SIENTIAPDE-1325

Enhance metrics handling in Gates and MLFlow classes

- Added checks for `None` response times before emitting OPC writing metrics in the Gates class to prevent unnecessary metric emissions.
- Updated the MLFlow class to conditionally sort and drop duplicates based on the presence of the 'created_at' column, ensuring robustness in data processing.
- Adjusted corresponding tests to validate the new behavior in both classes.

laborious/activities/mlflow.py

@@ -312,9 +312,12 @@ class MLFlow(SientiaMonitoring):
         self.debug(f'Timestamp: {timestamp}', metadata)
 
         # Sort by created_at in descending order and keep first occurrence of each variable/timestamp pair
-        data = data.sort_values('created_at', ascending=False).drop_duplicates(
-            subset=['variable', 'timestamp'], keep='first'
-        )
+        if 'created_at' in data.columns:
+            data = data.sort_values('created_at', ascending=False).drop_duplicates(
+                subset=['variable', 'timestamp'], keep='first'
+            )
+        else:
+            data = data.drop_duplicates(subset=['variable', 'timestamp'], keep='first')
 
         data.drop(columns=['model_id'], inplace=True, errors='ignore')
         data.drop(columns=['created_at'], inplace=True, errors='ignore')