Update app.py

app.py

@@ -1,4 +1,4 @@
-import gradio as gr
+mport gradio as gr
 import joblib
 import numpy as np
 import pandas as pd
@@ -76,6 +76,12 @@ def predict_performance(Location, Course, Faculty, College, Source, Event, Prese
     print("\nDataFrame after encoding:")
     print(df)
     
+    # Ensure the DataFrame columns match the order used during scaler fitting
+    expected_columns = ["Location", "Course", "Faculty", "College", "Source", "Event", 
+                        "Presenter", "Visited Parent", "Visited College for Inquiry", 
+                        "Attended Any Event", "College Fee", "GPA", "Year"]
+    df = df[expected_columns]
+    
     # Scale input data using the loaded scaler
     scaled_input = scaler.transform(df)
     
@@ -110,6 +116,7 @@ iface = gr.Interface(
         gr.Radio(["Ram", "Gita", "Manish", "Shyam", "Raj", "Hari", "Rina", "Shree"], 
                 label="Presenter"),
         gr.Radio(["Yes", "No"], label="Visited Parent"),
+        gr.Radio(["Trinity", "CCRC", "KMC", "SOS", "ISMT", "St. Xavier's", "Everest", "Prime"], label="College"),
         gr.Radio(["Yes", "No"], label="Visited College for Inquiry"),
         gr.Radio(["Yes", "No"], label="Attended Any Event"),
         gr.Number(label="College Fee"),