Update app.py

app.py

@@ -314,6 +314,40 @@ def generate_pdf_content(summary, preview_df, anomalies, amc_reminders, insights
         logging.error(f"Failed to generate PDF: {str(e)}")
         return None
 
+# Update filters
+def update_filters(current_file_path, cached_df_state):
+    try:
+        if not current_file_path or cached_df_state is None:
+            logging.warning("No file or cached DataFrame available for filter update")
+            return gr.update(choices=['All'], value='All'), gr.update(choices=['All'], value='All')
+        
+        df = cached_df_state
+        if df.empty:
+            logging.warning("Cached DataFrame is empty")
+            return gr.update(choices=['All'], value='All'), gr.update(choices=['All'], value='All')
+
+        lab_site_options = ['All']
+        if 'lab_site' in df.columns:
+            sites = df['lab_site'].dropna().astype(str).unique().tolist()
+            lab_site_options.extend([site for site in sites if site.strip()])
+            logging.info(f"Lab site options populated: {lab_site_options}")
+
+        equipment_type_options = ['All']
+        if 'equipment_type' in df.columns:
+            types = df['equipment_type'].dropna().astype(str).unique().tolist()
+            equipment_type_options.extend([t for t in types if t.strip()])
+            logging.info(f"Equipment type options populated: {equipment_type_options}")
+
+        if len(lab_site_options) == 1:
+            logging.warning("No valid lab_site values found in DataFrame")
+        if len(equipment_type_options) == 1:
+            logging.warning("No valid equipment_type values found in DataFrame")
+
+        return gr.update(choices=lab_site_options, value='All'), gr.update(choices=equipment_type_options, value='All')
+    except Exception as e:
+        logging.error(f"Failed to update filters: {str(e)}")
+        return gr.update(choices=['All'], value='All'), gr.update(choices=['All'], value='All')
+
 # Main processing function
 async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_range, last_modified_state, cached_df_state, cached_filtered_df_state, current_file_path):
     start_time = time.time()
@@ -437,20 +471,6 @@ async def generate_pdf(summary, preview_html, usage_chart, device_cards, daily_l
         logging.error(f"Failed to generate PDF: {str(e)}")
         return None
 
-# Update filters
-def update_filters(current_file_path, cached_df_state):
-    if not current_file_path or not cached_df_state:
-        logging.warning("No file or cached DataFrame available for filter update")
-        return gr.update(choices=['All'], value='All'), gr.update(choices=['All'], value='All')
-    try:
-        df = cached_df_state
-        lab_site_options = ['All'] + [site for site in df['lab_site'].dropna().astype(str).unique().tolist() if site.strip()] if 'lab_site' in df.columns else ['All']
-        equipment_type_options = ['All'] + [equip for equip in df['equipment_type'].dropna().astype(str).unique().tolist() if equip.strip()] if 'equipment_type' in df.columns else ['All']
-        return gr.update(choices=lab_site_options, value='All'), gr.update(choices=equipment_type_options, value='All')
-    except Exception as e:
-        logging.error(f"Failed to update filters: {str(e)}")
-        return gr.update(choices=['All'], value='All'), gr.update(choices=['All'], value='All')
-
 # Gradio Interface
 try:
     logging.info("Initializing Gradio interface...")
@@ -528,15 +548,16 @@ try:
             inputs=[file_input, cached_df_state, current_file_path],
             outputs=[current_file_path, cached_df_state, current_file_path],
             queue=False
+        ).then(
+            fn=process_logs,
+            inputs=[file_input, lab_site_filter, equipment_type_filter, date_range_filter, last_modified_state, cached_df_state, cached_filtered_df_state, current_file_path],
+            outputs=[summary_output, preview_output, usage_chart_output, device_cards_output, daily_log_trends_output, weekly_uptime_output, anomaly_alerts_output, downtime_chart_output, anomaly_output, amc_output, insights_output, pdf_output, last_modified_state, cached_df_state, cached_filtered_df_state, current_file_path],
+            queue=False
         ).then(
             fn=update_filters,
             inputs=[current_file_path, cached_df_state],
             outputs=[lab_site_filter, equipment_type_filter],
             queue=False
-        ).then(
-            fn=process_logs,
-            inputs=[file_input, lab_site_filter, equipment_type_filter, date_range_filter, last_modified_state, cached_df_state, cached_filtered_df_state, current_file_path],
-            outputs=[summary_output, preview_output, usage_chart_output, device_cards_output, daily_log_trends_output, weekly_uptime_output, anomaly_alerts_output, downtime_chart_output, anomaly_output, amc_output, insights_output, pdf_output, last_modified_state, cached_df_state, cached_filtered_df_state, current_file_path]
         )
 
         # Process logs on submit or filter change