docs/TODO.md

# Crossword Puzzle Webapp - TODO List

## 🎯 Current Status: **Phases 1-5 Complete - Phase 6 (LLM Enhancement) In Progress**

## ✅ COMPLETED PHASES (Phases 1-5)

### ✅ Phase 1: Project Setup 
- [x] ✅ Set up project structure and initialize repositories
  - [x] Create frontend/ and backend/ directories
  - [x] Initialize package.json files
  - [x] Set up Git repository
  - [x] Modern ES modules configuration

### ✅ Phase 2: Data Management (JSON-based)
- [x] ✅ Create data structure and seed data
  - [x] JSON-based word lists by topic (animals.json, science.json, etc.)
  - [x] 400+ words with quality clues
  - [x] In-memory caching system
  - [x] WordService for data management

### ✅ Phase 3: Core Algorithm Development
- [x] ✅ Implement advanced crossword generation algorithm
  - [x] Smart word selection with crossword suitability scoring
  - [x] Sophisticated grid placement with intersection optimization
  - [x] Robust backtracking with timeout handling
  - [x] Grid optimization with automatic trimming

### ✅ Phase 4: Backend API
- [x] ✅ Build comprehensive backend API endpoints
  - [x] GET /api/topics - List available topics
  - [x] POST /api/generate - Generate crossword puzzle
  - [x] POST /api/validate - Validate user answers
  - [x] GET /api/words/:topic - Get words for topic
  - [x] GET /api/health - Health check
  - [x] Error handling, rate limiting, CORS, security headers

### ✅ Phase 5: Frontend Components & Features
- [x] ✅ Create all frontend components
  - [x] TopicSelector with multi-select buttons and visual feedback
  - [x] PuzzleGrid with CSS Grid layout and interactive cells
  - [x] ClueList component (Across/Down) with click navigation
  - [x] LoadingSpinner with generation progress messages
  - [x] PuzzleControls (Reset/Reveal/Generate buttons)

### ✅ Phase 6: Interactive Features
- [x] ✅ Implement full interactive crossword functionality
  - [x] Click-to-focus input cells with keyboard navigation
  - [x] Real-time input validation and auto-uppercase
  - [x] Completion detection and success messages
  - [x] Solution reveal functionality

### ✅ Phase 7: User Experience & Styling
- [x] ✅ Professional UI/UX with responsive design
  - [x] Mobile-responsive design (tested on iPhone 14)
  - [x] Professional color scheme and typography
  - [x] Loading states and error messages
  - [x] Smooth user interactions

### ✅ Phase 8: Deployment
- [x] ✅ Deploy to production
  - [x] Docker containerization
  - [x] HuggingFace Spaces deployment
  - [x] Public access at https://vimalk78-abc123.hf.space/
  - [x] Production environment configuration

---

## 🚀 CURRENT FOCUS: Phase 6 - LLM-Enhanced Dynamic Word Generation

### 🔄 IN PROGRESS

#### 6.1 Core LLM Infrastructure
- [ ] Install and configure HuggingFace dependencies
  - [ ] Add `@huggingface/inference` package to backend
  - [ ] Set up environment variables for HF API keys
  - [ ] Create HuggingFace account and configure access tokens

- [ ] Implement EmbeddingWordService class
  - [ ] Create `backend/src/services/embeddingWordService.js`
  - [ ] Integrate `sentence-transformers/all-MiniLM-L6-v2` model
  - [ ] Implement semantic similarity search for word generation
  - [ ] Add error handling and fallback to static words

#### 6.2 Dynamic Word Generation
- [ ] Build topic-aware word generation system
  - [ ] Implement semantic word discovery using embeddings
  - [ ] Create word quality filtering for crossword suitability
  - [ ] Add word difficulty scoring and classification
  - [ ] Implement content validation (filter inappropriate words)

- [ ] Enhance word selection algorithm
  - [ ] Integrate AI-generated words with existing crossword algorithm
  - [ ] Optimize word selection for better grid placement
  - [ ] Add intersection-aware word generation

#### 6.3 LLM-Powered Clue Generation
- [ ] Implement intelligent clue generation
  - [ ] Set up small language model for clue creation
  - [ ] Create template-based clue generation with topic context
  - [ ] Ensure crossword-appropriate clue formatting
  - [ ] Add clue quality validation and scoring

- [ ] Enhance clue system
  - [ ] Context-aware clue generation based on topic
  - [ ] Difficulty-matched clue complexity
  - [ ] Multiple clue variations per word
  - [ ] A/B testing for clue quality

#### 6.4 Advanced Caching Implementation
- [ ] Design multi-tier cache architecture
  - [ ] L1: In-Memory (session cache) - existing ✅
  - [ ] L2: Redis integration for cross-session caching
  - [ ] L3: Enhanced fallback to JSON files

- [ ] Implement smart cache policies
  - [ ] Hybrid TTL + LRU eviction strategy
  - [ ] Usage-based scoring: `(frequency × 0.4) + (recency × 0.3) + (cost × 0.3)`
  - [ ] Adaptive TTL based on API response times and error rates
  - [ ] Topic-aware cache eviction with different TTL for popular vs niche topics

#### 6.5 Performance & Reliability
- [ ] Build robust fallback systems
  - [ ] Graceful degradation when LLM APIs fail
  - [ ] Offline mode with cached content
  - [ ] Error recovery and retry logic with exponential backoff
  - [ ] Health monitoring for LLM services

- [ ] Optimize for performance
  - [ ] Batch word generation requests
  - [ ] Precompute popular topic combinations
  - [ ] Async generation with real-time progress indicators
  - [ ] Request deduplication and coalescence

#### 6.6 Quality Control & Monitoring
- [ ] Implement content validation systems
  - [ ] Word appropriateness filtering
  - [ ] Crossword intersection analysis for AI-generated words
  - [ ] Difficulty consistency checking
  - [ ] User feedback collection system

- [ ] Add continuous improvement features
  - [ ] Analytics for AI-generated content quality metrics
  - [ ] Model performance monitoring
  - [ ] User rating system for generated puzzles
  - [ ] A/B testing framework for different models

### 🎯 FUTURE ENHANCEMENTS (Phase 7+)

#### 7.1 Advanced Features
- [ ] Custom topic support
  - [ ] User-defined topic combinations
  - [ ] Real-time topic similarity recommendations
  - [ ] Trending topic suggestions
  - [ ] Personal topic history

- [ ] Enhanced difficulty system
  - [ ] AI-driven difficulty assessment
  - [ ] Personalized difficulty scaling
  - [ ] Learning curve adaptation
  - [ ] Challenge progression system

#### 7.2 User Experience Improvements
- [ ] Advanced UI features
  - [ ] Puzzle saving and sharing
  - [ ] User accounts and puzzle history
  - [ ] Social features (puzzle sharing, challenges)
  - [ ] Mobile app development

#### 7.3 Analytics & Business Intelligence
- [ ] User behavior analytics
- [ ] Content performance metrics
- [ ] API usage monitoring
- [ ] Cost optimization analysis

## 📋 CURRENT SPRINT TASKS

**Week 1-2 (Current)**:
1. Set up HuggingFace integration
2. Create EmbeddingWordService class
3. Implement basic dynamic word generation
4. Add Redis caching layer

**Week 3-4**:
1. LLM clue generation system
2. Quality control and validation
3. Performance optimization
4. Comprehensive testing

**Week 5-6**:
1. Advanced caching strategies
2. Error handling and fallbacks
3. User feedback collection
4. Production deployment of Phase 6

## 🔗 Key Files Created ✅
- ✅ `backend/src/services/crosswordGenerator.js` - Advanced algorithm
- ✅ `backend/src/controllers/puzzleController.js` - API handlers
- ✅ `backend/src/services/wordService.js` - Data management
- ✅ `frontend/src/hooks/useCrossword.js` - State management
- ✅ `frontend/src/utils/gridHelpers.js` - Grid utilities
- ✅ `frontend/src/styles/puzzle.css` - Professional styling
- ✅ `backend/src/routes/api.js` - API routing
- ✅ `Dockerfile` - Production deployment

## 🎯 Next Priority Tasks
1. **LLM Integration Setup** - HuggingFace API and embeddings
2. **Dynamic Word Generation** - Semantic similarity-based word discovery
3. **Advanced Caching** - Redis integration with smart eviction policies
4. **Quality Control** - Validation and feedback systems