import gradio as gr
from infer_onnx import TTS
from ruaccent import RUAccent # https://huggingface.co/TeraTTS/accentuator

models = ["TeraTTS/natasha-g2p-vits", "TeraTTS/glados2-g2p-vits"]

models = {k:TTS(k) for k in models}

accentizer = RUAccent(workdir="./model/ruaccent")
accentizer.load(omograph_model_size='medium', dict_load_startup=True)


def process_text(text: str) -> str:
    text = accentizer.process_all(text)
    return text

def text_to_speech(model_name, text, prep_text):
    if prep_text:
        text = process_text(text)
    audio = models[model_name](text)
    models[model_name].save_wav(audio, 'temp.wav')

    return 'temp.wav', f"Обработанный текст: '{text}'"

model_choice = gr.Dropdown(choices=list(models.keys()), value="TeraTTS/natasha-g2p-vits", label="Выберите модель")
input_text = gr.Textbox(label="Введите текст для синтеза речи")
prep_text = gr.Checkbox(label="Предобработать", info="Хотите пред обработать текст?(Ударения, ё)", value=True)

output_audio = gr.Audio(label="Аудио", type="numpy")
output_text = gr.Textbox(label="Обработанный текст")

iface = gr.Interface(fn=text_to_speech, inputs=[model_choice, input_text, prep_text], outputs=[output_audio, output_text])
iface.launch()