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import gradio as gr
import pandas as pd
import os
import logging
from collections import defaultdict
import matplotlib
matplotlib.use('Agg') # Set backend for Matplotlib
# --- Module Imports ---
from utils.gradio_utils import get_url_user_token
# Functions from newly created/refactored modules
from config import (
PLOT_ID_TO_FORMULA_KEY_MAP,
LINKEDIN_CLIENT_ID_ENV_VAR,
BUBBLE_APP_NAME_ENV_VAR,
BUBBLE_API_KEY_PRIVATE_ENV_VAR,
BUBBLE_API_ENDPOINT_ENV_VAR
)
# UPDATED: Using the new data loading function from the refactored state manager
from services.state_manager import load_data_from_bubble
from ui.ui_generators import (
build_analytics_tab_plot_area,
build_home_tab_ui, # NEW: Import the function to build the Home tab UI
create_enhanced_report_tab, # NEW: Import the function to build the enhanced Report tab UI
BOMB_ICON, EXPLORE_ICON, FORMULA_ICON, ACTIVE_ICON
)
from ui.analytics_plot_generator import update_analytics_plots_figures, create_placeholder_plot
from formulas import PLOT_FORMULAS
# --- CHATBOT MODULE IMPORTS ---
from features.chatbot.chatbot_prompts import get_initial_insight_prompt_and_suggestions
from features.chatbot.chatbot_handler import generate_llm_response
# --- AGENTIC PIPELINE (DISPLAY ONLY) IMPORTS ---
try:
# This is the main function called on initial load to populate the agentic tabs
from run_agentic_pipeline import load_and_display_agentic_results
# This function is now called when a new report is selected from the dropdown
from services.report_data_handler import fetch_and_reconstruct_data_from_bubble
# UI formatting functions
from ui.insights_ui_generator import (
format_report_for_display, # This will now be the enhanced version
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 display modules: {e}. Tabs 3 and 4 will be disabled.")
AGENTIC_MODULES_LOADED = False
# Placeholder functions to prevent app from crashing if imports fail
def load_and_display_agentic_results(*args, **kwargs):
# NOTE: This return signature MUST match agentic_display_outputs
return gr.update(value="Modules not loaded."), gr.update(choices=[], value=None), gr.update(choices=[], value=[]), gr.update(value="Modules not loaded."), None, [], [], "Error", {}
def fetch_and_reconstruct_data_from_bubble(*args, **kwargs):
return None, {}
def format_report_for_display(report_data):
return "Agentic modules not loaded. Report display unavailable."
def extract_key_results_for_selection(okr_data):
return []
def format_single_okr_for_display(okr_data, **kwargs):
return "Agentic modules not loaded. OKR display unavailable."
# --- ANALYTICS TAB MODULE IMPORT ---
from services.analytics_tab_module import AnalyticsTab
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(module)s - %(message)s')
# API Key Setup
user_provided_api_key = os.environ.get("GEMINI_API_KEY")
if user_provided_api_key:
os.environ["GOOGLE_API_KEY"] = user_provided_api_key
logging.info("GOOGLE_API_KEY environment variable has been set from GEMINI_API_KEY.")
else:
logging.error("CRITICAL ERROR: The API key environment variable 'GEMINI_API_KEY' was not found.")
with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
title="LinkedIn Organization Dashboard") as app:
# --- STATE MANAGEMENT ---
token_state = gr.State(value={
"token": None, "client_id": None, "org_urn": None,
"bubble_posts_df": pd.DataFrame(), "bubble_post_stats_df": pd.DataFrame(),
"bubble_mentions_df": pd.DataFrame(), "bubble_follower_stats_df": pd.DataFrame(),
"bubble_agentic_analysis_data": pd.DataFrame(), # To store agentic results from Bubble
"url_user_token_temp_storage": None,
"config_date_col_posts": "published_at", "config_date_col_mentions": "date",
"config_date_col_followers": "date", "config_media_type_col": "media_type",
"config_eb_labels_col": "li_eb_label"
})
# States for analytics tab chatbot
chat_histories_st = gr.State({})
current_chat_plot_id_st = gr.State(None)
plot_data_for_chatbot_st = gr.State({})
# States for agentic results display
orchestration_raw_results_st = gr.State(None)
key_results_for_selection_st = gr.State([])
selected_key_result_ids_st = gr.State([])
# --- NEW: Session-specific cache for reconstructed OKR data ---
reconstruction_cache_st = gr.State({})
# --- UI LAYOUT ---
gr.Markdown("# 🚀 LinkedIn Organization Dashboard")
url_user_token_display = gr.Textbox(label="User Token (Hidden)", interactive=False, visible=False)
org_urn_display = gr.Textbox(label="Org URN (Hidden)", interactive=False, visible=False)
status_box = gr.Textbox(label="Status", interactive=False, value="Initializing...")
app.load(fn=get_url_user_token, inputs=None, outputs=[url_user_token_display, org_urn_display], api_name="get_url_params", show_progress=False)
def initial_data_load_sequence(url_token, org_urn_val, current_state):
"""
Handles the initial data loading from Bubble.
No longer generates dashboard HTML as the Home tab is now static.
"""
status_msg, new_state = load_data_from_bubble(url_token, org_urn_val, current_state)
return status_msg, new_state
analytics_icons = {'bomb': BOMB_ICON, 'explore': EXPLORE_ICON, 'formula': FORMULA_ICON, 'active': ACTIVE_ICON}
analytics_tab_instance = AnalyticsTab(
token_state=token_state,
chat_histories_st=chat_histories_st,
current_chat_plot_id_st=current_chat_plot_id_st,
plot_data_for_chatbot_st=plot_data_for_chatbot_st,
plot_id_to_formula_map=PLOT_ID_TO_FORMULA_KEY_MAP,
plot_formulas_data=PLOT_FORMULAS,
icons=analytics_icons,
fn_build_plot_area=build_analytics_tab_plot_area,
fn_update_plot_figures=update_analytics_plots_figures,
fn_create_placeholder_plot=create_placeholder_plot,
fn_get_initial_insight=get_initial_insight_prompt_and_suggestions,
fn_generate_llm_response=generate_llm_response
)
def update_report_display(selected_report_id: str, current_token_state: dict):
"""
Updates only the report display markdown when a new report is selected.
This function now uses the enhanced formatting from ui/insights_ui_generator.py.
"""
if not selected_report_id:
# Return an empty state HTML for no selection
return gr.update(value="""
<div class="empty-state">
<div class="empty-state-icon">📋</div>
<div class="empty-state-title">Select a Report</div>
<div class="empty-state-description">
Choose a report from the dropdown above to view its detailed analysis and insights.
</div>
</div>
""")
agentic_df = current_token_state.get("bubble_agentic_analysis_data")
if agentic_df is None or agentic_df.empty:
# Return an empty state HTML for no data
return gr.update(value="""
<div class="empty-state">
<div class="empty-state-icon">⚠️</div>
<div class="empty-state-title">Data Not Available</div>
<div class="empty-state-description">
Analysis data is not loaded or is empty. Please try refreshing the page.
</div>
</div>
""")
selected_report_series_df = agentic_df[agentic_df['_id'] == selected_report_id]
if selected_report_series_df.empty:
# Return an empty state HTML for report not found
return gr.update(value=f"""
<div class="empty-state">
<div class="empty-state-icon">❌</div>
<div class="empty-state-title">Report Not Found</div>
<div class="empty-state-description">
Report with ID '{selected_report_id}' was not found in the database.
</div>
</div>
""")
selected_report_series = selected_report_series_df.iloc[0]
# Call the now-enhanced format_report_for_display from ui/insights_ui_generator.py
report_markdown = format_report_for_display(selected_report_series)
return report_markdown
with gr.Tabs() as tabs:
# --- NEW HOME TAB ---
with gr.TabItem("1️⃣ Home", id="tab_home"):
# Call the new function from ui_generators to build the Home tab content
btn_graphs, btn_reports, btn_okr, btn_help = build_home_tab_ui()
# Link buttons to tab selection
btn_graphs.click(fn=lambda: gr.update(selected="tab_analytics_module"), outputs=tabs)
btn_reports.click(fn=lambda: gr.update(selected="tab_agentic_report"), outputs=tabs)
btn_okr.click(fn=lambda: gr.update(selected="tab_agentic_okrs"), outputs=tabs)
# btn_help.click(fn=lambda: gr.update(selected="tab_help"), outputs=tabs) # Uncomment if you add a help tab
analytics_tab_instance.create_tab_ui() # This is the "Graphs" tab, assuming its ID is "tab_analytics"
# --- REPLACED: Agentic Analysis Report Tab with enhanced UI ---
# The create_enhanced_report_tab function now builds this entire tab's UI.
# It also returns the relevant Gradio components needed for callbacks.
with gr.TabItem("3️⃣ Agentic Analysis Report", id="tab_agentic_report", visible=AGENTIC_MODULES_LOADED):
# The create_enhanced_report_tab function handles the CSS and HTML structure
agentic_pipeline_status_md, report_selector_dd, agentic_report_display_md = \
create_enhanced_report_tab(AGENTIC_MODULES_LOADED)
with gr.TabItem("4️⃣ Agentic OKRs & Tasks", id="tab_agentic_okrs", visible=AGENTIC_MODULES_LOADED):
gr.Markdown("## 🎯 AI Generated OKRs and Actionable Tasks (from Bubble.io)")
gr.Markdown("Basato sull'analisi AI, l'agente ha proposto i seguenti OKR. Seleziona i Key Results per dettagli.")
if not AGENTIC_MODULES_LOADED:
gr.Markdown("🔴 **Error:** Agentic modules could not be loaded.")
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### Suggested Key Results")
key_results_cbg = gr.CheckboxGroup(label="Select Key Results", choices=[], value=[], interactive=True)
with gr.Column(scale=3):
gr.Markdown("### Detailed OKRs and Tasks")
okr_detail_display_md = gr.Markdown("I dettagli OKR appariranno qui.")
def update_okr_display_on_selection(selected_kr_ids: list, raw_results: dict, all_krs: list):
if not raw_results or not AGENTIC_MODULES_LOADED:
return gr.update(value="Nessun dato di analisi caricato.")
actionable_okrs = raw_results.get("actionable_okrs")
if not actionable_okrs or not isinstance(actionable_okrs.get("okrs"), list):
return gr.update(value="Nessun OKR trovato.")
okrs_list, kr_id_map = actionable_okrs["okrs"], {kr['unique_kr_id']: (kr['okr_index'], kr['kr_index']) for kr in all_krs}
selected_krs_by_okr_idx = defaultdict(list)
if selected_kr_ids:
for kr_id in selected_kr_ids:
if kr_id in kr_id_map:
okr_idx, kr_idx = kr_id_map[kr_id]
selected_krs_by_okr_idx[okr_idx].append(kr_idx)
output_parts = []
for okr_idx, okr in enumerate(okrs_list):
if not selected_kr_ids:
output_parts.append(format_single_okr_for_display(okr, okr_main_index=okr_idx))
elif okr_idx in selected_krs_by_okr_idx:
accepted_indices = selected_krs_by_okr_idx.get(okr_idx)
output_parts.append(format_single_okr_for_display(okr, accepted_kr_indices=accepted_indices, okr_main_index=okr_idx))
final_md = "\n\n---\n\n".join(output_parts) if output_parts else "Nessun OKR corrisponde alla selezione."
return gr.update(value=final_md)
if AGENTIC_MODULES_LOADED:
key_results_cbg.change(
fn=update_okr_display_on_selection,
inputs=[key_results_cbg, orchestration_raw_results_st, key_results_for_selection_st],
outputs=[okr_detail_display_md]
)
if AGENTIC_MODULES_LOADED:
report_selector_dd.change(
fn=update_report_display, # This now calls the enhanced function
inputs=[report_selector_dd, token_state],
outputs=[agentic_report_display_md],
show_progress="minimal"
)
# Ensure agentic_display_outputs correctly maps to the newly created components
agentic_display_outputs = [
agentic_report_display_md, # Updated by create_enhanced_report_tab
report_selector_dd, # Updated by create_enhanced_report_tab
key_results_cbg,
okr_detail_display_md,
orchestration_raw_results_st,
selected_key_result_ids_st,
key_results_for_selection_st,
agentic_pipeline_status_md, # Updated by create_enhanced_report_tab
reconstruction_cache_st
]
initial_load_event = org_urn_display.change(
fn=initial_data_load_sequence,
inputs=[url_user_token_display, org_urn_display, token_state],
outputs=[status_box, token_state],
show_progress="full"
)
initial_load_event.then(
fn=analytics_tab_instance._refresh_analytics_graphs_ui,
inputs=[token_state, analytics_tab_instance.date_filter_selector, analytics_tab_instance.custom_start_date_picker,
analytics_tab_instance.custom_end_date_picker, chat_histories_st],
outputs=analytics_tab_instance.graph_refresh_outputs_list,
show_progress="full"
).then(
fn=load_and_display_agentic_results,
inputs=[token_state, reconstruction_cache_st],
outputs=agentic_display_outputs,
show_progress="minimal"
)
if __name__ == "__main__":
if not os.environ.get(LINKEDIN_CLIENT_ID_ENV_VAR):
logging.warning(f"WARNING: '{LINKEDIN_CLIENT_ID_ENV_VAR}' is not set.")
if not all(os.environ.get(var) for var in [BUBBLE_APP_NAME_ENV_VAR, BUBBLE_API_KEY_PRIVATE_ENV_VAR, BUBBLE_API_ENDPOINT_ENV_VAR]):
logging.warning("WARNING: One or more Bubble environment variables are not set.")
if not AGENTIC_MODULES_LOADED:
logging.warning("CRITICAL: Agentic modules failed to load.")
if not os.environ.get("GEMINI_API_KEY"):
logging.warning("WARNING: 'GEMINI_API_KEY' is not set.")
app.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)), debug=True)
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