mirror of
https://github.com/microsoft/agent-framework.git
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Dmytro Struk
b0fd4946e6
* Removed session_id filtering in Mem0 implementation * Fixed redis samples * Resolved comments
112 lines
4.3 KiB
Python
112 lines
4.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from agent_framework import tool
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from agent_framework.azure import AzureAIAgentClient
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from agent_framework.mem0 import Mem0ContextProvider
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from azure.identity.aio import AzureCliCredential
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
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@tool(approval_mode="never_require")
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def get_user_preferences(user_id: str) -> str:
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"""Mock function to get user preferences."""
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preferences = {
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"user123": "Prefers concise responses and technical details",
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"user456": "Likes detailed explanations with examples",
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}
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return preferences.get(user_id, "No specific preferences found")
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async def example_cross_session_memory() -> None:
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"""Example 1: Cross-session memory (memories shared across all sessions for a user)."""
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print("1. Cross-Session Memory Example:")
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print("-" * 40)
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user_id = "user123"
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async with (
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AzureCliCredential() as credential,
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AzureAIAgentClient(credential=credential).as_agent(
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name="MemoryAssistant",
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instructions="You are an assistant that remembers user preferences across conversations.",
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tools=get_user_preferences,
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context_providers=[Mem0ContextProvider(user_id=user_id)],
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) as agent,
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):
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# Store some preferences
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query = "Remember that I prefer technical responses with code examples when discussing programming."
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result}\n")
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# Mem0 processes and indexes memories asynchronously.
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print("Waiting for memories to be processed...")
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await asyncio.sleep(12)
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# Create a new session - memories should still be accessible
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# because Mem0 scopes by user_id, not session
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new_session = agent.create_session()
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query = "What do you know about my preferences?"
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print(f"User (new session): {query}")
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result = await agent.run(query, session=new_session)
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print(f"Agent: {result}\n")
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async def example_agent_scoped_memory() -> None:
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"""Example 2: Agent-scoped memory (memories isolated per agent)."""
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print("2. Agent-Scoped Memory Example:")
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print("-" * 40)
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async with (
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AzureCliCredential() as credential,
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AzureAIAgentClient(credential=credential).as_agent(
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name="PersonalAssistant",
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instructions="You are a personal assistant that helps with personal tasks.",
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context_providers=[Mem0ContextProvider(agent_id="agent_personal")],
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) as personal_agent,
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AzureAIAgentClient(credential=credential).as_agent(
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name="WorkAssistant",
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instructions="You are a work assistant that helps with professional tasks.",
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context_providers=[Mem0ContextProvider(agent_id="agent_work")],
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) as work_agent,
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):
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# Store personal information
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query = "Remember that I like to exercise at 6 AM and prefer outdoor activities."
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print(f"User to Personal Agent: {query}")
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result = await personal_agent.run(query)
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print(f"Personal Agent: {result}\n")
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# Store work information
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query = "Remember that I have team meetings every Tuesday at 2 PM."
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print(f"User to Work Agent: {query}")
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result = await work_agent.run(query)
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print(f"Work Agent: {result}\n")
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# Mem0 processes and indexes memories asynchronously.
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print("Waiting for memories to be processed...")
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await asyncio.sleep(12)
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# Test memory isolation - each agent should only recall its own memories
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query = "What do you know about my schedule?"
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print(f"User to Personal Agent: {query}")
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result = await personal_agent.run(query)
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print(f"Personal Agent: {result}\n")
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print(f"User to Work Agent: {query}")
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result = await work_agent.run(query)
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print(f"Work Agent: {result}\n")
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async def main() -> None:
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"""Run all Mem0 session management examples."""
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print("=== Mem0 Session Management Example ===\n")
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await example_cross_session_memory()
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await example_agent_scoped_memory()
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if __name__ == "__main__":
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asyncio.run(main())
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