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name: logging-patterns description: Use when adding logging to features - structured logging with LoggerService categories

Logging Patterns

Use this skill when implementing features that need logging or debugging.

Checklist

Setup Logger

• Import LoggerService: from app.services import logger_service
• Get logger with category: logger = logger_service.get_logger(__name__, category='[Category]')
• Verify category matches feature domain (see categories below)

Select Appropriate Category

Choose the category that matches your feature domain:

• [ModelLoad] - Model loading operations
• [Download] - Download operations
• [Generate] - Image generation
• [API] - API endpoints
• [Database] - Database operations
• [Service] - Service layer operations
• [Socket] - WebSocket events
• [GPU] - GPU operations

Use Appropriate Log Level

• .debug() - Detailed diagnostic information (only visible with LOG_LEVEL=DEBUG)
• .info() - General informational messages (progress, status updates)
• .warning() - Warning messages (degraded functionality, deprecated usage)
• .error() - Error messages (failures that don't stop execution)
• .exception() - Exceptions with full stack traces (use in except blocks)

Example Usage

Copyfrom app.services import logger_service

logger = logger_service.get_logger(__name__, category='ModelLoad')

def load_model(model_path: str):
    logger.info(f'Loading model from {model_path}')
    try:
        # ... model loading logic
        logger.debug('Model loaded successfully')
    except FileNotFoundError as error:
        logger.error(f'Model file not found: {error}')
        raise

Configuration

• Test with debug logging: LOG_LEVEL=DEBUG uv run python main.py
• Verify logs appear with correct category prefix in output

Reference

See app/services/logger.py for LoggerService implementation.