updated

app.py

@@ -657,13 +657,13 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
         
         output_path = "filtered_news_data.csv"; display_df.to_csv(output_path, index=False)
         return display_df, output_path, analyzed_df
-
+    
     start_scraper_button.click(
         fn=news_scraper_workflow,
         inputs=[search_keywords_textbox, sites_to_search_textbox, start_date_textbox, end_date_textbox, interval_days_slider, max_pages_slider, filter_keywords_textbox],
         outputs=[scraper_results_df, scraper_download_file, scraper_results_state]
     )
-
+    
     def update_news_dashboards(analyzed_df):
         if analyzed_df is None or analyzed_df.empty:
             return [gr.update(visible=False), '', '', '', None, None, None, gr.update(visible=False), None, None]
@@ -682,14 +682,14 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
             sentiment_updates.get(sentiment_pie_plot, None),
             sentiment_updates.get(sentiment_by_media_plot, None)
         ]
-
+    
     news_ui_components = [
         scraper_dashboard_group, kpi_total_articles, kpi_unique_media, kpi_date_range,
         dashboard_timeline_plot, dashboard_media_plot, dashboard_wordcloud_plot,
         sentiment_dashboard_tab, sentiment_pie_plot, sentiment_by_media_plot
     ]
     scraper_results_state.change(fn=update_news_dashboards, inputs=scraper_results_state, outputs=news_ui_components)
-
+    
     # --- YOUTUBE WORKFLOW ---
     def youtube_workflow(api_key, query, max_stats, num_comments, max_comments, published_after, progress=gr.Progress()):
         sanitized_api_key = api_key.strip()
@@ -699,30 +699,31 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
         )
         if videos_df_full.empty:
             gr.Info("No videos found for your YouTube query."); return None, None
-
+    
         if comments_df is not None and not comments_df.empty:
             progress(0.9, desc="Analyzing comment sentiment...")
             comments_df = run_sentiment_analysis(comments_df.copy(), 'comment_text', progress)
             
         top_videos_for_display = videos_df_full.head(int(num_comments))
         return top_videos_for_display, {"full_scan": videos_df_full, "comments": comments_df, "total_estimate": total_vids_est}
-
+    
     start_yt_analysis_button.click(
         fn=youtube_workflow,
         inputs=[yt_api_key, yt_search_keywords, yt_max_videos_for_stats, yt_num_videos_for_comments, yt_max_comments, yt_published_after],
         outputs=[yt_videos_df_output, youtube_results_state]
     )
-
+    
     def update_youtube_dashboards(results_data):
-        # If there are no results, return the correct number of empty items (13 in this case)
+        # This function is now corrected.
         if not results_data or results_data.get("full_scan") is None or results_data["full_scan"].empty:
+            # Return the correct number of empty items (13) to match the component list
             return [gr.update(visible=False), "0", "0", "0", "0", None, None, None, None, None, None, None, None]
-        
+            
         videos_df_full, comments_df, total_estimate = results_data.get("full_scan"), results_data.get("comments"), results_data.get("total_estimate", 0)
         deep_dive_updates = generate_youtube_dashboard(videos_df_full, comments_df)
         fig_ch_views, fig_quad, fig_age = generate_youtube_topic_dashboard(videos_df_full)
-    
-        # This return statement now provides a "picture" for every "frame" in the corrected list.
+        
+        # This return list now perfectly matches the yt_ui_components list below.
         return [
             gr.update(visible=True),
             f"{total_estimate:,}",
@@ -731,21 +732,22 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
             deep_dive_updates.get(kpi_yt_comments_scraped, "0"),
             deep_dive_updates.get('yt_channel_plot', None),
             deep_dive_updates.get('yt_wordcloud_plot', None),
-            fig_ch_views,
-            fig_quad,
-            fig_age,
             deep_dive_updates.get('yt_top_videos_plot', None),
             deep_dive_updates.get('yt_engagement_plot', None),
-            deep_dive_updates.get('yt_comment_activity_plot', None)
+            deep_dive_updates.get('yt_comment_activity_plot', None),
+            fig_ch_views,
+            fig_quad,
+            fig_age
         ]
     
+    # This is the list that was causing the error.
+    # The undefined variables `yt_sentiment_pie_plot` and `yt_sentiment_by_video_plot` have been removed.
     yt_ui_components = [
         yt_dashboard_group, kpi_yt_total_topic_videos, kpi_yt_videos_found, kpi_yt_views_scanned, kpi_yt_comments_scraped,
-        yt_channel_plot, yt_wordcloud_plot, yt_sentiment_pie_plot, yt_sentiment_by_video_plot,
-        yt_channel_views_plot, yt_performance_quadrant_plot, yt_content_age_plot
+        yt_channel_plot, yt_wordcloud_plot, yt_top_videos_plot, yt_engagement_plot,
+        yt_comment_activity_plot, yt_channel_views_plot, yt_performance_quadrant_plot, yt_content_age_plot
     ]
-    youtube_results_state.change(fn=update_youtube_dashboards, inputs=youtube_results_state, outputs=yt_ui_components)
-    
+    youtube_results_state.change(fn=update_youtube_dashboards, inputs=youtube_results_state, outputs=yt_ui_components)    
 # ==============================================================================
 # LAUNCH THE APP
 # ==============================================================================