Update app.py

app.py

@@ -37,7 +37,7 @@ from features.chatbot.chatbot_handler import generate_llm_response # Pass this
 
 # --- NEW AGENTIC PIPELINE IMPORTS ---
 try:
-    from run_agentic_pipeline import run_full_analytics_orchestration
+    from run_agentic_pipeline import run_agentic_pipeline_autonomously
     from ui.insights_ui_generator import (
         format_report_to_markdown,
         extract_key_results_for_selection,
@@ -212,113 +212,6 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                     api_name="update_okr_display_on_selection_module"
                 )
 
-    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
-            )
 
     # Define the output list for the agentic pipeline callbacks
     # Order: Report MD, KR CBG, OKR Detail MD, RawResults State, SelectedKRIDs State, KRList State, Status MD