> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-docs-scavio-google-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Video Input

> Process video as input with Agno agents.

In this example we will create an agent that can understand video input.

```python video_agent.py theme={null}
from pathlib import Path

from agno.agent import Agent
from agno.media import Video
from agno.models.google import Gemini

agent = Agent(
    model=Gemini(id="gemini-3.5-flash"),
    markdown=True,
)

# Please download "GreatRedSpot.mp4" using
# wget https://storage.googleapis.com/generativeai-downloads/images/GreatRedSpot.mp4
video_path = Path(__file__).parent.joinpath("GreatRedSpot.mp4")

agent.print_response("Tell me about this video", videos=[Video(filepath=video_path)])
```

## Usage

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U google-genai agno
    ```
  </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="Download the sample video">
    ```bash theme={null}
    wget https://storage.googleapis.com/generativeai-downloads/images/GreatRedSpot.mp4
    ```
  </Step>

  <Step title="Run Agent">
    ```bash theme={null}
    python video_agent.py
    ```
  </Step>
</Steps>