import numpy as np
import pandas as pd
import gradio as gr
import joblib
import pickle
from sklearn.tree import DecisionTreeClassifier

with open('./model_playgolf_decision_tree_classifier','rb') as f:
    dct_playgolf = pickle.load(f)

def predict(Windy: bool = True
            ,Outlook_Rainy: bool = True
            ,Outlook_Sunny: bool = True
            ,Temp_Hot: bool = True
            ,Temp_Mild: bool = True
            ,Humidity_Normal: bool = True):
    
    prediction_array = np.array([Windy, Outlook_Rainy, Outlook_Sunny, Temp_Hot, Temp_Mild, Humidity_Normal], dtype=np.double)
    play_golf = dct_playgolf.predict([prediction_array])   
                     
    if play_golf == ['Yes']:
        return f'Weather is good for playing golf'
    else:
        return f'Weather is horrible for playing golf'    

with gr.Blocks() as playgolf:
    with gr.Row() as outlookrow:
        Windy = gr.Dropdown(choices=[True,False], label="Windy Day?")
        Outlook_Rainy= gr.Dropdown(choices=[True,False], label="Rainy Day?")
        Outlook_Sunny= gr.Dropdown(choices=[True,False], label="Sunny Day?")

    with gr.Row() as Temprow:
        Temp_Hot = gr.Dropdown(choices=[True,False], label="Is Hot Today?")
        Temp_Mild= gr.Dropdown(choices=[True,False], label="Is Mild Temperature Today?")
        Humidity_Normal= gr.Dropdown(choices=[True,False], label="Is Humidity Normal?")

    submit = gr.Button(value='Predict')

    output = gr.Textbox(label='Is weather good to play Golf?', interactive = False)

    submit.click(predict, inputs=[Windy,Outlook_Rainy,Outlook_Sunny,Temp_Hot,Temp_Mild,Humidity_Normal], outputs = [output])

    
playgolf.launch(share = False, debug = True)