Adjust life status endpoint, pre-GG report adjustment, and migrate user adjustment

app/main.py

@@ -491,6 +491,23 @@ async def migrate_user(
         user.done_first_reflection = old_user_object.done_first_reflection
         user.client = client
         user.conversations.client = client
+        if hasattr(old_user_object, "goal"): setattr(user, "goal", old_user_object.goal)
+        if hasattr(old_user_object, "last_gg_session"): setattr(user, "last_gg_session", old_user_object.last_gg_session)
+        if hasattr(old_user_object, "micro_actions"): setattr(user, "micro_actions", old_user_object.micro_actions)
+        if hasattr(old_user_object, "recommended_micro_actions"): setattr(user, "recommended_micro_actions", old_user_object.recommended_micro_actions)
+        if hasattr(old_user_object, "challenges"): setattr(user, "challenges", old_user_object.challenges)
+        if hasattr(old_user_object, "other_focusses"): setattr(user, "other_focusses", old_user_object.other_focusses)
+        if hasattr(old_user_object, "personal_growth_score"): setattr(user, "personal_growth_score", old_user_object.personal_growth_score)
+        if hasattr(old_user_object, "career_growth_score"): setattr(user, "career_growth_score", old_user_object.career_growth_score)
+        if hasattr(old_user_object, "relationship_score"): setattr(user, "relationship_score", old_user_object.relationship_score)
+        if hasattr(old_user_object, "mental_well_being_score"): setattr(user, "mental_well_being_score", old_user_object.mental_well_being_score)
+        if hasattr(old_user_object, "health_and_wellness_score"): setattr(user, "health_and_wellness_score", old_user_object.health_and_wellness_score)
+        if hasattr(old_user_object, "reminders"): setattr(user, "reminders", old_user_object.reminders)
+        if hasattr(old_user_object, "recent_wins"): setattr(user, "recent_wins", old_user_object.recent_wins)
+        if hasattr(old_user_object, "recommended_gg_topics"): setattr(user, "recommended_gg_topics", old_user_object.recommended_gg_topics)
+        if hasattr(old_user_object, "growth_plan"): setattr(user, "growth_plan", old_user_object.growth_plan)
+        if hasattr(old_user_object, "user_interaction_guidelines"): setattr(user, "user_interaction_guidelines", old_user_object.user_interaction_guidelines)
+        if hasattr(old_user_object, "score_history"): setattr(user, "score_history", old_user_object.score_history)
 
         api_response = {
             "user": user.user_info,
@@ -504,7 +521,13 @@ async def migrate_user(
             "challenges": user.challenges,
             "other_focusses": user.other_focusses,
             "scores": f"Personal Growth: {user.personal_growth_score} || Career: {user.career_growth_score} || Health/Wellness: {user.health_and_wellness_score} || Relationships: {user.relationship_score} || Mental Health: {user.mental_well_being_score}",
-            "recent_wins": user.recent_wins
+            "recent_wins": user.recent_wins,
+            "last_gg_session": user.last_gg_session,
+            "reminders": user.reminders,
+            "recommended_gg_topics": user.recommended_gg_topics,
+            "growth_plan": user.growth_plan,
+            "user_interaction_guidelines": user.user_interaction_guidelines,
+            "score_history": user.score_history
         }
 
         add_to_cache(user)

app/user.py

@@ -117,6 +117,8 @@ class User:
         self.user_interaction_guidelines = self.generate_user_interaction_guidelines(user_info, client)
         self.conversations = ConversationManager(client, self, asst_id)
 
+        self.score_history = []
+
     @catch_error
     def extend_growth_plan(self):
         # Change current growth plan to 14d growth plan
@@ -267,6 +269,14 @@ class User:
         elif variable == 'Relationship':
             self.relationship_score += points_added
             logger.info(f"Added {points_added} points to Relationship for {notes}", extra={"user_id": self.user_id, "endpoint": "add_life_score_point"})
+        # Add historical data (append) to score_history
+        historical_entry = {
+            "area": variable,
+            "points_added": points_added,
+            "notes": notes,
+            "created_at": pd.Timestamp.now()
+        }
+        self.score_history.append(historical_entry)
     
     @catch_error
     def get_current_goal(self, full=False):

app/utils.py

@@ -371,6 +371,9 @@ def get_user_summary(user_id):
 
     3. **30-Minute Coaching Session Script**: A detailed, partitioned script to help the coach prepare for the session, including dialogue, questions, and guidance tailored to the client's needs, covering the five key areas. The script should be partitioned into several sections in the JSON output, similar to the structure provided for the Pre-Growth Guide Session Report.
 
+    ---
+    **Important Note**
+    The **chat history** shows the most updated information. Hence, if there is a difference between the goal/challenge/other key information in the user's chat history and the user's profile, you must create the reports based on the chat history!
     ---
 
     **Instructions:**
@@ -600,12 +603,19 @@ def get_user_summary(user_id):
     # Combine user information and chat history for context
     user_context = f"""
     Based on the following user profile and chat history, generate the required reports.
-
-    ### USER PROFILE ###
-    {user_info}
+    
+    **Important Note**
+    The **chat history** shows the most updated information. Hence, if there is a difference between the goal/challenge/other key information in the user's chat history and the user's profile, you must create the reports based on the chat history!
 
     ### CHAT HISTORY ###
     {chat_history}
+
+    ### USER GOAL ###
+    {user_goal}
+    
+    ### USER PROFILE ###
+    {user_info}
+    
     """
 
     # Step 3: Call the OpenAI API using the specified function
@@ -975,16 +985,69 @@ def get_user_life_status(user_id):
 
     # Get response and convert into dictionary
     mantra = json.loads(response.choices[0].message.content)["mantra_of_the_week"]
+    
+    cumulative_life_score = {
+            "overall": user.personal_growth_score + user.career_growth_score + user.relationship_score + user.mental_well_being_score + user.health_and_wellness_score,
+            "personal_growth": user.personal_growth_score,
+            "health_and_wellness": user.health_and_wellness_score,
+            "mental_well_being": user.mental_well_being_score,
+            "career_growth": user.career_growth_score,
+            "relationship": user.relationship_score
+    }
+
+    logger.info(f"{user.score_history}",extra={'user_id': user_id, 'endpoint': function_name})
 
     # Get current life score
-    life_score = {
-        "overall": user.personal_growth_score + user.career_growth_score + user.relationship_score + user.mental_well_being_score + user.health_and_wellness_score,
-        "personal_growth": user.personal_growth_score,
-        "health_and_wellness": user.health_and_wellness_score,
-        "mental_well_being": user.mental_well_being_score,
-        "career_growth": user.career_growth_score,
-        "relationship": user.relationship_score
-    }
+    if len(user.score_history) == 0:
+        thirtydays_life_score = cumulative_life_score
+    else:
+        # Calculate previous 30 days date
+        now = pd.Timestamp.now()
+        thirty_days_ago = now - pd.Timedelta(days=30)
+
+        # Filter the data
+        filtered_data = [entry for entry in user.score_history if thirty_days_ago <= entry["created_at"] <= now]
+        logger.info(f"Filtered Data: {filtered_data}", extra={'user_id': user_id, 'endpoint': function_name})
+
+        # Normalize area names to match expected keys
+        area_mapping = {
+            "Personal Growth": "personal_growth",
+            "Health and Wellness": "health_and_wellness",
+            "Mental Well-being": "mental_well_being",
+            "Career Growth": "career_growth",
+            "Relationship": "relationship"
+        }
+
+        # Normalize area names in filtered data
+        for entry in filtered_data:
+            entry["area"] = area_mapping.get(entry["area"], entry["area"])
+
+        # 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": 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": 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
+        logger.info(f"Final Thirty Days Life Score: {thirtydays_life_score}", extra={'user_id': user_id, 'endpoint': function_name})
+
     # Get current goal
     current_goal = '' if not user.goal else user.goal[-1].content
     # Get life score achievements in list
@@ -992,14 +1055,15 @@ def get_user_life_status(user_id):
     # Combine everything
 
     reports = {
-        "life_score": life_score,
+        "life_score": thirtydays_life_score,
+        "cumulative_life_score": cumulative_life_score,
         "mantra_of_the_week": mantra,
         "goal": current_goal,
         "recent_wins": recent_wins
     }
 
     # Step 4: Return the JSON reports
-    logger.info(f"User life status generated successfully for user {user_id}", extra={'user_id': user_id, 'endpoint': function_name})
+    logger.info(f"User life status generated successfully for user {user_id}: {reports}", extra={'user_id': user_id, 'endpoint': function_name})
     return reports
 
 async def get_api_key(api_key_header: str = Security(api_key_header)) -> str: