SIENTIAPDE-1712

Update Gates and FormatAndExportPrediction classes to use 'last_timestamp' for improved data handling

- Modified the Gates class to utilize 'last_timestamp' when only one row is present, ensuring accurate timestamp assignment.
- Updated the FormatAndExportPrediction class to replace 'timestamp' with 'last_timestamp' in the output data structure.

laborious/activities/gates.py

@@ -514,6 +514,8 @@ class Gates(MinioManager):
         and ensures data consistency before persistence. The method supports
         multiple storage policies for flexible data retention strategies.
 
+        If only one row is present, we use the last timestamp as the timestamp
+
         Storage Policies:
         - 'lts:N': Latest timestamp - retains N most recent predictions
         - 'erl:N': Earliest timestamp - retains N oldest predictions
@@ -521,7 +523,7 @@ class Gates(MinioManager):
         Args:
             input_data (dict): Input data containing:
                 - data (dict[str, Any]): Raw prediction data to format
-                - timestamp (str): Default timestamp if data lacks timestamp column
+                - last_timestamp (str): Last timestamp of the data
                 - model_id (str): Unique identifier for the ML model
                 - prediction_confidence (float): Confidence score for the prediction
                 - prediction_store_policy (str): Storage policy in format 'type:value'
@@ -530,6 +532,7 @@ class Gates(MinioManager):
             dict: Formatted prediction data ready for storage and export
         """
         metadata = input_data['metadata']
+        last_timestamp = input_data['last_timestamp']
         prediction_store_policy = input_data['prediction_store_policy']
         self.info('Formatting prediction...', metadata)
 
@@ -564,7 +567,11 @@ class Gates(MinioManager):
             self.error(f'Invalid policy type: {policy_type}, using default policy', metadata)
             raise ValueError(f'Invalid policy type: {policy_type}')
 
-        data = data.head(int(policy_value))
+        int_policy_value = int(policy_value)
+
+        data = data.head(int_policy_value)
+        if int_policy_value == 1:
+            data['timestamp'] = last_timestamp
 
         data['model_id'] = input_data['model_id']
         data['prediction_confidence'] = input_data['prediction_confidence']