Stato sincronizzazione...
") dashboard_display_html = gr.HTML("Caricamento dashboard...
") org_urn_display.change( fn=initial_load_sequence, inputs=[url_user_token_display, org_urn_display, token_state], outputs=[status_box, token_state, sync_data_btn, dashboard_display_html], show_progress="full" ) with gr.TabItem("2️⃣ Analisi", id="tab_analytics"): gr.Markdown("## 📈 Analisi Performance LinkedIn") gr.Markdown("Seleziona un intervallo di date. Clicca i pulsanti (💣 Insights, ƒ Formula, 🧭 Esplora) su un grafico per azioni.") analytics_status_md = gr.Markdown("Stato analisi...") with gr.Row(): date_filter_selector = gr.Radio( ["Sempre", "Ultimi 7 Giorni", "Ultimi 30 Giorni", "Intervallo Personalizzato"], label="Seleziona Intervallo Date", value="Sempre", scale=3 ) with gr.Column(scale=2): # Ensure this column is defined for date pickers custom_start_date_picker = gr.DateTime(label="Data Inizio", visible=False, include_time=False, type="datetime") custom_end_date_picker = gr.DateTime(label="Data Fine", visible=False, include_time=False, type="datetime") apply_filter_btn = gr.Button("🔍 Applica Filtro & Aggiorna Analisi", variant="primary") def toggle_custom_date_pickers(selection): is_custom = selection == "Intervallo Personalizzato" return gr.update(visible=is_custom), gr.update(visible=is_custom) date_filter_selector.change( fn=toggle_custom_date_pickers, inputs=[date_filter_selector], outputs=[custom_start_date_picker, custom_end_date_picker] ) plot_configs = [ {"label": "Numero di Follower nel Tempo", "id": "followers_count", "section": "Dinamiche dei Follower"}, {"label": "Tasso di Crescita Follower", "id": "followers_growth_rate", "section": "Dinamiche dei Follower"}, {"label": "Follower per Località", "id": "followers_by_location", "section": "Demografia Follower"}, {"label": "Follower per Ruolo (Funzione)", "id": "followers_by_role", "section": "Demografia Follower"}, {"label": "Follower per Settore", "id": "followers_by_industry", "section": "Demografia Follower"}, {"label": "Follower per Anzianità", "id": "followers_by_seniority", "section": "Demografia Follower"}, {"label": "Tasso di Engagement nel Tempo", "id": "engagement_rate", "section": "Approfondimenti Performance Post"}, {"label": "Copertura nel Tempo", "id": "reach_over_time", "section": "Approfondimenti Performance Post"}, {"label": "Visualizzazioni nel Tempo", "id": "impressions_over_time", "section": "Approfondimenti Performance Post"}, {"label": "Reazioni (Like) nel Tempo", "id": "likes_over_time", "section": "Approfondimenti Performance Post"}, {"label": "Click nel Tempo", "id": "clicks_over_time", "section": "Engagement Dettagliato Post nel Tempo"}, {"label": "Condivisioni nel Tempo", "id": "shares_over_time", "section": "Engagement Dettagliato Post nel Tempo"}, {"label": "Commenti nel Tempo", "id": "comments_over_time", "section": "Engagement Dettagliato Post nel Tempo"}, {"label": "Ripartizione Commenti per Sentiment", "id": "comments_sentiment", "section": "Engagement Dettagliato Post nel Tempo"}, {"label": "Frequenza Post", "id": "post_frequency_cs", "section": "Analisi Strategia Contenuti"}, {"label": "Ripartizione Contenuti per Formato", "id": "content_format_breakdown_cs", "section": "Analisi Strategia Contenuti"}, {"label": "Ripartizione Contenuti per Argomenti", "id": "content_topic_breakdown_cs", "section": "Analisi Strategia Contenuti"}, {"label": "Volume Menzioni nel Tempo (Dettaglio)", "id": "mention_analysis_volume", "section": "Analisi Menzioni (Dettaglio)"}, {"label": "Ripartizione Menzioni per Sentiment (Dettaglio)", "id": "mention_analysis_sentiment", "section": "Analisi Menzioni (Dettaglio)"} ] assert len(plot_configs) == 19, "Mancata corrispondenza in plot_configs e grafici attesi." active_panel_action_state = gr.State(None) # Stores {"plot_id": "...", "type": "insights/formula"} explored_plot_id_state = gr.State(None) # Stores plot_id of the currently "explored" (maximized) plot plot_ui_objects = {} # Will be populated by build_analytics_tab_plot_area with gr.Row(equal_height=False): with gr.Column(scale=8) as plots_area_col: plot_ui_objects = build_analytics_tab_plot_area(plot_configs) # --- UPDATED GLOBAL ACTIONS COLUMN with CHATBOT --- with gr.Column(scale=4, visible=False) as global_actions_column_ui: # This column's visibility is controlled gr.Markdown("### 💡 Azioni Contestuali Grafico") # General title for the panel # Chatbot components (initially hidden) insights_chatbot_ui = gr.Chatbot( label="Chat Insights", type="messages", height=450, bubble_full_width=False, visible=False, show_label=False, placeholder="L'analisi AI del grafico apparirà qui. Fai domande di approfondimento!" ) insights_chat_input_ui = gr.Textbox( label="La tua domanda:", placeholder="Chiedi all'AI riguardo a questo grafico...", lines=2, visible=False, show_label=False ) with gr.Row(visible=False) as insights_suggestions_row_ui: insights_suggestion_1_btn = gr.Button(value="Suggerimento 1", size="sm", min_width=50) insights_suggestion_2_btn = gr.Button(value="Suggerimento 2", size="sm", min_width=50) insights_suggestion_3_btn = gr.Button(value="Suggerimento 3", size="sm", min_width=50) # Formula display component (initially hidden) formula_display_markdown_ui = gr.Markdown( "I dettagli sulla formula/metodologia appariranno qui.", visible=False ) # --- END UPDATED GLOBAL ACTIONS COLUMN --- # --- Event Handler for Insights (Chatbot) and Formula Buttons --- async def handle_panel_action( plot_id_clicked: str, action_type: str, # "insights" or "formula" current_active_action_from_state: dict, # Stored active action {"plot_id": ..., "type": ...} # token_state_val: dict, # No longer directly needed here for chat/formula text current_chat_histories: dict, # from chat_histories_st current_chat_plot_id: str # from current_chat_plot_id_st ): logging.info(f"Azione '{action_type}' per grafico: {plot_id_clicked}. Attualmente attivo: {current_active_action_from_state}") # Find the label for the clicked plot_id 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}") # Basic error feedback if needed, though this shouldn't happen if UI is built correctly 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))] clicked_plot_label = clicked_plot_config["label"] hypothetical_new_active_state = {"plot_id": plot_id_clicked, "type": action_type} is_toggling_off = current_active_action_from_state == hypothetical_new_active_state new_active_action_state_to_set = None action_col_visible_update = gr.update(visible=True) # Default visibility for components in the action column insights_chatbot_visible_update = gr.update(visible=False) insights_chat_input_visible_update = gr.update(visible=False) insights_suggestions_row_visible_update = gr.update(visible=False) formula_display_visible_update = gr.update(visible=False) # Chat-specific updates chatbot_content_update = gr.update() suggestion_1_update = gr.update() suggestion_2_update = gr.update() suggestion_3_update = gr.update() new_current_chat_plot_id = current_chat_plot_id # Preserve by default updated_chat_histories = current_chat_histories # Preserve by default # Formula-specific updates formula_content_update = gr.update() if is_toggling_off: new_active_action_state_to_set = None action_col_visible_update = gr.update(visible=False) new_current_chat_plot_id = None # Clear active chat plot ID when panel closes logging.info(f"Chiusura pannello {action_type} per {plot_id_clicked}") else: new_active_action_state_to_set = hypothetical_new_active_state if action_type == "insights": insights_chatbot_visible_update = gr.update(visible=True) insights_chat_input_visible_update = gr.update(visible=True) insights_suggestions_row_visible_update = gr.update(visible=True) new_current_chat_plot_id = plot_id_clicked chat_history_for_this_plot = current_chat_histories.get(plot_id_clicked, []) if not chat_history_for_this_plot: # First time opening chat for this plot initial_insight_msg, suggestions = get_initial_insight_and_suggestions(plot_id_clicked, clicked_plot_label) chat_history_for_this_plot = [initial_insight_msg] updated_chat_histories = current_chat_histories.copy() updated_chat_histories[plot_id_clicked] = chat_history_for_this_plot else: # History exists, get suggestions again (or could store them) _, suggestions = get_initial_insight_and_suggestions(plot_id_clicked, clicked_plot_label) chatbot_content_update = gr.update(value=chat_history_for_this_plot) suggestion_1_update = gr.update(value=suggestions[0]) suggestion_2_update = gr.update(value=suggestions[1]) suggestion_3_update = gr.update(value=suggestions[2]) logging.info(f"Apertura pannello CHAT per {plot_id_clicked} ('{clicked_plot_label}')") elif action_type == "formula": formula_display_visible_update = gr.update(visible=True) formula_key = PLOT_ID_TO_FORMULA_KEY_MAP.get(plot_id_clicked) formula_text = f"**Formula/Metodologia per: {clicked_plot_label}**\n\nID Grafico: `{plot_id_clicked}`.\n\n" if formula_key and formula_key in PLOT_FORMULAS: formula_data = PLOT_FORMULAS[formula_key] formula_text += f"### {formula_data['title']}\n\n" formula_text += f"**Descrizione:**\n{formula_data['description']}\n\n" formula_text += "**Come viene calcolato:**\n" for step in formula_data['calculation_steps']: formula_text += f"- {step}\n" else: formula_text += "(Nessuna informazione dettagliata sulla formula trovata per questo ID grafico in `formulas.py`)" formula_content_update = gr.update(value=formula_text) new_current_chat_plot_id = None # Clear active chat plot ID when formula panel opens logging.info(f"Apertura pannello FORMULA per {plot_id_clicked} (mappato a {formula_key})") # Update button icons all_button_icon_updates = [] for cfg_item in plot_configs: p_id_iter = cfg_item["id"] # Insights (Bomb) button if new_active_action_state_to_set == {"plot_id": p_id_iter, "type": "insights"}: all_button_icon_updates.append(gr.update(value=ACTIVE_ICON)) else: all_button_icon_updates.append(gr.update(value=BOMB_ICON)) # Formula button if new_active_action_state_to_set == {"plot_id": p_id_iter, "type": "formula"}: all_button_icon_updates.append(gr.update(value=ACTIVE_ICON)) else: all_button_icon_updates.append(gr.update(value=FORMULA_ICON)) final_updates = [ action_col_visible_update, insights_chatbot_visible_update, chatbot_content_update, insights_chat_input_visible_update, insights_suggestions_row_visible_update, suggestion_1_update, suggestion_2_update, suggestion_3_update, formula_display_visible_update, formula_content_update, new_active_action_state_to_set, # For active_panel_action_state new_current_chat_plot_id, # For current_chat_plot_id_st updated_chat_histories # For chat_histories_st ] + all_button_icon_updates return final_updates # --- Event Handler for Chat Message Submission --- async def handle_chat_message_submission( user_message: str, current_plot_id: str, # From current_chat_plot_id_st chat_histories: dict, # From chat_histories_st # token_state_val: dict # If needed for context, but LLM should get context from history ): if not current_plot_id or not user_message.strip(): # Return current history for the plot_id if message is empty history_for_plot = chat_histories.get(current_plot_id, []) return history_for_plot, "", chat_histories # Chatbot, Textbox, Histories State # Find plot label for context plot_config = next((p for p in plot_configs if p["id"] == current_plot_id), None) plot_label = plot_config["label"] if plot_config else "Grafico Selezionato" history_for_plot = chat_histories.get(current_plot_id, []).copy() history_for_plot.append({"role": "user", "content": user_message}) # Show user message immediately yield history_for_plot, "", chat_histories # Update chatbot, clear input, keep histories # Generate bot response bot_response_text = await generate_llm_response(user_message, current_plot_id, plot_label, history_for_plot) history_for_plot.append({"role": "assistant", "content": bot_response_text}) updated_chat_histories = chat_histories.copy() updated_chat_histories[current_plot_id] = history_for_plot yield history_for_plot, "", updated_chat_histories # Final update # --- Event Handler for Suggested Question Click --- async def handle_suggested_question_click( suggestion_text: str, current_plot_id: str, # From current_chat_plot_id_st chat_histories: dict, # From chat_histories_st # token_state_val: dict ): # This will effectively call handle_chat_message_submission # We need to ensure the output signature matches what Gradio expects for this button's .click event # which is the same as handle_chat_message_submission's output. # The 'yield' pattern is for streaming, if handle_chat_message_submission uses it, this should too. # Simulate the submission process if not current_plot_id or not suggestion_text.strip(): history_for_plot = chat_histories.get(current_plot_id, []) return history_for_plot, "", chat_histories plot_config = next((p for p in plot_configs if p["id"] == current_plot_id), None) plot_label = plot_config["label"] if plot_config else "Grafico Selezionato" history_for_plot = chat_histories.get(current_plot_id, []).copy() history_for_plot.append({"role": "user", "content": suggestion_text}) yield history_for_plot, "", chat_histories # Update chatbot, clear input (though no input here), keep histories bot_response_text = await generate_llm_response(suggestion_text, current_plot_id, plot_label, history_for_plot) history_for_plot.append({"role": "assistant", "content": bot_response_text}) updated_chat_histories = chat_histories.copy() updated_chat_histories[current_plot_id] = history_for_plot yield history_for_plot, "", updated_chat_histories # --- Explore button logic (remains largely the same) --- def handle_explore_click(plot_id_clicked, current_explored_plot_id_from_state): # (This function's logic for showing/hiding plot panels based on explore state) # ... (original logic from user's code) ... logging.info(f"Click su Esplora per: {plot_id_clicked}. Attualmente esplorato da stato: {current_explored_plot_id_from_state}") if not plot_ui_objects: logging.error("plot_ui_objects non popolato durante handle_explore_click.") # Need to return updates for all explore buttons and panels updates_for_missing_ui = [current_explored_plot_id_from_state] for _ in plot_configs: updates_for_missing_ui.extend([gr.update(), gr.update()]) # panel, button return updates_for_missing_ui new_explored_id_to_set = None is_toggling_off = (plot_id_clicked == current_explored_plot_id_from_state) if is_toggling_off: new_explored_id_to_set = None logging.info(f"Interruzione esplorazione grafico: {plot_id_clicked}") else: new_explored_id_to_set = plot_id_clicked logging.info(f"Esplorazione grafico: {plot_id_clicked}") panel_and_button_updates = [] for cfg in plot_configs: p_id = cfg["id"] if p_id in plot_ui_objects: panel_visible = not new_explored_id_to_set or (p_id == new_explored_id_to_set) panel_and_button_updates.append(gr.update(visible=panel_visible)) # Panel component if p_id == new_explored_id_to_set: # Explored button icon panel_and_button_updates.append(gr.update(value=ACTIVE_ICON)) else: panel_and_button_updates.append(gr.update(value=EXPLORE_ICON)) else: # Should not happen if UI built correctly panel_and_button_updates.extend([gr.update(), gr.update()]) final_updates = [new_explored_id_to_set] + panel_and_button_updates # state + N*(panel_update, button_update) return final_updates # --- Define output lists for event handlers --- # Outputs for handle_panel_action (insights/formula clicks) action_panel_outputs_list = [ global_actions_column_ui, # Column visibility insights_chatbot_ui, insights_chatbot_ui, # Visibility, Content for chatbot insights_chat_input_ui, # Visibility for chat input insights_suggestions_row_ui, insights_suggestion_1_btn, insights_suggestion_2_btn, insights_suggestion_3_btn, # Row visibility, button content formula_display_markdown_ui, formula_display_markdown_ui, # Visibility, Content for formula active_panel_action_state, current_chat_plot_id_st, chat_histories_st ] for cfg_item_action in plot_configs: # Add bomb and formula button icon updates pid_action = cfg_item_action["id"] if pid_action in plot_ui_objects: action_panel_outputs_list.append(plot_ui_objects[pid_action]["bomb_button"]) action_panel_outputs_list.append(plot_ui_objects[pid_action]["formula_button"]) else: # Should not happen action_panel_outputs_list.extend([None, None]) # Outputs for handle_explore_click explore_buttons_outputs_list = [explored_plot_id_state] for cfg_item_explore in plot_configs: pid_explore = cfg_item_explore["id"] if pid_explore in plot_ui_objects: explore_buttons_outputs_list.append(plot_ui_objects[pid_explore]["panel_component"]) explore_buttons_outputs_list.append(plot_ui_objects[pid_explore]["explore_button"]) else: # Should not happen explore_buttons_outputs_list.extend([None, None]) # Inputs for action clicks (insights/formula) action_click_inputs = [ active_panel_action_state, # token_state, # No longer passing full token_state if not needed by handle_panel_action chat_histories_st, current_chat_plot_id_st ] # Inputs for explore clicks explore_click_inputs = [explored_plot_id_state] # Wire up action and explore buttons for config_item in plot_configs: plot_id = config_item["id"] plot_label = config_item["label"] # Get label for context if plot_id in plot_ui_objects: ui_obj = plot_ui_objects[plot_id] # Insights (Bomb) Button 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), inputs=action_click_inputs, # current_active_action_from_state, current_chat_histories, current_chat_plot_id outputs=action_panel_outputs_list, api_name=f"action_insights_{plot_id}" ) # Formula Button 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), inputs=action_click_inputs, outputs=action_panel_outputs_list, api_name=f"action_formula_{plot_id}" ) # Explore Button ui_obj["explore_button"].click( fn=lambda current_explored_val, p_id=plot_id: handle_explore_click(p_id, current_explored_val), inputs=explore_click_inputs, outputs=explore_buttons_outputs_list, api_name=f"action_explore_{plot_id}" ) else: logging.warning(f"Oggetto UI per plot_id '{plot_id}' non trovato durante il tentativo di associare i gestori di click.") # Wire up chat input submission chat_submission_outputs = [insights_chatbot_ui, insights_chat_input_ui, chat_histories_st] insights_chat_input_ui.submit( fn=handle_chat_message_submission, inputs=[insights_chat_input_ui, current_chat_plot_id_st, chat_histories_st], # token_state removed outputs=chat_submission_outputs, api_name="submit_chat_message" ) # Wire up suggested question buttons insights_suggestion_1_btn.click( fn=handle_suggested_question_click, inputs=[insights_suggestion_1_btn, current_chat_plot_id_st, chat_histories_st], # token_state removed outputs=chat_submission_outputs, # Same outputs as direct message submission api_name="click_suggestion_1" ) insights_suggestion_2_btn.click( fn=handle_suggested_question_click, inputs=[insights_suggestion_2_btn, current_chat_plot_id_st, chat_histories_st], # token_state removed outputs=chat_submission_outputs, api_name="click_suggestion_2" ) insights_suggestion_3_btn.click( fn=handle_suggested_question_click, inputs=[insights_suggestion_3_btn, current_chat_plot_id_st, chat_histories_st], # token_state removed outputs=chat_submission_outputs, api_name="click_suggestion_3" ) # --- Function to refresh all analytics UI elements (plots and action panel states) --- def refresh_all_analytics_ui_elements(current_token_state, date_filter_val, custom_start_val, custom_end_val, current_chat_histories): logging.info("Aggiornamento di tutti gli elementi UI delle analisi e reset delle azioni/chat.") plot_generation_results = update_analytics_plots_figures( current_token_state, date_filter_val, custom_start_val, custom_end_val ) status_message_update = plot_generation_results[0] generated_plot_figures = plot_generation_results[1:] all_updates = [status_message_update] # For analytics_status_md # Add plot figure updates for i in range(len(plot_configs)): if i < len(generated_plot_figures): all_updates.append(generated_plot_figures[i]) # Plot component else: # Should not happen if update_analytics_plots_figures is correct all_updates.append(create_placeholder_plot("Errore Figura", f"Figura mancante per grafico {plot_configs[i]['id']}")) # Reset global actions column and its content all_updates.extend([ gr.update(visible=False), # global_actions_column_ui gr.update(value=[], visible=False), # insights_chatbot_ui (clear history, hide) gr.update(value="", visible=False), # insights_chat_input_ui (clear text, hide) gr.update(visible=False), # insights_suggestions_row_ui gr.update(value="Suggerimento 1", visible=True), # insights_suggestion_1_btn (reset text, keep visible within hidden row) gr.update(value="Suggerimento 2", visible=True), # insights_suggestion_2_btn gr.update(value="Suggerimento 3", visible=True), # insights_suggestion_3_btn gr.update(value="I dettagli sulla formula/metodologia appariranno qui.", visible=False), # formula_display_markdown_ui None, # active_panel_action_state (reset to None) None, # current_chat_plot_id_st (reset to None) current_chat_histories, # chat_histories_st (preserve existing histories across refresh unless explicitly cleared) # If you want to clear all chats on refresh: use `{}` instead of current_chat_histories ]) # Reset action buttons (bomb, formula, explore icons) and plot panel visibility (for explore) for cfg in plot_configs: pid = cfg["id"] if pid in plot_ui_objects: all_updates.append(gr.update(value=BOMB_ICON)) # bomb_button all_updates.append(gr.update(value=FORMULA_ICON)) # formula_button all_updates.append(gr.update(value=EXPLORE_ICON)) # explore_button all_updates.append(gr.update(visible=True)) # panel_component (reset to default visibility) else: # Should not happen all_updates.extend([None, None, None, None]) all_updates.append(None) # explored_plot_id_state (reset to None) logging.info(f"Preparati {len(all_updates)} aggiornamenti per il refresh completo delle analisi.") return all_updates # Define the output list for apply_filter_btn and sync events that refresh analytics apply_filter_and_sync_outputs_list = [analytics_status_md] # Status message # Add plot components for config_item_filter_sync in plot_configs: pid_filter_sync = config_item_filter_sync["id"] if pid_filter_sync in plot_ui_objects and "plot_component" in plot_ui_objects[pid_filter_sync]: apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync]["plot_component"]) else: apply_filter_and_sync_outputs_list.append(None) # Placeholder if UI object not found # Add updates for the global actions column and its contents + states apply_filter_and_sync_outputs_list.extend([ global_actions_column_ui, # Column visibility insights_chatbot_ui, # Chatbot content and visibility insights_chat_input_ui, # Chat input text and visibility insights_suggestions_row_ui, # Suggestions row visibility insights_suggestion_1_btn, # Suggestion button 1 text/visibility insights_suggestion_2_btn, # Suggestion button 2 text/visibility insights_suggestion_3_btn, # Suggestion button 3 text/visibility formula_display_markdown_ui, # Formula markdown content and visibility active_panel_action_state, # State for active panel current_chat_plot_id_st, # State for current chat plot ID chat_histories_st # State for all chat histories ]) # Add updates for individual plot action buttons (bomb, formula, explore) and plot panels (explore visibility) for cfg_filter_sync_btns in plot_configs: pid_filter_sync_btns = cfg_filter_sync_btns["id"] if pid_filter_sync_btns in plot_ui_objects: apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync_btns]["bomb_button"]) apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync_btns]["formula_button"]) apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync_btns]["explore_button"]) apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync_btns]["panel_component"]) # For explore visibility else: apply_filter_and_sync_outputs_list.extend([None, None, None, None]) # Placeholders apply_filter_and_sync_outputs_list.append(explored_plot_id_state) # State for explored plot ID logging.info(f"Output totali definiti per apply_filter/sync: {len(apply_filter_and_sync_outputs_list)}") apply_filter_btn.click( fn=refresh_all_analytics_ui_elements, inputs=[token_state, date_filter_selector, custom_start_date_picker, custom_end_date_picker, chat_histories_st], outputs=apply_filter_and_sync_outputs_list, show_progress="full" ) with gr.TabItem("3️⃣ Menzioni", id="tab_mentions"): refresh_mentions_display_btn = gr.Button("🔄 Aggiorna Visualizzazione Menzioni", variant="secondary") mentions_html = gr.HTML("Dati menzioni...") mentions_sentiment_dist_plot = gr.Plot(label="Distribuzione Sentiment Menzioni") refresh_mentions_display_btn.click( fn=run_mentions_tab_display, inputs=[token_state], outputs=[mentions_html, mentions_sentiment_dist_plot], show_progress="full" ) with gr.TabItem("4️⃣ Statistiche Follower", id="tab_follower_stats"): refresh_follower_stats_btn = gr.Button("🔄 Aggiorna Visualizzazione Statistiche Follower", variant="secondary") follower_stats_html = gr.HTML("Statistiche follower...") with gr.Row(): # Ensure plots are within rows or columns for layout fs_plot_monthly_gains = gr.Plot(label="Guadagni Mensili Follower") with gr.Row(): fs_plot_seniority = gr.Plot(label="Follower per Anzianità (Top 10 Organici)") fs_plot_industry = gr.Plot(label="Follower per Settore (Top 10 Organici)") refresh_follower_stats_btn.click( fn=run_follower_stats_tab_display, inputs=[token_state], outputs=[follower_stats_html, fs_plot_monthly_gains, fs_plot_seniority, fs_plot_industry], show_progress="full" ) # Sync data flow sync_event_part1 = sync_data_btn.click( fn=sync_all_linkedin_data_orchestrator, inputs=[token_state], outputs=[sync_status_html_output, token_state], show_progress="full" ) sync_event_part2 = sync_event_part1.then( # Use .then() for sequential execution fn=process_and_store_bubble_token, # This function was defined in state_manager.py inputs=[url_user_token_display, org_urn_display, token_state], outputs=[status_box, token_state, sync_data_btn], show_progress=False # Assuming this is correct from original ) sync_event_part3 = sync_event_part2.then( fn=display_main_dashboard, # This function was defined in ui_generators.py inputs=[token_state], outputs=[dashboard_display_html], show_progress=False ) # After sync, refresh analytics tab including plots and resetting chat/formula panels sync_event_final = sync_event_part3.then( fn=refresh_all_analytics_ui_elements, inputs=[token_state, date_filter_selector, custom_start_date_picker, custom_end_date_picker, chat_histories_st], outputs=apply_filter_and_sync_outputs_list, # Use the comprehensive list show_progress="full" ) if __name__ == "__main__": if not os.environ.get(LINKEDIN_CLIENT_ID_ENV_VAR): logging.warning(f"ATTENZIONE: Variabile d'ambiente '{LINKEDIN_CLIENT_ID_ENV_VAR}' non impostata.") if not os.environ.get(BUBBLE_APP_NAME_ENV_VAR) or \ not os.environ.get(BUBBLE_API_KEY_PRIVATE_ENV_VAR) or \ not os.environ.get(BUBBLE_API_ENDPOINT_ENV_VAR): logging.warning("ATTENZIONE: Variabili d'ambiente Bubble non completamente impostate.") try: logging.info(f"Versione Matplotlib: {matplotlib.__version__}, Backend: {matplotlib.get_backend()}") except ImportError: # Matplotlib might not be an explicit import if only used by plot generators logging.warning("Matplotlib non trovato direttamente, ma potrebbe essere usato dai generatori di grafici.") app.launch(server_name="0.0.0.0", server_port=7860, debug=True)