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.
# Basic installation
pip install pdf2epub
# Full installation with all features
pip install pdf2epub[full]
# Convert a PDF to EPUB
pdf2epub document.pdf
# Advanced options
pdf2epub book.pdf --start-page 10 --max-pages 50 --langs "English,German"
pip3 uninstall torch torchvision torchaudio
pip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
pip3 uninstall torch torchvision torchaudio
pip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
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")
pip install pdf2epub
Includes core functionality with minimal dependencies.
pip install pdf2epub[full]
Includes all features: PDF processing, AI postprocessing, and GPU acceleration.
pip install pdf2epub[dev]
Includes development tools: testing, linting, and formatting.
NVIDIA CUDA:
pip install pdf2epub[full]
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
AMD ROCm:
pip install pdf2epub[full]
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2
# 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
import pdf2epub
# Configure default settings
pdf2epub.config.set_default_batch_multiplier(3)
pdf2epub.config.set_default_ai_provider("anthropic")
Run the test suite:
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)
Create custom AI postprocessing providers:
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")
| 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
| Feature | PDF2EPUB | calibre | pandoc |
|---|---|---|---|
| AI Enhancement | ✅ | ❌ | ❌ |
| Layout Detection | ✅ | ⚠️ | ⚠️ |
| GPU Acceleration | ✅ | ❌ | ❌ |
| Python API | ✅ | ⚠️ | ⚠️ |
| Plugin System | ✅ | ✅ | ❌ |
| CLI Interface | ✅ | ✅ | ✅ |
FROM python:3.11-slim
RUN pip install pdf2epub[full]
WORKDIR /workspace
ENTRYPOINT ["pdf2epub"]
- name: Convert PDFs
run: |
pip install pdf2epub[full]
pdf2epub documents/*.pdf
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)
}
We welcome contributions! Please see our Contributing Guide for details.
git checkout -b feature-namepytestblack .See CONTRIBUTING.md for detailed guidelines.
This project is licensed under the MIT License - see the LICENSE file for details.
This project builds upon excellent open-source libraries:
Transform your PDFs into beautiful, accessible EPUBs with AI-powered enhancement! 🚀📚
FAQs
Convert PDF files to EPUB format via Markdown with intelligent layout detection
We found that pdf2epub demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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