app.py

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

# --- 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
)
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, # Import the updated UI builder
    BOMB_ICON, EXPLORE_ICON, FORMULA_ICON, ACTIVE_ICON # Import icons
)
# Corrected import for analytics_data_processing
from analytics_data_processing import prepare_filtered_analytics_data
from analytics_plot_generator import (
    generate_posts_activity_plot, generate_engagement_type_plot,
    generate_mentions_activity_plot, generate_mention_sentiment_plot,
    generate_followers_count_over_time_plot,
    generate_followers_growth_rate_plot,
    generate_followers_by_demographics_plot,
    generate_engagement_rate_over_time_plot,
    generate_reach_over_time_plot,
    generate_impressions_over_time_plot,
    create_placeholder_plot, 
    generate_likes_over_time_plot,
    generate_clicks_over_time_plot,
    generate_shares_over_time_plot,
    generate_comments_over_time_plot,
    generate_comments_sentiment_breakdown_plot,
    generate_post_frequency_plot,
    generate_content_format_breakdown_plot,
    generate_content_topic_breakdown_plot
)

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

# --- Analytics Tab: Plot Figure Generation Function ---
def update_analytics_plots_figures(token_state_value, date_filter_option, custom_start_date, custom_end_date):
    logging.info(f"Updating analytics plot figures. Filter: {date_filter_option}, Custom Start: {custom_start_date}, Custom End: {custom_end_date}")
    num_expected_plots = 23 

    if not token_state_value or not token_state_value.get("token"):
        message = "❌ Access denied. No token. Cannot generate analytics."
        logging.warning(message)
        placeholder_figs = [create_placeholder_plot(title="Access Denied", message="No token.") for _ in range(num_expected_plots)]
        return [message] + placeholder_figs

    try:
        (filtered_merged_posts_df,
         filtered_mentions_df,
         date_filtered_follower_stats_df,
         raw_follower_stats_df,
         start_dt_for_msg, end_dt_for_msg) = \
            prepare_filtered_analytics_data(
                token_state_value, date_filter_option, custom_start_date, custom_end_date
            )
    except Exception as e:
        error_msg = f"❌ Error preparing analytics data: {e}"
        logging.error(error_msg, exc_info=True)
        placeholder_figs = [create_placeholder_plot(title="Data Preparation Error", message=str(e)) for _ in range(num_expected_plots)]
        return [error_msg] + placeholder_figs

    date_column_posts = token_state_value.get("config_date_col_posts", "published_at")
    date_column_mentions = token_state_value.get("config_date_col_mentions", "date")
    media_type_col_name = token_state_value.get("config_media_type_col", "media_type")
    eb_labels_col_name = token_state_value.get("config_eb_labels_col", "eb_labels")

    plot_figs = []
    try:
        plot_figs.append(generate_posts_activity_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_engagement_type_plot(filtered_merged_posts_df))
        fig_mentions_activity_shared = generate_mentions_activity_plot(filtered_mentions_df, date_column=date_column_mentions)
        fig_mention_sentiment_shared = generate_mention_sentiment_plot(filtered_mentions_df)
        plot_figs.append(fig_mentions_activity_shared)
        plot_figs.append(fig_mention_sentiment_shared)
        plot_figs.append(generate_followers_count_over_time_plot(date_filtered_follower_stats_df, type_value='follower_gains_monthly'))
        plot_figs.append(generate_followers_growth_rate_plot(date_filtered_follower_stats_df, type_value='follower_gains_monthly'))
        plot_figs.append(generate_followers_by_demographics_plot(raw_follower_stats_df, type_value='follower_geo', plot_title="Followers by Location"))
        plot_figs.append(generate_followers_by_demographics_plot(raw_follower_stats_df, type_value='follower_function', plot_title="Followers by Role"))
        plot_figs.append(generate_followers_by_demographics_plot(raw_follower_stats_df, type_value='follower_industry', plot_title="Followers by Industry"))
        plot_figs.append(generate_followers_by_demographics_plot(raw_follower_stats_df, type_value='follower_seniority', plot_title="Followers by Seniority"))
        plot_figs.append(generate_engagement_rate_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_reach_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_impressions_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_likes_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_clicks_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_shares_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_comments_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_comments_sentiment_breakdown_plot(filtered_merged_posts_df, sentiment_column='comment_sentiment'))
        plot_figs.append(generate_post_frequency_plot(filtered_merged_posts_df, date_column=date_column_posts))
        plot_figs.append(generate_content_format_breakdown_plot(filtered_merged_posts_df, format_col=media_type_col_name))
        plot_figs.append(generate_content_topic_breakdown_plot(filtered_merged_posts_df, topics_col=eb_labels_col_name))
        plot_figs.append(fig_mentions_activity_shared) 
        plot_figs.append(fig_mention_sentiment_shared)

        message = f"📊 Analytics updated for period: {date_filter_option}"
        if date_filter_option == "Custom Range":
            s_display = start_dt_for_msg.strftime('%Y-%m-%d') if start_dt_for_msg else "Any"
            e_display = end_dt_for_msg.strftime('%Y-%m-%d') if end_dt_for_msg else "Any"
            message += f" (From: {s_display} To: {e_display})"
        
        final_plot_figs = []
        for i, p_fig in enumerate(plot_figs):
            if p_fig is not None and not isinstance(p_fig, str): 
                final_plot_figs.append(p_fig)
            else:
                logging.warning(f"Plot figure generation failed or returned unexpected type for slot {i}, using placeholder. Figure: {p_fig}")
                final_plot_figs.append(create_placeholder_plot(title="Plot Error", message="Failed to generate this plot figure."))
        
        while len(final_plot_figs) < num_expected_plots:
            logging.warning(f"Padding missing plot figure. Expected {num_expected_plots}, got {len(final_plot_figs)}.")
            final_plot_figs.append(create_placeholder_plot(title="Missing Plot", message="Plot figure could not be generated."))
        
        return [message] + final_plot_figs[:num_expected_plots]

    except Exception as e:
        error_msg = f"❌ Error generating analytics plot figures: {e}"
        logging.error(error_msg, exc_info=True)
        placeholder_figs = [create_placeholder_plot(title="Plot Generation Error", message=str(e)) for _ in range(num_expected_plots)]
        return [error_msg] + placeholder_figs


# --- 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": "eb_labels"
    })

    gr.Markdown("# 🚀 LinkedIn Organization Dashboard")
    url_user_token_display = gr.Textbox(label="User Token (Hidden)", interactive=False, visible=False)
    status_box = gr.Textbox(label="Overall LinkedIn Token Status", interactive=False, value="Initializing...")
    org_urn_display = gr.Textbox(label="Organization URN (Hidden)", 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("System checks for existing data from Bubble. 'Sync' activates if new data is needed.")
            sync_data_btn = gr.Button("🔄 Sync LinkedIn Data", variant="primary", visible=False, interactive=False)
            sync_status_html_output = gr.HTML("<p style='text-align:center;'>Sync status...</p>")
            dashboard_display_html = gr.HTML("<p style='text-align:center;'>Dashboard loading...</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 Analytics", id="tab_analytics"):
            gr.Markdown("## 📈 LinkedIn Performance Analytics")
            gr.Markdown("Select a date range. Click buttons for actions.")
            
            analytics_status_md = gr.Markdown("Analytics status...")

            with gr.Row(): 
                date_filter_selector = gr.Radio(
                    ["All Time", "Last 7 Days", "Last 30 Days", "Custom Range"],
                    label="Select Date Range", value="Last 30 Days", scale=3
                )
                with gr.Column(scale=2):
                    custom_start_date_picker = gr.DateTime(label="Start Date", visible=False, include_time=False, type="datetime")
                    custom_end_date_picker = gr.DateTime(label="End Date", visible=False, include_time=False, type="datetime")
            
            apply_filter_btn = gr.Button("🔍 Apply Filter & Refresh Analytics", variant="primary")

            def toggle_custom_date_pickers(selection):
                is_custom = selection == "Custom Range"
                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": "Posts Activity Over Time", "id": "posts_activity", "section": "Posts & Engagement Overview"},
                {"label": "Post Engagement Types", "id": "engagement_type", "section": "Posts & Engagement Overview"},
                {"label": "Mentions Activity Over Time", "id": "mentions_activity", "section": "Mentions Overview"}, 
                {"label": "Mention Sentiment Distribution", "id": "mention_sentiment", "section": "Mentions Overview"}, 
                {"label": "Followers Count Over Time", "id": "followers_count", "section": "Follower Dynamics"},
                {"label": "Followers Growth Rate", "id": "followers_growth_rate", "section": "Follower Dynamics"},
                {"label": "Followers by Location", "id": "followers_by_location", "section": "Follower Demographics"},
                {"label": "Followers by Role (Function)", "id": "followers_by_role", "section": "Follower Demographics"},
                {"label": "Followers by Industry", "id": "followers_by_industry", "section": "Follower Demographics"},
                {"label": "Followers by Seniority", "id": "followers_by_seniority", "section": "Follower Demographics"},
                {"label": "Engagement Rate Over Time", "id": "engagement_rate", "section": "Post Performance Insights"},
                {"label": "Reach Over Time (Clicks)", "id": "reach_over_time", "section": "Post Performance Insights"},
                {"label": "Impressions Over Time", "id": "impressions_over_time", "section": "Post Performance Insights"},
                {"label": "Reactions (Likes) Over Time", "id": "likes_over_time", "section": "Post Performance Insights"},
                {"label": "Clicks Over Time", "id": "clicks_over_time", "section": "Detailed Post Engagement Over Time"},
                {"label": "Shares Over Time", "id": "shares_over_time", "section": "Detailed Post Engagement Over Time"},
                {"label": "Comments Over Time", "id": "comments_over_time", "section": "Detailed Post Engagement Over Time"},
                {"label": "Breakdown of Comments by Sentiment", "id": "comments_sentiment", "section": "Detailed Post Engagement Over Time"},
                {"label": "Post Frequency", "id": "post_frequency_cs", "section": "Content Strategy Analysis"},
                {"label": "Breakdown of Content by Format", "id": "content_format_breakdown_cs", "section": "Content Strategy Analysis"},
                {"label": "Breakdown of Content by Topics", "id": "content_topic_breakdown_cs", "section": "Content Strategy Analysis"},
                {"label": "Mentions Volume Over Time (Detailed)", "id": "mention_analysis_volume", "section": "Mention Analysis (Detailed)"}, 
                {"label": "Breakdown of Mentions by Sentiment (Detailed)", "id": "mention_analysis_sentiment", "section": "Mention Analysis (Detailed)"} 
            ]
            assert len(plot_configs) == 23, "Mismatch in plot_configs and expected plots."

            # --- State for Analytics Tab interactivity ---
            # Stores {"plot_id": "action_type"} e.g. {"posts_activity": "insights"} or None
            active_panel_action_state = gr.State(None) 
            # Stores plot_id of the currently explored plot, or None
            explored_plot_id_state = gr.State(None) 

            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)
                
                with gr.Column(scale=4, visible=False) as global_actions_column_ui: # Renamed for clarity
                    gr.Markdown("### 💡 Generated Content") # More generic title
                    global_actions_markdown_ui = gr.Markdown("Click a button (💣, ƒ) on a plot to see content here.")


            # --- Event Handler for Insights and Formula Buttons ---
            def handle_panel_action(plot_id_clicked, action_type, current_active_action, token_state_val):
                logging.info(f"Action '{action_type}' for plot: {plot_id_clicked}. Current active: {current_active_action}")
                
                clicked_plot_label = plot_ui_objects.get(plot_id_clicked, {}).get("label", "Selected Plot")
                
                # Determine new state for the action panel
                new_active_action_state = {"plot_id": plot_id_clicked, "type": action_type}
                is_toggling_off = current_active_action == new_active_action_state
                
                content_text = ""
                action_col_visible = False
                
                # Button icon updates - prepare a list of gr.update for all buttons
                button_updates = {} # Dict to hold updates for gr.Button objects

                if is_toggling_off:
                    new_active_action_state = None
                    content_text = f"{action_type.capitalize()} for {clicked_plot_label} hidden."
                    action_col_visible = False
                    logging.info(f"Closing {action_type} panel for {plot_id_clicked}")
                    # Reset the clicked button to its original icon
                    if action_type == "insights":
                        button_updates[plot_ui_objects[plot_id_clicked]["bomb_button"]] = gr.update(value=BOMB_ICON)
                    elif action_type == "formula":
                        button_updates[plot_ui_objects[plot_id_clicked]["formula_button"]] = gr.update(value=FORMULA_ICON)
                else: # Activating or switching
                    action_col_visible = True
                    if action_type == "insights":
                        # TODO: Implement actual insight generation
                        content_text = f"**Insights for: {clicked_plot_label}**\n\nPlot ID: `{plot_id_clicked}`.\nDetailed AI insights here."
                        button_updates[plot_ui_objects[plot_id_clicked]["bomb_button"]] = gr.update(value=ACTIVE_ICON)
                    elif action_type == "formula":
                        # TODO: Implement actual formula display
                        content_text = f"**Formula/Methodology for: {clicked_plot_label}**\n\nPlot ID: `{plot_id_clicked}`.\nMethodology details here."
                        button_updates[plot_ui_objects[plot_id_clicked]["formula_button"]] = gr.update(value=ACTIVE_ICON)
                    
                    logging.info(f"Opening {action_type} panel for {plot_id_clicked}")

                # Reset other action buttons for the *same* plot if a new action is chosen for it
                # And reset all buttons if switching plots or toggling off
                for pid, ui_obj in plot_ui_objects.items():
                    is_current_plot_active_bomb = new_active_action_state == {"plot_id": pid, "type": "insights"}
                    is_current_plot_active_formula = new_active_action_state == {"plot_id": pid, "type": "formula"}

                    if ui_obj["bomb_button"] not in button_updates: # Avoid overwriting the primary clicked button's update
                        button_updates[ui_obj["bomb_button"]] = gr.update(value=BOMB_ICON if not is_current_plot_active_bomb else ACTIVE_ICON)
                    if ui_obj["formula_button"] not in button_updates:
                        button_updates[ui_obj["formula_button"]] = gr.update(value=FORMULA_ICON if not is_current_plot_active_formula else ACTIVE_ICON)
                
                # Construct the list of updates for Gradio
                # Order: global_actions_column_ui, global_actions_markdown_ui, active_panel_action_state, then all button updates
                final_updates = [
                    gr.update(visible=action_col_visible), 
                    gr.update(value=content_text), 
                    new_active_action_state
                ]
                # Add button updates in a consistent order (e.g., order of plot_configs)
                for cfg in plot_configs:
                    p_id = cfg["id"]
                    if p_id in plot_ui_objects:
                        # Append updates for bomb, explore, formula buttons for this plot_id
                        # Ensure explore button is handled by its own handler or reset here if needed
                        if plot_ui_objects[p_id]["bomb_button"] in button_updates:
                            final_updates.append(button_updates[plot_ui_objects[p_id]["bomb_button"]])
                        else: # Default reset if not specifically handled
                            final_updates.append(gr.update(value=BOMB_ICON))
                        
                        # Explore button is handled separately, but ensure it's in the output list
                        # For now, we'll let its own handler manage its state, or reset it if another action occurs.
                        # This part needs careful thought for interactions between explore and other actions.
                        # Let's assume for now that activating insights/formula doesn't auto-close explore.
                        # We will need to add explore_button to the output list.
                        # For now, this handler focuses on insights/formula buttons.
                        # We'll need to expand the output list.

                        if plot_ui_objects[p_id]["formula_button"] in button_updates:
                            final_updates.append(button_updates[plot_ui_objects[p_id]["formula_button"]])
                        else: # Default reset
                            final_updates.append(gr.update(value=FORMULA_ICON))
                
                return final_updates

            # --- Event Handler for Explore Button ---
            def handle_explore_click(plot_id_clicked, current_explored_plot_id):
                logging.info(f"Explore clicked for: {plot_id_clicked}. Currently explored: {current_explored_plot_id}")
                
                panel_visibility_updates = {} # {panel_component: gr.update}
                button_icon_updates = {}    # {button_component: gr.update}
                new_explored_id = None

                is_toggling_off = (plot_id_clicked == current_explored_plot_id)

                if is_toggling_off:
                    new_explored_id = None
                    button_icon_updates[plot_ui_objects[plot_id_clicked]["explore_button"]] = gr.update(value=EXPLORE_ICON)
                    logging.info(f"Un-exploring plot: {plot_id_clicked}")
                else:
                    new_explored_id = plot_id_clicked
                    button_icon_updates[plot_ui_objects[plot_id_clicked]["explore_button"]] = gr.update(value=ACTIVE_ICON)
                    # If another plot was explored, reset its button
                    if current_explored_plot_id and current_explored_plot_id != plot_id_clicked:
                        button_icon_updates[plot_ui_objects[current_explored_plot_id]["explore_button"]] = gr.update(value=EXPLORE_ICON)
                    logging.info(f"Exploring plot: {plot_id_clicked}")
                
                # Determine visibility for all panels
                for i in range(0, len(plot_configs), 2):
                    config1_id = plot_configs[i]["id"]
                    panel1 = plot_ui_objects[config1_id]["panel_component"]
                    
                    show_panel1 = True
                    if new_explored_id: # If any plot is explored
                        show_panel1 = (config1_id == new_explored_id)
                    panel_visibility_updates[panel1] = gr.update(visible=show_panel1)

                    if i + 1 < len(plot_configs):
                        config2_id = plot_configs[i+1]["id"]
                        # Only process second panel if it's in the same section as the first
                        if plot_configs[i+1]["section"] == plot_configs[i]["section"]:
                            panel2 = plot_ui_objects[config2_id]["panel_component"]
                            show_panel2 = True
                            if new_explored_id: # If any plot is explored
                                show_panel2 = (config2_id == new_explored_id)
                            # If panel1 is explored, panel2 in the same row should be hidden unless panel2 is the one being explored
                            if config1_id == new_explored_id and config2_id != new_explored_id :
                                show_panel2 = False
                            elif config2_id == new_explored_id and config1_id != new_explored_id:
                                show_panel1 = False # Re-evaluate panel1 if panel2 is explored
                                panel_visibility_updates[panel1] = gr.update(visible=show_panel1)


                            panel_visibility_updates[panel2] = gr.update(visible=show_panel2)
                        # else: panel2 is in a new section, will be handled when its turn comes as config1_id

                # Construct final updates list
                # Order: explored_plot_id_state, then all panel visibility, then all explore button icons
                final_updates = [new_explored_id]
                for cfg in plot_configs:
                    p_id = cfg["id"]
                    if p_id in plot_ui_objects:
                        panel = plot_ui_objects[p_id]["panel_component"]
                        final_updates.append(panel_visibility_updates.get(panel, gr.update())) # Default no change if not in updates
                        
                        explore_btn = plot_ui_objects[p_id]["explore_button"]
                        final_updates.append(button_icon_updates.get(explore_btn, gr.update(value=EXPLORE_ICON))) # Default to original icon
                
                return final_updates

            # --- Connect Action Buttons ---
            # Outputs for Insights/Formula: global_actions_column_ui, global_actions_markdown_ui, active_panel_action_state, + all bomb_buttons, + all formula_buttons
            action_buttons_outputs = [
                global_actions_column_ui, 
                global_actions_markdown_ui, 
                active_panel_action_state
            ]
            # Add all bomb and formula buttons to the output list for icon updates
            for cfg in plot_configs:
                pid = cfg["id"]
                if pid in plot_ui_objects:
                    action_buttons_outputs.append(plot_ui_objects[pid]["bomb_button"])
                    action_buttons_outputs.append(plot_ui_objects[pid]["formula_button"])
            
            # Outputs for Explore: explored_plot_id_state, + all panel_components, + all explore_buttons
            explore_buttons_outputs = [explored_plot_id_state]
            for cfg in plot_configs:
                pid = cfg["id"]
                if pid in plot_ui_objects:
                    explore_buttons_outputs.append(plot_ui_objects[pid]["panel_component"])
                    explore_buttons_outputs.append(plot_ui_objects[pid]["explore_button"])


            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=lambda p_id=plot_id: handle_panel_action(p_id, "insights", active_panel_action_state.value, token_state.value), # Use .value for state in lambda
                        inputs=None, # Inputs are passed via lambda closure and state.value
                        outputs=action_buttons_outputs,
                        api_name=f"action_insights_{plot_id}"
                    )
                    ui_obj["formula_button"].click(
                        fn=lambda p_id=plot_id: handle_panel_action(p_id, "formula", active_panel_action_state.value, token_state.value),
                        inputs=None,
                        outputs=action_buttons_outputs,
                        api_name=f"action_formula_{plot_id}"
                    )
                    ui_obj["explore_button"].click(
                        fn=lambda p_id=plot_id: handle_explore_click(p_id, explored_plot_id_state.value),
                        inputs=None,
                        outputs=explore_buttons_outputs,
                        api_name=f"action_explore_{plot_id}"
                    )

            # --- Function to Refresh All Analytics UI ---
            def refresh_all_analytics_ui_elements(current_token_state, date_filter_val, custom_start_val, custom_end_val):
                logging.info("Refreshing all analytics UI elements and resetting actions.")
                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

                # Plot figure updates
                for i, config in enumerate(plot_configs):
                    p_id_key = config["id"]
                    if p_id_key in plot_ui_objects:
                        if i < len(generated_plot_figures):
                            all_updates.append(generated_plot_figures[i])
                        else:
                            all_updates.append(create_placeholder_plot("Figure Error", f"No figure for {p_id_key}"))
                    else:
                         all_updates.append(None) # Placeholder if UI object doesn't exist

                # Reset Global Action Column
                all_updates.append(gr.update(visible=False)) 
                all_updates.append(gr.update(value="Click a button (💣, ƒ) on a plot...")) 
                all_updates.append(None) # Reset active_panel_action_state
                
                # Reset all button icons (bomb, formula, explore) and 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 (for explore reset)
                    else: # Add placeholders if UI object doesn't exist to keep list length
                        all_updates.extend([None,None,None,None])


                all_updates.append(None) # Reset explored_plot_id_state
                
                logging.info(f"Prepared {len(all_updates)} updates for analytics refresh.")
                return all_updates

            # --- Define outputs for the apply_filter_btn and sync.then() ---
            apply_filter_and_sync_outputs = [analytics_status_md]
            for config in plot_configs: # Plot components
                pid = config["id"]
                apply_filter_and_sync_outputs.append(plot_ui_objects[pid]["plot_component"] if pid in plot_ui_objects else None)
            
            apply_filter_and_sync_outputs.extend([ # Global action column and its state
                global_actions_column_ui, 
                global_actions_markdown_ui, 
                active_panel_action_state
            ])
            
            # Add all button components and panel components for reset
            for cfg in plot_configs:
                pid = cfg["id"]
                if pid in plot_ui_objects:
                    apply_filter_and_sync_outputs.append(plot_ui_objects[pid]["bomb_button"])
                    apply_filter_and_sync_outputs.append(plot_ui_objects[pid]["formula_button"])
                    apply_filter_and_sync_outputs.append(plot_ui_objects[pid]["explore_button"])
                    apply_filter_and_sync_outputs.append(plot_ui_objects[pid]["panel_component"])
                else:
                    apply_filter_and_sync_outputs.extend([None,None,None,None])


            apply_filter_and_sync_outputs.append(explored_plot_id_state)
            
            logging.info(f"Total outputs for apply_filter/sync: {len(apply_filter_and_sync_outputs)}")

            apply_filter_btn.click(
                fn=refresh_all_analytics_ui_elements,
                inputs=[token_state, date_filter_selector, custom_start_date_picker, custom_end_date_picker],
                outputs=apply_filter_and_sync_outputs,
                show_progress="full"
            )

        with gr.TabItem("3️⃣ Mentions", id="tab_mentions"):
            refresh_mentions_display_btn = gr.Button("🔄 Refresh Mentions Display", variant="secondary")
            mentions_html = gr.HTML("Mentions data...")
            mentions_sentiment_dist_plot = gr.Plot(label="Mention Sentiment Distribution")
            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 Follower Stats", id="tab_follower_stats"):
            refresh_follower_stats_btn = gr.Button("🔄 Refresh Follower Stats Display", variant="secondary")
            follower_stats_html = gr.HTML("Follower statistics...")
            with gr.Row():
                fs_plot_monthly_gains = gr.Plot(label="Monthly Follower Gains")
            with gr.Row():
                fs_plot_seniority = gr.Plot(label="Followers by Seniority (Top 10 Organic)")
                fs_plot_industry = gr.Plot(label="Followers by Industry (Top 10 Organic)")

            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], 
        outputs=apply_filter_and_sync_outputs, show_progress="full"
    )

if __name__ == "__main__":
    if not os.environ.get(LINKEDIN_CLIENT_ID_ENV_VAR):
        logging.warning(f"WARNING: '{LINKEDIN_CLIENT_ID_ENV_VAR}' env var not set.")
    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("WARNING: Bubble env vars not fully set.")

    try:
        logging.info(f"Matplotlib version: {matplotlib.__version__}, Backend: {matplotlib.get_backend()}")
    except ImportError:
        logging.error("Matplotlib is not installed. Plots will not be generated.")

    app.launch(server_name="0.0.0.0", server_port=7860, debug=True)