mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Eduard van Valkenburg
534e5f5bf7
* Python: improve .env precedence and observability samples - Switch load_settings to explicit precedence: overrides -> explicit .env -> environment -> defaults\n- Raise when env_file_path is provided but missing\n- Update settings docs and tests for new behavior\n- Refresh observability samples and README guidance for env loading options\n\nCloses #3864\n\nCo-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed some imports * Fix load_settings CI regressions Allow explicit env_file_path values that exist but are not regular files (for example /dev/null) by checking path existence before dotenv parsing, and restore a dict accumulator with typed return cast to satisfy mypy. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Avoid implicit dotenv in observability Only load dotenv in observability helpers when env_file_path is explicitly provided, and remove test os.devnull workarounds that are no longer necessary. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
79 lines
3.1 KiB
Python
79 lines
3.1 KiB
Python
# 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.azure import AzureAIClient
|
|
from agent_framework.observability import get_tracer
|
|
from azure.ai.projects.aio import AIProjectClient
|
|
from azure.identity.aio import AzureCliCredential
|
|
from dotenv import load_dotenv
|
|
from opentelemetry.trace import SpanKind
|
|
from opentelemetry.trace.span import format_trace_id
|
|
from pydantic import Field
|
|
|
|
"""
|
|
This sample shows you can setup telemetry for an Azure AI agent.
|
|
It uses the Azure AI client to setup the telemetry, this calls out to
|
|
Azure AI for the connection string of the attached Application Insights
|
|
instance.
|
|
|
|
You must add an Application Insights instance to your Azure AI project
|
|
for this sample to work.
|
|
"""
|
|
|
|
# For loading the `AZURE_AI_PROJECT_ENDPOINT` environment variable
|
|
load_dotenv()
|
|
|
|
|
|
# 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")
|
|
async def get_weather(
|
|
location: Annotated[str, Field(description="The location to get the weather for.")],
|
|
) -> str:
|
|
"""Get the weather for a given location."""
|
|
await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call
|
|
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 main():
|
|
async with (
|
|
AzureCliCredential() as credential,
|
|
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
|
|
AzureAIClient(project_client=project_client) as client,
|
|
):
|
|
# This will enable tracing and configure the application to send telemetry data to the
|
|
# Application Insights instance attached to the Azure AI project.
|
|
# This will override any existing configuration.
|
|
await client.configure_azure_monitor(enable_live_metrics=True)
|
|
|
|
questions = ["What's the weather in Amsterdam?", "and in Paris, and which is better?", "Why is the sky blue?"]
|
|
|
|
with get_tracer().start_as_current_span("Single Agent Chat", kind=SpanKind.CLIENT) as current_span:
|
|
print(f"Trace ID: {format_trace_id(current_span.get_span_context().trace_id)}")
|
|
|
|
agent = Agent(
|
|
client=client,
|
|
tools=get_weather,
|
|
name="WeatherAgent",
|
|
instructions="You are a weather assistant.",
|
|
id="edvan-weather-agent",
|
|
)
|
|
session = agent.create_session()
|
|
for question in questions:
|
|
print(f"\nUser: {question}")
|
|
print(f"{agent.name}: ", end="")
|
|
async for update in agent.run(question, session=session, stream=True):
|
|
if update.text:
|
|
print(update.text, end="")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|