Spaced Repetition Study Tool

A modern flashcard application using spaced repetition algorithms (SM-2 and SM-15) to optimize learning and retention.

Overview

This application helps users learn and retain information efficiently through scientifically-proven spaced repetition techniques. Users can create decks of flashcards, import content from files, use AI to generate cards, and review them at optimal intervals.

Tech Stack

Backend

• NestJS with TypeScript
• PostgreSQL database with Prisma ORM
• JWT authentication
• Docker for containerization
• OpenRouter API for AI integration

Frontend

• Next.js with TypeScript (static export)
• React Context for state management
• fetch for API communication
• Tailwind CSS with shadcn for styling

Core Features

1. Authentication System

• User registration and login
• JWT-based authentication with refresh tokens
• Password reset functionality
• Protected routes and auth guards

2. Deck Management

• Create, edit, and delete decks
• Public/private deck settings
• Community deck sharing
• Deck statistics and analytics

3. Card Management

• Create flashcards with front/back content
• Bulk operations (create, edit, delete) (when ai is implemented)
• Card ordering and organization
• Card preview functionality

4. File Processing

• Upload PDF and text files
• Automatic content extraction
• Convert file content to flashcards
• Support for multiple file formats

5. AI Integration

• Generate cards from text prompts
• Bulk card generation from files
• OpenRouter API integration
• Usage tracking and cost estimation

6. Review System

• SM-2 Algorithm: Basic spaced repetition
• SM-15 Algorithm: Advanced algorithm with OF Matrix
• Card scheduling based on performance
• Review queue generation
• Progress tracking and statistics

7. Advanced Features

• Keyboard shortcuts for reviews
• Dark mode support
• Mobile responsive design
• Performance analytics dashboard

Spaced Repetition Algorithms

SM-2 (Default)

• Simple algorithm with 6 grade levels
• Easiness factor adjustments
• Interval multiplier based on performance

SM-15 (Advanced)

• Optimum Factor (OF) Matrix
• Memory stability calculations
• A-Factor for difficulty assessment
• Forgetting curves visualization

Development Phases

1. Phase 1: Project setup, database configuration, authentication system
2. Phase 2: Core backend infrastructure and user management
3. Phase 3: Deck and card CRUD operations
4. Phase 4: File processing and content extraction
5. Phase 5: AI integration for card generation
6. Phase 6: Review system with SM-2 algorithm
7. Phase 7: Advanced SM-15 algorithm implementation
8. Phase 8: Testing, UI polish, and documentation
9. Phase 9: Deployment and production setup

Getting Started

Prerequisites

• Node.js (v18+)
• PostgreSQL
• Docker & Docker Compose
• OpenRouter API key (for AI features)

Installation

# Clone the repository
git clone [repository-url]

# Install backend dependencies
cd backend
npm install

# Install frontend dependencies
cd ../frontend
npm install

# Setup environment variables
cp .env.example .env
# Edit .env with your configuration

# Run database migrations
cd backend
npx prisma migrate dev

# Start development servers
# Backend
npm run start:dev

# Frontend (new terminal)
cd frontend
npm run dev

Environment Variables

Backend (.env)

DATABASE_URL=postgresql://user:password@localhost:5432/study_tool
JWT_SECRET=your_jwt_secret
JWT_REFRESH_SECRET=your_refresh_secret
OPENROUTER_API_KEY=your_api_key

Frontend (.env.local)

NEXT_PUBLIC_API_URL=http://localhost:3000

Contributing

This project follows a multi-developer workflow. Please:

1. Pick an issue from GitHub Issues
2. Create a feature branch
3. Follow the existing code patterns
4. Submit a PR when complete

License

Private