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

# Image Bytes Input Agent

> Pass raw image bytes fetched with requests to a Ministral 14B agent for analysis.

## Code

```python image_bytes_input_agent.py theme={null}
import requests
from agno.agent import Agent
from agno.media import Image
from agno.models.mistral.mistral import MistralChat

agent = Agent(
    model=MistralChat(id="ministral-14b-2512"),
    markdown=True,
)

image_url = (
    "https://tripfixers.com/wp-content/uploads/2019/11/eiffel-tower-with-snow.jpeg"
)

def fetch_image_bytes(url: str) -> bytes:
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
        "Accept": "image/avif,image/webp,image/apng,image/svg+xml,image/*,*/*;q=0.8",
        "Accept-Language": "en-US,en;q=0.9",
    }
    response = requests.get(url, headers=headers)
    response.raise_for_status()
    return response.content

image_bytes_from_url = fetch_image_bytes(image_url)

agent.print_response(
    "Tell me about this image.",
    images=[
        Image(content=image_bytes_from_url),
    ],
)

```

## Usage

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

**1. Set your API key**

```bash theme={null}
export MISTRAL_API_KEY=xxx
```

**2. Install dependencies**

```bash theme={null}
uv pip install -U mistralai requests agno
```

**3. Run Agent**

Save the code above as `image_bytes_input_agent.py`, then run:

```bash theme={null}
python image_bytes_input_agent.py
```


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