import gradio as gr import edge_tts import asyncio import librosa import soundfile import io from inference.infer_tool import Svc def get_or_create_eventloop(): try: return asyncio.get_event_loop() except RuntimeError as ex: if "There is no current event loop in thread" in str(ex): loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) return asyncio.get_event_loop() def tts_get_voices_list(): voices = [] tts_voice_list = asyncio.get_event_loop().run_until_complete(edge_tts.list_voices()) for item in tts_voice_list: voices.append(item['ShortName']) return voices def tts_mode(txt, voice): tts = asyncio.run(edge_tts.Communicate(txt, voice).save('temp\\test.mp3')) audio, sr = librosa.load('temp\\test.mp3', sr=16000, mono=True) raw_path = io.BytesIO() soundfile.write(raw_path, audio, 16000, format="wav") raw_path.seek(0) model = Svc(fr"Herta-Svc/G_10000.pth", f"Herta-Svc/config.json", device = 'cpu') out_audio, out_sr = model.infer('speaker0', 0, raw_path, auto_predict_f0 = True,) soundfile.write('temp\\xxx.wav', out_audio.cpu().numpy(), 44100) audio_file = open('temp\\xxx.wav', 'rb') audio_bytes = audio_file.read() return audio_bytes if __name__ == '__main__': loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) with gr.Blocks() as app: with gr.Tabs(): with gr.TabItem('Herta'): tts_text = gr.Textbox(label="TTS text (100 words limitation)", visible = True) tts_voice = gr.Dropdown(choices= tts_get_voices_list(), visible = True) audio_output = gr.Audio(label="Output Audio") btn_submit = gr.Button("Generate") btn_submit.click(tts_mode, [tts_text, tts_voice], [audio_output]) app.launch()