Update app.py

app.py

@@ -109,37 +109,55 @@ def update_analytics_plots_figures(token_state_value, date_filter_option, custom
     
     plot_figs = []
     try:
-        # Generate plots, ensuring all 19 slots are potentially filled
-        plot_fns_args = [
-            (generate_followers_count_over_time_plot, [date_filtered_follower_stats_df, 'follower_gains_monthly']),
-            (generate_followers_growth_rate_plot, [date_filtered_follower_stats_df, 'follower_gains_monthly']),
-            (generate_followers_by_demographics_plot, [raw_follower_stats_df, 'follower_geo', "Follower per Località"]),
-            (generate_followers_by_demographics_plot, [raw_follower_stats_df, 'follower_function', "Follower per Ruolo"]),
-            (generate_followers_by_demographics_plot, [raw_follower_stats_df, 'follower_industry', "Follower per Settore"]),
-            (generate_followers_by_demographics_plot, [raw_follower_stats_df, 'follower_seniority', "Follower per Anzianità"]),
-            (generate_engagement_rate_over_time_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_reach_over_time_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_impressions_over_time_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_likes_over_time_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_clicks_over_time_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_shares_over_time_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_comments_over_time_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_comments_sentiment_breakdown_plot, [filtered_merged_posts_df, 'comment_sentiment']),
-            (generate_post_frequency_plot, [filtered_merged_posts_df, date_column_posts]),
-            (generate_content_format_breakdown_plot, [filtered_merged_posts_df, media_type_col_name]),
-            (generate_content_topic_breakdown_plot, [filtered_merged_posts_df, eb_labels_col_name]),
-            (generate_mentions_activity_plot, [filtered_mentions_df, date_column_mentions]), # Shared for mention_analysis_volume
-            (generate_mention_sentiment_plot, [filtered_mentions_df]) # Shared for mention_analysis_sentiment
+        # Define plot functions and their arguments
+        # Order matters and must match plot_configs
+        plot_definitions = [
+            {"func": generate_followers_count_over_time_plot, "args": [date_filtered_follower_stats_df, 'follower_gains_monthly'], "is_demographic": False},
+            {"func": generate_followers_growth_rate_plot, "args": [date_filtered_follower_stats_df, 'follower_gains_monthly'], "is_demographic": False},
+            {"func": generate_followers_by_demographics_plot, "args": [raw_follower_stats_df, 'follower_geo', "Follower per Località"], "type_value_key": "follower_geo", "is_demographic": True},
+            {"func": generate_followers_by_demographics_plot, "args": [raw_follower_stats_df, 'follower_function', "Follower per Ruolo"], "type_value_key": "follower_function", "is_demographic": True},
+            {"func": generate_followers_by_demographics_plot, "args": [raw_follower_stats_df, 'follower_industry', "Follower per Settore"], "type_value_key": "follower_industry", "is_demographic": True},
+            {"func": generate_followers_by_demographics_plot, "args": [raw_follower_stats_df, 'follower_seniority', "Follower per Anzianità"], "type_value_key": "follower_seniority", "is_demographic": True},
+            {"func": generate_engagement_rate_over_time_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_reach_over_time_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_impressions_over_time_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_likes_over_time_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_clicks_over_time_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_shares_over_time_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_comments_over_time_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_comments_sentiment_breakdown_plot, "args": [filtered_merged_posts_df, 'comment_sentiment'], "is_demographic": False},
+            {"func": generate_post_frequency_plot, "args": [filtered_merged_posts_df, date_column_posts], "is_demographic": False},
+            {"func": generate_content_format_breakdown_plot, "args": [filtered_merged_posts_df, media_type_col_name], "is_demographic": False},
+            {"func": generate_content_topic_breakdown_plot, "args": [filtered_merged_posts_df, eb_labels_col_name], "is_demographic": False},
+            {"func": generate_mentions_activity_plot, "args": [filtered_mentions_df, date_column_mentions], "is_demographic": False},
+            {"func": generate_mention_sentiment_plot, "args": [filtered_mentions_df], "is_demographic": False}
         ]
 
-        for i, (plot_fn, args) in enumerate(plot_fns_args):
+        for i, plot_def in enumerate(plot_definitions):
+            plot_fn = plot_def["func"]
+            args = plot_def["args"]
+            plot_title_for_error = args[2] if plot_def["is_demographic"] else plot_fn.__name__
             try:
+                # Specific check for demographic plots if raw_follower_stats_df is empty or missing key columns
+                if plot_def["is_demographic"]:
+                    df_arg = args[0] # raw_follower_stats_df
+                    type_val_col = plot_def["type_value_key"]
+                    if df_arg is None or df_arg.empty:
+                        logging.warning(f"raw_follower_stats_df is empty. Cannot generate demographic plot: {plot_title_for_error}")
+                        raise ValueError(f"Dati demografici mancanti (raw_follower_stats_df vuoto).")
+                    if type_val_col not in df_arg.columns:
+                        logging.warning(f"Colonna '{type_val_col}' mancante in raw_follower_stats_df per il grafico '{plot_title_for_error}'. Colonne disponibili: {df_arg.columns.tolist()}")
+                        raise KeyError(f"Colonna dati '{type_val_col}' non trovata.")
+                
                 fig = plot_fn(*args)
                 plot_figs.append(fig)
-            except Exception as plot_e:
-                logging.error(f"Error generating plot for slot {i} ({plot_fn.__name__}): {plot_e}", exc_info=True)
-                plot_figs.append(create_placeholder_plot(title=f"Errore Grafico {i+1}", message=f"Dettaglio: {str(plot_e)[:100]}"))
-        
+            except (KeyError, ValueError) as plot_e: # Catch KeyError for missing columns, ValueError for other data issues
+                logging.error(f"Errore generazione grafico '{plot_title_for_error}' (slot {i}): {plot_e}", exc_info=False) # Set exc_info to False for cleaner logs for known data issues
+                plot_figs.append(create_placeholder_plot(title=f"Errore Dati: {plot_title_for_error}", message=f"Impossibile generare: {str(plot_e)}"))
+            except Exception as plot_e: # Catch other unexpected errors
+                logging.error(f"Errore imprevisto generazione grafico '{plot_title_for_error}' (slot {i}): {plot_e}", exc_info=True)
+                plot_figs.append(create_placeholder_plot(title=f"Errore Grafico: {plot_title_for_error}", message=f"Dettaglio: {str(plot_e)[:100]}"))
+
         message = f"📊 Analisi aggiornate per il periodo: {date_filter_option}"
         if date_filter_option == "Intervallo Personalizzato": 
             s_display = start_dt_for_msg.strftime('%Y-%m-%d') if start_dt_for_msg else "Qualsiasi"
@@ -288,7 +306,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                         "I dettagli sulla formula/metodologia appariranno qui.", visible=False
                     )
 
-            async def handle_panel_action(
+            async def handle_panel_action( # This function is async
                 plot_id_clicked: str, 
                 action_type: str, 
                 current_active_action_from_state: dict, 
@@ -300,7 +318,12 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 clicked_plot_config = next((p for p in plot_configs if p["id"] == plot_id_clicked), None)
                 if not clicked_plot_config:
                     logging.error(f"Configurazione non trovata per plot_id {plot_id_clicked}")
-                    return [gr.update(visible=False)] * 7 + [current_active_action_from_state, current_chat_plot_id, current_chat_histories] + [gr.update() for _ in range(2 * len(plot_configs))]
+                    # Ensure we return the correct number of updates even on error
+                    num_button_updates = 2 * len(plot_configs)
+                    error_updates = [gr.update(visible=False)] * 10 # Updates for action column components
+                    error_updates.extend([current_active_action_from_state, current_chat_plot_id, current_chat_histories]) # States
+                    error_updates.extend([gr.update()] * num_button_updates) # Button icons
+                    return error_updates
 
                 clicked_plot_label = clicked_plot_config["label"]
                 
@@ -393,7 +416,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                     updated_chat_histories         
                 ] + all_button_icon_updates
                 
-                return final_updates
+                return final_updates # This list should have 13 + (19*2) = 51 items
 
             async def handle_chat_message_submission(
                 user_message: str, 
@@ -402,7 +425,6 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
             ):
                 if not current_plot_id or not user_message.strip():
                     history_for_plot = chat_histories.get(current_plot_id, [])
-                    # Corrected: Use yield and then a bare return for early exit in async generator
                     yield history_for_plot, "", chat_histories 
                     return
 
@@ -430,7 +452,6 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
             ):
                 if not current_plot_id or not suggestion_text.strip():
                     history_for_plot = chat_histories.get(current_plot_id, [])
-                    # Corrected: Use yield and then a bare return for early exit in async generator
                     yield history_for_plot, "", chat_histories 
                     return
 
@@ -525,14 +546,16 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 plot_label = config_item["label"] 
                 if plot_id in plot_ui_objects:
                     ui_obj = plot_ui_objects[plot_id]
+                    # FIX: Make lambda async and await the call to handle_panel_action
                     ui_obj["bomb_button"].click(
-                        fn=lambda current_active_val, current_chats_val, current_chat_pid, p_id=plot_id: handle_panel_action(p_id, "insights", current_active_val, current_chats_val, current_chat_pid),
+                        fn=async lambda current_active_val, current_chats_val, current_chat_pid, p_id=plot_id: await handle_panel_action(p_id, "insights", current_active_val, current_chats_val, current_chat_pid),
                         inputs=action_click_inputs, 
                         outputs=action_panel_outputs_list,
                         api_name=f"action_insights_{plot_id}"
                     )
+                    # FIX: Make lambda async and await the call to handle_panel_action
                     ui_obj["formula_button"].click(
-                        fn=lambda current_active_val, current_chats_val, current_chat_pid, p_id=plot_id: handle_panel_action(p_id, "formula", current_active_val, current_chats_val, current_chat_pid),
+                        fn=async lambda current_active_val, current_chats_val, current_chat_pid, p_id=plot_id: await handle_panel_action(p_id, "formula", current_active_val, current_chats_val, current_chat_pid),
                         inputs=action_click_inputs,
                         outputs=action_panel_outputs_list,
                         api_name=f"action_formula_{plot_id}"