# 🚀 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
```bash
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](https://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! 🎉**