> ## 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.

# PDF Input Local

> Summarize a local PDF and ask follow-up questions with the file_search tool through the OpenAI Responses API.

## Code

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

from agno.agent import Agent
from agno.media import File
from agno.models.openai.responses import OpenAIResponses
from agno.utils.media import download_file

pdf_path = Path(__file__).parent.joinpath("ThaiRecipes.pdf")

# Download the file using the download_file function
download_file(
    "https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf", str(pdf_path)
)

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[{"type": "file_search"}],
    markdown=True,
    add_history_to_context=True,
)

agent.print_response(
    "Summarize the contents of the attached file.",
    files=[File(filepath=pdf_path)],
)
agent.print_response("Suggest me a recipe from the attached file.")

```

## Usage

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

**1. Set your API key**

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

**2. Install dependencies**

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

**3. Run Agent**

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

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


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