Change response to show category name and category_id instead of budget_name

app/models.py

@@ -24,7 +24,8 @@ class Budget(BaseModel):
     end_date: Optional[datetime] = None
 
 class BudgetRecommendation(BaseModel):
-    budget_name: str = Field(..., description="Budget name (e.g., Groceries, Transport)")
+    category: str = Field(..., description="Category name (e.g., Groceries, Transport)")
+    category_id: Optional[str] = Field(None, description="Category ID from database")
     average_expense: float
     recommended_budget: float
     reason: str

app/smart_recommendation.py

@@ -48,29 +48,33 @@ class SmartBudgetRecommender:
         
         recommendations: List[BudgetRecommendation] = []
 
-        for category, data in category_data.items():
+        for category_key, data in category_data.items():
+            # Extract category_name and category_id from data
+            category_name = data.get("category_name", category_key.split("|")[0] if "|" in category_key else category_key)
+            category_id = data.get("category_id")
             avg_expense = data["average_monthly"]
             confidence = self._calculate_confidence(data)
 
             # Always try OpenAI first (primary source of recommendation)
-            ai_result = self._get_ai_recommendation(category, data, avg_expense)
+            ai_result = self._get_ai_recommendation(category_name, data, avg_expense)
             if ai_result and ai_result.get("recommended_budget"):
                 recommended_budget = ai_result.get("recommended_budget")
-                reason = ai_result.get("reason", f"AI recommendation for {category}")
+                reason = ai_result.get("reason", f"AI recommendation for {category_name}")
                 action = ai_result.get("action")
-                print(f"✅ OpenAI recommendation for {category}: {recommended_budget} (action: {action})")
+                print(f"✅ OpenAI recommendation for {category_name}: {recommended_budget} (action: {action})")
             else:
                 # Fallback to rule-based recommendation if OpenAI fails
                 recommended_budget = self._calculate_recommended_budget(avg_expense, data)
-                reason = self._generate_reason(category, avg_expense, recommended_budget)
+                reason = self._generate_reason(category_name, avg_expense, recommended_budget)
                 action = None
                 if not ai_result:
-                    print(f"❌ OpenAI unavailable (no API key or error), using rule-based for {category}: {recommended_budget}")
+                    print(f"❌ OpenAI unavailable (no API key or error), using rule-based for {category_name}: {recommended_budget}")
                 else:
-                    print(f"⚠️ OpenAI returned invalid data, using rule-based for {category}: {recommended_budget}")
+                    print(f"⚠️ OpenAI returned invalid data, using rule-based for {category_name}: {recommended_budget}")
 
             recommendations.append(BudgetRecommendation(
-                budget_name=category,
+                category=category_name,
+                category_id=category_id,
                 average_expense=round(avg_expense, 2),
                 recommended_budget=round(recommended_budget or 0, 2),
                 reason=reason,
@@ -521,9 +525,15 @@ class SmartBudgetRecommender:
                 base_amount = 0
 
             # Only add budget if it has an amount - use category name as key
+            # Store both category_name and category_id in the result
             if base_amount > 0:
-                if category_name not in result:
-                    result[category_name] = {
+                # Use a unique key that includes category_id to handle multiple budgets with same category name
+                result_key = f"{category_name}|{category_id}" if category_id else category_name
+                
+                if result_key not in result:
+                    result[result_key] = {
+                        "category_name": category_name,
+                        "category_id": str(category_id) if category_id else None,
                         "average_monthly": base_amount,
                         "total": base_amount,
                         "count": 1,
@@ -532,15 +542,17 @@ class SmartBudgetRecommender:
                         "monthly_values": [base_amount],
                     }
                 else:
-                    result[category_name]["total"] += base_amount
-                    result[category_name]["count"] += 1
-                    result[category_name]["months_analyzed"] = result[category_name]["count"]
-                    result[category_name]["average_monthly"] = (
-                        result[category_name]["total"] / result[category_name]["count"]
+                    result[result_key]["total"] += base_amount
+                    result[result_key]["count"] += 1
+                    result[result_key]["months_analyzed"] = result[result_key]["count"]
+                    result[result_key]["average_monthly"] = (
+                        result[result_key]["total"] / result[result_key]["count"]
                     )
-                    result[category_name]["monthly_values"].append(base_amount)
+                    result[result_key]["monthly_values"].append(base_amount)
 
-        print(f"✅ Processed {len(result)} budget categories for recommendations: {list(result.keys())}")
+        # Extract category names for logging
+        category_names = [data.get("category_name", key.split("|")[0] if "|" in key else key) for key, data in result.items()]
+        print(f"✅ Processed {len(result)} budget categories for recommendations: {category_names}")
         return result
 
     def _get_ai_recommendation(self, category: str, data: Dict, avg_expense: float):