> ## 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.

# Agent with Image Input

> Send image input to an AwsBedrock agent with amazon.nova-pro-v1:0.

AWS Bedrock supports image input with models like `amazon.nova-pro-v1:0`. You can use this to analyze images and get information about them.

## Code

```python image_agent.py theme={null}
from pathlib import Path
from agno.agent import Agent
from agno.media import Image
from agno.models.aws import AwsBedrock
from agno.tools.websearch import WebSearchTools

agent = Agent(
    model=AwsBedrock(id="amazon.nova-pro-v1:0"),
    tools=[WebSearchTools()],
    markdown=True,
)

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

# Read the image file content as bytes
with open(image_path, "rb") as img_file:
    image_bytes = img_file.read()

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

## Usage

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

**1. Set your AWS Credentials**

```bash theme={null}
export AWS_ACCESS_KEY_ID=***
export AWS_SECRET_ACCESS_KEY=***
export AWS_REGION=***
```

**2. Install dependencies**

```bash theme={null}
uv pip install -U boto3 ddgs agno
```

**3. Add an Image**

Place an image file named `sample.jpg` in the same directory as your script.

**4. Run Agent**

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


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