Update app.py

app.py

@@ -1,3 +1,5 @@
+# app.py 
+# (Showing relevant parts that need modification)
 import gradio as gr
 import pandas as pd
 import os
@@ -46,7 +48,7 @@ from analytics_plot_generator import (
 from formulas import PLOT_FORMULAS 
 
 # --- NEW CHATBOT MODULE IMPORTS ---
-from chatbot_prompts import get_initial_insight_and_suggestions
+from chatbot_prompts import get_initial_insight_prompt_and_suggestions # MODIFIED IMPORT
 from chatbot_handler import generate_llm_response
 # --- END NEW CHATBOT MODULE IMPORTS ---
 
@@ -93,60 +95,65 @@ def generate_chatbot_data_summaries(
     """
     data_summaries = {}
     date_col_posts = token_state_value.get("config_date_col_posts", "published_at")
+    
     # Ensure date columns are datetime objects for proper formatting and comparison
-    if date_col_posts in filtered_merged_posts_df.columns:
+    # Make copies to avoid SettingWithCopyWarning if dataframes are slices
+    if not filtered_merged_posts_df.empty and date_col_posts in filtered_merged_posts_df.columns:
+        # Use .loc to ensure modification happens on the correct DataFrame
+        filtered_merged_posts_df = filtered_merged_posts_df.copy()
         filtered_merged_posts_df[date_col_posts] = pd.to_datetime(filtered_merged_posts_df[date_col_posts], errors='coerce')
-    if 'date' in date_filtered_follower_stats_df.columns:
-         date_filtered_follower_stats_df['date'] = pd.to_datetime(date_filtered_follower_stats_df['date'], errors='coerce')
+    
+    if not date_filtered_follower_stats_df.empty and 'date' in date_filtered_follower_stats_df.columns:
+        date_filtered_follower_stats_df = date_filtered_follower_stats_df.copy()
+        date_filtered_follower_stats_df['date'] = pd.to_datetime(date_filtered_follower_stats_df['date'], errors='coerce')
     # Add more date conversions as needed for other dataframes
 
     for plot_cfg in plot_configs_list:
         plot_id = plot_cfg["id"]
-        summary_text = f"No data summary available for {plot_cfg['label']} for the selected period."
+        summary_text = f"Nessun sommario dati specifico disponibile per '{plot_cfg['label']}' per il periodo selezionato." # Ensure this matches prompt logic
 
         try:
-            if plot_id == "followers_count" and not date_filtered_follower_stats_df.empty:
+            if plot_id == "followers_count" and not date_filtered_follower_stats_df.empty and 'follower_gains_monthly' in date_filtered_follower_stats_df.columns and 'date' in date_filtered_follower_stats_df.columns:
                 df_summary = date_filtered_follower_stats_df[['date', 'follower_gains_monthly']].copy()
                 df_summary['date'] = df_summary['date'].dt.strftime('%Y-%m-%d')
-                summary_text = f"Follower Count (Monthly Gains):\n{df_summary.tail(5).to_string(index=False)}"
+                summary_text = f"Follower Count (Monthly Gains):\n{df_summary.sort_values(by='date').tail(5).to_string(index=False)}"
             
-            elif plot_id == "followers_growth_rate" and not date_filtered_follower_stats_df.empty:
-                df_summary = date_filtered_follower_stats_df[['date', 'growth_rate_monthly']].copy() # Assuming 'growth_rate_monthly' column
+            elif plot_id == "followers_growth_rate" and not date_filtered_follower_stats_df.empty and 'growth_rate_monthly' in date_filtered_follower_stats_df.columns and 'date' in date_filtered_follower_stats_df.columns:
+                df_summary = date_filtered_follower_stats_df[['date', 'growth_rate_monthly']].copy() 
                 df_summary['date'] = df_summary['date'].dt.strftime('%Y-%m-%d')
-                summary_text = f"Follower Growth Rate (Monthly):\n{df_summary.tail(5).to_string(index=False)}"
-
-            elif plot_id == "followers_by_location" and not raw_follower_stats_df.empty and 'follower_geo' in raw_follower_stats_df.columns:
-                # Assuming 'follower_geo' contains location names and another column like 'count' exists
-                # This part needs to align with how generate_followers_by_demographics_plot processes 'follower_geo' data
-                # For simplicity, let's assume raw_follower_stats_df has pre-aggregated data for geo
-                # This is a placeholder, actual column names for count and name are needed from your data prep
-                if 'geo_name' in raw_follower_stats_df.columns and 'geo_count' in raw_follower_stats_df.columns:
-                    df_summary = raw_follower_stats_df[['geo_name', 'geo_count']].nlargest(5, 'geo_count')
-                    summary_text = f"Followers by Location (Top 5):\n{df_summary.to_string(index=False)}"
-                else:
-                    summary_text = "Follower location data structure not as expected for summary."
+                summary_text = f"Follower Growth Rate (Monthly %):\n{df_summary.sort_values(by='date').tail(5).to_string(index=False)}"
 
+            elif plot_id == "followers_by_location" and not raw_follower_stats_df.empty:
+                # This assumes 'follower_geo' is a column that needs processing similar to the plot generator
+                # For simplicity, if your raw_follower_stats_df might have pre-aggregated 'geo_name' and 'geo_count'
+                if 'follower_geo_processed_for_summary' in raw_follower_stats_df.columns: # Placeholder for actual processed data
+                    # Example: df_summary = raw_follower_stats_df[['geo_name', 'geo_count']].nlargest(5, 'geo_count')
+                    # summary_text = f"Followers by Location (Top 5):\n{df_summary.to_string(index=False)}"
+                    pass # Implement actual summary logic based on your data structure
+                else: # Fallback if specific processed columns aren't ready for summary
+                    summary_text = f"Follower location demographic data for '{plot_cfg['label']}' is complex; specific summary requires pre-processing aligned with the chart."
 
-            elif plot_id == "engagement_rate" and not filtered_merged_posts_df.empty:
+
+            elif plot_id == "engagement_rate" and not filtered_merged_posts_df.empty and 'engagement_rate' in filtered_merged_posts_df.columns and date_col_posts in filtered_merged_posts_df.columns:
                 df_summary = filtered_merged_posts_df[[date_col_posts, 'engagement_rate']].copy()
                 df_summary[date_col_posts] = df_summary[date_col_posts].dt.strftime('%Y-%m-%d')
-                summary_text = f"Engagement Rate Over Time:\n{df_summary.tail(5).to_string(index=False)}"
+                summary_text = f"Engagement Rate Over Time (%):\n{df_summary.sort_values(by=date_col_posts).tail(5).to_string(index=False)}"
             
-            elif plot_id == "reach_over_time" and not filtered_merged_posts_df.empty:
+            elif plot_id == "reach_over_time" and not filtered_merged_posts_df.empty and 'reach' in filtered_merged_posts_df.columns and date_col_posts in filtered_merged_posts_df.columns:
                 df_summary = filtered_merged_posts_df[[date_col_posts, 'reach']].copy()
                 df_summary[date_col_posts] = df_summary[date_col_posts].dt.strftime('%Y-%m-%d')
-                summary_text = f"Reach Over Time:\n{df_summary.tail(5).to_string(index=False)}"
+                summary_text = f"Reach Over Time:\n{df_summary.sort_values(by=date_col_posts).tail(5).to_string(index=False)}"
 
-            elif plot_id == "impressions_over_time" and not filtered_merged_posts_df.empty:
-                df_summary = filtered_merged_posts_df[[date_col_posts, 'impressions_sum']].copy() # Assuming 'impressions_sum' or similar
+            elif plot_id == "impressions_over_time" and not filtered_merged_posts_df.empty and 'impressions_sum' in filtered_merged_posts_df.columns and date_col_posts in filtered_merged_posts_df.columns:
+                df_summary = filtered_merged_posts_df[[date_col_posts, 'impressions_sum']].copy() 
                 df_summary[date_col_posts] = df_summary[date_col_posts].dt.strftime('%Y-%m-%d')
-                summary_text = f"Impressions Over Time:\n{df_summary.tail(5).to_string(index=False)}"
+                summary_text = f"Impressions Over Time:\n{df_summary.sort_values(by=date_col_posts).tail(5).to_string(index=False)}"
 
             elif plot_id == "comments_sentiment" and not filtered_merged_posts_df.empty and 'comment_sentiment' in filtered_merged_posts_df.columns:
                 sentiment_counts = filtered_merged_posts_df['comment_sentiment'].value_counts().reset_index()
                 sentiment_counts.columns = ['Sentiment', 'Count']
                 summary_text = f"Comments Sentiment Breakdown:\n{sentiment_counts.to_string(index=False)}"
-
+            
             # Add more elif blocks for other plot_ids, extracting relevant data:
             # e.g., likes_over_time, clicks_over_time, shares_over_time, comments_over_time
             # post_frequency_cs, content_format_breakdown_cs, content_topic_breakdown_cs
@@ -217,7 +224,7 @@ def update_analytics_plots_figures(token_state_value, date_filter_option, custom
     try:
         # Dinamiche dei Follower (2 plots)
         plot_figs.append(generate_followers_count_over_time_plot(date_filtered_follower_stats_df, type_value='follower_gains_monthly'))
-        plot_figs.append(generate_followers_growth_rate_plot(date_filtered_follower_stats_df, type_value='follower_gains_monthly'))
+        plot_figs.append(generate_followers_growth_rate_plot(date_filtered_follower_stats_df, type_value='follower_gains_monthly')) # Assuming this uses 'follower_gains_monthly' to calculate rate
         
         # Demografia Follower (4 plots)
         plot_figs.append(generate_followers_by_demographics_plot(raw_follower_stats_df, type_value='follower_geo', plot_title="Follower per Località"))
@@ -228,7 +235,7 @@ def update_analytics_plots_figures(token_state_value, date_filter_option, custom
         # Approfondimenti Performance Post (4 plots)
         plot_figs.append(generate_engagement_rate_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
         plot_figs.append(generate_reach_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
-        plot_figs.append(generate_impressions_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
+        plot_figs.append(generate_impressions_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts)) # Ensure 'impressions_sum' or equivalent is used by this func
         plot_figs.append(generate_likes_over_time_plot(filtered_merged_posts_df, date_column=date_column_posts))
         
         # Engagement Dettagliato Post nel Tempo (4 plots)
@@ -288,13 +295,13 @@ def update_analytics_plots_figures(token_state_value, date_filter_option, custom
         placeholder_figs_general = [create_placeholder_plot(title=plot_titles_for_errors[i] if i < len(plot_titles_for_errors) else f"Grafico {i+1}", message=str(e_general)) for i in range(num_expected_plots)]
         for p_cfg in current_plot_configs: # Ensure summaries dict is populated on error
              if p_cfg["id"] not in plot_data_summaries_for_chatbot:
-                plot_data_summaries_for_chatbot[p_cfg["id"]] = f"Errore generale grafici: {e_general}"
+                 plot_data_summaries_for_chatbot[p_cfg["id"]] = f"Errore generale grafici: {e_general}"
         return [error_msg] + placeholder_figs_general + [plot_data_summaries_for_chatbot]
 
 
 # --- Gradio UI Blocks ---
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
-               title="LinkedIn Organization Dashboard") as app:
+                title="LinkedIn Organization Dashboard") as app:
     token_state = gr.State(value={
         "token": None, "client_id": None, "org_urn": None,
         "bubble_posts_df": pd.DataFrame(), "bubble_post_stats_df": pd.DataFrame(),
@@ -361,8 +368,6 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 outputs=[custom_start_date_picker, custom_end_date_picker]
             )
             
-            # Moved plot_configs to be globally accessible within the Blocks scope if needed by update_analytics_plots_figures
-            # or pass it explicitly. For now, it's defined here.
             plot_configs = [
                 {"label": "Numero di Follower nel Tempo", "id": "followers_count", "section": "Dinamiche dei Follower"},
                 {"label": "Tasso di Crescita Follower", "id": "followers_growth_rate", "section": "Dinamiche dei Follower"},
@@ -430,7 +435,8 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 if not clicked_plot_config:
                     logging.error(f"Configurazione non trovata per plot_id {plot_id_clicked}")
                     num_button_updates = 2 * len(plot_configs) # insights, formula buttons
-                    error_updates = [gr.update(visible=False)] * 10 # action_col, chatbot, input, suggestions_row, 3x sugg_btn, formula_md
+                    error_updates = [gr.update(visible=False)] * 7 # action_col, chatbot, input, suggestions_row, 3x sugg_btn
+                    error_updates.append(gr.update(visible=False, value="")) # formula_md (visibility and value)
                     error_updates.extend([current_active_action_from_state, current_chat_plot_id, current_chat_histories]) 
                     error_updates.extend([gr.update()] * num_button_updates) 
                     return error_updates
@@ -448,7 +454,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 insights_suggestions_row_visible_update = gr.update(visible=False)
                 formula_display_visible_update = gr.update(visible=False)
                 
-                chatbot_content_update = gr.update()
+                chatbot_content_update = gr.update() # No change by default
                 suggestion_1_update = gr.update()
                 suggestion_2_update = gr.update()
                 suggestion_3_update = gr.update()
@@ -472,27 +478,38 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                         new_current_chat_plot_id = plot_id_clicked
                         chat_history_for_this_plot = current_chat_histories.get(plot_id_clicked, [])
                         
-                        # Get data summary for this plot
                         plot_specific_data_summary = current_plot_data_for_chatbot.get(plot_id_clicked, f"Nessun sommario dati specifico disponibile per '{clicked_plot_label}'.")
 
                         if not chat_history_for_this_plot: 
-                            initial_insight_msg, suggestions = get_initial_insight_and_suggestions(
+                            initial_llm_prompt, suggestions = get_initial_insight_prompt_and_suggestions(
                                 plot_id_clicked, 
                                 clicked_plot_label,
-                                plot_specific_data_summary # Pass the summary
+                                plot_specific_data_summary 
+                            )
+                            # History for LLM's first turn: the system's prompt as a user message
+                            history_for_llm_first_turn = [{"role": "user", "content": initial_llm_prompt}]
+                            
+                            logging.info(f"Generating initial LLM insight for {plot_id_clicked}...")
+                            initial_bot_response_text = await generate_llm_response(
+                                user_message=initial_llm_prompt, # For context/logging in handler
+                                plot_id=plot_id_clicked, 
+                                plot_label=clicked_plot_label, 
+                                chat_history_for_plot=history_for_llm_first_turn, 
+                                plot_data_summary=plot_specific_data_summary 
                             )
-                            chat_history_for_this_plot = [initial_insight_msg] # Gradio expects list of dicts
+                            logging.info(f"LLM initial insight received for {plot_id_clicked}.")
+                            
+                            # History for Gradio display starts with the assistant's response
+                            chat_history_for_this_plot = [{"role": "assistant", "content": initial_bot_response_text}]
                             updated_chat_histories = current_chat_histories.copy()
                             updated_chat_histories[plot_id_clicked] = chat_history_for_this_plot
-                        else: 
-                            # If history exists, still get fresh suggestions, but don't overwrite history's first message
-                            _, suggestions = get_initial_insight_and_suggestions(
+                        else: # History exists, get fresh suggestions
+                            _, suggestions = get_initial_insight_prompt_and_suggestions(
                                 plot_id_clicked, 
                                 clicked_plot_label,
-                                plot_specific_data_summary # Pass summary for context if needed by suggestions
+                                plot_specific_data_summary
                             )
 
-
                         chatbot_content_update = gr.update(value=chat_history_for_this_plot)
                         suggestion_1_update = gr.update(value=suggestions[0])
                         suggestion_2_update = gr.update(value=suggestions[1])
@@ -537,8 +554,8 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                     insights_suggestions_row_visible_update, suggestion_1_update, suggestion_2_update, suggestion_3_update,
                     formula_display_visible_update, formula_content_update,
                     new_active_action_state_to_set, 
-                    new_current_chat_plot_id,    
-                    updated_chat_histories     
+                    new_current_chat_plot_id,  
+                    updated_chat_histories   
                 ] + all_button_icon_updates
                 
                 return final_updates
@@ -561,7 +578,6 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 # Retrieve the specific data summary for the current plot
                 plot_specific_data_summary = current_plot_data_for_chatbot.get(current_plot_id, f"Nessun sommario dati specifico disponibile per '{plot_label}'.")
 
-
                 history_for_plot = chat_histories.get(current_plot_id, []).copy()
                 history_for_plot.append({"role": "user", "content": user_message})
                 
@@ -573,7 +589,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                     user_message, 
                     current_plot_id, 
                     plot_label, 
-                    history_for_plot, # This history now includes the initial insight with summary + user message
+                    history_for_plot, # This history now includes the user message
                     plot_specific_data_summary # Explicitly pass for this turn if needed by LLM handler logic
                 )
                 
@@ -660,7 +676,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                     action_panel_outputs_list.append(plot_ui_objects[pid_action]["bomb_button"])
                     action_panel_outputs_list.append(plot_ui_objects[pid_action]["formula_button"])
                 else: 
-                    action_panel_outputs_list.extend([None, None]) 
+                    action_panel_outputs_list.extend([gr.update(), gr.update()]) # Use gr.update() as placeholder
 
             # Outputs for explore actions
             explore_buttons_outputs_list = [explored_plot_id_state]
@@ -670,7 +686,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                     explore_buttons_outputs_list.append(plot_ui_objects[pid_explore]["panel_component"])
                     explore_buttons_outputs_list.append(plot_ui_objects[pid_explore]["explore_button"])
                 else: 
-                    explore_buttons_outputs_list.extend([None, None])
+                    explore_buttons_outputs_list.extend([gr.update(), gr.update()])
 
             # Inputs for panel actions
             action_click_inputs = [
@@ -767,16 +783,16 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 
                 all_updates.extend([
                     gr.update(visible=False), # global_actions_column_ui
-                    gr.update(value=[], visible=False), # insights_chatbot_ui (value)
-                    gr.update(value="", visible=False), # insights_chat_input_ui (value)
+                    gr.update(value=[], visible=False), # insights_chatbot_ui (value & visibility)
+                    gr.update(value="", visible=False), # insights_chat_input_ui (value & visibility)
                     gr.update(visible=False), # insights_suggestions_row_ui
-                    gr.update(value="Suggerimento 1", visible=True), # insights_suggestion_1_btn
-                    gr.update(value="Suggerimento 2", visible=True), # insights_suggestion_2_btn
-                    gr.update(value="Suggerimento 3", visible=True), # insights_suggestion_3_btn
+                    gr.update(value="Suggerimento 1"), # insights_suggestion_1_btn (reset value, visibility handled by row)
+                    gr.update(value="Suggerimento 2"), # insights_suggestion_2_btn
+                    gr.update(value="Suggerimento 3"), # insights_suggestion_3_btn
                     gr.update(value="I dettagli sulla formula/metodologia appariranno qui.", visible=False), # formula_display_markdown_ui
                     None, # active_panel_action_state
                     None, # current_chat_plot_id_st
-                    current_chat_histories, # chat_histories_st (preserve or reset as needed, here preserving)
+                    {}, # chat_histories_st (reset chat histories on filter change)
                     new_plot_data_summaries # NEW: plot_data_for_chatbot_st
                 ])
                 
@@ -786,9 +802,9 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                         all_updates.append(gr.update(value=BOMB_ICON))   
                         all_updates.append(gr.update(value=FORMULA_ICON)) 
                         all_updates.append(gr.update(value=EXPLORE_ICON)) 
-                        all_updates.append(gr.update(visible=True))      # panel_component visibility
+                        all_updates.append(gr.update(visible=True))     # panel_component visibility
                     else: 
-                        all_updates.extend([None, None, None, None])
+                        all_updates.extend([gr.update(), gr.update(), gr.update(), gr.update()])
                 
                 all_updates.append(None) # explored_plot_id_state
                 
@@ -801,21 +817,21 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 if pid_filter_sync in plot_ui_objects and "plot_component" in plot_ui_objects[pid_filter_sync]:
                     apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync]["plot_component"])
                 else:
-                    apply_filter_and_sync_outputs_list.append(None) 
+                    apply_filter_and_sync_outputs_list.append(gr.update()) 
             
             apply_filter_and_sync_outputs_list.extend([
-                global_actions_column_ui,         # Reset visibility
-                insights_chatbot_ui,              # Reset content & visibility
-                insights_chat_input_ui,           # Reset content & visibility
-                insights_suggestions_row_ui,      # Reset visibility
-                insights_suggestion_1_btn,        # Reset text & visibility
+                global_actions_column_ui,       # Reset visibility
+                insights_chatbot_ui,            # Reset content & visibility
+                insights_chat_input_ui,         # Reset content & visibility
+                insights_suggestions_row_ui,    # Reset visibility
+                insights_suggestion_1_btn,      # Reset text & visibility
                 insights_suggestion_2_btn,
                 insights_suggestion_3_btn,
-                formula_display_markdown_ui,      # Reset content & visibility
-                active_panel_action_state,        # Reset state
-                current_chat_plot_id_st,          # Reset state
-                chat_histories_st,                # Preserve or reset state
-                plot_data_for_chatbot_st          # NEW: Update this state
+                formula_display_markdown_ui,    # Reset content & visibility
+                active_panel_action_state,      # Reset state
+                current_chat_plot_id_st,        # Reset state
+                chat_histories_st,              # Preserve or reset state (resetting via refresh_all_analytics_ui_elements)
+                plot_data_for_chatbot_st        # NEW: Update this state
             ])
 
             for cfg_filter_sync_btns in plot_configs:
@@ -826,7 +842,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                     apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync_btns]["explore_button"])
                     apply_filter_and_sync_outputs_list.append(plot_ui_objects[pid_filter_sync_btns]["panel_component"]) 
                 else:
-                    apply_filter_and_sync_outputs_list.extend([None, None, None, None]) 
+                    apply_filter_and_sync_outputs_list.extend([gr.update(), gr.update(), gr.update(), gr.update()]) 
             
             apply_filter_and_sync_outputs_list.append(explored_plot_id_state) # Reset state
             
@@ -897,4 +913,4 @@ if __name__ == "__main__":
     except ImportError: 
         logging.warning("Matplotlib non trovato direttamente, ma potrebbe essere usato dai generatori di grafici.")
         
-    app.launch(server_name="0.0.0.0", server_port=7860, debug=True)
+    app.launch(server_name="0.0.0.0", server_port=7860, debug=True)