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

# Llama Image Input Bytes

> Pass a downloaded image as bytes to Llama 4 Maverick and search the web for related news.

```python image_input_bytes.py theme={null}
"""
Meta Image Input Bytes
======================

Cookbook example for `meta/llama/image_input_bytes.py`.
"""

from pathlib import Path

from agno.agent import Agent
from agno.media import Image
from agno.models.meta import LlamaOpenAI
from agno.tools.websearch import WebSearchTools
from agno.utils.media import download_image

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

agent = Agent(
    model=LlamaOpenAI(id="Llama-4-Maverick-17B-128E-Instruct-FP8"),
    tools=[WebSearchTools()],
    markdown=True,
)

image_path = Path(__file__).parent.joinpath("sample.jpg")

download_image(
    url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg",
    output_path=str(image_path),
)

# Read the image file content as bytes
image_bytes = image_path.read_bytes()

agent.print_response(
    "Tell me about this image and give me the latest news about it.",
    images=[
        Image(content=image_bytes),
    ],
    stream=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass
```

## Run the Example

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

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

  <Step title="Export your Meta Llama API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export LLAMA_API_KEY="your_llama_api_key_here"
      ```

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

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

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

Full source: [cookbook/90\_models/meta/llama/image\_input\_bytes.py](https://github.com/agno-agi/agno/blob/main/cookbook/90_models/meta/llama/image_input_bytes.py)