update app

app.py

@@ -13,18 +13,10 @@ from transformers import pipeline
 # spec_generator_2 = MixerTTSModel.from_pretrained("tts_en_lj_mixerttsx")
 # model1 = HifiGanModel.from_pretrained(model_name="tts_en_lj_hifigan_ft_mixerttsx")
 
-
 def greet(name):
     return "Hello " + name + "!!"
 
-def run():
-
-    spec_generator = FastPitchModel.from_pretrained("tts_en_fastpitch_multispeaker")
-    spec_generator.eval()
-    voc_model = HifiGanModel.from_pretrained(model_name="tts_en_hifitts_hifigan_ft_fastpitch")
-    voc_model.eval()
-
-    pipe = pipeline("text-to-speech", model="suno/bark-small")
+def run(spec_generator, voc_model, pipe):
 
     def generate_tts(text: str, speaker: int = 0):
         sr = 44100
@@ -32,17 +24,25 @@ def run():
         spectrogram = spec_generator.generate_spectrogram(tokens=parsed, speaker=speaker)
         audio = voc_model.convert_spectrogram_to_audio(spec=spectrogram)
         
-        return (sr, audio.squeeze(0).cpu().numpy())
+        return gr.Audio.update(sr, audio.squeeze(0).cpu().numpy())
 
     demo = gr.Interface(
         fn=generate_tts,
         inputs=[gr.Textbox(value="This is a test.", label="Text to Synthesize"),
                 gr.Slider(0, 10, step=1, label="Speaker")],
         outputs=gr.Audio(label="Output", type="numpy"),
+        allow_flagging=False,
     )
 
     demo.launch(server_name="0.0.0.0", server_port=7860)
 
-
 if __name__ == "__main__":
-    run()
+
+    spec_generator = FastPitchModel.from_pretrained("tts_en_fastpitch_multispeaker")
+    spec_generator.eval()
+    voc_model = HifiGanModel.from_pretrained(model_name="tts_en_hifitts_hifigan_ft_fastpitch")
+    voc_model.eval()
+
+    pipe = pipeline("text-to-speech", model="suno/bark-small")
+    
+    run(spec_generator, voc_model, pipe)