# OpenAI Chat Responses (/examples/agents/advanced/interchange-model/openai-chat-responses)



The local `get_weather` function returns simulated weather, not live conditions. Tool choice remains model-selected; a summary turn may reuse history without calling the tool again. This example demonstrates tool-message and history interchange.

```python title="openai_chat_responses.py"
import os

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIChat, OpenAIResponses


def get_weather(city: str) -> str:
    """Get the current weather for a city."""
    return f"The weather in {city} is sunny and 22C."


def main() -> None:
    db_url = os.getenv(
        "AGNO_POSTGRES_URL",
        "postgresql+psycopg://ai:ai@localhost:5532/ai",
    )
    db = PostgresDb(db_url)

    agent = Agent(
        model=OpenAIChat(id="gpt-5.6-luna"),
        db=db,
        add_history_to_context=True,
        num_history_runs=10,
        tools=[get_weather],
    )

    # Turn 1 — OpenAI with tool call (works fine)
    agent.print_response("What is the weather in Paris?")

    # Turn 2 — OpenAI Responses with tool call
    agent.model = OpenAIResponses()
    agent.print_response("What is the weather in London?")

    # Turn 3 — OpenAI with tool call (works fine on its own)
    agent.model = OpenAIChat(id="gpt-5.6-luna")
    agent.print_response("What is the weather in Tokyo?")

    # Turn 4 — OpenAI Responses summary
    agent.model = OpenAIResponses()
    agent.print_response("Summarize all the weather we checked.")


if __name__ == "__main__":
    main()
```

## Run the Example [#run-the-example]

<Steps>
    <Step title="Set up your virtual environment">
      <CodeBlockTabs defaultValue="Mac">
        <CodeBlockTabsList>
          <CodeBlockTabsTrigger value="Mac">
            Mac
          </CodeBlockTabsTrigger>

          <CodeBlockTabsTrigger value="Windows">
            Windows
          </CodeBlockTabsTrigger>
        </CodeBlockTabsList>

        <CodeBlockTab value="Mac">
          ```bash
          uv venv --python 3.12
          source .venv/bin/activate
          ```
        </CodeBlockTab>

        <CodeBlockTab value="Windows">
          ```bash
          uv venv --python 3.12
          .venv\Scripts\activate
          ```
        </CodeBlockTab>
      </CodeBlockTabs>
    </Step>

  <Step title="Install dependencies">
    ```bash
    uv pip install -U agno "psycopg[binary]" openai sqlalchemy
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeBlockTabs defaultValue="Mac/Linux">
      <CodeBlockTabsList>
        <CodeBlockTabsTrigger value="Mac/Linux">
          Mac/Linux
        </CodeBlockTabsTrigger>

        <CodeBlockTabsTrigger value="Windows">
          Windows
        </CodeBlockTabsTrigger>
      </CodeBlockTabsList>

      <CodeBlockTab value="Mac/Linux">
        ```bash
        export OPENAI_API_KEY="your_openai_api_key_here"
        ```
      </CodeBlockTab>

      <CodeBlockTab value="Windows">
        ```bash
        $Env:OPENAI_API_KEY="your_openai_api_key_here"
        ```
      </CodeBlockTab>
    </CodeBlockTabs>
  </Step>

    <Step title="Run PgVector">
      <CodeBlockTabs defaultValue="macOS / Linux">
        <CodeBlockTabsList>
          <CodeBlockTabsTrigger value="macOS / Linux">
            macOS / Linux
          </CodeBlockTabsTrigger>

          <CodeBlockTabsTrigger value="Windows">
            Windows
          </CodeBlockTabsTrigger>
        </CodeBlockTabsList>

        <CodeBlockTab value="macOS / Linux">
          ```bash
          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
          ```
        </CodeBlockTab>

        <CodeBlockTab value="Windows">
          ```powershell
          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
          ```
        </CodeBlockTab>
      </CodeBlockTabs>
    </Step>

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

    ```bash
    python openai_chat_responses.py
    ```
  </Step>
</Steps>

Full source: [cookbook/02\_agents/14\_advanced/interchange\_model/openai\_chat\_responses.py](https://github.com/agno-agi/agno/blob/8f36eaf2d18e91afa7b327eec66a3cd3685dcb87/cookbook/02_agents/14_advanced/interchange_model/openai_chat_responses.py)