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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
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 import Agent
from agno.db.postgres import PostgresDb
from agno.memory import MemoryManager # noqa: F401
from agno.models.openai import OpenAIResponses
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=OpenAIResponses(id="gpt-5.2"),
)
team = Team(
model=OpenAIResponses(id="gpt-5.2"),
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
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
Install dependencies
uv pip install -U agno openai psycopg sqlalchemy
Set up PostgreSQL database
Start PostgreSQL with pgvector and update the connection string in the code as needed.
Set environment variables
export OPENAI_API_KEY=your_openai_api_key_here
Run the example
python team_with_agentic_memory.py