Update app.py

app.py

@@ -115,6 +115,11 @@ def normalize_recommendation_data(data: Dict) -> Dict:
     }
     
     return normalized
+
+def create_loading_state():
+    """Create loading indicator message"""
+    return "⏳ **Loading...** Please wait while we fetch your recommendation.", None
+
     
 from datetime import date
 from typing import Optional, Tuple, List, Dict, Any
@@ -222,23 +227,26 @@ def get_recommendation_with_ai(user_id, merchant, category, amount):
     if amount <= 0:
         return "❌ Please enter a valid amount greater than $0.", None
     
+    # Show loading state
+    yield "⏳ **Loading recommendation...** Analyzing your cards and transaction...", None
+    
     try:
         # Get base recommendation from orchestrator
-        # Note: Your API client expects (user_id, merchant, category, amount, mcc)
         result = client.get_recommendation(
             user_id=user_id,
             merchant=merchant,
             category=category,
             amount=float(amount),
-            mcc=None  # Let the client map category to MCC
+            mcc=None
         )
         
         # Check for errors
         if not result.get('success'):
             error_msg = result.get('error', 'Unknown error')
-            return f"❌ Error: {error_msg}", None
+            yield f"❌ Error: {error_msg}", None
+            return
         
-        # Normalize the data to ensure all fields exist
+        # Normalize the data
         data = normalize_recommendation_data(result.get('data', {}))
         
         # Generate LLM explanation if enabled
@@ -260,38 +268,30 @@ def get_recommendation_with_ai(user_id, merchant, category, amount):
                 print(f"LLM explanation failed: {e}")
                 ai_explanation = ""
         
-        # Format output with AI explanation
+        # Format output
         output = f"""
 ## 🎯 Recommendation for ${amount:.2f} at {merchant}
 
 ### 💳 Best Card: **{data['recommended_card']}**
 
 **Rewards Earned:** ${data['rewards_earned']:.2f} ({data['rewards_rate']})
-
 """
         
-        # Add mock data indicator
         if data.get('mock_data'):
             output += """
 > ⚠️ **Demo Mode:** Using sample data. Connect to orchestrator for real recommendations.
-
 """
         
-        # Add AI explanation if available
         if ai_explanation:
             output += f"""
 ### 🤖 AI Insight
-
 {ai_explanation}
 
 ---
-
 """
         
-        # Add detailed breakdown
         output += f"""
 ### 📊 Breakdown
-
 - **Category:** {data['category']}
 - **Merchant:** {data['merchant']}
 - **Reasoning:** {data['reasoning']}
@@ -299,13 +299,11 @@ def get_recommendation_with_ai(user_id, merchant, category, amount):
 - **Optimization Score:** {data['optimization_score']}/100
 """
         
-        # Add warnings
         if data['warnings']:
             output += "\n\n### ⚠️ Important Warnings\n\n"
             for warning in data['warnings']:
                 output += f"- {warning}\n"
         
-        # Add alternatives
         if data['alternatives']:
             output += "\n\n### 🔄 Alternative Options\n\n"
             for alt in data['alternatives']:
@@ -314,14 +312,13 @@ def get_recommendation_with_ai(user_id, merchant, category, amount):
         # Create visualization
         chart = create_rewards_comparison_chart(data)
         
-        return output, chart
+        yield output, chart
         
     except Exception as e:
         import traceback
         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
-        
+        yield 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"""
@@ -839,50 +836,59 @@ Get AI-powered credit card recommendations that maximize your rewards based on:
             )
         
         # ===================== Analytics Update Function (ENHANCED) =====================
-        def update_analytics_with_charts(user_id: str) -> tuple:
+        def update_analytics_with_charts(user_id: str):
             """Fetch and format analytics with charts for selected user"""
             
+            # Show loading state first
+            empty_fig = create_empty_chart("⏳ Loading...")
+            loading_html = """
+            <div style="text-align: center; padding: 40px;">
+                <h2>⏳ Loading Analytics...</h2>
+                <p>Please wait while we fetch your data</p>
+            </div>
+            """
+            
+            yield (
+                loading_html,
+                empty_fig, empty_fig, empty_fig, empty_fig, empty_fig,
+                "⏳ Loading...",
+                "⏳ Loading...",
+                "⏳ Loading...",
+                "*Loading analytics...*"
+            )
+            
             try:
                 # Fetch analytics data from API
                 result = client.get_user_analytics(user_id)
                 
-                # DEBUG: Print what we received
-                print("=" * 60)
-                print(f"DEBUG: Analytics for {user_id}")
-                print(f"Success: {result.get('success')}")
-                print(f"Has data key: {'data' in result}")
-                if result.get('data'):
-                    print(f"Data keys: {result['data'].keys()}")
-                    print(f"Category breakdown length: {len(result['data'].get('category_breakdown', []))}")
-                print("=" * 60)
-                
                 # Check if request was successful
                 if not result.get('success'):
                     error_msg = result.get('error', 'Unknown error')
-                    empty_fig = create_empty_chart(f"Error: {error_msg}")
-                    return (
+                    error_fig = create_empty_chart(f"Error: {error_msg}")
+                    yield (
                         f"<p>❌ Error: {error_msg}</p>",
-                        empty_fig, empty_fig, empty_fig, empty_fig, empty_fig,
+                        error_fig, error_fig, error_fig, error_fig, error_fig,
                         "Error loading data",
                         "Error loading data",
                         "Error loading data",
                         f"*Error: {error_msg}*"
                     )
+                    return
                 
-                # ✅ FIX: Extract the actual data (unwrap from success wrapper)
+                # Extract the actual data
                 analytics_data = result.get('data', {})
                 
-                # Verify we have data
                 if not analytics_data:
-                    empty_fig = create_empty_chart("No analytics data available")
-                    return (
+                    error_fig = create_empty_chart("No analytics data available")
+                    yield (
                         "<p>No data available</p>",
-                        empty_fig, empty_fig, empty_fig, empty_fig, empty_fig,
+                        error_fig, error_fig, error_fig, error_fig, error_fig,
                         "No data",
                         "No data",
                         "No data",
                         "*No data available*"
                     )
+                    return
                 
                 # Import chart functions
                 from utils.formatters import (
@@ -894,10 +900,10 @@ Get AI-powered credit card recommendations that maximize your rewards based on:
                     create_card_performance_chart
                 )
                 
-                # Format text data (pass unwrapped data)
+                # Format text data
                 metrics_html, table_md, insights_md, forecast_md = format_analytics_metrics(analytics_data)
                 
-                # Generate charts (pass unwrapped data)
+                # Generate charts
                 spending_fig = create_spending_chart(analytics_data)
                 pie_fig = create_rewards_pie_chart(analytics_data)
                 gauge_fig = create_optimization_gauge(analytics_data)
@@ -908,17 +914,17 @@ Get AI-powered credit card recommendations that maximize your rewards based on:
                 from datetime import datetime
                 status = f"*Analytics updated for {user_id} at {datetime.now().strftime('%I:%M %p')}*"
                 
-                return (
-                    metrics_html,      # Metric cards
-                    spending_fig,      # Spending bar chart
-                    gauge_fig,         # Optimization gauge
-                    pie_fig,           # Rewards pie chart
-                    performance_fig,   # Card performance chart
-                    trend_fig,         # Trend line chart
-                    table_md,          # Spending table
-                    insights_md,       # Insights text
-                    forecast_md,       # Forecast text
-                    status             # Status message
+                yield (
+                    metrics_html,
+                    spending_fig,
+                    gauge_fig,
+                    pie_fig,
+                    performance_fig,
+                    trend_fig,
+                    table_md,
+                    insights_md,
+                    forecast_md,
+                    status
                 )
                 
             except Exception as e:
@@ -928,18 +934,17 @@ Get AI-powered credit card recommendations that maximize your rewards based on:
                 print(error_msg)
                 print(error_details)
                 
-                # Return empty/error states
-                empty_fig = create_empty_chart("Error loading chart")
+                error_fig = create_empty_chart("Error loading chart")
                 
-                return (
+                yield (
                     f"<p>{error_msg}</p>",
-                    empty_fig, empty_fig, empty_fig, empty_fig, empty_fig,
+                    error_fig, error_fig, error_fig, error_fig, error_fig,
                     "Error loading table",
                     "Error loading insights",
                     "Error loading forecast",
                     f"*{error_msg}*"
                 )
-        
+                
         
         def create_empty_chart(message: str) -> go.Figure:
             """Helper to create empty chart with message"""
@@ -1009,11 +1014,15 @@ Get AI-powered credit card recommendations that maximize your rewards based on:
             )
             
             def respond(message, chat_history, user_id):
-                """Handle chat responses with error handling"""
+                """Handle chat responses with error handling and loading state"""
                 if not message.strip():
                     return "", chat_history
                 
-                # Get user context with error handling
+                # Add loading message
+                loading_history = chat_history + [(message, "⏳ Thinking...")]
+                yield "", loading_history
+                
+                # Get user context
                 user_context = {}
                 try:
                     analytics = client.get_user_analytics(user_id)
@@ -1032,7 +1041,7 @@ Get AI-powered credit card recommendations that maximize your rewards based on:
                         'top_category': 'Groceries'
                     }
                 
-                # Generate AI response with error handling
+                # Generate AI response
                 try:
                     if config.LLM_ENABLED:
                         bot_response = llm.chat_response(message, user_context, chat_history)
@@ -1043,21 +1052,7 @@ Get AI-powered credit card recommendations that maximize your rewards based on:
                     bot_response = f"I encountered an error. Please try asking your question differently."
                 
                 chat_history.append((message, bot_response))
-                return "", chat_history
-            
-            msg.submit(respond, [msg, chatbot, chat_user], [msg, chatbot])
-            send_btn.click(respond, [msg, chatbot, chat_user], [msg, chatbot])
-            
-            # Example questions
-            gr.Examples(
-                examples=[
-                    ["Which card should I use at Costco?"],
-                    ["How can I maximize my grocery rewards?"],
-                    ["What's the best travel card for international trips?"],
-                    ["Am I close to any spending caps?"],
-                ],
-                inputs=[msg]
-            )
+                yield "", chat_history
         # ========== Tab 3: About ==========
         with gr.Tab("ℹ️ About"):
             gr.Markdown(