Update model_inference/model_inference.py

model_inference/model_inference.py

@@ -1,15 +1,14 @@
 # from utils.load_model import load_model
 from feature_construction.feature_construction import FeatureConstructor
 import pandas as pd
-from logger.logger import MongoLogger
+import logging
 
 
 def predict(loaded_model, x: pd.DataFrame, predict_proba: bool = True,
             use_deployed_model: bool = True, model_file_name: str = None, predict_label: bool = False):
     prediction = None
-    logger = MongoLogger()
     try:
-        logger.log_to_db(level="INFO", message="entering model_inference.predict")
+        logging.warning("entering model_inference.predict")
         # loaded_model = load_model(load_deployed_model=use_deployed_model, model_file_name=model_file_name)
 
         if loaded_model is not None:
@@ -70,8 +69,8 @@ def predict(loaded_model, x: pd.DataFrame, predict_proba: bool = True,
                     prediction = label_encoder.inverse_transform(prediction)
 
     except Exception as e:
-        logger.log_to_db(level="CRITICAL", message=f"unexpected model_inference.predict error: {e}")
+        logging.warning(f"unexpected model_inference.predict error: {e}")
         raise
-    logger.log_to_db(level="INFO", message="exiting model_inference.predict")
+    logging.warning("exiting model_inference.predict")
 
     return prediction