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

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

    return round(int(prediction_test_produksi.Label))


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

iface.launch()