# Deployment Guide for Hugging Face Spaces

## Prerequisites

- Hugging Face account
- HF_TOKEN (optional, for model access if needed)
- GPU Space (T4 or A100 recommended)

## Deployment Steps

### 1. Create a New Space

1. Go to https://huggingface.co/new-space
2. Choose a name: `medical-report-analysis-platform`
3. Select SDK: **Docker**
4. Select Hardware: **GPU T4** (or higher)
5. Set visibility: **Public** or **Private**

### 2. Configure Space

Create the following files in your Space:

#### `Dockerfile`
```dockerfile
FROM python:3.10-slim

WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    tesseract-ocr \
    poppler-utils \
    libgl1-mesa-glx \
    libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

# Copy requirements and install
COPY backend/requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy application code
COPY backend/ ./backend/
COPY medical-ai-frontend/dist/ ./backend/static/

# Expose port
EXPOSE 7860

# Environment variables
ENV PYTHONUNBUFFERED=1
ENV PORT=7860

# Run application
CMD ["python", "backend/main.py"]
```

#### `README.md`
```markdown
---
title: Medical Report Analysis Platform
emoji: 🏥
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: mit
---

# Medical Report Analysis Platform

Advanced AI-powered medical document analysis using 50+ specialized models.

## Features

- Multi-modal PDF processing
- 50+ specialized medical AI models
- Real-time analysis visualization
- HIPAA/GDPR compliant architecture

## Usage

1. Upload a medical PDF report
2. Wait for AI analysis (30-60 seconds)
3. Review comprehensive results

**Disclaimer**: This platform provides AI-assisted analysis. All results must be reviewed by qualified healthcare professionals.
```

### 3. Upload Files

Upload the following directory structure:

```
your-space/
├── Dockerfile
├── README.md
├── backend/
│   ├── main.py
│   ├── pdf_processor.py
│   ├── document_classifier.py
│   ├── model_router.py
│   ├── analysis_synthesizer.py
│   └── requirements.txt
└── medical-ai-frontend/
    └── dist/
        ├── index.html
        └── assets/
```

### 4. Environment Variables (Optional)

If you need to access gated models:

1. Go to Space Settings → Variables
2. Add:
   - Key: `HF_TOKEN`
   - Value: Your Hugging Face token

### 5. Build and Deploy

The Space will automatically:
1. Build the Docker container
2. Install all dependencies
3. Start the application on port 7860
4. Serve both backend API and frontend UI

### 6. Access Your Application

Once deployed, your Space will be available at:
```
https://huggingface.co/spaces/YOUR_USERNAME/medical-report-analysis-platform
```

## Monitoring

### Check Logs
View logs in the Space's "Logs" tab to monitor:
- Application startup
- Request processing
- Error messages

### Performance
- Initial load: 2-5 minutes (building Docker image)
- Analysis time: 30-60 seconds per document
- Concurrent users: Depends on GPU hardware

## Troubleshooting

### Common Issues

1. **Out of Memory**
   - Upgrade to A100 GPU
   - Reduce concurrent processing
   - Implement request queuing

2. **Slow Performance**
   - Check GPU utilization
   - Optimize model loading
   - Enable model caching

3. **Build Failures**
   - Verify all files are uploaded
   - Check requirements.txt syntax
   - Review Dockerfile syntax

### Debug Mode

To enable debug logging, add to Dockerfile:
```dockerfile
ENV LOG_LEVEL=DEBUG
```

## Scaling Considerations

For production deployment:

1. **Load Balancing**: Use HF Spaces Replicas
2. **Caching**: Implement Redis for job tracking
3. **Storage**: Use external storage for large files
4. **Monitoring**: Set up health checks and alerts

## Security Notes

- Files are processed in temporary storage
- No persistent file storage by default
- Implement user authentication for production
- Add rate limiting for API endpoints

## Cost Estimation

Hugging Face Spaces pricing (approximate):

- **T4 GPU**: ~$0.60/hour
- **A10G GPU**: ~$1.10/hour
- **A100 GPU**: ~$4.13/hour

For 24/7 operation with T4:
- Monthly cost: ~$432

## Support

For issues or questions:
- Check Space logs
- Review README documentation
- Contact space maintainer

---

**Medical Report Analysis Platform** - Advanced AI-Powered Clinical Intelligence