> ## 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.

# Anthropic Image Input Local File

> Download the file using the download_file function.

```python theme={null}
"""
In this example, we upload a PDF file to Anthropic directly and then use it as an input to an agent.
"""

from pathlib import Path

from agno.agent import Agent
from agno.media import Image
from agno.models.anthropic import Claude
from agno.utils.media import download_file
from anthropic import Anthropic

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

img_path = Path(__file__).parent.joinpath("agno-intro.png")

# Download the file using the download_file function
download_file(
    "https://agno-public.s3.us-east-1.amazonaws.com/images/agno-intro.png",
    str(img_path),
)

# Initialize Anthropic client
client = Anthropic()

agent = Agent(
    model=Claude(id="claude-sonnet-4-20250514"),
    markdown=True,
)

agent.print_response(
    "What does the attached image say.",
    images=[Image(filepath=img_path)],
)

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

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

## Run the Example

```bash theme={null}
# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/90_models/anthropic

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python image_input_local_file.py
```