Update app.py

app.py

@@ -1,57 +1,30 @@
 import pickle
-import numpy as np
 import gradio as gr
+import numpy as np
+
 
-# Load the model
 with open("Model.pickle", "rb") as f:
     model = pickle.load(f)
 
-# Function to encode categorical features
-def encode_features(num_passengers, sales_channel, trip_type, purchase_lead, length_of_stay, 
-                    flight_hour, flight_day, route, wants_extra_baggage, 
-                    wants_preferred_seat, wants_in_flight_meals, flight_duration):  
-    # Encoding Sales Channel (e.g., Online -> 0, Offline -> 1)
-    sales_channel_mapping = {"Online": 0, "Offline": 1}
-    trip_type_mapping = {"Single Trip": 0, "Round Trip": 1}
-    binary_mapping = {"Yes": 1, "No": 0}  # Used for extra baggage, preferred seat, meals
 
-    # Encoding categorical values
-    sales_channel = sales_channel_mapping.get(sales_channel, 0)
-    trip_type = trip_type_mapping.get(trip_type, 0)
-    wants_extra_baggage = binary_mapping.get(wants_extra_baggage, 0)
-    wants_preferred_seat = binary_mapping.get(wants_preferred_seat, 0)
-    wants_in_flight_meals = binary_mapping.get(wants_in_flight_meals, 0)
+def predict(num_passengers, sales_channel, trip_type, purchase_lead, length_of_stay, 
+            flight_hour, flight_day, route, booking_origin, wants_extra_baggage, 
+            wants_preferred_seat, wants_in_flight_meals, flight_duration):
+    
+    input_data = np.array([[num_passengers, sales_channel, trip_type, purchase_lead, length_of_stay, 
+                            flight_hour, flight_day, route, booking_origin, wants_extra_baggage, 
+                            wants_preferred_seat, wants_in_flight_meals, flight_duration]])
+
+    prediction = model.predict(input_data)[0]
 
-    # Encode the route if necessary (assuming it was label-encoded during training)
-    routes = ["AKLDEL", "AKLHGH", "AKLHND", "AKLICN", "AKLKIX", "AKLKTM"]
-    route_mapping = {route: idx for idx, route in enumerate(routes)}
-    route = route_mapping.get(route, 0)  # Default to 0 if route is not found
+    return "Booking Completed ✅" if prediction == 1 else "Booking Not Completed ❌"
 
-    # Convert everything into a NumPy array
-    input_data = np.array([[num_passengers, sales_channel, trip_type, purchase_lead, length_of_stay, 
-                             flight_hour, flight_day, route, wants_extra_baggage, 
-                             wants_preferred_seat, wants_in_flight_meals, flight_duration]])
 
-    return input_data
 
-# Prediction function
-def predict_booking(num_passengers, sales_channel, trip_type, purchase_lead, length_of_stay, 
-                    flight_hour, flight_day, route, wants_extra_baggage, 
-                    wants_preferred_seat, wants_in_flight_meals, flight_duration):  
-    # Encode categorical features
-    input_data = encode_features(num_passengers, sales_channel, trip_type, purchase_lead, length_of_stay, 
-                                 flight_hour, flight_day, route, wants_extra_baggage, 
-                                 wants_preferred_seat, wants_in_flight_meals, flight_duration)
 
-    # Make prediction
-    prediction = model.predict(input_data)[0]
-    
-    return "Booking Completed ✅" if prediction == 1 else "Booking Not Completed ❌"
 
-# Define Routes
 routes = ["AKLDEL", "AKLHGH", "AKLHND", "AKLICN", "AKLKIX", "AKLKTM"]
 
-# Gradio Interface
 iface = gr.Interface(
     fn=predict_booking,
     inputs=[
@@ -62,15 +35,15 @@ iface = gr.Interface(
         gr.Number(label="Length of Stay"),
         gr.Number(label="Flight Hours"),
         gr.Number(label="Flight Day"),
-        gr.Dropdown(choices=routes, label="Route"),
+        gr.Dropdown(choices=routes, label="Route"),  # ✅ Fixed: Dropdown instead of Number
         gr.Dropdown(choices=["Yes", "No"], label="Want Extra Baggage"),
-        gr.Dropdown(choices=["Yes", "No"], label="Want Preferred Seat"),
+        gr.Dropdown(choices=["Yes", "No"], label="Want Preferred Seat"),  # ✅ Fixed spelling
         gr.Dropdown(choices=["Yes", "No"], label="Want In-Flight Meals"),
         gr.Number(label="Flight Duration")
     ],
-    outputs=gr.Textbox(label="Booking Prediction"),
+    outputs=gr.Textbox(label="Booking Prediction"),  # ✅ Fixed spelling
     title="British Airways Booking Predictions",
-    description="Enter Flight Details to Predict Booking Completion"
+    description="Enter Flight Details to Predict Booking Completion"  # ✅ Fixed case-sensitive error
 )
 
 iface.launch()