app.py

import gradio as gr
import pandas as pd
from fastai.tabular.all import *

learn = load_learner('model.pkl')

def predict(Gender, SmokingHistory, Age, Hypertension, HeartDisease, BMI, HbLevel, GlucoseLevel):

    data = [[Gender, SmokingHistory, int(Age), int(Hypertension), int(HeartDisease), float(BMI), float(HbLevel), int(GlucoseLevel)]]

    row_df = pd.DataFrame(data,columns=['gender','smoking_history', 'age', 'hypertension', 'heart_disease', 'bmi', 'HbA1c_level', 'blood_glucose_level'])
    
    row, clas, probs = learn.predict(row_df.iloc[0])
    if probs[0] < 0.5:
        return "Tem diabetes"
    else:
        return "Não tem diabetes"

gr.Interface(
    fn=predict,
    title="Predict Diabetes",
    allow_flagging="never",
    inputs=[
        gr.inputs.Radio(["Male", "Female"], label="Gender", default="Male"),
        gr.inputs.Dropdown(
            ["never", "No info", "current" , "former"], label="SmokingHistory", default="never"
        ),
        gr.inputs.Number(default=60, label="Age"),
        gr.inputs.Radio(["1", "0"], label="HyperTension", default="1"),
        gr.inputs.Radio(["1", "0"], label="HeartDisease", default="1"),
        gr.inputs.Number(default=30, label="BMI"),
        gr.inputs.Number(default=5.1, label="HbLevel"),
        gr.inputs.Number(default=90, label="GlucoseLevel")
    ],
    outputs="text").launch(inline=False)