Update run_agentic_pipeline.py

run_agentic_pipeline.py

@@ -1,11 +1,13 @@
 import gradio as gr
 import pandas as pd
-import json
 import logging
 from typing import Dict, Any, List, Optional
 
-# Assuming these functions are in ui.insights_ui_generator
-# Make sure to have this file updated with the new `format_report_for_display` function
+# --- MODIFIED: Import the reconstruction function ---
+# This function is now central to fetching the detailed OKR data.
+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,
@@ -20,50 +22,31 @@ except ImportError as e:
     def extract_key_results_for_selection(okrs_dict): return []
     def format_single_okr_for_display(okr_data, **kwargs): return "Agentic modules not loaded. OKR display unavailable."
 
-
 logger = logging.getLogger(__name__)
 
-def load_and_display_agentic_results(
-    token_state: dict, 
-    orchestration_raw_results_st: Optional[dict], 
-    selected_key_result_ids_st: List[str], 
-    key_results_for_selection_st: List[dict]
-):
+def load_and_display_agentic_results(token_state: dict):
     """
     Loads pre-computed agentic results from the state, populates the report library dropdown,
-    and displays the latest report and its associated OKRs by default.
+    and displays the LATEST report and its fully reconstructed OKRs by default.
 
-    This function is designed to work with the UI defined in app.py and expects a specific
-    order of outputs.
+    This function is called on the initial application load.
 
     Args:
         token_state: The main state dictionary containing the bubble_agentic_analysis_data DataFrame.
-        orchestration_raw_results_st: The state holding the raw JSON/dict of the currently displayed report.
-        selected_key_result_ids_st: The state for the IDs of selected Key Results.
-        key_results_for_selection_st: The state holding the list of all available Key Results for selection.
 
     Returns:
         A tuple of Gradio updates matching the `agentic_display_outputs` list in `app.py`.
     """
-    # Default empty/initial return values that match the output components list
-    # The order is critical:
-    # 1. agentic_report_display_md
-    # 2. report_selector_dd
-    # 3. key_results_cbg
-    # 4. okr_detail_display_md
-    # 5. orchestration_raw_results_st
-    # 6. selected_key_result_ids_st
-    # 7. key_results_for_selection_st
-    # 8. agentic_pipeline_status_md
+    # Default empty/initial return values that match the output components list. The order is critical.
     initial_updates = (
-        "No agentic analysis data found in Bubble.",
-        gr.update(choices=[], value=None, interactive=False),
-        gr.update(choices=[], value=[], interactive=False),
-        "No OKRs to display.",
-        None,
-        [],
-        [],
-        "Status: No agentic analysis data found."
+        "No agentic analysis data found in Bubble.",          # 1. agentic_report_display_md
+        gr.update(choices=[], value=None, interactive=False), # 2. report_selector_dd
+        gr.update(choices=[], value=[], interactive=False),   # 3. key_results_cbg
+        "No OKRs to display.",                                # 4. okr_detail_display_md
+        None,                                                 # 5. orchestration_raw_results_st
+        [],                                                   # 6. selected_key_result_ids_st
+        [],                                                   # 7. key_results_for_selection_st
+        "Status: No agentic analysis data found."             # 8. agentic_pipeline_status_md
     )
 
     if not AGENTIC_MODULES_LOADED:
@@ -82,11 +65,9 @@ def load_and_display_agentic_results(
         if 'Created Date' not in agentic_df.columns or '_id' not in agentic_df.columns:
             raise KeyError("Required columns ('Created Date', '_id') not found in agentic data.")
         
-        # Ensure 'Created Date' is datetime, then sort to get the latest report first
         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)
         
-        # Create choices for the dropdown: (Display Name, Unique ID)
         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()
@@ -95,56 +76,57 @@ def load_and_display_agentic_results(
         if not report_choices:
             return initial_updates
 
-        # --- 2. Load and Display the Latest Report by Default ---
+        # --- 2. Process the Latest Report by Default ---
         latest_report_series = agentic_df.iloc[0]
         latest_report_id = latest_report_series['_id']
         
-        # Format the latest report's content for the Markdown display
+        # Format the main report text for display
         report_display_md = format_report_for_display(latest_report_series)
         
-        # Create the update for the report library dropdown
+        # Update the report library dropdown and select the latest one
         report_selector_update = gr.update(choices=report_choices, value=latest_report_id, interactive=True)
 
-        # --- 3. Load and Prepare OKRs from the Latest Report ---
+        # --- 3. MODIFIED: Fetch, Reconstruct, and Prepare OKRs from the Latest Report ---
         raw_results_state = None
         okr_details_md = "No OKRs found in the latest report."
         key_results_cbg_update = gr.update(choices=[], value=[], interactive=False)
         all_krs_state = []
         
-        # Assumption: The full JSON from the agent is stored in 'orchestration_results'.
-        if 'orchestration_results' in latest_report_series and pd.notna(latest_report_series['orchestration_results']):
-            try:
-                raw_results_state = json.loads(latest_report_series['orchestration_results'])
-            except json.JSONDecodeError:
-                logger.error(f"Failed to parse 'orchestration_results' JSON for report ID {latest_report_id}")
-                raw_results_state = {} # Avoid crashing, proceed with empty data
+        # Call the key function to get all linked data (OKRs, KRs, Tasks) from Bubble
+        reconstructed_data = fetch_and_reconstruct_data_from_bubble(latest_report_series)
+        
+        if reconstructed_data:
+            raw_results_state = reconstructed_data
+            actionable_okrs_dict = raw_results_state.get("actionable_okrs", {})
+            
+            if actionable_okrs_dict:
+                all_krs_state = extract_key_results_for_selection(actionable_okrs_dict)
+                if all_krs_state:
+                    # Populate the Key Results checkbox group
+                    kr_choices = [(kr['kr_description'], kr['unique_kr_id']) for kr in all_krs_state]
+                    key_results_cbg_update = gr.update(choices=kr_choices, value=[], interactive=True)
+                    
+                    # Format all OKRs for the initial detailed display
+                    okrs_list = actionable_okrs_dict.get("okrs", [])
+                    output_md_parts = [
+                        format_single_okr_for_display(okr_data, okr_main_index=okr_idx)
+                        for okr_idx, okr_data in enumerate(okrs_list)
+                    ]
+                    okr_details_md = "\n\n---\n\n".join(output_md_parts) if output_md_parts else okr_details_md
         else:
-            raw_results_state = {}
+            logger.error(f"Failed to reconstruct full data for latest report ID {latest_report_id}")
+            okr_details_md = "Error: Could not reconstruct OKR data for this report."
 
-        actionable_okrs_dict = raw_results_state.get("actionable_okrs", {})
-        
-        if actionable_okrs_dict:
-            all_krs_state = extract_key_results_for_selection(actionable_okrs_dict)
-            if all_krs_state:
-                kr_choices = [(kr['kr_description'], kr['unique_kr_id']) for kr in all_krs_state]
-                key_results_cbg_update = gr.update(choices=kr_choices, value=[], interactive=True)
-                
-                # Format all OKRs for initial display
-                okrs_list = actionable_okrs_dict.get("okrs", [])
-                output_md_parts = [
-                    format_single_okr_for_display(okr_data, okr_main_index=okr_idx)
-                    for okr_idx, okr_data in enumerate(okrs_list)
-                ]
-                okr_details_md = "\n\n---\n\n".join(output_md_parts) if output_md_parts else okr_details_md
 
         status_update = f"Status: Loaded {len(agentic_df)} reports. Displaying the latest from {latest_report_series['Created Date'].strftime('%Y-%m-%d')}."
         
+        # --- 4. Return all UI and State Updates ---
         return (
-            report_display_md, 
+            report_display_md,
             report_selector_update,
-            key_results_cbg_update, 
-            okr_details_md, 
-            raw_results_state, 
+            key_results_cbg_update,
+            okr_details_md,
+            raw_results_state, # This is now the fully reconstructed dictionary
             [], # Reset selected KRs
             all_krs_state,
             status_update