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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>
106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from typing import Any
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from agent_framework import Agent, AgentSession, BaseContextProvider, SessionContext
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from agent_framework.foundry import FoundryChatClient
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from azure.identity import AzureCliCredential
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"""
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Agent Memory with Context Providers and Session State
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Context providers inject dynamic context into each agent call. This sample
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shows a provider that stores the user's name in session state and personalizes
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responses — the name persists across turns via the session.
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"""
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# <context_provider>
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class UserMemoryProvider(BaseContextProvider):
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"""A context provider that remembers user info in session state."""
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DEFAULT_SOURCE_ID = "user_memory"
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def __init__(self):
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super().__init__(self.DEFAULT_SOURCE_ID)
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async def before_run(
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self,
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*,
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agent: Any,
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session: AgentSession | None,
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context: SessionContext,
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state: dict[str, Any],
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) -> None:
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"""Inject personalization instructions based on stored user info."""
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user_name = state.get("user_name")
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if user_name:
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context.extend_instructions(
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self.source_id,
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f"The user's name is {user_name}. Always address them by name.",
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)
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else:
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context.extend_instructions(
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self.source_id,
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"You don't know the user's name yet. Ask for it politely.",
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)
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async def after_run(
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self,
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*,
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agent: Any,
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session: AgentSession | None,
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context: SessionContext,
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state: dict[str, Any],
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) -> None:
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"""Extract and store user info in session state after each call."""
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for msg in context.input_messages:
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text = msg.text if hasattr(msg, "text") else ""
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if isinstance(text, str) and "my name is" in text.lower():
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state["user_name"] = text.lower().split("my name is")[-1].strip().split()[0].capitalize()
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# </context_provider>
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async def main() -> None:
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# <create_agent>
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client = FoundryChatClient(
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project_endpoint="https://your-project.services.ai.azure.com",
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model="gpt-4o",
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credential=AzureCliCredential(),
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)
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agent = Agent(
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client=client,
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name="MemoryAgent",
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instructions="You are a friendly assistant.",
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context_providers=[UserMemoryProvider()],
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)
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# </create_agent>
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# <run_with_memory>
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session = agent.create_session()
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# The provider doesn't know the user yet — it will ask for a name
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result = await agent.run("Hello! What's the square root of 9?", session=session)
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print(f"Agent: {result}\n")
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# Now provide the name — the provider stores it in session state
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result = await agent.run("My name is Alice", session=session)
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print(f"Agent: {result}\n")
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# Subsequent calls are personalized — name persists via session state
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result = await agent.run("What is 2 + 2?", session=session)
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print(f"Agent: {result}\n")
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# Inspect session state to see what the provider stored
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provider_state = session.state.get("user_memory", {})
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print(f"[Session State] Stored user name: {provider_state.get('user_name')}")
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# </run_with_memory>
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if __name__ == "__main__":
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asyncio.run(main())
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