app.py

# Medical Cost charges Predictor

import pandas as pd
import gradio as gr
import pickle

# Load the model file
with open('medical_cost_model.pkl', 'rb') as f:   
    model = pickle.load(f)

# The predicion workhorse
def predict(*args):
    data = pd.DataFrame({
        'sex': [args[0]],
        'smoker': [args[1]],
        'region': [args[2]],
        'age': [args[3]],
        'bmi': [args[4]],
        'children': [args[5]]
    })
    return '<strong>charges: ' + str(model.predict(data)[0]) + '</strong>'

# User Interface
number = gr.components.Number
radio = gr.components.Radio
dropdown = gr.components.Dropdown
with gr.Blocks() as service:
    gr.Markdown(value='<h4>Medical Cost charges Predictor</h4>Powered by <b>Magic canAI</b>')

    # User inputs
    sex = radio(['female', 'male'], value="female", label="sex")
    smoker = radio(['no', 'yes'], value="no", label="smoker")
    region = dropdown(['northeast', 'northwest', 'southeast', 'southwest'], value="northeast", label="region")
    age = number(value=39, label="age")
    bmi = number(value=30.5118, label="bmi")
    children = number(value=1, label="children")

    # The output
    output = gr.Markdown(label="Prediction")

    # Command controls
    check_btn = gr.components.Button("Predict")
    check_btn.click(fn=predict, inputs=[sex, smoker, region, age, bmi, children], outputs=output)

    # Launch the app
    service.launch(debug=True)
###