import gradio as gr
from pycaret.regression import *
import pandas as pd
import numpy as np
model = load_model('protas__fi__umur_fix')

def inferencing_model(ID_Afdeling, Luas, Tandan, HK, Jumlah_Pokok, Tahun_Tanam_Awal, Tahun_Tanam_Akhir, Curah_Hujan):
    HK_Luas = ((HK / Luas * 100) - 100 )
    pkk_ha = Jumlah_Pokok / Luas
    tandan_pkk = Tandan / Jumlah_Pokok
    umur = Tahun_Tanam_Akhir - Tahun_Tanam_Awal
    test_data = [[tandan_pkk, umur, pkk_ha, HK_Luas, Curah_Hujan, Jumlah_Pokok, Tandan, HK]]
    pred = pd.DataFrame(test_data, columns=['tandan_pkk','umur', 'pkk_ha', 'hk_pkk', 'curah_hujan', 'jumlah_pokok', 'tandan', 'hk'])
    prediction_test_protas = predict_model(model, data = pred)

    return round(int(prediction_test_protas.Label))

afd = ["SRO_I", "SRO_II", "SRO_III", "SRO_IV", "SRO_V", "SRO_VI", "SRO_VII", "SRO_VIII", "SRO_IX", "SRO_X"]
iface = gr.Interface(
    inferencing_model, 
    inputs = [
     gr.inputs.Dropdown(choices= afd, label='Afdeling'), #Afdeling
     "number", #Luas
     "number", #Tandan
     "number", #HK
     "number", #Jumlah_Pokok
     "number", #Tahun_Tanam_Awal
     "number", #Tahun_Tanam_Akhir
     "number" #Curah_Hujan
    ],
    outputs= ["number"],
    # interpretation="default",  # Removed interpretation for dataframes
    examples=[
        ["SRO_X", 920.50, 120166, 714, 142978, 1998, 2011, 216]
    ], allow_flagging=False,
    theme="huggingface", title="Protas Prediction"
    
)

iface.launch(debug=False)