adjustment

app/utils.py

@@ -1025,24 +1025,24 @@ def get_user_life_status(user_id):
         # Sum points_added, group by area
         temp_df = pd.DataFrame(filtered_data)
         grouped_points = temp_df.groupby("area")["points_added"].sum()
-
+        
         # Debug: Check the grouped points result
         logger.info(f"Grouped Points: {grouped_points}", extra={'user_id': user_id, 'endpoint': function_name})
 
         # Structure the output safely
         thirtydays_life_score = {
-            "overall": sum([
+            "overall": int(sum([
                 grouped_points.get("personal_growth", 0),
                 grouped_points.get("career_growth", 0),
                 grouped_points.get("health_and_wellness", 0),
                 grouped_points.get("mental_well_being", 0),
                 grouped_points.get("relationship", 0),
-            ]),
-            "personal_growth": grouped_points.get("personal_growth", 0),
-            "health_and_wellness": grouped_points.get("health_and_wellness", 0),
-            "mental_well_being": grouped_points.get("mental_well_being", 0),
-            "career_growth": grouped_points.get("career_growth", 0),
-            "relationship": grouped_points.get("relationship", 0)
+            ])),
+            "personal_growth": int(grouped_points.get("personal_growth", 0)),
+            "health_and_wellness": int(grouped_points.get("health_and_wellness", 0)),
+            "mental_well_being": int(grouped_points.get("mental_well_being", 0)),
+            "career_growth": int(grouped_points.get("career_growth", 0)),
+            "relationship": int(grouped_points.get("relationship", 0))
         }
 
         # Debug: Check the final structured result