app.py

import gradio as gr
import skimage 
import pickle
import pandas as pd


with open('model.pkl', 'rb') as f:
    model = pickle.load(f)
    
def predict(Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age):

    data = [[int(Pregnancies), int(Glucose), int(BloodPressure), int(SkinThickness), int(Insulin), float(BMI), float(DiabetesPedigreeFunction), int(Age)]]

    row_df=pd.DataFrame(data,columns=['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness','Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age'])
    
    predictions = model.predict(row_df)
    y_pred = model.predict(row_df)
    if y_pred[0] == 1:
        return "Tem diabetes"
    else:
        return "Não tem diabetes"
    return 0

gr.Interface(
    fn=predict,
    title="Predict Diabetes",
    allow_flagging="never",
    inputs=[
        gr.inputs.Number(default=1, label="Pregnancies"),
        gr.inputs.Number(default=126, label="Glucose"),
        gr.inputs.Number(default=60, label="BloodPressure"),
        gr.inputs.Number(default=0, label="SkinThickness"),
        gr.inputs.Number(default=0, label="Insulin"),
        gr.inputs.Number(default=30.1, label="BMI"),
        gr.inputs.Number(default=0.349, label="DiabetesPedigreeFunction"),
        gr.inputs.Number(default=47, label="Age")
    ],
    outputs="text").launch()