import streamlit as st import hopsworks import joblib import pandas as pd from datetime import timedelta, datetime from functions import * def fancy_header(text, font_size=24): res = f'{text}' st.markdown(res, unsafe_allow_html=True) st.title('Air Quality Prediction Project🌩') st.write(36 * "-") fancy_header('\n Connecting to Hopsworks Feature Store...') project = hopsworks.login() st.write("Successfully connected!✔️") st.write(36 * "-") fancy_header('\n Getting data from Feature Store...') today = datetime.date.today() city = "vienna" weekly_data = get_weather_data_weekly(city, today) st.write(36 * "-") mr = project.get_model_registry() model = mr.get_best_model("aqi_model", "rmse", "min") model_dir = model.download() model = joblib.load(model_dir + "/aqi_model.pkl") st.sidebar.write("-" * 36) preds = model.predict(data_encoder(weekly_data)).astype(int) poll_level = get_aplevel(preds.T.reshape(-1, 1)) next_week = [[(today + timedelta(days=d)).strftime('%Y-%m-%d'),(today + timedelta(days=d)).strftime('%A')] for d in range(1, 7)] df = pd.DataFrame(data=[preds, poll_level], index=["AQI", "Air pollution level"], columns=[f"AQI Predictions for {next_day}" for next_day in next_week]) st.write(df) st.button("Re-run")