chore: import upstream snapshot with attribution

python/samples/02-agents/providers/ollama/README.md

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+# 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 `qwen3:8b`
+   - For multimodal examples, use models like `gemma3:4b`
+
+> **Note**: Not all models support all features. Function calling, reasoning, and multimodal capabilities depend on the specific model you're using.
+
+## Recommended Approach
+
+The recommended way to use Ollama with Agent Framework is via the native `OllamaChatClient` from the `agent-framework-ollama` package. This provides full support for Ollama-specific features like reasoning mode.
+
+Alternatively, you can use the `OpenAIChatClient` configured to point to your local Ollama server, which may be useful if you're already familiar with the OpenAI client interface.
+
+## Examples
+
+| File | Description |
+|------|-------------|
+| [`ollama_agent_basic.py`](ollama_agent_basic.py) | Basic Ollama agent with tool calling using native Ollama Chat Client. Shows both streaming and non-streaming responses. |
+| [`ollama_agent_reasoning.py`](ollama_agent_reasoning.py) | Ollama agent with reasoning capabilities using native Ollama Chat Client. Shows how to enable thinking/reasoning mode. |
+| [`ollama_chat_client.py`](ollama_chat_client.py) | Direct usage of the native Ollama Chat Client with tool calling. |
+| [`ollama_chat_multimodal.py`](ollama_chat_multimodal.py) | Ollama Chat Client with multimodal (image) input capabilities. |
+| [`ollama_with_openai_chat_client.py`](ollama_with_openai_chat_client.py) | Alternative approach using OpenAI Chat Client configured to use local Ollama models. |
+
+## Configuration
+
+The examples use environment variables for configuration. Set the appropriate variables based on which example you're running:
+
+### For Native Ollama Examples
+
+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_MODEL`: The model name to use
+  - Example: `export OLLAMA_MODEL="qwen2.5:8b"`
+  - Must be a model you have pulled with Ollama
+
+### For OpenAI Client with Ollama (`ollama_with_openai_chat_client.py`)
+
+Set the following environment variables:
+
+- `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

python/samples/02-agents/providers/ollama/ollama_agent_basic.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from datetime import datetime
+
+from agent_framework import Agent, tool
+from agent_framework.ollama import OllamaChatClient
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+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_MODEL environment variable or modify the code below.
+https://ollama.com/
+
+"""
+
+
+# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production;
+# see samples/02-agents/tools/function_tool_with_approval.py
+# and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
+@tool(approval_mode="never_require")
+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 = Agent(
+        client=OllamaChatClient(),
+        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 = Agent(
+        client=OllamaChatClient(),
+        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(query, stream=True):
+        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())

python/samples/02-agents/providers/ollama/ollama_agent_reasoning.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import Agent
+from agent_framework.ollama import OllamaChatClient
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+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_MODEL environment variable or modify the code below.
+https://ollama.com/
+
+"""
+
+
+async def main() -> None:
+    print("=== Response Reasoning Example ===")
+
+    agent = Agent(
+        client=OllamaChatClient(),
+        name="TimeAgent",
+        instructions="You are a helpful agent answer in one sentence.",
+        default_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 or "") for c in result.messages[-1].contents if c.type == "text_reasoning")
+    print(f"Reasoning: {reasoning}")
+    print(f"Answer: {result}\n")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/02-agents/providers/ollama/ollama_chat_client.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from datetime import datetime
+
+from agent_framework import Message, tool
+from agent_framework.ollama import OllamaChatClient
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+Ollama Chat Client Example
+
+This sample demonstrates using the native Ollama Chat Client directly.
+
+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_MODEL environment variable or modify the code below.
+https://ollama.com/
+
+"""
+
+
+# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production;
+# see samples/02-agents/tools/function_tool_with_approval.py
+# and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
+@tool(approval_mode="never_require")
+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"
+    messages = [Message(role="user", contents=[message])]
+    stream = False
+    print(f"User: {message}")
+    if stream:
+        print("Assistant: ", end="")
+        async for chunk in client.get_response(messages, options={"tools": [get_time]}, stream=True):
+            if str(chunk):
+                print(str(chunk), end="")
+        print("")
+    else:
+        response = await client.get_response(messages, options={"tools": [get_time]})
+        print(f"Assistant: {response}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/02-agents/providers/ollama/ollama_chat_multimodal.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import Content, Message
+from agent_framework.ollama import OllamaChatClient
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+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_MODEL 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 = Message(
+        role="user",
+        contents=[
+            Content.from_text(text="What's in this image?"),
+            Content.from_uri(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())

python/samples/02-agents/providers/ollama/ollama_with_openai_chat_client.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import os
+from random import randint
+from typing import Annotated
+
+from agent_framework import Agent, tool
+from agent_framework.openai import OpenAIChatClient
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+Ollama with OpenAI Chat Client Example
+
+This sample demonstrates using Ollama models through OpenAI Chat Client by
+configuring the base URL to point to your local Ollama server for local AI inference.
+Ollama allows you to run large language models locally on your machine.
+
+Environment Variables:
+- OLLAMA_ENDPOINT: The base URL for your Ollama server (e.g., "http://localhost:11434/v1/")
+- OLLAMA_MODEL: The model name to use (e.g., "mistral", "llama3.2", "phi3")
+"""
+
+
+# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production;
+# see samples/02-agents/tools/function_tool_with_approval.py
+# and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
+@tool(approval_mode="never_require")
+def get_weather(
+    location: Annotated[str, "The location to get the weather for."],
+) -> str:
+    """Get the weather for a given location."""
+    conditions = ["sunny", "cloudy", "rainy", "stormy"]
+    return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
+
+
+async def non_streaming_example() -> None:
+    """Example of non-streaming response (get the complete result at once)."""
+    print("=== Non-streaming Response Example ===")
+
+    _client = OpenAIChatClient(
+        api_key="ollama",  # Just a placeholder, Ollama doesn't require API key
+        base_url=os.getenv("OLLAMA_ENDPOINT"),
+        model=os.getenv("OLLAMA_MODEL"),
+    )
+    agent = Agent(
+        client=_client,
+        name="WeatherAgent",
+        instructions="You are a helpful weather agent.",
+        tools=[get_weather],
+    )
+
+    query = "What's the weather like in Seattle?"
+    print(f"User: {query}")
+    result = await agent.run(query)
+    print(f"Agent: {result}\n")
+
+
+async def streaming_example() -> None:
+    """Example of streaming response (get results as they are generated)."""
+    print("=== Streaming Response Example ===")
+
+    _client = OpenAIChatClient(
+        api_key="ollama",  # Just a placeholder, Ollama doesn't require API key
+        base_url=os.getenv("OLLAMA_ENDPOINT"),
+        model=os.getenv("OLLAMA_MODEL"),
+    )
+    agent = Agent(
+        client=_client,
+        name="WeatherAgent",
+        instructions="You are a helpful weather agent.",
+        tools=[get_weather],
+    )
+
+    query = "What's the weather like in Portland?"
+    print(f"User: {query}")
+    print("Agent: ", end="", flush=True)
+    async for chunk in agent.run(query, stream=True):
+        if chunk.text:
+            print(chunk.text, end="", flush=True)
+    print("\n")
+
+
+async def main() -> None:
+    print("=== Ollama with OpenAI Chat Client Agent Example ===")
+
+    await non_streaming_example()
+    await streaming_example()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())