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

# Respond Directly With History

> Demonstrates direct member responses with team history persisted in SQLite.

```python respond_directly_with_history.py theme={null}
"""
Respond Directly With History
=============================

Demonstrates direct member responses with team history persisted in SQLite.
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.team import Team, TeamMode


# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------
def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny."


weather_agent = Agent(
    name="Weather Agent",
    role="You are a weather agent that can answer questions about the weather.",
    model=OpenAIResponses(id="gpt-5-mini"),
    tools=[get_weather],
)


def get_news(topic: str) -> str:
    return f"The news about {topic} is that it is going well!"


news_agent = Agent(
    name="News Agent",
    role="You are a news agent that can answer questions about the news.",
    model=OpenAIResponses(id="gpt-5-mini"),
    tools=[get_news],
)


def get_activities(city: str) -> str:
    return f"The activities in {city} are that it is going well!"


activities_agent = Agent(
    name="Activities Agent",
    role="You are a activities agent that can answer questions about the activities.",
    model=OpenAIResponses(id="gpt-5-mini"),
    tools=[get_activities],
)

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
geo_search_team = Team(
    name="Geo Search Team",
    model=OpenAIResponses(id="gpt-5-mini"),
    mode=TeamMode.route,
    members=[
        weather_agent,
        news_agent,
        activities_agent,
    ],
    instructions="You are a geo search agent that can answer questions about the weather, news and activities in a city.",
    use_instruction_tags=True,
    db=SqliteDb(
        db_file="tmp/geo_search_team.db"
    ),  # Add a database to store the conversation history
    add_history_to_context=True,  # Ensure that the team leader knows about previous requests
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    geo_search_team.print_response(
        "I am doing research on Tokyo. What is the weather like there?", stream=True
    )

    geo_search_team.print_response(
        "Is there any current news about that city?", stream=True
    )

    geo_search_team.print_response("What are the activities in that city?", stream=True)
```

## Run the Example

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai sqlalchemy
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```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"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `respond_directly_with_history.py`, then run:

    ```bash theme={null}
    python respond_directly_with_history.py
    ```
  </Step>
</Steps>

Full source: [cookbook/03\_teams/01\_quickstart/04\_respond\_directly\_with\_history.py](https://github.com/agno-agi/agno/blob/main/cookbook/03_teams/01_quickstart/04_respond_directly_with_history.py)