diff --git a/python/packages/ollama/LICENSE b/python/packages/ollama/LICENSE new file mode 100644 index 0000000000..9e841e7a26 --- /dev/null +++ b/python/packages/ollama/LICENSE @@ -0,0 +1,21 @@ + MIT License + + Copyright (c) Microsoft Corporation. + + 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/python/packages/ollama/README.md b/python/packages/ollama/README.md new file mode 100644 index 0000000000..d49879c7cc --- /dev/null +++ b/python/packages/ollama/README.md @@ -0,0 +1,13 @@ +# Get Started with Microsoft Agent Framework Ollama + +Please install this package as the extra for `agent-framework`: + +```bash +pip install agent-framework-ollama --pre +``` + +and see the [README](https://github.com/microsoft/agent-framework/tree/main/python/README.md) for more information. + +# Run samples with the Ollama Conector + +You can find samples how to run the connector under the [Getting_started] (./getting_started/README.md) folder diff --git a/python/packages/ollama/agent_framework_ollama/__init__.py b/python/packages/ollama/agent_framework_ollama/__init__.py new file mode 100644 index 0000000000..969b607623 --- /dev/null +++ b/python/packages/ollama/agent_framework_ollama/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) Microsoft. All rights reserved. + +import importlib.metadata + +from ._chat_client import OllamaChatClient, OllamaSettings + +try: + __version__ = importlib.metadata.version(__name__) +except importlib.metadata.PackageNotFoundError: + __version__ = "0.0.0" # Fallback for development mode + +__all__ = [ + "OllamaChatClient", + "OllamaSettings", + "__version__", +] diff --git a/python/packages/ollama/agent_framework_ollama/_chat_client.py b/python/packages/ollama/agent_framework_ollama/_chat_client.py new file mode 100644 index 0000000000..07df5a0d5f --- /dev/null +++ b/python/packages/ollama/agent_framework_ollama/_chat_client.py @@ -0,0 +1,315 @@ +# Copyright (c) Microsoft. All rights reserved. + +import json +from collections.abc import ( + AsyncIterable, + Callable, + Mapping, + MutableMapping, + MutableSequence, + Sequence, +) +from itertools import chain +from typing import Any, ClassVar + +from agent_framework import ( + AIFunction, + BaseChatClient, + ChatMessage, + ChatOptions, + ChatResponse, + ChatResponseUpdate, + Contents, + DataContent, + FunctionCallContent, + FunctionResultContent, + Role, + TextContent, + TextReasoningContent, + ToolProtocol, + UsageDetails, + get_logger, + use_chat_middleware, + use_function_invocation, +) +from agent_framework._pydantic import AFBaseSettings +from agent_framework.exceptions import ( + ServiceInitializationError, + ServiceInvalidRequestError, + ServiceResponseException, +) +from agent_framework.observability import use_instrumentation +from ollama import AsyncClient + +# Rename imported types to avoid naming conflicts with Agent Framework types +from ollama._types import ChatResponse as OllamaChatResponse +from ollama._types import Message as OllamaMessage +from pydantic import ValidationError + + +class OllamaSettings(AFBaseSettings): + """Ollama settings.""" + + env_prefix: ClassVar[str] = "OLLAMA_" + + host: str | None = None + model_id: str | None = None + + +logger = get_logger("agent_framework.ollama") + + +@use_function_invocation +@use_instrumentation +@use_chat_middleware +class OllamaChatClient(BaseChatClient): + """Ollama Chat completion class.""" + + OTEL_PROVIDER_NAME: ClassVar[str] = "ollama" + + def __init__( + self, + *, + host: str | None = None, + client: AsyncClient | None = None, + model_id: str | None = None, + env_file_path: str | None = None, + env_file_encoding: str | None = None, + **kwargs: Any, + ) -> None: + """Initialize an Ollama Chat client. + + Keyword Args: + host: Ollama server URL, if none `http://localhost:11434` is used. + Can be set via the OLLAMA_HOST env variable. + client: An optional Ollama Client instance. If not provided, a new instance will be created. + model_id: The Ollama chat model ID to use. Can be set via the OLLAMA_MODEL_ID env variable. + env_file_path: An optional path to a dotenv (.env) file to load environment variables from. + env_file_encoding: The encoding to use when reading the dotenv (.env) file. Defaults to 'utf-8'. + **kwargs: Additional keyword arguments passed to BaseChatClient. + """ + try: + ollama_settings = OllamaSettings( + host=host, + model_id=model_id, + env_file_encoding=env_file_encoding, + env_file_path=env_file_path, + ) + except ValidationError as ex: + raise ServiceInitializationError("Failed to create Ollama settings.", ex) from ex + + if ollama_settings.model_id is None: + raise ServiceInitializationError( + "Ollama chat model ID must be provided via model_id or OLLAMA_MODEL_ID environment variable." + ) + + self.model_id = ollama_settings.model_id + self.client = client or AsyncClient(host=ollama_settings.host) + # Save Host URL for serialization with to_dict() + self.host = str(self.client._client.base_url) + + super().__init__(**kwargs) + + async def _inner_get_response( + self, + *, + messages: MutableSequence[ChatMessage], + chat_options: ChatOptions, + **kwargs: Any, + ) -> ChatResponse: + options_dict = self._prepare_options(messages, chat_options) + + try: + response: OllamaChatResponse = await self.client.chat( # type: ignore[misc] + stream=False, + **options_dict, + **kwargs, + ) + except Exception as ex: + raise ServiceResponseException(f"Ollama chat request failed : {ex}", ex) from ex + + return self._ollama_response_to_agent_framework_response(response) + + async def _inner_get_streaming_response( + self, + *, + messages: MutableSequence[ChatMessage], + chat_options: ChatOptions, + **kwargs: Any, + ) -> AsyncIterable[ChatResponseUpdate]: + options_dict = self._prepare_options(messages, chat_options) + + try: + response_object: AsyncIterable[OllamaChatResponse] = await self.client.chat( # type: ignore[misc] + stream=True, + **options_dict, + **kwargs, + ) + except Exception as ex: + raise ServiceResponseException(f"Ollama streaming chat request failed : {ex}", ex) from ex + + async for part in response_object: + yield self._ollama_streaming_response_to_agent_framework_response(part) + + def _prepare_options(self, messages: MutableSequence[ChatMessage], chat_options: ChatOptions) -> dict[str, Any]: + # Preprocess web search tool if it exists + options_dict = chat_options.to_dict(exclude={"instructions", "type"}) + + # Promote additional_properties to the top level of options_dict + additional_props = options_dict.pop("additional_properties", {}) + options_dict.update(additional_props) + + # Prepare Messages from Agent Framework format to Ollama format + if messages and "messages" not in options_dict: + options_dict["messages"] = self._prepare_chat_history_for_request(messages) + if "messages" not in options_dict: + raise ServiceInvalidRequestError("Messages are required for chat completions") + + # Prepare Tools from Agent Framework format to Json Schema format + if chat_options.tools: + options_dict["tools"] = self._chat_to_tool_spec(chat_options.tools) + + # Currently Ollama only supports auto tool choice + if chat_options.tool_choice == "required": + raise ServiceInvalidRequestError("Ollama does not support required tool choice.") + # Always auto: remove tool_choice since Ollama does not expose configuration to force or disable tools. + if "tool_choice" in options_dict: + del options_dict["tool_choice"] + + # Rename model_id to model for Ollama API, if no model is provided use the one from client initialization + if "model_id" in options_dict: + options_dict["model"] = options_dict.pop("model_id") + + if "model_id" not in options_dict: + options_dict["model"] = self.model_id + + return options_dict + + def _prepare_chat_history_for_request(self, messages: MutableSequence[ChatMessage]) -> list[OllamaMessage]: + ollama_messages = [self._agent_framework_message_to_ollama_message(msg) for msg in messages] + # Flatten the list of lists into a single list + return list(chain.from_iterable(ollama_messages)) + + def _agent_framework_message_to_ollama_message(self, message: ChatMessage) -> list[OllamaMessage]: + message_converters: dict[str, Callable[[ChatMessage], list[OllamaMessage]]] = { + Role.SYSTEM.value: self._format_system_message, + Role.USER.value: self._format_user_message, + Role.ASSISTANT.value: self._format_assistant_message, + Role.TOOL.value: self._format_tool_message, + } + return message_converters[message.role.value](message) + + def _format_system_message(self, message: ChatMessage) -> list[OllamaMessage]: + return [OllamaMessage(role="system", content=message.text)] + + def _format_user_message(self, message: ChatMessage) -> list[OllamaMessage]: + if not any(isinstance(c, (DataContent, TextContent)) for c in message.contents) and not message.text: + raise ServiceInvalidRequestError( + "Ollama connector currently only supports user messages with TextContent or DataContent." + ) + + if not any(isinstance(c, DataContent) for c in message.contents): + return [OllamaMessage(role="user", content=message.text)] + + user_message = OllamaMessage(role="user", content=message.text) + data_contents = [c for c in message.contents if isinstance(c, DataContent)] + if data_contents: + if not any(c.has_top_level_media_type("image") for c in data_contents): + raise ServiceInvalidRequestError("Only image data content is supported for user messages in Ollama.") + # Ollama expects base64 strings without prefix + user_message["images"] = [c.uri.split(",")[1] for c in data_contents] + return [user_message] + + def _format_assistant_message(self, message: ChatMessage) -> list[OllamaMessage]: + text_content = message.text + reasoning_contents = "".join(c.text for c in message.contents if isinstance(c, TextReasoningContent)) + + assistant_message = OllamaMessage(role="assistant", content=text_content, thinking=reasoning_contents) + + tool_calls = [item for item in message.contents if isinstance(item, FunctionCallContent)] + if tool_calls: + assistant_message["tool_calls"] = [ + { + "function": { + "call_id": tool_call.call_id, + "name": tool_call.name, + "arguments": tool_call.arguments + if isinstance(tool_call.arguments, Mapping) + else json.loads(tool_call.arguments or "{}"), + } + } + for tool_call in tool_calls + ] + return [assistant_message] + + def _format_tool_message(self, message: ChatMessage) -> list[OllamaMessage]: + # Ollama does not support multiple tool results in a single message, so we create a separate + return [ + OllamaMessage(role="tool", content=str(item.result), tool_name=item.call_id) + for item in message.contents + if isinstance(item, FunctionResultContent) + ] + + def _ollama_response_to_agent_framework_content(self, response: OllamaChatResponse) -> list[Contents]: + contents: list[Contents] = [] + if response.message.thinking: + contents.append(TextReasoningContent(text=response.message.thinking)) + if response.message.content: + contents.append(TextContent(text=response.message.content)) + if response.message.tool_calls: + tool_calls = self._parse_ollama_tool_calls(response.message.tool_calls) + contents.extend(tool_calls) + return contents + + def _ollama_streaming_response_to_agent_framework_response( + self, response: OllamaChatResponse + ) -> ChatResponseUpdate: + contents = self._ollama_response_to_agent_framework_content(response) + return ChatResponseUpdate( + contents=contents, + role=Role.ASSISTANT, + ai_model_id=response.model, + created_at=response.created_at, + ) + + def _ollama_response_to_agent_framework_response(self, response: OllamaChatResponse) -> ChatResponse: + contents = self._ollama_response_to_agent_framework_content(response) + + return ChatResponse( + messages=[ChatMessage(role=Role.ASSISTANT, contents=contents)], + model_id=response.model, + created_at=response.created_at, + usage_details=UsageDetails( + input_token_count=response.prompt_eval_count, + output_token_count=response.eval_count, + ), + ) + + def _parse_ollama_tool_calls(self, tool_calls: Sequence[OllamaMessage.ToolCall]) -> list[Contents]: + resp: list[Contents] = [] + for tool in tool_calls: + fcc = FunctionCallContent( + call_id=tool.function.name, # Use name of function as call ID since Ollama doesn't provide a call ID + name=tool.function.name, + arguments=tool.function.arguments if isinstance(tool.function.arguments, dict) else "", + raw_representation=tool.function, + ) + resp.append(fcc) + return resp + + def _chat_to_tool_spec(self, tools: list[ToolProtocol | MutableMapping[str, Any]]) -> list[dict[str, Any]]: + chat_tools: list[dict[str, Any]] = [] + for tool in tools: + if isinstance(tool, ToolProtocol): + match tool: + case AIFunction(): + chat_tools.append(tool.to_json_schema_spec()) + case _: + raise ServiceInvalidRequestError( + "Unsupported tool type '" + f"{type(tool).__name__}" + "' for Ollama client. Supported tool types: AIFunction." + ) + else: + chat_tools.append(tool if isinstance(tool, dict) else dict(tool)) + return chat_tools diff --git a/python/packages/ollama/agent_framework_ollama/py.typed b/python/packages/ollama/agent_framework_ollama/py.typed new file mode 100644 index 0000000000..e69de29bb2 diff --git a/python/packages/ollama/getting_started/README.md b/python/packages/ollama/getting_started/README.md new file mode 100644 index 0000000000..bf159c5475 --- /dev/null +++ b/python/packages/ollama/getting_started/README.md @@ -0,0 +1,38 @@ +# Ollama Examples + +This folder contains examples demonstrating how to use Ollama models with the Agent Framework. + +## Prerequisites + +1. **Install Ollama**: Download and install Ollama from [ollama.com](https://ollama.com/) +2. **Start Ollama**: Ensure Ollama is running on your local machine +3. **Pull a model**: Run `ollama pull mistral` (or any other model you prefer) + - For function calling examples, use models that support tool calling like `mistral` or `qwen2.5` + - For reasoning examples, use models that support reasoning like `qwen2.5:8b` + - For Multimodality you can use models like `gemma3:4b` + +> **Note**: Not all models support all features. Function calling and reasoning capabilities depend on the specific model you're using. + +## Examples + +| File | Description | +|------|-------------| +| [`ollama_agent_basic.py`](ollama_agent_basic.py) | Demonstrates basic Ollama agent usage with the native Ollama Chat Client. Shows both streaming and non-streaming responses with tool calling capabilities. | +| [`ollama_agent_reasoning.py`](ollama_agent_reasoning.py) | Demonstrates Ollama agent with reasoning capabilities using the native Ollama Chat Client. Shows how to enable thinking/reasoning mode. | +| [`ollama_chat_client.py`](ollama_chat_client.py) | Ollama Chat Client with native Ollama Chat Client | +| [`ollama_chat_multimodal.py`](ollama_chat_multimodal.py) | Ollama Chat with multimodal native Ollama Chat Client | + +## Configuration + +The examples use environment variables for configuration. Set the appropriate variables based on which example you're running: + +### For Native Ollama Examples (`ollama_agent_basic.py`, `ollama_agent_reasoning.py`) + +Set the following environment variables: + +- `OLLAMA_HOST`: The base URL for your Ollama server (optional, defaults to `http://localhost:11434`) + - Example: `export OLLAMA_HOST="http://localhost:11434"` + +- `OLLAMA_CHAT_MODEL_ID`: The model name to use + - Example: `export OLLAMA_CHAT_MODEL_ID="qwen2.5:8b"` + - Must be a model you have pulled with Ollama \ No newline at end of file diff --git a/python/packages/ollama/getting_started/ollama_agent_basic.py b/python/packages/ollama/getting_started/ollama_agent_basic.py new file mode 100644 index 0000000000..3769410332 --- /dev/null +++ b/python/packages/ollama/getting_started/ollama_agent_basic.py @@ -0,0 +1,68 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +from datetime import datetime + +from agent_framework_ollama import OllamaChatClient + +""" +Ollama Agent Basic Example + +This sample demonstrates implementing a Ollama agent with basic tool usage. + +Ensure to install Ollama and have a model running locally before running the sample +Not all Models support function calling, to test function calling try llama3.2 or qwen3:4b +Set the model to use via the OLLAMA_CHAT_MODEL_ID environment variable or modify the code below. +https://ollama.com/ + +""" + + +def get_time(location: str) -> str: + """Get the current time.""" + return f"The current time in {location} is {datetime.now().strftime('%I:%M %p')}." + + +async def non_streaming_example() -> None: + """Example of non-streaming response (get the complete result at once).""" + print("=== Non-streaming Response Example ===") + + agent = OllamaChatClient().create_agent( + name="TimeAgent", + instructions="You are a helpful time agent answer in one sentence.", + tools=get_time, + ) + + query = "What time is it in Seattle? Use a tool call" + print(f"User: {query}") + result = await agent.run(query) + print(f"Result: {result}\n") + + +async def streaming_example() -> None: + """Example of streaming response (get results as they are generated).""" + print("=== Streaming Response Example ===") + + agent = OllamaChatClient().create_agent( + name="TimeAgent", + instructions="You are a helpful time agent answer in one sentence.", + tools=get_time, + ) + query = "What time is it in San Francisco? Use a tool call" + print(f"User: {query}") + print("Agent: ", end="", flush=True) + async for chunk in agent.run_stream(query): + if chunk.text: + print(chunk.text, end="", flush=True) + print("\n") + + +async def main() -> None: + print("=== Basic Ollama Chat Client Agent Example ===") + + await non_streaming_example() + await streaming_example() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/packages/ollama/getting_started/ollama_agent_reasoning.py b/python/packages/ollama/getting_started/ollama_agent_reasoning.py new file mode 100644 index 0000000000..a76492b42b --- /dev/null +++ b/python/packages/ollama/getting_started/ollama_agent_reasoning.py @@ -0,0 +1,46 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio + +from agent_framework import TextReasoningContent + +from agent_framework_ollama import OllamaChatClient + +""" +Ollama Agent Reasoning Example + +This sample demonstrates implementing a Ollama agent with reasoning. + +Ensure to install Ollama and have a model running locally before running the sample +Not all Models support reasoning, to test reasoning try qwen3:8b +Set the model to use via the OLLAMA_CHAT_MODEL_ID environment variable or modify the code below. +https://ollama.com/ + +""" + + +async def reasoning_example() -> None: + print("=== Response Reasoning Example ===") + + agent = OllamaChatClient().create_agent( + name="TimeAgent", + instructions="You are a helpful agent answer in one sentence.", + additional_chat_options={"think": True}, # Enable Reasoning on agent level + ) + query = "Hey what is 3+4? Can you explain how you got to that answer?" + print(f"User: {query}") + # Enable Reasoning on per request level + result = await agent.run(query) + reasoning = "".join(c.text for c in result.messages[-1].contents if isinstance(c, TextReasoningContent)) + print(f"Reasoning: {reasoning}") + print(f"Answer: {result}\n") + + +async def main() -> None: + print("=== Basic Ollama Chat Client Agent Reasoning ===") + + await reasoning_example() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/packages/ollama/getting_started/ollama_chat_client.py b/python/packages/ollama/getting_started/ollama_chat_client.py new file mode 100644 index 0000000000..5cde122ecd --- /dev/null +++ b/python/packages/ollama/getting_started/ollama_chat_client.py @@ -0,0 +1,36 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +from datetime import datetime + +from agent_framework_ollama import OllamaChatClient + +# Ensure to install Ollama and have a model running locally before running the sample +# Not all Models support function calling, to test function calling try llama3.2 +# Set the model to use via the OLLAMA_CHAT_MODEL_ID environment variable or modify the code below. +# https://ollama.com/ + + +def get_time(): + """Get the current time.""" + return f"The current time is {datetime.now().strftime('%I:%M %p')}." + + +async def main() -> None: + client = OllamaChatClient() + message = "What time is it? Use a tool call" + stream = False + print(f"User: {message}") + if stream: + print("Assistant: ", end="") + async for chunk in client.get_streaming_response(message, tools=get_time): + if str(chunk): + print(str(chunk), end="") + print("") + else: + response = await client.get_response(message, tools=get_time) + print(f"Assistant: {response}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/packages/ollama/getting_started/ollama_chat_multimodal.py b/python/packages/ollama/getting_started/ollama_chat_multimodal.py new file mode 100644 index 0000000000..e0670d785d --- /dev/null +++ b/python/packages/ollama/getting_started/ollama_chat_multimodal.py @@ -0,0 +1,54 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio + +from agent_framework import ChatMessage, DataContent, Role, TextContent + +from agent_framework_ollama import OllamaChatClient + +""" +Ollama Agent Multimodal Example + +This sample demonstrates implementing a Ollama agent with multimodal input capabilities. + +Ensure to install Ollama and have a model running locally before running the sample +Not all Models support multimodal input, to test multimodal input try gemma3:4b +Set the model to use via the OLLAMA_CHAT_MODEL_ID environment variable or modify the code below. +https://ollama.com/ + +""" + + +def create_sample_image() -> str: + """Create a simple 1x1 pixel PNG image for testing.""" + # This is a tiny red pixel in PNG format + png_data = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg==" + return f"data:image/png;base64,{png_data}" + + +async def test_image() -> None: + """Test image analysis with Ollama.""" + + client = OllamaChatClient() + + image_uri = create_sample_image() + + message = ChatMessage( + role=Role.USER, + contents=[ + TextContent(text="What's in this image?"), + DataContent(uri=image_uri, media_type="image/png"), + ], + ) + + response = await client.get_response(message) + print(f"Image Response: {response}") + + +async def main() -> None: + print("=== Testing Ollama Multimodal ===") + await test_image() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/packages/ollama/pyproject.toml b/python/packages/ollama/pyproject.toml new file mode 100644 index 0000000000..07a28d5a6d --- /dev/null +++ b/python/packages/ollama/pyproject.toml @@ -0,0 +1,95 @@ +[project] +name = "agent-framework-ollama" +description = "Ollama integration for Microsoft Agent Framework." +authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}] +readme = "README.md" +requires-python = ">=3.10" +version = "0.1.0b1" +license-files = ["LICENSE"] +urls.homepage = "https://learn.microsoft.com/en-us/agent-framework/" +urls.source = "https://github.com/microsoft/agent-framework/tree/main/python" +urls.release_notes = "https://github.com/microsoft/agent-framework/releases?q=tag%3Apython-1&expanded=true" +urls.issues = "https://github.com/microsoft/agent-framework/issues" +classifiers = [ + "License :: OSI Approved :: MIT License", + "Development Status :: 4 - Beta", + "Intended Audience :: Developers", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Framework :: Pydantic :: 2", + "Typing :: Typed", +] +dependencies = [ + "agent-framework-core", + "ollama >= 0.5.3", +] + +[tool.uv] +prerelease = "if-necessary-or-explicit" +environments = [ + "sys_platform == 'darwin'", + "sys_platform == 'linux'", + "sys_platform == 'win32'" +] + +[tool.uv-dynamic-versioning] +fallback-version = "0.0.0" +[tool.pytest.ini_options] +testpaths = 'tests' +addopts = "-ra -q -r fEX" +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" +filterwarnings = [] +timeout = 120 + +[tool.ruff] +line-length = 120 + +[tool.ruff.lint] +select = ["E", "F", "I", "N", "W"] + +[tool.coverage.run] +omit = [ + "**/__init__.py" +] + +[tool.pyright] +extend = "../../pyproject.toml" +exclude = ['tests'] + +[tool.mypy] +plugins = ['pydantic.mypy'] +strict = true +python_version = "3.10" +ignore_missing_imports = true +disallow_untyped_defs = true +no_implicit_optional = true +check_untyped_defs = true +warn_return_any = true +show_error_codes = true +warn_unused_ignores = false +disallow_incomplete_defs = true +disallow_untyped_decorators = true +disallow_any_unimported = true + +[tool.bandit] +targets = ["agent_framework_ollama"] +exclude_dirs = ["tests"] + +[tool.poe] +executor.type = "uv" +include = "../../shared_tasks.toml" +[tool.poe.tasks] +mypy = "mypy --config-file $POE_ROOT/pyproject.toml agent_framework_ollama" +test = "pytest --cov=agent_framework_ollama --cov-report=term-missing:skip-covered tests" + +[tool.uv.build-backend] +module-name = "agent_framework_ollama" +module-root = "" + +[build-system] +requires = ["uv_build>=0.8.2,<0.9.0"] +build-backend = "uv_build" diff --git a/python/packages/ollama/tests/conftest.py b/python/packages/ollama/tests/conftest.py new file mode 100644 index 0000000000..dd2529c98c --- /dev/null +++ b/python/packages/ollama/tests/conftest.py @@ -0,0 +1,47 @@ +# Copyright (c) Microsoft. All rights reserved. +from typing import Any + +from agent_framework import ChatMessage +from pytest import fixture + + +# region: Connector Settings fixtures +@fixture +def exclude_list(request: Any) -> list[str]: + """Fixture that returns a list of environment variables to exclude.""" + return request.param if hasattr(request, "param") else [] + + +@fixture +def override_env_param_dict(request: Any) -> dict[str, str]: + """Fixture that returns a dict of environment variables to override.""" + return request.param if hasattr(request, "param") else {} + + +# These two fixtures are used for multiple things, also non-connector tests +@fixture() +def ollama_unit_test_env(monkeypatch, exclude_list, override_env_param_dict): # type: ignore + """Fixture to set environment variables for OllamaSettings.""" + + if exclude_list is None: + exclude_list = [] + + if override_env_param_dict is None: + override_env_param_dict = {} + + env_vars = {"OLLAMA_HOST": "http://localhost:12345", "OLLAMA_MODEL_ID": "test"} + + env_vars.update(override_env_param_dict) # type: ignore + + for key, value in env_vars.items(): + if key in exclude_list: + monkeypatch.delenv(key, raising=False) # type: ignore + continue + monkeypatch.setenv(key, value) # type: ignore + + return env_vars + + +@fixture +def chat_history() -> list[ChatMessage]: + return [] diff --git a/python/packages/ollama/tests/test_ollama_chat_client.py b/python/packages/ollama/tests/test_ollama_chat_client.py new file mode 100644 index 0000000000..fbb88695c1 --- /dev/null +++ b/python/packages/ollama/tests/test_ollama_chat_client.py @@ -0,0 +1,511 @@ +# Copyright (c) Microsoft. All rights reserved. + +import os +from collections.abc import AsyncIterable +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest +from agent_framework import ( + BaseChatClient, + ChatMessage, + ChatResponseUpdate, + DataContent, + FunctionCallContent, + FunctionResultContent, + HostedWebSearchTool, + TextContent, + TextReasoningContent, + UriContent, + chat_middleware, +) +from agent_framework.exceptions import ( + ServiceInitializationError, + ServiceInvalidRequestError, + ServiceResponseException, +) +from ollama import AsyncClient +from ollama._types import ChatResponse as OllamaChatResponse +from ollama._types import Message as OllamaMessage +from openai import AsyncStream + +from agent_framework_ollama import OllamaChatClient + +# region Service Setup + +skip_if_azure_integration_tests_disabled = pytest.mark.skipif( + os.getenv("RUN_INTEGRATION_TESTS", "false").lower() != "true" + or os.getenv("OLLAMA_MODEL_ID", "") in ("", "test-model"), + reason="No real Ollama chat model provided; skipping integration tests." + if os.getenv("RUN_INTEGRATION_TESTS", "false").lower() == "true" + else "Integration tests are disabled.", +) + + +@pytest.fixture +def mock_streaming_chat_completion_response() -> AsyncStream[OllamaChatResponse]: + response = OllamaChatResponse( + message=OllamaMessage(content="test", role="assistant"), + model="test", + ) + stream = MagicMock(spec=AsyncStream) + stream.__aiter__.return_value = [response] + return stream + + +@pytest.fixture +def mock_streaming_chat_completion_response_reasoning() -> AsyncStream[OllamaChatResponse]: + response = OllamaChatResponse( + message=OllamaMessage(thinking="test", role="assistant"), + model="test", + ) + stream = MagicMock(spec=AsyncStream) + stream.__aiter__.return_value = [response] + return stream + + +@pytest.fixture +def mock_chat_completion_response() -> OllamaChatResponse: + return OllamaChatResponse( + message=OllamaMessage(content="test", role="assistant"), + model="test", + eval_count=1, + prompt_eval_count=1, + created_at="2024-01-01T00:00:00Z", + ) + + +@pytest.fixture +def mock_chat_completion_response_reasoning() -> OllamaChatResponse: + return OllamaChatResponse( + message=OllamaMessage(thinking="test", role="assistant"), + model="test", + eval_count=1, + prompt_eval_count=1, + created_at="2024-01-01T00:00:00Z", + ) + + +@pytest.fixture +def mock_streaming_chat_completion_tool_call() -> AsyncStream[OllamaChatResponse]: + ollama_tool_call = OllamaChatResponse( + message=OllamaMessage( + content="", + role="assistant", + tool_calls=[{"function": {"name": "hello_world", "arguments": {"arg1": "value1"}}}], + ), + model="test", + ) + stream = MagicMock(spec=AsyncStream) + stream.__aiter__.return_value = [ollama_tool_call] + return stream + + +@pytest.fixture +def mock_chat_completion_tool_call() -> OllamaChatResponse: + return OllamaChatResponse( + message=OllamaMessage( + content="", + role="assistant", + tool_calls=[{"function": {"name": "hello_world", "arguments": {"arg1": "value1"}}}], + ), + model="test", + created_at="2024-01-01T00:00:00Z", + ) + + +def hello_world(arg1: str) -> str: + return "Hello World" + + +def test_init(ollama_unit_test_env: dict[str, str]) -> None: + # Test successful initialization + ollama_chat_client = OllamaChatClient() + + assert ollama_chat_client.client is not None + assert isinstance(ollama_chat_client.client, AsyncClient) + assert ollama_chat_client.model_id == ollama_unit_test_env["OLLAMA_MODEL_ID"] + assert isinstance(ollama_chat_client, BaseChatClient) + + +def test_init_client(ollama_unit_test_env: dict[str, str]) -> None: + # Test successful initialization with provided client + test_client = MagicMock(spec=AsyncClient) + # Mock underlying HTTP client's base_url + test_client._client = MagicMock() + test_client._client.base_url = ollama_unit_test_env["OLLAMA_MODEL_ID"] + ollama_chat_client = OllamaChatClient(client=test_client) + + assert ollama_chat_client.client is test_client + assert ollama_chat_client.model_id == ollama_unit_test_env["OLLAMA_MODEL_ID"] + assert isinstance(ollama_chat_client, BaseChatClient) + + +@pytest.mark.parametrize("exclude_list", [["OLLAMA_MODEL_ID"]], indirect=True) +def test_with_invalid_settings(ollama_unit_test_env: dict[str, str]) -> None: + with pytest.raises(ServiceInitializationError): + OllamaChatClient( + host="http://localhost:12345", + model_id=None, + env_file_path="test.env", + ) + + +def test_serialize(ollama_unit_test_env: dict[str, str]) -> None: + settings = { + "host": ollama_unit_test_env["OLLAMA_HOST"], + "model_id": ollama_unit_test_env["OLLAMA_MODEL_ID"], + } + + ollama_chat_client = OllamaChatClient.from_dict(settings) + serialized = ollama_chat_client.to_dict() + + assert isinstance(serialized, dict) + assert serialized["host"] == ollama_unit_test_env["OLLAMA_HOST"] + assert serialized["model_id"] == ollama_unit_test_env["OLLAMA_MODEL_ID"] + + +def test_chat_middleware(ollama_unit_test_env: dict[str, str]) -> None: + @chat_middleware + async def sample_middleware(context, next): + await next(context) + + ollama_chat_client = OllamaChatClient(middleware=[sample_middleware]) + assert len(ollama_chat_client.middleware) == 1 + assert ollama_chat_client.middleware[0] == sample_middleware + + +def test_additional_properties(ollama_unit_test_env: dict[str, str]) -> None: + additional_properties = { + "user_location": { + "country": "US", + "city": "Seattle", + } + } + ollama_chat_client = OllamaChatClient( + additional_properties=additional_properties, + ) + assert ollama_chat_client.additional_properties == additional_properties + + +# region CMC + + +async def test_empty_messages() -> None: + ollama_chat_client = OllamaChatClient( + host="http://localhost:12345", + model_id="test-model", + ) + with pytest.raises(ServiceInvalidRequestError): + await ollama_chat_client.get_response(messages=[]) + + +async def test_function_choice_required_argument() -> None: + ollama_chat_client = OllamaChatClient( + host="http://localhost:12345", + model_id="test-model", + ) + with pytest.raises(ServiceInvalidRequestError): + await ollama_chat_client.get_response( + messages=[ChatMessage(text="hello world", role="user")], + tool_choice="required", + tools=[hello_world], + ) + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_chat_completion_response: AsyncStream[OllamaChatResponse], +) -> None: + mock_chat.return_value = mock_chat_completion_response + chat_history.append(ChatMessage(text="hello world", role="system")) + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + result = await ollama_client.get_response(messages=chat_history) + + assert result.text == "test" + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_reasoning( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_chat_completion_response_reasoning: AsyncStream[OllamaChatResponse], +) -> None: + mock_chat.return_value = mock_chat_completion_response_reasoning + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + result = await ollama_client.get_response(messages=chat_history) + + reasoning = "".join(c.text for c in result.messages.pop().contents if isinstance(c, TextReasoningContent)) + assert reasoning == "test" + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_chat_failure( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], +) -> None: + # Simulate a failure in the Ollama client + mock_chat.side_effect = Exception("Connection error") + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + + with pytest.raises(ServiceResponseException) as exc_info: + await ollama_client.get_response(messages=chat_history) + + assert "Ollama chat request failed" in str(exc_info.value) + assert "Connection error" in str(exc_info.value) + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_streaming( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_streaming_chat_completion_response: AsyncStream[OllamaChatResponse], +) -> None: + mock_chat.return_value = mock_streaming_chat_completion_response + chat_history.append(ChatMessage(text="hello world", role="system")) + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + result = ollama_client.get_streaming_response(messages=chat_history) + + async for chunk in result: + assert chunk.text == "test" + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_streaming_reasoning( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_streaming_chat_completion_response_reasoning: AsyncStream[OllamaChatResponse], +) -> None: + mock_chat.return_value = mock_streaming_chat_completion_response_reasoning + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + result = ollama_client.get_streaming_response(messages=chat_history) + + async for chunk in result: + reasoning = "".join(c.text for c in chunk.contents if isinstance(c, TextReasoningContent)) + assert reasoning == "test" + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_streaming_chat_failure( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], +) -> None: + # Simulate a failure in the Ollama client for streaming + mock_chat.side_effect = Exception("Streaming connection error") + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + + with pytest.raises(ServiceResponseException) as exc_info: + async for _ in ollama_client.get_streaming_response(messages=chat_history): + pass + + assert "Ollama streaming chat request failed" in str(exc_info.value) + assert "Streaming connection error" in str(exc_info.value) + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_streaming_with_tool_call( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_streaming_chat_completion_response: AsyncStream[OllamaChatResponse], + mock_streaming_chat_completion_tool_call: AsyncStream[OllamaChatResponse], +) -> None: + mock_chat.side_effect = [ + mock_streaming_chat_completion_tool_call, + mock_streaming_chat_completion_response, + ] + + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + result = ollama_client.get_streaming_response(messages=chat_history, tools=[hello_world]) + + chunks: list[ChatResponseUpdate] = [] + async for chunk in result: + chunks.append(chunk) + + # Check parsed Toolcalls + assert isinstance(chunks[0].contents[0], FunctionCallContent) + tool_call = chunks[0].contents[0] + assert tool_call.name == "hello_world" + assert tool_call.arguments == {"arg1": "value1"} + assert isinstance(chunks[1].contents[0], FunctionResultContent) + tool_result = chunks[1].contents[0] + assert tool_result.result == "Hello World" + assert isinstance(chunks[2].contents[0], TextContent) + text_result = chunks[2].contents[0] + assert text_result.text == "test" + + +async def test_cmc_with_hosted_tool_call( + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], +) -> None: + with pytest.raises(ServiceInvalidRequestError): + additional_properties = { + "user_location": { + "country": "US", + "city": "Seattle", + } + } + + chat_history.append(ChatMessage(text="hello world", role="user")) + + ollama_client = OllamaChatClient() + await ollama_client.get_response( + messages=chat_history, + tools=[HostedWebSearchTool(additional_properties=additional_properties)], + ) + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_with_data_content_type( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_chat_completion_response: OllamaChatResponse, +) -> None: + mock_chat.return_value = mock_chat_completion_response + chat_history.append( + ChatMessage( + contents=[DataContent(uri="data:image/png;base64,xyz", media_type="image/png")], + role="user", + ) + ) + + ollama_client = OllamaChatClient() + + result = await ollama_client.get_response(messages=chat_history) + assert result.text == "test" + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_with_invalid_data_content_media_type( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_streaming_chat_completion_response: AsyncStream[OllamaChatResponse], +) -> None: + with pytest.raises(ServiceInvalidRequestError): + mock_chat.return_value = mock_streaming_chat_completion_response + # Remote Uris are not supported by Ollama client + chat_history.append( + ChatMessage( + contents=[DataContent(uri="data:audio/mp3;base64,xyz", media_type="audio/mp3")], + role="user", + ) + ) + + ollama_client = OllamaChatClient() + ollama_client.client.chat = AsyncMock(return_value=mock_streaming_chat_completion_response) + + await ollama_client.get_response(messages=chat_history) + + +@patch.object(AsyncClient, "chat", new_callable=AsyncMock) +async def test_cmc_with_invalid_content_type( + mock_chat: AsyncMock, + ollama_unit_test_env: dict[str, str], + chat_history: list[ChatMessage], + mock_chat_completion_response: AsyncStream[OllamaChatResponse], +) -> None: + with pytest.raises(ServiceInvalidRequestError): + mock_chat.return_value = mock_chat_completion_response + # Remote Uris are not supported by Ollama client + chat_history.append( + ChatMessage( + contents=[UriContent(uri="http://example.com/image.png", media_type="image/png")], + role="user", + ) + ) + + ollama_client = OllamaChatClient() + + await ollama_client.get_response(messages=chat_history) + + +@skip_if_azure_integration_tests_disabled +async def test_cmc_integration_with_tool_call( + chat_history: list[ChatMessage], +) -> None: + chat_history.append(ChatMessage(text="Call the hello world function and repeat what it says", role="user")) + + ollama_client = OllamaChatClient() + result = await ollama_client.get_response(messages=chat_history, tools=[hello_world]) + + assert "hello" in result.text.lower() and "world" in result.text.lower() + assert isinstance(result.messages[-2].contents[0], FunctionResultContent) + tool_result = result.messages[-2].contents[0] + assert tool_result.result == "Hello World" + + +@skip_if_azure_integration_tests_disabled +async def test_cmc_integration_with_chat_completion( + chat_history: list[ChatMessage], +) -> None: + chat_history.append(ChatMessage(text="Say Hello World", role="user")) + + ollama_client = OllamaChatClient() + result = await ollama_client.get_response(messages=chat_history) + + assert "hello" in result.text.lower() + + +@skip_if_azure_integration_tests_disabled +async def test_cmc_streaming_integration_with_tool_call( + chat_history: list[ChatMessage], +) -> None: + chat_history.append(ChatMessage(text="Call the hello world function and repeat what it says", role="user")) + + ollama_client = OllamaChatClient() + result: AsyncIterable[ChatResponseUpdate] = ollama_client.get_streaming_response( + messages=chat_history, tools=[hello_world] + ) + + chunks: list[ChatResponseUpdate] = [] + async for chunk in result: + chunks.append(chunk) + + for c in chunks: + if len(c.contents) > 0: + if isinstance(c.contents[0], FunctionResultContent): + tool_result = c.contents[0] + assert tool_result.result == "Hello World" + if isinstance(c.contents[0], FunctionCallContent): + tool_call = c.contents[0] + assert tool_call.name == "hello_world" + + +@skip_if_azure_integration_tests_disabled +async def test_cmc_streaming_integration_with_chat_completion( + chat_history: list[ChatMessage], +) -> None: + chat_history.append(ChatMessage(text="Say Hello World", role="user")) + + ollama_client = OllamaChatClient() + result: AsyncIterable[ChatResponseUpdate] = ollama_client.get_streaming_response(messages=chat_history) + + full_text = "" + async for chunk in result: + full_text += chunk.text + + assert "hello" in full_text.lower() and "world" in full_text.lower() diff --git a/python/pyproject.toml b/python/pyproject.toml index 464f7c3f61..8564c471aa 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -96,6 +96,7 @@ agent-framework-declarative = { workspace = true } agent-framework-devui = { workspace = true } agent-framework-lab = { workspace = true } agent-framework-mem0 = { workspace = true } +agent-framework-ollama = { workspace = true } agent-framework-purview = { workspace = true } agent-framework-redis = { workspace = true } diff --git a/python/samples/README.md b/python/samples/README.md index 970b86d8e5..9c87ddd67b 100644 --- a/python/samples/README.md +++ b/python/samples/README.md @@ -102,6 +102,8 @@ This directory contains samples demonstrating the capabilities of Microsoft Agen | File | Description | |------|-------------| | [`getting_started/agents/ollama/ollama_with_openai_chat_client.py`](./getting_started/agents/ollama/ollama_with_openai_chat_client.py) | Ollama with OpenAI Chat Client Example | +| [`packages/ollama/getting_started/ollama_agent_basic.py`](../packages/ollama/getting_started/ollama_agent_basic.py) | (Experimental) Ollama Agent with native Ollama Chat Client | +| [`packages/ollama/getting_started/ollama_agent_reasoning.py`](../packages/ollama/getting_started/ollama_agent_reasoning.py) | (Experimental) Ollama Reasoning Agent with native Ollama Chat Client | ### OpenAI @@ -147,6 +149,8 @@ This directory contains samples demonstrating the capabilities of Microsoft Agen | [`getting_started/chat_client/openai_assistants_client.py`](./getting_started/chat_client/openai_assistants_client.py) | OpenAI Assistants Client Direct Usage Example | | [`getting_started/chat_client/openai_chat_client.py`](./getting_started/chat_client/openai_chat_client.py) | OpenAI Chat Client Direct Usage Example | | [`getting_started/chat_client/openai_responses_client.py`](./getting_started/chat_client/openai_responses_client.py) | OpenAI Responses Client Direct Usage Example | +| [`packages/ollama/getting_started/ollama_chat_client.py`](../packages/ollama/getting_started/ollama_chat_client.py) | (Experimental) Ollama Chat Client with native Ollama Chat Client | + ## Context Providers @@ -221,6 +225,8 @@ This directory contains samples demonstrating the capabilities of Microsoft Agen | [`getting_started/multimodal_input/azure_chat_multimodal.py`](./getting_started/multimodal_input/azure_chat_multimodal.py) | Azure OpenAI Chat with multimodal (image) input example | | [`getting_started/multimodal_input/azure_responses_multimodal.py`](./getting_started/multimodal_input/azure_responses_multimodal.py) | Azure OpenAI Responses with multimodal (image) input example | | [`getting_started/multimodal_input/openai_chat_multimodal.py`](./getting_started/multimodal_input/openai_chat_multimodal.py) | OpenAI Chat with multimodal (image) input example | +| [`packages/ollama/getting_started/ollama_chat_multimodal.py`](../packages/ollama/getting_started/ollama_chat_multimodal.py) | (Experimental) Ollama Chat with multimodal native Ollama Chat Client | + ## Azure Functions diff --git a/python/samples/getting_started/agents/ollama/README.md b/python/samples/getting_started/agents/ollama/README.md index e8c98f2147..e6d0878c74 100644 --- a/python/samples/getting_started/agents/ollama/README.md +++ b/python/samples/getting_started/agents/ollama/README.md @@ -6,7 +6,11 @@ This folder contains examples demonstrating how to use Ollama models with the Ag 1. **Install Ollama**: Download and install Ollama from [ollama.com](https://ollama.com/) 2. **Start Ollama**: Ensure Ollama is running on your local machine -3. **Pull a model**: Run `ollama pull mistral` (or any other model you prefer that supports function calling) +3. **Pull a model**: Run `ollama pull mistral` (or any other model you prefer) + - For function calling examples, use models that support tool calling like `mistral` or `qwen2.5` + - For reasoning examples, use models that support reasoning like `qwen2.5:8b` + +> **Note**: Not all models support all features. Function calling and reasoning capabilities depend on the specific model you're using. ## Examples @@ -16,15 +20,16 @@ This folder contains examples demonstrating how to use Ollama models with the Ag ## Configuration -The examples use environment variables for configuration: +The examples use environment variables for configuration. Set the appropriate variables based on which example you're running: + -### Environment Variables +### For OpenAI Client with Ollama (`ollama_with_openai_chat_client.py`) -Set the following environment variables before running the examples: +Set the following environment variables: -- `OLLAMA_ENDPOINT`: The base URL for your Ollama server +- `OLLAMA_ENDPOINT`: The base URL for your Ollama server with `/v1/` suffix - Example: `export OLLAMA_ENDPOINT="http://localhost:11434/v1/"` - `OLLAMA_MODEL`: The model name to use - Example: `export OLLAMA_MODEL="mistral"` - - Must be a model you have pulled with Ollama + - Must be a model you have pulled with Ollama \ No newline at end of file diff --git a/python/samples/getting_started/chat_client/README.md b/python/samples/getting_started/chat_client/README.md index a0951c3864..293b454821 100644 --- a/python/samples/getting_started/chat_client/README.md +++ b/python/samples/getting_started/chat_client/README.md @@ -32,3 +32,9 @@ Depending on which client you're using, set the appropriate environment variable - `OPENAI_API_KEY`: Your OpenAI API key - `OPENAI_CHAT_MODEL_ID`: The OpenAI model to use for chat clients (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`) - `OPENAI_RESPONSES_MODEL_ID`: The OpenAI model to use for responses clients (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`) + +**For Ollama client:** +- `OLLAMA_HOST`: Your Ollama server URL (defaults to `http://localhost:11434` if not set) +- `OLLAMA_CHAT_MODEL_ID`: The Ollama model to use for chat (e.g., `llama3.2`, `llama2`, `codellama`) + +> **Note**: For Ollama, ensure you have Ollama installed and running locally with at least one model downloaded. 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