# DubswayVideoAI - Error Fixes Summary

## Issues Identified and Fixed

### 1. **Unicode Encoding Errors (Windows Console)**
**Problem**: Windows console couldn't display emoji characters (❌, 🎬, 📥, etc.) causing `UnicodeEncodeError: 'charmap' codec can't encode character`

**Solution**: 
- Removed all emoji characters from logging messages
- Updated logging configuration to use UTF-8 encoding
- Used `sys.stdout` for better encoding support

**Files Modified**:
- `worker/daemon.py` - Removed emojis from all log messages
- `app/utils/whisper_llm.py` - Removed emojis from all log messages

### 2. **FAISS API Compatibility Error**
**Problem**: `FAISS.__init__() got an unexpected keyword argument 'allow_dangerous_deserialization'`

**Solution**: 
- Removed the `allow_dangerous_deserialization=True` parameter from FAISS calls
- Updated to use the current FAISS API version

**Files Modified**:
- `app/utils/whisper_llm.py` - Fixed FAISS initialization calls

### 3. **Database Session Management**
**Problem**: Linter errors about async session context manager

**Solution**: 
- Updated `app/database.py` to use `async_sessionmaker` instead of `sessionmaker`
- Added proper error handling and connection pooling
- Added database initialization and cleanup functions

**Files Modified**:
- `app/database.py` - Complete rewrite with modern SQLAlchemy 2.0+ patterns

### 4. **Video Processing Errors**
**Problem**: "tuple index out of range" errors in video processing

**Solution**: 
- Added proper temp file cleanup in error cases
- Improved error handling in video download and processing
- Added better exception handling with cleanup

**Files Modified**:
- `app/utils/whisper_llm.py` - Added temp file cleanup and better error handling

### 5. **Missing Dependencies**
**Problem**: Missing SQLite support for development

**Solution**: 
- Added `aiosqlite` to requirements.txt for SQLite support

**Files Modified**:
- `requirements.txt` - Added aiosqlite dependency

## Improved Features

### 1. **Better Logging**
- UTF-8 encoded log files
- Structured logging format
- Separate log file for worker (`worker.log`)

### 2. **Graceful Shutdown**
- Signal handling for SIGINT and SIGTERM
- Proper cleanup of database connections
- Graceful worker loop termination

### 3. **Database Management**
- Automatic database initialization
- Connection pooling with health checks
- Proper async session management

### 4. **Error Recovery**
- Better error handling in all processing steps
- Automatic cleanup of temporary files
- Status tracking for failed videos

## How to Run

### 1. **Activate Virtual Environment**
```bash
myenv31\Scripts\Activate.ps1  # PowerShell
# or
myenv31\Scripts\activate.bat  # Command Prompt
```

### 2. **Install Dependencies**
```bash
pip install -r requirements.txt
```

### 3. **Run the Daemon**
```bash
# From project root
python -m worker.daemon

# Or use the batch script
start-worker.bat
```

### 4. **Test Setup**
```bash
python test_daemon.py
```

## Environment Configuration

Create a `.env` file based on `env.example`:
```bash
# Database Configuration
DATABASE_URL=sqlite+aiosqlite:///./dubsway_dev.db

# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key_here

# AWS S3 Configuration (if using S3)
AWS_ACCESS_KEY_ID=your_aws_access_key
AWS_SECRET_ACCESS_KEY=your_aws_secret_key
AWS_REGION=us-east-1
S3_BUCKET_NAME=your_s3_bucket_name
```

## Key Improvements

1. **Windows Compatibility**: Fixed all Unicode encoding issues
2. **Modern SQLAlchemy**: Updated to use async_sessionmaker
3. **Better Error Handling**: Comprehensive error handling with cleanup
4. **Resource Management**: Proper cleanup of temporary files and connections
5. **Logging**: Structured logging without emoji characters
6. **Graceful Shutdown**: Proper signal handling and cleanup

## Testing

The daemon should now:
- Start without Unicode errors
- Handle video processing errors gracefully
- Clean up resources properly
- Log messages clearly without encoding issues
- Shutdown gracefully on Ctrl+C

## Next Steps

1. Test with actual video files
2. Monitor the `worker.log` file for any remaining issues
3. Configure production database (PostgreSQL) if needed
4. Set up proper environment variables for production