# Quick Deployment Guide

Follow these steps to deploy the Lineage Graph Extractor to Hugging Face Spaces:

## Quick Start (5 minutes)

### 1. Create Space
```bash
# Go to: https://huggingface.co/new-space
# Choose: Gradio SDK
# Hardware: CPU Basic (free)
```

### 2. Upload Files
Upload these files from `/hf_space/` to your Space:
- ✅ `app.py`
- ✅ `requirements.txt`
- ✅ `README.md`
- ⚠️ `.env.example` (optional reference)
- ⚠️ `SETUP_GUIDE.md` (optional)

### 3. Add Secrets
In Space Settings → Repository Secrets, add:
- `ANTHROPIC_API_KEY` - Your Claude API key (**required**)
- `GOOGLE_CLOUD_PROJECT` - For BigQuery (optional)

### 4. Wait for Build
- Space will automatically build (2-3 minutes)
- Check "Logs" tab for any errors
- Once ready, the app will be live!

## Detailed Step-by-Step

### Method 1: Web Interface (Easiest)

1. **Create Space**
   - Go to https://huggingface.co/spaces
   - Click "Create new Space"
   - Name: `lineage-graph-extractor`
   - SDK: Gradio
   - Click "Create Space"

2. **Upload Files**
   - Click "Files and versions"
   - Click "Add file" → "Upload files"
   - Select all files from `/hf_space/`
   - Click "Commit changes"

3. **Configure Secrets**
   - Click "Settings"
   - Scroll to "Repository secrets"
   - Add `ANTHROPIC_API_KEY` with your API key
   - Save

4. **Verify Deployment**
   - Go to "App" tab
   - Wait for build to complete
   - Test the interface

### Method 2: Git CLI (For Developers)

```bash
# Clone your Space
git clone https://huggingface.co/spaces/YOUR_USERNAME/lineage-graph-extractor
cd lineage-graph-extractor

# Copy files (adjust path to where you saved the files)
cp /path/to/hf_space/app.py .
cp /path/to/hf_space/requirements.txt .
cp /path/to/hf_space/README.md .

# Commit and push
git add .
git commit -m "Initial deployment"
git push
```

Then add secrets via the web interface (Settings → Repository secrets).

### Method 3: Hugging Face CLI

```bash
# Install Hugging Face CLI
pip install huggingface_hub

# Login
huggingface-cli login

# Create Space
huggingface-cli repo create lineage-graph-extractor --type space --space_sdk gradio

# Upload files
huggingface-cli upload lineage-graph-extractor /path/to/hf_space/ .
```

## Important: Connect Your Agent

⚠️ **The template needs your agent integration!**

The `app.py` file contains placeholder functions. You need to integrate your actual agent:

### Quick Integration Example

Edit `app.py` and replace the `extract_lineage_from_text` function:

```python
import anthropic
import os

client = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))

def extract_lineage_from_text(metadata_text, source_type, viz_format):
    """Extract lineage using Claude AI agent."""
    
    prompt = f"""
    You are a lineage extraction expert. Extract data lineage from this {source_type} metadata 
    and create a {viz_format} visualization.
    
    Metadata:
    {metadata_text}
    
    Return:
    1. The visualization code
    2. A brief summary
    """
    
    response = client.messages.create(
        model="claude-3-5-sonnet-20241022",
        max_tokens=4000,
        messages=[{"role": "user", "content": prompt}]
    )
    
    # Parse response to extract visualization and summary
    text = response.content[0].text
    
    # Simple parsing (improve this based on your needs)
    parts = text.split("---")
    visualization = parts[0] if len(parts) > 0 else text
    summary = parts[1] if len(parts) > 1 else "Lineage extracted successfully"
    
    return visualization.strip(), summary.strip()
```

### Using Agent Memory Files

To use your full agent configuration:

1. Copy `/memories/` directory to Space:
```bash
cp -r /memories /path/to/space/
```

2. Reference agent instructions in your code:
```python
with open("memories/agent.md") as f:
    agent_instructions = f.read()

# Use instructions in prompts
```

## Post-Deployment

### Test Functionality
1. ✅ Text/File extraction works
2. ✅ BigQuery integration (if configured)
3. ✅ URL fetching works
4. ✅ Visualizations render correctly

### Optimize Performance
- Upgrade hardware if needed (Settings → Hardware)
- Add caching for repeated queries
- Implement rate limiting

### Share Your Space
- Make it public (Settings → Visibility)
- Share URL: `https://huggingface.co/spaces/YOUR_USERNAME/lineage-graph-extractor`
- Add to your profile or collection

## Costs

- **Basic CPU**: Free forever ✅
- **Upgraded CPU**: ~$0.03/hour
- **GPU**: ~$0.60/hour (if needed for heavy processing)
- **API costs**: Anthropic Claude API usage (pay-as-you-go)

## Troubleshooting

### Build Fails
- Check requirements.txt for incompatible versions
- Review logs for specific error messages
- Ensure Python 3.9+ compatibility

### App Won't Load
- Verify `app.py` has no syntax errors
- Check that `demo.launch()` is called
- Review Space logs

### API Errors
- Verify `ANTHROPIC_API_KEY` is set correctly
- Check API key has proper permissions
- Monitor API usage and rate limits

### Visualization Issues
- Test Mermaid syntax at https://mermaid.live/
- Ensure proper code block formatting
- Check browser console for rendering errors

## Support

- **Hugging Face Docs**: https://huggingface.co/docs/hub/spaces
- **Gradio Docs**: https://gradio.app/docs
- **Community Forum**: https://discuss.huggingface.co/

## Next Steps

1. ✅ Deploy to Hugging Face Spaces
2. 🔧 Integrate your agent backend
3. 🧪 Test with real metadata
4. 🎨 Customize UI/UX
5. 📊 Add analytics
6. 🚀 Share with community

---

**Ready to deploy?** Start with Method 1 (Web Interface) - it's the easiest!