"""
Main execution file for AIOps pipeline
"""
import logging
from src.logger import setup_logging

# Setup logging
setup_logging()
logger = logging.getLogger(__name__)

def main():
    """Main pipeline function"""
    logger.info("Starting AIOps pipeline...")
    
    try:
        # Import and execute pipeline components
        from src.data_ingestion import DataIngestion
        from src.data_preprocessing import DataPreprocessor
        from src.model_builder import ModelBuilder
        from src.model_evaluator import ModelEvaluator
        
        logger.info("Pipeline components imported successfully")
        
        # Example workflow (users will modify this)
        logger.info("1. Data ingestion...")
        # ingestion = DataIngestion()
        # data = ingestion.load_data()
        
        logger.info("2. Data preprocessing...")
        # preprocessor = DataPreprocessor()
        # processed_data = preprocessor.transform(data)
        
        logger.info("3. Model building...")
        # model = ModelBuilder()
        # trained_model = model.train(processed_data)
        
        logger.info("4. Model evaluation...")
        # evaluator = ModelEvaluator()
        # metrics = evaluator.evaluate(trained_model, test_data)
        
        logger.info("Pipeline execution completed")
        
    except Exception as e:
        logger.error(f"Pipeline execution failed: {e}")
        raise

if __name__ == "__main__":
    main()