T(YTTP)ER - YouTube Transcript Processor

Overview

T(YTTP)ER (pronounced "Typer") is a complete revamp of YTTP-AI, rebuilt from the ground up with PySide6 for a smoother, faster experience. This application maintains all the powerful features of the original while delivering noticeable performance improvements and a more polished interface.

Key enhancements:

• ⚡ Smoother performance with PySide6 interface
• ✍️ Improved typewriter effect for better readability
• 📜 New History feature for tracking processed videos
• 🎨 Refined modern UI with cleaner design
• 🚀 Optimized processing pipeline for faster results

Requirements

Software Requirements

• Python 3.10+
• Ollama installed and running
• Ollama model of your choice (recommended: llama3.2 or deepseek-r1)

Hardware Recommendations

For optimal performance:

• CPU: Intel i5/Ryzen 5 or better
• RAM: 8GB+ (16GB recommended)
• GPU: 4GB+ VRAM
• Storage: SSD with 100MB free space

For llama3.2 model:

• Minimum: 4GB RAM + 2GB VRAM
• Recommended: 8GB RAM + 4GB VRAM

Installation & Setup

1. Install Ollama:

   • Download from https://ollama.com/download
   • Launch and keep running in background

2. Download model:

   ollama pull llama3.2  # Optimal balance of speed/quality

3. Launch T(YTTP)ER:

   python Start_tyttper.py

The application will:

• Auto-install Python dependencies
• Configure optimized defaults
• Prepare processing environment

Key Features

🆕 History System

• Track previously processed videos
• Quick access to past sessions
• Organized workflow management

✨ Enhanced Processing

• Optimized text chunk handling
• Smoother typewriter animation
• Improved memory management

🎛️ Modern Interface

• Professional PySide6 framework
• Responsive and polished UI
• Intuitive navigation

Quick Start Guide

1. Launch the application:

   python Start_tyttper.py

2. Process videos:

   1. Enter YouTube URL in Start screen
   2. Monitor real-time AI processing
   3. Access history via new menu

3. Workflow:

   • Simplified interface
   • Focused functionality

Performance Tips

Recommended Configurations

Hardware Profile	Model	Chunk Size	Overlap
Basic (4GB RAM)	llama3.2	250 words	30
Balanced (8GB RAM)	deepseek-r1	400 words	50
Advanced (16GB+ RAM)	llama3	700 words	75

Optimization Tips

• Use smaller models for faster processing
• Adjust chunk size based on RAM
• Close other applications during processing

Troubleshooting

Common Solutions

1. Transcript issues:

   • Verify video has captions
   • Try different video URL format

2. Performance tuning:

   • Reduce chunk size
   • Use llama3.2 model
   • Restart application periodically

3. Ollama connection:

   • Ensure Ollama is running
   • Check ollama serve status

Temporary Files

The application automatically clears temporary files. Manual cleanup:

rm -rf temp/

Or simply delete the folder

Why Choose T(YTTP)ER?

Improvements Over Previous Version

• Modern interface: PySide6 vs Tkinter
• History feature: Track processed videos
• Performance: Optimized processing pipeline
• Typewriter effect: Smoother text display

Contribution

We welcome contributions:

• Bug reports
• UI improvements
• Documentation updates
• Performance optimizations

License

MIT License - see LICENSE for details.

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Note: This application uses YouTube's public API. Please respect content creators' rights and adhere to YouTube's Terms of Service.