Team with Agentic Memory

Let a team create and update user memories during a run.

The local database setup below requires Docker.

Set enable_agentic_memory=True to give a team the update_user_memory tool for creating and updating user memories during a run.

Code

from agno.agent import Agent
from agno.db.postgres import PostgresDb
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)

Usage

Set up your virtual environment

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

Install dependencies

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

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

Set environment variables

export OPENAI_API_KEY=your_openai_api_key_here

Run the example

python team_with_agentic_memory.py