mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Eduard van Valkenburg
3a49b1d6dd
* [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces Also clean up follow-on docs, environment guidance, package metadata, and lab test stability. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix deleted semantic-kernel sample links Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * improve foundry language * Fix A2A Foundry sample regression Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
64 lines
2.0 KiB
Python
64 lines
2.0 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from typing import Annotated
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from agent_framework import Agent, FunctionInvocationContext, tool
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from agent_framework.openai import OpenAIChatClient
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from dotenv import load_dotenv
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from pydantic import Field
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# Load environment variables from .env file
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load_dotenv()
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"""
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AI Function with kwargs Example
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This example demonstrates how to inject runtime context into an AI function
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from the agent's run method, without exposing it to the AI model.
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This is useful for passing runtime information like access tokens, user IDs, or
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request-specific context that the tool needs but the model shouldn't know about
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or provide. The injected context parameter can be typed as
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``FunctionInvocationContext`` as shown here, or left untyped as ``ctx`` when you
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prefer a lighter-weight sample setup.
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"""
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# Define the function tool with explicit invocation context.
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# The context parameter can also be declared as an untyped ``ctx`` parameter.
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@tool(approval_mode="never_require")
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def get_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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ctx: FunctionInvocationContext,
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) -> str:
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"""Get the weather for a given location."""
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# Extract the injected argument from the explicit context
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user_id = ctx.kwargs.get("user_id", "unknown")
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# Simulate using the user_id for logging or personalization
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print(f"Getting weather for user: {user_id}")
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return f"The weather in {location} is cloudy with a high of 15°C."
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async def main() -> None:
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agent = Agent(
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client=OpenAIChatClient(),
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name="WeatherAgent",
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instructions="You are a helpful weather assistant.",
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tools=[get_weather],
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)
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# Pass the runtime context explicitly when running the agent.
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response = await agent.run(
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"What is the weather like in Amsterdam?",
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function_invocation_kwargs={"user_id": "user_123"},
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)
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print(f"Agent: {response.text}")
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if __name__ == "__main__":
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asyncio.run(main())
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