mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Giles Odigwe
6f6ee61834
* Python: Fix broken samples and add missing READMEs - simple_context_provider: move instructions kwarg into options dict - suspend_resume_session: use OpenAIChatCompletionClient for in-memory demo - foundry_chat_client_with_hosted_mcp: move store kwarg into options dict - Add README.md for context_providers and conversations sample folders Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix additional sample issues in context_providers - mem0_basic: send preferences query before sleep so Mem0 can learn them, print result from new session recall - mem0_sessions: add session for multi-turn conversation in agent-scoped example, remove user_id from agent-scoped provider (Mem0 API stores memories without user_id when agent_id is provided), use single message for storing preferences - redis_basics: print retrieved context messages instead of raw object - redis_sessions: add missing load_dotenv() call - redis_basics/redis_sessions: fix docstrings referencing wrong client type - azure_redis_conversation: replace duplicate copyright with load_dotenv() Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix broken link in declarative README openai_responses_agent.py was renamed to openai_agent.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
102 lines
3.5 KiB
Python
102 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 agent_framework.openai import OpenAIChatCompletionClient
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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=OpenAIChatCompletionClient(),
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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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