import tempfile import gradio as gr from datetime import datetime from enum import Enum from ukrainian_tts.tts import TTS, Stress, Voices from torch.cuda import is_available from os import getenv from data_logger import log_data from threading import Thread from queue import Queue from time import sleep def check_thread(logging_queue: Queue): logging_callback = log_data(hf_token=getenv("HF_API_TOKEN"), dataset_name="uk-tts-output", private=True) while True: sleep(60) batch = [] while not logging_queue.empty(): batch.append(logging_queue.get()) if len(batch) > 0: try: logging_callback(batch) except: print("Error happened while pushing data to HF. Puttting items back in queue...") for item in batch: logging_queue.put(item) if getenv("HF_API_TOKEN") is not None: log_queue = Queue() t = Thread(target=check_thread, args=(log_queue,)) t.start() class StressOption(Enum): AutomaticStress = "Автоматичні наголоси (за словником) 📖" AutomaticStressWithModel = "Автоматичні наголоси (за допомогою моделі) 🧮" class VoiceOption(Enum): Olena = "Олена (жіночий) 👩" Mykyta = "Микита (чоловічий) 👨" Lada = "Лада (жіночий) 👩" Dmytro = "Дмитро (чоловічий) 👨" Olga = "Ольга (жіночий) 👩" print(f"CUDA available? {is_available()}") badge = ( "https://visitor-badge-reloaded.herokuapp.com/badge?page_id=robinhad.ukrainian-tts" ) ukr_tts = TTS(use_cuda=is_available()) def tts(text: str, voice: str, stress: str): print("============================") print("Original text:", text) print("Voice", voice) print("Stress:", stress) print("Time:", datetime.utcnow()) voice_mapping = { VoiceOption.Olena.value: Voices.Olena.value, VoiceOption.Mykyta.value: Voices.Mykyta.value, VoiceOption.Lada.value: Voices.Lada.value, VoiceOption.Dmytro.value: Voices.Dmytro.value, VoiceOption.Olga.value: Voices.Olga.value, } stress_mapping = { StressOption.AutomaticStress.value: Stress.Dictionary.value, StressOption.AutomaticStressWithModel.value: Stress.Model.value } speaker_name = voice_mapping[voice] stress_selected = stress_mapping[stress] text_limit = 7200 text = ( text if len(text) < text_limit else text[0:text_limit] ) # mitigate crashes on hf space if getenv("HF_API_TOKEN") is not None: log_queue.put([text, speaker_name, stress_selected, str(datetime.utcnow())]) with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp: _, text = ukr_tts.tts(text, speaker_name, stress_selected, fp) return fp.name, text with open("README.md") as file: article = file.read() article = article[article.find("---\n", 4) + 5::] iface = gr.Interface( fn=tts, inputs=[ gr.components.Textbox( label="Input", value="Введіть, будь ласка, своє р+ечення.", ), gr.components.Radio( label="Голос", choices=[option.value for option in VoiceOption], value=VoiceOption.Olena.value, ), gr.components.Radio( label="Наголоси", choices=[option.value for option in StressOption], value=StressOption.AutomaticStress.value ), ], outputs=[ gr.components.Audio(label="Output"), gr.components.Textbox(label="Наголошений текст"), ], title="🐸💬🇺🇦 - Coqui TTS", description="Україномовний🇺🇦 TTS за допомогою Coqui TTS (щоб вручну поставити наголос, використовуйте + перед голосною)", article=article + f'\n