SIENTIAPDE-1222

Enhance MLFlow data handling by adding timestamp column and improving debug logging

- Added a 'timestamp' column to the input data, converting the index to a datetime format for better tracking of predictions.
- Improved debug logging to provide clearer context by including the input data preview in the log output.

laborious/activities/mlflow.py

@@ -169,11 +169,15 @@ class MLFlow(BaseActivity):
         model_name = input_data['model_name']
         model_config = input_data.get('model_config', {})
 
-        self.debug(data.head(5).to_string(), metadata)
+        self.debug(f"Input data for: \n {data.head(5).to_string()}", metadata)
 
         # Convert numpy.nan to None for model compatibility
         data.replace(np.nan, None, inplace=True)
 
+        data['timestamp'] = data.index
+        data['timestamp'] = to_datetime(
+            data['timestamp'], format=DATETIME_FORMAT_WITH_TZ).dt.strftime(DATETIME_FORMAT)
+
         # Request prediction from MLFlow model
         response_data = self.model_monitoring_repository.predict(
             model_name, data, model_config, metadata