Update run_agentic_pipeline.py

run_agentic_pipeline.py

@@ -3,8 +3,7 @@ import pandas as pd
 import logging
 from typing import Dict, Any, List, Optional
 
-# --- MODIFIED: Import the reconstruction function ---
-# This function is now central to fetching the detailed OKR data.
+# 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
@@ -18,35 +17,31 @@ try:
 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
-    def format_report_for_display(report_data): return "Agentic modules not loaded. Report unavailable."
+    def format_report_for_display(report_data): return "Agentic modules not loaded."
     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."
+    def format_single_okr_for_display(okr_data, **kwargs): return "Agentic modules not loaded."
 
 logger = logging.getLogger(__name__)
 
-def load_and_display_agentic_results(token_state: dict):
+def load_and_display_agentic_results(token_state: dict, session_cache: dict):
     """
-    Loads pre-computed agentic results from the state, populates the report library dropdown,
-    and displays the LATEST report and its fully reconstructed OKRs by default.
-
-    This function is called on the initial application load.
+    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 containing the bubble_agentic_analysis_data DataFrame.
+        token_state: The main state dictionary with Bubble data.
+        session_cache: The session-specific cache for reconstructed data.
 
     Returns:
-        A tuple of Gradio updates matching the `agentic_display_outputs` list in `app.py`.
+        A tuple of Gradio updates, including the updated cache.
     """
-    # Default empty/initial return values that match the output components list. The order is critical.
     initial_updates = (
-        "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
+        "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.",
+        session_cache # Return the cache unchanged
     )
 
     if not AGENTIC_MODULES_LOADED:
@@ -57,79 +52,56 @@ def load_and_display_agentic_results(token_state: dict):
     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 in the state.")
+        logger.warning("Agentic analysis DataFrame is missing or empty.")
         return initial_updates
 
     try:
-        # --- 1. Prepare Report Library ---
         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.")
+            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()
-        ]
+        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
 
-        # --- 2. Process the Latest Report by Default ---
         latest_report_series = agentic_df.iloc[0]
         latest_report_id = latest_report_series['_id']
         
-        # Format the main report text for display
         report_display_md = format_report_for_display(latest_report_series)
-        
-        # 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. MODIFIED: Fetch, Reconstruct, and Prepare OKRs from the Latest Report ---
-        raw_results_state = None
-        okr_details_md = "No OKRs found in the latest report."
+        # --- 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, okr_details_md = None, "No OKRs found in the latest report."
         key_results_cbg_update = gr.update(choices=[], value=[], interactive=False)
         all_krs_state = []
         
-        # 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)
-                    ]
+                    output_md_parts = [format_single_okr_for_display(okr, okr_main_index=i) for i, okr in enumerate(okrs_list)]
                     okr_details_md = "\n\n---\n\n".join(output_md_parts) if output_md_parts else okr_details_md
         else:
-            logger.error(f"Failed to reconstruct full data for latest report ID {latest_report_id}")
+            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."
 
-
-        status_update = f"Status: Loaded {len(agentic_df)} reports. Displaying the latest from {latest_report_series['Created Date'].strftime('%Y-%m-%d')}."
+        status_update = f"Status: Loaded {len(agentic_df)} reports. Displaying latest from {latest_report_series['Created Date'].strftime('%Y-%m-%d')}."
         
-        # --- 4. Return all UI and State Updates ---
         return (
-            report_display_md,
-            report_selector_update,
-            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
+            report_display_md, report_selector_update, key_results_cbg_update,
+            okr_details_md, raw_results_state, [], all_krs_state, status_update,
+            updated_cache # Return the potentially updated cache
         )
 
     except Exception as e: