vexy-pdf-werk 1.1.4

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Vexy PDF Werk

Transform PDFs into high-quality, accessible formats with AI-enhanced processing

Vexy PDF Werk (VPW) is a Python package that converts PDF documents into multiple high-quality formats using modern tools and optional AI enhancement. Transform your PDFs into PDF/A archives, paginated Markdown, ePub books, and structured bibliographic metadata.

• SPEC.md is the full specification

Features

🔧 Modern PDF Processing

• PDF/A conversion for long-term archival
• OCR enhancement using OCRmyPDF
• Quality optimization with qpdf
• In-depth PDF analysis to detect text, images, and scanned documents.

📚 Multiple Output Formats

• Paginated Markdown documents with smart naming and YAML frontmatter.
• ePub generation from Markdown content.
• Structured bibliographic YAML metadata, including estimated word count and content preview.
• Preserves original PDF alongside enhanced versions.

🤖 Optional AI Enhancement (Future)

• Text correction using Claude or Gemini CLI.
• Content structure optimization.
• Fallback to proven traditional methods.

⚙️ Flexible Architecture

• Multiple conversion backends (Marker, MarkItDown, Docling, basic).
• Platform-appropriate configuration storage (~/.config/vexy-pdf-werk/config.toml).
• Robust error handling with graceful fallbacks.
• Command-line interface for easy integration into workflows.

Quick Start

Installation

# Install from PyPI
pip install vexy-pdf-werk

# Or install in development mode
git clone https://github.com/vexyart/vexy-pdf-werk
cd vexy-pdf-werk
pip install -e .

CLI Usage

The primary way to use Vexy PDF Werk is through its command-line interface, vpw.

Process a PDF

# Process a PDF into all default formats (pdfa, markdown, epub, yaml)
vpw process document.pdf

# Specify output directory and formats
vpw process document.pdf --output_dir ./my-output --formats "markdown,epub"

# Enable verbose logging for debugging
vpw process document.pdf --verbose

Manage Configuration

# Display the current configuration
vpw config --show

# Create a default configuration file if one doesn't exist
vpw config --init

Output Structure

VPW creates organized output with consistent naming:

output/
├── document_enhanced.pdf    # PDF/A version
├── 000--introduction.md     # Paginated Markdown files
├── 001--chapter-one.md
├── 002--conclusions.md
├── document.epub            # Generated ePub
└── metadata.yaml            # Bibliographic data

System Requirements

Required Dependencies

• Python 3.10+
• tesseract-ocr
• qpdf
• ghostscript

Optional Dependencies

• pandoc (for ePub generation)
• marker-pdf (advanced PDF conversion)
• markitdown (Microsoft's document converter)
• docling (IBM's document understanding)

Installation Commands

Ubuntu/Debian:

sudo apt-get update
sudo apt-get install tesseract-ocr tesseract-ocr-eng qpdf ghostscript pandoc

macOS:

brew install tesseract tesseract-lang qpdf ghostscript pandoc

Windows:

choco install tesseract qpdf ghostscript pandoc

Configuration

VPW stores configuration in platform-appropriate directories:

• Linux/macOS: ~/.config/vexy-pdf-werk/config.toml
• Windows: %APPDATA%\vexy-pdf-werk\config.toml

You can initialize a default configuration file by running vpw config --init.

Example Configuration

[processing]
ocr_language = "eng"
pdf_quality = "high" # high, medium, low
force_ocr = false
deskew = true
rotate_pages = true

[conversion]
markdown_backend = "auto"  # auto, marker, markitdown, docling, basic
paginate_markdown = true
include_images = true
extract_tables = true

[ai]
enabled = false
provider = "claude"  # claude, gemini, custom
correction_enabled = false
enhancement_enabled = false
max_tokens = 4000

[output]
formats = ["pdfa", "markdown", "epub", "yaml"]
preserve_original = true
output_directory = "./output"
filename_template = "{stem}_{format}.{ext}"

Architecture

VPW follows a modular pipeline architecture:

PDF Input → Analysis → OCR Enhancement → Content Extraction → Format Generation → Multi-Format Output
                          ↓
                   Optional AI Enhancement

Core Components

• PDFProcessor: Handles OCR, PDF/A conversion, and analysis of the PDF file. It uses ocrmypdf and qpdf for robust processing.
• MarkdownGenerator: Converts the processed PDF into Markdown. It supports different backends (currently basic is implemented) and can create paginated or single-file output.
• EpubCreator: Generates an ePub file from the Markdown content, creating chapters for each page.
• MetadataExtractor: Extracts comprehensive metadata from the PDF and the processing results, saving it to a metadata.yaml file. This includes file info, PDF properties, and content summaries like word count.
• cli.py: Provides the command-line interface using fire, allowing for easy configuration and execution of the processing pipeline.
• config.py: Manages the application's configuration using pydantic and toml, with support for environment variable overrides.

Development

This project uses modern Python tooling:

• Package Management: uv + hatch (use uv run to run but for other operations use hatch like hatch test)
• Code Quality: ruff + mypy
• Testing: pytest
• Version Control: git-tag-based semver with hatch-vcs

Development Setup

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone and setup
git clone https://github.com/vexyart/vexy-pdf-werk
cd vexy-pdf-werk
uv venv --python 3.12
uv sync --all-extras

# Run tests
hatch run test

# Run linting
hatch run lint:fmt

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes following the code quality standards
4. Run tests and linting
5. Commit your changes (git commit -m 'Add amazing feature')
6. Push to the branch (git push origin feature/amazing-feature)
7. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Authors

• Fontlab Ltd - Initial work - Vexy Art

Acknowledgments

• Built on proven tools: qpdf, OCRmyPDF, tesseract
• Integration with cutting-edge AI services
• Inspired by the need for better PDF accessibility and archival

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Project Status: Under active development

For detailed implementation specifications, see the spec/ directory.