Update run_agentic_pipeline.py

run_agentic_pipeline.py

@@ -30,7 +30,6 @@ from data_processing.analytics_data_processing import prepare_filtered_analytics
 logger = logging.getLogger(__name__)
 
 
-
 async def run_full_analytics_orchestration(
     token_state: Dict[str, Any],
     date_filter_selection: str,
@@ -107,3 +106,112 @@ async def run_full_analytics_orchestration(
         logger.critical(f"Critical error during analytics orchestration: {e}", exc_info=True)
         return None
 
+
+
+async def run_agentic_pipeline_autonomously(current_token_state_val):
+    logging.info(f"Agentic pipeline check triggered for token_state update. Current token: {'Set' if current_token_state_val.get('token') else 'Not Set'}")
+    # Initial state before pipeline runs or if skipped
+    initial_yield = (
+        gr.update(value="Pipeline AI: In attesa dei dati necessari..."), # agentic_report_display_md
+        gr.update(choices=[], value=[], interactive=False),             # key_results_cbg
+        gr.update(value="Pipeline AI: In attesa dei dati necessari..."), # okr_detail_display_md
+        orchestration_raw_results_st.value, # Preserve current raw results
+        selected_key_result_ids_st.value,   # Preserve current selection
+        key_results_for_selection_st.value, # Preserve current options
+        "Pipeline AI: In attesa dei dati..." # agentic_pipeline_status_md
+    )
+
+    if not current_token_state_val or not current_token_state_val.get("token"):
+        logging.info("Agentic pipeline: Token not available in token_state. Skipping.")
+        yield initial_yield
+        return
+
+    logging.info("Agentic pipeline starting autonomously with 'Sempre' filter.")
+    # Update status to indicate processing
+    yield (
+        gr.update(value="Analisi AI (Sempre) in corso..."),
+        gr.update(choices=[], value=[], interactive=False), # Keep CBG disabled during run
+        gr.update(value="Dettagli OKR (Sempre) in corso di generazione..."),
+        orchestration_raw_results_st.value, # Preserve
+        selected_key_result_ids_st.value,   # Preserve
+        key_results_for_selection_st.value, # Preserve
+        "Esecuzione pipeline AI (Sempre)..."
+    )
+
+    if not AGENTIC_MODULES_LOADED:
+        logging.warning("Agentic modules not loaded. Skipping autonomous pipeline.")
+        yield (
+            gr.update(value="Moduli AI non caricati. Report non disponibile."),
+            gr.update(choices=[], value=[], interactive=False),
+            gr.update(value="Moduli AI non caricati. OKR non disponibili."),
+            None, [], [], "Pipeline AI: Moduli non caricati."
+        )
+        return
+
+    try:
+        # Parameters for 'Sempre' filter for the agentic pipeline
+        date_filter_val_agentic = "Sempre"
+        custom_start_val_agentic = None
+        custom_end_val_agentic = None
+
+        orchestration_output = await run_full_analytics_orchestration(
+            current_token_state_val,
+            date_filter_val_agentic,
+            custom_start_val_agentic,
+            custom_end_val_agentic
+        )
+        agentic_status_text = "Pipeline AI (Sempre) completata."
+        logging.info(f"Autonomous agentic pipeline finished. Output keys: {orchestration_output.keys() if orchestration_output else 'None'}")
+
+        if orchestration_output:
+            orchestration_results_update = orchestration_output # Store full results in state
+            report_str = orchestration_output.get('comprehensive_analysis_report', "Nessun report dettagliato fornito.")
+            agentic_report_md_update = gr.update(value=format_report_to_markdown(report_str))
+
+            actionable_okrs = orchestration_output.get('actionable_okrs_and_tasks') # This is the dict containing 'okrs' list
+            krs_for_ui_selection_list = extract_key_results_for_selection(actionable_okrs) # Expects the dict
+            
+            krs_for_selection_update = krs_for_ui_selection_list # Update state with list of KR dicts
+            
+            # Choices for CheckboxGroup: list of (label, value) tuples
+            kr_choices_for_cbg = [(kr['kr_description'], kr['unique_kr_id']) for kr in krs_for_ui_selection_list]
+            key_results_cbg_update = gr.update(choices=kr_choices_for_cbg, value=[], interactive=True) # Reset selection
+
+            # Display all OKRs by default after pipeline run
+            all_okrs_md_parts = []
+            if actionable_okrs and isinstance(actionable_okrs.get("okrs"), list):
+                for okr_idx, okr_item in enumerate(actionable_okrs["okrs"]):
+                    all_okrs_md_parts.append(format_single_okr_for_display(okr_item, accepted_kr_indices=None, okr_main_index=okr_idx))
+            
+            if not all_okrs_md_parts:
+                okr_detail_display_md_update = gr.update(value="Nessun OKR generato o trovato (Sempre).")
+            else:
+                okr_detail_display_md_update = gr.update(value="\n\n---\n\n".join(all_okrs_md_parts))
+            
+            selected_krs_update = [] # Reset selected KRs state
+        else:
+            agentic_report_md_update = gr.update(value="Nessun report generato dalla pipeline AI (Sempre).")
+            key_results_cbg_update = gr.update(choices=[], value=[], interactive=False)
+            okr_detail_display_md_update = gr.update(value="Nessun OKR generato o errore nella pipeline AI (Sempre).")
+            orchestration_results_update = None
+            selected_krs_update = []
+            krs_for_selection_update = []
+
+        yield (
+            agentic_report_md_update,
+            key_results_cbg_update,
+            okr_detail_display_md_update,
+            orchestration_results_update, # state
+            selected_krs_update,          # state
+            krs_for_selection_update,     # state
+            agentic_status_text
+        )
+    except Exception as e:
+        logging.error(f"Error during autonomous agentic pipeline execution: {e}", exc_info=True)
+        agentic_status_text = f"Errore pipeline AI (Sempre): {str(e)}"
+        yield (
+            gr.update(value=f"Errore generazione report AI (Sempre): {str(e)}"),
+            gr.update(choices=[], value=[], interactive=False),
+            gr.update(value=f"Errore generazione OKR AI (Sempre): {str(e)}"),
+            None, [], [], agentic_status_text # Reset states on error
+        )