import skops.io as sio import gradio as gr #pipe = sio.load("bank_marketing_pipe.skops", trusted=True) pipe = sio.load("sgd_bank_marketing_pipe.skops", trusted=True) classes = [ "Not Subscribe", "Subscribe"] def classifier(age, job, marital, education, default, balance, housing,loan, contact): pred = pipe.predict([[age, job, marital, education, default, balance, housing,loan, contact]])[0] label = f"Predicted output: **{classes[pred]}**" return label inputs = [ gr.Slider(10, 90, step=1, label="Age"), gr.Dropdown(["admin.","unknown","unemployed","management","housemaid","entrepreneur","student","blue-collar", "self-employed","retired","technician","services"], label="Job", multiselect=False), gr.Dropdown(["married","divorced","single"], label="Marital", multiselect=False), gr.Dropdown(["unknown","secondary","primary","tertiary"], label="Education", multiselect=False), gr.Radio(["yes","no"], label="Default", info='has credit in default?'), gr.Slider(-100000, 100000, step=1, label="Balance"), gr.Radio(["yes","no"], label="Housing", info='has housing loan?'), gr.Radio(["yes","no"], label="Loan", info='has personal loan?'), gr.Dropdown(["unknown","telephone","cellular"], label="Contact") ] outputs = [gr.Label(num_top_classes=2)] title = "Deposit Subscription Prediction" description = "Enter the details to identify where or not the customer is subscribed or not subscribed for deposit" gr.Interface( fn=classifier, inputs=inputs, outputs=outputs, title=title, description=description, ).launch()