new models

app.py

@@ -152,6 +152,8 @@ def generate_forecast(sensor_internal: str, days: int) -> str | None:
     # Future weather (city-level, same for all sensors)
     df_future = weather_fg.read().sort_values("date")
     df_future["date"] = pd.to_datetime(df_future["date"]).dt.date
+    print("DEBUG: WEATHER FUTURE DATES:", df_future["date"].tail(15).tolist())
+    print("DEBUG: Today:", today)
 
     # PM2.5 history for this sensor
     aq_fg = project.get_feature_store().get_feature_group("dundee_air_quality", version=1)
@@ -177,7 +179,7 @@ def generate_forecast(sensor_internal: str, days: int) -> str | None:
         target_date = today + timedelta(days=offset)
         row = df_future[df_future["date"] == target_date]
         if len(row) == 0:
-            # no weather data for that date
+            print("DEBUG: Missing weather data for:", target_date)
             continue
 
         lag1, lag2, lag3 = pm25_history[-1], pm25_history[-2], pm25_history[-3]