import gradio as gr
import numpy as np
import pickle

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

# Define the mappings for 'Type of Travel' and 'Class' before using them
type_of_travel_map = {'Personal Travel': 0, 'Business travel': 1}
class_map = {'Eco Plus': 0, 'Business': 1, 'Eco': 2}

def predict_satisfaction(online_boarding, type_of_travel, inflight_entertainment, seat_comfort,
                         onboard_service, flight_class, leg_room_service, cleanliness, flight_distance, inflight_wifi_service):
    try:
        # Check the inputs
        print(f"Received inputs: {online_boarding}, {type_of_travel}, {inflight_entertainment}, {seat_comfort}, "
              f"{onboard_service}, {flight_class}, {leg_room_service}, {cleanliness}, {flight_distance}, {inflight_wifi_service}")

        # Map the inputs to the expected model format
        features = [
            online_boarding,
            type_of_travel_map[type_of_travel],  # map 'Type of Travel'
            inflight_entertainment,
            seat_comfort,
            onboard_service,
            class_map[flight_class],  # map 'Class'
            leg_room_service,
            cleanliness,
            flight_distance,
            inflight_wifi_service
        ]

        # Get probabilities of satisfaction (class 0) and dissatisfaction (class 1)
        probabilities = model.predict_proba([features])[0]  # Assuming it returns a 2D array

        # Set threshold for satisfaction
        satisfaction_probability = probabilities[0]  # Probability for being satisfied (class 0)

        # Apply threshold of 0.87 for satisfaction
        if satisfaction_probability >= 0.87:
            return "Satisfied"
        else:
            return "Neutral or Dissatisfied"

    except Exception as e:
        return f"Error: {str(e)}"

import gradio as gr
inputs = [
    gr.Slider(minimum=0, maximum=5, label="Online Boarding"),
    gr.Dropdown(choices=["Personal Travel", "Business travel"], label="Type of Travel"),
    gr.Slider(minimum=0, maximum=5, label="Inflight Entertainment"),
    gr.Slider(minimum=0, maximum=5, label="Seat Comfort"),
    gr.Slider(minimum=0, maximum=5, label="On-board Service"),
    gr.Dropdown(choices=["Eco Plus", "Business", "Eco"], label="Class"),
    gr.Slider(minimum=0, maximum=5, label="Leg Room Service"),
    gr.Slider(minimum=0, maximum=5, label="Cleanliness"),
    gr.Slider(minimum=31, maximum=4983, label="Flight Distance"),
    gr.Slider(minimum=0, maximum=5, label="Inflight Wifi Service")
]

outputs = gr.Textbox(label="Customer Satisfaction Prediction")

gr.Interface(fn=predict_satisfaction, inputs=inputs, outputs=outputs).launch()