> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Team with Agentic Memory

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

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

## Code

```python team_with_agentic_memory.py theme={null}
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

<Snippet file="create-venv-step.mdx" />

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno openai 'psycopg[binary]' sqlalchemy
```

**2. Start PostgreSQL database**

```bash theme={null}
./cookbook/scripts/run_pgvector.sh
```

**3. Set environment variables**

```bash theme={null}
export OPENAI_API_KEY=your_openai_api_key_here
```

**4. Run the example**

```bash theme={null}
python team_with_agentic_memory.py
```


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