app.py

import gradio as gr
import numpy as np

import hopsworks
import joblib

project = hopsworks.login()
fs = project.get_feature_store()

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

def air_quality(temp, humidity, precip, pressure, cloudcover, visibility, uvindex):
    input_list=[]
    input_list.append("Helsinki") #city
    input_list.append(temp)
    input_list.append(humidity)
    input_list.append(precip)
    input_list.append(cloudcover)
    input_list.append(visibility)
    input_list.append(uvindex)

    res = model.predict(np.asarray(input_list).reshape(1,-1))
    return res[0]

aqi = gr.Interface(
    fn=air_quality,
    title="Predicting air quality - Helsinki",
    description="Predictive air quality model for Helsinki",
    allow_flagging="never",
    inputs=[
        gr.components.Slider(-30,35, value=0, label="What is today's temperature?"), #temp
        gr.components.Slider(-4,4,value=0, label="Today's humidity?"),
        gr.components.Slider(-1,10,value=0, label="How much precipitation today?"),
        gr.components.Slider(-2,2,value=0, label="How cloudy is it today?"),
        gr.components.Slider(-3,2,value=0, label="How good is visibility today?"),
        gr.components.Slider(-2,3,value=0, label="What is the uvindex today?")
    ],
    outputs=["label"],
)

aqi.launch()