Team With Agentic Memory

team_with_agentic_memory.py

"""
Team With Agentic Memory
========================

Demonstrates team-level agentic memory creation and updates during runs.
"""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIResponses
from agno.team import Team

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db_url=db_url)
john_doe_id = "john_doe@example.com"

# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------
agent = Agent(
    model=OpenAIResponses(id="gpt-5-mini"),
)

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
team = Team(
    model=OpenAIResponses(id="gpt-5-mini"),
    members=[agent],
    db=db,
    enable_agentic_memory=True,
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    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)

Example behavior

enable_agentic_memory=True gives the leader a memory-update tool. It saves information when the model chooses that tool, rather than automatically extracting memories after every response. Reuse the same database and user_id to recall those stored records in later sessions.

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Install dependencies

uv pip install -U agno "psycopg[binary]" openai sqlalchemy

Export your OpenAI API key

export OPENAI_API_KEY="your_openai_api_key_here"

Run PgVector

docker run -d \
  -e POSTGRES_DB=ai \
  -e POSTGRES_USER=ai \
  -e POSTGRES_PASSWORD=ai \
  -e PGDATA=/var/lib/postgresql \
  -v pgvolume:/var/lib/postgresql \
  -p 5532:5432 \
  --name pgvector \
  agnohq/pgvector:18

Run the example

Save the code above as team_with_agentic_memory.py, then run:

python team_with_agentic_memory.py

Full source: cookbook/03_teams/06_memory/02_team_with_agentic_memory.py