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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() |