Update app.py

app.py

@@ -360,10 +360,11 @@ with gr.Blocks(
         text-align: center;
         margin-bottom: 2rem;
         padding: 2rem;
-        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+        background: linear-gradient(135deg, #1e3c72 0%, #2a5298 100%);
         border-radius: 15px;
         color: white;
         margin-bottom: 30px;
+        box-shadow: 0 8px 32px rgba(0,0,0,0.2);
     }
     .tab-nav {
         margin-bottom: 20px;
@@ -373,10 +374,10 @@ with gr.Blocks(
     
     gr.HTML("""
     <div class="main-header">
-        <h1 style="font-size: 2.5rem; margin-bottom: 15px; text-shadow: 2px 2px 4px rgba(0,0,0,0.3);">
+        <h1 style="font-size: 2.5rem; margin-bottom: 15px; text-shadow: 2px 2px 4px rgba(0,0,0,0.5); color: white; font-weight: bold;">
             🏢 SAP Account Receivable ML Prediction Demo
         </h1>
-        <p style="font-size: 1.2rem; opacity: 0.95; margin: 0;">
+        <p style="font-size: 1.2rem; color: rgba(255,255,255,0.9); margin: 0; text-shadow: 1px 1px 2px rgba(0,0,0,0.3);">
             Machine Learning-powered invoice payment prediction system using TensorFlow
         </p>
     </div>
@@ -433,17 +434,16 @@ with gr.Blocks(
             
             prediction_status = gr.HTML()
             
-            with gr.Row():
-                with gr.Column(scale=2):
-                    predictions_df = gr.Dataframe(
-                        label="📋 Invoice Predictions",
-                        interactive=False,
-                        wrap=True,
-  #                      height=400
-                    )
+            # Changed layout to stack vertically instead of side by side
+            with gr.Column():
+                predictions_df = gr.Dataframe(
+                    label="📋 Invoice Predictions",
+                    interactive=False,
+                    wrap=True,
+                    height=400
+                )
                 
-                with gr.Column(scale=1):
-                    probability_plot = gr.Plot(label="📊 Probability Distribution")
+                probability_plot = gr.Plot(label="📊 Probability Distribution")
     
     # Event handlers
     train_btn.click(