🎧 Podlr - Transform Podcasts & YouTube to eBooks

Convert podcasts and YouTube videos into beautifully formatted eBooks using AI transcription

Perfect for accessibility, learning, and reading on the go. Transform hours of audio content into searchable, portable PDF eBooks with professional formatting.

✨ Features

🧠 AI-Powered Transcription

• OpenAI Whisper integration with multi-language support
• Smart device detection - automatically uses GPU when available
• Quality modes: Fast, Balanced, or Best Quality processing
• Real-time progress tracking with system monitoring

🎯 Multi-Source Support

• RSS Podcast Feeds - Any podcast with RSS feed
• YouTube Videos - Single videos or entire playlists
• YouTube Channels - Convert channel content
• Batch Processing - Process multiple URLs from file

📚 Beautiful eBook Generation

• Professional PDF formatting with covers and chapters
• Automatic metadata extraction (title, author, thumbnails)
• Custom licensing and copyright information
• Chapter organization with proper formatting

🌐 Modern Web Interface

• One-command setup - Just run and go!
• Real-time progress monitoring with live updates
• Responsive design - Works on desktop and mobile
• Drag & drop URL input with auto-detection

♿ Accessibility First

• Perfect for deaf/hard of hearing users
• Reading-preferred content consumption
• Searchable text format for easy navigation
• Screen reader compatible PDF output

🔒 Privacy & Performance

• 100% local processing - No data sent to external servers
• Parallel processing - Multi-threaded for speed
• Smart resume - Continue interrupted conversions
• System optimization - Automatic hardware detection

🚀 Quick Start

Prerequisites

• Python 3.8+ (Download from python.org)
• Node.js (Download from nodejs.org) - Required for YouTube downloads

One-Command Installation & Launch

# 1. Clone the repository
git clone https://github.com/Kehn-Marv/Podlr.git
cd Podlr

# 2. Start the web interface (handles everything automatically!)
cd web-ui
python start_server.py

That's it! 🎉 The web browser will automatically open to http://localhost:5000

The setup script automatically:

• ✅ Creates virtual environment
• ✅ Installs all Python dependencies
• ✅ Downloads and configures FFmpeg
• ✅ Starts the web server
• ✅ Opens your browser

📖 Usage Guide

Web Interface (Recommended)

1. Open your browser to http://localhost:5000
2. Paste your URL - RSS feed or YouTube link
3. Configure options - Quality, language, range
4. Start conversion - Watch real-time progress
5. Download your eBook - Professional PDF ready!

Command Line Interface

# Convert a podcast RSS feed
python podlr.py "https://feeds.example.com/podcast.rss"

# Convert YouTube video/playlist
python podlr.py "https://youtube.com/watch?v=VIDEO_ID"

# Advanced options
python podlr.py "https://podcast.rss" \
  --start 1 --end 5 \
  --preference quality \
  --language auto \
  --workers 4

# Preview content before converting
python podlr.py --info "https://youtube.com/playlist?list=PLAYLIST_ID"

# Check system dependencies
python podlr.py --check

Batch Processing

Create a text file with URLs (one per line):

# batch_urls.txt
https://feeds.example.com/podcast1.rss
https://youtube.com/watch?v=VIDEO1
https://youtube.com/playlist?list=PLAYLIST1

python podlr.py --batch batch_urls.txt

⚙️ Configuration Options

Quality Settings

• Fast ⚡ - Quick processing, basic accuracy
• Balanced ⚖️ - Good speed/quality balance (default)
• Quality 🎯 - Best accuracy, slower processing

Language Modes

• English Optimized 🇺🇸 - Faster for English content
• Multilingual 🌍 - Supports 99+ languages

Advanced Options

• Parallel Workers - Multi-threaded processing (1-8 workers)
• Custom License - Add copyright/license text
• Resume Support - Continue interrupted conversions
• Range Selection - Process specific episodes/videos

🛠️ Technical Details

System Requirements

• Python 3.8+ with pip
• Node.js (for YouTube downloads)
• 2GB+ RAM (4GB+ recommended)
• Internet connection for downloads

Supported Formats

• Input: RSS feeds, YouTube (videos/playlists/channels)
• Output: PDF eBooks with embedded metadata
• Audio: MP3, M4A, WebM (auto-converted)

AI Models

Podlr automatically selects the best Whisper model based on your hardware:

Model	Parameters	Memory	Speed	Quality
tiny	39M	~1GB	10x	Minimal
base	74M	~1GB	7x	Basic
small	244M	~2GB	4x	Decent
medium	769M	~5GB	2x	Good
large	1550M	~10GB	1x	Best

📁 Project Structure

Podlr/
├── 📄 podlr.py              # Main CLI application
├── 📄 requirements.txt      # Python dependencies
├── 📄 install.py           # Complete installation script
├── 📄 setup_ffmpeg.py      # FFmpeg auto-installer
├── 🌐 web-ui/              # Web interface
│   ├── 📄 start_server.py  # One-command launcher
│   ├── 📄 api.py           # Flask backend API
│   ├── 📄 index.html       # Web interface
│   ├── 📄 script.js        # Frontend logic
│   ├── 📄 styles.css       # UI styling
│   └── 🖼️ assets/          # Images and logos
├── 📁 docs/                # Documentation
└── 📁 venv/                # Virtual environment (auto-created)

🔧 Troubleshooting

Common Issues

"No JavaScript runtime found"

# Install Node.js from https://nodejs.org/
# Or use package manager:
# Windows: winget install OpenJS.NodeJS
# macOS: brew install node
# Ubuntu: sudo apt install nodejs npm

"FFmpeg not found"

# Run the FFmpeg installer
python setup_ffmpeg.py

"Permission denied" on Windows

# Run as Administrator for FFmpeg installation
# Right-click Command Prompt → "Run as administrator"

Slow processing

• Use --preference fast for speed
• Reduce --workers if system struggles
• Check available RAM and disk space

Getting Help

1. Check dependencies: python podlr.py --check
2. View logs in the web interface
3. Check issues on GitHub
4. Read documentation in the docs/ folder

🗺️ Roadmap

🔄 Next Update (v1.3.0)

• Better error handling for RAM/PC specs detection
• RSS.com support for podcast hosting platform
• Conversion modal UI processing improvements
• Enhanced PDF formatting with better styling
• About documentation section in web UI
• Demo video integration
• Toast notification improvements
• Legal notice display fixes
• Parallel worker limits based on system specs
• Automatic cleanup of processed folders
• Diarization support for speaker identification
• Separate eBook folders for better organization

🚀 Future Features

• Multiple output formats (EPUB, MOBI)
• Cloud storage integration (Google Drive, Dropbox)
• Advanced PDF styling with themes
• Audio chapter detection and splitting
• Subtitle/caption extraction support
• Mobile app for iOS/Android
• Plugin system for extensibility

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

git clone https://github.com/Kehn-Marv/Podlr.git
cd Podlr
python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows
pip install -r requirements.txt

📄 License

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

🙏 Acknowledgments

• OpenAI Whisper - State-of-the-art speech recognition
• yt-dlp - Robust YouTube downloading
• ReportLab - Professional PDF generation
• Flask - Lightweight web framework
• FFmpeg - Universal media processing

⚖️ Legal Notice

Important: This tool is for personal use and educational purposes. Please ensure you have the right to download and convert content. Respect copyright laws and content creators' rights. YouTube's Terms of Service may prohibit downloading videos.

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Made with ❤️ for accessibility and learning

🌟 Star this repo • 🐛 Report Bug • 💡 Request Feature