import gradio as gr

from main_pipeline import main_pipeline
from scipy.io.wavfile import write

url = "https://t.me/diarizarion_bot"


title = "Audio_denoise and speaker diarization.Faster inference <a href='{}' target='_blank'>tg_bot</a>".format(url)

example_list = [
    ["dialog.mp3"]
]


def app_pipeline(audio):
    audio_path = 'test.wav'
    write(audio_path, audio[0], audio[1])
    denoised_audio_path, result_diarization = main_pipeline(audio_path)

    return result_diarization + [None] * (10 - len(result_diarization))


gr.Interface(
    app_pipeline,
    gr.Audio(type="numpy", label="Input"),
    [gr.Audio(visible=True) for i in range(10)],
    title=title,
    examples=example_list,
    cache_examples=False,

).launch(enable_queue=True)