Crossword Studio - AI-Powered Puzzle Generator

A production-ready, commercial-grade crossword puzzle generator that demonstrates AI/LLM capabilities through an interactive web application. Users can input topics (e.g., "The Office", "Basketball", "Pixar Characters") and receive fully playable crossword puzzles with generated clues.

🚀 Features

• AI-Powered Word Generation: Generates themed words and clues using multiple LLM providers
• Robust Crossword Algorithm: Creates valid crosswords with proper word intersections
• Interactive Grid: Professional crossword interface with click/type interaction
• Multi-Provider LLM Support: OpenAI, Anthropic, Ollama, and mock fallback
• Production Ready: Docker containerization with health checks
• Comprehensive Testing: Full test suite with 80%+ coverage

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │    │   Backend       │    │   LLM APIs      │
│   (React/TS)    │◄──►│   (FastAPI)     │◄──►│   Multi-provider│
│   Port: 3000    │    │   Port: 8000    │    │   External APIs │
│   Nginx Proxy   │    │   Python        │    │   + Local Ollama│
└─────────────────┘    └─────────────────┘    └─────────────────┘

🚀 Quick Start

Using Docker (Recommended)

1. Clone and setup:

   git clone <repository>
   cd faster_dynamic_crossword
   cp .env.template .env

2. Configure environment (edit .env):

   LLM_PROVIDER=anthropic  # or openai, ollama, mock
   ANTHROPIC_API_KEY=your_key_here
   OPENAI_API_KEY=your_key_here

3. Start the application:

   docker-compose up --build

4. Access the application:

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:8000
   • Health Check: http://localhost:8000/health

Local Development

Backend Setup

cd backend
pip install -r requirements.txt
python start_server.py

Frontend Setup

cd frontend
npm install
npm start

🧪 Testing

Backend Tests

cd backend
pytest tests/ -v

Test Coverage

• Crossword generation algorithm validation
• LLM integration with multiple providers
• API endpoint functionality
• Error handling and edge cases

🛠️ Core Components

Backend (/backend)

• FastAPI Application: RESTful API with CORS support
• Crossword Generator: Robust algorithm preventing invalid word formations
• LLM Service: Multi-provider integration with fallback
• Comprehensive Tests: pytest suite with mocking

Frontend (/frontend)

• React TypeScript: Modern component architecture
• Interactive Grid: Professional crossword interface
• Tab System: Topic generation vs. custom words
• Responsive Design: Mobile-friendly with touch support

📋 API Endpoints

• POST /generate-from-topic - Generate words from topic
• POST /generate-crossword - Create crossword from word list
• GET /clues/{crossword_id} - Retrieve stored clues
• GET /health - Health check

🔧 Configuration

Environment Variables

Variable	Description	Default
LLM_PROVIDER	LLM provider (openai/anthropic/ollama/mock)	mock
OPENAI_API_KEY	OpenAI API key	-
ANTHROPIC_API_KEY	Anthropic API key	-
OLLAMA_BASE_URL	Ollama server URL	http://localhost:11434

LLM Providers

1. OpenAI: GPT-3.5-turbo for word generation
2. Anthropic: Claude Haiku for word generation
3. Ollama: Local LLM support (llama2)
4. Mock: Fallback with curated word lists

🎯 Crossword Algorithm

The crossword generation engine implements:

• Intersection Validation: Ensures proper word connections
• Boundary Checking: Prevents word merging and overflow
• Perpendicular Word Validation: Avoids creating invalid words
• Connectivity Requirements: All words must connect to main structure
• Quality Filtering: Professional crossword standards

🔒 Security Features

• API Key Management: Environment-based configuration
• CORS Protection: Proper cross-origin headers
• Input Validation: Sanitized user inputs
• Container Security: Non-root users, minimal images
• Health Monitoring: Built-in health checks

📱 User Experience

1. Topic Input: Enter any topic (e.g., "Basketball")
2. Word Generation: AI generates 30 themed words with clues
3. Crossword Creation: Algorithm creates valid puzzle structure
4. Interactive Solving: Click cells, type letters, navigate with arrows
5. Validation: Check answers or reveal solution
6. Completion Tracking: Real-time progress indication

🐛 Troubleshooting

Common Issues

CORS Errors: Ensure backend is running and CORS is configured LLM API Failures: Check API keys and network connectivity Docker Build Failures: Verify Docker and docker-compose versions Frontend Build Issues: Clear npm cache and reinstall dependencies

Debug Mode

# Backend with debug logging
cd backend
uvicorn src.api:app --reload --log-level debug

# Frontend with detailed errors
cd frontend
npm start

🚢 Deployment

Production Deployment

1. Set production environment variables
2. Use production Docker configurations
3. Configure reverse proxy (nginx)
4. Set up monitoring and logging
5. Implement backup strategies

Scaling Considerations

• Stateless backend design for horizontal scaling
• Session storage can be moved to Redis/database
• CDN for frontend assets
• Load balancing for multiple backend instances

📊 Performance

• Backend Response: < 2 seconds for crossword generation
• Frontend Rendering: 60fps animations, smooth interactions
• LLM Calls: Timeout handling with fallback
• Docker Images: Optimized with multi-stage builds

🤝 Contributing

1. Fork the repository
2. Create feature branch
3. Add tests for new functionality
4. Ensure all tests pass
5. Submit pull request

📄 License

This project is built for demonstration purposes and showcases AI integration patterns for crossword generation.

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Built with AI-powered crossword generation 🧩