Update app.py

app.py

@@ -18,10 +18,28 @@ def safe_get(data: Dict, key: str, default: Any = None) -> Any:
 def normalize_recommendation_data(data: Dict) -> Dict:
     """
     Normalize API response to ensure all required fields exist.
-    Handles both orchestrator format and direct API format.
+    Handles both orchestrator format and mock data format.
     """
     
-    # Handle case where recommended_card is a dict (orchestrator format)
+    # Check if this is mock data (simpler format)
+    if data.get('mock_data'):
+        # Mock data has simpler structure
+        return {
+            'recommended_card': safe_get(data, 'recommended_card', 'Unknown Card'),
+            'rewards_earned': float(safe_get(data, 'rewards_earned', 0)),
+            'rewards_rate': safe_get(data, 'rewards_rate', 'N/A'),
+            'merchant': safe_get(data, 'merchant', 'Unknown Merchant'),
+            'category': safe_get(data, 'category', 'Unknown'),
+            'amount': float(safe_get(data, 'amount', 0)),
+            'annual_potential': float(safe_get(data, 'annual_potential', 0)),
+            'optimization_score': int(safe_get(data, 'optimization_score', 85)),
+            'reasoning': safe_get(data, 'reasoning', 'Optimal choice'),
+            'warnings': safe_get(data, 'warnings', []),
+            'alternatives': safe_get(data, 'alternatives', []),
+            'mock_data': True
+        }
+    
+    # Handle orchestrator format (recommended_card is a dict)
     recommended_card = safe_get(data, 'recommended_card', {})
     if isinstance(recommended_card, dict):
         card_name = safe_get(recommended_card, 'card_name', 'Unknown Card')
@@ -205,25 +223,23 @@ def get_recommendation_with_ai(user_id, merchant, category, amount):
         return "❌ Please enter a valid amount greater than $0.", None
     
     try:
-        # Map category to MCC
-        mcc = MCC_CATEGORIES.get(category, "5999")
-        
         # Get base recommendation from orchestrator
-        # NEW:
+        # Note: Your API client expects (user_id, merchant, category, amount, mcc)
         result = client.get_recommendation(
             user_id=user_id,
             merchant=merchant,
-            mcc=mcc,
-            amount_usd=float(amount)
+            category=category,
+            amount=float(amount),
+            mcc=None  # Let the client map category to MCC
         )
         
         # Check for errors
-        if result.get('error'):
+        if not result.get('success'):
             error_msg = result.get('error', 'Unknown error')
             return f"❌ Error: {error_msg}", None
         
         # Normalize the data to ensure all fields exist
-        data = normalize_recommendation_data(result)
+        data = normalize_recommendation_data(result.get('data', {}))
         
         # Generate LLM explanation if enabled
         ai_explanation = ""
@@ -305,7 +321,7 @@ def get_recommendation_with_ai(user_id, merchant, category, amount):
         error_details = traceback.format_exc()
         print(f"Recommendation error: {error_details}")
         return f"❌ Error: {str(e)}\n\nPlease check your API connection or try again.", None
-
+        
         
 def create_rewards_comparison_chart(data: Dict) -> go.Figure:
     """Create rewards comparison chart with proper error handling"""