app.py

import gradio as gr
import numpy as np
from joblib import load

rf = load("model_smoke_pred.pkl")

columns = [
    "age",
    "height(cm)",
    "weight(kg)",
    "waist(cm)",
    "eyesight(left)",
    "eyesight(right)",
    "hearing(left)",
    "hearing(right)",
    "systolic",
    "relaxation",
    "fasting_blood_sugar",
    "cholesterol",
    "triglyceride",
    "hdl",
    "ldl",
    "hemoglobin",
    "urine_protein",
    "serum_creatinine",
    "ast",
    "alt",
    "gtp",
    "dental_caries",
]


def predict(
    age,
    height,
    weight,
    waist,
    eyesight_left,
    eyesight_right,
    hearing_left,
    hearing_right,
    systolic,
    relaxation,
    fasting_blood_sugar,
    cholesterol,
    triglyceride,
    hdl,
    ldl,
    hemoglobin,
    urine_protein,
    serum_creatinine,
    ast,
    alt,
    gtp,
    dental_caries,
):
    data = np.array(
        [
            [
                age,
                height,
                weight,
                waist,
                eyesight_left,
                eyesight_right,
                hearing_left,
                hearing_right,
                systolic,
                relaxation,
                fasting_blood_sugar,
                cholesterol,
                triglyceride,
                hdl,
                ldl,
                hemoglobin,
                urine_protein,
                serum_creatinine,
                ast,
                alt,
                gtp,
                dental_caries,
            ]
        ]
    )
    pred = rf.predict(data)[0]
    return {"fumante": pred}


inputs = [
    gr.Number(label="age"),
    gr.Number(label="height(cm)"),
    gr.Number(label="weight(kg)"),
    gr.Number(label="waist(cm)"),
    gr.Number(label="eyesight(left)"),
    gr.Number(label="eyesight(right)"),
    gr.Slider(minimum=0, maximum=1, label="hearing(left)"),  # Assuming it's a boolean
    gr.Slider(minimum=0, maximum=1, label="hearing(right)"),  # Assuming it's a boolean
    gr.Number(label="systolic"),
    gr.Number(label="relaxation"),
    gr.Number(label="fasting_blood_sugar"),
    gr.Number(label="cholesterol"),
    gr.Number(label="triglyceride"),
    gr.Number(label="hdl"),
    gr.Number(label="ldl"),
    gr.Number(label="hemoglobin"),
    gr.Number(label="urine_protein"),
    gr.Number(label="serum_creatinine"),
    gr.Number(label="ast"),
    gr.Number(label="alt"),
    gr.Number(label="gtp"),
    gr.Slider(minimum=0, maximum=1, label="dental_caries"),  # Assuming it's a boolean
]


output = gr.Label(num_top_classes=1)

iface = gr.Interface(
    fn=predict,
    inputs=inputs,
    outputs=output,
    description="O modelo em questão tenta realizar a predição se o usuario é ou não fumante.",
)

iface.launch()