DEPLOYMENT_FIX.md

# 🚀 Deployment Fix - Resolving Build Issues

## 🔧 Fixed Issues

### 1. **Requirements.txt Problems**
- ✅ Removed problematic packages (flash-attn, xformers)
- ✅ Added missing dependencies (pyyaml, requests)
- ✅ Pinned versions for stability
- ✅ Focused on core functionality only

### 2. **Docker Build Optimization**
- ✅ Updated Dockerfile with better error handling
- ✅ Added build-essential for compilation
- ✅ Increased timeout for slow builds
- ✅ Added health check
- ✅ Created .dockerignore to reduce build context

### 3. **Dependency Management**
- ✅ CPU-only PyTorch for reliable deployment
- ✅ Stable numpy/scipy versions
- ✅ Removed optional heavy packages
- ✅ Maintained core TTS and API functionality

## 📦 Current Build Status

The repository should now build successfully with:

### **Core Features Available:**
✅ FastAPI endpoints for avatar generation  
✅ Gradio web interface  
✅ Advanced TTS system with multiple fallbacks  
✅ Audio generation and processing  
✅ Image URL support  
✅ Voice profile selection  

### **OmniAvatar Video Features:**
⏳ Requires model download (~30GB)  
⏳ Available after running `python setup_omniavatar.py`  

## 🔨 Build Commands

### **Local Build:**
```bash
# Install dependencies
pip install -r requirements.txt

# Run locally
python app.py
```

### **Docker Build:**
```bash
# Build image
docker build -t omniavatar-app .

# Run container
docker run -p 7860:7860 omniavatar-app
```

### **HuggingFace Spaces:**
The repository should now build automatically when pushed to HF Spaces.

## 📊 What Changed

### **requirements.txt:**
- Removed: flash-attn, xformers, omegaconf, datasets, protobuf
- Added: pyyaml, requests (missing dependencies)
- Pinned: numpy<1.25.0, scipy<1.12.0 for stability
- CPU-only PyTorch for reliable deployment

### **Dockerfile:**
- Added build-essential for compilation needs
- Increased timeout for slow package installs
- Better directory structure creation
- Added health check endpoint
- More robust error handling

### **.dockerignore:**
- Excluded large files (pretrained_models/, *.md files)
- Reduced build context size significantly
- Faster builds and smaller images

## 🎯 Deployment Strategy

### **Phase 1: TTS-Only Mode (Current)**
- ✅ Builds reliably
- ✅ Full TTS functionality
- ✅ Web interface working
- ✅ API endpoints functional

### **Phase 2: Full OmniAvatar (After Model Download)**
- Download models manually or via script
- Enable video generation capabilities
- Full avatar animation features

## 💡 Troubleshooting

If builds still fail:

1. **Check logs** for specific error messages
2. **Verify Python version** (should be 3.10+)
3. **Clear build cache** if using Docker
4. **Check network connectivity** for package downloads

The build should now succeed on most platforms including HuggingFace Spaces! 🎉