> ## 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 Input Bytes Content

> Send image bytes read from disk to a Together vision model.

## Code

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

from agno.agent import Agent
from agno.media import Image
from agno.models.together import Together

agent = Agent(
    model=Together(id=os.environ["TOGETHER_MODEL_ID"]),
    markdown=True,
)

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

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

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

Set `TOGETHER_MODEL_ID` to a current model that accepts image input. See the [Together vision guide](https://docs.together.ai/docs/inference/vision/overview) and [serverless catalog](https://docs.together.ai/docs/serverless/models).

## Usage

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

**1. Set your API key**

```bash theme={null}
export TOGETHER_API_KEY=xxx
export TOGETHER_MODEL_ID=your-model-id
```

**2. Install dependencies**

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

**3. Add sample image**

Place a sample image named `sample.jpg` in the same directory as the script.

**4. Run Agent**

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

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


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.