Update app.py

app.py

@@ -55,8 +55,14 @@ best_model = tuner.get_best_models(1)[0]
 
 # Define prediction function for Gradio
 def predict_performance(hours, prev_score, sleep, papers, activity):
-    X_user = [[hours, prev_score, sleep, papers, activity]]
-    X_user = preprocess.transform(X_user)
+    user_input = pd.DataFrame([{
+        'Hours Studied': hours,
+        'Previous Scores': prev_score,
+        'Sleep Hours': sleep,
+        'Sample Question Papers Practiced': papers,
+        'Extracurricular Activities': activity
+    }])
+    X_user = preprocess.transform(user_input)
     pred = best_model.predict(X_user).item()
     return f"📊 Predicted Performance Index: {pred:.2f}"