import gradio as gr import pandas as pd import os import logging from collections import defaultdict import matplotlib matplotlib.use('Agg') # Set backend for Matplotlib # --- Module Imports --- from utils.gradio_utils import get_url_user_token # Functions from newly created/refactored modules from config import ( PLOT_ID_TO_FORMULA_KEY_MAP, LINKEDIN_CLIENT_ID_ENV_VAR, BUBBLE_APP_NAME_ENV_VAR, BUBBLE_API_KEY_PRIVATE_ENV_VAR, BUBBLE_API_ENDPOINT_ENV_VAR ) from services.analytics_tab_module import AnalyticsTab # UPDATED: Using the new data loading function from the refactored state manager from services.state_manager import load_data_from_bubble from ui.ui_generators import ( build_analytics_tab_plot_area, build_home_tab_ui, # NEW: Import the function to build the Home tab UI create_enhanced_report_tab, # NEW: Import the function to build the enhanced Report tab UI BOMB_ICON, EXPLORE_ICON, FORMULA_ICON, ACTIVE_ICON ) #ui import from ui.config import custom_title_css # NEW: Import the new OKR UI functions from ui.okr_ui_generator import create_enhanced_okr_tab, format_okrs_for_enhanced_display, get_initial_okr_display from ui.analytics_plot_generator import update_analytics_plots_figures, create_placeholder_plot from formulas import PLOT_FORMULAS # --- CHATBOT MODULE IMPORTS --- from features.chatbot.chatbot_prompts import get_initial_insight_prompt_and_suggestions from features.chatbot.chatbot_handler import generate_llm_response # --- AGENTIC PIPELINE (DISPLAY ONLY) IMPORTS --- try: # This is the main function called on initial load to populate the agentic tabs from run_agentic_pipeline import load_and_display_agentic_results # This function is now called when a new report is selected from the dropdown from services.report_data_handler import fetch_and_reconstruct_data_from_bubble # UI formatting functions from ui.insights_ui_generator import ( format_report_for_display, # This will now return header HTML and body Markdown # REMOVED: extract_key_results_for_selection, - Moved to okr_ui_generator (implicitly) # REMOVED: format_single_okr_for_display - Moved to okr_ui_generator (implicitly) ) AGENTIC_MODULES_LOADED = True except ImportError as e: logging.error(f"Could not import agentic pipeline display modules: {e}. Tabs 3 and 4 will be disabled.") AGENTIC_MODULES_LOADED = False # Placeholder functions to prevent app from crashing if imports fail def load_and_display_agentic_results(*args, **kwargs): # NOTE: This return signature MUST match agentic_display_outputs # Adjusted return values for the new split report display components and the new OKR HTML empty_header_html = """
📝 Comprehensive Analysis Report
AI-Generated Insights from Your LinkedIn Data
Generated from Bubble.io
""" empty_body_markdown = """
📄
No Report Selected
Please select a report from the library above to view its detailed analysis and insights.
""" # The load_and_display_agentic_results function returns many values. # Ensure the placeholder returns the correct number of gr.update components # matching the `outputs` in the .then() call later. return ( gr.update(value="Modules not loaded."), # agentic_pipeline_status_md (0) gr.update(choices=[], value=None), # report_selector_dd (1) gr.update(choices=[], value=[]), # key_results_cbg (2) - KEPT HIDDEN for compatibility gr.update(value="Modules not loaded."), # okr_detail_display_md (3) - KEPT HIDDEN for compatibility None, # orchestration_raw_results_st (4) [], # selected_key_result_ids_st (5) - KEPT HIDDEN for compatibility [], # key_results_for_selection_st (6) - KEPT HIDDEN for compatibility gr.update(value=empty_header_html), # report_header_html_display (7) gr.update(value=empty_body_markdown), # report_body_markdown_display (8) {}, # reconstruction_cache_st (9) gr.update(value=get_initial_okr_display()), # NEW: enhanced_okr_display_html (10) gr.update(value={}) # NEW: actionable_okrs_data_st (11) ) def fetch_and_reconstruct_data_from_bubble(*args, **kwargs): return None, {} def format_report_for_display(report_data): # Placeholder for when modules are not loaded, returns structure matching the new design return {'header_html': '

Agentic modules not loaded.

', 'body_markdown': 'Report display unavailable.'} with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"), title="LinkedIn Organization Dashboard") as app: # --- STATE MANAGEMENT --- 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(), "bubble_agentic_analysis_data": pd.DataFrame(), # To store agentic results from Bubble "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" }) # States for analytics tab chatbot chat_histories_st = gr.State({}) current_chat_plot_id_st = gr.State(None) plot_data_for_chatbot_st = gr.State({}) # States for agentic results display orchestration_raw_results_st = gr.State(None) # KEPT for compatibility with load_and_display_agentic_results signature key_results_for_selection_st = gr.State([]) selected_key_result_ids_st = gr.State([]) # --- NEW: Session-specific cache for reconstructed OKR data --- reconstruction_cache_st = gr.State({}) # NEW: State to hold the actionable_okrs dictionary explicitly actionable_okrs_data_st = gr.State({}) # --- UI LAYOUT --- # --- ENHANCED UI HEADER --- with gr.Row(): with gr.Column(): gr.HTML("""
🚀LinkedIn Organization Dashboard
Advanced Analytics & AI-Powered Insights for Your LinkedIn Performance
""") url_user_token_display = gr.Textbox(label="User Token (Hidden)", interactive=False, visible=False) org_urn_display = gr.Textbox(label="Org URN (Hidden)", interactive=False, visible=False) # MODIFIED: Initially hide the status_box and make its value empty status_box = gr.Textbox(label="Status", interactive=False, value="", 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_data_load_sequence(url_token, org_urn_val, current_state): """ Handles the initial data loading from Bubble and controls status_box visibility. """ status_msg, new_state = load_data_from_bubble(url_token, org_urn_val, current_state) # Determine if the status box should be visible # It should be visible if the token is not available (None) # OR if the status message indicates an error or warning, even if a token *might* be present. show_status_box = False if new_state.get("token") is None: show_status_box = True elif "Error" in status_msg or "Warning" in status_msg: show_status_box = True # Return the gr.update object to control value and visibility return gr.update(value=status_msg, visible=show_status_box), new_state analytics_icons = {'bomb': BOMB_ICON, 'explore': EXPLORE_ICON, 'formula': FORMULA_ICON, 'active': ACTIVE_ICON} analytics_tab_instance = AnalyticsTab( token_state=token_state, chat_histories_st=chat_histories_st, current_chat_plot_id_st=current_chat_plot_id_st, plot_data_for_chatbot_st=plot_data_for_chatbot_st, plot_id_to_formula_map=PLOT_ID_TO_FORMULA_KEY_MAP, plot_formulas_data=PLOT_FORMULAS, icons=analytics_icons, fn_build_plot_area=build_analytics_tab_plot_area, fn_update_plot_figures=update_analytics_plots_figures, fn_create_placeholder_plot=create_placeholder_plot, fn_get_initial_insight=get_initial_insight_prompt_and_suggestions, fn_generate_llm_response=generate_llm_response ) def update_report_display(selected_report_id: str, current_token_state: dict): """ Updates the report header and body display when a new report is selected. This function now expects format_report_for_display to return a dict with 'header_html' and 'body_markdown'. """ # Define empty states for header and body empty_header_html = """
📝 Comprehensive Analysis Report
AI-Generated Insights from Your LinkedIn Data
Generated from Bubble.io
""" empty_body_markdown_no_selection = """
📋
Select a Report
Choose a report from the dropdown above to view its detailed analysis and insights.
""" empty_body_markdown_no_data = """
⚠️
Data Not Available
Analysis data is not loaded or is empty. Please try refreshing the page.
""" empty_body_markdown_not_found = lambda _id: f"""
❌
Report Not Found
Report with ID '{_id}' was not found in the database.
""" if not selected_report_id: # When no report is selected, update both header and body return gr.update(value=empty_header_html), gr.update(value=empty_body_markdown_no_selection) agentic_df = current_token_state.get("bubble_agentic_analysis_data") if agentic_df is None or agentic_df.empty: # When no data is available, update both header and body return gr.update(value=empty_header_html), gr.update(value=empty_body_markdown_no_data) selected_report_series_df = agentic_df[agentic_df['_id'] == selected_report_id] if selected_report_series_df.empty: # When report is not found, update both header and body return gr.update(value=empty_header_html), gr.update(value=empty_body_markdown_not_found(selected_report_id)) selected_report_series = selected_report_series_df.iloc[0] # Call the format_report_for_display, which now returns a dict formatted_content_parts = format_report_for_display(selected_report_series) # Update the two separate Gradio components return ( gr.update(value=formatted_content_parts['header_html']), gr.update(value=formatted_content_parts['body_markdown']) ) with gr.Tabs() as tabs: # --- NEW HOME TAB --- with gr.TabItem("🏠 Home", id="tab_home"): # Call the new function from ui_generators to build the Home tab content btn_graphs, btn_reports, btn_okr, btn_help = build_home_tab_ui() # Link buttons to tab selection btn_graphs.click(fn=lambda: gr.update(selected="tab_analytics_module"), outputs=tabs) btn_reports.click(fn=lambda: gr.update(selected="tab_agentic_report"), outputs=tabs) btn_okr.click(fn=lambda: gr.update(selected="tab_agentic_okrs"), outputs=tabs) # btn_help.click(fn=lambda: gr.update(selected="tab_help"), outputs=tabs) # Uncomment if you add a help tab analytics_tab_instance.create_tab_ui() # This is the "Graphs" tab, assuming its ID is "tab_analytics" # --- REPLACED: Agentic Analysis Report Tab with enhanced UI --- # The create_enhanced_report_tab function now builds this entire tab's UI. # It also returns the relevant Gradio components needed for callbacks. with gr.TabItem("📝 AI Analysis Reports", id="tab_agentic_report", visible=AGENTIC_MODULES_LOADED): # The create_enhanced_report_tab function handles the CSS and HTML structure # MODIFIED: Unpacked 4 values instead of 3 agentic_pipeline_status_md, report_selector_dd, report_header_html_display, report_body_markdown_display = \ create_enhanced_report_tab(AGENTIC_MODULES_LOADED) with gr.TabItem("🎯 OKRs & Action Items", id="tab_agentic_okrs", visible=AGENTIC_MODULES_LOADED): gr.Markdown("## 🎯 AI Generated OKRs and Actionable Tasks (from Bubble.io)") gr.Markdown("Basato sull'analisi AI, l'agente ha proposto i seguenti OKR.") if not AGENTIC_MODULES_LOADED: gr.Markdown("🔴 **Error:** Agentic modules could not be loaded.") # Keep the old components but make them invisible to maintain load_and_display_agentic_results signature with gr.Column(visible=False): gr.Markdown("### Suggested Key Results (OLD UI - HIDDEN)") key_results_cbg = gr.CheckboxGroup(label="Select Key Results", choices=[], value=[], interactive=True) gr.Markdown("### Detailed OKRs and Tasks (OLD UI - HIDDEN)") okr_detail_display_md = gr.Markdown("I dettagli OKR appariranno qui.") # NEW: Add the enhanced OKR display HTML component enhanced_okr_display_html = create_enhanced_okr_tab() # REMOVED: The old update_okr_display_on_selection function and its change event # as the new UI handles display dynamically from raw_results_st if AGENTIC_MODULES_LOADED: report_selector_dd.change( fn=update_report_display, # This now calls the enhanced function # MODIFIED: Updated outputs to match the two new display components inputs=[report_selector_dd, token_state], outputs=[report_header_html_display, report_body_markdown_display], show_progress="minimal" ) # Ensure agentic_display_outputs correctly maps to the newly created components # This list must match the outputs of load_and_display_agentic_results agentic_display_outputs = [ agentic_pipeline_status_md, # 0: Status Markdown (hidden) report_selector_dd, # 1: Dropdown for selecting reports key_results_cbg, # 2: Checkbox group for OKRs (kept hidden) okr_detail_display_md, # 3: Markdown for detailed OKR display (kept hidden) orchestration_raw_results_st, # 4: Raw results state selected_key_result_ids_st, # 5: Selected KR IDs state (kept hidden) key_results_for_selection_st, # 6: All KRs for selection state (kept hidden) report_header_html_display, # 7: New HTML output for header report_body_markdown_display, # 8: New Markdown output for body reconstruction_cache_st, # 9: Reconstruction cache state enhanced_okr_display_html, # 10: NEW: The enhanced HTML display for OKRs actionable_okrs_data_st # 11: NEW: The actionable_okrs dictionary state ] # MODIFIED: Chain the initial_load_event to first show "Loading...", then perform data load. initial_load_event = org_urn_display.change( fn=lambda: gr.update(value="Loading data...", visible=True), # Show loading message immediately inputs=[], outputs=[status_box], show_progress="full" ).then( fn=initial_data_load_sequence, inputs=[url_user_token_display, org_urn_display, token_state], outputs=[status_box, token_state], # status_box is updated here with final message/visibility show_progress="full" ) initial_load_event.then( fn=analytics_tab_instance._refresh_analytics_graphs_ui, inputs=[token_state, analytics_tab_instance.date_filter_selector, analytics_tab_instance.custom_start_date_picker, analytics_tab_instance.custom_end_date_picker, chat_histories_st], outputs=analytics_tab_instance.graph_refresh_outputs_list, show_progress="full" ).then( fn=load_and_display_agentic_results, inputs=[token_state, reconstruction_cache_st], # MODIFIED: Updated outputs to match all components returned by load_and_display_agentic_results (now 12) outputs=agentic_display_outputs, show_progress="minimal" ).then( # NEW CHAIN: Update the enhanced OKR display after load_and_display_agentic_results runs fn=format_okrs_for_enhanced_display, inputs=[reconstruction_cache_st], # Change from actionable_okrs_data_st to reconstruction_cache_st outputs=[enhanced_okr_display_html], show_progress="minimal" ) if __name__ == "__main__": if not os.environ.get(LINKEDIN_CLIENT_ID_ENV_VAR): logging.warning(f"WARNING: '{LINKEDIN_CLIENT_ID_ENV_VAR}' is not set.") 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("WARNING: One or more Bubble environment variables are not set.") if not AGENTIC_MODULES_LOADED: logging.warning("CRITICAL: Agentic modules failed to load.") if not os.environ.get("GEMINI_API_KEY"): logging.warning("WARNING: 'GEMINI_API_KEY' is not set.") app.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)), debug=True)