Fix UnboundLocalError: calculate monthly statistics from budgets when data variable doesn't exist

app/smart_recommendation.py

@@ -416,9 +416,90 @@ class SmartBudgetRecommender:
             std_dev = avg_expense * 0.05  # Assume 5% typical variation for new budgets
             months_analyzed = 1  # Only one month of data (the provided budget_amount)
         else:
-            monthly_values = data.get("monthly_values", [avg_expense])
-            std_dev = data.get("std_dev", 0.0)
-            months_analyzed = data.get("months_analyzed", 1)
+            # We have historical budget data - calculate statistics from budgets
+            # Try to get monthly values from budgets by analyzing dates
+            monthly_values = []
+            try:
+                # Get budgets again to calculate monthly statistics
+                try:
+                    category_objid = ObjectId(category_id) if len(category_id) == 24 and all(c in '0123456789abcdefABCDEF' for c in category_id) else category_id
+                except (ValueError, TypeError):
+                    category_objid = category_id
+                
+                user_query = {
+                    "$or": [
+                        {"createdBy": ObjectId(user_id) if len(user_id) == 24 and all(c in '0123456789abcdefABCDEF' for c in user_id) else user_id},
+                        {"createdBy": user_id},
+                        {"user_id": ObjectId(user_id) if len(user_id) == 24 and all(c in '0123456789abcdefABCDEF' for c in user_id) else user_id},
+                        {"user_id": user_id}
+                    ]
+                }
+                
+                category_query = {
+                    "$or": [
+                        {"category": category_objid},
+                        {"categoryId": category_objid},
+                        {"headCategory": category_objid},
+                        {"headCategories.headCategory": category_objid},
+                        {"headCategories.categories.category": category_objid}
+                    ]
+                }
+                
+                budget_query = {"$and": [user_query, category_query]}
+                budgets = list(self.db.budgets.find(budget_query).sort("createdAt", -1).limit(12))
+                
+                # Group by month and calculate monthly totals
+                monthly_totals = defaultdict(float)
+                monthly_counts = defaultdict(int)
+                
+                for budget in budgets:
+                    try:
+                        # Get date from budget
+                        budget_date = budget.get("createdAt") or budget.get("date") or budget.get("startDate")
+                        if budget_date:
+                            if isinstance(budget_date, str):
+                                budget_date = datetime.fromisoformat(budget_date.replace('Z', '+00:00'))
+                            elif not isinstance(budget_date, datetime):
+                                continue
+                            
+                            month_key = f"{budget_date.year}-{budget_date.month:02d}"
+                            
+                            max_amount = float(budget.get("maxAmount", 0) or budget.get("max_amount", 0) or budget.get("amount", 0) or 0)
+                            spend_amount = float(budget.get("spendAmount", 0) or budget.get("spend_amount", 0) or budget.get("spent", 0) or 0)
+                            budget_amount_val = float(budget.get("budget", 0) or budget.get("budgetAmount", 0) or 0)
+                            
+                            base_amount = spend_amount if spend_amount > 0 else (max_amount if max_amount > 0 else budget_amount_val)
+                            if base_amount > 0:
+                                monthly_totals[month_key] += base_amount
+                                monthly_counts[month_key] += 1
+                    except (ValueError, TypeError, AttributeError):
+                        continue
+                
+                # Convert to monthly values list
+                if monthly_totals:
+                    # Sort by month key and calculate averages
+                    sorted_months = sorted(monthly_totals.keys())
+                    monthly_values = [monthly_totals[month] / monthly_counts[month] for month in sorted_months]
+                    months_analyzed = len(monthly_values)
+                    
+                    # Calculate std_dev
+                    if len(monthly_values) > 1:
+                        mean = sum(monthly_values) / len(monthly_values)
+                        variance = sum((x - mean) ** 2 for x in monthly_values) / len(monthly_values)
+                        std_dev = variance ** 0.5
+                    else:
+                        std_dev = avg_expense * 0.05  # Default 5% variation
+                else:
+                    # Fallback: use avg_expense as single data point
+                    monthly_values = [avg_expense]
+                    std_dev = avg_expense * 0.05
+                    months_analyzed = 1
+            except Exception as e:
+                print(f"Error calculating monthly statistics: {e}")
+                # Fallback: use avg_expense as single data point
+                monthly_values = [avg_expense]
+                std_dev = avg_expense * 0.05
+                months_analyzed = 1
         
         data = {
             "average_monthly": avg_expense,