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* 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>
51 lines
1.9 KiB
Python
51 lines
1.9 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Multi-Agent Sample - Durable Task Integration (Combined Worker + Client)
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This sample demonstrates running both the worker and client in a single process
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for multiple agents with different tools. The worker registers two agents
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(WeatherAgent and MathAgent), each with their own specialized capabilities.
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Prerequisites:
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- Set AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_MODEL
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- Sign in with Azure CLI for AzureCliCredential authentication
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- Durable Task Scheduler must be running (e.g., using Docker)
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To run this sample:
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python sample.py
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"""
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import logging
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# Import helper functions from worker and client modules
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from client import get_client, run_client
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from dotenv import load_dotenv
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from worker import get_worker, setup_worker
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# Configure logging
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logging.basicConfig(level=logging.INFO, force=True)
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logger = logging.getLogger(__name__)
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def main():
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"""Main entry point - runs both worker and client in single process."""
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logger.debug("Starting Durable Task Multi-Agent Sample (Combined Worker + Client)...")
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silent_handler = logging.NullHandler()
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# Create and start the worker using helper function and context manager
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with get_worker(log_handler=silent_handler) as dts_worker:
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# Register agents using helper function
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setup_worker(dts_worker)
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# Start the worker
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dts_worker.start()
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logger.debug("Worker started and listening for requests...")
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# Create the client using helper function
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agent_client = get_client(log_handler=silent_handler)
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try:
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# Run client interactions using helper function
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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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logger.debug("Sample completed. Worker shutting down...")
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if __name__ == "__main__":
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load_dotenv()
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main()
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