> ## 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.

# Image Agent

> Stream an LMStudio vision agent's response describing an image fetched over HTTP with httpx.

## Code

```python image_agent.py theme={null}
import httpx

from agno.agent import Agent
from agno.media import Image
from agno.models.lmstudio import LMStudio

agent = Agent(
    model=LMStudio(id="llama3.2-vision"),
    markdown=True,
)

response = httpx.get(
    "https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg"
)

agent.print_response(
    "Tell me about this image",
    images=[Image(content=response.content)],
    stream=True,
)
```

## Usage

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

  <Step title="Install LM Studio">
    Install LM Studio from [here](https://lmstudio.ai/download) and download the
    model you want to use.
  </Step>

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

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

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