app.py

import gradio as gr
import numpy as np
from PIL import Image
import requests
import hopsworks
import joblib
import os
from datetime import datetime, timedelta
project = hopsworks.login()

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




def forecast():
    
    fs = project.get_feature_store() 
    feature_view = fs.get_feature_view(
        name = 'miami_air_quality_fv',
        version = 1
    )
    train_data = feature_view.get_training_data(1)[0]
    # train_data = train_data.drop(labels = 'city_y',axis =1)
    # train_data = train_data.rename(columns = {'city_x':'city'})
    train_data = train_data.sort_values(by="date", ascending=True).reset_index(drop=True)
    train_data["aqi_next_day"] = train_data.groupby('city')['aqi'].shift(1)

    X = train_data.drop(columns=["date"]).fillna(0)
    y = X.pop("aqi_next_day")
    X = X.drop(columns =['city','conditions']).fillna(0)
    
    today_data = X[1:2]
    y = model.predict(today_data)

    res = int(y[0])
    return res
    
date_today = datetime.now()
day = timedelta(days = 1)
date_today = date_today + day
date_today = date_today.strftime("%Y-%m-%d")
output_label = date_today + " 's air quality is "

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


demo.launch()