Update app.py

app.py

@@ -4,10 +4,19 @@ import json
 import plotly
 
 def predict_fraud(selected_model, selected_interpretability_method, step, transaction_type, amount, oldbalanceOrg):
-    # Validation check for all fields
-    
-    if not all([selected_model, selected_interpretability_method, step, transaction_type, amount, oldbalanceOrg]):
-        return "All fields are required. Please ensure no fields are left empty."
+    # Validation checks
+    if not selected_model:
+        return "Model Selection is required.", None, None, None, None, None, None, None, None, None, None
+    if not selected_interpretability_method:
+        return "Interpretability Technique is required.", None, None, None, None, None, None, None, None, None, None
+    if step == 0:  # Assuming step is a numerical value, check for None explicitly
+        return "Step (Transaction Time) is required.", None, None, None, None, None, None, None, None, None, None
+    if not transaction_type:
+        return "Transaction Type is required.", None, None, None, None, None, None, None, None, None, None
+    if amount == 0:  # Assuming amount is a numerical value, check for None explicitly
+        return "Transaction Amount is required.", None, None, None, None, None, None, None, None, None, None
+    if oldbalanceOrg is None:  # Assuming oldbalanceOrg is a numerical value, check for None explicitly
+         return "Old Balance Org is required.", None, None, None, None, None, None, None, None, None, None
 
     url = "https://sea-lion-app-5kxay.ondigitalocean.app/predict_and_explain"
     data = {
@@ -63,6 +72,7 @@ def predict_fraud(selected_model, selected_interpretability_method, step, transa
 with gr.Blocks() as app:
     gr.Markdown("<h2 style='text-align: center; font-weight: bold;'>FraudSenseXAI - Advanced Fraud Detection</h2>")
     gr.Markdown("<p style='text-align: center;'>Predict and analyze fraudulent transactions.</p>", elem_id="description")
+    error_message = gr.Textbox(label="Error Message", visible=False, lines=2, interactive=False)
     
     
     with gr.Row():
@@ -102,6 +112,17 @@ with gr.Blocks() as app:
             bar_chart = gr.Plot(label="Bar Chart")
             narrative = gr.Textbox(label="Narrative")
 
+            
+    def update_error_message(error_text, *rest):
+        if error_text and not error_text.startswith("Error: "):
+            error_message.update(value=error_text, visible=True)
+            return (None,) * len(rest)  # Update to match the number of outputs minus the error message
+        else:
+            error_message.update(visible=False)
+            return (error_text,) + rest
+
+
+    
     submit_btn.click(
         predict_fraud,
         inputs=[model_selection, interpretability_selection, step, transaction_type, transaction_amount, old_balance_org],