diff --git a/.github/scripts/get_min_versions.py b/.github/scripts/get_min_versions.py index f91dd00ee06d9f..0838a6e7e3957f 100644 --- a/.github/scripts/get_min_versions.py +++ b/.github/scripts/get_min_versions.py @@ -7,12 +7,17 @@ # for python 3.10 and below, which doesnt have stdlib tomllib import tomli as tomllib -from packaging.version import parse as parse_version from packaging.specifiers import SpecifierSet from packaging.version import Version + +import requests +from packaging.version import parse +from typing import List + import re + MIN_VERSION_LIBS = [ "langchain-core", "langchain-community", @@ -31,29 +36,61 @@ ] -def get_min_version(version: str) -> str: - # base regex for x.x.x with cases for rc/post/etc - # valid strings: https://peps.python.org/pep-0440/#public-version-identifiers - vstring = r"\d+(?:\.\d+){0,2}(?:(?:a|b|rc|\.post|\.dev)\d+)?" - # case ^x.x.x - _match = re.match(f"^\\^({vstring})$", version) - if _match: - return _match.group(1) +def get_pypi_versions(package_name: str) -> List[str]: + """ + Fetch all available versions for a package from PyPI. + + Args: + package_name (str): Name of the package + + Returns: + List[str]: List of all available versions - # case >=x.x.x,=({vstring}),<({vstring})$", version) - if _match: - _min = _match.group(1) - _max = _match.group(2) - assert parse_version(_min) < parse_version(_max) - return _min + Raises: + requests.exceptions.RequestException: If PyPI API request fails + KeyError: If package not found or response format unexpected + """ + pypi_url = f"https://pypi.org/pypi/{package_name}/json" + response = requests.get(pypi_url) + response.raise_for_status() + return list(response.json()["releases"].keys()) - # case x.x.x - _match = re.match(f"^({vstring})$", version) - if _match: - return _match.group(1) - raise ValueError(f"Unrecognized version format: {version}") +def get_minimum_version(package_name: str, spec_string: str) -> Optional[str]: + """ + Find the minimum published version that satisfies the given constraints. + + Args: + package_name (str): Name of the package + spec_string (str): Version specification string (e.g., ">=0.2.43,<0.4.0,!=0.3.0") + + Returns: + Optional[str]: Minimum compatible version or None if no compatible version found + """ + # rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string) + spec_string = re.sub(r"\^0\.0\.(\d+)", r"0.0.\1", spec_string) + # rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1 (can be anywhere in constraint string) + for y in range(1, 10): + spec_string = re.sub(rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y+1}", spec_string) + # rewrite occurrences of ^x.y.z to >=x.y.z,={x}.\1.\2,<{x+1}", spec_string + ) + + spec_set = SpecifierSet(spec_string) + all_versions = get_pypi_versions(package_name) + + valid_versions = [] + for version_str in all_versions: + try: + version = parse(version_str) + if spec_set.contains(version): + valid_versions.append(version) + except ValueError: + continue + + return str(min(valid_versions)) if valid_versions else None def get_min_version_from_toml( @@ -96,7 +133,7 @@ def get_min_version_from_toml( ][0]["version"] # Use parse_version to get the minimum supported version from version_string - min_version = get_min_version(version_string) + min_version = get_minimum_version(lib, version_string) # Store the minimum version in the min_versions dictionary min_versions[lib] = min_version @@ -112,6 +149,20 @@ def check_python_version(version_string, constraint_string): :param constraint_string: A string representing the package's Python version constraints (e.g. ">=3.6, <4.0"). :return: True if the version matches the constraints, False otherwise. """ + + # rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string) + constraint_string = re.sub(r"\^0\.0\.(\d+)", r"0.0.\1", constraint_string) + # rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1.0 (can be anywhere in constraint string) + for y in range(1, 10): + constraint_string = re.sub( + rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y+1}.0", constraint_string + ) + # rewrite occurrences of ^x.y.z to >=x.y.z,={x}.0.\1,<{x+1}.0.0", constraint_string + ) + try: version = Version(version_string) constraints = SpecifierSet(constraint_string) diff --git a/.github/workflows/_integration_test.yml b/.github/workflows/_integration_test.yml index 13051f5efc224b..60a74ff08734dd 100644 --- a/.github/workflows/_integration_test.yml +++ b/.github/workflows/_integration_test.yml @@ -81,7 +81,6 @@ jobs: ES_URL: ${{ secrets.ES_URL }} ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }} ES_API_KEY: ${{ secrets.ES_API_KEY }} - GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # for airbyte MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }} VOYAGE_API_KEY: ${{ secrets.VOYAGE_API_KEY }} COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }} diff --git a/.github/workflows/_release.yml b/.github/workflows/_release.yml index f84ff3ac28d19e..7eaa9410beb06f 100644 --- a/.github/workflows/_release.yml +++ b/.github/workflows/_release.yml @@ -95,9 +95,25 @@ jobs: PKG_NAME: ${{ needs.build.outputs.pkg-name }} VERSION: ${{ needs.build.outputs.version }} run: | - REGEX="^$PKG_NAME==\\d+\\.\\d+\\.\\d+\$" - echo $REGEX - PREV_TAG=$(git tag --sort=-creatordate | grep -P $REGEX || true | head -1) + PREV_TAG="$PKG_NAME==${VERSION%.*}.$(( ${VERSION##*.} - 1 ))"; [[ "${VERSION##*.}" -eq 0 ]] && PREV_TAG="" + + # backup case if releasing e.g. 0.3.0, looks up last release + # note if last release (chronologically) was e.g. 0.1.47 it will get + # that instead of the last 0.2 release + if [ -z "$PREV_TAG" ]; then + REGEX="^$PKG_NAME==\\d+\\.\\d+\\.\\d+\$" + echo $REGEX + PREV_TAG=$(git tag --sort=-creatordate | grep -P $REGEX || true | head -1) + fi + + # confirm prev-tag actually exists in git repo with git tag + GIT_TAG_RESULT=$(git tag -l "$PREV_TAG") + if [ -z "$GIT_TAG_RESULT" ]; then + echo "Previous tag $PREV_TAG not found in git repo" + exit 1 + fi + + TAG="${PKG_NAME}==${VERSION}" if [ "$TAG" == "$PREV_TAG" ]; then echo "No new version to release" @@ -231,7 +247,7 @@ jobs: working-directory: ${{ inputs.working-directory }} id: min-version run: | - poetry run pip install packaging + poetry run pip install packaging requests python_version="$(poetry run python --version | awk '{print $2}')" min_versions="$(poetry run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml release $python_version)" echo "min-versions=$min_versions" >> "$GITHUB_OUTPUT" @@ -289,7 +305,6 @@ jobs: ES_URL: ${{ secrets.ES_URL }} ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }} ES_API_KEY: ${{ secrets.ES_API_KEY }} - GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # for airbyte MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }} VOYAGE_API_KEY: ${{ secrets.VOYAGE_API_KEY }} UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }} diff --git a/.github/workflows/_test.yml b/.github/workflows/_test.yml index 9d01508367e0d5..0e03bbb16aece6 100644 --- a/.github/workflows/_test.yml +++ b/.github/workflows/_test.yml @@ -47,7 +47,7 @@ jobs: id: min-version shell: bash run: | - poetry run pip install packaging tomli + poetry run pip install packaging tomli requests python_version="$(poetry run python --version | awk '{print $2}')" min_versions="$(poetry run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml pull_request $python_version)" echo "min-versions=$min_versions" >> "$GITHUB_OUTPUT" diff --git a/.github/workflows/api_doc_build.yml b/.github/workflows/api_doc_build.yml index fd8e09848ceea2..26e2b19cb46022 100644 --- a/.github/workflows/api_doc_build.yml +++ b/.github/workflows/api_doc_build.yml @@ -72,9 +72,7 @@ jobs: - name: Install dependencies working-directory: langchain run: | - - # skip airbyte due to pandas dependency issue - python -m uv pip install $(ls ./libs/partners | grep -vE "airbyte" | xargs -I {} echo "./libs/partners/{}") + 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 -r docs/api_reference/requirements.txt diff --git a/.github/workflows/check_diffs.yml b/.github/workflows/check_diffs.yml index b5729611645c6a..5caa9c9348b128 100644 --- a/.github/workflows/check_diffs.yml +++ b/.github/workflows/check_diffs.yml @@ -31,7 +31,7 @@ jobs: uses: Ana06/get-changed-files@v2.2.0 - id: set-matrix run: | - python -m pip install packaging + python -m pip install packaging requests python .github/scripts/check_diff.py ${{ steps.files.outputs.all }} >> $GITHUB_OUTPUT outputs: lint: ${{ steps.set-matrix.outputs.lint }} diff --git a/docs/api_reference/create_api_rst.py b/docs/api_reference/create_api_rst.py index b5807e0bd13727..56ec6f870b4e0c 100644 --- a/docs/api_reference/create_api_rst.py +++ b/docs/api_reference/create_api_rst.py @@ -530,7 +530,6 @@ def _out_file_path(package_name: str) -> Path: def _build_index(dirs: List[str]) -> None: custom_names = { - "airbyte": "Airbyte", "aws": "AWS", "ai21": "AI21", "ibm": "IBM", diff --git a/docs/docs/concepts/messages.mdx b/docs/docs/concepts/messages.mdx index a12b4287195910..d1b307b98c1d81 100644 --- a/docs/docs/concepts/messages.mdx +++ b/docs/docs/concepts/messages.mdx @@ -12,7 +12,7 @@ Each message has a **role** (e.g., "user", "assistant"), **content** (e.g., text LangChain provides a unified message format that can be used across chat models, allowing users to work with different chat models without worrying about the specific details of the message format used by each model provider. -## What inside a message? +## What is inside a message? A message typically consists of the following pieces of information: diff --git a/docs/docs/how_to/document_loader_csv.ipynb b/docs/docs/how_to/document_loader_csv.ipynb index ebab8d287a1f1f..fa2b5f77165eb0 100644 --- a/docs/docs/how_to/document_loader_csv.ipynb +++ b/docs/docs/how_to/document_loader_csv.ipynb @@ -157,7 +157,7 @@ " temp_file_path = temp_file.name\n", "\n", "loader = CSVLoader(file_path=temp_file_path)\n", - "loader.load()\n", + "data = loader.load()\n", "for record in data[:2]:\n", " print(record)" ] diff --git a/docs/docs/how_to/multi_vector.ipynb b/docs/docs/how_to/multi_vector.ipynb index 9c37cbd5aa0c97..69b4b0df0e0466 100644 --- a/docs/docs/how_to/multi_vector.ipynb +++ b/docs/docs/how_to/multi_vector.ipynb @@ -207,7 +207,7 @@ "id": "cdef8339-f9fa-4b3b-955f-ad9dbdf2734f", "metadata": {}, "source": [ - "The default search type the retriever performs on the vector database is a similarity search. LangChain vector stores also support searching via [Max Marginal Relevance](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.VectorStore.html#langchain_core.vectorstores.VectorStore.max_marginal_relevance_search). This can be controlled via the `search_type` parameter of the retriever:" + "The default search type the retriever performs on the vector database is a similarity search. LangChain vector stores also support searching via [Max Marginal Relevance](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html#langchain_core.vectorstores.base.VectorStore.max_marginal_relevance_search). This can be controlled via the `search_type` parameter of the retriever:" ] }, { 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 c3ad3936bec46f..c757e5ef35c127 100644 --- a/docs/docs/how_to/qa_chat_history_how_to.ipynb +++ b/docs/docs/how_to/qa_chat_history_how_to.ipynb @@ -155,7 +155,7 @@ "id": "15f8ad59-19de-42e3-85a8-3ba95ee0bd43", "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.VectorStore.html#langchain_core.vectorstores.VectorStore.as_retriever) method to build a retriever that can be incorporated into [LCEL](/docs/concepts/lcel) chains." + "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." ] }, { diff --git a/docs/docs/how_to/vectorstore_retriever.ipynb b/docs/docs/how_to/vectorstore_retriever.ipynb index 760bcb2f90e4a8..cc9958eb32a387 100644 --- a/docs/docs/how_to/vectorstore_retriever.ipynb +++ b/docs/docs/how_to/vectorstore_retriever.ipynb @@ -28,7 +28,7 @@ "\n", "## Creating a retriever from a vectorstore\n", "\n", - "You can build a retriever from a vectorstore using its [.as_retriever](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.VectorStore.html#langchain_core.vectorstores.VectorStore.as_retriever) method. Let's walk through an example.\n", + "You can build a retriever from a vectorstore using 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. Let's walk through an example.\n", "\n", "First we instantiate a vectorstore. We will use an in-memory [FAISS](https://python.langchain.com/api_reference/community/vectorstores/langchain_community.vectorstores.faiss.FAISS.html) vectorstore:" ] diff --git a/docs/docs/integrations/providers/databricks.md b/docs/docs/integrations/providers/databricks.md index 54a10c7c6a62c1..a45e8e3e03eb22 100644 --- a/docs/docs/integrations/providers/databricks.md +++ b/docs/docs/integrations/providers/databricks.md @@ -14,23 +14,13 @@ Databricks embraces the LangChain ecosystem in various ways: Installation ------------ -First-party Databricks integrations are available in the langchain-databricks partner package. +First-party Databricks integrations are now available in the databricks-langchain partner package. ``` -pip install langchain-databricks +pip install databricks-langchain ``` -🚧 Upcoming Package Consolidation Notice - -This package (`langchain-databricks`) will soon be consolidated into a new package: `databricks-langchain`. The new package will serve as the primary hub for all Databricks Langchain integrations. - -What’s Changing? -In the coming months, `databricks-langchain` will include all features currently in `langchain-databricks`, as well as additional integrations to provide a unified experience for Databricks users. - -What You Need to Know -For now, continue to use `langchain-databricks` as usual. When `databricks-langchain` is ready, we’ll provide clear migration instructions to make the transition seamless. During the transition period, `langchain-databricks` will remain operational, and updates will be shared here with timelines and guidance. - -Thank you for your support as we work toward an improved, streamlined experience! +The legacy langchain-databricks partner package is still available but will be soon deprecated. Chat Model ---------- @@ -38,7 +28,7 @@ Chat Model `ChatDatabricks` is a Chat Model class to access chat endpoints hosted on Databricks, including state-of-the-art models such as Llama3, Mixtral, and DBRX, as well as your own fine-tuned models. ``` -from langchain_databricks import ChatDatabricks +from databricks_langchain import ChatDatabricks chat_model = ChatDatabricks(endpoint="databricks-meta-llama-3-70b-instruct") ``` @@ -69,7 +59,7 @@ Embeddings `DatabricksEmbeddings` is an Embeddings class to access text-embedding endpoints hosted on Databricks, including state-of-the-art models such as BGE, as well as your own fine-tuned models. ``` -from langchain_databricks import DatabricksEmbeddings +from databricks_langchain import DatabricksEmbeddings embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") ``` @@ -83,7 +73,7 @@ Vector Search Databricks Vector Search is a serverless similarity search engine that allows you to store a vector representation of your data, including metadata, in a vector database. With Vector Search, you can create auto-updating vector search indexes from [Delta](https://docs.databricks.com/en/introduction/delta-comparison.html) tables managed by [Unity Catalog](https://www.databricks.com/product/unity-catalog) and query them with a simple API to return the most similar vectors. ``` -from langchain_databricks.vectorstores import DatabricksVectorSearch +from databricks_langchain import DatabricksVectorSearch dvs = DatabricksVectorSearch( endpoint="", diff --git a/docs/docs/integrations/providers/vectara/index.mdx b/docs/docs/integrations/providers/vectara/index.mdx index d7ff70fef3ea22..10de5f001f1128 100644 --- a/docs/docs/integrations/providers/vectara/index.mdx +++ b/docs/docs/integrations/providers/vectara/index.mdx @@ -4,15 +4,14 @@ > which is grounded in the data, documents, and knowledge that they have (technically, it is Retrieval-Augmented-Generation-as-a-service). **Vectara Overview:** -`Vectara` is RAG-as-a-service, providing all the components of RAG behind an easy-to-use API, including: +[Vectara](https://vectara.com/) is the trusted AI Assistant and Agent platform which focuses on enterprise readiness for mission-critical applications. +Vectara serverless RAG-as-a-service provides all the components of RAG behind an easy-to-use API, including: 1. A way to extract text from files (PDF, PPT, DOCX, etc) 2. ML-based chunking that provides state of the art performance. 3. The [Boomerang](https://vectara.com/how-boomerang-takes-retrieval-augmented-generation-to-the-next-level-via-grounded-generation/) embeddings model. 4. Its own internal vector database where text chunks and embedding vectors are stored. -5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments -(including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) and -[MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/)) -7. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations. +5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments, including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) as well as multiple reranking options such as the [multi-lingual relevance reranker](https://www.vectara.com/blog/deep-dive-into-vectara-multilingual-reranker-v1-state-of-the-art-reranker-across-100-languages), [MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/), [UDF reranker](https://www.vectara.com/blog/rag-with-user-defined-functions-based-reranking). +6. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations. For more information: - [Documentation](https://docs.vectara.com/docs/) @@ -22,7 +21,7 @@ For more information: ## Installation and Setup To use `Vectara` with LangChain no special installation steps are required. -To get started, [sign up](https://vectara.com/integrations/langchain) for a free Vectara account (if you don't already have one), +To get started, [sign up](https://vectara.com/integrations/langchain) for a free Vectara trial, and follow the [quickstart](https://docs.vectara.com/docs/quickstart) guide to create a corpus and an API key. Once you have these, you can provide them as arguments to the Vectara `vectorstore`, or you can set them as environment variables. diff --git a/docs/docs/integrations/providers/vectara/vectara_chat.ipynb b/docs/docs/integrations/providers/vectara/vectara_chat.ipynb index f31f7599a28003..652f58919086e2 100644 --- a/docs/docs/integrations/providers/vectara/vectara_chat.ipynb +++ b/docs/docs/integrations/providers/vectara/vectara_chat.ipynb @@ -7,19 +7,19 @@ "source": [ "# Vectara Chat\n", "\n", - "[Vectara](https://vectara.com/) provides a Trusted Generative AI platform, allowing organizations to rapidly create a ChatGPT-like experience (an AI assistant) which is grounded in the data, documents, and knowledge that they have (technically, it is Retrieval-Augmented-Generation-as-a-service). \n", + "[Vectara](https://vectara.com/) is the trusted AI Assistant and Agent platform which focuses on enterprise readiness for mission-critical applications.\n", "\n", "Vectara serverless RAG-as-a-service provides all the components of RAG behind an easy-to-use API, including:\n", "1. A way to extract text from files (PDF, PPT, DOCX, etc)\n", "2. ML-based chunking that provides state of the art performance.\n", "3. The [Boomerang](https://vectara.com/how-boomerang-takes-retrieval-augmented-generation-to-the-next-level-via-grounded-generation/) embeddings model.\n", "4. Its own internal vector database where text chunks and embedding vectors are stored.\n", - "5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments (including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) and [MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/))\n", - "7. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations.\n", + "5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments (including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) as well as multiple reranking options such as the [multi-lingual relevance reranker](https://www.vectara.com/blog/deep-dive-into-vectara-multilingual-reranker-v1-state-of-the-art-reranker-across-100-languages), [MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/), [UDF reranker](https://www.vectara.com/blog/rag-with-user-defined-functions-based-reranking). \n", + "6. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations.\n", "\n", "See the [Vectara API documentation](https://docs.vectara.com/docs/) for more information on how to use the API.\n", "\n", - "This notebook shows how to use Vectara's [Chat](https://docs.vectara.com/docs/api-reference/chat-apis/chat-apis-overview) functionality." + "This notebook shows how to use Vectara's [Chat](https://docs.vectara.com/docs/api-reference/chat-apis/chat-apis-overview) functionality, which provides automatic storage of conversation history and ensures follow up questions consider that history." ] }, { @@ -30,7 +30,7 @@ "# Getting Started\n", "\n", "To get started, use the following steps:\n", - "1. If you don't already have one, [Sign up](https://www.vectara.com/integrations/langchain) for your free Vectara account. Once you have completed your sign up you will have a Vectara customer ID. You can find your customer ID by clicking on your name, on the top-right of the Vectara console window.\n", + "1. If you don't already have one, [Sign up](https://www.vectara.com/integrations/langchain) for your free Vectara trial. Once you have completed your sign up you will have a Vectara customer ID. You can find your customer ID by clicking on your name, on the top-right of the Vectara console window.\n", "2. Within your account you can create one or more corpora. Each corpus represents an area that stores text data upon ingest from input documents. To create a corpus, use the **\"Create Corpus\"** button. You then provide a name to your corpus as well as a description. Optionally you can define filtering attributes and apply some advanced options. If you click on your created corpus, you can see its name and corpus ID right on the top.\n", "3. Next you'll need to create API keys to access the corpus. Click on the **\"Access Control\"** tab in the corpus view and then the **\"Create API Key\"** button. Give your key a name, and choose whether you want query-only or query+index for your key. Click \"Create\" and you now have an active API key. Keep this key confidential. \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 72e242b16d75c2..fe98c8f12a624a 100644 --- a/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb @@ -7,15 +7,15 @@ "source": [ "# Vectara self-querying \n", "\n", - "[Vectara](https://vectara.com/) provides a Trusted Generative AI platform, allowing organizations to rapidly create a ChatGPT-like experience (an AI assistant) which is grounded in the data, documents, and knowledge that they have (technically, it is Retrieval-Augmented-Generation-as-a-service). \n", + "[Vectara](https://vectara.com/) is the trusted AI Assistant and Agent platform which focuses on enterprise readiness for mission-critical applications.\n", "\n", "Vectara serverless RAG-as-a-service provides all the components of RAG behind an easy-to-use API, including:\n", "1. A way to extract text from files (PDF, PPT, DOCX, etc)\n", "2. ML-based chunking that provides state of the art performance.\n", "3. The [Boomerang](https://vectara.com/how-boomerang-takes-retrieval-augmented-generation-to-the-next-level-via-grounded-generation/) embeddings model.\n", "4. Its own internal vector database where text chunks and embedding vectors are stored.\n", - "5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments (including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) and [MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/))\n", - "7. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations.\n", + "5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments, including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) as well as multiple reranking options such as the [multi-lingual relevance reranker](https://www.vectara.com/blog/deep-dive-into-vectara-multilingual-reranker-v1-state-of-the-art-reranker-across-100-languages), [MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/), [UDF reranker](https://www.vectara.com/blog/rag-with-user-defined-functions-based-reranking). \n", + "6. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations.\n", "\n", "See the [Vectara API documentation](https://docs.vectara.com/docs/) for more information on how to use the API.\n", "\n", @@ -30,7 +30,7 @@ "# Getting Started\n", "\n", "To get started, use the following steps:\n", - "1. If you don't already have one, [Sign up](https://www.vectara.com/integrations/langchain) for your free Vectara account. Once you have completed your sign up you will have a Vectara customer ID. You can find your customer ID by clicking on your name, on the top-right of the Vectara console window.\n", + "1. If you don't already have one, [Sign up](https://www.vectara.com/integrations/langchain) for your free Vectara trial. Once you have completed your sign up you will have a Vectara customer ID. You can find your customer ID by clicking on your name, on the top-right of the Vectara console window.\n", "2. Within your account you can create one or more corpora. Each corpus represents an area that stores text data upon ingest from input documents. To create a corpus, use the **\"Create Corpus\"** button. You then provide a name to your corpus as well as a description. Optionally you can define filtering attributes and apply some advanced options. If you click on your created corpus, you can see its name and corpus ID right on the top.\n", "3. Next you'll need to create API keys to access the corpus. Click on the **\"Access Control\"** tab in the corpus view and then the **\"Create API Key\"** button. Give your key a name, and choose whether you want query-only or query+index for your key. Click \"Create\" and you now have an active API key. Keep this key confidential. \n", "\n", diff --git a/docs/docs/integrations/vectorstores/vectara.ipynb b/docs/docs/integrations/vectorstores/vectara.ipynb index d041d8b669a013..758ea4be83eddf 100644 --- a/docs/docs/integrations/vectorstores/vectara.ipynb +++ b/docs/docs/integrations/vectorstores/vectara.ipynb @@ -7,15 +7,15 @@ "source": [ "# Vectara\n", "\n", - "[Vectara](https://vectara.com/) provides a Trusted Generative AI platform, allowing organizations to rapidly create a ChatGPT-like experience (an AI assistant) which is grounded in the data, documents, and knowledge that they have (technically, it is Retrieval-Augmented-Generation-as-a-service). \n", + "[Vectara](https://vectara.com/) is the trusted AI Assistant and Agent platform which focuses on enterprise readiness for mission-critical applications.\n", "\n", "Vectara serverless RAG-as-a-service provides all the components of RAG behind an easy-to-use API, including:\n", "1. A way to extract text from files (PDF, PPT, DOCX, etc)\n", "2. ML-based chunking that provides state of the art performance.\n", "3. The [Boomerang](https://vectara.com/how-boomerang-takes-retrieval-augmented-generation-to-the-next-level-via-grounded-generation/) embeddings model.\n", "4. Its own internal vector database where text chunks and embedding vectors are stored.\n", - "5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments (including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) and [MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/))\n", - "7. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations.\n", + "5. A query service that automatically encodes the query into embedding, and retrieves the most relevant text segments (including support for [Hybrid Search](https://docs.vectara.com/docs/api-reference/search-apis/lexical-matching) as well as multiple reranking options such as the [multi-lingual relevance reranker](https://www.vectara.com/blog/deep-dive-into-vectara-multilingual-reranker-v1-state-of-the-art-reranker-across-100-languages), [MMR](https://vectara.com/get-diverse-results-and-comprehensive-summaries-with-vectaras-mmr-reranker/), [UDF reranker](https://www.vectara.com/blog/rag-with-user-defined-functions-based-reranking). \n", + "6. An LLM to for creating a [generative summary](https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-overview), based on the retrieved documents (context), including citations.\n", "\n", "See the [Vectara API documentation](https://docs.vectara.com/docs/) for more information on how to use the API.\n", "\n", @@ -32,7 +32,7 @@ "# Getting Started\n", "\n", "To get started, use the following steps:\n", - "1. If you don't already have one, [Sign up](https://www.vectara.com/integrations/langchain) for your free Vectara account. Once you have completed your sign up you will have a Vectara customer ID. You can find your customer ID by clicking on your name, on the top-right of the Vectara console window.\n", + "1. If you don't already have one, [Sign up](https://www.vectara.com/integrations/langchain) for your free Vectara trial. Once you have completed your sign up you will have a Vectara customer ID. You can find your customer ID by clicking on your name, on the top-right of the Vectara console window.\n", "2. Within your account you can create one or more corpora. Each corpus represents an area that stores text data upon ingest from input documents. To create a corpus, use the **\"Create Corpus\"** button. You then provide a name to your corpus as well as a description. Optionally you can define filtering attributes and apply some advanced options. If you click on your created corpus, you can see its name and corpus ID right on the top.\n", "3. Next you'll need to create API keys to access the corpus. Click on the **\"Access Control\"** tab in the corpus view and then the **\"Create API Key\"** button. Give your key a name, and choose whether you want query-only or query+index for your key. Click \"Create\" and you now have an active API key. Keep this key confidential. \n", "\n", diff --git a/docs/docs/tutorials/rag.ipynb b/docs/docs/tutorials/rag.ipynb index ef49ec4c40c2e4..72a366403ba9e4 100644 --- a/docs/docs/tutorials/rag.ipynb +++ b/docs/docs/tutorials/rag.ipynb @@ -502,7 +502,7 @@ "\n", "- [Docs](/docs/how_to/vectorstores): Detailed documentation on how to use vector stores.\n", "- [Integrations](/docs/integrations/vectorstores/): 40+ integrations to choose from.\n", - "- [Interface](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.VectorStore.html): API reference for the base interface.\n", + "- [Interface](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html): API reference for the base interface.\n", "\n", "This completes the **Indexing** portion of the pipeline. At this point\n", "we have a query-able vector store containing the chunked contents of our\n", diff --git a/docs/docs/tutorials/retrievers.ipynb b/docs/docs/tutorials/retrievers.ipynb index 9c9bd12e047417..e4024a53dde886 100644 --- a/docs/docs/tutorials/retrievers.ipynb +++ b/docs/docs/tutorials/retrievers.ipynb @@ -151,13 +151,13 @@ "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.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", + "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", "\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.VectorStore.html) includes methods for querying:\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", "- By string query and by vector;\n", "- With and without returning similarity scores;\n", - "- By similarity and [maximum marginal relevance](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.VectorStore.html#langchain_core.vectorstores.VectorStore.max_marginal_relevance_search) (to balance similarity with query to diversity in retrieved results).\n", + "- By similarity and [maximum marginal relevance](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html#langchain_core.vectorstores.base.VectorStore.max_marginal_relevance_search) (to balance similarity with query to diversity in retrieved results).\n", "\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", @@ -303,7 +303,7 @@ "source": [ "Learn more:\n", "\n", - "- [API reference](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.VectorStore.html)\n", + "- [API reference](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html)\n", "- [How-to guide](/docs/how_to/vectorstores)\n", "- [Integration-specific docs](/docs/integrations/vectorstores)\n", "\n", @@ -348,7 +348,7 @@ "id": "a36d3f64-a8bc-4baa-b2ea-07e324a0143e", "metadata": {}, "source": [ - "Vectorstores implement an `as_retriever` method that will generate a Retriever, specifically a [VectorStoreRetriever](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.VectorStoreRetriever.html). These retrievers include specific `search_type` and `search_kwargs` attributes that identify what methods of the underlying vector store to call, and how to parameterize them. For instance, we can replicate the above with the following:" + "Vectorstores implement an `as_retriever` method that will generate a Retriever, specifically a [VectorStoreRetriever](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStoreRetriever.html). These retrievers include specific `search_type` and `search_kwargs` attributes that identify what methods of the underlying vector store to call, and how to parameterize them. For instance, we can replicate the above with the following:" ] }, { diff --git a/docs/scripts/partner_pkg_table.py b/docs/scripts/partner_pkg_table.py index 6bc8b4badf7ac9..e5b4fd0eda37ce 100644 --- a/docs/scripts/partner_pkg_table.py +++ b/docs/scripts/partner_pkg_table.py @@ -76,7 +76,6 @@ CUSTOM_NAME = { "google-genai": "Google Generative AI", "aws": "AWS", - "airbyte": "Airbyte", "ibm": "IBM", } CUSTOM_PROVIDER_PAGES = { diff --git a/docs/sidebars.js b/docs/sidebars.js index 94daa97f1f709f..62d53f91a3e61d 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -50,7 +50,7 @@ module.exports = { { type: "category", link: {type: 'doc', id: 'concepts/index'}, - label: "Conceptual Guide", + label: "Conceptual guide", collapsible: false, items: [{ type: 'autogenerated', diff --git a/docs/src/theme/FeatureTables.js b/docs/src/theme/FeatureTables.js index 94b179113bb8c9..7217c245a12c9d 100644 --- a/docs/src/theme/FeatureTables.js +++ b/docs/src/theme/FeatureTables.js @@ -300,6 +300,12 @@ const FEATURE_TABLES = { package: "langchain-google_vertexai", apiLink: "https://python.langchain.com/api_reference/google_vertexai/llms/langchain_google_vertexai.llms.VertexAI.html" }, + { + name: "NVIDIA", + link: "NVIDIA", + package: "langchain-nvidia", + apiLink: "https://python.langchain.com/api_reference/nvidia_ai_endpoints/llm/langchain_nvidia_ai_endpoints.llm.NVIDIA.html" + }, ], }, text_embedding: { @@ -387,6 +393,12 @@ const FEATURE_TABLES = { package: "langchain-ibm", apiLink: "https://python.langchain.com/api_reference/ibm/embeddings/langchain_ibm.embeddings.WatsonxEmbeddings.html" }, + { + name: "NVIDIA", + link: "NVIDIAEmbeddings", + package: "langchain-nvidia", + apiLink: "https://python.langchain.com/api_reference/nvidia_ai_endpoints/embeddings/langchain_nvidia_ai_endpoints.embeddings.NVIDIAEmbeddings.html" + }, ] }, document_retrievers: { diff --git a/docs/vercel.json b/docs/vercel.json index 1f2aa98c786e82..4f368093c5aeda 100644 --- a/docs/vercel.json +++ b/docs/vercel.json @@ -87,7 +87,7 @@ "destination": "/docs/integrations/providers/:path*" }, { - "source": "/docs/troubleshooting/errors/:path((?:GRAPH_RECURSION_LIMIT|INVALID_CONCURRENT_GRAPH_UPDATE|INVALID_GRAPH_NODE_RETURN_VALUE|MULTIPLE_SUBGRAPHS)/?)*", + "source": "/docs/troubleshooting/errors/:path((?:GRAPH_RECURSION_LIMIT|INVALID_CONCURRENT_GRAPH_UPDATE|INVALID_GRAPH_NODE_RETURN_VALUE|MULTIPLE_SUBGRAPHS|INVALID_CHAT_HISTORY)/?)*", "destination": "https://langchain-ai.github.io/langgraph/troubleshooting/errors/:path*" }, { diff --git a/libs/cli/langchain_cli/integration_template/pyproject.toml b/libs/cli/langchain_cli/integration_template/pyproject.toml index 5f50f0c54d066b..efdcb9efeadcde 100644 --- a/libs/cli/langchain_cli/integration_template/pyproject.toml +++ b/libs/cli/langchain_cli/integration_template/pyproject.toml @@ -1,3 +1,7 @@ +[build-system] +requires = [ "poetry-core>=1.0.0",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "__package_name__" version = "0.1.0" @@ -7,82 +11,68 @@ readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/__package_name_short__" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22__package_name_short__%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" + +[tool.ruff.lint] +select = [ "E", "F", "I", "T201",] + +[tool.coverage.run] +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",] +asyncio_mode = "auto" [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.4.3" pytest-asyncio = "^0.23.2" pytest-socket = "^0.7.0" -langchain-core = { path = "../../core", develop = true } pytest-watcher = "^0.3.4" -[tool.poetry.group.codespell] -optional = true - [tool.poetry.group.codespell.dependencies] codespell = "^2.2.6" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.5" [tool.poetry.group.typing.dependencies] mypy = "^1.10" -langchain-core = { path = "../../core", develop = true } -[tool.poetry.group.dev] -optional = true +[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.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -addopts = "--strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/cli/langchain_cli/package_template/pyproject.toml b/libs/cli/langchain_cli/package_template/pyproject.toml index c3e4e08acf3c03..3a6ab95f439ffd 100644 --- a/libs/cli/langchain_cli/package_template/pyproject.toml +++ b/libs/cli/langchain_cli/package_template/pyproject.toml @@ -1,3 +1,7 @@ +[build-system] +requires = [ "poetry-core",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "__package_name__" version = "0.0.1" @@ -5,21 +9,16 @@ description = "" authors = [] readme = "README.md" +[tool.langserve] +export_module = "__module_name__" +export_attr = "chain" + [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" langchain-openai = ">=0.0.1" - [tool.poetry.group.dev.dependencies] langchain-cli = ">=0.0.4" fastapi = "^0.104.0" sse-starlette = "^1.6.5" - -[tool.langserve] -export_module = "__module_name__" -export_attr = "chain" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py b/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py index 424d967abbf1ef..113ff9be53c703 100644 --- a/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py +++ b/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py @@ -51,7 +51,7 @@ class PowerBIToolkit(BaseToolkit): examples: Optional. The examples for the prompt. Default is None. max_iterations: Optional. The maximum iterations to run. Default is 5. callback_manager: Optional. The callback manager. Default is None. - output_token_limit: Optional. The output token limit. Default is None. + output_token_limit: The output token limit. Default is 4000. tiktoken_model_name: Optional. The TikToken model name. Default is None. """ @@ -60,7 +60,7 @@ class PowerBIToolkit(BaseToolkit): examples: Optional[str] = None max_iterations: int = 5 callback_manager: Optional[BaseCallbackManager] = None - output_token_limit: Optional[int] = None + output_token_limit: int = 4000 tiktoken_model_name: Optional[str] = None model_config = ConfigDict( diff --git a/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py b/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py index 741528d9152888..93f32e9a83e58e 100644 --- a/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py +++ b/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py @@ -68,9 +68,16 @@ def convert_message_to_dict(message: BaseMessage) -> dict: message_dict = {"role": "assistant", "content": message.content} if "function_call" in message.additional_kwargs: message_dict["function_call"] = message.additional_kwargs["function_call"] - # If function call only, content is None not empty string - if message_dict["content"] == "": - message_dict["content"] = None + elif len(message.tool_calls) != 0: + tool_call = message.tool_calls[0] + message_dict["function_call"] = { + "name": tool_call["name"], + "args": tool_call["args"], + } + + # If function call only, content is None not empty string + if "function_call" in message_dict and message_dict["content"] == "": + message_dict["content"] = None elif isinstance(message, (FunctionMessage, ToolMessage)): message_dict = { "role": "function", diff --git a/libs/community/langchain_community/embeddings/ovhcloud.py b/libs/community/langchain_community/embeddings/ovhcloud.py index 5786a761f49fe1..49b9cbfa21097d 100644 --- a/libs/community/langchain_community/embeddings/ovhcloud.py +++ b/libs/community/langchain_community/embeddings/ovhcloud.py @@ -1,3 +1,4 @@ +import json import logging import time from typing import Any, List @@ -41,17 +42,55 @@ def _generate_embedding(self, text: str) -> List[float]: Returns: List[float]: Embeddings for the text. """ + + return self._send_request_to_ai_endpoints("text/plain", text, "text2vec") + + def embed_documents(self, texts: List[str]) -> List[List[float]]: + """Embed a list of documents. + Args: + texts (List[str]): The list of texts to embed. + + Returns: + List[List[float]]: List of embeddings, one for each input text. + + """ + + return self._send_request_to_ai_endpoints( + "application/json", json.dumps(texts), "batch_text2vec" + ) + + def embed_query(self, text: str) -> List[float]: + """Embed a single query text. + Args: + text (str): The text to embed. + Returns: + List[float]: Embeddings for the text. + """ + return self._generate_embedding(text) + + def _send_request_to_ai_endpoints( + self, contentType: str, payload: str, route: str + ) -> Any: + """Send a HTTPS request to OVHcloud AI Endpoints + Args: + contentType (str): The content type of the request, application/json or text/plain. + payload (str): The payload of the request. + route (str): The route of the request, batch_text2vec or text2vec. + """ # noqa: E501 headers = { - "content-type": "text/plain", + "content-type": contentType, "Authorization": f"Bearer {self.access_token}", } session = requests.session() while True: response = session.post( - f"https://{self.model_name}.endpoints.{self.region}.ai.cloud.ovh.net/api/text2vec", + ( + f"https://{self.model_name}.endpoints.{self.region}" + f".ai.cloud.ovh.net/api/{route}" + ), headers=headers, - data=text, + data=payload, ) if response.status_code != 200: if response.status_code == 429: @@ -74,22 +113,3 @@ def _generate_embedding(self, text: str) -> List[float]: ) ) return response.json() - - def embed_documents(self, texts: List[str]) -> List[List[float]]: - """Create a retry decorator for PremAIEmbeddings. - Args: - texts (List[str]): The list of texts to embed. - - Returns: - List[List[float]]: List of embeddings, one for each input text. - """ - return [self._generate_embedding(text) for text in texts] - - def embed_query(self, text: str) -> List[float]: - """Embed a single query text. - Args: - text (str): The text to embed. - Returns: - List[float]: Embeddings for the text. - """ - return self._generate_embedding(text) diff --git a/libs/community/langchain_community/graph_vectorstores/base.py b/libs/community/langchain_community/graph_vectorstores/base.py index 0a320d98f9eca9..3c0d81b915f48b 100644 --- a/libs/community/langchain_community/graph_vectorstores/base.py +++ b/libs/community/langchain_community/graph_vectorstores/base.py @@ -8,6 +8,7 @@ ClassVar, Optional, Sequence, + cast, ) from langchain_core._api import beta @@ -701,7 +702,7 @@ def as_retriever(self, **kwargs: Any) -> GraphVectorStoreRetriever: docsearch.as_retriever(search_kwargs={'k': 1}) """ - return GraphVectorStoreRetriever(vector_store=self, **kwargs) + return GraphVectorStoreRetriever(vectorstore=self, **kwargs) @beta(message="Added in version 0.3.1 of langchain_community. API subject to change.") @@ -837,8 +838,8 @@ class GraphVectorStoreRetriever(VectorStoreRetriever): retriever = graph_vectorstore.as_retriever(search_kwargs={"score_threshold": 0.5}) """ # noqa: E501 - vector_store: GraphVectorStore - """GraphVectorStore to use for retrieval.""" + vectorstore: VectorStore + """VectorStore to use for retrieval.""" search_type: str = "traversal" """Type of search to perform. Defaults to "traversal".""" allowed_search_types: ClassVar[Collection[str]] = ( @@ -849,14 +850,20 @@ class GraphVectorStoreRetriever(VectorStoreRetriever): "mmr_traversal", ) + @property + def graph_vectorstore(self) -> GraphVectorStore: + return cast(GraphVectorStore, self.vectorstore) + def _get_relevant_documents( self, query: str, *, run_manager: CallbackManagerForRetrieverRun ) -> list[Document]: if self.search_type == "traversal": - return list(self.vector_store.traversal_search(query, **self.search_kwargs)) + return list( + self.graph_vectorstore.traversal_search(query, **self.search_kwargs) + ) elif self.search_type == "mmr_traversal": return list( - self.vector_store.mmr_traversal_search(query, **self.search_kwargs) + self.graph_vectorstore.mmr_traversal_search(query, **self.search_kwargs) ) else: return super()._get_relevant_documents(query, run_manager=run_manager) @@ -867,14 +874,14 @@ async def _aget_relevant_documents( if self.search_type == "traversal": return [ doc - async for doc in self.vector_store.atraversal_search( + async for doc in self.graph_vectorstore.atraversal_search( query, **self.search_kwargs ) ] elif self.search_type == "mmr_traversal": return [ doc - async for doc in self.vector_store.ammr_traversal_search( + async for doc in self.graph_vectorstore.ammr_traversal_search( query, **self.search_kwargs ) ] diff --git a/libs/community/langchain_community/vectorstores/vectara.py b/libs/community/langchain_community/vectorstores/vectara.py index b71e7d12cff8b3..7e77c6e69052c5 100644 --- a/libs/community/langchain_community/vectorstores/vectara.py +++ b/libs/community/langchain_community/vectorstores/vectara.py @@ -22,6 +22,7 @@ MMR_RERANKER_ID = 272725718 RERANKER_MULTILINGUAL_V1_ID = 272725719 +UDF_RERANKER_ID = 272725722 @dataclass @@ -38,7 +39,7 @@ class SummaryConfig: is_enabled: bool = False max_results: int = 7 response_lang: str = "eng" - prompt_name: str = "vectara-summary-ext-v1.2.0" + prompt_name: str = "vectara-summary-ext-24-05-med-omni" stream: bool = False @@ -67,7 +68,7 @@ class MMRConfig: class RerankConfig: """Configuration for Reranker. - reranker: "mmr", "rerank_multilingual_v1" or "none" + reranker: "mmr", "rerank_multilingual_v1", "udf" or "none" rerank_k: number of results to fetch before reranking, defaults to 50 mmr_diversity_bias: for MMR only - a number between 0 and 1 that determines the degree of diversity among the results with 0 corresponding @@ -76,11 +77,13 @@ class RerankConfig: Note: mmr_diversity_bias is equivalent 1-lambda_mult where lambda_mult is the value often used in max_marginal_relevance_search() We chose to use that since we believe it's more intuitive to the user. + user_function: for UDF only - the user function to use for reranking. """ reranker: str = "none" rerank_k: int = 50 mmr_diversity_bias: float = 0.3 + user_function: str = "" @dataclass @@ -445,7 +448,7 @@ def _get_query_body( config.rerank_config.rerank_k if ( config.rerank_config.reranker - in ["mmr", "rerank_multilingual_v1"] + in ["mmr", "udf", "rerank_multilingual_v1"] ) else config.k ), @@ -473,6 +476,11 @@ def _get_query_body( "rerankerId": MMR_RERANKER_ID, "mmrConfig": {"diversityBias": config.rerank_config.mmr_diversity_bias}, } + elif config.rerank_config.reranker == "udf": + body["query"][0]["rerankingConfig"] = { + "rerankerId": UDF_RERANKER_ID, + "userFunction": config.rerank_config.user_function, + } elif config.rerank_config.reranker == "rerank_multilingual_v1": body["query"][0]["rerankingConfig"] = { "rerankerId": RERANKER_MULTILINGUAL_V1_ID, diff --git a/libs/community/poetry.lock b/libs/community/poetry.lock index 2dbe93a155af5c..beeae92b1e4c98 100644 --- a/libs/community/poetry.lock +++ b/libs/community/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 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -1840,7 +1840,7 @@ develop = true [package.dependencies] aiohttp = "^3.8.3" async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""} -langchain-core = "^0.3.14" +langchain-core = "^0.3.15" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" numpy = [ @@ -1859,7 +1859,7 @@ url = "../langchain" [[package]] name = "langchain-core" -version = "0.3.14" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -1893,7 +1893,7 @@ develop = true [package.dependencies] httpx = "^0.27.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" pytest = ">=7,<9" syrupy = "^4" @@ -1911,7 +1911,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" [package.source] type = "directory" @@ -2529,30 +2529,41 @@ files = [ {file = "pandas-2.2.3-cp310-cp310-macosx_11_0_arm64.whl", hash = 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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 = "0.3.4" +version = "0.3.5" 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 = "^0.3.14" +langchain-core = "^0.3.15" langchain = "^0.3.6" -SQLAlchemy = ">=1.4,<2.0.36" # TODO(ccurme): https://github.com/Mause/duckdb_engine/issues/1128 +SQLAlchemy = ">=1.4,<2.0.36" requests = "^2" PyYAML = ">=5.3" aiohttp = "^3.8.3" @@ -44,7 +41,6 @@ dataclasses-json = ">= 0.5.7, < 0.7" pydantic-settings = "^2.4.0" langsmith = "^0.1.125" httpx-sse = "^0.4.0" - [[tool.poetry.dependencies.numpy]] version = "^1" python = "<3.12" @@ -54,24 +50,16 @@ version = "^1.26.0" 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 @@ -103,12 +91,13 @@ pytest-mock = "^3.10.0" pytest-socket = "^0.6.0" syrupy = "^4.0.2" requests-mock = "^1.11.0" -# TODO: hack to fix 3.9 builds -cffi = [ - { version = "<1.17.1", python = "<3.10" }, - { version = "*", python = ">=3.10" }, -] +[[tool.poetry.group.test.dependencies.cffi]] +version = "<1.17.1" +python = "<3.10" +[[tool.poetry.group.test.dependencies.cffi]] +version = "*" +python = ">=3.10" [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" @@ -119,12 +108,13 @@ vcrpy = "^6" [tool.poetry.group.lint.dependencies] ruff = "^0.5" -# TODO: hack to fix 3.9 builds -cffi = [ - { version = "<1.17.1", python = "<3.10" }, - { version = "*", python = ">=3.10" }, -] +[[tool.poetry.group.lint.dependencies.cffi]] +version = "<1.17.1" +python = "<3.10" +[[tool.poetry.group.lint.dependencies.cffi]] +version = "*" +python = ">=3.10" [tool.poetry.group.dev.dependencies] jupyter = "^1.0.0" diff --git a/libs/community/tests/integration_tests/graph_vectorstores/test_cassandra.py b/libs/community/tests/integration_tests/graph_vectorstores/test_cassandra.py index d55f5469e546ad..337497a528446c 100644 --- a/libs/community/tests/integration_tests/graph_vectorstores/test_cassandra.py +++ b/libs/community/tests/integration_tests/graph_vectorstores/test_cassandra.py @@ -440,6 +440,17 @@ def test_gvs_traversal_search_sync( ts_labels = {doc.metadata["label"] for doc in ts_response} assert ts_labels == {"AR", "A0", "BR", "B0", "TR", "T0"} + # verify the same works as a retriever + retriever = g_store.as_retriever( + search_type="traversal", search_kwargs={"k": 2, "depth": 2} + ) + + ts_labels = { + doc.metadata["label"] + for doc in retriever.get_relevant_documents(query="[2, 10]") + } + assert ts_labels == {"AR", "A0", "BR", "B0", "TR", "T0"} + async def test_gvs_traversal_search_async( self, populated_graph_vector_store_d2: CassandraGraphVectorStore, @@ -453,6 +464,17 @@ async def test_gvs_traversal_search_async( # so ordering is not deterministic: assert ts_labels == {"AR", "A0", "BR", "B0", "TR", "T0"} + # verify the same works as a retriever + retriever = g_store.as_retriever( + search_type="traversal", search_kwargs={"k": 2, "depth": 2} + ) + + ts_labels = { + doc.metadata["label"] + for doc in await retriever.aget_relevant_documents(query="[2, 10]") + } + assert ts_labels == {"AR", "A0", "BR", "B0", "TR", "T0"} + def test_gvs_mmr_traversal_search_sync( self, populated_graph_vector_store_d2: CassandraGraphVectorStore, diff --git a/libs/community/tests/integration_tests/vectorstores/test_vectara.py b/libs/community/tests/integration_tests/vectorstores/test_vectara.py index d8f557bc6d1cb9..958fda1087c84f 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_vectara.py +++ b/libs/community/tests/integration_tests/vectorstores/test_vectara.py @@ -22,7 +22,7 @@ # VECTARA_API_KEY, VECTARA_CORPUS_ID and VECTARA_CUSTOMER_ID # -test_prompt_name = "vectara-experimental-summary-ext-2023-12-11-sml" +test_prompt_name = "vectara-summary-ext-24-05-med-omni" def get_abbr(s: str) -> str: @@ -299,8 +299,36 @@ def test_vectara_with_langchain_mmr(vectara3: Vectara) -> None: # type: ignore[ ) -def test_vectara_mmr(vectara3: Vectara) -> None: # type: ignore[no-untyped-def] - # test MMR directly with rerank_config +def test_vectara_rerankers(vectara3: Vectara) -> None: # type: ignore[no-untyped-def] + # test Vectara multi-lingual reranker + summary_config = SummaryConfig(is_enabled=True, max_results=7, response_lang="eng") + rerank_config = RerankConfig(reranker="rerank_multilingual_v1", rerank_k=50) + config = VectaraQueryConfig( + k=10, + lambda_val=0.005, + rerank_config=rerank_config, + summary_config=summary_config, + ) + rag = vectara3.as_rag(config) + output1 = rag.invoke("what is generative AI?")["answer"] + assert len(output1) > 0 + + # test Vectara udf reranker + summary_config = SummaryConfig(is_enabled=True, max_results=7, response_lang="eng") + rerank_config = RerankConfig( + reranker="udf", rerank_k=50, user_function="get('$.score')" + ) + config = VectaraQueryConfig( + k=10, + lambda_val=0.005, + rerank_config=rerank_config, + summary_config=summary_config, + ) + rag = vectara3.as_rag(config) + output1 = rag.invoke("what is generative AI?")["answer"] + assert len(output1) > 0 + + # test Vectara MMR reranker summary_config = SummaryConfig(is_enabled=True, max_results=7, response_lang="eng") rerank_config = RerankConfig(reranker="mmr", rerank_k=50, mmr_diversity_bias=0.2) config = VectaraQueryConfig( diff --git a/libs/core/langchain_core/output_parsers/list.py b/libs/core/langchain_core/output_parsers/list.py index 858ba86c79fa2f..ebaca8f8ca94f8 100644 --- a/libs/core/langchain_core/output_parsers/list.py +++ b/libs/core/langchain_core/output_parsers/list.py @@ -1,9 +1,11 @@ from __future__ import annotations +import csv import re from abc import abstractmethod from collections import deque from collections.abc import AsyncIterator, Iterator +from io import StringIO from typing import Optional as Optional from typing import TypeVar, Union @@ -162,7 +164,14 @@ def parse(self, text: str) -> list[str]: Returns: A list of strings. """ - return [part.strip() for part in text.split(",")] + try: + reader = csv.reader( + StringIO(text), quotechar='"', delimiter=",", skipinitialspace=True + ) + return [item for sublist in reader for item in sublist] + except csv.Error: + # keep old logic for backup + return [part.strip() for part in text.split(",")] @property def _type(self) -> str: diff --git a/libs/core/tests/unit_tests/output_parsers/test_list_parser.py b/libs/core/tests/unit_tests/output_parsers/test_list_parser.py index 3f43edfa2aed83..11bd11b6a0b92e 100644 --- a/libs/core/tests/unit_tests/output_parsers/test_list_parser.py +++ b/libs/core/tests/unit_tests/output_parsers/test_list_parser.py @@ -64,6 +64,25 @@ def test_multiple_items() -> None: assert list(parser.transform(iter([text]))) == [[a] for a in expected] +def test_multiple_items_with_comma() -> None: + """Test that a string with multiple comma-separated items with 1 item containing a + comma is parsed to a list.""" + parser = CommaSeparatedListOutputParser() + text = '"foo, foo2",bar,baz' + expected = ["foo, foo2", "bar", "baz"] + + assert parser.parse(text) == expected + assert add(parser.transform(t for t in text)) == expected + assert list(parser.transform(t for t in text)) == [[a] for a in expected] + assert list(parser.transform(t for t in text.splitlines(keepends=True))) == [ + [a] for a in expected + ] + assert list( + parser.transform(" " + t if i > 0 else t for i, t in enumerate(text.split(" "))) + ) == [[a] for a in expected] + assert list(parser.transform(iter([text]))) == [[a] for a in expected] + + def test_numbered_list() -> None: parser = NumberedListOutputParser() text1 = ( diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index bc6600b5932e90..3ceb6d136b1bce 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/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 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -1988,7 +1988,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.14" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -2013,7 +2013,7 @@ url = "../core" [[package]] name = "langchain-openai" -version = "0.2.4" +version = "0.2.5" description = "An integration package connecting OpenAI and LangChain" optional = true python-versions = ">=3.9,<4.0" @@ -2021,7 +2021,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" openai = "^1.52.0" tiktoken = ">=0.7,<1" @@ -2058,7 +2058,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" [package.source] type = "directory" @@ -4073,14 +4073,61 @@ description = "Database Abstraction Library" optional = false python-versions = ">=3.7" files = [ + {file = 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"7d093bafda2acfc3eae68b365b8a9d3801ad77d6cd47aa8dd3cb8298e3168cb3" diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml index 4fe14479baeb8c..79fb6cb232565d 100644 --- a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain" -version = "0.3.6" +version = "0.3.7" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -33,7 +33,7 @@ langchain-server = "langchain.server:main" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.14" +langchain-core = "^0.3.15" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" pydantic = "^2.7.4" diff --git a/libs/packages.yml b/libs/packages.yml index 994bb3a718637e..8f9a16d2f48bd4 100644 --- a/libs/packages.yml +++ b/libs/packages.yml @@ -23,10 +23,6 @@ packages: - name: langchain-ai21 repo: langchain-ai/langchain-ai21 path: libs/ai21 - - name: langchain-airbyte - repo: langchain-ai/langchain - path: libs/partners/airbyte - disabled: true # dependency issues / stale - name: langchain-anthropic repo: langchain-ai/langchain path: libs/partners/anthropic diff --git a/libs/partners/airbyte/.gitignore b/libs/partners/airbyte/.gitignore deleted file mode 100644 index bee8a64b79a995..00000000000000 --- a/libs/partners/airbyte/.gitignore +++ /dev/null @@ -1 +0,0 @@ -__pycache__ diff --git a/libs/partners/airbyte/LICENSE b/libs/partners/airbyte/LICENSE deleted file mode 100644 index fc0602feecdd67..00000000000000 --- a/libs/partners/airbyte/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2024 LangChain, Inc. - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/libs/partners/airbyte/Makefile b/libs/partners/airbyte/Makefile deleted file mode 100644 index 82e64b38398154..00000000000000 --- a/libs/partners/airbyte/Makefile +++ /dev/null @@ -1,59 +0,0 @@ -.PHONY: all format lint test tests integration_tests docker_tests help extended_tests - -# Default target executed when no arguments are given to make. -all: help - -# Define a variable for the test file path. -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) - -test_watch: - poetry run ptw --snapshot-update --now . -- -vv $(TEST_FILE) - - -###################### -# LINTING AND FORMATTING -###################### - -# Define a variable for Python and notebook files. -PYTHON_FILES=. -MYPY_CACHE=.mypy_cache -lint format: PYTHON_FILES=. -lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/airbyte --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$') -lint_package: PYTHON_FILES=langchain_airbyte -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 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) - -spell_check: - poetry run codespell --toml pyproject.toml - -spell_fix: - poetry run codespell --toml pyproject.toml -w - -check_imports: $(shell find langchain_airbyte -name '*.py') - poetry run python ./scripts/check_imports.py $^ - -###################### -# HELP -###################### - -help: - @echo '----' - @echo 'check_imports - check imports' - @echo 'format - run code formatters' - @echo 'lint - run linters' - @echo 'test - run unit tests' - @echo 'tests - run unit tests' - @echo 'test TEST_FILE= - run all tests in file' diff --git a/libs/partners/airbyte/README.md b/libs/partners/airbyte/README.md deleted file mode 100644 index b5c5b5f67397d4..00000000000000 --- a/libs/partners/airbyte/README.md +++ /dev/null @@ -1,27 +0,0 @@ -# langchain-airbyte - -This package contains the LangChain integration with Airbyte - -## Installation - -```bash -pip install -U langchain-airbyte -``` - -The integration package doesn't have any global environment variables that need to be -set, but some integrations (e.g. `source-github`) may need credentials passed in. - -## Document Loaders - -`AirbyteLoader` class exposes a single document loader for Airbyte sources. - -```python -from langchain_airbyte import AirbyteLoader - -loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 100}, -) -docs = loader.load() -``` diff --git a/libs/partners/airbyte/langchain_airbyte/__init__.py b/libs/partners/airbyte/langchain_airbyte/__init__.py deleted file mode 100644 index cf3c11697c0256..00000000000000 --- a/libs/partners/airbyte/langchain_airbyte/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from langchain_airbyte.document_loaders import AirbyteLoader - -__all__ = ["AirbyteLoader"] diff --git a/libs/partners/airbyte/langchain_airbyte/document_loaders.py b/libs/partners/airbyte/langchain_airbyte/document_loaders.py deleted file mode 100644 index 08b1513d54cbcd..00000000000000 --- a/libs/partners/airbyte/langchain_airbyte/document_loaders.py +++ /dev/null @@ -1,127 +0,0 @@ -"""Airbyte vector stores.""" - -from __future__ import annotations - -from typing import ( - TYPE_CHECKING, - Any, - AsyncIterator, - Dict, - Iterator, - List, - Mapping, - Optional, - TypeVar, -) - -import airbyte as ab -from langchain_core.documents import Document -from langchain_core.prompts import PromptTemplate -from langchain_core.runnables import run_in_executor -from langchain_core.vectorstores import VectorStore - -if TYPE_CHECKING: - from langchain_text_splitters import TextSplitter - -VST = TypeVar("VST", bound=VectorStore) - - -class AirbyteLoader: - """Airbyte Document Loader. - - Example: - .. code-block:: python - - from langchain_airbyte import AirbyteLoader - - loader = AirbyteLoader( - source="github", - stream="pull_requests", - ) - documents = loader.lazy_load() - """ - - def __init__( - self, - source: str, - stream: str, - *, - config: Optional[Dict] = None, - include_metadata: bool = True, - template: Optional[PromptTemplate] = None, - ): - self._airbyte_source = ab.get_source(source, config=config, streams=[stream]) - self._stream = stream - self._template = template - self._include_metadata = include_metadata - - def load(self) -> List[Document]: - """Load source data into Document objects.""" - return list(self.lazy_load()) - - def load_and_split( - self, text_splitter: Optional[TextSplitter] = None - ) -> List[Document]: - """Load Documents and split into chunks. Chunks are returned as Documents. - - Args: - text_splitter: TextSplitter instance to use for splitting documents. - Defaults to RecursiveCharacterTextSplitter. - - Returns: - List of Documents. - """ - - if text_splitter is None: - try: - from langchain_text_splitters import RecursiveCharacterTextSplitter - except ImportError as e: - raise ImportError( - "Unable to import from langchain_text_splitters. Please specify " - "text_splitter or install langchain_text_splitters with " - "`pip install -U langchain-text-splitters`." - ) from e - _text_splitter: TextSplitter = RecursiveCharacterTextSplitter() - else: - _text_splitter = text_splitter - docs = self.lazy_load() - return _text_splitter.split_documents(docs) - - def lazy_load(self) -> Iterator[Document]: - """A lazy loader for Documents.""" - # if no prompt template defined, use default airbyte documents - if not self._template: - for document in self._airbyte_source.get_documents(self._stream): - # convert airbyte document to langchain document - metadata = ( - {} - if not self._include_metadata - else { - **document.metadata, - "_last_modified": document.last_modified, - "_id": document.id, - } - ) - yield Document( - page_content=document.content, - metadata=metadata, - ) - else: - records: Iterator[Mapping[str, Any]] = self._airbyte_source.get_records( - self._stream - ) - for record in records: - metadata = {} if not self._include_metadata else dict(record) - yield Document( - page_content=self._template.format(**record), metadata=metadata - ) - - async def alazy_load(self) -> AsyncIterator[Document]: - """A lazy loader for Documents.""" - iterator = await run_in_executor(None, self.lazy_load) - done = object() - while True: - doc = await run_in_executor(None, next, iterator, done) # type: ignore[call-arg, arg-type] - if doc is done: - break - yield doc # type: ignore[misc] diff --git a/libs/partners/airbyte/langchain_airbyte/py.typed b/libs/partners/airbyte/langchain_airbyte/py.typed deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/libs/partners/airbyte/poetry.lock b/libs/partners/airbyte/poetry.lock deleted file mode 100644 index feda0d3091fcb7..00000000000000 --- a/libs/partners/airbyte/poetry.lock +++ /dev/null @@ -1,2940 +0,0 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. - -[[package]] -name = "aiohttp" -version = "3.9.5" -description = "Async http client/server framework (asyncio)" -optional = false -python-versions = ">=3.8" -files = [ - 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-[package.dependencies] -idna = ">=2.0" -multidict = ">=4.0" - -[metadata] -lock-version = "2.0" -python-versions = ">=3.9,<3.12.4" -content-hash = "2f0f83ffdf5ce990513760a4f1e6544ef7e133bd69f10263af39d148bc9dbdbd" diff --git a/libs/partners/airbyte/pyproject.toml b/libs/partners/airbyte/pyproject.toml deleted file mode 100644 index b122c46f89e97f..00000000000000 --- a/libs/partners/airbyte/pyproject.toml +++ /dev/null @@ -1,88 +0,0 @@ -[tool.poetry] -name = "langchain-airbyte" -version = "0.1.1" -description = "An integration package connecting Airbyte and LangChain" -authors = [] -readme = "README.md" -repository = "https://github.com/langchain-ai/langchain" -license = "MIT" - -[tool.poetry.urls] -"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/airbyte" -"Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-airbyte%3D%3D0%22&expanded=true" - -[tool.poetry.dependencies] -python = ">=3.9,<3.12.4" -langchain-core = "^0.3.0.dev" -airbyte = "^0.7.3" -pydantic = ">=1.10.8,<2" - -[tool.poetry.group.test] -optional = true - -[tool.poetry.group.test.dependencies] -pytest = "^7.4.3" -pytest-asyncio = "^0.23.2" -langchain-core = { path = "../../core", develop = true } - -[tool.poetry.group.codespell] -optional = true - -[tool.poetry.group.codespell.dependencies] -codespell = "^2.2.6" - -[tool.poetry.group.test_integration] -optional = true - -[tool.poetry.group.test_integration.dependencies] - -[tool.poetry.group.lint] -optional = true - -[tool.poetry.group.lint.dependencies] -ruff = "^0.1.8" - -[tool.poetry.group.typing.dependencies] -mypy = "^1.7.1" -langchain-core = { path = "../../core", develop = true } -langchain-text-splitters = { path = "../../text-splitters", develop = true } -langchain = { path = "../../langchain", develop = true } - -[tool.poetry.group.dev] -optional = true - -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } - -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -addopts = "--strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" diff --git a/libs/partners/airbyte/scripts/check_imports.py b/libs/partners/airbyte/scripts/check_imports.py deleted file mode 100644 index 58a460c1493530..00000000000000 --- a/libs/partners/airbyte/scripts/check_imports.py +++ /dev/null @@ -1,17 +0,0 @@ -import sys -import traceback -from importlib.machinery import SourceFileLoader - -if __name__ == "__main__": - files = sys.argv[1:] - has_failure = False - for file in files: - try: - SourceFileLoader("x", file).load_module() - except Exception: - has_failure = True - print(file) # noqa: T201 - traceback.print_exc() - print() # noqa: T201 - - sys.exit(1 if has_failure else 0) diff --git a/libs/partners/airbyte/scripts/lint_imports.sh b/libs/partners/airbyte/scripts/lint_imports.sh deleted file mode 100755 index 19ccec1480c01a..00000000000000 --- a/libs/partners/airbyte/scripts/lint_imports.sh +++ /dev/null @@ -1,18 +0,0 @@ -#!/bin/bash - -set -eu - -# Initialize a variable to keep track of errors -errors=0 - -# make sure not importing from langchain, langchain_experimental, or langchain_community -git --no-pager grep '^from langchain\.' . && errors=$((errors+1)) -git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1)) -git --no-pager grep '^from langchain_community\.' . && errors=$((errors+1)) - -# Decide on an exit status based on the errors -if [ "$errors" -gt 0 ]; then - exit 1 -else - exit 0 -fi diff --git a/libs/partners/airbyte/tests/__init__.py b/libs/partners/airbyte/tests/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/libs/partners/airbyte/tests/integration_tests/__init__.py b/libs/partners/airbyte/tests/integration_tests/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/libs/partners/airbyte/tests/integration_tests/test_compile.py b/libs/partners/airbyte/tests/integration_tests/test_compile.py deleted file mode 100644 index 33ecccdfa0fbda..00000000000000 --- a/libs/partners/airbyte/tests/integration_tests/test_compile.py +++ /dev/null @@ -1,7 +0,0 @@ -import pytest - - -@pytest.mark.compile -def test_placeholder() -> None: - """Used for compiling integration tests without running any real tests.""" - pass diff --git a/libs/partners/airbyte/tests/integration_tests/test_document_loaders.py b/libs/partners/airbyte/tests/integration_tests/test_document_loaders.py deleted file mode 100644 index 0c5008d85ea032..00000000000000 --- a/libs/partners/airbyte/tests/integration_tests/test_document_loaders.py +++ /dev/null @@ -1,28 +0,0 @@ -"""Test Airbyte embeddings.""" - -import os - -from langchain_airbyte import AirbyteLoader - -GITHUB_TOKEN = os.environ.get("GITHUB_TOKEN") - - -def test_load_github() -> None: - """Test loading from GitHub.""" - airbyte_loader = AirbyteLoader( - source="source-github", - stream="issues", - config={ - "repositories": ["airbytehq/quickstarts"], - "credentials": {"personal_access_token": GITHUB_TOKEN}, - }, - ) - documents = airbyte_loader.load() - assert len(documents) > 0 - # make sure some documents have body in metadata - found_body = False - for doc in documents: - if "body" in doc.metadata and doc.metadata["body"]: - found_body = True - break - assert found_body, "No documents with body found" diff --git a/libs/partners/airbyte/tests/unit_tests/__init__.py b/libs/partners/airbyte/tests/unit_tests/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/libs/partners/airbyte/tests/unit_tests/test_document_loaders.py b/libs/partners/airbyte/tests/unit_tests/test_document_loaders.py deleted file mode 100644 index e97f4122685ab4..00000000000000 --- a/libs/partners/airbyte/tests/unit_tests/test_document_loaders.py +++ /dev/null @@ -1,77 +0,0 @@ -from langchain_core.prompts import PromptTemplate - -from langchain_airbyte import AirbyteLoader - - -def test_initialization() -> None: - """Test integration loader initialization.""" - AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - ) - - -def test_load() -> None: - """Test loading from source.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 5}, - ) - documents = airbyte_loader.load() - assert len(documents) == 5 - - -def test_lazy_load() -> None: - """Test lazy loading from source.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - ) - documents = airbyte_loader.lazy_load() - assert len(list(documents)) == 3 - - -async def test_alazy_load() -> None: - """Test async lazy loading from source.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - ) - documents = airbyte_loader.alazy_load() - lendocs = 0 - async for _ in documents: - lendocs += 1 - assert lendocs == 3 - - -def test_load_with_template() -> None: - """Test loading from source with template.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - template=PromptTemplate.from_template("My name is {name}"), - ) - documents = airbyte_loader.load() - assert len(documents) == 3 - for doc in documents: - assert doc.page_content.startswith("My name is ") - assert doc.metadata["name"] # should have a name - - -def test_load_no_metadata() -> None: - """Test loading from source with no metadata.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - include_metadata=False, - ) - documents = airbyte_loader.load() - assert len(documents) == 3 - for doc in documents: - assert doc.metadata == {} diff --git a/libs/partners/airbyte/tests/unit_tests/test_imports.py b/libs/partners/airbyte/tests/unit_tests/test_imports.py deleted file mode 100644 index 40a369414dd1bb..00000000000000 --- a/libs/partners/airbyte/tests/unit_tests/test_imports.py +++ /dev/null @@ -1,9 +0,0 @@ -from langchain_airbyte import __all__ - -EXPECTED_ALL = [ - "AirbyteLoader", -] - - -def test_all_imports() -> None: - assert sorted(EXPECTED_ALL) == sorted(__all__) diff --git a/libs/partners/box/poetry.lock b/libs/partners/box/poetry.lock index ff2f7db6dfc861..8589034ae40f92 100644 --- a/libs/partners/box/poetry.lock +++ b/libs/partners/box/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 1.8.2 and should not be changed by hand. [[package]] name = "annotated-types" @@ -459,7 +459,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.13" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -1099,4 +1099,4 @@ zstd = ["zstandard (>=0.18.0)"] [metadata] lock-version = "2.0" python-versions = ">=3.9.0,<3.13" -content-hash = "bd2a5266b1ec798a570e0e6aa5c9b5e255aa19d9d42565c9cab406326f794530" +content-hash = "c85860d3c2b38a4aeb9f1fe93aa25ee61d9a7cb7e5cda8006004d3f27ce8bdb5" diff --git a/libs/partners/box/pyproject.toml b/libs/partners/box/pyproject.toml index 8a1786cda1c899..8f454f4ee0122e 100644 --- a/libs/partners/box/pyproject.toml +++ b/libs/partners/box/pyproject.toml @@ -1,93 +1,84 @@ +[build-system] +requires = [ "poetry-core>=1.0.0",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "langchain-box" -version = "0.2.2" +version = "0.2.3" description = "An integration package connecting Box and LangChain" authors = [] readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/box" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-box%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9.0,<3.13" -langchain-core = "^0.3.13" -box-sdk-gen = { extras = ["jwt"], version = "^1.5.0" } +langchain-core = "^0.3.15" pydantic = "^2" +[tool.ruff.lint] +select = [ "E", "F", "I", "T201",] + +[tool.coverage.run] +omit = [ "tests/*",] + +[tool.pytest.ini_options] +markers = [ "compile: mark placeholder test used to compile integration tests without running them",] +asyncio_mode = "auto" + +[tool.poetry.dependencies.box-sdk-gen] +extras = [ "jwt",] +version = "^1.5.0" + [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.4.3" pytest_mock = "^3.14.0" pytest-asyncio = "^0.23.2" pytest-socket = "^0.7.0" -langchain-core = { path = "../../core", develop = true } - -[tool.poetry.group.codespell] -optional = true [tool.poetry.group.codespell.dependencies] codespell = "^2.2.6" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] python-dotenv = "^1.0.1" -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.1.8" [tool.poetry.group.typing.dependencies] mypy = "^1.7.1" -langchain-core = { path = "../../core", develop = true } types-requests = "^2.32.0.20240712" -[tool.poetry.group.dev] -optional = true - -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } - -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] +[tool.poetry.group.test.dependencies.langchain-core] +path = "../../core" +develop = true -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" +[tool.poetry.group.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -# addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/partners/chroma/poetry.lock b/libs/partners/chroma/poetry.lock index 435c4533c76726..19729f51db44d1 100644 --- a/libs/partners/chroma/poetry.lock +++ b/libs/partners/chroma/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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["pytest-mypy"] [metadata] lock-version = "2.0" -python-versions = ">=3.8.1,<4" -content-hash = "fb0291adcbf1f22fd16d20298665d5790734b3f334b4d8bbec8db24c12ba9c55" +python-versions = ">=3.9,<4" +content-hash = "2747536a10c5e463604c0ff0024055c186363e673fe755b01df356deb9800435" diff --git a/libs/partners/chroma/pyproject.toml b/libs/partners/chroma/pyproject.toml index fdde6826a455d4..3fa59a97f74e34 100644 --- a/libs/partners/chroma/pyproject.toml +++ b/libs/partners/chroma/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-chroma" -version = "0.1.5" +version = "0.2.0" description = "An integration package connecting Chroma and LangChain" authors = [] readme = "README.md" @@ -19,14 +19,8 @@ disallow_untyped_defs = true "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-chroma%3D%3D0%22&expanded=true" [tool.poetry.dependencies] -python = ">=3.8.1,<4" -[[tool.poetry.dependencies.langchain-core]] 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python = ">=3.10"}] [tool.poetry.group.dev.dependencies] [[tool.poetry.group.dev.dependencies.langchain-core]] diff --git a/libs/partners/couchbase/poetry.lock b/libs/partners/couchbase/poetry.lock index 39ad5dce0b9992..5931a6a913b839 100644 --- a/libs/partners/couchbase/poetry.lock +++ b/libs/partners/couchbase/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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a/libs/partners/exa/poetry.lock +++ b/libs/partners/exa/poetry.lock @@ -402,7 +402,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -411,14 +411,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -427,13 +427,13 @@ url = "../../core" [[package]] name = "langsmith" -version = "0.1.120" +version = "0.1.139" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" 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"langchain-pinecone" -version = "0.2.0" +version = "0.2.1" description = "An integration package connecting Pinecone and LangChain" authors = [] readme = "README.md" @@ -20,10 +20,9 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<3.13" -langchain-core = "^0.3" +langchain-core = "^0.3.15" pinecone-client = "^5.0.0" aiohttp = ">=3.9.5,<3.10" - [[tool.poetry.dependencies.numpy]] version = "^1" python = "<3.12" @@ -33,17 +32,14 @@ version = "^1.26.0" 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 = "--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" [tool.poetry.group.test] diff --git a/libs/partners/prompty/poetry.lock b/libs/partners/prompty/poetry.lock index 5965576a6da198..3753802ecc0dff 100644 --- a/libs/partners/prompty/poetry.lock +++ b/libs/partners/prompty/poetry.lock @@ -637,7 +637,7 @@ files = [ [[package]] name = "langchain" -version = "0.3.0" +version = "0.3.6" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -647,7 +647,7 @@ develop = true [package.dependencies] aiohttp = "^3.8.3" async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""} -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" numpy = [ @@ -658,7 +658,7 @@ pydantic = "^2.7.4" PyYAML = ">=5.3" requests = "^2" SQLAlchemy = ">=1.4,<3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10" [package.source] type = "directory" @@ -666,7 +666,7 @@ url = "../../langchain" [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -675,14 +675,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -691,7 +691,7 @@ url = "../../core" [[package]] name = "langchain-text-splitters" -version = "0.3.0" +version = "0.3.1" description = "LangChain text splitting utilities" optional = false python-versions = ">=3.9,<4.0" @@ -699,7 +699,7 @@ files = [] develop = true 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"python_full_version >= \"3.12.4\""}, ] requests = ">=2,<3" +requests-toolbelt = ">=1.0.0,<2.0.0" [[package]] name = "multidict" @@ -1320,6 +1321,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"}, + {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"}, +] + +[package.dependencies] +requests = ">=2.0.1,<3.0.0" + [[package]] name = "ruff" version = "0.1.15" @@ -1377,7 +1392,9 @@ python-versions = ">=3.7" files = [ {file = "SQLAlchemy-2.0.34-cp310-cp310-macosx_10_9_x86_64.whl", hash = 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+[tool.ruff] +select = [ "E", "F", "I",] + +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/prompty" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-prompty%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" pyyaml = "^6.0.1" +[tool.coverage.run] +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",] +asyncio_mode = "auto" + [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.3.0" freezegun = "^1.2.2" @@ -26,71 +56,38 @@ pytest-mock = "^3.10.0" syrupy = "^4.0.2" pytest-watcher = "^0.3.4" pytest-asyncio = "^0.21.1" -langchain-core = { path = "../../core", develop = true } -langchain = { path = "../../langchain", develop = true } -langchain-text-splitters = { path = "../../text-splitters", develop = true } - -[tool.poetry.group.codespell] -optional = true [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.1.5" -[tool.poetry.group.typing.dependencies] -mypy = "^0.991" +[tool.poetry.group.dev.dependencies] types-pyyaml = "^6.0.12.20240311" -langchain-core = { path = "../../core", develop = true } - -[tool.poetry.group.dev] -optional = true -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } +[tool.poetry.group.typing.dependencies] +mypy = "^0.991" types-pyyaml = "^6.0.12.20240311" -[tool.ruff] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort -] +[tool.poetry.group.test.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.mypy] -disallow_untyped_defs = "True" +[tool.poetry.group.test.dependencies.langchain] +path = "../../langchain" +develop = true -[tool.coverage.run] -omit = ["tests/*"] +[tool.poetry.group.test.dependencies.langchain-text-splitters] +path = "../../text-splitters" +develop = true -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" +[tool.poetry.group.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -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.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/partners/qdrant/langchain_qdrant/vectorstores.py b/libs/partners/qdrant/langchain_qdrant/vectorstores.py index 498e6d0f923145..9b8af6f7273e6c 100644 --- a/libs/partners/qdrant/langchain_qdrant/vectorstores.py +++ b/libs/partners/qdrant/langchain_qdrant/vectorstores.py @@ -2168,7 +2168,7 @@ def _generate_rest_batches( points = [ models.PointStruct( id=point_id, - vector=vector + vector=vector # type: ignore[arg-type] if self.vector_name is None else {self.vector_name: vector}, payload=payload, @@ -2208,7 +2208,7 @@ async def _agenerate_rest_batches( points = [ models.PointStruct( id=point_id, - vector=vector + vector=vector # type: ignore[arg-type] if self.vector_name is None else {self.vector_name: vector}, payload=payload, diff --git a/libs/partners/qdrant/poetry.lock b/libs/partners/qdrant/poetry.lock index f1fe800775219c..56c3a7f9718139 100644 --- a/libs/partners/qdrant/poetry.lock +++ b/libs/partners/qdrant/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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[] readme = "README.md" @@ -22,17 +22,12 @@ disallow_untyped_defs = true "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-qdrant%3D%3D0%22&expanded=true" [tool.poetry.dependencies] -python = ">=3.8.1,<4" +python = ">=3.9,<4" qdrant-client = "^1.10.1" fastembed = { version = "^0.3.3", python = ">=3.9,<3.13", optional = true } pydantic = "^2.7.4" -[[tool.poetry.dependencies.langchain-core]] -version = ">=0.1.52,<0.4" -python = ">=3.9" +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.langchain-core]] -version = ">=0.1.52,<0.3" -python = "<3.9" [tool.poetry.extras] fastembed = ["fastembed"] diff --git a/libs/partners/voyageai/poetry.lock b/libs/partners/voyageai/poetry.lock index d807625792933e..3f84762f354561 100644 --- a/libs/partners/voyageai/poetry.lock +++ b/libs/partners/voyageai/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 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -572,7 +572,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -581,14 +581,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -597,13 +597,13 @@ url = "../../core" [[package]] name = "langsmith" -version = "0.1.120" +version = "0.1.139" 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-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"}, - {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"}, + {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, + {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, ] [package.dependencies] @@ -614,6 +614,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] requests = ">=2,<3" +requests-toolbelt = ">=1.0.0,<2.0.0" [[package]] name = "multidict" @@ -1207,6 +1208,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"}, + {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"}, +] + +[package.dependencies] +requests = ">=2.0.1,<3.0.0" + [[package]] name = "ruff" version = "0.1.15" @@ -1491,4 +1506,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "7743429cd1357000a4fe104cf06f7e7fd8207c318af580053965257bf858ab8e" +content-hash = "c037eee2ed1ce2ed484992fb08ee187a0db037bf8c84cf69d8715c7c62a59bfe" diff --git a/libs/partners/voyageai/pyproject.toml b/libs/partners/voyageai/pyproject.toml index 9b416f3ce59701..0193cc36d5e26b 100644 --- a/libs/partners/voyageai/pyproject.toml +++ b/libs/partners/voyageai/pyproject.toml @@ -1,25 +1,55 @@ +[build-system] +requires = [ "poetry-core>=1.0.0",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "langchain-voyageai" -version = "0.1.2" +version = "0.1.3" description = "An integration package connecting VoyageAI and LangChain" authors = [] readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/voyageai" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-voyageai%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" voyageai = ">=0.2.1,<1" pydantic = ">=2,<3" +[tool.ruff.lint] +select = [ "E", "F", "I",] + +[tool.coverage.run] +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",] +asyncio_mode = "auto" + [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.3.0" freezegun = "^1.2.2" @@ -27,8 +57,6 @@ pytest-mock = "^3.10.0" syrupy = "^4.0.2" pytest-watcher = "^0.3.4" pytest-asyncio = "^0.21.1" -langchain-core = { path = "../../core", develop = true } - [[tool.poetry.group.test.dependencies.numpy]] version = "^1.24.0" python = "<3.12" @@ -37,65 +65,25 @@ python = "<3.12" version = "^1.26.0" python = ">=3.12" -[tool.poetry.group.codespell] -optional = true - [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.1.5" [tool.poetry.group.typing.dependencies] mypy = "^1.10" -langchain-core = { path = "../../core", develop = true } -[tool.poetry.group.dev] -optional = true +[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.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -addopts = "--strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -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.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/standard-tests/poetry.lock b/libs/standard-tests/poetry.lock index 67b5fee2313cb6..8655b65aa7753f 100644 --- a/libs/standard-tests/poetry.lock +++ b/libs/standard-tests/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 1.8.2 and should not be changed by hand. [[package]] name = "annotated-types" @@ -294,7 +294,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -303,14 +303,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -319,13 +319,13 @@ url = "../core" [[package]] name = "langsmith" -version = "0.1.120" +version = "0.1.139" 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-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"}, - {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"}, + {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, + {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, ] [package.dependencies] @@ -336,6 +336,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] requests = ">=2,<3" +requests-toolbelt = ">=1.0.0,<2.0.0" [[package]] name = "mypy" @@ -737,6 +738,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"}, + {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"}, +] + +[package.dependencies] +requests = ">=2.0.1,<3.0.0" + [[package]] name = "ruff" version = "0.1.15" @@ -845,4 +860,4 @@ zstd = ["zstandard (>=0.18.0)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "ba5e8730ffc3c7a10aded2e9625abaa51299be5b5f499d946b1ccb8f78341eb7" +content-hash = "cb3804aa252eed812fd6dc0762ffb110d6b55046f7e691f3fe14080d8ab06b38" diff --git a/libs/standard-tests/pyproject.toml b/libs/standard-tests/pyproject.toml index 9c3201688a706b..a3775ed9b30104 100644 --- a/libs/standard-tests/pyproject.toml +++ b/libs/standard-tests/pyproject.toml @@ -1,84 +1,70 @@ +[build-system] +requires = [ "poetry-core",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "langchain-standard-tests" version = "0.1.1" description = "Standard tests for LangChain implementations" -authors = ["Erick Friis "] +authors = [ "Erick Friis ",] readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/standard-tests" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" pytest = ">=7,<9" httpx = "^0.27.0" syrupy = "^4" +[tool.ruff.lint] +select = [ "E", "F", "I", "T201",] + +[tool.coverage.run] +omit = [ "tests/*",] + +[tool.pytest.ini_options] +addopts = "--strict-markers --strict-config --durations=5 -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",] +asyncio_mode = "auto" + [tool.poetry.group.test] optional = true -[tool.poetry.group.test.dependencies] -langchain-core = { path = "../core", develop = true } -pytest-asyncio = "^0.23.7" - [tool.poetry.group.test_integration] optional = true -[tool.poetry.group.test_integration.dependencies] - [tool.poetry.group.codespell] optional = true -[tool.poetry.group.codespell.dependencies] -codespell = "^2.2.0" - [tool.poetry.group.lint] optional = true +[tool.poetry.group.test.dependencies] +pytest-asyncio = "^0.23.7" + +[tool.poetry.group.test_integration.dependencies] + +[tool.poetry.group.codespell.dependencies] +codespell = "^2.2.0" + [tool.poetry.group.lint.dependencies] ruff = "^0.1.5" [tool.poetry.group.typing.dependencies] mypy = "^0.991" -langchain-core = { path = "../core", develop = true } -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] +[tool.poetry.group.test.dependencies.langchain-core] +path = "../core" +develop = true -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -addopts = "--strict-markers --strict-config --durations=5 -vv" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -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" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../core" +develop = true diff --git a/libs/text-splitters/poetry.lock b/libs/text-splitters/poetry.lock index 00296208416ddc..ff73e1b8838eee 100644 --- a/libs/text-splitters/poetry.lock +++ b/libs/text-splitters/poetry.lock @@ -1170,7 +1170,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.13" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -2980,4 +2980,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "985bbcb3e82965a3b68764c90270cece172f6a3a825e5e08644d4df63049cb44" +content-hash = "1ca2ffa7cad6f306bdedb6aa3497597cd0292172c6a2a48684881cd344458598" diff --git a/libs/text-splitters/pyproject.toml b/libs/text-splitters/pyproject.toml index f880c8a74c9438..c4c8a7535860e8 100644 --- a/libs/text-splitters/pyproject.toml +++ b/libs/text-splitters/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-text-splitters" -version = "0.3.1" +version = "0.3.2" description = "LangChain text splitting utilities" authors = [] license = "MIT" @@ -23,7 +23,7 @@ ignore_missing_imports = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" [tool.ruff.lint] select = [ "E", "F", "I", "T201",]