import gradio as gr
import hopsworks
import joblib
import pandas as pd
import numpy as np
import json
import time
from datetime import timedelta, datetime


from functions import *


project = hopsworks.login()
	

start_date = datetime.now() - timedelta(days=1)
start_time = int(start_date.timestamp()) * 1000
X = pd.read_csv('x.csv')

X = X.drop(columns=["date"]).fillna(0)

X=X.drop(df.columns[0],axis=1)

print(gb.predict(df)[:7])

mr = project.get_model_registry()
model = mr.get_model("gradient_boost_paris_model", version=1)
model_dir = model.download()
model = joblib.load(model_dir + "/model.pkl")
	    
preds = model.predict(X)
	
	
    
demo = gr.Interface(fn=air_quality, title="Air quality predictor",
description="Input a value to get next weeks AQI prediction for Paris", inputs="text", outputs="text")
	

	    
if __name__ == "__main__":
	demo.launch()