# Hugging Face Spaces Deployment

This guide explains how to deploy the Knowledge Graph Extraction app to Hugging Face Spaces using the provided Dockerfile.

## Deployment Steps

### 1. Create a New Space
1. Go to [Hugging Face Spaces](https://huggingface.co/spaces)
2. Click "Create new Space"
3. Choose a name for your space
4. Select "Docker" as the SDK
5. Choose "Public" or "Private" visibility

### 2. Upload Files
Upload all the project files to your space, including:
- `Dockerfile`
- `app_streamlit.py`
- `requirements.txt`
- `src/` directory with all modules
- `config/` directory
- `.env.example` (optional)

### 3. Environment Variables
In your Hugging Face Space settings, add the following environment variable:
- `OPENROUTER_API_KEY`: Your OpenRouter API key (optional, users can also input it in the app)

### 4. Docker Configuration
The Dockerfile is already optimized for HF Spaces with:
- Port 7860 (HF Spaces standard)
- Proper system dependencies for PDF processing
- Streamlit configured for headless deployment
- Health checks enabled

### 5. App Features
Once deployed, users can:
- Upload PDF, TXT, DOCX, or JSON documents
- Enter their OpenRouter API key in the sidebar
- Extract knowledge graphs using LLM processing
- Visualize graphs with various layout options
- Filter entities by type and importance
- Export graphs in JSON, GraphML, or GEXF formats

## Technical Details

### Dependencies
The Dockerfile installs:
- System packages: `poppler-utils`, `libpoppler-cpp-dev` for PDF processing
- Python packages: All from `requirements.txt`

### File Limits
- Default Streamlit file upload limit: 200MB
- Recommended per-file limit in config: 10MB

### Models Used
- Primary: `qwen/qwen3-32b` (free model via OpenRouter)
- The app uses cost-effective models to minimize API costs

## Usage Notes
- Users need their own OpenRouter API key
- Processing time depends on document size and complexity
- The app supports batch processing of multiple documents
- Temporary files are automatically cleaned up after processing

## Troubleshooting
If deployment fails:
1. Check that all files are uploaded correctly
2. Verify the Dockerfile syntax
3. Check HF Spaces logs for specific error messages
4. Ensure requirements.txt contains all necessary dependencies