updated for non political

app.py

@@ -34,12 +34,12 @@ logger.info("Application starting up.")
 
 # --- APPLICATION CONFIGURATION ---
 APP_TITLE = "Social Perception Analyzer"
-APP_TAGLINE = "Prepared for the Policymakers of Bangladesh Nationalist Party (BNP)"
-APP_FOOTER = "Developed by CDSR"
+APP_TAGLINE = "Analyze GoogleNews & YouTube video trends, engagement, and comment activity for your search topics."
+APP_FOOTER = "Developed by Arjon"
 
 # --- FONT CONFIGURATION ---
 FONT_PATH = 'NotoSansBengali-Regular.ttf'
-BANGLA_FONT = None
+BANGLA_FONT = FONT_PATH
 
 def setup_bangla_font():
     """Properly set up Bengali font for all visualizations"""
@@ -99,6 +99,7 @@ PHRASES_TO_JOIN = {
     "তারেক রহমান": "তারেক_রহমান",
     "খালেদা জিয়া": "খালেদা_জিয়া",
     "বিএনপি জিন্দাবাদ": "বিএনপি_জিন্দাবাদ"
+    "মুহাম্মদ ইউনূস": "মুহাম্মদ_ইউনূস"
 }
 
 def get_dynamic_time_agg(start_date, end_date):
@@ -556,17 +557,22 @@ def generate_scraper_dashboard(df: pd.DataFrame):
     if not media_counts.empty:
         fig_media, ax = plt.subplots(figsize=(8, 6))
         media_counts.plot(kind='barh', ax=ax, color='skyblue')
-        ax.set_title("Top 15 Media Sources", fontproperties=BANGLA_FONT)
-        ax.set_xlabel("Article Count", fontproperties=BANGLA_FONT)
-        ax.set_ylabel("মিডিয়া", fontproperties=BANGLA_FONT)
+        ax.set_title("Top 15 Media Sources", fontproperties=BANGLA_FONT, fontsize=18)
+        ax.set_xlabel("Article Count", fontproperties=BANGLA_FONT, fontsize=14)
+        ax.set_ylabel("মিডিয়া", fontproperties=BANGLA_FONT, fontsize=14)
         yticks = np.arange(len(media_counts.index))
         ax.set_yticks(yticks)
-        ax.set_yticklabels(media_counts.index, fontproperties=BANGLA_FONT, fontsize=12)
-        # Ensure all tick labels use Bengali font
+        ax.set_yticklabels(media_counts.index, fontproperties=BANGLA_FONT, fontsize=14)
         for label in ax.get_xticklabels():
             label.set_fontproperties(BANGLA_FONT)
+            label.set_fontsize(12)
         for label in ax.get_yticklabels():
             label.set_fontproperties(BANGLA_FONT)
+            label.set_fontsize(14)
+        legend = ax.get_legend()
+        if legend:
+            for text in legend.get_texts():
+                text.set_fontproperties(BANGLA_FONT)
         plt.tight_layout()
     
     # Word cloud generation
@@ -652,12 +658,22 @@ def generate_youtube_dashboard(videos_df, comments_df):
         if not channel_views.empty:
             fig_channel_dominance, ax = plt.subplots(figsize=(10, 6))
             channel_views.plot(kind='barh', ax=ax, color='slateblue')
-            ax.set_title("Top 10 Dominant Channels by View Count", fontproperties=BANGLA_FONT)
-            ax.set_xlabel("মোট ভিউ", fontproperties=BANGLA_FONT)
-            ax.set_ylabel("চ্যানেল", fontproperties=BANGLA_FONT)
+            ax.set_title("Top 10 Dominant Channels by View Count", fontproperties=BANGLA_FONT, fontsize=18)
+            ax.set_xlabel("মোট ভিউ", fontproperties=BANGLA_FONT, fontsize=14)
+            ax.set_ylabel("চ্যানেল", fontproperties=BANGLA_FONT, fontsize=14)
             yticks = np.arange(len(channel_views.index))
             ax.set_yticks(yticks)
-            ax.set_yticklabels(channel_views.index, fontproperties=BANGLA_FONT, fontsize=12)
+            ax.set_yticklabels(channel_views.index, fontproperties=BANGLA_FONT, fontsize=14)
+            for label in ax.get_xticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(12)
+            for label in ax.get_yticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(14)
+            legend = ax.get_legend()
+            if legend:
+                for text in legend.get_texts():
+                    text.set_fontproperties(BANGLA_FONT)
             plt.tight_layout()
     dashboard_components["yt_channel_dominance_plot"] = fig_channel_dominance
 
@@ -676,9 +692,19 @@ def generate_youtube_dashboard(videos_df, comments_df):
             )
             ax.axvline(median_views, color='blue', linestyle='--', label='Median Views')
             ax.axhline(median_engagement, color='green', linestyle='--', label='Median Engagement')
-            ax.set_xlabel("মোট ভিউ", fontproperties=BANGLA_FONT)
-            ax.set_ylabel("এনগেজমেন্ট রেট", fontproperties=BANGLA_FONT)
-            ax.set_title("Content Performance Quadrant", fontproperties=BANGLA_FONT)
+            ax.set_xlabel("মোট ভিউ", fontproperties=BANGLA_FONT, fontsize=14)
+            ax.set_ylabel("এনগেজমেন্ট রেট", fontproperties=BANGLA_FONT, fontsize=14)
+            ax.set_title("Content Performance Quadrant", fontproperties=BANGLA_FONT, fontsize=18)
+            for label in ax.get_xticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(12)
+            for label in ax.get_yticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(14)
+            legend = ax.get_legend()
+            if legend:
+                for text in legend.get_texts():
+                    text.set_fontproperties(BANGLA_FONT)
             plt.tight_layout()
         except Exception as e:
             logger.error(f"Quadrant plot failed: {e}")
@@ -720,9 +746,19 @@ def generate_youtube_dashboard(videos_df, comments_df):
         if not channel_counts.empty:
             fig_channels, ax = plt.subplots(figsize=(8, 6))
             channel_counts.plot(kind='barh', ax=ax, color='coral')
-            ax.set_title("Top 15 Channels by Video Volume", fontproperties=BANGLA_FONT)
-            ax.set_yticklabels(channel_counts.index, fontproperties=BANGLA_FONT)
-            ax.set_xlabel("Video Count", fontproperties=BANGLA_FONT)
+            ax.set_title("Top 15 Channels by Video Volume", fontproperties=BANGLA_FONT, fontsize=18)
+            ax.set_yticklabels(channel_counts.index, fontproperties=BANGLA_FONT, fontsize=14)
+            ax.set_xlabel("Video Count", fontproperties=BANGLA_FONT, fontsize=14)
+            for label in ax.get_xticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(12)
+            for label in ax.get_yticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(14)
+            legend = ax.get_legend()
+            if legend:
+                for text in legend.get_texts():
+                    text.set_fontproperties(BANGLA_FONT)
             plt.tight_layout()
     dashboard_components["yt_channel_plot"] = fig_channels
     
@@ -783,12 +819,22 @@ def generate_youtube_dashboard(videos_df, comments_df):
         if not top_videos.empty:
             fig_top_videos, ax = plt.subplots(figsize=(10, 6))
             top_videos.plot(kind='barh', ax=ax, color='dodgerblue')
-            ax.set_title("Top 10 Videos by Comment Count", fontproperties=BANGLA_FONT)
-            ax.set_xlabel("মন্তব্য সংখ্যা", fontproperties=BANGLA_FONT)
-            ax.set_ylabel("ভিডিও শিরোনাম", fontproperties=BANGLA_FONT)
+            ax.set_title("Top 10 Videos by Comment Count", fontproperties=BANGLA_FONT, fontsize=18)
+            ax.set_xlabel("মন্তব্য সংখ্যা", fontproperties=BANGLA_FONT, fontsize=14)
+            ax.set_ylabel("ভিডিও শিরোনাম", fontproperties=BANGLA_FONT, fontsize=14)
             yticks = np.arange(len(top_videos.index))
             ax.set_yticks(yticks)
-            ax.set_yticklabels(top_videos.index, fontproperties=BANGLA_FONT, fontsize=12)
+            ax.set_yticklabels(top_videos.index, fontproperties=BANGLA_FONT, fontsize=14)
+            for label in ax.get_xticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(12)
+            for label in ax.get_yticklabels():
+                label.set_fontproperties(BANGLA_FONT)
+                label.set_fontsize(14)
+            legend = ax.get_legend()
+            if legend:
+                for text in legend.get_texts():
+                    text.set_fontproperties(BANGLA_FONT)
             plt.tight_layout()
     dashboard_components["yt_top_videos_plot"] = fig_top_videos
     
@@ -812,12 +858,22 @@ def generate_youtube_dashboard(videos_df, comments_df):
                 if not top_engagement.empty:
                     fig_engagement, ax = plt.subplots(figsize=(10, 6))
                     ax.barh(top_engagement['video_title'], top_engagement['engagement_rate'], color='mediumseagreen')
-                    ax.set_title("Top 10 Videos by Engagement Rate", fontproperties=BANGLA_FONT)
-                    ax.set_xlabel("এনগেজমেন্ট রেট (মন্তব্য/ভিউ)", fontproperties=BANGLA_FONT)
-                    ax.set_ylabel("ভিডিও শিরোনাম", fontproperties=BANGLA_FONT)
+                    ax.set_title("Top 10 Videos by Engagement Rate", fontproperties=BANGLA_FONT, fontsize=18)
+                    ax.set_xlabel("এনগেজমেন্ট রেট (মন্তব্য/ভিউ)", fontproperties=BANGLA_FONT, fontsize=14)
+                    ax.set_ylabel("ভিডিও শিরোনাম", fontproperties=BANGLA_FONT, fontsize=14)
                     yticks = np.arange(len(top_engagement['video_title']))
                     ax.set_yticks(yticks)
-                    ax.set_yticklabels(top_engagement['video_title'], fontproperties=BANGLA_FONT, fontsize=12)
+                    ax.set_yticklabels(top_engagement['video_title'], fontproperties=BANGLA_FONT, fontsize=14)
+                    for label in ax.get_xticklabels():
+                        label.set_fontproperties(BANGLA_FONT)
+                        label.set_fontsize(12)
+                    for label in ax.get_yticklabels():
+                        label.set_fontproperties(BANGLA_FONT)
+                        label.set_fontsize(14)
+                    legend = ax.get_legend()
+                    if legend:
+                        for text in legend.get_texts():
+                            text.set_fontproperties(BANGLA_FONT)
                     plt.tight_layout()
             except Exception as e:
                 logger.error(f"Engagement rate calculation failed: {e}")
@@ -864,7 +920,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
                     gr.Markdown("### Search Criteria")
                     search_keywords_textbox = gr.Textbox(
                         label="Search Keywords", 
-                        placeholder="e.g., বিএনপি সমাবেশ", 
+                        placeholder="e.g., বাংলাদেশ, নির্বাচন", 
                         info="Keywords to search for in news articles."
                     )
                     sites_to_search_textbox = gr.Textbox(
@@ -896,7 +952,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
                     )
                     filter_keywords_textbox = gr.Textbox(
                         label="Filter Keywords (comma-separated, optional)", 
-                        placeholder="e.g., নির্বাচন, সরকার", 
+                        placeholder="e.g., ডাকসু, নোবেল", 
                         info="Filter results by these keywords."
                     )
                     
@@ -951,7 +1007,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
                 with gr.Column(scale=1):
                     yt_search_keywords = gr.Textbox(
                         label="YouTube Search Keywords", 
-                        placeholder="e.g., BNP Rally", 
+                        placeholder="e.g., ক্রিকেট", 
                         info="Keywords to search for in YouTube videos."
                     )
                     yt_max_videos_slider = gr.Slider(
@@ -1205,5 +1261,383 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
 # ==============================================================================
 # LAUNCH THE APP
 # ==============================================================================
-if __name__ == "__main__":
-    app.launch( debug=True,share=True)
+custom_css = """
+body, .gradio-container {
+    background: #181a20 !important;
+    font-family: 'Inter', 'Noto Sans', sans-serif;
+}
+.gr-card {
+    background: #23263a;
+    border-radius: 18px;
+    box-shadow: 0 4px 24px rgba(0,0,0,0.12);
+    padding: 24px;
+    margin-bottom: 24px;
+}
+.gr-title {
+    color: #fff;
+    font-size: 2.2rem;
+    font-weight: 700;
+    margin-bottom: 12px;
+}
+.gr-metric {
+    color: #22d3ee;
+    font-size: 2.5rem;
+    font-weight: 800;
+}
+.gr-label {
+    color: #94a3b8;
+    font-size: 1.1rem;
+    margin-bottom: 6px;
+}
+.gradio-row, .gradio-column {
+    background: transparent !important;
+}
+.gradio-button {
+    border-radius: 8px !important;
+    background: linear-gradient(90deg,#3b82f6,#22d3ee) !important;
+    color: #fff !important;
+    font-weight: 600 !important;
+    box-shadow: 0 2px 8px rgba(34,211,238,0.08);
+    transition: background 0.2s;
+}
+.gradio-button:hover {
+    background: linear-gradient(90deg,#22d3ee,#3b82f6) !important;
+}
+.gradio-markdown h1, .gradio-markdown h2, .gradio-markdown h3 {
+    color: #fff !important;
+}
+.gradio-markdown {
+    color: #cbd5e1 !important;
+}
+"""
+
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"), title=APP_TITLE, css=custom_css) as app:
+    gr.HTML("""
+    <div class='gr-card' style='margin-bottom:32px;'>
+        <div class='gr-title'>Social Perception Analyzer</div>
+        <div style='color:#94a3b8;font-size:1.2rem;margin-bottom:8px;'>Prepared for the Policymakers of Bangladesh Nationalist Party (BNP)</div>
+        <div style='color:#22d3ee;font-size:1rem;'>Developed by CDSR</div>
+    </div>
+    """)
+    # --- STATE MANAGEMENT ---
+    scraper_results_state = gr.State()
+    youtube_results_state = gr.State()
+
+    with gr.Tabs():
+        with gr.TabItem("1. News Scraper", id=0):
+            gr.HTML("<div class='gr-card' style='margin-bottom:24px;'><h2>News Scraper</h2><p>Search and filter news articles from top Bangladeshi sources. Use advanced filters and download results.</p></div>")
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.HTML("<div class='gr-card'><h3>Search Criteria</h3></div>")
+                    search_keywords_textbox = gr.Textbox(
+                        label="Search Keywords", 
+                        placeholder="e.g., বিএনপি সমাবেশ", 
+                        info="Keywords to search for in news articles."
+                    )
+                    sites_to_search_textbox = gr.Textbox(
+                        label="Target Sites (Optional, comma-separated)", 
+                        placeholder="e.g., prothomalo.com", 
+                        info="Limit search to specific news sites."
+                    )
+                    start_date_textbox = gr.Textbox(
+                        label="Start Date", 
+                        placeholder="YYYY-MM-DD or 'last week'", 
+                        info="Start date for news scraping."
+                    )
+                    end_date_textbox = gr.Textbox(
+                        label="End Date", 
+                        placeholder="YYYY-MM-DD or 'today'", 
+                        info="End date for news scraping."
+                    )
+                    gr.HTML("<div class='gr-card'><h3>Scraping Parameters</h3></div>")
+                    interval_days_slider = gr.Slider(
+                        1, 7, 3, step=1, 
+                        label="Days per Interval", 
+                        info="How many days to group each scraping interval."
+                    )
+                    max_pages_slider = gr.Slider(
+                        1, 10, 5, step=1, 
+                        label="Max Pages per Interval", 
+                        info="Maximum number of pages to fetch per interval."
+                    )
+                    filter_keywords_textbox = gr.Textbox(
+                        label="Filter Keywords (comma-separated, optional)", 
+                        placeholder="e.g., নির্বাচন, সরকার", 
+                        info="Filter results by these keywords."
+                    )
+                    start_scraper_button = gr.Button("Start Scraping & Analysis", variant="primary")
+                    scraper_progress = gr.Progress()
+                with gr.Column(scale=2):
+                    gr.HTML("<div class='gr-card'><h3>Filtered Results</h3></div>")
+                    scraper_results_df = gr.DataFrame(
+                        label="Filtered Results", 
+                        interactive=True
+                    )
+                    scraper_download_file = gr.File(
+                        label="Download Filtered Results CSV"
+                    )
+        with gr.TabItem("2. News Analytics", id=1):
+            gr.HTML("<div class='gr-card' style='margin-bottom:24px;'><h2>News Analytics Dashboard</h2><p>Visualize key metrics, trends, and top sources from scraped news data. All plots and metrics update dynamically.</p></div>")
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.HTML("<div class='gr-card'><h3>Key Metrics</h3></div>")
+                    kpi_total_articles = gr.HTML()
+                    kpi_unique_media = gr.HTML()
+                    kpi_date_range = gr.HTML()
+                with gr.Column(scale=2):
+                    gr.HTML("<div class='gr-card'><h3>Trends</h3></div>")
+                    dashboard_timeline_plot = gr.LinePlot(
+                        label="News Volume Timeline"
+                    )
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.HTML("<div class='gr-card'><h3>Top Sources</h3></div>")
+                    dashboard_media_plot = gr.Plot(
+                        label="Top Media Sources by Article Count"
+                    )
+                with gr.Column(scale=1):
+                    gr.HTML("<div class='gr-card'><h3>Headline Word Cloud</h3></div>")
+                    dashboard_wordcloud_plot = gr.Plot(
+                        label="Headline Word Cloud"
+                    )
+        with gr.TabItem("3. YouTube Topic Analysis", id=2):
+            gr.HTML("<div class='gr-card' style='margin-bottom:24px;'><h2>YouTube Topic Analysis</h2><p>Analyze YouTube video trends, engagement, and comment activity for your search topics.</p></div>")
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.HTML("<div class='gr-card'><h3>Search Criteria</h3></div>")
+                    yt_search_keywords = gr.Textbox(
+                        label="YouTube Search Keywords", 
+                        placeholder="e.g., BNP Rally", 
+                        info="Keywords to search for in YouTube videos."
+                    )
+                    yt_max_videos_slider = gr.Slider(
+                        10, 100, 30, step=5, 
+                        label="Max Videos for Stats", 
+                        info="Maximum number of videos to scan for statistics."
+                    )
+                    yt_num_videos_comments_slider = gr.Slider(
+                        1, 20, 5, step=1, 
+                        label="Videos for Comments", 
+                        info="Number of top videos to scrape comments from."
+                    )
+                    yt_max_comments_slider = gr.Slider(
+                        10, 200, 50, step=10, 
+                        label="Max Comments per Video", 
+                        info="Maximum number of comments to fetch per video."
+                    )
+                    yt_published_after = gr.Textbox(
+                        label="Published After (Optional)", 
+                        placeholder="YYYY-MM-DD", 
+                        info="Only include videos published after this date."
+                    )
+                    start_youtube_analysis_button = gr.Button(
+                        "Start YouTube Analysis", 
+                        variant="primary"
+                    )
+                    yt_progress = gr.Progress()
+                with gr.Column(scale=2):
+                    gr.HTML("<div class='gr-card'><h3>Video Results</h3></div>")
+                    yt_results_df = gr.DataFrame(
+                        label="YouTube Video Results", 
+                        interactive=True
+                    )
+                    yt_videos_download_file = gr.File(
+                        label="Download YouTube Video Results CSV"
+                    )
+                    yt_comments_df = gr.DataFrame(
+                        label="YouTube Comments Results", 
+                        interactive=True
+                    )
+                    yt_comments_download_file = gr.File(
+                        label="Download YouTube Comments CSV"
+                    )
+                    yt_dashboard_html = gr.HTML()
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.HTML("<div class='gr-card'><h3>Top Channels & Engagement</h3></div>")
+                    kpi_yt_videos_found = gr.HTML()
+                    kpi_yt_views_scanned = gr.HTML()
+                    kpi_yt_comments_scraped = gr.HTML()
+                    yt_channel_plot = gr.Plot(
+                        label="Top Channels by Video Volume"
+                    )
+                    yt_channel_dominance_plot = gr.Plot(
+                        label="Channel Dominance by View Count"
+                    )
+                    yt_top_videos_plot = gr.Plot(
+                        label="Top Videos by Comment Count"
+                    )
+                    yt_content_quadrant_plot = gr.Plot(
+                        label="Content Performance Quadrant"
+                    )
+                    yt_engagement_plot = gr.Plot(
+                        label="Top Videos by Engagement Rate"
+                    )
+                with gr.Column(scale=1):
+                    gr.HTML("<div class='gr-card'><h3>Comment Activity & Word Cloud</h3></div>")
+                    yt_time_series_plot = gr.LinePlot(
+                        label="Comment Activity Over Time"
+                    )
+                    yt_wordcloud_plot = gr.Plot(
+                        label="Bengali Word Cloud from Comments"
+                    )
+                    yt_detailed_summary = gr.HTML()
+    # --- EVENT HANDLERS ---
+    def scraper_button_handler(search_keywords, sites, start_date, end_date, interval, max_pages, filter_keys):
+        """Handle news scraper button click event."""
+        try:
+            df, filtered_df = run_news_scraper_pipeline(
+                search_keywords, sites, start_date, end_date, 
+                interval, max_pages, filter_keys
+            )
+            scraper_results_state = df
+            dashboard = generate_scraper_dashboard(df)
+            if not df.empty:
+                csv_path = "news_results.csv"
+                df.to_csv(csv_path, index=False)
+                scraper_download_file = gr.File(value=csv_path, visible=True)
+            else:
+                scraper_download_file = gr.File(visible=False)
+            return (
+                filtered_df,
+                scraper_download_file,
+                dashboard["kpi_total_articles"],
+                dashboard["kpi_unique_media"],
+                dashboard["kpi_date_range"],
+                dashboard["dashboard_timeline_plot"],
+                dashboard["dashboard_media_plot"],
+                dashboard["dashboard_wordcloud_plot"]
+            )
+        except Exception as e:
+            logger.error(f"Error in scraper button handler: {str(e)}")
+            gr.Error(f"An error occurred during scraping: {str(e)}")
+            return (
+                pd.DataFrame(), 
+                gr.File(visible=False),
+                gr.HTML(""), gr.HTML(""), gr.HTML(""),
+                None, None, None
+            )
+
+    start_scraper_button.click(
+        fn=scraper_button_handler,
+        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,
+            kpi_total_articles,
+            kpi_unique_media,
+            kpi_date_range,
+            dashboard_timeline_plot,
+            dashboard_media_plot,
+            dashboard_wordcloud_plot
+        ]
+    )
+
+    def youtube_button_handler(keywords, max_videos, num_comments_videos, max_comments, published_after):
+        """Handle YouTube analysis button click event."""
+        try:
+            videos_df, comments_df, summary_html = run_youtube_analysis_pipeline(
+                api_key=None,
+                query=keywords,
+                max_videos_for_stats=max_videos,
+                num_videos_for_comments=num_comments_videos,
+                max_comments_per_video=max_comments,
+                published_after=published_after
+            )
+            youtube_results_state = (videos_df, comments_df)
+            yt_videos_csv = "youtube_videos.csv"
+            yt_comments_csv = "youtube_comments.csv"
+            if not videos_df.empty:
+                videos_df.to_csv(yt_videos_csv, index=False)
+                yt_videos_download_file = gr.File(value=yt_videos_csv, visible=True)
+            else:
+                yt_videos_download_file = gr.File(visible=False)
+            if not comments_df.empty:
+                if "video_title" not in comments_df.columns and "video_id" in comments_df.columns:
+                    title_map = videos_df.set_index("video_id")["video_title"].to_dict()
+                    comments_df["video_title"] = comments_df["video_id"].map(title_map)
+                if "channel" not in comments_df.columns and "channel_title" in comments_df.columns:
+                    comments_df["channel"] = comments_df["channel_title"]
+                comments_df.to_csv(yt_comments_csv, index=False)
+                yt_comments_download_file = gr.File(value=yt_comments_csv, visible=True)
+            else:
+                yt_comments_download_file = gr.File(visible=False)
+            dashboard = generate_youtube_dashboard(videos_df, comments_df)
+            return (
+                videos_df,
+                yt_videos_download_file,
+                comments_df,
+                yt_comments_download_file,
+                summary_html,
+                dashboard["kpi_yt_videos_found"],
+                dashboard["kpi_yt_views_scanned"],
+                dashboard["kpi_yt_comments_scraped"],
+                dashboard["yt_channel_plot"],
+                dashboard["yt_channel_dominance_plot"],
+                dashboard["yt_time_series_plot"],
+                dashboard["yt_top_videos_plot"],
+                dashboard["yt_content_quadrant_plot"],
+                dashboard["yt_engagement_plot"],
+                dashboard["yt_wordcloud_plot"],
+                dashboard["yt_detailed_summary"]
+            )
+        except Exception as e:
+            logger.error(f"Error in YouTube button handler: {str(e)}")
+            gr.Error(f"An error occurred during YouTube analysis: {str(e)}")
+            return (
+                pd.DataFrame(),                # yt_results_df
+                gr.File(visible=False),         # yt_videos_download_file
+                pd.DataFrame(),                # yt_comments_df
+                gr.File(visible=False),         # yt_comments_download_file
+                gr.HTML(""),                   # yt_dashboard_html
+                gr.HTML(""),                   # kpi_yt_videos_found
+                gr.HTML(""),                   # kpi_yt_views_scanned
+                gr.HTML(""),                   # kpi_yt_comments_scraped
+                None,                          # yt_channel_plot
+                None,                          # yt_channel_dominance_plot
+                None,                          # yt_time_series_plot
+                None,                          # yt_top_videos_plot
+                None,                          # yt_content_quadrant_plot
+                None,                          # yt_engagement_plot
+                None,                          # yt_wordcloud_plot
+                gr.HTML("")                    # yt_detailed_summary
+            )
+
+    start_youtube_analysis_button.click(
+        fn=youtube_button_handler,
+        inputs=[
+            yt_search_keywords, 
+            yt_max_videos_slider, 
+            yt_num_videos_comments_slider, 
+            yt_max_comments_slider, 
+            yt_published_after
+        ],
+        outputs=[
+            yt_results_df,
+            yt_videos_download_file,
+            yt_comments_df,
+            yt_comments_download_file,
+            yt_dashboard_html,
+            kpi_yt_videos_found,
+            kpi_yt_views_scanned,
+            kpi_yt_comments_scraped,
+            yt_channel_plot,
+            yt_channel_dominance_plot,
+            yt_time_series_plot,
+            yt_top_videos_plot,
+            yt_content_quadrant_plot,
+            yt_engagement_plot,
+            yt_wordcloud_plot,
+            yt_detailed_summary
+        ]
+    )
+    if __name__ == "__main__":
+        app.launch(debug=True, share=True)