# PDF2EPUB 📚
[](https://badge.fury.io/py/pdf2epub)
[](https://github.com/porfanid/pdf2epub/actions/workflows/ci.yml)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
A powerful Python package for converting PDF files to EPUB format via Markdown with intelligent layout detection, AI-powered postprocessing, and seamless CLI/API integration.
## ✨ Features
- 📖 **Smart Layout Detection** - Handles books, academic papers, and complex documents
- 🔍 **Advanced PDF Processing** - OCR, table detection, and image extraction
- 🤖 **AI Postprocessing** - Enhance quality with Anthropic Claude integration
- 📝 **Clean Markdown Output** - Structured, readable markdown with preserved formatting
- 📱 **Professional EPUB** - High-quality EPUB 3.0 output with customizable styling
- 🌍 **Multi-language Support** - Process documents in multiple languages
- 🚀 **GPU Acceleration** - NVIDIA CUDA and AMD ROCm support for faster processing
- 🍎 **Apple Silicon Support** - Optimized performance on Apple Silicon devices
- 🛠️ **Flexible API** - Use as CLI tool or import as Python library
- 🔌 **Plugin Architecture** - Extensible AI provider system
## 🚀 Quick Start
### Installation
```bash
# Basic installation
pip install pdf2epub
# Full installation with all features
pip install pdf2epub[full]
```
### Command Line Usage
```bash
# Convert a PDF to EPUB
pdf2epub document.pdf
# Advanced options
pdf2epub book.pdf --start-page 10 --max-pages 50 --langs "English,German"
```
### Python API
- For Apple Silicon, install with MPS support:
```bash
pip3 uninstall torch torchvision torchaudio
pip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
```
- For Apple Silicon, install with MPS support:
```bash
pip3 uninstall torch torchvision torchaudio
pip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
```
3. Verify GPU support:
```python
import torch
print(torch.__version__) # PyTorch version
print(torch.cuda.is_available()) # Should return True for NVIDIA
print(torch.mps.is_available()) # Should return True for Apple Silicon
print(torch.version.hip) # Should print ROCm version for AMD
import pdf2epub
# Simple conversion
pdf2epub.convert_pdf_to_markdown("document.pdf", "output/")
pdf2epub.convert_markdown_to_epub("output/", "final/")
# Advanced usage with AI enhancement
processor = pdf2epub.AIPostprocessor("output/")
processor.run_postprocessing("document.md", "anthropic")
```
## 📦 Installation Options
### Basic Installation
```bash
pip install pdf2epub
```
Includes core functionality with minimal dependencies.
### Full Installation
```bash
pip install pdf2epub[full]
```
Includes all features: PDF processing, AI postprocessing, and GPU acceleration.
### Development Installation
```bash
pip install pdf2epub[dev]
```
Includes development tools: testing, linting, and formatting.
### GPU Support
**NVIDIA CUDA:**
```bash
pip install pdf2epub[full]
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
```
**AMD ROCm:**
```bash
pip install pdf2epub[full]
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2
```
## 📚 Documentation
- **[Quick Tutorial](docs/tutorial.md)** - Convert your first PDF in 5 minutes
- **[Installation Guide](docs/installation.md)** - Detailed setup instructions
- **[CLI Reference](docs/cli.md)** - Complete command-line documentation
- **[Python API](docs/api.md)** - Library usage and examples
- **[Advanced Features](docs/guides/advanced-features.md)** - GPU acceleration, batch processing
- **[AI Integration](docs/ai/overview.md)** - Enhance quality with AI postprocessing
- **[Plugin Development](docs/developers/plugins.md)** - Create custom AI providers
## 🎯 Use Cases
### Academic Research
- Convert research papers to readable EPUB format
- Extract and preserve mathematical equations
- Maintain citation formatting and structure
### Digital Publishing
- Transform print-ready PDFs into distribution-ready EPUBs
- Preserve complex layouts and formatting
- Optimize for e-reader compatibility
### Document Archival
- Convert legacy documents to modern formats
- Batch process document collections
- Enhance readability with AI postprocessing
### Accessibility
- Create screen-reader compatible versions
- Improve text structure and navigation
- Add semantic markup for better accessibility
## 🔧 Configuration
### Environment Variables
```bash
# Required for AI postprocessing
export ANTHROPIC_API_KEY="your-anthropic-api-key"
# Optional: Control GPU usage
export CUDA_VISIBLE_DEVICES="0" # Use specific GPU
export CUDA_VISIBLE_DEVICES="" # Force CPU-only mode
```
### API Configuration
```python
import pdf2epub
# Configure default settings
pdf2epub.config.set_default_batch_multiplier(3)
pdf2epub.config.set_default_ai_provider("anthropic")
```
## 🧪 Testing
Run the test suite:
```bash
pytest # Run all tests
pytest --cov=pdf2epub # Run with coverage
pytest tests/test_pdf2md.py # Run specific test file
```
Current test coverage: **49%** with **100% pass rate** (41/41 tests)
## 🔌 Plugin System
Create custom AI postprocessing providers:
```python
from pdf2epub.postprocessing.ai import AIPostprocessor
class CustomAIProvider:
@staticmethod
def getjsonparams(system_prompt: str, request: str) -> str:
# Implement your AI API integration
return process_with_custom_ai(system_prompt, request)
# Register and use your provider
processor = AIPostprocessor(work_dir)
processor.register_provider("custom", CustomAIProvider)
processor.run_postprocessing(markdown_file, "custom")
```
## 📊 Performance
### Benchmarks
| Document Type | Pages | Processing Time | Memory Usage |
|---------------|-------|----------------|--------------|
| Research Paper | 20 | 45 seconds | 2.1 GB |
| Technical Book | 200 | 6 minutes | 4.8 GB |
| Magazine | 50 | 2 minutes | 1.9 GB |
*Results on NVIDIA RTX 3080 with 16GB RAM*
### Optimization Tips
- **Use GPU acceleration** for 3-5x speed improvement
- **Adjust batch multiplier** based on available memory
- **Process in chunks** for very large documents
- **Enable AI postprocessing** for best quality (slower)
## 🆚 Comparison
| Feature | PDF2EPUB | calibre | pandoc |
|---------|----------|---------|--------|
| AI Enhancement | ✅ | ❌ | ❌ |
| Layout Detection | ✅ | ⚠️ | ⚠️ |
| GPU Acceleration | ✅ | ❌ | ❌ |
| Python API | ✅ | ⚠️ | ⚠️ |
| Plugin System | ✅ | ✅ | ❌ |
| CLI Interface | ✅ | ✅ | ✅ |
## 🚢 Deployment
### Docker
```dockerfile
FROM python:3.11-slim
RUN pip install pdf2epub[full]
WORKDIR /workspace
ENTRYPOINT ["pdf2epub"]
```
### GitHub Actions
```yaml
- name: Convert PDFs
run: |
pip install pdf2epub[full]
pdf2epub documents/*.pdf
```
### Production Deployment
```python
import pdf2epub
from pathlib import Path
def production_converter(pdf_path: str) -> dict:
"""Production-ready PDF conversion with error handling."""
try:
output_dir = pdf2epub.convert_pdf_to_markdown(
pdf_path,
batch_multiplier=2, # Conservative memory usage
max_pages=1000 # Prevent runaway processing
)
epub_path = pdf2epub.convert_to_epub(output_dir)
return {
"status": "success",
"markdown_path": output_dir,
"epub_path": epub_path,
"processing_time": time.time() - start_time
}
except Exception as e:
return {
"status": "error",
"error": str(e)
}
```
## 🤝 Contributing
We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
### Quick Contributing Steps
1. **Fork** the repository
2. **Create** a feature branch: `git checkout -b feature-name`
3. **Make** your changes and add tests
4. **Test** your changes: `pytest`
5. **Format** code: `black .`
6. **Submit** a pull request
See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed guidelines.
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
This project builds upon excellent open-source libraries:
- **[marker-pdf](https://github.com/VikParuchuri/marker)** - PDF processing engine
- **[mark2epub](https://github.com/AlexPof/mark2epub)** - Markdown to EPUB conversion
- **[PyTorch](https://pytorch.org/)** - GPU acceleration framework
- **[Transformers](https://huggingface.co/transformers)** - AI/ML text processing
- **[Anthropic](https://www.anthropic.com/)** - AI API for text enhancement
## 📈 Project Status
- **Version**: 0.1.0 (Beta)
- **Status**: Active development
- **Python**: 3.9+ supported
- **Testing**: 49% coverage, 100% pass rate
- **CI/CD**: GitHub Actions
- **Documentation**: Comprehensive
## 🔗 Links
- **[PyPI Package](https://pypi.org/project/pdf2epub/)**
- **[GitHub Repository](https://github.com/porfanid/pdf2epub)**
- **[Documentation](docs/README.md)**
- **[Issue Tracker](https://github.com/porfanid/pdf2epub/issues)**
- **[Discussions](https://github.com/porfanid/pdf2epub/discussions)**
- **[Security Policy](SECURITY.md)**
## 📞 Support
- **GitHub Issues**: [Report bugs or request features](https://github.com/porfanid/pdf2epub/issues)
- **GitHub Discussions**: [Ask questions and get help](https://github.com/porfanid/pdf2epub/discussions)
- **Documentation**: [Browse the docs](docs/README.md)
---
**Transform your PDFs into beautiful, accessible EPUBs with AI-powered enhancement!** 🚀📚
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"description": "# PDF2EPUB \ud83d\udcda\n\n[](https://badge.fury.io/py/pdf2epub)\n[](https://github.com/porfanid/pdf2epub/actions/workflows/ci.yml)\n[](https://www.python.org/downloads/)\n[](https://opensource.org/licenses/MIT)\n\nA powerful Python package for converting PDF files to EPUB format via Markdown with intelligent layout detection, AI-powered postprocessing, and seamless CLI/API integration.\n\n## \u2728 Features\n\n- \ud83d\udcd6 **Smart Layout Detection** - Handles books, academic papers, and complex documents\n- \ud83d\udd0d **Advanced PDF Processing** - OCR, table detection, and image extraction\n- \ud83e\udd16 **AI Postprocessing** - Enhance quality with Anthropic Claude integration\n- \ud83d\udcdd **Clean Markdown Output** - Structured, readable markdown with preserved formatting\n- \ud83d\udcf1 **Professional EPUB** - High-quality EPUB 3.0 output with customizable styling\n- \ud83c\udf0d **Multi-language Support** - Process documents in multiple languages\n- \ud83d\ude80 **GPU Acceleration** - NVIDIA CUDA and AMD ROCm support for faster processing\n- \ud83c\udf4e **Apple Silicon Support** - Optimized performance on Apple Silicon devices\n- \ud83d\udee0\ufe0f **Flexible API** - Use as CLI tool or import as Python library\n- \ud83d\udd0c **Plugin Architecture** - Extensible AI provider system\n\n## \ud83d\ude80 Quick Start\n\n### Installation\n\n```bash\n# Basic installation\npip install pdf2epub\n\n# Full installation with all features\npip install pdf2epub[full]\n```\n\n### Command Line Usage\n\n```bash\n# Convert a PDF to EPUB\npdf2epub document.pdf\n\n# Advanced options\npdf2epub book.pdf --start-page 10 --max-pages 50 --langs \"English,German\"\n```\n\n### Python API\n\n- For Apple Silicon, install with MPS support:\n```bash\npip3 uninstall torch torchvision torchaudio\npip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu\n```\n\n- For Apple Silicon, install with MPS support:\n```bash\npip3 uninstall torch torchvision torchaudio\npip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu\n```\n\n3. Verify GPU support:\n```python\nimport torch\nprint(torch.__version__) # PyTorch version\nprint(torch.cuda.is_available()) # Should return True for NVIDIA\nprint(torch.mps.is_available()) # Should return True for Apple Silicon\nprint(torch.version.hip) # Should print ROCm version for AMD\n\nimport pdf2epub\n\n# Simple conversion\npdf2epub.convert_pdf_to_markdown(\"document.pdf\", \"output/\")\npdf2epub.convert_markdown_to_epub(\"output/\", \"final/\")\n\n# Advanced usage with AI enhancement\nprocessor = pdf2epub.AIPostprocessor(\"output/\")\nprocessor.run_postprocessing(\"document.md\", \"anthropic\")\n```\n\n## \ud83d\udce6 Installation Options\n\n### Basic Installation\n```bash\npip install pdf2epub\n```\nIncludes core functionality with minimal dependencies.\n\n### Full Installation\n```bash\npip install pdf2epub[full]\n```\nIncludes all features: PDF processing, AI postprocessing, and GPU acceleration.\n\n### Development Installation\n```bash\npip install pdf2epub[dev]\n```\nIncludes development tools: testing, linting, and formatting.\n\n### GPU Support\n\n**NVIDIA CUDA:**\n```bash\npip install pdf2epub[full]\npip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121\n```\n\n**AMD ROCm:**\n```bash\npip install pdf2epub[full]\npip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2\n```\n\n## \ud83d\udcda Documentation\n\n- **[Quick Tutorial](docs/tutorial.md)** - Convert your first PDF in 5 minutes\n- **[Installation Guide](docs/installation.md)** - Detailed setup instructions\n- **[CLI Reference](docs/cli.md)** - Complete command-line documentation\n- **[Python API](docs/api.md)** - Library usage and examples\n- **[Advanced Features](docs/guides/advanced-features.md)** - GPU acceleration, batch processing\n- **[AI Integration](docs/ai/overview.md)** - Enhance quality with AI postprocessing\n- **[Plugin Development](docs/developers/plugins.md)** - Create custom AI providers\n\n## \ud83c\udfaf Use Cases\n\n### Academic Research\n- Convert research papers to readable EPUB format\n- Extract and preserve mathematical equations\n- Maintain citation formatting and structure\n\n### Digital Publishing\n- Transform print-ready PDFs into distribution-ready EPUBs\n- Preserve complex layouts and formatting\n- Optimize for e-reader compatibility\n\n### Document Archival\n- Convert legacy documents to modern formats\n- Batch process document collections\n- Enhance readability with AI postprocessing\n\n### Accessibility\n- Create screen-reader compatible versions\n- Improve text structure and navigation\n- Add semantic markup for better accessibility\n\n## \ud83d\udd27 Configuration\n\n### Environment Variables\n\n```bash\n# Required for AI postprocessing\nexport ANTHROPIC_API_KEY=\"your-anthropic-api-key\"\n\n# Optional: Control GPU usage\nexport CUDA_VISIBLE_DEVICES=\"0\" # Use specific GPU\nexport CUDA_VISIBLE_DEVICES=\"\" # Force CPU-only mode\n```\n\n### API Configuration\n\n```python\nimport pdf2epub\n\n# Configure default settings\npdf2epub.config.set_default_batch_multiplier(3)\npdf2epub.config.set_default_ai_provider(\"anthropic\")\n```\n\n## \ud83e\uddea Testing\n\nRun the test suite:\n```bash\npytest # Run all tests\npytest --cov=pdf2epub # Run with coverage\npytest tests/test_pdf2md.py # Run specific test file\n```\n\nCurrent test coverage: **49%** with **100% pass rate** (41/41 tests)\n\n## \ud83d\udd0c Plugin System\n\nCreate custom AI postprocessing providers:\n\n```python\nfrom pdf2epub.postprocessing.ai import AIPostprocessor\n\nclass CustomAIProvider:\n @staticmethod\n def getjsonparams(system_prompt: str, request: str) -> str:\n # Implement your AI API integration\n return process_with_custom_ai(system_prompt, request)\n\n# Register and use your provider\nprocessor = AIPostprocessor(work_dir)\nprocessor.register_provider(\"custom\", CustomAIProvider)\nprocessor.run_postprocessing(markdown_file, \"custom\")\n```\n\n## \ud83d\udcca Performance\n\n### Benchmarks\n\n| Document Type | Pages | Processing Time | Memory Usage |\n|---------------|-------|----------------|--------------|\n| Research Paper | 20 | 45 seconds | 2.1 GB |\n| Technical Book | 200 | 6 minutes | 4.8 GB |\n| Magazine | 50 | 2 minutes | 1.9 GB |\n\n*Results on NVIDIA RTX 3080 with 16GB RAM*\n\n### Optimization Tips\n\n- **Use GPU acceleration** for 3-5x speed improvement\n- **Adjust batch multiplier** based on available memory\n- **Process in chunks** for very large documents\n- **Enable AI postprocessing** for best quality (slower)\n\n## \ud83c\udd9a Comparison\n\n| Feature | PDF2EPUB | calibre | pandoc |\n|---------|----------|---------|--------|\n| AI Enhancement | \u2705 | \u274c | \u274c |\n| Layout Detection | \u2705 | \u26a0\ufe0f | \u26a0\ufe0f |\n| GPU Acceleration | \u2705 | \u274c | \u274c |\n| Python API | \u2705 | \u26a0\ufe0f | \u26a0\ufe0f |\n| Plugin System | \u2705 | \u2705 | \u274c |\n| CLI Interface | \u2705 | \u2705 | \u2705 |\n\n## \ud83d\udea2 Deployment\n\n### Docker\n\n```dockerfile\nFROM python:3.11-slim\n\nRUN pip install pdf2epub[full]\n\nWORKDIR /workspace\nENTRYPOINT [\"pdf2epub\"]\n```\n\n### GitHub Actions\n\n```yaml\n- name: Convert PDFs\n run: |\n pip install pdf2epub[full]\n pdf2epub documents/*.pdf\n```\n\n### Production Deployment\n\n```python\nimport pdf2epub\nfrom pathlib import Path\n\ndef production_converter(pdf_path: str) -> dict:\n \"\"\"Production-ready PDF conversion with error handling.\"\"\"\n try:\n output_dir = pdf2epub.convert_pdf_to_markdown(\n pdf_path, \n batch_multiplier=2, # Conservative memory usage\n max_pages=1000 # Prevent runaway processing\n )\n \n epub_path = pdf2epub.convert_to_epub(output_dir)\n \n return {\n \"status\": \"success\",\n \"markdown_path\": output_dir,\n \"epub_path\": epub_path,\n \"processing_time\": time.time() - start_time\n }\n \n except Exception as e:\n return {\n \"status\": \"error\", \n \"error\": str(e)\n }\n```\n\n## \ud83e\udd1d Contributing\n\nWe welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.\n\n### Quick Contributing Steps\n\n1. **Fork** the repository\n2. **Create** a feature branch: `git checkout -b feature-name`\n3. **Make** your changes and add tests\n4. **Test** your changes: `pytest`\n5. **Format** code: `black .`\n6. **Submit** a pull request\n\nSee [CONTRIBUTING.md](CONTRIBUTING.md) for detailed guidelines.\n\n## \ud83d\udcc4 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## \ud83d\ude4f Acknowledgments\n\nThis project builds upon excellent open-source libraries:\n\n- **[marker-pdf](https://github.com/VikParuchuri/marker)** - PDF processing engine\n- **[mark2epub](https://github.com/AlexPof/mark2epub)** - Markdown to EPUB conversion \n- **[PyTorch](https://pytorch.org/)** - GPU acceleration framework\n- **[Transformers](https://huggingface.co/transformers)** - AI/ML text processing\n- **[Anthropic](https://www.anthropic.com/)** - AI API for text enhancement\n\n## \ud83d\udcc8 Project Status\n\n- **Version**: 0.1.0 (Beta)\n- **Status**: Active development\n- **Python**: 3.9+ supported\n- **Testing**: 49% coverage, 100% pass rate\n- **CI/CD**: GitHub Actions\n- **Documentation**: Comprehensive\n\n## \ud83d\udd17 Links\n\n- **[PyPI Package](https://pypi.org/project/pdf2epub/)**\n- **[GitHub Repository](https://github.com/porfanid/pdf2epub)**\n- **[Documentation](docs/README.md)**\n- **[Issue Tracker](https://github.com/porfanid/pdf2epub/issues)**\n- **[Discussions](https://github.com/porfanid/pdf2epub/discussions)**\n- **[Security Policy](SECURITY.md)**\n\n## \ud83d\udcde Support\n\n- **GitHub Issues**: [Report bugs or request features](https://github.com/porfanid/pdf2epub/issues)\n- **GitHub Discussions**: [Ask questions and get help](https://github.com/porfanid/pdf2epub/discussions)\n- **Documentation**: [Browse the docs](docs/README.md)\n\n---\n\n**Transform your PDFs into beautiful, accessible EPUBs with AI-powered enhancement!** \ud83d\ude80\ud83d\udcda\n",
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