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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.
Code
cookbook/examples/teams/memory/02_team_with_agentic_memory.py
"""
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 Agent
from agno.db.postgres import PostgresDb
from agno.memory import MemoryManager # noqa: F401
from agno.models.openai import OpenAIChat
from agno.team import Team
db_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
# )
Usage
Create a virtual environment
Open the Terminal and create a python virtual environment.python3 -m venv .venv
source .venv/bin/activate
Set up PostgreSQL database
./cookbook/run_pgvector.sh
Install required libraries
pip install agno openai 'psycopg[binary]' sqlalchemy
Set environment variables
export OPENAI_API_KEY=****
Run the agent
python cookbook/examples/teams/memory/02_team_with_agentic_memory.py