HUGGINGFACE_DEPLOYMENT.md

# 🚀 Hugging Face Spaces Deployment Guide

This guide will help you deploy your Dubsway Video AI system to Hugging Face Spaces via GitHub.

## 📋 Prerequisites

1. **GitHub Repository**: Your code should be pushed to a GitHub repository
2. **Hugging Face Account**: Create an account at [huggingface.co](https://huggingface.co)
3. **Environment Variables**: Set up your API keys and configuration

## 🔧 Step-by-Step Deployment

### 1. Prepare Your Repository

Your repository should already have the necessary files:
- `.huggingface.yaml` - Hugging Face Spaces configuration
- `Dockerfile` - Container configuration
- `requirements-hf.txt` - Optimized dependencies
- `app/main.py` - FastAPI application

### 2. Set Up Environment Variables

In your Hugging Face Space settings, add these environment variables:

```bash
# Required for Groq LLM
GROQ_API_KEY=your_groq_api_key_here

# Database (use SQLite for simplicity)
DATABASE_URL=sqlite+aiosqlite:///./dubsway_hf.db

# AWS S3 (optional - for file storage)
AWS_ACCESS_KEY_ID=your_aws_access_key
AWS_SECRET_ACCESS_KEY=your_aws_secret_key
AWS_REGION=us-east-1
S3_BUCKET_NAME=your_s3_bucket_name

# Application
SECRET_KEY=your_secret_key_here
ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30

# Environment
ENVIRONMENT=production
```

### 3. Create Hugging Face Space

1. Go to [huggingface.co/spaces](https://huggingface.co/spaces)
2. Click "Create new Space"
3. Choose settings:
   - **Owner**: Your username
   - **Space name**: `dubsway-video-ai` (or your preferred name)
   - **License**: MIT
   - **SDK**: Docker
   - **Visibility**: Public or Private

### 4. Connect GitHub Repository

1. In your Space settings, go to "Repository" tab
2. Select "Connect to existing repository"
3. Choose your GitHub repository
4. Set the branch (usually `main` or `master`)

### 5. Configure Build Settings

The Space will automatically use:
- `.huggingface.yaml` for configuration
- `Dockerfile` for container build
- `requirements-hf.txt` for dependencies

### 6. Deploy

1. Push your changes to GitHub
2. Hugging Face will automatically build and deploy
3. Monitor the build logs in your Space

## 🔍 Verification

Once deployed, you can:

1. **Check the API**: Visit `https://your-username-dubsway-video-ai.hf.space/`
2. **View Documentation**: Visit `https://your-username-dubsway-video-ai.hf.space/docs`
3. **Health Check**: Visit `https://your-username-dubsway-video-ai.hf.space/health`

## 🛠️ API Endpoints

Your deployed API will have these endpoints:

- `GET /` - Root endpoint with API info
- `GET /health` - Health check
- `GET /docs` - Interactive API documentation
- `POST /api/auth/register` - User registration
- `POST /api/auth/login` - User login
- `POST /api/upload/video` - Video upload and analysis
- `GET /api/dashboard/videos` - Get user videos
- `POST /api/custom-chatbot/chat` - Chat with video content

## 🔧 Troubleshooting

### Common Issues

1. **Build Failures**:
   - Check the build logs in your Space
   - Ensure all dependencies are in `requirements-hf.txt`
   - Verify Dockerfile syntax

2. **Environment Variables**:
   - Make sure all required env vars are set in Space settings
   - Check for typos in variable names

3. **Memory Issues**:
   - The Space uses CPU-only PyTorch to save memory
   - Consider using smaller models for production

4. **Database Issues**:
   - Use SQLite for simplicity in Spaces
   - Ensure database directory is writable

### Monitoring

- Check Space logs for errors
- Monitor resource usage
- Test API endpoints regularly

## 🔄 Continuous Deployment

Once connected to GitHub:
1. Push changes to your repository
2. Hugging Face automatically rebuilds and deploys
3. Monitor deployment status in your Space

## 📊 Performance Optimization

For better performance in Hugging Face Spaces:

1. **Use CPU-only PyTorch**: Already configured in Dockerfile
2. **Optimize model loading**: Models are loaded on first request
3. **Use SQLite**: Lighter than PostgreSQL for Spaces
4. **Cache results**: Implement caching for repeated requests

## 🔐 Security Considerations

1. **API Keys**: Store sensitive keys in Space environment variables
2. **CORS**: Configure allowed origins for production
3. **Rate Limiting**: Implement rate limiting for public APIs
4. **Input Validation**: Validate all user inputs

## 📞 Support

If you encounter issues:
1. Check the build logs in your Space
2. Review the troubleshooting section
3. Check Hugging Face Spaces documentation
4. Monitor your application logs

---

**Happy Deploying! 🎉**

Your Dubsway Video AI system will be accessible at:
`https://your-username-dubsway-video-ai.hf.space/`