pocketflow/cookbook/pocketflow-tool-pdf-vision/README.md

PocketFlow Tool: PDF Vision

A PocketFlow example project demonstrating PDF processing with OpenAI's Vision API for OCR and text extraction.

Features

• Convert PDF pages to images while maintaining quality and size limits
• Extract text from scanned documents using GPT-4 Vision API
• Support for custom extraction prompts
• Maintain page order and formatting in extracted text
• Batch processing of multiple PDFs from a directory

Installation

1. Clone the repository
2. Install dependencies:

   pip install -r requirements.txt
   

3. Set your OpenAI API key as an environment variable:

   export OPENAI_API_KEY=your_api_key_here
   

Usage

1. Place your PDF files in the pdfs directory
2. Run the example:

   python main.py
   

   The script will process all PDF files in the pdfs directory and output the extracted text for each one.

Project Structure

pocketflow-tool-pdf-vision/
├── pdfs/           # Directory for PDF files to process
├── tools/
│   ├── pdf.py     # PDF to image conversion
│   └── vision.py  # Vision API integration
├── utils/
│   └── call_llm.py # OpenAI client config
├── nodes.py       # PocketFlow nodes
├── flow.py        # Flow configuration
└── main.py        # Example usage

Flow Description

1. LoadPDFNode: Loads PDF and converts pages to images
2. ExtractTextNode: Processes images with Vision API
3. CombineResultsNode: Combines extracted text from all pages

Customization

You can customize the extraction by modifying the prompt in shared:

shared = {
    "pdf_path": "your_file.pdf",
    "extraction_prompt": "Your custom prompt here"
}

Limitations

• Maximum PDF page size: 2000px (configurable in tools/pdf.py)
• Vision API token limit: 1000 tokens per response
• Image size limit: 20MB per image for Vision API

License

MIT