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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>
101 lines
3.5 KiB
Python
101 lines
3.5 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from agent_framework import Agent, AgentSession
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from agent_framework.foundry import FoundryChatClient
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from azure.identity.aio import AzureCliCredential
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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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"""
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Session Suspend and Resume Example
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This sample demonstrates how to suspend and resume conversation sessions, comparing
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service-managed sessions (Azure AI) with in-memory sessions (OpenAI) for persistent
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conversation state across sessions.
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"""
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async def suspend_resume_service_managed_session() -> None:
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"""Demonstrates how to suspend and resume a service-managed session."""
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print("=== Suspend-Resume Service-Managed Session ===")
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# FoundryChatClient supports service-managed sessions.
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async with (
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AzureCliCredential() as credential,
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Agent(
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client=FoundryChatClient(credential=credential),
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name="MemoryBot",
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instructions="You are a helpful assistant that remembers our conversation.",
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) as agent,
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):
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# Start a new session for the agent conversation.
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session = agent.create_session()
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# Respond to user input.
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query = "Hello! My name is Alice and I love pizza."
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print(f"User: {query}")
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print(f"Agent: {await agent.run(query, session=session)}\n")
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# Serialize the session state, so it can be stored for later use.
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serialized_session = session.to_dict()
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# The session can now be saved to a database, file, or any other storage mechanism and loaded again later.
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print(f"Serialized session: {serialized_session}\n")
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# Deserialize the session state after loading from storage.
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resumed_session = AgentSession.from_dict(serialized_session)
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# Respond to user input.
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query = "What do you remember about me?"
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print(f"User: {query}")
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print(f"Agent: {await agent.run(query, session=resumed_session)}\n")
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async def suspend_resume_in_memory_session() -> None:
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"""Demonstrates how to suspend and resume an in-memory session."""
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print("=== Suspend-Resume In-Memory Session ===")
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# OpenAI Chat Client is used as an example here,
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# other chat clients can be used as well.
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agent = Agent(
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client=FoundryChatClient(),
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name="MemoryBot",
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instructions="You are a helpful assistant that remembers our conversation.",
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)
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# Start a new session for the agent conversation.
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session = agent.create_session()
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# Respond to user input.
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query = "Hello! My name is Alice and I love pizza."
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print(f"User: {query}")
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print(f"Agent: {await agent.run(query, session=session)}\n")
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# Serialize the session state, so it can be stored for later use.
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serialized_session = session.to_dict()
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# The session can now be saved to a database, file, or any other storage mechanism and loaded again later.
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print(f"Serialized session: {serialized_session}\n")
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# Deserialize the session state after loading from storage.
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resumed_session = AgentSession.from_dict(serialized_session)
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# Respond to user input.
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query = "What do you remember about me?"
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print(f"User: {query}")
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print(f"Agent: {await agent.run(query, session=resumed_session)}\n")
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async def main() -> None:
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print("=== Suspend-Resume Session Examples ===")
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await suspend_resume_service_managed_session()
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await suspend_resume_in_memory_session()
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if __name__ == "__main__":
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asyncio.run(main())
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