Upload 2 files

app.py

@@ -29,7 +29,7 @@ fancy_header('\n📡 Connecting to Hopsworks Feature Store...')
 project = hopsworks.login()
 fs = project.get_feature_store()
 feature_view = fs.get_feature_view(
-    name = 'air_quality_fv',
+    name = 'miami_air_quality_fv',
     version = 1
 )
 
@@ -39,7 +39,7 @@ progress_bar.progress(20)
 st.write(36 * "-")
 fancy_header('\n☁️ Getting batch data from Feature Store...')
 
-start_date = datetime.now() - timedelta(days=1)
+start_date = datetime.now() - timedelta(days=4) # date today minus 2023-1-10
 start_time = int(start_date.timestamp()) * 1000
 
 X = feature_view.get_batch_data(start_time=start_time)
@@ -73,12 +73,13 @@ folium.LayerControl().add_to(my_map)
 data_to_display = data_to_display[["city", "temp", "humidity",
                                             "conditions", "aqi"]]
 
-cities_coords = {("Sundsvall", "Sweden"): [62.390811, 17.306927],
-                 ("Stockholm", "Sweden"): [59.334591, 18.063240],
-                 ("Malmo", "Sweden"): [55.604981, 13.003822]}
+# cities_coords = {("Sundsvall", "Sweden"): [62.390811, 17.306927],
+#                  ("Stockholm", "Sweden"): [59.334591, 18.063240],
+#                  ("Malmo", "Sweden"): [55.604981, 13.003822]}
+cities_coords = {("Miami", "USA"): [25.761681, -80.191788]}
 
-if "Kyiv" in data_to_display["city"]:
-    cities_coords[("Kyiv", "Ukraine")]: [50.450001, 30.523333]
+# if "Kyiv" in data_to_display["city"]:
+#     cities_coords[("Kyiv", "Ukraine")]: [50.450001, 30.523333]
 
 data_to_display = data_to_display.set_index("city")
 
@@ -123,8 +124,8 @@ st.sidebar.write("-" * 36)
 
 
 model = get_model(project=project,
-                  model_name="gradient_boost_model",
-                  evaluation_metric="f1_score",
+                  model_name="xgboost_model",
+                  evaluation_metric="f1",
                   sort_metrics_by="max")
 
 preds = model.predict(X)
@@ -133,6 +134,7 @@ cities = [city_tuple[0] for city_tuple in cities_coords.keys()]
 
 next_day_date = datetime.today() + timedelta(days=1)
 next_day = next_day_date.strftime ('%d/%m/%Y')
+print('-------', preds, '------', X, '--------')
 df = pd.DataFrame(data=preds, index=cities, columns=[f"AQI Predictions for {next_day}"], dtype=int)
 
 st.sidebar.write(df)

requirements.txt

@@ -7,4 +7,5 @@ pandas==1.5.2
 python-dotenv==0.21.0
 requests==2.28.1
 streamlit==1.17.0
-streamlit_folium==0.10.0
+streamlit_folium==0.10.0
+xgboost==0.90