app.py

# 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
)
from analytics_plot_generator import update_analytics_plots_figures, create_placeholder_plot
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."
            
            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 = {} 
            section_titles_map = {} 

            with gr.Row(equal_height=False):
                with gr.Column(scale=8) as plots_area_col:
                    ui_elements_tuple = build_analytics_tab_plot_area(plot_configs) # This function is in ui_generators.py
                    if isinstance(ui_elements_tuple, tuple) and len(ui_elements_tuple) == 2:
                        plot_ui_objects, section_titles_map = ui_elements_tuple
                        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.")
                            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} (Error Placeholder)") 
                    else:
                        logging.error("build_analytics_tab_plot_area did not return (plot_ui_objects, section_titles_map).")
                        plot_ui_objects = ui_elements_tuple if isinstance(ui_elements_tuple, dict) else {} # Fallback
                        for sec_name in unique_ordered_sections: # Fallback for section titles
                            section_titles_map[sec_name] = gr.Markdown(f"### {sec_name} (Error Placeholder)")


                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
                    )
                    # NEW: Hint for closing the formula panel
                    formula_close_hint_md = gr.Markdown(
                        "<p style='font-size:0.9em; text-align:center; margin-top:10px;'><em>Click the active ƒ button on the plot again to close this panel.</em></p>", 
                        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"Panel Action: '{action_type}' for plot '{plot_id_clicked}'. Active: {current_active_action_from_state}, Explored: {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"Config not found for plot_id {plot_id_clicked}")
                    # Ensure this error return matches the expected number of outputs
                    num_plots = len(plot_configs)
                    # Count for action_panel_outputs_list: 11 base UI + 4 states + N panels + 3N buttons + M sections = 15 + 4N + M
                    # 15 + 4*19 + 6 = 15 + 76 + 6 = 97
                    error_list_len = 11 + 4 + num_plots + (3 * num_plots) + num_unique_sections # Matches action_panel_outputs_list structure
                    error_list = [gr.update()] * error_list_len
                    # Manually set key states to avoid further issues if possible
                    error_list[11] = current_active_action_from_state # active_panel_action_state
                    error_list[12] = current_chat_plot_id # current_chat_plot_id_st
                    error_list[13] = current_chat_histories # chat_histories_st
                    error_list[14] = current_explored_plot_id # explored_plot_id_state
                    return error_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)
                formula_close_hint_visible_update = gr.update(visible=False) 
                chatbot_content_update, s1_upd, s2_upd, s3_upd, formula_content_update = gr.update(), gr.update(), gr.update(), gr.update(), gr.update()
                
                new_active_action_state_to_set, new_current_chat_plot_id = None, current_chat_plot_id
                updated_chat_histories, new_explored_plot_id_to_set = current_chat_histories, current_explored_plot_id

                panel_vis_updates, action_btn_updates, explore_btn_updates = [], [], []
                section_title_vis_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"Toggling OFF panel {action_type} for {plot_id_clicked}.")
                    if current_explored_plot_id: 
                        explored_cfg = next((p for p in plot_configs if p["id"] == current_explored_plot_id), None)
                        explored_sec = explored_cfg["section"] if explored_cfg else None
                        for i, sec_name in enumerate(unique_ordered_sections):
                            section_title_vis_updates[i] = gr.update(visible=(sec_name == explored_sec))
                        for cfg in plot_configs:
                            is_exp = (cfg["id"] == current_explored_plot_id)
                            panel_vis_updates.append(gr.update(visible=is_exp))
                            explore_btn_updates.append(gr.update(value=ACTIVE_ICON if is_exp else EXPLORE_ICON))
                    else: 
                        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))
                    for _ in plot_configs: 
                        action_btn_updates.extend([gr.update(value=BOMB_ICON), gr.update(value=FORMULA_ICON)])
                    if action_type == "insights": new_current_chat_plot_id = None

                else: 
                    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 
                    logging.info(f"Toggling ON panel {action_type} for {plot_id_clicked}. Cancelling explore view.")

                    for i, sec_name in enumerate(unique_ordered_sections): 
                        section_title_vis_updates[i] = gr.update(visible=(sec_name == clicked_plot_section))
                    for cfg in plot_configs: 
                        panel_vis_updates.append(gr.update(visible=(cfg["id"] == plot_id_clicked)))
                        explore_btn_updates.append(gr.update(value=EXPLORE_ICON)) 
                    
                    for cfg_btn in plot_configs: 
                        is_act_ins = new_active_action_state_to_set == {"plot_id": cfg_btn["id"], "type": "insights"}
                        is_act_for = new_active_action_state_to_set == {"plot_id": cfg_btn["id"], "type": "formula"}
                        action_btn_updates.extend([gr.update(value=ACTIVE_ICON if is_act_ins else BOMB_ICON), 
                                                   gr.update(value=ACTIVE_ICON if is_act_for 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
                        history = current_chat_histories.get(plot_id_clicked, [])
                        summary = current_plot_data_for_chatbot.get(plot_id_clicked, f"No summary for '{clicked_plot_label}'.")
                        if not history:
                            prompt, sugg = get_initial_insight_prompt_and_suggestions(plot_id_clicked, clicked_plot_label, summary)
                            llm_hist = [{"role": "user", "content": prompt}]
                            resp = await generate_llm_response(prompt, plot_id_clicked, clicked_plot_label, llm_hist, summary)
                            history = [{"role": "assistant", "content": resp}]
                            updated_chat_histories = {**current_chat_histories, plot_id_clicked: history}
                        else: _, sugg = get_initial_insight_prompt_and_suggestions(plot_id_clicked, clicked_plot_label, summary)
                        chatbot_content_update = gr.update(value=history)
                        s1_upd,s2_upd,s3_upd = gr.update(value=sugg[0] if sugg else "N/A"),gr.update(value=sugg[1] if len(sugg)>1 else "N/A"),gr.update(value=sugg[2] if len(sugg)>2 else "N/A")
                    elif action_type == "formula":
                        formula_display_visible_update = gr.update(visible=True)
                        formula_close_hint_visible_update = gr.update(visible=True) 
                        f_key = PLOT_ID_TO_FORMULA_KEY_MAP.get(plot_id_clicked)
                        f_text = f"**Formula/Methodology for: {clicked_plot_label}** (ID: `{plot_id_clicked}`)\n\n"
                        if f_key and f_key in PLOT_FORMULAS:
                            f_data = PLOT_FORMULAS[f_key]
                            f_text += f"### {f_data['title']}\n\n{f_data['description']}\n\n**Calculation:**\n" + "\n".join([f"- {s}" for s in f_data['calculation_steps']])
                        else: f_text += "(No detailed formula information found.)"
                        formula_content_update = gr.update(value=f_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, 
                    s1_upd, s2_upd, s3_upd, formula_display_visible_update, formula_content_update,
                    formula_close_hint_visible_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_vis_updates)
                final_updates.extend(action_btn_updates) # Should be 2*N items
                final_updates.extend(explore_btn_updates) # Should be N items
                final_updates.extend(section_title_vis_updates)
                # Total: 11 (base UI) + 4 (states) + N (panels) + 2N (action_btns) + N (explore_btns) + M (sections)
                # = 15 + 4N + M. For N=19, M=6: 15 + 76 + 6 = 97. This matches action_panel_outputs_list.
                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
                cfg = next((p for p in plot_configs if p["id"] == current_plot_id), None)
                lbl = cfg["label"] if cfg else "Selected Plot"
                summary = current_plot_data_for_chatbot.get(current_plot_id, f"No summary for '{lbl}'.")
                hist = chat_histories.get(current_plot_id, []).copy() + [{"role": "user", "content": user_message}]
                yield hist, gr.update(value=""), chat_histories
                resp = await generate_llm_response(user_message, current_plot_id, lbl, hist, summary)
                hist.append({"role": "assistant", "content": resp})
                yield hist, "", {**chat_histories, current_plot_id: hist}

            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"Explore Click: Plot '{plot_id_clicked}'. Current Explored: {current_explored_plot_id_from_state}. Active Panel: {current_active_panel_action_state}")
                num_plots = len(plot_configs)
                if not plot_ui_objects: 
                    logging.error("plot_ui_objects not populated for handle_explore_click.")
                    # explore_outputs_list: 4 base states/UI + N panels + N explore_btns + 2N action_btns + M sections
                    # = 4 + 4N + M. For N=19, M=6: 4 + 76 + 6 = 86
                    error_list_len = 4 + num_plots + num_plots + (2 * num_plots) + num_unique_sections
                    error_list = [gr.update()] * error_list_len
                    error_list[0] = current_explored_plot_id_from_state
                    error_list[2] = current_active_panel_action_state
                    return error_list


                new_explored_id_to_set, is_toggling_off_explore = None, (plot_id_clicked == current_explored_plot_id_from_state)
                action_col_upd, new_active_panel_state_upd = gr.update(), current_active_panel_action_state
                panel_vis, explore_btns, bomb_btns, formula_btns = [], [], [], []
                section_title_vis = [gr.update()] * num_unique_sections
                formula_hint_upd = gr.update(visible=False) 

                clicked_cfg = next((p for p in plot_configs if p["id"] == plot_id_clicked), None)
                sec_of_clicked = clicked_cfg["section"] if clicked_cfg else None

                if is_toggling_off_explore:
                    new_explored_id_to_set = None
                    logging.info(f"Stopping explore for {plot_id_clicked}. All plots/sections visible.")
                    for i in range(num_unique_sections): section_title_vis[i] = gr.update(visible=True)
                    for _ in plot_configs:
                        panel_vis.append(gr.update(visible=True)); explore_btns.append(gr.update(value=EXPLORE_ICON))
                        bomb_btns.append(gr.update()); formula_btns.append(gr.update()) 
                else: 
                    new_explored_id_to_set = plot_id_clicked
                    logging.info(f"Exploring {plot_id_clicked}. Hiding other plots/sections.")
                    for i, sec_name in enumerate(unique_ordered_sections): section_title_vis[i] = gr.update(visible=(sec_name == sec_of_clicked))
                    for cfg_idx, cfg in enumerate(plot_configs): # Iterate with index for bomb_btns/formula_btns
                        is_target = (cfg["id"] == new_explored_id_to_set)
                        panel_vis.append(gr.update(visible=is_target))
                        explore_btns.append(gr.update(value=ACTIVE_ICON if is_target else EXPLORE_ICON))
                        # Initialize bomb_btns and formula_btns correctly for all plots
                        if current_active_panel_action_state and current_active_panel_action_state.get("plot_id") == cfg["id"]:
                             # This should not happen if we are closing active panel below
                            pass # Will be overridden
                        
                    if current_active_panel_action_state: 
                        logging.info("Closing active insight/formula panel due to explore click.")
                        action_col_upd = gr.update(visible=False); new_active_panel_state_upd = None
                        # Reset all bomb and formula buttons
                        bomb_btns = [gr.update(value=BOMB_ICON) for _ in plot_configs]
                        formula_btns = [gr.update(value=FORMULA_ICON) for _ in plot_configs]
                    else: 
                        # If no panel was active, keep current state of bomb/formula buttons (no update)
                        bomb_btns = [gr.update() for _ in plot_configs]
                        formula_btns = [gr.update() for _ in plot_configs]
                
                # Order: states (4), panels (N), explore_btns (N), bomb_btns (N), formula_btns (N), section_titles (M)
                # Total: 4 + N + N + N + N + M = 4 + 4N + M.
                return [new_explored_id_to_set, action_col_upd, new_active_panel_state_upd, formula_hint_upd] + \
                       panel_vis + explore_btns + bomb_btns + formula_btns + section_title_vis

            # --- Define Output Lists for Event Handlers ---
            # Base UI for action panel (insights/formula): 11 elements
            _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, # Formula MD (vis + value)
                formula_close_hint_md 
            ]
            # States for action panel: 4 elements
            _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 # 11 + 4 = 15
            action_panel_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("panel_component", gr.update()) for pc in plot_configs]) # +N (panels)
            action_panel_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("bomb_button", gr.update()) for pc in plot_configs])    # +N (bomb_button)
            action_panel_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("formula_button", gr.update()) for pc in plot_configs]) # +N (formula_button)
            action_panel_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("explore_button", gr.update()) for pc in plot_configs]) # +N (explore_button)
            action_panel_outputs_list.extend([section_titles_map.get(s_name, gr.update()) for s_name in unique_ordered_sections]) # +M (sections)
            # Total for action_panel_outputs_list = 15 + 4N + M. For N=19, M=6: 15 + 76 + 6 = 97.

            # Base UI/States for explore click: 4 elements
            _explore_base_outputs = [explored_plot_id_state, global_actions_column_ui, active_panel_action_state, formula_close_hint_md] 
            explore_outputs_list = _explore_base_outputs # 4
            explore_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("panel_component", gr.update()) for pc in plot_configs]) # +N (panels)
            explore_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("explore_button", gr.update()) for pc in plot_configs]) # +N (explore_button)
            explore_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("bomb_button", gr.update()) for pc in plot_configs])    # +N (bomb_button)
            explore_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("formula_button", gr.update()) for pc in plot_configs]) # +N (formula_button)
            explore_outputs_list.extend([section_titles_map.get(s_name, gr.update()) for s_name in unique_ordered_sections]) # +M (sections)
            # Total for explore_outputs_list = 4 + 4N + M. For N=19, M=6: 4 + 76 + 6 = 86.

            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_gen_results = update_analytics_plots_figures(current_token_state, date_filter_val, custom_start_val, custom_end_val, plot_configs)
                status_msg, gen_figs, new_summaries = plot_gen_results[0], plot_gen_results[1:-1], plot_gen_results[-1]
                
                all_updates = [status_msg] # 1
                all_updates.extend(gen_figs if len(gen_figs) == len(plot_configs) else [create_placeholder_plot("Error", f"Fig missing {i}") for i in range(len(plot_configs))]) # +N (19)
                
                # UI Resets (9 elements) + State Resets (4 elements) = 13 elements
                all_updates.extend([ 
                    gr.update(visible=False), gr.update(value=[], visible=False), gr.update(value="", visible=False), # global_actions_col, chatbot, chat_input
                    gr.update(visible=False), gr.update(value="S1"), gr.update(value="S2"), gr.update(value="S3"), # suggestions_row, sugg_btns
                    gr.update(value="Formula details here.", visible=False), gr.update(visible=False), # formula_md, formula_hint_md
                    None, None, {}, new_summaries # active_panel_state, current_chat_plot_id, chat_histories, plot_data_for_chatbot
                ]) # +13
                
                for _ in plot_configs: # Reset button icons (3) & panel visibility (1) = 4 per plot
                    all_updates.extend([gr.update(value=BOMB_ICON), gr.update(value=FORMULA_ICON), gr.update(value=EXPLORE_ICON), gr.update(visible=True)]) # +4N (76)
                
                all_updates.append(None) # Reset explored_plot_id_state (1 element)
                all_updates.extend([gr.update(visible=True)] * num_unique_sections) # Make all section titles visible (M = 6 elements)
                # Total: 1 + N + 13 + 4N + 1 + M = 1 + 19 + 13 + 76 + 1 + 6 = 116. This matches apply_filter_and_sync_outputs_list.
                logging.info(f"Prepared {len(all_updates)} updates for analytics refresh.")
                return all_updates

            # Construction of apply_filter_and_sync_outputs_list
            # This list defines the components Gradio expects to be updated.
            # Its length must match the number of items returned by refresh_all_analytics_ui_elements.
            
            apply_filter_and_sync_outputs_list = [analytics_status_md] # 1. Status
            apply_filter_and_sync_outputs_list.extend([plot_ui_objects.get(pc["id"], {}).get("plot_component", gr.update()) for pc in plot_configs]) # 2. Plot figures (N)
            
            # 3. UI Resets (9 elements for action panel)
            _ui_resets_for_filter = [
                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, formula_close_hint_md 
            ]
            apply_filter_and_sync_outputs_list.extend(_ui_resets_for_filter)
            
            # 4. State Resets (4 elements)
            _state_resets_for_filter = [active_panel_action_state, current_chat_plot_id_st, chat_histories_st, plot_data_for_chatbot_st]
            apply_filter_and_sync_outputs_list.extend(_state_resets_for_filter)

            # 5. Plot-specific buttons (3 per plot) and panel visibility (1 per plot) = 4N elements
            for pc in plot_configs: 
                pid = pc["id"]
                apply_filter_and_sync_outputs_list.extend([
                    plot_ui_objects.get(pid, {}).get("bomb_button", gr.update()),
                    plot_ui_objects.get(pid, {}).get("formula_button", gr.update()),
                    plot_ui_objects.get(pid, {}).get("explore_button", gr.update()),
                    plot_ui_objects.get(pid, {}).get("panel_component", gr.update())
                ])
            
            # 6. Explored state reset (1 element)
            apply_filter_and_sync_outputs_list.append(explored_plot_id_state) 
            
            # 7. Section Titles (M elements)
            apply_filter_and_sync_outputs_list.extend([section_titles_map.get(s_name, gr.update()) for s_name in unique_ordered_sections]) 
            # Total elements: 1 + N + 9 + 4 + 4N + 1 + M = 15 + 5N + M
            # For N=19, M=6: 15 + 5*19 + 6 = 15 + 95 + 6 = 110 + 6 = 116. This is correct.
            
            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():
                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)