DEPLOYMENT_SUMMARY.md

Deployment Summary - Hugging Face Integration

Changes Made for Hugging Face Deployment

1. Frontend Configuration (frontend/script.js)

Changed:

• Updated API base URL from http://127.0.0.1:8000 to https://moazx-api.hf.space

Impact:

• Frontend now connects to the deployed Hugging Face Space API
• Works seamlessly with the production backend

2. Backend Configuration (app.py)

Changed:

• Updated host from 127.0.0.1 to 0.0.0.0 (bind to all interfaces)
• Updated port to use environment variable PORT (default: 7860)
• Disabled reload for production
• Configured for single worker deployment

Impact:

• Backend now accepts connections from external sources
• Compatible with Hugging Face Spaces port configuration
• Optimized for production deployment

3. CORS Middleware (api/middleware.py)

Already Configured:

• CORS middleware already includes https://moazx-api.hf.space
• Supports multiple origins for development and production
• Allows credentials for authentication

No changes needed - already production-ready!

4. Docker Configuration (Dockerfile)

Already Configured:

• Multi-stage build for optimized image size
• Exposes port 7860 (Hugging Face standard)
• Runs as non-root user for security
• Uses Python 3.11-slim for minimal footprint

No changes needed - already production-ready!

5. Environment Variables (.env.example)

Updated:

• Added comprehensive documentation for all environment variables
• Included GitHub storage configuration
• Added server configuration (PORT, HOST)
• Added CORS configuration
• Documented authentication credentials

Action Required:

• Copy .env.example to .env and fill in your actual values
• Set these as secrets in Hugging Face Space settings

6. Documentation

Created/Updated:

• DEPLOYMENT.md - Comprehensive deployment guide
• README.md - Updated with full feature list and usage instructions
• .env.example - Complete environment variable documentation

Deployment Checklist

✅ Code Changes Complete

• Frontend API endpoint updated
• Backend configured for production
• CORS properly configured
• Docker configuration verified
• Environment variables documented

📋 Next Steps for Deployment

1. Prepare Hugging Face Space

   # Create a new Space on Hugging Face
   # Name: moazx-api
   # SDK: Docker
   # Hardware: CPU Basic (or better)
   

2. Set Environment Variables in Hugging Face Go to Space Settings → Variables and Secrets:

   OPENAI_API_KEY=your_actual_key
   GITHUB_TOKEN=your_github_token
   GITHUB_REPO=username/repo
   GITHUB_BRANCH=main
   PORT=7860
   

3. Deploy Code to Hugging Face

   # Clone your HF Space
   git clone https://huggingface.co/spaces/YOUR_USERNAME/moazx-api
   cd moazx-api
   
   # Copy all backend files
   cp -r /path/to/backend/* .
   
   # Commit and push
   git add .
   git commit -m "Initial deployment"
   git push
   

4. Verify Deployment

   • Wait for build to complete (check logs)
   • Test health endpoint: https://moazx-api.hf.space/health
   • Test API docs: https://moazx-api.hf.space/docs
   • Test frontend by opening frontend/index.html

5. Test Functionality

   • Login with credentials (admin/admin123)
   • Ask a test question
   • Verify citations are working
   • Test export functionality
   • Check streaming responses

File Structure for Deployment

backend/
├── api/
│   ├── __init__.py
│   ├── app.py                 # Main FastAPI application
│   ├── middleware.py          # CORS, auth, rate limiting
│   ├── exceptions.py
│   ├── models.py
│   └── routers/
│       ├── medical.py         # Medical query endpoints
│       ├── health.py          # Health check endpoints
│       ├── export.py          # Export endpoints
│       └── auth.py            # Authentication endpoints
├── core/
│   ├── agent.py              # LangChain agent configuration ⭐
│   ├── tools.py              # Agent tools
│   ├── retrievers.py         # Hybrid search
│   ├── context_enrichment.py # Context page enrichment
│   ├── vector_store.py       # FAISS vector store
│   └── ...
├── frontend/
│   ├── index.html            # Main UI
│   ├── script.js             # Frontend logic ⭐ (updated)
│   ├── styles.css            # Styling
│   └── login.html            # Login page
├── data/
│   ├── chunks.pkl            # Preprocessed document chunks
│   └── medical_terms_cache.json
├── Dockerfile                # Docker configuration
├── requirements.txt          # Python dependencies
├── app.py                    # Entry point ⭐ (updated)
├── README.md                 # Documentation ⭐ (updated)
├── DEPLOYMENT.md             # Deployment guide ⭐ (new)
├── .env.example              # Environment variables ⭐ (updated)
└── .gitignore

⭐ = Files modified/created for deployment

Configuration Summary

API Endpoint

• Production: https://moazx-api.hf.space
• Local Dev: http://localhost:7860

Authentication

• Default Username: admin
• Default Password: admin123
• ⚠️ Change in production!

Required Environment Variables

OPENAI_API_KEY=required
GITHUB_TOKEN=optional (for side effects)
GITHUB_REPO=optional
PORT=7860

Optional Environment Variables

LANGSMITH_API_KEY=optional (for tracing)
ALLOWED_ORIGINS=optional (auto-configured)
AUTH_USERNAME=optional (defaults to admin)
AUTH_PASSWORD=optional (defaults to admin123)

Testing the Deployment

1. Health Check

curl https://moazx-api.hf.space/health

Expected response:

{
  "status": "healthy",
  "timestamp": "2025-01-22T...",
  "version": "1.0.0"
}

2. API Documentation

Visit: https://moazx-api.hf.space/docs

3. Test Query (with authentication)

# Login first
curl -X POST https://moazx-api.hf.space/auth/login \
  -H "Content-Type: application/json" \
  -d '{"username":"admin","password":"admin123"}' \
  -c cookies.txt

# Ask a question
curl -X GET "https://moazx-api.hf.space/ask?query=What%20is%20EGFR%20mutation&session_id=test123" \
  -b cookies.txt

Troubleshooting

Issue: Build fails on Hugging Face

• Check Dockerfile syntax
• Verify requirements.txt has all dependencies
• Check Space logs for specific errors

Issue: API returns 500 errors

• Verify OPENAI_API_KEY is set correctly
• Check application logs in Space
• Verify data files (chunks.pkl) are present

Issue: Frontend can't connect

• Verify CORS settings in middleware.py
• Check that frontend is using correct API URL
• Test API endpoint directly first

Issue: Authentication fails

• Verify credentials in auth.py
• Check cookie settings
• Ensure HTTPS is being used

Performance Considerations

Current Setup

• CPU-optimized: Uses faiss-cpu and CPU-only PyTorch
• Memory: ~2-4GB RAM usage
• Startup time: 30-60 seconds (background initialization)

Optimization Options

1. Upgrade to GPU tier - Faster embeddings and inference
2. Enable caching - Cache frequently accessed documents
3. Optimize chunk size - Reduce memory footprint
4. Use persistent storage - Store vector index on disk

Security Checklist

• HTTPS enabled (automatic on Hugging Face)
• Session-based authentication implemented
• Rate limiting configured (100 req/min)
• CORS properly configured
• Input validation in place
• Change default credentials (TODO in production)
• Rotate API keys regularly (TODO)
• Enable monitoring/logging (TODO)

Monitoring

Key Metrics to Monitor

1. API Response Time: Check X-Process-Time header
2. Error Rate: Monitor 500 errors in logs
3. Initialization Status: /health/initialization endpoint
4. OpenAI API Usage: Monitor token consumption

Logs Location

• Hugging Face Space logs tab
• Application logs: /logs/app.log

Next Steps After Deployment

1. Test thoroughly with real clinical questions
2. Monitor performance and optimize as needed
3. Update documentation with actual deployment URL
4. Set up monitoring and alerts
5. Plan for scaling if usage increases
6. Regular updates to medical guidelines
7. Security audit and credential rotation

Support Resources

• Deployment Guide: See DEPLOYMENT.md
• API Documentation: Visit /docs on deployed Space
• Hugging Face Docs: https://huggingface.co/docs/hub/spaces
• FastAPI Docs: https://fastapi.tiangolo.com/

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Deployment Status: ✅ Ready for Deployment

All code changes are complete. Follow the deployment checklist to deploy to Hugging Face Spaces.