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# run_agentic_pipeline.py
"""
This module is responsible for loading and displaying pre-computed AI analysis
results (reports and OKRs) that have been fetched from Bubble.io. It does not
perform any new analysis.
"""
import logging
import gradio as gr
# UI formatting and data reconstruction functions are still needed
try:
from ui.insights_ui_generator import (
format_report_to_markdown,
extract_key_results_for_selection,
format_single_okr_for_display
)
from services.report_data_handler import fetch_and_reconstruct_data_from_bubble
AGENTIC_MODULES_LOADED = True
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
# Define placeholder functions if imports fail
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."
def fetch_and_reconstruct_data_from_bubble(df): return None
def load_and_display_agentic_results(current_token_state, orchestration_raw_results_st, selected_key_result_ids_st, key_results_for_selection_st):
"""
Loads pre-computed agentic analysis and OKR data from the application state
(which was fetched from Bubble) and formats it for display in the Gradio UI.
"""
logging.info("Loading and displaying pre-computed agentic results from state.")
# A tuple of Gradio updates to return in case of errors or no data
initial_yield_updates = (
gr.update(value="Nessun dato di analisi trovato..."), # agentic_report_display_md
gr.update(choices=[], value=[], interactive=False), # key_results_cbg
gr.update(value="Nessun OKR trovato..."), # okr_detail_display_md
None, # orchestration_raw_results_st
[], # selected_key_result_ids_st
[], # key_results_for_selection_st
"Stato: In attesa di dati" # agentic_pipeline_status_md
)
if not AGENTIC_MODULES_LOADED:
logging.warning("Agentic display modules not loaded. Cannot display results.")
error_updates = list(initial_yield_updates)
error_updates[-1] = "Errore: Moduli AI non caricati."
return tuple(error_updates)
# The raw DataFrame fetched from Bubble's agentic analysis table
agentic_data_df = current_token_state.get('bubble_agentic_analysis_data')
if agentic_data_df is None or agentic_data_df.empty:
logging.warning("No agentic analysis data found in the application state.")
return initial_yield_updates
# Use the handler to reconstruct the report and OKRs from the DataFrame
reconstructed_data = fetch_and_reconstruct_data_from_bubble(agentic_data_df)
if not reconstructed_data:
logging.warning("Could not reconstruct agentic data from the fetched DataFrame.")
error_updates = list(initial_yield_updates)
error_updates[0] = gr.update(value="I dati di analisi esistenti non sono nel formato corretto.")
error_updates[2] = gr.update(value="Impossibile visualizzare gli OKR.")
error_updates[-1] = "Stato: Errore formato dati"
return tuple(error_updates)
# --- Prepare UI updates with the reconstructed data ---
report_str = reconstructed_data.get('report_str', "Nessun report di analisi trovato nei dati.")
actionable_okrs = reconstructed_data.get('actionable_okrs') # This is the dict with 'okrs' list
# 1. Update Report Tab
agentic_report_md_update = gr.update(value=format_report_to_markdown(report_str))
# 2. Update OKR Tab components
if actionable_okrs and isinstance(actionable_okrs.get("okrs"), list):
krs_for_ui_selection_list = extract_key_results_for_selection(actionable_okrs)
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)
krs_for_selection_state_update = krs_for_ui_selection_list
all_okrs_md_parts = [
format_single_okr_for_display(okr_item, accepted_kr_indices=None, okr_main_index=okr_idx)
for okr_idx, okr_item in enumerate(actionable_okrs["okrs"])
]
okr_detail_display_md_update = gr.update(value="\n\n---\n\n".join(all_okrs_md_parts))
else:
# Handle case where there are no OKRs in the data
krs_for_selection_state_update = []
key_results_cbg_update = gr.update(choices=[], value=[], interactive=False)
okr_detail_display_md_update = gr.update(value="Nessun OKR trovato nei dati di analisi caricati.")
# Return all the final updates for the Gradio interface
return (
agentic_report_md_update,
key_results_cbg_update,
okr_detail_display_md_update,
reconstructed_data, # Store the full reconstructed data dict in the state
[], # Reset the selected KR IDs state
krs_for_selection_state_update, # Update the state with all available KRs
"Stato: Dati di analisi caricati correttamente da Bubble" # Final status message
)
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