Update app.py

app.py

@@ -1,3 +1,4 @@
+#importing necessary packages and modules
 import gradio as gr
 import joblib
 import numpy as np
@@ -5,6 +6,9 @@ import numpy as np
 # Load the trained loan model
 model = joblib.load("loan_RFmodel.joblib")
 
+#This function 
+#Takes input from user and uses the trained model to predict loan eligibility.
+
 def predict_loan_status(
     married,
     dependents,
@@ -16,14 +20,8 @@ def predict_loan_status(
     credit_history,
     property_area
 ):
-    """
-    This function:
-    - Receives user inputs
-    - Converts categorical inputs to numeric values
-    - Uses the trained model to predict loan status
-    """
 
-    # Encoding categorical variables (must match training logic)
+    #Encoding the categorical variables for model prediction
     married = 1 if married == "Yes" else 0
     education = 1 if education == "Graduate" else 0
 
@@ -47,13 +45,13 @@ def predict_loan_status(
         property_area
     ]])
 
-    # Make prediction
+    # Making prediction
     prediction = model.predict(features)[0]
 
     return "Loan Approved" if prediction == 1 else "Loan Rejected"
 
-# Gradio Interface
-interface = gr.Interface(
+# Building the Gradio User Interface
+Gardio_interface = gr.Interface(
     fn=predict_loan_status,
     inputs=[
         gr.Radio(["Yes", "No"], label="Married"),
@@ -72,4 +70,4 @@ interface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    interface.launch()
+    Gardio_interface.launch()