An emergency sprint build designed to generate $20M in revenue within 23 hours through viral AI-powered content creation.
- Docker & Docker Compose
- Node.js 20+ (for local development)
- Python 3.11+ (for local development)
- PostgreSQL 16
- Redis 7
- Clone the repository
git clone https://github.com/yourusername/create-ai.git
cd create-ai
- Copy environment files
cp backend/.env.example backend/.env
- Update the
.env
file with your API keys:
- AI Model API keys (Whisper, QwQ, Llama, FLUX, MeloTTS)
- Stripe API keys
- AWS S3 credentials
- Sentry DSN (optional)
- Mixpanel token (optional)
# Start all services
docker-compose up -d
# View logs
docker-compose logs -f
# Stop services
docker-compose down
Services will be available at:
- Frontend: http://localhost:3000
- Backend API: http://localhost:8000
- API Docs: http://localhost:8000/docs
cd backend
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
python run.py
cd frontend
npm install
npm run dev
# PostgreSQL
docker run -d --name postgres -e POSTGRES_PASSWORD=password -p 5432:5432 postgres:16
# Redis
docker run -d --name redis -p 6379:6379 redis:7-alpine
# Celery Worker (in backend directory)
celery -A app.celery_app worker --loglevel=info
# Celery Beat (in another terminal)
celery -A app.celery_app beat --loglevel=info
- Frontend: Next.js 14, TypeScript, Tailwind CSS, Framer Motion
- Backend: FastAPI, Python 3.11, Celery, Redis
- Database: PostgreSQL with SQLAlchemy ORM
- Storage: AWS S3 with CloudFront CDN
- AI Models:
- Whisper Large v3 Turbo (speech-to-text)
- QwQ-32B (reasoning)
- Llama 4 Scout 17B (content generation)
- FLUX.1 Schnell (image generation)
- MeloTTS (text-to-speech)
- Llama 3.2 11B Vision (quality checking)
- ⚡ Sub-30 second content creation pipeline
- 💰 Dynamic surge pricing based on server load
- 🏆 Viral challenge system with leaderboards
- 🔄 Platform-specific sharing (TikTok, Instagram, Twitter, YouTube)
- 💳 Stripe payment integration
- 📊 Real-time analytics dashboard
- 🚀 Auto-scaling with connection pooling
- 🛡️ Rate limiting and DDoS protection
- Backend metrics: http://localhost:8000/metrics
- Prometheus: http://localhost:9090 (if configured)
- Creation success rate
- Average processing time
- Revenue per hour
- Viral coefficient
- Server load percentage
- API response times
- Set all environment variables
- Configure SSL certificates
- Set up CloudFlare DDoS protection
- Configure auto-scaling groups
- Set up database backups
- Configure Sentry error tracking
- Set up Mixpanel analytics
- Test payment flows
- Load test with expected traffic
- Set up monitoring alerts
- CPU usage > 80%
- Memory usage > 80%
- Active users > 10,000
- Launch with 5 template challenges
- Influencer seeding (first 100 users)
- Referral rewards (1 free creation per 3 referrals)
- Platform-optimized sharing
- Real-time leaderboards
Creation failures
- Check AI API keys and endpoints
- Verify Redis is running
- Check Celery worker logs
Slow processing
- Monitor AI model latencies
- Check database connection pool
- Verify S3 upload speeds
Payment issues
- Verify Stripe webhook configuration
- Check webhook secret is correct
- Monitor Stripe dashboard
Interactive API docs available at: http://localhost:8000/docs
Key endpoints:
- POST
/api/auth/register
- User registration - POST
/api/creations/create
- Create content - GET
/api/challenges/trending
- Get trending challenges - POST
/api/payments/purchase
- Process payment
The system is designed to handle:
- 10M+ concurrent users
- 100K+ creations per minute
- Auto-scaling based on load
- Fallback AI endpoints
- Smart caching with Redis
Proprietary - Built for the $20M Sprint Challenge
Success Metric: $20M revenue in 23 hours 🎯