import streamlit as st
import pandas as pd
import pickle

st.write('Model untuk prediksi gagal bayar atau tidak gagal bayar. \
    \n0: Sukses bayar\
    \n1: Telat sebulan\
    \n2: Telat 2 bulan\
    \n3: Telat 3 bulan\
    \n4: Telah lebih dari 3 bulan.')

def run():
    # Load All Files
    with open('model.pkl', 'rb') as file:
        full_process = pickle.load(file)

    pay_1 = st.selectbox(label='choose delay payment in a month', options=[0.0, 1.0, 2.0, 3.0, 4.0], key='pay_1')
    pay_2 = st.selectbox(label='choose delay payment in a month', options=[0.0, 1.0, 2.0, 3.0, 4.0], key='pay_2')
    pay_3 = st.selectbox(label='choose delay payment in a month', options=[0.0, 2.0, 3.0, 4.0], key='pay_3')
    pay_4 = st.selectbox(label='choose delay payment in a month', options=[0.0, 2.0, 3.0, 4.0], key='pay_4')
    pay_5 = st.selectbox(label='choose delay payment in a month', options=[0.0, 2.0, 3.0, 4.0], key='pay_5')
    pay_6 = st.selectbox(label='choose delay payment in a month', options=[0.0, 2.0, 3.0, 4.0], key='pay_6')
    limit_balance = st.number_input(label='Limit Balance', key='limit_balance')
    pay_amt_1 = st.number_input(label='Pay Amount 1', key='pay_amt_1')
    pay_amt_2 = st.number_input(label='Pay Amount 2', key='pay_amt_2')
    pay_amt_3 = st.number_input(label='Pay Amount 3', key='pay_amt_3')
    pay_amt_4 = st.number_input(label='Pay Amount 4', key='pay_amt_4')
    pay_amt_6 = st.number_input(label='Pay Amount 6', key='pay_amt_6')
    
    st.write('In the following is the result of the data you have input:')
    
    data_inf = pd.DataFrame({
         'pay_1': [pay_1],
         'pay_2': [pay_2],
         'pay_3': [pay_3],
         'pay_4': [pay_4],
         'pay_5': [pay_5],
         'pay_6': [pay_6],
         'Limit Balance': [limit_balance],
         'pay amount 1': [pay_amt_1],
         'pay amount 2': [pay_amt_2],
         'pay amount 3': [pay_amt_3],
         'pay amount 4': [pay_amt_4],
         'pay amount 6': [pay_amt_6]
    })

    st.table(data_inf)

    if st.button(label='Predict'):
        # data dummy prediction
        yPred_inf = full_process.predict(data_inf)
        st.metric(label="Here is a prediction of default payment next month:", value=y_pred_inf[0])

        # result of prediction
        if yPred_inf[0] == 0:
            st.write('Not Default')

        else:
            st.write('Default')