app.py

#!/usr/bin/env python
# coding: utf-8

import gradio as gr
from joblib import load

# Load your trained model
model = load("model_joblib")

# Prediction logic
def predict_loan(Age, Experience, Income, Family, CCAvg, Education, Mortgage,
                 SecuritiesAccount, CDAccount, Online, CreditCard):
    
    input_data = [[Age, Experience, Income, Family, CCAvg, Education, Mortgage,
                 SecuritiesAccount, CDAccount, Online, CreditCard]]
    
    prediction = model.predict(input_data)[0]
    
    result = "✅ Yes - Will Accept Loan" if prediction == 1 else "❌ No - Will Not Accept Loan"
    return result

# Gradio Interface
iface = gr.Interface(
    fn=predict_loan,
    inputs=[
        gr.Number(label="Age"),
        gr.Number(label="Experience (years)"),
        gr.Number(label="Income (in $000)"),
        gr.Number(label="Family Members"),
        gr.Number(label="CC Average Balance (in $000)"),
        gr.Number(label="Education Level (1=Undergrad, 2=Graduate, 3=Advanced)"),
        gr.Number(label="Mortgage (in $000)"),
        gr.Number(label="Securities Account (1=Yes, 0=No)"),
        gr.Number(label="CD Account (1=Yes, 0=No)"),
        gr.Number(label="Online Banking (1=Yes, 0=No)"),
        gr.Number(label="Credit Card (1=Yes, 0=No)")
    ],
    outputs="text",
    title="📊 Personal Loan Offer Prediction",
    description="Enter customer details to predict if they will accept the personal loan offer."
)

if __name__ == "__main__":
    print("✅ App starting... waiting for Gradio interface")
    iface.launch(server_name="0.0.0.0", server_port=7860)