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

# Direct Response with Team History

> Combine respond_directly with add_history_to_context so a team member answering the user directly still sees prior conversation turns.

The team leader routes each request to the appropriate member, and that member responds directly to the user.

In addition, the team has access to the conversation history through `add_history_to_context=True`.

```python respond_directly_with_history.py theme={null}
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.team.team import Team


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-5.2"),
    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-5.2"),
    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-5.2"),
    tools=[get_activities],
)


geo_search_team = Team(
    name="Geo Search Team",
    model=OpenAIResponses(id="gpt-5.2"),
    respond_directly=True,
    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.",
    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
)


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)
```

## Usage

<Steps>
  <Step title="Create a Python file">
    Create `respond_directly_with_history.py` with the code above.
  </Step>

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