import gradio as gr import pandas as pd import logging from typing import Dict, Any, List, Optional # Import the reconstruction function that now expects a cache dictionary from services.report_data_handler import fetch_and_reconstruct_data_from_bubble # UI formatting functions try: from ui.insights_ui_generator import ( format_report_for_display, # REMOVED: extract_key_results_for_selection, - No longer directly used here for display # REMOVED: format_single_okr_for_display - No longer directly used here for display ) # NEW: Import the enhanced OKR display functions from ui.okr_ui_generator import format_okrs_for_enhanced_display, get_initial_okr_display 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 for when modules are not loaded, ensuring return signatures match def format_report_for_display(report_data): return {'header_html': '

Agentic modules not loaded.

', 'body_markdown': 'Report display unavailable.'} # These functions are now used by app.py directly for placeholder returns if modules are not loaded, # but their definitions might still be expected in some contexts, so providing minimal ones. def extract_key_results_for_selection(okrs_dict): return [] def format_single_okr_for_display(okr_data, **kwargs): return "Agentic modules not loaded." # Placeholder for the new OKR UI display def format_okrs_for_enhanced_display(raw_results): return get_initial_okr_display() def get_initial_okr_display(): return """
🎯 AI-Generated OKRs & Strategic Tasks
Intelligent objectives and key results based on your LinkedIn analytics
0
Objectives
0
Key Results
0
Tasks
0
High Priority
⚠️
Modules Not Loaded
Agentic analysis modules could not be loaded. OKR display unavailable.
""" logger = logging.getLogger(__name__) def load_and_display_agentic_results(token_state: dict, session_cache: dict): """ Loads agentic results from state, populates the report library, and displays the LATEST report and its fully reconstructed OKRs by default, using a session-specific cache. Args: token_state: The main state dictionary with Bubble data. session_cache: The session-specific cache for reconstructed data. Returns: A tuple of Gradio updates, including the updated cache, the new enhanced OKR HTML, and the extracted actionable_okrs_dict. This function now returns 12 values to match the expected outputs in app.py. """ # Define placeholder content for empty or error states to match 12 outputs empty_header_html = """
📊 Comprehensive Analysis Report
AI-Generated Insights from Your LinkedIn Data
Generated from Bubble.io
""" empty_body_markdown_no_selection = """
📄
No Report Selected
Please select a report from the library above to view its detailed analysis and insights.
""" # Default initial updates for 12 outputs initial_updates = ( gr.update(value="Status: No agentic analysis data found."), # 0: agentic_pipeline_status_md gr.update(choices=[], value=None, interactive=False), # 1: report_selector_dd gr.update(choices=[], value=[], interactive=False), # 2: key_results_cbg (hidden in app.py) gr.update(value="No OKRs to display."), # 3: okr_detail_display_md (hidden in app.py) gr.update(value=None), # 4: orchestration_raw_results_st gr.update(value=[]), # 5: selected_key_result_ids_st (hidden in app.py) gr.update(value=[]), # 6: key_results_for_selection_st (hidden in app.py) gr.update(value=empty_header_html), # 7: report_header_html_display gr.update(value=empty_body_markdown_no_selection), # 8: report_body_markdown_display gr.update(value=session_cache), # 9: reconstruction_cache_st gr.update(value=get_initial_okr_display()), # 10: enhanced_okr_display_html gr.update(value={}) # 11: actionable_okrs_data_st (NEW) ) if not AGENTIC_MODULES_LOADED: logger.error("Agentic modules not loaded, returning placeholder updates.") # Ensure error updates match the 12-item signature error_header_html = '
Error Loading Report
Agentic modules not loaded.
Error
' error_body_markdown = '
Module Error
Agentic analysis modules could not be loaded. Report display unavailable.
' return ( gr.update(value="Status: Critical module import error."), # 0 gr.update(choices=[], value=None, interactive=False), # 1 gr.update(choices=[], value=[], interactive=False), # 2 gr.update(value="Agentic modules not loaded. No OKRs to display."), # 3 gr.update(value=None), # 4 gr.update(value=[]), # 5 gr.update(value=[]), # 6 gr.update(value=error_header_html), # 7 gr.update(value=error_body_markdown), # 8 gr.update(value=session_cache), # 9 gr.update(value=get_initial_okr_display()), # 10: Placeholder for enhanced OKR display gr.update(value={}) # 11: Placeholder for actionable_okrs_data_st (NEW) ) agentic_df = token_state.get("bubble_agentic_analysis_data") if agentic_df is None or agentic_df.empty: logger.warning("Agentic analysis DataFrame is missing or empty.") return initial_updates try: if 'Created Date' not in agentic_df.columns or '_id' not in agentic_df.columns: raise KeyError("Required columns ('Created Date', '_id') not found.") agentic_df['Created Date'] = pd.to_datetime(agentic_df['Created Date']) agentic_df = agentic_df.sort_values(by='Created Date', ascending=False).reset_index(drop=True) report_choices = [(f"{row.get('report_type', 'Report')} - {row['Created Date'].strftime('%Y-%m-%d %H:%M')}", row['_id']) for _, row in agentic_df.iterrows()] if not report_choices: return initial_updates quarterly_reports_df = agentic_df[agentic_df['report_type'] == 'Quarter'].copy() if quarterly_reports_df.empty: logger.warning("No quarterly reports found, falling back to latest available report.") latest_report_series = agentic_df.iloc[0] # Use the absolute latest if no quarterly else: latest_report_series = quarterly_reports_df.iloc[0] latest_report_id = latest_report_series['_id'] # Split the formatted report content into header and body formatted_report_parts = format_report_for_display(latest_report_series) report_header_content = formatted_report_parts['header_html'] report_body_content = formatted_report_parts['body_markdown'] report_selector_update = gr.update(choices=report_choices, value=latest_report_id, interactive=True) # --- MODIFIED: Use the session cache for data reconstruction --- reconstructed_data, updated_cache = fetch_and_reconstruct_data_from_bubble(latest_report_series, session_cache) raw_results_state = None okr_details_md = "No OKRs found in the latest report." # This is for the old, hidden component enhanced_okr_html_content = get_initial_okr_display() # Default to loading state or empty actionable_okrs_dict_for_state = {} # NEW: Initialize the new state variable key_results_cbg_update = gr.update(choices=[], value=[], interactive=False) all_krs_state = [] if reconstructed_data: raw_results_state = reconstructed_data actionable_okrs_dict = raw_results_state.get("actionable_okrs", {}) # Refined check for actionable_okrs_dict content if actionable_okrs_dict and isinstance(actionable_okrs_dict, dict) and actionable_okrs_dict.get("okrs"): actionable_okrs_dict_for_state = actionable_okrs_dict # Store for the new state # Format for the new enhanced HTML display enhanced_okr_html_content = format_okrs_for_enhanced_display(raw_results_state) else: logger.info(f"No 'actionable_okrs' key or 'okrs' list found in reconstructed data for report ID {latest_report_id}. " f"Content of 'actionable_okrs_dict': {actionable_okrs_dict}") enhanced_okr_html_content = get_initial_okr_display() # Show empty state if no OKRs else: logger.error(f"Failed to reconstruct data for latest report ID {latest_report_id}") okr_details_md = "Error: Could not reconstruct OKR data for this report." enhanced_okr_html_content = get_initial_okr_display() # Show empty state on reconstruction error status_update = f"Status: Loaded {len(agentic_df)} reports. Displaying latest from {latest_report_series['Created Date'].strftime('%Y-%m-%d')}." return ( gr.update(value=status_update), # 0: agentic_pipeline_status_md report_selector_update, # 1: report_selector_dd key_results_cbg_update, # 2: key_results_cbg (kept for compatibility) gr.update(value=okr_details_md), # 3: okr_detail_display_md (kept for compatibility) gr.update(value=raw_results_state), # 4: orchestration_raw_results_st gr.update(value=[]), # 5: selected_key_result_ids_st (kept for compatibility) gr.update(value=all_krs_state), # 6: key_results_for_selection_st (kept for compatibility) gr.update(value=report_header_content), # 7: report_header_html_display gr.update(value=report_body_content), # 8: report_body_markdown_display gr.update(value=updated_cache), # 9: reconstruction_cache_st gr.update(value=enhanced_okr_html_content), # 10: NEW: The enhanced HTML display for OKRs gr.update(value=actionable_okrs_dict_for_state) # 11: NEW: Explicit actionable_okrs_data_st ) except Exception as e: logger.error(f"Failed to process and display agentic results: {e}", exc_info=True) # Ensure error returns match the 12-item signature error_header_html = """
⚠️ Error Loading Report
An error occurred during data processing.
Error
""" error_body_markdown = f"""
🚨
Report Loading Failed
An error occurred while loading or processing the report data: {e}. Please try again or contact support if the issue persists.
""" return ( gr.update(value=f"Status: An error occurred: {e}"), # 0 gr.update(choices=[], value=None, interactive=False), # 1 gr.update(choices=[], value=[], interactive=False), # 2 gr.update(value="Error: Could not display OKRs due to an error."), # 3 gr.update(value=None), # 4 gr.update(value=[]), # 5 gr.update(value=[]), # 6 gr.update(value=error_header_html), # 7 gr.update(value=error_body_markdown), # 8 gr.update(value=session_cache), # 9 gr.update(value=get_initial_okr_display()), # 10: Placeholder for enhanced OKR display on error gr.update(value={}) # 11: Placeholder for actionable_okrs_data_st on error )