# Hugging Face Spaces Deployment

This document explains the changes made to support Hugging Face Spaces deployment.

## Changes Made

### 1. Root-level Entry Point (`app.py`)
- Created a root-level `app.py` file that serves as the entry point for Hugging Face Spaces
- This file imports the FastAPI app from the `ai_med_extract` package
- Includes multiple fallback strategies for robust error handling
- Added comprehensive logging for debugging

### 2. Package Structure
- Added `__init__.py` at the root level to make it a proper Python package
- The main application code remains in `services/ai-service/src/ai_med_extract/`

### 3. Requirements File
- Created a root-level `requirements.txt` with all necessary dependencies
- This is used by Hugging Face Spaces for dependency installation

### 4. Environment Configuration
- Set `FAST_MODE=true` and `PRELOAD_SMALL_MODELS=false` for Hugging Face Spaces
- This ensures faster startup and reduced memory usage

### 5. Dockerfile Updates
- Updated the Dockerfile to use `app:app` instead of `ai_med_extract.app:app`
- Added cache clearing configuration in `.huggingface.yaml`

## How It Works

1. Hugging Face Spaces looks for `app.py` at the root level
2. The `app.py` file adds the source directory to the Python path
3. It tries multiple import strategies:
   - Primary: Import from `ai_med_extract.app`
   - Fallback: Direct import from nested structure
   - Emergency: Create minimal FastAPI app
4. The app is initialized with minimal preloading for faster startup

## Fallback Strategies

The app includes three levels of fallback:

1. **Primary**: Normal import from `ai_med_extract.app`
2. **Fallback**: Direct import from nested structure if package import fails
3. **Emergency**: Minimal FastAPI app if all imports fail

## Testing

To test the import structure locally:

```bash
python -c "import app; print('App imported successfully:', app.app.title)"
```

## Deployment

The app should now work correctly when deployed to Hugging Face Spaces. The key changes ensure that:

- The module structure is properly recognized
- Dependencies are correctly installed
- The app starts with minimal resource usage
- Multiple fallback strategies provide robust error handling
- Comprehensive logging helps with debugging

## Troubleshooting

If you still encounter issues:

1. **Check the logs** - The app now includes comprehensive logging
2. **Verify file structure** - Ensure all files are in the correct locations
3. **Clear cache** - The `.huggingface.yaml` includes cache clearing
4. **Check dependencies** - Ensure all requirements are properly specified