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

MODEL_NAME = "BlueRaccoon/whisper-small-kab"  # this always needs to stay in line 8 :D sorry for the hackiness
lang = "uz"

device = 0 if torch.cuda.is_available() else "cpu"
pipe = pipeline(
    task="automatic-speech-recognition",
    model=MODEL_NAME,
    chunk_length_s=30,
    device=device,
)

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


def transcribe(microphone, file_upload):
    warn_output = ""
    if (microphone is not None) and (file_upload is not None):
        warn_output = (
            "WARNING: You've uploaded an audio file and used the microphone. "
            "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
        )

    elif (microphone is None) and (file_upload is None):
        return "ERROR: You have to either use the microphone or upload an audio file"

    file = microphone if microphone is not None else file_upload

    text = pipe(file)["text"]

    return warn_output + text


def _return_yt_html_embed(yt_url):
    video_id = yt_url.split("?v=")[-1]
    HTML_str = (
        f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
        " </center>"
    )
    return HTML_str


def yt_transcribe(yt_url):
    yt = pt.YouTube(yt_url)
    html_embed_str = _return_yt_html_embed(yt_url)
    stream = yt.streams.filter(only_audio=True)[0]
    stream.download(filename="audio.mp3")

    text = pipe("audio.mp3")["text"]

    return html_embed_str, text


with gr.Blocks() as demo:
    with gr.Tab("Transcribe Audio"):
        gr.Markdown(
            f"""
            # Whisper Demo: Transcribe Audio
            Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the fine-tuned
            checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files
            of arbitrary length.
            """
        )
        # Inputs for microphone recording or file upload
        microphone_input = gr.Audio(type="filepath", label="Record or Upload Audio")
        file_upload_input = gr.Audio(type="filepath", label="Upload Audio File (Optional)")
        gr.Interface(
            fn=transcribe,
            inputs=[microphone_input, file_upload_input],
            outputs=gr.Textbox(label="Transcription"),
        )

    with gr.Tab("Transcribe YouTube"):
        gr.Markdown(
            f"""
            # Whisper Demo: Transcribe YouTube
            Transcribe long-form YouTube videos with the click of a button! Demo uses the fine-tuned checkpoint
            [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files of
            arbitrary length.
            """
        )
        yt_url_input = gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL")
        gr.Interface(
            fn=yt_transcribe,
            inputs=[yt_url_input],
            outputs=[gr.HTML(label="YouTube Video"), gr.Textbox(label="Transcription")],
        )

demo.launch(enable_queue=True)