 8a3bf5d0a32b2..53b9dd1a9c8d4 100644 --- a/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py +++ b/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py @@ -4,21 +4,11 @@ VectorStore, ) -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests -class TestInMemoryVectorStore(ReadWriteTestSuite): +class TestInMemoryVectorStore(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> VectorStore: embeddings = self.get_embeddings() return InMemoryVectorStore(embedding=embeddings) - - -class TestAsyncInMemoryVectorStore(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> VectorStore: - embeddings = self.get_embeddings() - return InMemoryVectorStore(embedding=embeddings) diff --git a/libs/text-splitters/README.md b/libs/text-splitters/README.md index 83d711b8ec0f6..fbbfc34f5d69b 100644 --- a/libs/text-splitters/README.md +++ b/libs/text-splitters/README.md @@ -13,7 +13,7 @@ pip install langchain-text-splitters LangChain Text Splitters contains utilities for splitting into chunks a wide variety of text documents. -For full documentation see the [API reference](https://api.python.langchain.com/en/stable/text_splitters_api_reference.html) +For full documentation see the [API reference](https://python.langchain.com/api_reference/text_splitters/index.html) and the [Text Splitters](https://python.langchain.com/docs/modules/data_connection/document_transformers/) module in the main docs. ## 📕 Releases & Versioning diff --git a/libs/text-splitters/langchain_text_splitters/__init__.py b/libs/text-splitters/langchain_text_splitters/__init__.py index 58ad7b0e4c585..65af087fdd85f 100644 --- a/libs/text-splitters/langchain_text_splitters/__init__.py +++ b/libs/text-splitters/langchain_text_splitters/__init__.py @@ -1,6 +1,5 @@ """**Text Splitters** are classes for splitting text. - **Class hierarchy:** .. code-block:: diff --git a/libs/text-splitters/langchain_text_splitters/base.py b/libs/text-splitters/langchain_text_splitters/base.py index 0e0a49c182da7..10dd6903ba172 100644 --- a/libs/text-splitters/langchain_text_splitters/base.py +++ b/libs/text-splitters/langchain_text_splitters/base.py @@ -249,6 +249,21 @@ def __init__( self._disallowed_special = disallowed_special def split_text(self, text: str) -> List[str]: + """Splits the input text into smaller chunks based on tokenization. + + This method uses a custom tokenizer configuration to encode the input text + into tokens, processes the tokens in chunks of a specified size with overlap, + and decodes them back into text chunks. The splitting is performed using the + `split_text_on_tokens` function. + + Args: + text (str): The input text to be split into smaller chunks. + + Returns: + List[str]: A list of text chunks, where each chunk is derived from a portion + of the input text based on the tokenization and chunking rules. + """ + def _encode(_text: str) -> List[int]: return self._tokenizer.encode( _text, diff --git a/libs/text-splitters/langchain_text_splitters/character.py b/libs/text-splitters/langchain_text_splitters/character.py index f65c38869d394..a2918bd27f0ac 100644 --- a/libs/text-splitters/langchain_text_splitters/character.py +++ b/libs/text-splitters/langchain_text_splitters/character.py @@ -115,17 +115,45 @@ def _split_text(self, text: str, separators: List[str]) -> List[str]: return final_chunks def split_text(self, text: str) -> List[str]: + """Split the input text into smaller chunks based on predefined separators. + + Args: + text (str): The input text to be split. + + Returns: + List[str]: A list of text chunks obtained after splitting. + """ return self._split_text(text, self._separators) @classmethod def from_language( cls, language: Language, **kwargs: Any ) -> RecursiveCharacterTextSplitter: + """Return an instance of this class based on a specific language. + + This method initializes the text splitter with language-specific separators. + + Args: + language (Language): The language to configure the text splitter for. + **kwargs (Any): Additional keyword arguments to customize the splitter. + + Returns: + RecursiveCharacterTextSplitter: An instance of the text splitter configured + for the specified language. + """ separators = cls.get_separators_for_language(language) return cls(separators=separators, is_separator_regex=True, **kwargs) @staticmethod def get_separators_for_language(language: Language) -> List[str]: + """Retrieve a list of separators specific to the given language. + + Args: + language (Language): The language for which to get the separators. + + Returns: + List[str]: A list of separators appropriate for the specified language. + """ if language == Language.C or language == Language.CPP: return [ # Split along class definitions diff --git a/libs/text-splitters/langchain_text_splitters/html.py b/libs/text-splitters/langchain_text_splitters/html.py index cdbea7f724b53..241c0981f58f5 100644 --- a/libs/text-splitters/langchain_text_splitters/html.py +++ b/libs/text-splitters/langchain_text_splitters/html.py @@ -21,8 +21,8 @@ class ElementType(TypedDict): class HTMLHeaderTextSplitter: - """ - Splitting HTML files based on specified headers. + """Splitting HTML files based on specified headers. + Requires lxml package. """ @@ -46,7 +46,7 @@ def __init__( def aggregate_elements_to_chunks( self, elements: List[ElementType] ) -> List[Document]: - """Combine elements with common metadata into chunks + """Combine elements with common metadata into chunks. Args: elements: HTML element content with associated identifying info and metadata @@ -72,7 +72,7 @@ def aggregate_elements_to_chunks( ] def split_text_from_url(self, url: str, **kwargs: Any) -> List[Document]: - """Split HTML from web URL + """Split HTML from web URL. Args: url: web URL @@ -83,7 +83,7 @@ def split_text_from_url(self, url: str, **kwargs: Any) -> List[Document]: return self.split_text_from_file(BytesIO(r.content)) def split_text(self, text: str) -> List[Document]: - """Split HTML text string + """Split HTML text string. Args: text: HTML text @@ -91,7 +91,7 @@ def split_text(self, text: str) -> List[Document]: return self.split_text_from_file(StringIO(text)) def split_text_from_file(self, file: Any) -> List[Document]: - """Split HTML file + """Split HTML file. Args: file: HTML file @@ -166,8 +166,8 @@ def split_text_from_file(self, file: Any) -> List[Document]: class HTMLSectionSplitter: - """ - Splitting HTML files based on specified tag and font sizes. + """Splitting HTML files based on specified tag and font sizes. + Requires lxml package. """ @@ -186,6 +186,8 @@ def __init__( xslt_path: path to xslt file for document transformation. Uses a default if not passed. Needed for html contents that using different format and layouts. + **kwargs (Any): Additional optional arguments for customizations. + """ self.headers_to_split_on = dict(headers_to_split_on) @@ -210,7 +212,7 @@ def split_documents(self, documents: Iterable[Document]) -> List[Document]: return text_splitter.split_documents(results) def split_text(self, text: str) -> List[Document]: - """Split HTML text string + """Split HTML text string. Args: text: HTML text @@ -236,6 +238,23 @@ def create_documents( return documents def split_html_by_headers(self, html_doc: str) -> List[Dict[str, Optional[str]]]: + """Split an HTML document into sections based on specified header tags. + + This method uses BeautifulSoup to parse the HTML content and divides it into + sections based on headers defined in `headers_to_split_on`. Each section + contains the header text, content under the header, and the tag name. + + Args: + html_doc (str): The HTML document to be split into sections. + + Returns: + List[Dict[str, Optional[str]]]: A list of dictionaries representing + sections. + Each dictionary contains: + - 'header': The header text or a default title for the first section. + - 'content': The content under the header. + - 'tag_name': The name of the header tag (e.g., "h1", "h2"). + """ try: from bs4 import BeautifulSoup, PageElement # type: ignore[import-untyped] except ImportError as e: @@ -259,7 +278,7 @@ def split_html_by_headers(self, html_doc: str) -> List[Dict[str, Optional[str]]] section_content: List = [] else: current_header = header_element.text.strip() - current_header_tag = header_element.name + current_header_tag = header_element.name # type: ignore[attr-defined] section_content = [] for element in header_element.next_elements: if i + 1 < len(headers) and element == headers[i + 1]: @@ -280,6 +299,18 @@ def split_html_by_headers(self, html_doc: str) -> List[Dict[str, Optional[str]]] return sections def convert_possible_tags_to_header(self, html_content: str) -> str: + """Convert specific HTML tags to headers using an XSLT transformation. + + This method uses an XSLT file to transform the HTML content, converting + certain tags into headers for easier parsing. If no XSLT path is provided, + the HTML content is returned unchanged. + + Args: + html_content (str): The HTML content to be transformed. + + Returns: + str: The transformed HTML content as a string. + """ if self.xslt_path is None: return html_content @@ -299,7 +330,7 @@ def convert_possible_tags_to_header(self, html_content: str) -> str: return str(result) def split_text_from_file(self, file: Any) -> List[Document]: - """Split HTML file + """Split HTML file. Args: file: HTML file diff --git a/libs/text-splitters/langchain_text_splitters/json.py b/libs/text-splitters/langchain_text_splitters/json.py index c83d8b2a42880..c58174dd8b33a 100644 --- a/libs/text-splitters/langchain_text_splitters/json.py +++ b/libs/text-splitters/langchain_text_splitters/json.py @@ -8,9 +8,38 @@ class RecursiveJsonSplitter: + """Splits JSON data into smaller, structured chunks while preserving hierarchy. + + This class provides methods to split JSON data into smaller dictionaries or + JSON-formatted strings based on configurable maximum and minimum chunk sizes. + It supports nested JSON structures, optionally converts lists into dictionaries + for better chunking, and allows the creation of document objects for further use. + + Attributes: + max_chunk_size (int): The maximum size for each chunk. Defaults to 2000. + min_chunk_size (int): The minimum size for each chunk, derived from + `max_chunk_size` if not explicitly provided. + """ + def __init__( self, max_chunk_size: int = 2000, min_chunk_size: Optional[int] = None ): + """Initialize the chunk size configuration for text processing. + + This constructor sets up the maximum and minimum chunk sizes, ensuring that + the `min_chunk_size` defaults to a value slightly smaller than the + `max_chunk_size` if not explicitly provided. + + Args: + max_chunk_size (int): The maximum size for a chunk. Defaults to 2000. + min_chunk_size (Optional[int]): The minimum size for a chunk. If None, + defaults to the maximum chunk size minus 200, with a lower bound of 50. + + Attributes: + max_chunk_size (int): The configured maximum size for each chunk. + min_chunk_size (int): The configured minimum size for each chunk, derived + from `max_chunk_size` if not explicitly provided. + """ super().__init__() self.max_chunk_size = max_chunk_size self.min_chunk_size = ( @@ -51,9 +80,7 @@ def _json_split( current_path: Optional[List[str]] = None, chunks: Optional[List[Dict]] = None, ) -> List[Dict]: - """ - Split json into maximum size dictionaries while preserving structure. - """ + """Split json into maximum size dictionaries while preserving structure.""" current_path = current_path or [] chunks = chunks if chunks is not None else [{}] if isinstance(data, dict): @@ -83,8 +110,7 @@ def split_json( json_data: Dict[str, Any], convert_lists: bool = False, ) -> List[Dict]: - """Splits JSON into a list of JSON chunks""" - + """Splits JSON into a list of JSON chunks.""" if convert_lists: chunks = self._json_split(self._list_to_dict_preprocessing(json_data)) else: @@ -101,8 +127,7 @@ def split_text( convert_lists: bool = False, ensure_ascii: bool = True, ) -> List[str]: - """Splits JSON into a list of JSON formatted strings""" - + """Splits JSON into a list of JSON formatted strings.""" chunks = self.split_json(json_data=json_data, convert_lists=convert_lists) # Convert to string diff --git a/libs/text-splitters/langchain_text_splitters/markdown.py b/libs/text-splitters/langchain_text_splitters/markdown.py index fdcd010f50d43..34c7d2197d238 100644 --- a/libs/text-splitters/langchain_text_splitters/markdown.py +++ b/libs/text-splitters/langchain_text_splitters/markdown.py @@ -45,7 +45,8 @@ def __init__( self.strip_headers = strip_headers def aggregate_lines_to_chunks(self, lines: List[LineType]) -> List[Document]: - """Combine lines with common metadata into chunks + """Combine lines with common metadata into chunks. + Args: lines: Line of text / associated header metadata """ @@ -87,10 +88,11 @@ def aggregate_lines_to_chunks(self, lines: List[LineType]) -> List[Document]: ] def split_text(self, text: str) -> List[Document]: - """Split markdown file - Args: - text: Markdown file""" + """Split markdown file. + Args: + text: Markdown file + """ # Split the input text by newline character ("\n"). lines = text.split("\n") # Final output @@ -225,8 +227,7 @@ class HeaderType(TypedDict): class ExperimentalMarkdownSyntaxTextSplitter: - """ - An experimental text splitter for handling Markdown syntax. + """An experimental text splitter for handling Markdown syntax. This splitter aims to retain the exact whitespace of the original text while extracting structured metadata, such as headers. It is a re-implementation of the @@ -280,6 +281,22 @@ def __init__( return_each_line: bool = False, strip_headers: bool = True, ): + """Initialize the text splitter with header splitting and formatting options. + + This constructor sets up the required configuration for splitting text into + chunks based on specified headers and formatting preferences. + + Args: + headers_to_split_on (Union[List[Tuple[str, str]], None]): + A list of tuples, where each tuple contains a header tag (e.g., "h1") + and its corresponding metadata key. If None, default headers are used. + return_each_line (bool): + Whether to return each line as an individual chunk. + Defaults to False, which aggregates lines into larger chunks. + strip_headers (bool): + Whether to exclude headers from the resulting chunks. + Defaults to True. + """ self.chunks: List[Document] = [] self.current_chunk = Document(page_content="") self.current_header_stack: List[Tuple[int, str]] = [] @@ -292,6 +309,21 @@ def __init__( self.return_each_line = return_each_line def split_text(self, text: str) -> List[Document]: + """Split the input text into structured chunks. + + This method processes the input text line by line, identifying and handling + specific patterns such as headers, code blocks, and horizontal rules to + split it into structured chunks based on headers, code blocks, and + horizontal rules. + + Args: + text (str): The input text to be split into chunks. + + Returns: + List[Document]: A list of `Document` objects representing the structured + chunks of the input text. If `return_each_line` is enabled, each line + is returned as a separate `Document`. + """ raw_lines = text.splitlines(keepends=True) while raw_lines: diff --git a/libs/text-splitters/langchain_text_splitters/sentence_transformers.py b/libs/text-splitters/langchain_text_splitters/sentence_transformers.py index beb314d810d9e..3b19c5edc594d 100644 --- a/libs/text-splitters/langchain_text_splitters/sentence_transformers.py +++ b/libs/text-splitters/langchain_text_splitters/sentence_transformers.py @@ -51,6 +51,20 @@ def _initialize_chunk_configuration( ) def split_text(self, text: str) -> List[str]: + """Splits the input text into smaller components by splitting text on tokens. + + This method encodes the input text using a private `_encode` method, then + strips the start and stop token IDs from the encoded result. It returns the + processed segments as a list of strings. + + Args: + text (str): The input text to be split. + + Returns: + List[str]: A list of string components derived from the input text after + encoding and processing. + """ + def encode_strip_start_and_stop_token_ids(text: str) -> List[int]: return self._encode(text)[1:-1] @@ -64,6 +78,17 @@ def encode_strip_start_and_stop_token_ids(text: str) -> List[int]: return split_text_on_tokens(text=text, tokenizer=tokenizer) def count_tokens(self, *, text: str) -> int: + """Counts the number of tokens in the given text. + + This method encodes the input text using a private `_encode` method and + calculates the total number of tokens in the encoded result. + + Args: + text (str): The input text for which the token count is calculated. + + Returns: + int: The number of tokens in the encoded text. + """ return len(self._encode(text)) _max_length_equal_32_bit_integer: int = 2**32 diff --git a/libs/text-splitters/langchain_text_splitters/spacy.py b/libs/text-splitters/langchain_text_splitters/spacy.py index 447a3e429600c..a15e8b00418a0 100644 --- a/libs/text-splitters/langchain_text_splitters/spacy.py +++ b/libs/text-splitters/langchain_text_splitters/spacy.py @@ -8,7 +8,6 @@ class SpacyTextSplitter(TextSplitter): """Splitting text using Spacy package. - Per default, Spacy's `en_core_web_sm` model is used and its default max_length is 1000000 (it is the length of maximum character this model takes which can be increased for large files). For a faster, but diff --git a/libs/text-splitters/pyproject.toml b/libs/text-splitters/pyproject.toml index c4c8a7535860e..53f8993809454 100644 --- a/libs/text-splitters/pyproject.toml +++ b/libs/text-splitters/pyproject.toml @@ -26,7 +26,20 @@ python = ">=3.9,<4.0" langchain-core = "^0.3.15" [tool.ruff.lint] -select = [ "E", "F", "I", "T201",] +select = [ + "E", # pycodestyle + "F", # Pyflakes + "I", # isort + "T201", # print + "D", # pydocstyle +] +ignore = ["D100"] # ignore missing module docstring + +[tool.ruff.lint.pydocstyle] +convention = "google" + +[tool.ruff.lint.per-file-ignores] +"tests/**" = ["D"] # ignore docstring checks for tests [tool.coverage.run] omit = [ "tests/*",] diff --git a/poetry.lock b/poetry.lock index ed5ccf94d4f76..a651014235914 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. [[package]] name = "aiofiles" @@ -2917,7 +2917,7 @@ url = "libs/community" [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.20" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0"