feat: implement unified configuration loading and logging setup across entry points

train.py

@@ -1,26 +1,43 @@
 #!.venv/bin/python3
 import argparse
+import sys
 
-from core.config import setup_logging, get_config
+from core.config import setup_config_and_logging
 from research.model_trainer import ModelTrainer
 
 
 def main():
-    setup_logging(get_config())
     parser = argparse.ArgumentParser(description="Train DRC Names Models")
+    parser.add_argument("--config", type=str, help="Path to configuration file")
+    parser.add_argument(
+        "--env", type=str, default="development",
+        help="Environment name (default: development)"
+    )
     parser.add_argument("--type", type=str, help="Specific model type to train")
     parser.add_argument("--name", type=str, help="Model name")
 
     args = parser.parse_args()
-    trainer = ModelTrainer()
 
-    # Train specific model
-    trainer.train_single_model(
-        model_name=args.name,
-        model_type=args.type,
-        features=["full_name"]
-    )
+    try:
+        # Load configuration and setup logging
+        config = setup_config_and_logging(config_path=args.config, env=args.env)
+
+        trainer = ModelTrainer()
+
+        # Train specific model
+        trainer.train_single_model(
+            model_name=args.name,
+            model_type=args.type,
+            features=["full_name"]
+        )
+
+        return 0
+
+    except Exception as e:
+        print(f"Training failed: {e}")
+        return 1
 
 
 if __name__ == "__main__":
-    main()
+    exit_code = main()
+    sys.exit(exit_code)