Update app.py

app.py

@@ -63,7 +63,7 @@ def combine_audio_arrays(audio_list):
     combined_audio = np.concatenate(audio_list, axis=0)
     return combined_audio
 
-@spaces.GPU(duration=30)
+@spaces.GPU(duration=25)
 # Function to generate audio for a single sentence
 def generate_single_wav_from_text(sentence, description):
     torch.manual_seed(SEED)
@@ -124,13 +124,25 @@ with gr.Blocks() as demo:
             combined_audio = combine_audio_arrays(all_audio)
             all_text += f"**Sentence**: {sentence}\n\n"
             yield (sample_rate, combined_audio), all_text
+    examples = [
+    [
+        "Once upon a time, in the depth of winter, when the flakes of snow fell like feathers from the clouds, a queen sat sewing at her pal-ace window, which had a carved frame of black wood.",
+        "In an inferior recording quality, a female speaker delivers her slightly expressive and animated words with a fast pace. There's high level of background noise and a very distant-sounding reverberation. Her voice is slightly higher pitched than average.",
+        None,
+    ],
+    [
+        "The Importance of AI Safety.pdf",
+        "Gary's voice is monotone yet slightly fast in delivery, with a very close recording that has no background noise.",
+        None
+    ]            
+]
 
     input_mode.change(
         fn=lambda choice: [gr.update(visible=choice == "Upload PDF"), gr.update(visible=choice == "Type Text")],
         inputs=input_mode,
-        outputs=[pdf_input, text_input]
+        outputs=[pdf_input, text_input],
     )
-    
+    gr.Examples(examples=examples, fn=gen_tts, inputs=inputs, outputs=outputs, cache_examples=True)
     source_lang.change(update_target_lang, inputs=source_lang, outputs=target_lang)
 
     run_button.click(run_pipeline, inputs=[input_mode, pdf_input, text_input, translate_checkbox, source_lang, target_lang, description], outputs=[audio_output, markdown_output])