app.py

import gradio as gr
import pandas as pd
import pickle


# Define params names
PARAMS_NAME = [
        "BMI",
        "Smoking",
        "AlcoholDrinking",
        "Stroke",
        "PhysicalHealth",
        "MentalHealth",
        "DiffWalking",
        "Sex",
        "AgeCategory",
        "Race",
        "Diabetic",
        "PhysicalActivity",
        "GenHealth",
        "SleepTime",
        "Asthma",
        "KidneyDisease",
        "SkinCancer"
]

           
# Load model
with open("model/model1.pkl", "rb") as f:
    model = pickle.load(f)




def predict(*args):
    answer_dict = {}

    for i in range(len(PARAMS_NAME)):
        answer_dict[PARAMS_NAME[i]] = [args[i]]

    # Crear dataframe
    single_instance = pd.DataFrame.from_dict(answer_dict)

    data4 = single_instance
    
    

    data4=data4.replace({'80 or older': '80'})
    def limpiar_valor(valor):
        return valor.replace('-', '').replace(' ', '')
    data4['AgeCategory'] = data4['AgeCategory'].apply(limpiar_valor).astype(int)
    data4=data4.replace({'Yes': 0, 'No': 1})
    data4=data4.replace({'Female': 0, 'Male': 1})
    data4=data4.replace({'Fair': 0, 'Good': 1, 'Very good': 2})
    data4['Diabetic']=data4['Diabetic'].replace({'Yes (during pregnancy)': 1, 'No, borderline diabetes': 1})
    data4.rename(columns={'Race': 'Etnic'}, inplace=True)
    data4['GenHealth']=data4['GenHealth'].replace({'Fair': 0, 'Poor': 1, 'Good': 2, 'Very good': 3, 'Excellent': 4})
    data4['Etnic'] = data4['Etnic'].replace({'White': 'Gringo', 'Black': 'Afro'})    
    data4=data4.replace({'American Indian/Alaskan Native': 0, 'Asian': 1, 'Afro': 2, 'Hispanic': 3, 'Other': 4, 'Gringo': 5})
    data4[['PhysicalHealth', 'MentalHealth', 'SleepTime']] = data4[['PhysicalHealth', 'MentalHealth', 'SleepTime']].astype(int)

    
    prediction = model.predict(data4)

    # Como sabemos el model nos devuelve los tipos de fraude 1, 2 y 3 en el response. Podemos devolver un response estilo semáforo.
    
    # Cast numpy.int64 to just a int
    result = int(prediction[0])


    # Adaptación respuesta
    response = result
    if result == 1:
        response = "Still eating trash food and smoking, you're inmortal dude"
    if result == 0:
        response = "Leave the chips, the cakes and take walk everyday NOW!"


    return response


with gr.Blocks() as demo:
    gr.Markdown(
        """
        #   Heart Status ❤️‍🩹
        """
    )

    with gr.Row():
        with gr.Column():

            gr.Markdown(
                """
                ## Insert your health data here please 😮‍💨
                """
            )
            

            BMI = gr.Slider(
                label='Bmi - Body Mass Index',
                minimum=12.02,
                maximum=44.85,
                step=1,
                randomize=True
            )

            Smoking = gr.Radio(
                label='Have you smoked at least 100 cigarettes in your entire life?',
                choices=['Yes', 'No'],
                value='No',
            )

            AlcoholDrinking = gr.Radio(
                label='Heavy drinkers (adult men having more than 14 drinks per week and adult women having more than 7 drinks per week',
                choices=['No', 'Yes'],
                value='No',
            )

            Stroke = gr.Radio(
                label='(Ever told) (you had) a stroke?',
                choices=['No', 'Yes'],
                value='No',
            )

            PhysicalHealth = gr.Slider(
                label='Now thinking about your physical health, which includes physical illness and injury, for how many days during the past 30',
                minimum=0,
                maximum=30,
                step=1,
                randomize=True
            )

            MentalHealth = gr.Slider(
                label='Thinking about your mental health, for how many days during the past 30 days was your mental health not good?',
                minimum=0,
                maximum=30,
                step=1,
                randomize=True
            )

            DiffWalking = gr.Radio(
                label='Do you have serious difficulty walking or climbing stairs?',
                choices=['No', 'Yes'],
                value='No',
            )

            Sex = gr.Radio(
                label='Are you male or female?',
                choices=['Female', 'Male'],
                value='Female',
            )

            AgeCategory = gr.Dropdown(
                label='Age Category',
                choices=['55-59', '80 or older', '65-69', '75-79', '40-44', '70-74', '60-64', '50-54', '45-49', '18-24', '35-39', '30-34', '25-29'],
                multiselect=False,
                value='65-69',
            )

            Race = gr.Dropdown(
                label='Etnic',
                choices=['Gringo', 'Afro', 'Asian', 'American Indian/Alaskan Native', 'Other', 'Hispanic'],
                multiselect=False,
                value='Gringo',
            )

            Diabetic = gr.Dropdown(
                label='Diabetic',
                choices=['Yes', 'No', 'No, borderline diabetes', 'Yes (during pregnancy)'],
                multiselect=False,
                value='No',
            )

            PhysicalActivity = gr.Radio(
                label='Physical activity',
                choices=['Yes', 'No'],
                value='Yes',
            )

            GenHealth = gr.Dropdown(
                label='Gen health',
                choices=['Very good', 'Fair', 'Good', 'Poor', 'Excellent'],
                multiselect=False,
                value='Very good',
            )

            SleepTime = gr.Slider(
                label='Sleeptime',
                minimum=3,
                maximum=12,
                step=1,
                randomize=True
            )

            Asthma = gr.Radio(
                label='Asthma',
                choices=['Yes', 'No'],
                value='No',
            )

            KidneyDisease = gr.Radio(
                label='Kidney disease',
                choices=['No', 'Yes'],
                value='No',
            )

            SkinCancer = gr.Radio(
                label='Skin cancer',
                choices=['Yes', 'No'],
                value='No',
            )



        with gr.Column():

            gr.Markdown(
                """
                ## Let see the medical board review
                ## <img src="https://media.tenor.com/ny2kroyiSI4AAAAC/hi-everybody-simpsons.gif" alt="GIF">
                """
            )

            label = gr.Label(label="medical board")
            predict_btn = gr.Button(value="How is my heart Nick?")
            predict_btn.click(
                predict,
                inputs=[
                    BMI,
                    Smoking,
                    AlcoholDrinking,
                    Stroke,
                    PhysicalHealth,
                    MentalHealth,
                    DiffWalking,
                    Sex,
                    AgeCategory,
                    Race,
                    Diabetic,
                    PhysicalActivity,
                    GenHealth,
                    SleepTime,
                    Asthma,
                    KidneyDisease,
                    SkinCancer,
                ],
                outputs=[label],
                api_name="prediccion"
            )
    gr.Markdown(
        """
        <p style='text-align: center'>
            <a href='https://www.escueladedatosvivos.ai/cursos/bootcamp-de-data-science' 
                target='_blank'>Proyecto demo creado en el bootcamp de EDVAI 🤗
            </a>
        </p>
        <p style='text-align: center'>
            <a href='https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease' 
                target='_blank'>Data From Personal Key Indicators of Heart Disease in Kaggle
            </a>
        </p>
        <p style='text-align: center'>
            <a href='https://github.com/GarganoNicolas/heart' 
                target='_blank'>GitHub Project 🛠️
            </a>
        </p>        
        """
    )

demo.launch()