app.py

# Import necessary modules
import numpy as np
import gradio as gr
import joblib
import pandas as pd
import os

# Load the pre-trained model and preprocessor
def load_model():
    cwd = os.getcwd()
    destination = os.path.join(cwd, "saved cap")
    Final_model_file_path = os.path.join(destination, "Final_model.joblib")
    preprocessor_file_path = os.path.join(destination, "preprocessor.joblib")

    Final_model = joblib.load(Final_model_file_path)
    preprocessor = joblib.load(preprocessor_file_path)

    return Final_model, preprocessor

Final_model, preprocessor = load_model()

# Define the prediction function
def make_prediction(input_data):
    # Transform the input data using the preprocessor
    transformer = preprocessor.transform(input_data)
    predt = Final_model.predict(transformer)
    
    # Return prediction
    if predt[0] == 1:
        return "Customer will Churn"
    return "Customer will not Churn"

# Create the input components for gradio (organize them into two columns)
input_column1 = [
    gr.inputs.Dropdown(choices=['DAKAR', 'THIES', 'SAINT-LOUIS', 'LOUGA', 'KAOLACK', 'DIOURBEL', 'TAMBACOUNDA', 'KAFFRINE', 'KOLDA', 'FATICK', 'MATAM', 'ZIGUINCHOR', 'SEDHIOU', 'KEDOUGOU']),
    gr.inputs.Dropdown(choices=['K > 24 month', 'I 18-21 month', 'H 15-18 month', 'G 12-15 month', 'J 21-24 month', 'F 9-12 month', 'E 6-9 month', 'D 3-6 month']),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
]

input_column2 = [
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Number(),
    gr.inputs.Dropdown(choices=['NO']),
    gr.inputs.Number(),
    gr.inputs.Number(),
]

# Define the output component
output = gr.Textbox(label='Prediction')

# Create the interface component with two columns
app = gr.Interface(
    fn=make_prediction,
    inputs=[input_column1, input_column2],
    title="Customer Churn Predictor",
    description="Enter the fields below and click the submit button to Make Your Prediction",
    outputs=output
)

app.launch(debug=True)