import streamlit as st 
import pandas as pd 
import numpy as np 
import pickle 
import json 
import joblib as jb

#load models
model = jb.load('model.pkl')

def run():
    with st.form('key=form_prediction') :
        age = st.number_input('Age', min_value=40, max_value=95, value= 60, step=1, help='Usia anda')
        anaemia = st.selectbox('Anemia',(0,1), index= 1)
        creatinine_phosphokinase= st.number_input('creatinine_phosphokinase', min_value=23, max_value=7861)
        diabetes = st.selectbox('Diabetes',(0,1), index= 1)
        ejection_fraction = st.number_input('ejection_fraction', min_value=14, max_value=80)
        high_blood_pressure = st.selectbox('Tekanan Darah',(0,1), index= 1) 
        platelets = st.number_input('platelets', min_value=25100, max_value=850000)
        serum_creatinine = st.number_input('serum creatinine',min_value=0.5,max_value=9.4)
        serum_sodium = st.number_input('serum_sodium',min_value=113, max_value=148)
        sex = st.selectbox('Jenis Kelamin',(0,1), index= 1) 
        smoking = st.selectbox('smoking',(0,1), index= 1)
        time =  st.slider('serum creatinine',4,135,285) 


        submitted = st.form_submit_button('Predict')

    data_inf = {
    'age': age,
    'anaemia': anaemia,
    'creatinine_phosphokinase':creatinine_phosphokinase,
    'diabetes':diabetes,
    'ejection_fraction': ejection_fraction,
    'high_blood_pressure': high_blood_pressure,
    'platelets' :platelets,
    'serum_creatinine' :serum_creatinine,
    'serum_sodium' :serum_sodium,
    'sex': sex,
    'smoking':smoking,
    'time': time
    }

    data_inf = pd.DataFrame([data_inf])
    st.dataframe(data_inf)

    if submitted:

        # Predict using bagging 
        y_pred_inf = model.predict(data_inf)

        st.write('# Death Prediction : ', str(int(y_pred_inf)))


if __name__=='__main__':
    run()