Update app_qwen_tts_fast.py

app_qwen_tts_fast.py

@@ -174,7 +174,8 @@ def run_pipeline(question: str, language_id: str):
 # GRADIO UI
 # =====================================================
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-   
+
+    gr.Markdown("# 📄 Qwen CPU Assistant + TTS (Multilingual)")
 
     with gr.Row():
         with gr.Column(scale=1):
@@ -190,15 +191,49 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             )
             ask_btn = gr.Button("Ask")
 
+            # ===== Example questions =====
+            gr.Markdown("### Example Questions")
+            
+            with gr.Tabs():
+                with gr.Tab("English"):
+                    gr.Button("Who is the CEO of OhamLab?").click(
+                        lambda: ("Who is the CEO of OhamLab?", "en"), 
+                        outputs=[user_input, language_dropdown]
+                    )
+                    gr.Button("What does OhamLab AI do?").click(
+                        lambda: ("What does OhamLab AI do?", "en"), 
+                        outputs=[user_input, language_dropdown]
+                    )
+                    gr.Button("Where is OhamLab located?").click(
+                        lambda: ("Where is OhamLab located?", "en"), 
+                        outputs=[user_input, language_dropdown]
+                    )
+
+                with gr.Tab("Hindi"):
+                    gr.Button("ओहमलैब के सीईओ कौन हैं?").click(
+                        lambda: ("ओहमलैब के सीईओ कौन हैं?", "hi"), 
+                        outputs=[user_input, language_dropdown]
+                    )
+                    gr.Button("ओहमलैब एआई क्या करता है?").click(
+                        lambda: ("ओहमलैब एआई क्या करता है?", "hi"), 
+                        outputs=[user_input, language_dropdown]
+                    )
+                    gr.Button("ओहमलैब कहाँ स्थित है?").click(
+                        lambda: ("ओहमलैब कहाँ स्थित है?", "hi"), 
+                        outputs=[user_input, language_dropdown]
+                    )
+
         with gr.Column(scale=1):
             answer_text = gr.Markdown()
             answer_audio = gr.Audio(type="filepath")
 
+    # ===== Ask button click =====
     ask_btn.click(
         fn=run_pipeline,
         inputs=[user_input, language_dropdown],
         outputs=[answer_text, answer_audio]
     )
 
+
 demo.queue()  # enable long-running jobs for TTS
 demo.launch(server_name="0.0.0.0", server_port=7860, share=False)