import gradio as gr
import numpy as np
from PIL import Image
import requests
import hopsworks
import joblib
import os

project = hopsworks.login(api_key_value="B8TDkmcSyPyWFM2o.YuXEbXM7MUFk5gdBXFXsbMz24uZipqY4BttbZ9wIoZ0cn9vQd4bSWgj57vDGXqdh")

mr = project.get_model_registry()
model = mr.get_model("iris_modal2", version=1)
model_dir = model.download()
model = joblib.load(model_dir + "/air_model2.pkl")




def forecast():
    
    x = [ 0.        , 24        , -0.68645433, -0.06804887, -0.31264014,
       -0.13749569, -0.32063957, -0.2942814 , -0.18460245, -0.41253886,
        0.06395449,  0.71276574, -0.36466156, -1.03879548, -0.65985627,
        0        ,  0        ,  0.12254366,  0.39172671,  0.34205118,
        0.21383452, -1.0216134 ,  0.40277851, -0.34577169, -0.36832646,
       -0.7210296 ,  0        ]

    res = model.predict(np.asarray(x).reshape(-1, 1))
    
    return model_dir

demo = gr.Interface(
    fn=forecast,
    title="Air Quality Prediction",
    description="Get aqi value",
    allow_flagging="never",
    inputs=[],
    outputs=gr.Textbox(label="Result: "))

demo.launch()