app.py

import torch
import gradio as gr
import pytube as pt
from transformers import pipeline

MODEL_NAME = "ales/whisper-small-belarusian"
lang = "be"

device = 0 if torch.cuda.is_available() else "cpu"
print(f"Device set to use {device}")

pipe = pipeline(
    task="automatic-speech-recognition",
    model=MODEL_NAME,
    chunk_length_s=8,
    stride_length_s=1,
    device=device,
)

pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language=lang, task="transcribe")


def transcribe(audio_file):
    if audio_file is None:
        return "ERROR: Please upload or record audio"
    return pipe(audio_file)["text"]


def yt_transcribe(yt_url):
    if not yt_url:
        return "", "ERROR: You must provide a YouTube URL."
    yt = pt.YouTube(yt_url)
    video_id = yt_url.split("?v=")[-1].split("&")[0]
    embed = f'<center><iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}" frameborder="0" allowfullscreen></iframe></center>'
    stream = yt.streams.filter(only_audio=True).first()
    stream.download(filename="audio.mp3")
    text = pipe("audio.mp3")["text"]
    return embed, text


with gr.Blocks() as demo:
    with gr.Tab("🎤 Transcribe Audio"):
        gr.Markdown("## Запішы або загрузі аўдыё")
        audio_input = gr.Audio(type="filepath", label="Record or Upload Audio")
        transcribe_button = gr.Button("Transcribe")
        transcription_output = gr.Textbox(label="Transcription")

        transcribe_button.click(
            fn=transcribe,
            inputs=[audio_input],
            outputs=[transcription_output],
        )

    with gr.Tab("📺 Transcribe YouTube"):
        gr.Markdown("## Устаў спасылку на YouTube-відэа")
        yt_input = gr.Textbox(label="YouTube URL", placeholder="https://www.youtube.com/watch?v=...")
        yt_button = gr.Button("Transcribe YouTube")
        yt_embed = gr.HTML()
        yt_text = gr.Textbox(label="Transcription")

        yt_button.click(
            fn=yt_transcribe,
            inputs=[yt_input],
            outputs=[yt_embed, yt_text],
        )

demo.launch()