Update app.py

app.py

@@ -6,10 +6,8 @@ import joblib
 model = joblib.load("model.joblib")
 
 def predict_excel(file):
-    # Read uploaded Excel file
     df = pd.read_excel(file.name)
 
-    # Check if required columns exist
     required_cols = [
         "CustomerID", "Tenure", "PreferredLoginDevice", "CityTier",
         "WarehouseToHome", "PreferredPaymentMode", "Gender", "HourSpendOnApp",
@@ -21,27 +19,28 @@ def predict_excel(file):
 
     missing = [c for c in required_cols if c not in df.columns]
     if missing:
-        return f"❌ Missing columns in Excel: {missing}"
+        return None, f"❌ Missing columns in Excel: {missing}"
 
-    # Predict
     preds = model.predict(df[required_cols])
-
-    # Add prediction column
     df["Prediction"] = preds
 
-    # Save to new Excel file
     out_path = "predicted_output.xlsx"
     df.to_excel(out_path, index=False)
 
-    return out_path  # Gradio will let user download it
+    return out_path, "✅ Successfully generated predictions!"
+
 
 # Gradio UI
 demo = gr.Interface(
     fn=predict_excel,
     inputs=gr.File(label="Upload Excel File (.xlsx)"),
-    outputs=gr.File(label="Download Updated Excel With Predictions"),
+    outputs=[
+        gr.File(label="Download Updated Excel With Predictions"),
+        gr.Text(label="Status Message")
+    ],
     title="Excel-Based Customer Churn Predictor",
     description="Upload an Excel file to receive a new Excel file with model predictions added."
 )
 
+
 demo.launch()