Update app.py

app.py

@@ -3,6 +3,8 @@ import gradio as gr
 import json
 from Data_Fetching_and_Rendering import fetch_and_render_dashboard
 from analytics_fetch_and_rendering import fetch_and_render_analytics
+from mentions_dashboard import generate_mentions_dashboard
+
 
 # Shared state
 token_received = {"status": False, "token": None, "client_id": None}
@@ -61,6 +63,15 @@ def guarded_fetch_analytics():
     )
     return count_md, plot
 
+def run_mentions_and_load(comm_token, comm_client_id):
+    try:
+        html_path = generate_mentions_dashboard(comm_client_id, comm_token)
+        with open(html_path, "r", encoding="utf-8") as f:
+            return f.read()
+    except Exception as e:
+        return f"<p style='color:red;'>Failed to load mentions: {e}</p>"
+
+
 # --- Build the Gradio UI ---
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                title="LinkedIn Post Viewer & Analytics") as app:
@@ -114,6 +125,17 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                 outputs=[follower_count, follower_plot]
             )
 
+        with gr.TabItem("3️⃣ Mentions"):
+            gr.Markdown("Analyze sentiment of recent posts that mention your organization.")
+            fetch_mentions_btn = gr.Button("🧠 Fetch Mentions & Sentiment", variant="primary")
+            mentions_html = gr.HTML(value="<p style='text-align:center; color:#555;'>Waiting for token...</p>")
+            fetch_mentions_btn.click(
+                fn=run_mentions_and_load,
+                inputs=[token_display, client_display],
+                outputs=[mentions_html]
+            )
+
+
 # Launch the app
 if __name__ == "__main__":
     app.launch(server_name="0.0.0.0", server_port=7860, share=True)