mirror of
https://github.com/microsoft/agent-framework.git
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6acab3d1d6
* Refactor Anthropic model option and provider clients Rename the Anthropic client model option from model_id to model, add provider-specific Anthropic wrappers for Foundry, Bedrock, and Vertex, and expose them through the Anthropic, Foundry, Amazon, and Google namespaces. Update core option handling, docs, samples, and tests accordingly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Anthropic skills sample typing Cast the Anthropic beta client to Any in the skills sample so the pre-commit sample pyright check no longer fails on beta skills and files endpoints that are not exposed by the current SDK stubs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * undo sample mypy * Retry CI after transient external failures Retrigger PR validation after an unrelated Copilot review workflow SAML failure and a transient external tau2 git fetch failure in the Windows Python test setup. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback on model option merging Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Anthropic compatibility review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * moved all to `model` * fixes for azure ai search * Python: standardize remaining sample env var names Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix foundry-local pyright compatibility Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated env vars in cicd --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
121 lines
3.8 KiB
Python
121 lines
3.8 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Client application for interacting with multiple hosted agents.
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This client connects to the Durable Task Scheduler and interacts with two different
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agents (WeatherAgent and MathAgent), demonstrating how to work with multiple agents
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each with their own specialized capabilities and tools.
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Prerequisites:
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- The worker must be running with both agents registered
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- Set AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_MODEL when running the worker
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- Sign in with Azure CLI for AzureCliCredential authentication
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- Durable Task Scheduler must be running
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"""
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import asyncio
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import logging
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import os
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from agent_framework.azure import DurableAIAgentClient
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from azure.identity import AzureCliCredential
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from dotenv import load_dotenv
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from durabletask.azuremanaged.client import DurableTaskSchedulerClient
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# Load environment variables from .env file
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load_dotenv()
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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def get_client(
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taskhub: str | None = None, endpoint: str | None = None, log_handler: logging.Handler | None = None
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) -> DurableAIAgentClient:
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"""Create a configured DurableAIAgentClient.
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Args:
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taskhub: Task hub name (defaults to TASKHUB env var or "default")
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endpoint: Scheduler endpoint (defaults to ENDPOINT env var or "http://localhost:8080")
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log_handler: Optional logging handler for client logging
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Returns:
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Configured DurableAIAgentClient instance
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"""
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taskhub_name = taskhub or os.getenv("TASKHUB", "default")
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endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080")
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logger.debug(f"Using taskhub: {taskhub_name}")
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logger.debug(f"Using endpoint: {endpoint_url}")
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credential = None if endpoint_url == "http://localhost:8080" else AzureCliCredential()
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dts_client = DurableTaskSchedulerClient(
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host_address=endpoint_url,
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secure_channel=endpoint_url != "http://localhost:8080",
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taskhub=taskhub_name,
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token_credential=credential,
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log_handler=log_handler,
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)
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return DurableAIAgentClient(dts_client)
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def run_client(agent_client: DurableAIAgentClient) -> None:
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"""Run client interactions with both WeatherAgent and MathAgent.
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Args:
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agent_client: The DurableAIAgentClient instance
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"""
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logger.debug("Testing WeatherAgent")
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# Get reference to WeatherAgent
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weather_agent = agent_client.get_agent("WeatherAgent")
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weather_session = weather_agent.create_session()
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logger.debug(f"Created weather conversation session: {weather_session.session_id}")
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# Test WeatherAgent
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weather_message = "What is the weather in Seattle?"
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logger.info(f"User: {weather_message}")
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weather_response = weather_agent.run(weather_message, session=weather_session)
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logger.info(f"WeatherAgent: {weather_response.text} \n")
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logger.debug("Testing MathAgent")
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# Get reference to MathAgent
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math_agent = agent_client.get_agent("MathAgent")
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math_session = math_agent.create_session()
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logger.debug(f"Created math conversation session: {math_session.session_id}")
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# Test MathAgent
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math_message = "Calculate a 20% tip on a $50 bill"
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logger.info(f"User: {math_message}")
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math_response = math_agent.run(math_message, session=math_session)
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logger.info(f"MathAgent: {math_response.text} \n")
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logger.debug("Both agents completed successfully!")
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async def main() -> None:
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"""Main entry point for the client application."""
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logger.debug("Starting Durable Task Multi-Agent Client...")
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# Create client using helper function
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agent_client = get_client()
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try:
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run_client(agent_client)
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except Exception as e:
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logger.exception(f"Error during agent interaction: {e}")
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finally:
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logger.debug("Client shutting down")
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if __name__ == "__main__":
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asyncio.run(main())
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