DEPLOYMENT_SUMMARY.md

🚀 Quick Deployment Summary

✅ Files Created/Updated for Hugging Face Deployment

1. .huggingface.yaml - Hugging Face Spaces configuration
2. Dockerfile - Optimized for HF Spaces with CPU-only PyTorch
3. requirements-hf.txt - Lightweight dependencies for deployment
4. app/main.py - Added health checks and root endpoints
5. .github/workflows/deploy-hf.yml - GitHub Actions workflow
6. deploy-to-hf.bat - Windows deployment helper script
7. HUGGINGFACE_DEPLOYMENT.md - Complete deployment guide

🎯 Quick Deployment Steps

1. Push to GitHub

git add .
git commit -m "Deploy to Hugging Face Spaces"
git push origin main

2. Create Hugging Face Space

1. Go to huggingface.co/spaces
2. Click "Create new Space"
3. Settings:
   • SDK: Docker
   • License: MIT
   • Connect to your GitHub repo

3. Set Environment Variables

In your Space settings, add:

GROQ_API_KEY=your_groq_api_key
DATABASE_URL=sqlite+aiosqlite:///./dubsway_hf.db
SECRET_KEY=your_secret_key
ENVIRONMENT=production

4. Deploy

• Hugging Face will automatically build and deploy
• Monitor build logs in your Space
• Your API will be available at: https://your-username-dubsway-video-ai.hf.space/

🔍 Test Your Deployment

1. Health Check: GET /health
2. API Docs: GET /docs
3. Root Endpoint: GET /

📞 Need Help?

• Run deploy-to-hf.bat for step-by-step guidance
• Check HUGGINGFACE_DEPLOYMENT.md for detailed instructions
• Monitor build logs in your Hugging Face Space

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Your Dubsway Video AI is ready for deployment! 🎉