SIENTIAPDE-1222

Enhance debug logging in MLFlowRepository to improve data traceability

- Added a debug logging statement to capture received data for model prediction, improving visibility into input data.
- Changed an existing info logging statement to debug level for consistency, ensuring all relevant data is logged at the appropriate level.

laborious/utils/repository/model_repository.py

@@ -84,6 +84,9 @@ class MLFlowRepository():
 
             input_index = data.index
             start_time = datetime.now()
+
+            self.logger.debug(
+                f"Data received for model prediction: {data.to_string()}")
             data = self.model_serving.get_cached_predict(
                 model_name, data, model_retention, flavor,
                 compressed, retention_target
@@ -91,7 +94,7 @@ class MLFlowRepository():
 
             end_time = datetime.now()
             data = pd.DataFrame(data, columns=['prediction'])
-            self.logger.info(
+            self.logger.debug(
                 f"Data received from model prediction: {data.to_string()}")
             data.index = input_index
             data['response_time'] = (end_time - start_time).total_seconds()