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* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
144 lines
4.2 KiB
Python
144 lines
4.2 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from agent_framework import Agent
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from agent_framework.openai import OpenAIResponsesClient
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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"""Background Responses Sample.
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This sample demonstrates long-running agent operations using the OpenAI
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Responses API ``background`` option. Two patterns are shown:
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1. **Non-streaming polling** – start a background run, then poll with the
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``continuation_token`` until the operation completes.
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2. **Streaming with resumption** – start a background streaming run, simulate
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an interruption, and resume from the last ``continuation_token``.
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Prerequisites:
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- Set the ``OPENAI_API_KEY`` environment variable.
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- A model that benefits from background execution (e.g. ``o3``).
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"""
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# 1. Create the agent with an OpenAI Responses client.
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agent = Agent(
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name="researcher",
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instructions="You are a helpful research assistant. Be concise.",
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client=OpenAIResponsesClient(model="o3"),
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)
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async def non_streaming_polling() -> None:
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"""Demonstrate non-streaming background run with polling."""
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print("=== Non-Streaming Polling ===\n")
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session = agent.create_session()
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# 2. Start a background run — returns immediately.
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response = await agent.run(
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messages="Briefly explain the theory of relativity in two sentences.",
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session=session,
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options={"background": True},
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)
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print(f"Initial status: continuation_token={'set' if response.continuation_token else 'None'}")
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# 3. Poll until the operation completes.
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poll_count = 0
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while response.continuation_token is not None:
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poll_count += 1
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await asyncio.sleep(2)
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response = await agent.run(
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session=session,
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options={"continuation_token": response.continuation_token},
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)
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print(f" Poll {poll_count}: continuation_token={'set' if response.continuation_token else 'None'}")
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# 4. Done — print the final result.
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print(f"\nResult ({poll_count} poll(s)):\n{response.text}\n")
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async def streaming_with_resumption() -> None:
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"""Demonstrate streaming background run with simulated interruption and resumption."""
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print("=== Streaming with Resumption ===\n")
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session = agent.create_session()
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# 2. Start a streaming background run.
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last_token = None
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stream = agent.run(
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messages="Briefly list three benefits of exercise.",
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stream=True,
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session=session,
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options={"background": True},
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)
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# 3. Read some chunks, then simulate an interruption.
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chunk_count = 0
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print("First stream (before interruption):")
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async for update in stream:
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last_token = update.continuation_token
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if update.text:
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print(update.text, end="", flush=True)
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chunk_count += 1
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if chunk_count >= 3:
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print("\n [simulated interruption]")
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break
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# 4. Resume from the last continuation token.
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if last_token is not None:
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print("Resumed stream:")
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stream = agent.run(
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stream=True,
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session=session,
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options={"continuation_token": last_token},
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)
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async for update in stream:
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if update.text:
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print(update.text, end="", flush=True)
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print("\n")
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async def main() -> None:
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await non_streaming_polling()
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await streaming_with_resumption()
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if __name__ == "__main__":
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asyncio.run(main())
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"""
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Sample output:
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=== Non-Streaming Polling ===
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Initial status: continuation_token=set
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Poll 1: continuation_token=set
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Poll 2: continuation_token=None
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Result (2 poll(s)):
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The theory of relativity, developed by Albert Einstein, consists of special
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relativity (1905), which shows that the laws of physics are the same for all
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non-accelerating observers and that the speed of light is constant, and general
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relativity (1915), which describes gravity as the curvature of spacetime caused
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by mass and energy.
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=== Streaming with Resumption ===
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First stream (before interruption):
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Here are three
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[simulated interruption]
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Resumed stream:
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key benefits of regular exercise:
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1. **Improved cardiovascular health** ...
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2. **Better mental health** ...
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3. **Stronger muscles and bones** ...
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"""
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