app.py

import whisper
import yt_dlp
import gradio as gr
import os
import re

model = whisper.load_model("base")

def get_audio(url):
    try:
        ydl_opts = {
            'format': 'bestaudio/best',
            'noplaylist': True,
            'quiet': True,
            'outtmpl': '%(title)s.%(ext)s'  # Specify output template to get the file path
        }
        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
            info = ydl.extract_info(url, download=True)
            # Use 'requested_downloads' to get the downloaded file path
            audio_file = ydl.prepare_filename(info)
            return audio_file
    except Exception as e:
        raise gr.Error(f"Exception: {e}")

def get_text(url):
    try:
        if url != '':
            audio_file = get_audio(url)
            result = model.transcribe(audio_file)
            return result['text'].strip()
        else:
            return "Please enter a YouTube video URL."
    except Exception as e:
        raise gr.Error(f"Exception: {e}")

def get_summary(article):
    try:
        first_sentences = ' '.join(re.split(r'(?<=[.:;])\s', article)[:5])
        return first_sentences
    except Exception as e:
        raise gr.Error(f"Exception: {e}")

with gr.Blocks() as demo:
    gr.Markdown("<h1><center>Free Fast YouTube URL Video-to-Text using <a href=https://openai.com/blog/whisper/ target=_blank>OpenAI's Whisper</a> Model</center></h1>")
    gr.Markdown("<center>Enter the link of any YouTube video to generate a text transcript of the video.</center>")
    gr.Markdown("<center><b>'Whisper is a neural net that approaches human level robustness and accuracy on English speech recognition.'</b></center>")
    gr.Markdown("<center>Transcription takes 5-10 seconds per minute of the video (bad audio/hard accents slow it down a bit). #patience<br />If you have time while waiting, check out my <a href=https://www.artificial-intelligence.blog target=_blank>AI blog</a> (opens in new tab).</center>")
    
    input_text_url = gr.Textbox(placeholder='Youtube video URL', label='URL')
    result_button_transcribe = gr.Button('1. Transcribe')
    output_text_transcribe = gr.Textbox(placeholder='Transcript of the YouTube video.', label='Transcript')

    result_button_transcribe.click(get_text, inputs=input_text_url, outputs=output_text_transcribe)

    demo.queue(default_enabled=True).launch(debug=True)