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PDF-Redaction-API / DEPLOYMENT.md

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# Deployment Guide for HuggingFace Spaces

## Prerequisites

1. **HuggingFace Account**: Sign up at https://huggingface.co/
2. **Git**: Installed on your local machine
3. **Git LFS**: For large file storage (optional)

## Step-by-Step Deployment

### 1. Create a New Space

1. Go to https://huggingface.co/spaces
2. Click "Create new Space"
3. Fill in the details:
   - **Space name**: `pdf-redaction-api` (or your preferred name)
   - **License**: MIT
   - **SDK**: Docker
   - **Hardware**: CPU Basic (free tier) or upgrade if needed
4. Click "Create Space"

### 2. Clone Your Space Repository

```bash
git clone https://huggingface.co/spaces/YOUR_USERNAME/pdf-redaction-api
cd pdf-redaction-api
```

### 3. Copy All Files to the Repository

Copy all files from this project to your cloned space:

```bash
# Copy all files
cp -r /path/to/pdf-redaction-api/* .
# Check the files
ls -la
```

You should see:
- `main.py`
- `app/`
- `Dockerfile`
- `requirements.txt`
- `README.md`
- `.gitignore`
- `.dockerignore`
- `uploads/` (with .gitkeep)
- `outputs/` (with .gitkeep)

### 4. Commit and Push

```bash
# Add all files
git add .
# Commit
git commit -m "Initial deployment of PDF Redaction API"
# Push to HuggingFace
git push
```

### 5. Monitor Deployment

1. Go to your Space URL: `https://huggingface.co/spaces/YOUR_USERNAME/pdf-redaction-api`
2. You'll see the build logs
3. Wait for the build to complete (usually 5-10 minutes)
4. Once complete, your API will be live!

### 6. Test Your Deployment

```bash
# Check health
curl https://YOUR_USERNAME-pdf-redaction-api.hf.space/health
# Test with a PDF
curl -X POST "https://YOUR_USERNAME-pdf-redaction-api.hf.space/redact" \
  -F "file=@test.pdf" \
  -F "dpi=300"
```

## Configuration Options

### Hardware Upgrades

For better performance, consider upgrading your Space hardware:

1. Go to Space Settings
2. Click on "Hardware"
3. Choose:
   - **CPU Basic** (Free): Good for testing, slower processing
   - **CPU Upgrade** (~$0.50/hour): Faster processing
   - **GPU** (~$0.60-3/hour): Best for large documents

### Environment Variables

Add environment variables in Space Settings if needed:

```bash
HF_HOME=/app/cache
PYTHONUNBUFFERED=1
```

### Persistent Storage

For persistent file storage:

1. Go to Space Settings
2. Enable "Persistent Storage"
3. This keeps uploaded/processed files between restarts

## Custom Domain (Optional)

To use a custom domain:

1. Go to Space Settings
2. Click "Domains"
3. Add your custom domain
4. Follow DNS configuration instructions

## Monitoring and Logs

### View Logs

1. Go to your Space page
2. Click on "Logs" tab
3. Monitor real-time logs

### Check Resource Usage

1. Click on "Insights" tab
2. View CPU/Memory usage
3. Monitor request patterns

## Security Considerations

### For Production Use

1. **Add Authentication**: 
   - Implement API key authentication
   - Use OAuth2 for user management

2. **Rate Limiting**:
   - Add rate limiting to prevent abuse
   - Use slowapi or similar libraries

3. **File Size Limits**:
   - Restrict upload file sizes
   - Implement timeout for long-running requests

4. **HTTPS Only**:
   - HuggingFace Spaces provides HTTPS by default
   - Ensure all requests use HTTPS

Example with API key authentication:

```python
from fastapi import Security, HTTPException, status
from fastapi.security import APIKeyHeader
API_KEY = "your-secret-key"
api_key_header = APIKeyHeader(name="X-API-Key")
def verify_api_key(api_key: str = Security(api_key_header)):
    if api_key != API_KEY:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail="Invalid API Key"
        )
    return api_key
# Add to endpoints
@app.post("/redact")
async def redact_pdf(
    file: UploadFile = File(...),
    api_key: str = Security(verify_api_key)
):
    # Your code here
```

## Troubleshooting

### Build Fails

**Problem**: Docker build fails

**Solution**:
- Check Dockerfile syntax
- Ensure all dependencies are in requirements.txt
- Review build logs for specific errors

### Out of Memory

**Problem**: API crashes with OOM errors

**Solution**:
- Reduce default DPI to 200
- Upgrade to larger hardware
- Implement request queuing

### Slow Processing

**Problem**: Redaction takes too long

**Solution**:
- Lower DPI (150-200 for faster processing)
- Upgrade to GPU hardware
- Optimize batch processing

### Model Download Issues

**Problem**: Model fails to download

**Solution**:
- Check HuggingFace model availability
- Verify internet access in Space
- Pre-download model and include in Docker image

## Updating Your Space

To update your deployed API:

```bash
# Make changes locally
# Test changes
# Commit and push
git add .
git commit -m "Update: description of changes"
git push
# HuggingFace will automatically rebuild
```

## Cost Estimation

### Free Tier
- CPU Basic
- Limited to 2 CPU cores
- 16GB RAM
- Good for: Testing, low-traffic demos

### Paid Tiers
- CPU Upgrade: ~$0.50/hour (~$360/month if always on)
- GPU T4: ~$0.60/hour (~$432/month)
- GPU A10G: ~$1.50/hour (~$1,080/month)

**Recommendation**: Start with free tier, upgrade based on usage

## Alternative Deployment Options

### 1. Deploy on Your Own Server

```bash
# Build Docker image
docker build -t pdf-redaction-api .
# Run container
docker run -p 7860:7860 pdf-redaction-api
```

### 2. Deploy on Cloud Platforms

- **AWS ECS/Fargate**: For scalable production
- **Google Cloud Run**: Serverless container deployment
- **Azure Container Instances**: Easy container deployment
- **DigitalOcean App Platform**: Simple PaaS deployment

### 3. Deploy on Render.com

1. Connect your GitHub repo
2. Select "Docker" as environment
3. Deploy automatically

## Support

For issues:
1. Check HuggingFace Spaces documentation
2. Review logs in Space dashboard
3. Test locally with Docker first
4. Open issue on your repository

## Next Steps

After successful deployment:

1. ✅ Test all API endpoints
2. ✅ Set up monitoring
3. ✅ Configure custom domain (optional)
4. ✅ Add authentication for production
5. ✅ Implement rate limiting
6. ✅ Set up error tracking (e.g., Sentry)
7. ✅ Create API documentation with examples
8. ✅ Add usage analytics

Your API is now live and ready to use! 🚀

	# Deployment Guide for HuggingFace Spaces

	## Prerequisites

	1. HuggingFace Account: Sign up at https://huggingface.co/
	2. Git: Installed on your local machine
	3. Git LFS: For large file storage (optional)

	## Step-by-Step Deployment

	### 1. Create a New Space

	1. Go to https://huggingface.co/spaces
	2. Click "Create new Space"
	3. Fill in the details:
	- Space name: `pdf-redaction-api` (or your preferred name)
	- License: MIT
	- SDK: Docker
	- Hardware: CPU Basic (free tier) or upgrade if needed
	4. Click "Create Space"

	### 2. Clone Your Space Repository

	```bash
	git clone https://huggingface.co/spaces/YOUR_USERNAME/pdf-redaction-api
	cd pdf-redaction-api
	```

	### 3. Copy All Files to the Repository

	Copy all files from this project to your cloned space:

	```bash
	# Copy all files
	cp -r /path/to/pdf-redaction-api/* .

	# Check the files
	ls -la
	```

	You should see:
	- `main.py`
	- `app/`
	- `Dockerfile`
	- `requirements.txt`
	- `README.md`
	- `.gitignore`
	- `.dockerignore`
	- `uploads/` (with .gitkeep)
	- `outputs/` (with .gitkeep)

	### 4. Commit and Push

	```bash
	# Add all files
	git add .

	# Commit
	git commit -m "Initial deployment of PDF Redaction API"

	# Push to HuggingFace
	git push
	```

	### 5. Monitor Deployment

	1. Go to your Space URL: `https://huggingface.co/spaces/YOUR_USERNAME/pdf-redaction-api`
	2. You'll see the build logs
	3. Wait for the build to complete (usually 5-10 minutes)
	4. Once complete, your API will be live!

	### 6. Test Your Deployment

	```bash
	# Check health
	curl https://YOUR_USERNAME-pdf-redaction-api.hf.space/health

	# Test with a PDF
	curl -X POST "https://YOUR_USERNAME-pdf-redaction-api.hf.space/redact" \
	-F "file=@test.pdf" \
	-F "dpi=300"
	```

	## Configuration Options

	### Hardware Upgrades

	For better performance, consider upgrading your Space hardware:

	1. Go to Space Settings
	2. Click on "Hardware"
	3. Choose:
	- CPU Basic (Free): Good for testing, slower processing
	- CPU Upgrade (~$0.50/hour): Faster processing
	- GPU (~$0.60-3/hour): Best for large documents

	### Environment Variables

	Add environment variables in Space Settings if needed:

	```bash
	HF_HOME=/app/cache
	PYTHONUNBUFFERED=1
	```

	### Persistent Storage

	For persistent file storage:

	1. Go to Space Settings
	2. Enable "Persistent Storage"
	3. This keeps uploaded/processed files between restarts

	## Custom Domain (Optional)

	To use a custom domain:

	1. Go to Space Settings
	2. Click "Domains"
	3. Add your custom domain
	4. Follow DNS configuration instructions

	## Monitoring and Logs

	### View Logs

	1. Go to your Space page
	2. Click on "Logs" tab
	3. Monitor real-time logs

	### Check Resource Usage

	1. Click on "Insights" tab
	2. View CPU/Memory usage
	3. Monitor request patterns

	## Security Considerations

	### For Production Use

	1. Add Authentication:
	- Implement API key authentication
	- Use OAuth2 for user management

	2. Rate Limiting:
	- Add rate limiting to prevent abuse
	- Use slowapi or similar libraries

	3. File Size Limits:
	- Restrict upload file sizes
	- Implement timeout for long-running requests

	4. HTTPS Only:
	- HuggingFace Spaces provides HTTPS by default
	- Ensure all requests use HTTPS

	Example with API key authentication:

	```python
	from fastapi import Security, HTTPException, status
	from fastapi.security import APIKeyHeader

	API_KEY = "your-secret-key"
	api_key_header = APIKeyHeader(name="X-API-Key")

	def verify_api_key(api_key: str = Security(api_key_header)):
	if api_key != API_KEY:
	raise HTTPException(
	status_code=status.HTTP_401_UNAUTHORIZED,
	detail="Invalid API Key"
	)
	return api_key

	# Add to endpoints
	@app.post("/redact")
	async def redact_pdf(
	file: UploadFile = File(...),
	api_key: str = Security(verify_api_key)
	):
	# Your code here
	```

	## Troubleshooting

	### Build Fails

	Problem: Docker build fails

	Solution:
	- Check Dockerfile syntax
	- Ensure all dependencies are in requirements.txt
	- Review build logs for specific errors

	### Out of Memory

	Problem: API crashes with OOM errors

	Solution:
	- Reduce default DPI to 200
	- Upgrade to larger hardware
	- Implement request queuing

	### Slow Processing

	Problem: Redaction takes too long

	Solution:
	- Lower DPI (150-200 for faster processing)
	- Upgrade to GPU hardware
	- Optimize batch processing

	### Model Download Issues

	Problem: Model fails to download

	Solution:
	- Check HuggingFace model availability
	- Verify internet access in Space
	- Pre-download model and include in Docker image

	## Updating Your Space

	To update your deployed API:

	```bash
	# Make changes locally
	# Test changes

	# Commit and push
	git add .
	git commit -m "Update: description of changes"
	git push

	# HuggingFace will automatically rebuild
	```

	## Cost Estimation

	### Free Tier
	- CPU Basic
	- Limited to 2 CPU cores
	- 16GB RAM
	- Good for: Testing, low-traffic demos

	### Paid Tiers
	- CPU Upgrade: ~$0.50/hour (~$360/month if always on)
	- GPU T4: ~$0.60/hour (~$432/month)
	- GPU A10G: ~$1.50/hour (~$1,080/month)

	Recommendation: Start with free tier, upgrade based on usage

	## Alternative Deployment Options

	### 1. Deploy on Your Own Server

	```bash
	# Build Docker image
	docker build -t pdf-redaction-api .

	# Run container
	docker run -p 7860:7860 pdf-redaction-api
	```

	### 2. Deploy on Cloud Platforms

	- AWS ECS/Fargate: For scalable production
	- Google Cloud Run: Serverless container deployment
	- Azure Container Instances: Easy container deployment
	- DigitalOcean App Platform: Simple PaaS deployment

	### 3. Deploy on Render.com

	1. Connect your GitHub repo
	2. Select "Docker" as environment
	3. Deploy automatically

	## Support

	For issues:
	1. Check HuggingFace Spaces documentation
	2. Review logs in Space dashboard
	3. Test locally with Docker first
	4. Open issue on your repository

	## Next Steps

	After successful deployment:

	1. ✅ Test all API endpoints
	2. ✅ Set up monitoring
	3. ✅ Configure custom domain (optional)
	4. ✅ Add authentication for production
	5. ✅ Implement rate limiting
	6. ✅ Set up error tracking (e.g., Sentry)
	7. ✅ Create API documentation with examples
	8. ✅ Add usage analytics

	Your API is now live and ready to use! 🚀