# app.py
# (Showing relevant parts that need modification)
import gradio as gr
import pandas as pd
import os
import logging
import matplotlib
matplotlib.use('Agg') # Set backend for Matplotlib to avoid GUI conflicts with Gradio
import matplotlib.pyplot as plt
import time # For profiling if needed
from datetime import datetime, timedelta # Added timedelta
import numpy as np
from collections import OrderedDict # To maintain section order

# --- Module Imports ---
from gradio_utils import get_url_user_token
# Functions from newly created/refactored modules
from config import (
    LINKEDIN_CLIENT_ID_ENV_VAR, BUBBLE_APP_NAME_ENV_VAR,
    BUBBLE_API_KEY_PRIVATE_ENV_VAR, BUBBLE_API_ENDPOINT_ENV_VAR,
    PLOT_ID_TO_FORMULA_KEY_MAP)
from state_manager import process_and_store_bubble_token
from sync_logic import sync_all_linkedin_data_orchestrator
from ui_generators import (
    display_main_dashboard,
    run_mentions_tab_display,
    run_follower_stats_tab_display,
    build_analytics_tab_plot_area, # EXPECTED TO RETURN: plot_ui_objects, section_titles_map
    BOMB_ICON, EXPLORE_ICON, FORMULA_ICON, ACTIVE_ICON,
    create_placeholder_plot # Assuming you have this or similar for error cases
)
from analytics_plot_generator import update_analytics_plots_figures
from formulas import PLOT_FORMULAS

# --- NEW CHATBOT MODULE IMPORTS ---
from chatbot_prompts import get_initial_insight_prompt_and_suggestions # MODIFIED IMPORT
from chatbot_handler import generate_llm_response
# --- END NEW CHATBOT MODULE IMPORTS ---

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(module)s - %(message)s')


# --- Gradio UI Blocks ---
with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
               title="LinkedIn Organization Dashboard") as app:
    token_state = gr.State(value={
        "token": None, "client_id": None, "org_urn": None,
        "bubble_posts_df": pd.DataFrame(), "bubble_post_stats_df": pd.DataFrame(),
        "bubble_mentions_df": pd.DataFrame(), "bubble_follower_stats_df": pd.DataFrame(),
        "fetch_count_for_api": 0, "url_user_token_temp_storage": None,
        "config_date_col_posts": "published_at", "config_date_col_mentions": "date",
        "config_date_col_followers": "date", "config_media_type_col": "media_type",
        "config_eb_labels_col": "li_eb_label"
    })

    chat_histories_st = gr.State({})
    current_chat_plot_id_st = gr.State(None)
    plot_data_for_chatbot_st = gr.State({})

    gr.Markdown("# 🚀 LinkedIn Organization Dashboard")
    url_user_token_display = gr.Textbox(label="User Token (Nascosto)", interactive=False, visible=False)
    status_box = gr.Textbox(label="Stato Generale Token LinkedIn", interactive=False, value="Inizializzazione...")
    org_urn_display = gr.Textbox(label="URN Organizzazione (Nascosto)", interactive=False, visible=False)

    app.load(fn=get_url_user_token, inputs=None, outputs=[url_user_token_display, org_urn_display], api_name="get_url_params", show_progress=False)

    def initial_load_sequence(url_token, org_urn_val, current_state):
        status_msg, new_state, btn_update = process_and_store_bubble_token(url_token, org_urn_val, current_state)
        dashboard_content = display_main_dashboard(new_state)
        return status_msg, new_state, btn_update, dashboard_content

    with gr.Tabs() as tabs:
        with gr.TabItem("1️⃣ Dashboard & Sync", id="tab_dashboard_sync"):
            gr.Markdown("Il sistema controlla i dati esistenti da Bubble. 'Sincronizza' si attiva se sono necessari nuovi dati.")
            sync_data_btn = gr.Button("🔄 Sincronizza Dati LinkedIn", variant="primary", visible=False, interactive=False)
            sync_status_html_output = gr.HTML("<p style='text-align:center;'>Stato sincronizzazione...</p>")
            dashboard_display_html = gr.HTML("<p style='text-align:center;'>Caricamento dashboard...</p>")

            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):
                    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."
            
            # Get unique section names in order of appearance in plot_configs
            unique_ordered_sections = list(OrderedDict.fromkeys(pc["section"] for pc in plot_configs))
            num_unique_sections = len(unique_ordered_sections)

            active_panel_action_state = gr.State(None)
            explored_plot_id_state = gr.State(None)

            # plot_ui_objects will store plot-specific UI like panels and buttons
            # section_titles_map will store Markdown components for section titles
            plot_ui_objects = {} 
            section_titles_map = {} # Expected to be populated by build_analytics_tab_plot_area

            with gr.Row(equal_height=False):
                with gr.Column(scale=8) as plots_area_col:
                    # IMPORTANT ASSUMPTION: build_analytics_tab_plot_area now returns a tuple:
                    # (dict_of_plot_ui_elements, dict_of_section_title_markdown_components)
                    # Ensure ui_generators.py is updated accordingly.
                    ui_elements_tuple = build_analytics_tab_plot_area(plot_configs)
                    if isinstance(ui_elements_tuple, tuple) and len(ui_elements_tuple) == 2:
                        plot_ui_objects = ui_elements_tuple[0]
                        section_titles_map = ui_elements_tuple[1]
                        # Verify section_titles_map contains all unique_ordered_sections
                        if not all(sec_name in section_titles_map for sec_name in unique_ordered_sections):
                            logging.error("section_titles_map from build_analytics_tab_plot_area is incomplete or missing keys for defined sections.")
                            # Fallback for safety, though this indicates an issue in ui_generators
                            for sec_name in unique_ordered_sections:
                                if sec_name not in section_titles_map:
                                     section_titles_map[sec_name] = gr.Markdown(f"## {sec_name} (Placeholder - Error)") # Placeholder
                    else:
                        logging.error("build_analytics_tab_plot_area did not return the expected tuple (plot_ui_objects, section_titles_map). Section titles will not work correctly.")
                        plot_ui_objects = ui_elements_tuple # Old behavior, section titles won't work
                        # Create placeholder section_titles_map to prevent crashes, but log error
                        for sec_name in unique_ordered_sections:
                            section_titles_map[sec_name] = gr.Markdown(f"## {sec_name} (Placeholder - Error)")


                with gr.Column(scale=4, visible=False) as global_actions_column_ui:
                    gr.Markdown("### 💡 Azioni Contestuali Grafico")
                    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_markdown_ui = gr.Markdown(
                        "I dettagli sulla formula/metodologia appariranno qui.", visible=False
                    )

            async def handle_panel_action(
                plot_id_clicked: str,
                action_type: str, 
                current_active_action_from_state: dict,
                current_chat_histories: dict,
                current_chat_plot_id: str,
                current_plot_data_for_chatbot: dict,
                current_explored_plot_id: str 
            ):
                logging.info(f"Azione '{action_type}' per grafico: {plot_id_clicked}. Attualmente attivo: {current_active_action_from_state}, Esplorato: {current_explored_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}")
                    num_plots = len(plot_configs)
                    error_output_list = [
                        gr.update(visible=False), gr.update(visible=False), gr.update(value=[]),
                        gr.update(visible=False), gr.update(visible=False), gr.update(), gr.update(), gr.update(),
                        gr.update(visible=False), gr.update(value=""),
                        current_active_action_from_state, current_chat_plot_id, current_chat_histories,
                        current_explored_plot_id 
                    ]
                    error_output_list.extend([gr.update()] * num_plots)  # Panel vis
                    error_output_list.extend([gr.update()] * (2 * num_plots))  # Bomb, Formula icons
                    error_output_list.extend([gr.update()] * num_plots)  # Explore icons
                    error_output_list.extend([gr.update()] * num_unique_sections) # Section title vis
                    return error_output_list

                clicked_plot_label = clicked_plot_config["label"]
                clicked_plot_section = clicked_plot_config["section"]
                hypothetical_new_active_state = {"plot_id": plot_id_clicked, "type": action_type}
                is_toggling_off = current_active_action_from_state == hypothetical_new_active_state

                action_col_visible_update = gr.update(visible=False)
                insights_chatbot_visible_update, insights_chat_input_visible_update, insights_suggestions_row_visible_update = gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
                formula_display_visible_update = gr.update(visible=False)
                chatbot_content_update, suggestion_1_update, suggestion_2_update, suggestion_3_update, formula_content_update = gr.update(), gr.update(), gr.update(), gr.update(), gr.update()
                
                new_active_action_state_to_set = None
                new_current_chat_plot_id = current_chat_plot_id
                updated_chat_histories = current_chat_histories
                new_explored_plot_id_to_set = current_explored_plot_id 

                panel_visibility_updates = []
                action_button_updates = [] 
                explore_button_updates = []
                section_title_visibility_updates = [gr.update()] * num_unique_sections


                if is_toggling_off:
                    new_active_action_state_to_set = None
                    action_col_visible_update = gr.update(visible=False)
                    logging.info(f"Chiusura pannello {action_type} per {plot_id_clicked}.")

                    if current_explored_plot_id: 
                        explored_plot_cfg = next((p for p in plot_configs if p["id"] == current_explored_plot_id), None)
                        explored_section_to_show = explored_plot_cfg["section"] if explored_plot_cfg else None
                        for i, sec_name in enumerate(unique_ordered_sections):
                            section_title_visibility_updates[i] = gr.update(visible=(sec_name == explored_section_to_show))
                        for cfg_item_iter in plot_configs:
                            is_explored = (cfg_item_iter["id"] == current_explored_plot_id)
                            panel_visibility_updates.append(gr.update(visible=is_explored))
                            explore_button_updates.append(gr.update(value=ACTIVE_ICON if is_explored else EXPLORE_ICON))
                    else: 
                        for i in range(num_unique_sections): section_title_visibility_updates[i] = gr.update(visible=True)
                        for _ in plot_configs:
                            panel_visibility_updates.append(gr.update(visible=True))
                            explore_button_updates.append(gr.update(value=EXPLORE_ICON))
                    
                    for _ in plot_configs: # Reset bomb/formula icons
                        action_button_updates.append(gr.update(value=BOMB_ICON))
                        action_button_updates.append(gr.update(value=FORMULA_ICON))
                    if action_type == "insights": new_current_chat_plot_id = None

                else: # Opening a new panel or switching
                    new_active_action_state_to_set = hypothetical_new_active_state
                    action_col_visible_update = gr.update(visible=True)
                    new_explored_plot_id_to_set = None # Cancel explore
                    
                    logging.info(f"Apertura pannello {action_type} per {plot_id_clicked}. Solo questo grafico visibile. Esplorazione annullata.")

                    for i, sec_name in enumerate(unique_ordered_sections): # Show only relevant section title
                        section_title_visibility_updates[i] = gr.update(visible=(sec_name == clicked_plot_section))

                    for cfg_item_iter in plot_configs: # Show only relevant plot panel
                        panel_visibility_updates.append(gr.update(visible=(cfg_item_iter["id"] == plot_id_clicked)))
                        explore_button_updates.append(gr.update(value=EXPLORE_ICON)) # Reset all explore buttons

                    for cfg_item_btn_iter in plot_configs: # Set active icons for bomb/formula
                        is_active_insights = new_active_action_state_to_set == {"plot_id": cfg_item_btn_iter["id"], "type": "insights"}
                        is_active_formula = new_active_action_state_to_set == {"plot_id": cfg_item_btn_iter["id"], "type": "formula"}
                        action_button_updates.append(gr.update(value=ACTIVE_ICON if is_active_insights else BOMB_ICON))
                        action_button_updates.append(gr.update(value=ACTIVE_ICON if is_active_formula else FORMULA_ICON))

                    if action_type == "insights":
                        insights_chatbot_visible_update, insights_chat_input_visible_update, insights_suggestions_row_visible_update = gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
                        new_current_chat_plot_id = plot_id_clicked
                        chat_history_for_this_plot = current_chat_histories.get(plot_id_clicked, [])
                        plot_specific_data_summary = current_plot_data_for_chatbot.get(plot_id_clicked, f"Nessun sommario dati specifico disponibile per '{clicked_plot_label}'.")
                        if not chat_history_for_this_plot:
                            initial_llm_prompt, suggestions = get_initial_insight_prompt_and_suggestions(plot_id_clicked, clicked_plot_label, plot_specific_data_summary)
                            history_for_llm_first_turn = [{"role": "user", "content": initial_llm_prompt}]
                            initial_bot_response_text = await generate_llm_response(initial_llm_prompt, plot_id_clicked, clicked_plot_label, history_for_llm_first_turn, plot_specific_data_summary)
                            chat_history_for_this_plot = [{"role": "assistant", "content": initial_bot_response_text}]
                            updated_chat_histories = {**current_chat_histories, plot_id_clicked: chat_history_for_this_plot}
                        else:
                            _, suggestions = get_initial_insight_prompt_and_suggestions(plot_id_clicked, clicked_plot_label, plot_specific_data_summary)
                        chatbot_content_update = gr.update(value=chat_history_for_this_plot)
                        suggestion_1_update, suggestion_2_update, suggestion_3_update = gr.update(value=suggestions[0] if suggestions else "N/A"), gr.update(value=suggestions[1] if len(suggestions) > 1 else "N/A"), gr.update(value=suggestions[2] if len(suggestions) > 2 else "N/A")
                    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"
                        formula_text += PLOT_FORMULAS.get(formula_key, {}).get('description', "(Nessuna descrizione dettagliata)") if formula_key else "(Formula non definita)"
                        formula_content_update = gr.update(value=formula_text)
                        new_current_chat_plot_id = None

                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, new_current_chat_plot_id, updated_chat_histories,
                    new_explored_plot_id_to_set 
                ]
                final_updates.extend(panel_visibility_updates)
                final_updates.extend(action_button_updates)
                final_updates.extend(explore_button_updates)
                final_updates.extend(section_title_visibility_updates)
                return final_updates

            async def handle_chat_message_submission(user_message: str, current_plot_id: str, chat_histories: dict, current_plot_data_for_chatbot: dict ):
                if not current_plot_id or not user_message.strip():
                    yield chat_histories.get(current_plot_id, []), gr.update(value=""), chat_histories
                    return
                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"
                plot_specific_data_summary = current_plot_data_for_chatbot.get(current_plot_id, f"Nessun sommario dati specifico disponibile per '{plot_label}'.")
                history_for_plot = chat_histories.get(current_plot_id, []).copy() + [{"role": "user", "content": user_message}]
                yield history_for_plot, gr.update(value=""), chat_histories
                bot_response_text = await generate_llm_response(user_message, current_plot_id, plot_label, history_for_plot, plot_specific_data_summary)
                history_for_plot.append({"role": "assistant", "content": bot_response_text})
                yield history_for_plot, "", {**chat_histories, current_plot_id: history_for_plot}

            async def handle_suggested_question_click(suggestion_text: str, current_plot_id: str, chat_histories: dict, current_plot_data_for_chatbot: dict):
                if not current_plot_id or not suggestion_text.strip():
                    yield chat_histories.get(current_plot_id, []), gr.update(value=""), chat_histories
                    return
                async for update in handle_chat_message_submission(suggestion_text, current_plot_id, chat_histories, current_plot_data_for_chatbot):
                    yield update

            def handle_explore_click(plot_id_clicked, current_explored_plot_id_from_state, current_active_panel_action_state):
                logging.info(f"Click Esplora: {plot_id_clicked}. Esplorato: {current_explored_plot_id_from_state}. Pannello Attivo: {current_active_panel_action_state}")
                num_plots = len(plot_configs)
                if not plot_ui_objects: # Should use plot_ui_objects here
                    logging.error("plot_ui_objects non popolato.")
                    error_updates = [current_explored_plot_id_from_state, gr.update(visible=False), current_active_panel_action_state] + \
                                    [gr.update()] * (num_plots + num_plots + 2 * num_plots + num_unique_sections)
                    return error_updates

                new_explored_id_to_set = None
                is_toggling_off_explore = (plot_id_clicked == current_explored_plot_id_from_state)
                action_col_update = gr.update() 
                new_active_panel_action_state_update = current_active_panel_action_state
                
                panel_vis_updates, explore_btn_updates, bomb_btn_icon_upds, formula_btn_icon_upds = [], [], [], []
                section_title_vis_updates = [gr.update()] * num_unique_sections
                
                clicked_plot_cfg = next((p for p in plot_configs if p["id"] == plot_id_clicked), None)
                section_of_clicked_plot = clicked_plot_cfg["section"] if clicked_plot_cfg else None

                if is_toggling_off_explore:
                    new_explored_id_to_set = None
                    logging.info(f"Stop esplorazione: {plot_id_clicked}. Tutti i grafici/titoli visibili.")
                    for i in range(num_unique_sections): section_title_vis_updates[i] = gr.update(visible=True)
                    for _ in plot_configs:
                        panel_vis_updates.append(gr.update(visible=True))
                        explore_btn_updates.append(gr.update(value=EXPLORE_ICON))
                        bomb_btn_icon_upds.append(gr.update()) # No change if not active
                        formula_btn_icon_upds.append(gr.update()) # No change if not active
                else: 
                    new_explored_id_to_set = plot_id_clicked
                    logging.info(f"Esplorazione: {plot_id_clicked}. Altri grafici/titoli nascosti.")
                    for i, sec_name in enumerate(unique_ordered_sections):
                        section_title_vis_updates[i] = gr.update(visible=(sec_name == section_of_clicked_plot))
                    for cfg in plot_configs:
                        is_target = (cfg["id"] == new_explored_id_to_set)
                        panel_vis_updates.append(gr.update(visible=is_target))
                        explore_btn_updates.append(gr.update(value=ACTIVE_ICON if is_target else EXPLORE_ICON))
                    if current_active_panel_action_state: # Close insight/formula if explore is activated
                        logging.info("Chiusura pannello azioni per attivazione esplorazione.")
                        action_col_update = gr.update(visible=False)
                        new_active_panel_action_state_update = None
                        for _ in plot_configs:
                            bomb_btn_icon_upds.append(gr.update(value=BOMB_ICON))
                            formula_btn_icon_upds.append(gr.update(value=FORMULA_ICON))
                    else:
                        for _ in plot_configs: bomb_btn_icon_upds.append(gr.update()); formula_btn_icon_upds.append(gr.update())
                
                return [new_explored_id_to_set, action_col_update, new_active_panel_action_state_update] + \
                       panel_vis_updates + explore_btn_updates + bomb_btn_icon_upds + formula_btn_icon_upds + section_title_vis_updates

            # --- Define Output Lists for Event Handlers ---
            # Base UI elements for action panel
            _base_action_panel_ui_outputs = [
                global_actions_column_ui, insights_chatbot_ui, insights_chatbot_ui, 
                insights_chat_input_ui, insights_suggestions_row_ui, 
                insights_suggestion_1_btn, insights_suggestion_2_btn, insights_suggestion_3_btn,
                formula_display_markdown_ui, formula_display_markdown_ui
            ]
            _action_panel_state_outputs = [active_panel_action_state, current_chat_plot_id_st, chat_histories_st, explored_plot_id_state]
            
            action_panel_outputs_list = _base_action_panel_ui_outputs + _action_panel_state_outputs
            action_panel_outputs_list.extend([plot_ui_objects[pid]["panel_component"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]]) # Panel vis
            action_panel_outputs_list.extend([plot_ui_objects[pid]["bomb_button"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]])    # Bomb icon
            action_panel_outputs_list.extend([plot_ui_objects[pid]["formula_button"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]]) # Formula icon
            action_panel_outputs_list.extend([plot_ui_objects[pid]["explore_button"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]]) # Explore icon
            action_panel_outputs_list.extend([section_titles_map[s_name] if s_name in section_titles_map else gr.update() for s_name in unique_ordered_sections]) # Section Titles

            _explore_state_outputs = [explored_plot_id_state, global_actions_column_ui, active_panel_action_state]
            explore_outputs_list = _explore_state_outputs
            explore_outputs_list.extend([plot_ui_objects[pid]["panel_component"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]]) # Panel vis
            explore_outputs_list.extend([plot_ui_objects[pid]["explore_button"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]]) # Explore icon
            explore_outputs_list.extend([plot_ui_objects[pid]["bomb_button"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]])    # Bomb icon
            explore_outputs_list.extend([plot_ui_objects[pid]["formula_button"] if pid in plot_ui_objects else gr.update() for pid in [pc["id"] for pc in plot_configs]]) # Formula icon
            explore_outputs_list.extend([section_titles_map[s_name] if s_name in section_titles_map else gr.update() for s_name in unique_ordered_sections]) # Section Titles

            action_click_inputs = [active_panel_action_state, chat_histories_st, current_chat_plot_id_st, plot_data_for_chatbot_st, explored_plot_id_state]
            explore_click_inputs = [explored_plot_id_state, active_panel_action_state]

            def create_panel_action_handler(p_id, action_type_str):
                async def _handler(curr_active_val, curr_chats_val, curr_chat_pid, curr_plot_data, curr_explored_id):
                    return await handle_panel_action(p_id, action_type_str, curr_active_val, curr_chats_val, curr_chat_pid, curr_plot_data, curr_explored_id)
                return _handler

            for config_item in plot_configs:
                plot_id = config_item["id"]
                if plot_id in plot_ui_objects:
                    ui_obj = plot_ui_objects[plot_id]
                    ui_obj["bomb_button"].click(fn=create_panel_action_handler(plot_id, "insights"), inputs=action_click_inputs, outputs=action_panel_outputs_list, api_name=f"action_insights_{plot_id}")
                    ui_obj["formula_button"].click(fn=create_panel_action_handler(plot_id, "formula"), inputs=action_click_inputs, outputs=action_panel_outputs_list, api_name=f"action_formula_{plot_id}")
                    ui_obj["explore_button"].click(fn=lambda current_explored_val, current_active_panel_val, p_id=plot_id: handle_explore_click(p_id, current_explored_val, current_active_panel_val), inputs=explore_click_inputs, outputs=explore_outputs_list, api_name=f"action_explore_{plot_id}")
                else: logging.warning(f"UI object for plot_id '{plot_id}' not found for click handlers.")

            chat_submission_outputs = [insights_chatbot_ui, insights_chat_input_ui, chat_histories_st]
            chat_submission_inputs = [insights_chat_input_ui, current_chat_plot_id_st, chat_histories_st, plot_data_for_chatbot_st]
            insights_chat_input_ui.submit(fn=handle_chat_message_submission, inputs=chat_submission_inputs, outputs=chat_submission_outputs, api_name="submit_chat_message")
            suggestion_click_inputs = [current_chat_plot_id_st, chat_histories_st, plot_data_for_chatbot_st]
            insights_suggestion_1_btn.click(fn=handle_suggested_question_click, inputs=[insights_suggestion_1_btn] + suggestion_click_inputs, outputs=chat_submission_outputs, api_name="click_suggestion_1")
            insights_suggestion_2_btn.click(fn=handle_suggested_question_click, inputs=[insights_suggestion_2_btn] + suggestion_click_inputs, outputs=chat_submission_outputs, api_name="click_suggestion_2")
            insights_suggestion_3_btn.click(fn=handle_suggested_question_click, inputs=[insights_suggestion_3_btn] + suggestion_click_inputs, outputs=chat_submission_outputs, api_name="click_suggestion_3")

            def refresh_all_analytics_ui_elements(current_token_state, date_filter_val, custom_start_val, custom_end_val, current_chat_histories):
                logging.info("Refreshing all analytics UI elements and resetting actions/chat.")
                plot_generation_results = update_analytics_plots_figures(current_token_state, date_filter_val, custom_start_val, custom_end_val, plot_configs)
                status_msg, generated_figs, new_plot_data_summaries = plot_generation_results[0], plot_generation_results[1:-1], plot_generation_results[-1]
                
                all_updates = [status_msg]
                all_updates.extend(generated_figs if len(generated_figs) == len(plot_configs) else [create_placeholder_plot("Error", f"Fig missing {i}") for i in range(len(plot_configs))])
                
                all_updates.extend([ # Reset action panel UI
                    gr.update(visible=False), gr.update(value=[], visible=False), gr.update(value="", visible=False),
                    gr.update(visible=False), gr.update(value="S1"), gr.update(value="S2"), gr.update(value="S3"),
                    gr.update(value="Formula details here.", visible=False),
                    None, None, {}, new_plot_data_summaries # Reset states
                ])
                for _ in plot_configs: # Reset button icons & panel visibility
                    all_updates.extend([gr.update(value=BOMB_ICON), gr.update(value=FORMULA_ICON), gr.update(value=EXPLORE_ICON), gr.update(visible=True)])
                all_updates.append(None) # Reset explored_plot_id_state
                all_updates.extend([gr.update(visible=True)] * num_unique_sections) # Make all section titles visible
                logging.info(f"Prepared {len(all_updates)} updates for analytics refresh.")
                return all_updates

            apply_filter_and_sync_outputs_list = [analytics_status_md] # Status
            apply_filter_and_sync_outputs_list.extend([plot_ui_objects[pc["id"]]["plot_component"] if pc["id"] in plot_ui_objects and "plot_component" in plot_ui_objects[pc["id"]] else gr.update() for pc in plot_configs]) # Plot figures
            apply_filter_and_sync_outputs_list.extend([ # Action panel UI reset
                global_actions_column_ui, insights_chatbot_ui, insights_chat_input_ui,
                insights_suggestions_row_ui, insights_suggestion_1_btn, insights_suggestion_2_btn, insights_suggestion_3_btn,
                formula_display_markdown_ui,
                active_panel_action_state, current_chat_plot_id_st, chat_histories_st, plot_data_for_chatbot_st
            ])
            for pc in plot_configs: # Button icons and panel visibility
                pid = pc["id"]
                apply_filter_and_sync_outputs_list.extend([
                    plot_ui_objects[pid]["bomb_button"] if pid in plot_ui_objects else gr.update(),
                    plot_ui_objects[pid]["formula_button"] if pid in plot_ui_objects else gr.update(),
                    plot_ui_objects[pid]["explore_button"] if pid in plot_ui_objects else gr.update(),
                    plot_ui_objects[pid]["panel_component"] if pid in plot_ui_objects else gr.update()
                ])
            apply_filter_and_sync_outputs_list.append(explored_plot_id_state) # Reset explored state
            apply_filter_and_sync_outputs_list.extend([section_titles_map[s_name] if s_name in section_titles_map else gr.update() for s_name in unique_ordered_sections]) # Section Titles
            
            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"):
            # ... (rest of the tab unchanged) ...
            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"):
            # ... (rest of the tab unchanged) ...
            refresh_follower_stats_btn = gr.Button("🔄 Aggiorna Visualizzazione Statistiche Follower", variant="secondary")
            follower_stats_html = gr.HTML("Statistiche follower...")
            with gr.Row():
                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_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(fn=process_and_store_bubble_token, inputs=[url_user_token_display, org_urn_display, token_state], outputs=[status_box, token_state, sync_data_btn], show_progress=False)
    sync_event_part3 = sync_event_part2.then(fn=display_main_dashboard, inputs=[token_state], outputs=[dashboard_display_html], show_progress=False)
    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, show_progress="full")

if __name__ == "__main__":
    if not os.environ.get(LINKEDIN_CLIENT_ID_ENV_VAR): logging.warning(f"ATTENZIONE: '{LINKEDIN_CLIENT_ID_ENV_VAR}' non impostata.")
    if not all(os.environ.get(var) for var in [BUBBLE_APP_NAME_ENV_VAR, BUBBLE_API_KEY_PRIVATE_ENV_VAR, BUBBLE_API_ENDPOINT_ENV_VAR]):
        logging.warning("ATTENZIONE: Variabili Bubble non impostate.")
    try: logging.info(f"Matplotlib: {matplotlib.__version__}, Backend: {matplotlib.get_backend()}")
    except ImportError: logging.warning("Matplotlib non trovato.")
    app.launch(server_name="0.0.0.0", server_port=7860, debug=True)