import pickle
import gradio as gr
import numpy as np

# Load the trained model
with open(r"final_pickle_test.pkl","rb") as f:
    model = pickle.load(f)

# Define encoding mappings for categorical variables
sales_channel_mapping = {"Online": 0, "Offline": 1}
trip_type_mapping = {"Single Trip": 0, "Round Trip": 1}
route_mapping = {
    "AKLDEL": 0, "AKLHGH": 1, "AKLHND": 2, "AKLICN": 3, "AKLKIX": 4, "AKLKTM": 5
}
booking_origin_mapping = {"India": 0, "USA": 1, "UK": 2}  # Add actual values

def predict_booking(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):
    
    # Convert categorical values to numerical
    sales_channel_encoded = sales_channel_mapping.get(sales_channel, -1)
    trip_type_encoded = trip_type_mapping.get(trip_type, -1)
    route_encoded = route_mapping.get(route, -1)
    booking_origin_encoded = booking_origin_mapping.get(booking_origin, -1)
    
    wants_extra_baggage = 1 if wants_extra_baggage == "Yes" else 0
    wants_preferred_seat = 1 if wants_preferred_seat == "Yes" else 0
    wants_in_flight_meals = 1 if wants_in_flight_meals == "Yes" else 0

    # Ensure correct feature shape
    input_data = np.array([[num_passengers, sales_channel_encoded, trip_type_encoded, purchase_lead, 
                            length_of_stay, flight_hour, flight_day, route_encoded, booking_origin_encoded, 
                            wants_extra_baggage, wants_preferred_seat, wants_in_flight_meals, flight_duration]])

    print("Input Data Shape:", input_data.shape)  # Debugging

    # Make prediction
    prediction = model.predict(input_data)[0]

    return "Booking Completed ✅" if prediction == 1 else "Booking Not Completed ❌"

# Define available options for dropdowns
routes = ["AKLDEL", "AKLHGH", "AKLHND", "AKLICN", "AKLKIX", "AKLKTM"]
booking_origins = ["India", "USA", "UK"]  # Add actual locations if needed

# Create Gradio interface
iface = gr.Interface(
    fn=predict_booking,
    inputs=[
        gr.Number(label="Number of Passengers"),
        gr.Dropdown(choices=["Online", "Offline"], label="Sales Channel"),
        gr.Dropdown(choices=["Single Trip", "Round Trip"], label="Trip Type"),
        gr.Number(label="Purchase Lead"),
        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=booking_origins, label="Booking Origin"),
        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 In-Flight Meals"),
        gr.Number(label="Flight Duration")
    ],
    outputs=gr.Textbox(label="Booking Prediction"),
    title="British Airways Booking Predictions",
    description="Enter Flight Details to Predict Booking Completion"
)

iface.launch()