Update app.py

app.py

@@ -111,12 +111,14 @@ def fetch_and_process_sdo_data(target_dt, forecast_horizon_minutes):
                 if data_maps[t].get("hmi_bx"): data_maps[t][channel] = data_maps[t]["hmi_bx"]
                 continue
             
-            time_attr = a.Time(t - datetime.timedelta(minutes=2), t + datetime.timedelta(minutes=2))
+            # *** FIX: Removed the non-existent 'a.Time.nearest' attribute. ***
+            time_attr = a.Time(t - datetime.timedelta(minutes=5), t + datetime.timedelta(minutes=5))
             instrument = a.Instrument.hmi if "hmi" in channel else a.Instrument.aia
-            query = Fido.search(time_attr, instrument, physobs, sample, a.Time.nearest==True)
+            query = Fido.search(time_attr, instrument, physobs, sample)
             
-            if not query: raise ValueError(f"No data found for {channel} near {t}")
-            files = Fido.fetch(query, path="./data/sdo_cache")
+            if not query: raise ValueError(f"No data found for {channel} near {t}. Try a slightly different time.")
+            # We fetch the first result, which is the closest match within the window.
+            files = Fido.fetch(query[0,0], path="./data/sdo_cache")
             data_maps[t][channel] = sunpy.map.Map(files[0])
             
     yield "✅ All files downloaded. Starting preprocessing..."
@@ -138,7 +140,6 @@ def fetch_and_process_sdo_data(target_dt, forecast_horizon_minutes):
             if exp_time is None or exp_time <= 0: exp_time = 1.0
             norm_data = reprojected_data / exp_time
 
-            # *** FIX: Corrected the syntax error on this line ***
             scaled_data = scaler.transform(norm_data.reshape(-1, 1), c_idx=i).reshape(norm_data.shape)
             channel_tensors.append(torch.from_numpy(scaled_data.astype(np.float32)))
         processed_tensors[t] = torch.stack(channel_tensors)