Create app.py

app.py

@@ -0,0 +1,60 @@
+import streamlit as st
+import hopsworks
+import joblib
+import pandas as pd
+import numpy as np
+import folium
+from streamlit_folium import st_folium, folium_static
+import json
+import time
+from datetime import timedelta, datetime
+from branca.element import Figure
+import gradio as gr
+
+from functions import decode_features, get_model, get_weather_df, get_weather_data
+
+
+project = hopsworks.login()
+fs = project.get_feature_store()
+feature_view = fs.get_feature_view(
+    name = 'oslo_air_quality_fv',
+    version = 1
+)
+
+model = get_model(project=project,
+                  model_name="air_quality_model",
+                  evaluation_metric="f1_score",
+                  sort_metrics_by="max")
+
+
+def pred(name):
+    str1 = " "
+    for i in range(8):
+        target_date = datetime.today() + timedelta(days=i)
+        target_date = target_date.strftime('%Y-%m-%d')
+
+        data_weather = [get_weather_data('oslo',target_date)]
+        df_weather = get_weather_df(data_weather)
+        df_weather['conditions'] = df_weather['conditions'].replace(['Rain','Clear','Snow','Partially cloudy','Overcast','Snow, Partially cloudy',
+                                                             'Rain, Partially cloudy','Rain, Overcast','Snow, Overcast',
+                                                             'Snow, Freezing Drizzle/Freezing Rain, Overcast','Snow, Rain',
+                                                             'Snow, Rain, Freezing Drizzle/Freezing Rain, Ice, Overcast',
+                                                             'Snow, Rain, Freezing Drizzle/Freezing Rain, Overcast','Snow, Rain, Ice, Overcast',
+                                                             'Snow, Rain, Overcast','Snow, Rain, Partially cloudy'],[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15])
+        df_weather = df_weather.drop(columns=["date"]).fillna(0)
+        df_weather["aqi"] = 0
+        preds = model.predict(df_weather)
+        print(preds)
+        if(i!=0):
+            str1 += target_date + " predicted aqi:" + str(int(preds))+"\n"
+    
+    return str1
+            
+
+    # next_day_date = datetime.today() + timedelta(days=i)
+    # next_day = next_day_date.strftime ('%d/%m/%Y')
+
+demo = gr.Interface(fn=pred,title="Predict AQI of Oslo" ,inputs="text", outputs="text")
+
+if __name__ == "__main__":
+    demo.launch()