services/agentic_handlers.py

# handlers/agentic_handlers.py
import gradio as gr
import logging
from collections import defaultdict

# Attempt to import agentic pipeline functions and UI formatters
try:
    from run_agentic_pipeline import run_full_analytics_orchestration
    from ui.insights_ui_generator import (
        format_report_to_markdown,
        extract_key_results_for_selection,
        format_single_okr_for_display
    )
    AGENTIC_MODULES_LOADED = True
except ImportError as e:
    logging.error(f"Could not import agentic pipeline modules for AgenticHandlers: {e}.")
    AGENTIC_MODULES_LOADED = False
    # Define placeholder functions if modules are not loaded to avoid NameErrors during class definition
    async def run_full_analytics_orchestration(*args, **kwargs): return None
    def format_report_to_markdown(report_string): return "Agentic modules not loaded. Report unavailable."
    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."


class AgenticHandlers:
    def __init__(self, agentic_report_components, agentic_okrs_components,
                 token_state_ref, orchestration_raw_results_st_ref, 
                 key_results_for_selection_st_ref, selected_key_result_ids_st_ref):
        
        self.report_components = agentic_report_components
        self.okrs_components = agentic_okrs_components
        
        # References to global states
        self.token_state = token_state_ref
        self.orchestration_raw_results_st = orchestration_raw_results_st_ref
        self.key_results_for_selection_st = key_results_for_selection_st_ref
        self.selected_key_result_ids_st = selected_key_result_ids_st_ref # Though this is updated by CBG, might be read
        
        self.agentic_modules_really_loaded = AGENTIC_MODULES_LOADED # Store the flag
        logging.info(f"AgenticHandlers initialized. Modules loaded: {self.agentic_modules_really_loaded}")

    async def run_agentic_pipeline_autonomously_on_update(self, current_token_state_val):
        """
        This function is intended to be triggered by changes in token_state
        (e.g., after initial load or after sync).
        It yields updates for the agentic report and OKR tabs.
        """
        logging.info(f"Agentic pipeline auto-trigger. Token: {'Set' if current_token_state_val.get('token') else 'Not Set'}")

        # Initial "waiting" status updates
        initial_report_status = "Pipeline AI: In attesa dei dati necessari..."
        initial_okr_choices = []
        initial_okr_value = []
        initial_okr_interactive = False
        initial_okr_details = "Pipeline AI: In attesa dei dati necessari..."
        initial_orchestration_results = self.orchestration_raw_results_st.value # Preserve if re-running
        initial_selected_krs = self.selected_key_result_ids_st.value
        initial_krs_for_selection = self.key_results_for_selection_st.value
        
        # Check if components exist (in case tabs were conditionally not fully rendered)
        report_status_md_update = gr.update(value=initial_report_status) if self.report_components.get("agentic_pipeline_status_md") else gr.update()
        report_display_md_update = gr.update() # No change to report display yet
        
        okrs_cbg_update = gr.update(choices=initial_okr_choices, value=initial_okr_value, interactive=initial_okr_interactive) if self.okrs_components.get("key_results_cbg") else gr.update()
        okrs_detail_md_update = gr.update(value=initial_okr_details) if self.okrs_components.get("okr_detail_display_md") else gr.update()

        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 actual run.")
            yield (
                report_status_md_update, # For agentic_pipeline_status_md
                report_display_md_update, # For agentic_report_display_md (no change yet)
                okrs_cbg_update,         # For key_results_cbg
                okrs_detail_md_update,   # For okr_detail_display_md
                initial_orchestration_results, # For orchestration_raw_results_st
                initial_selected_krs,          # For selected_key_result_ids_st
                initial_krs_for_selection      # For key_results_for_selection_st
            )
            return

        # Update status to "in progress"
        in_progress_status = "Analisi AI (Sempre) in corso..."
        if self.report_components.get("agentic_pipeline_status_md"):
            report_status_md_update = gr.update(value=in_progress_status)
        if self.okrs_components.get("okr_detail_display_md"): # Also update OKR detail placeholder
             okrs_detail_md_update = gr.update(value="Dettagli OKR (Sempre) in corso di generazione...")
        
        yield (
            report_status_md_update, report_display_md_update, okrs_cbg_update, okrs_detail_md_update,
            initial_orchestration_results, initial_selected_krs, initial_krs_for_selection
        )

        if not self.agentic_modules_really_loaded:
            logging.warning("Agentic modules not loaded. Skipping autonomous pipeline actual run.")
            error_status = "Moduli AI non caricati. Operazione non disponibile."
            if self.report_components.get("agentic_pipeline_status_md"):
                report_status_md_update = gr.update(value=error_status)
            if self.report_components.get("agentic_report_display_md"):
                report_display_md_update = gr.update(value=error_status) # Update report display too
            if self.okrs_components.get("okr_detail_display_md"):
                 okrs_detail_md_update = gr.update(value=error_status) # Update OKR detail too

            yield (
                report_status_md_update, report_display_md_update, okrs_cbg_update, okrs_detail_md_update,
                None, [], [] # Reset states
            )
            return

        try:
            # Always use "Sempre" filter for the autonomous agentic pipeline
            date_filter_val_agentic = "Sempre"
            custom_start_val_agentic = None
            custom_end_val_agentic = None
            
            logging.info("Agentic pipeline: Calling run_full_analytics_orchestration...")
            orchestration_output = await run_full_analytics_orchestration(
                current_token_state_val, 
                date_filter_val_agentic, 
                custom_start_val_agentic, 
                custom_end_val_agentic
            )
            
            final_status_text = "Pipeline AI (Sempre) completata."
            logging.info(f"Autonomous agentic pipeline finished. Output keys: {orchestration_output.keys() if orchestration_output else 'None'}")

            orchestration_results_update_val = None
            selected_krs_update_val = []
            krs_for_selection_update_val = []

            if orchestration_output:
                orchestration_results_update_val = orchestration_output # Store the raw output
                
                report_str = orchestration_output.get('comprehensive_analysis_report', "Nessun report testuale fornito.")
                if self.report_components.get("agentic_report_display_md"):
                    report_display_md_update = gr.update(value=format_report_to_markdown(report_str))
                
                actionable_okrs = orchestration_output.get('actionable_okrs_and_tasks')
                krs_for_ui_selection_list = extract_key_results_for_selection(actionable_okrs)
                krs_for_selection_update_val = krs_for_ui_selection_list # Store for CBG change handler
                
                kr_choices_for_cbg = [(kr['kr_description'], kr['unique_kr_id']) for kr in krs_for_ui_selection_list]
                if self.okrs_components.get("key_results_cbg"):
                    okrs_cbg_update = gr.update(choices=kr_choices_for_cbg, value=[], interactive=True)
                
                # Display all OKRs initially (before any KR selection)
                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:
                    if self.okrs_components.get("okr_detail_display_md"):
                        okrs_detail_md_update = gr.update(value="Nessun OKR generato o trovato (Sempre).")
                else:
                    if self.okrs_components.get("okr_detail_display_md"):
                        okrs_detail_md_update = gr.update(value="\n\n---\n\n".join(all_okrs_md_parts))
                
                selected_krs_update_val = [] # Reset selection
            else: # No output from pipeline
                final_status_text = "Pipeline AI (Sempre): Nessun risultato prodotto."
                if self.report_components.get("agentic_report_display_md"):
                    report_display_md_update = gr.update(value="Nessun report generato dalla pipeline AI (Sempre).")
                if self.okrs_components.get("key_results_cbg"):
                    okrs_cbg_update = gr.update(choices=[], value=[], interactive=False)
                if self.okrs_components.get("okr_detail_display_md"):
                    okrs_detail_md_update = gr.update(value="Nessun OKR generato o errore nella pipeline AI (Sempre).")
            
            if self.report_components.get("agentic_pipeline_status_md"):
                 report_status_md_update = gr.update(value=final_status_text)

            yield (
                report_status_md_update, report_display_md_update, okrs_cbg_update, okrs_detail_md_update,
                orchestration_results_update_val, selected_krs_update_val, krs_for_selection_update_val
            )

        except Exception as e:
            logging.error(f"Error during autonomous agentic pipeline execution: {e}", exc_info=True)
            error_status_text = f"Errore pipeline AI (Sempre): {str(e)}"
            if self.report_components.get("agentic_pipeline_status_md"):
                report_status_md_update = gr.update(value=error_status_text)
            if self.report_components.get("agentic_report_display_md"):
                 report_display_md_update = gr.update(value=f"Errore generazione report AI (Sempre): {str(e)}")
            if self.okrs_components.get("key_results_cbg"):
                okrs_cbg_update = gr.update(choices=[], value=[], interactive=False)
            if self.okrs_components.get("okr_detail_display_md"):
                okrs_detail_md_update = gr.update(value=f"Errore generazione OKR AI (Sempre): {str(e)}")

            yield (
                report_status_md_update, report_display_md_update, okrs_cbg_update, okrs_detail_md_update,
                None, [], [] # Reset states on error
            )

    def update_okr_display_on_kr_selection(self, selected_kr_unique_ids: list, 
                                           raw_orchestration_results: dict, 
                                           all_krs_for_selection_list: list):
        """
        Updates the OKR detail display when Key Results are selected in the CheckboxGroup.
        """
        if not self.agentic_modules_really_loaded:
            return gr.update(value="Moduli AI non caricati. Impossibile visualizzare i dettagli OKR.")
        if not raw_orchestration_results:
            return gr.update(value="Nessun dato dalla pipeline AI o moduli non caricati.")

        actionable_okrs_dict = raw_orchestration_results.get("actionable_okrs_and_tasks")
        if not actionable_okrs_dict or not isinstance(actionable_okrs_dict.get("okrs"), list):
            return gr.update(value="Nessun OKR trovato nei risultati della pipeline.")

        okrs_list = actionable_okrs_dict["okrs"]
        if not okrs_list: # Should be caught by above, but defensive
            return gr.update(value="Nessun OKR generato.")

        # Create a mapping from unique_kr_id to its (okr_index, kr_index_within_okr)
        kr_id_to_indices = {}
        if all_krs_for_selection_list: # This list comes from extract_key_results_for_selection
            for kr_info in all_krs_for_selection_list:
                kr_id_to_indices[kr_info['unique_kr_id']] = (kr_info['okr_index'], kr_info['kr_index'])
        
        # Group selected KR indices by their parent OKR index
        selected_krs_by_okr_idx = defaultdict(list)
        if selected_kr_unique_ids: # This is the list of unique_kr_ids from the checkboxgroup
            for kr_unique_id in selected_kr_unique_ids:
                if kr_unique_id in kr_id_to_indices:
                    okr_idx, kr_idx_in_okr = kr_id_to_indices[kr_unique_id]
                    selected_krs_by_okr_idx[okr_idx].append(kr_idx_in_okr)
        
        output_md_parts = []
        for okr_idx, okr_data in enumerate(okrs_list):
            # If specific KRs are selected, only show OKRs that have at least one selected KR,
            # and then format that OKR to only show its selected KRs.
            # If no KRs are selected, show all OKRs with all their KRs.
            
            accepted_indices_for_this_okr = selected_krs_by_okr_idx.get(okr_idx) # This will be a list of KR indices or None

            if selected_kr_unique_ids: # If there's any selection active
                if accepted_indices_for_this_okr is not None: # Only format/display if this OKR has selected KRs
                    formatted_okr_md = format_single_okr_for_display(
                        okr_data, 
                        accepted_kr_indices=accepted_indices_for_this_okr, 
                        okr_main_index=okr_idx
                    )
                    output_md_parts.append(formatted_okr_md)
            else: # No KRs selected, display all OKRs fully
                formatted_okr_md = format_single_okr_for_display(
                    okr_data, 
                    accepted_kr_indices=None, # None means show all KRs for this OKR
                    okr_main_index=okr_idx
                )
                output_md_parts.append(formatted_okr_md)

        if not output_md_parts and selected_kr_unique_ids:
            final_md = "Nessun OKR corrisponde alla selezione corrente o i KR selezionati non hanno task dettagliati."
        elif not output_md_parts and not selected_kr_unique_ids: # Should mean okrs_list was empty
            final_md = "Nessun OKR generato."
        else:
            final_md = "\n\n---\n\n".join(output_md_parts)
            
        return gr.update(value=final_md)

    def setup_event_handlers(self):
        """Sets up event handlers for the agentic OKRs tab."""
        if not self.agentic_modules_really_loaded:
            logging.warning("Agentic modules not loaded. Skipping agentic event handler setup.")
            return

        if self.okrs_components.get("key_results_cbg"):
            self.okrs_components['key_results_cbg'].change(
                fn=self.update_okr_display_on_kr_selection,
                inputs=[
                    self.okrs_components['key_results_cbg'], # Current value of checkbox group
                    self.orchestration_raw_results_st,      # State
                    self.key_results_for_selection_st       # State
                ],
                outputs=[self.okrs_components['okr_detail_display_md']],
                api_name="update_okr_display_on_kr_selection"
            )
            logging.info("Agentic OKR selection handler setup complete.")
        else:
            logging.warning("key_results_cbg component not found for agentic OKR handler setup.")