youtube-summarizer/.taskmaster/docs/prd.txt

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# YouTube Summarizer Web Application - Product Requirements Document
## Product Overview
A web-based application that allows users to input YouTube video URLs and receive AI-generated summaries, key points, and insights. The application will support multiple AI models, provide various export formats, and include caching for efficiency.
## Target Users
- Students and researchers who need to quickly understand video content
- Content creators analyzing competitor videos
- Professionals extracting insights from educational content
- Anyone wanting to save time by getting video summaries
## Core Features
### MVP Features (Phase 1)
1. YouTube URL input and validation
2. Automatic transcript extraction from YouTube videos
3. AI-powered summary generation using at least one model
4. Basic web interface for input and display
5. Summary display with key points
6. Copy-to-clipboard functionality
7. Basic error handling and user feedback
### Enhanced Features (Phase 2)
1. Multiple AI model support (OpenAI, Anthropic, DeepSeek)
2. Model selection by user
3. Summary customization (length, style, focus)
4. Chapter/timestamp generation
5. Export to multiple formats (Markdown, PDF, TXT)
6. Summary history and retrieval
7. Caching system to reduce API calls
8. Rate limiting and quota management
### Advanced Features (Phase 3)
1. Batch processing of multiple videos
2. Playlist summarization
3. Real-time progress updates via WebSocket
4. User authentication and personal libraries
5. Summary sharing and collaboration
6. Advanced search within summaries
7. API endpoints for programmatic access
8. Integration with note-taking apps
## Technical Requirements
### Frontend
- Responsive web interface
- Clean, intuitive design
- Real-time status updates
- Mobile-friendly layout
- Dark/light theme support
### Backend
- FastAPI framework for API development
- Async processing for better performance
- Robust error handling
- Comprehensive logging
- Database for storing summaries
- Queue system for batch processing
### AI Integration
- Support for multiple AI providers
- Fallback mechanisms between models
- Token usage optimization
- Response streaming for long summaries
- Context window management
### YouTube Integration
- YouTube Transcript API integration
- Fallback to YouTube Data API when needed
- Support for multiple video formats
- Auto-language detection
- Subtitle preference handling
### Data Storage
- SQLite for development, PostgreSQL for production
- Efficient caching strategy
- Summary versioning
- User preference storage
- Usage analytics
## Performance Requirements
- Summary generation within 30 seconds for average video
- Support for videos up to 3 hours long
- Handle 100 concurrent users
- 99% uptime availability
- Response time under 2 seconds for cached content
## Security Requirements
- Secure API key management
- Input sanitization
- Rate limiting per IP/user
- CORS configuration
- SQL injection prevention
- XSS protection
## User Experience Requirements
- Clear loading indicators
- Helpful error messages
- Intuitive navigation
- Accessible design (WCAG 2.1)
- Multi-language support (future)
## Success Metrics
- Average summary generation time
- User satisfaction rating
- API usage efficiency
- Cache hit rate
- Error rate below 1%
- User retention rate
## Constraints
- Must work with free tier of AI services initially
- Should minimize API costs through caching
- Must respect YouTube's terms of service
- Should handle rate limits gracefully
## Development Phases
### Phase 1: MVP (Week 1-2)
- Basic functionality
- Single AI model
- Simple web interface
- Core summarization features
### Phase 2: Enhancement (Week 3-4)
- Multiple AI models
- Export features
- Caching system
- Improved UI/UX
### Phase 3: Advanced (Week 5-6)
- User accounts
- Batch processing
- API development
- Advanced features
## Testing Requirements
- Unit tests for all services
- Integration tests for API endpoints
- End-to-end testing for critical flows
- Performance testing
- Security testing
- User acceptance testing
## Documentation Requirements
- API documentation
- User guide
- Developer setup guide
- Deployment instructions
- Troubleshooting guide
## Future Considerations
- Mobile application
- Browser extension
- Podcast support
- Video clip extraction
- AI-powered Q&A on video content
- Integration with learning management systems