> ## 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.

# Gemini Interactions - Multi-turn Conversation

> Demonstrates server-side conversation history with the Interactions API.

Demonstrates server-side conversation history with the Interactions API. After the first response, subsequent turns only send the new message and reference the previous interaction via `previous_interaction_id`. This enables implicit caching and reduces token costs.

```python multi_turn.py theme={null}
"""
Gemini Interactions - Multi-turn Conversation
==============================================

Demonstrates server-side conversation history with the Interactions API.
After the first response, subsequent turns only send the new message
and reference the previous interaction via `previous_interaction_id`.
This enables implicit caching and reduces token costs.

Multi-turn requires a db (e.g. SqliteDb) so the interaction_id from each
turn's response is persisted on the assistant message and read back on
the next turn.
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.google import GeminiInteractions

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

agent = Agent(
    model=GeminiInteractions(id="gemini-3.5-flash"),
    add_history_to_context=True,
    db=SqliteDb(db_file="tmp/data.db"),
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    # First turn - establishes the interaction
    agent.print_response("My name is Alice and I love hiking in the mountains.")

    # Second turn - references the previous interaction for context
    agent.print_response("What did I just tell you about myself?")

    # Third turn - continues the conversation chain
    agent.print_response(
        "Suggest a hiking destination based on what you know about me."
    )
```

## Run the Example

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

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

  <Step title="Export your Google API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export GOOGLE_API_KEY="your_google_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:GOOGLE_API_KEY="your_google_api_key_here"
      ```
    </CodeGroup>
  </Step>

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

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

Full source: [cookbook/90\_models/google/gemini\_interactions/multi\_turn.py](https://github.com/agno-agi/agno/blob/main/cookbook/90_models/google/gemini_interactions/multi_turn.py)