This example demonstrates how to use agentic memory with a team. Unlike simple memory storage, agentic memory allows the AI to actively create, update, and delete user memories during each run based on the conversation context, providing intelligent memory management.
"""This example shows you how to use persistent memory with an Agent.During each run the Agent can create/update/delete user memories.To enable this, set `enable_agentic_memory=True` in the Agent config."""from agno.agent.agent import Agentfrom agno.db.postgres import PostgresDbfrom agno.memory import MemoryManager # noqa: F401from agno.models.openai import OpenAIChatfrom agno.team import Teamdb_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"db = PostgresDb(db_url=db_url)john_doe_id = "john_doe@example.com"agent = Agent( model=OpenAIChat(id="gpt-5-mini"),)team = Team( model=OpenAIChat(id="gpt-5-mini"), members=[agent], db=db, enable_agentic_memory=True,)team.print_response( "My name is John Doe and I like to hike in the mountains on weekends.", stream=True, user_id=john_doe_id,)team.print_response("What are my hobbies?", stream=True, user_id=john_doe_id)# More examples:# agent.print_response(# "Remove all existing memories of me.",# stream=True,# user_id=john_doe_id,# )# agent.print_response(# "My name is John Doe and I like to paint.", stream=True, user_id=john_doe_id# )# agent.print_response(# "I don't pain anymore, i draw instead.", stream=True, user_id=john_doe_id# )