> ## 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 Learning: Async Mode

> Demonstrates Team learning with async database operations.

```python team_async_learning.py theme={null}
"""
Team Learning: Async Mode
=========================
Demonstrates Team learning with async database operations.

Uses AsyncPostgresDb for non-blocking database access.
"""

import asyncio

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

db = AsyncPostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

researcher = Agent(
    name="Researcher",
    model=OpenAIResponses(id="gpt-5.2"),
    role="Research topics thoroughly.",
)

summarizer = Agent(
    name="Summarizer",
    model=OpenAIResponses(id="gpt-5.2"),
    role="Create concise summaries.",
)

team = Team(
    name="Research Team",
    model=OpenAIResponses(id="gpt-5.2"),
    members=[researcher, summarizer],
    db=db,
    learning=True,
    markdown=True,
)


async def main():
    user_id = "async_test@example.com"

    print("\n" + "=" * 60)
    print("SESSION 1: Async learning extraction")
    print("=" * 60 + "\n")

    await team.aprint_response(
        "I'm a backend engineer interested in distributed systems. "
        "I prefer deep technical content with architecture diagrams.",
        user_id=user_id,
        session_id="async_session_1",
        stream=True,
    )

    lm = team.learning_machine
    print("\n--- Extracted Profile (Async) ---")
    lm.user_profile_store.print(user_id=user_id)

    print("\n" + "=" * 60)
    print("SESSION 2: Async recall in new session")
    print("=" * 60 + "\n")

    await team.aprint_response(
        "Based on my background, explain consensus algorithms.",
        user_id=user_id,
        session_id="async_session_2",
        stream=True,
    )


if __name__ == "__main__":
    asyncio.run(main())
```

## Run the Example

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

**1. Install dependencies**

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

**2. Export your OpenAI API key**

```bash Mac/Linux theme={null}
export OPENAI_API_KEY="your_openai_api_key_here"
```

```bash Windows theme={null}
$Env:OPENAI_API_KEY="your_openai_api_key_here"
```

<Snippet file="run-pgvector-step.mdx" />

**3. Run the example**

Save the code above as `team_async_learning.py`, then run:

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

Full source: [cookbook/03\_teams/12\_learning/09\_team\_async\_learning.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/03_teams/12_learning/09_team_async_learning.py)


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