mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Eduard van Valkenburg
2576e7a091
* updated telemetry work * updated telemetry * slight improvement * updated tests * fixes for telemetry * fixes for mypy * added settings setup to runner to avoid error * streamline usage * updated tests * updated tests * further refinement * fix dumped item for otel * removed enable_workflow_otel * final fixes * final fixes * updated samples * removed exporters * fix tests * fixed last import' * fixed devui
83 lines
2.8 KiB
Python
83 lines
2.8 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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# type: ignore
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import asyncio
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from random import randint
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from typing import TYPE_CHECKING, Annotated
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from agent_framework.openai import OpenAIResponsesClient
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from pydantic import Field
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if TYPE_CHECKING:
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from agent_framework import ChatClientProtocol
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"""
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This is the simplest sample of using the Agent Framework with telemetry.
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This relies on the environment setting up the telemetry, you can test this with
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by navigating to this folder and running:
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uv run --env-file=zero_code.env opentelemetry-instrument python 01-zero_code.py
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Check the zero_code.env file for the settings used in this example and to adapt it to your environment.
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"""
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async def get_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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) -> str:
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"""Get the weather for a given location."""
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await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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async def run_chat_client(client: "ChatClientProtocol", stream: bool = False) -> None:
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"""Run an AI service.
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This function runs an AI service and prints the output.
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Telemetry will be collected for the service execution behind the scenes,
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and the traces will be sent to the configured telemetry backend.
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The telemetry will include information about the AI service execution.
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Args:
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stream: Whether to use streaming for the plugin
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Remarks:
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When function calling is outside the open telemetry loop
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each of the call to the model is handled as a seperate span,
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while when the open telemetry is put last, a single span
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is shown, which might include one or more rounds of function calling.
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So for the scenario below, you should see the following:
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2 spans with gen_ai.operation.name=chat
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The first has finish_reason "tool_calls"
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The second has finish_reason "stop"
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2 spans with gen_ai.operation.name=execute_tool
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"""
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message = "What's the weather in Amsterdam and in Paris?"
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print(f"User: {message}")
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if stream:
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print("Assistant: ", end="")
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async for chunk in client.get_streaming_response(message, tools=get_weather):
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if str(chunk):
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print(str(chunk), end="")
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print("")
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else:
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response = await client.get_response(message, tools=get_weather)
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print(f"Assistant: {response}")
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async def main() -> None:
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client = OpenAIResponsesClient()
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# Scenarios where telemetry is collected in the SDK, from the most basic to the most complex.
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await run_chat_client(client, stream=True)
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await run_chat_client(client, stream=False)
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if __name__ == "__main__":
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asyncio.run(main())
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