Create app.py

app.py

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+import whisper
+import yt_dlp
+import gradio as gr
+import os
+import re
+import logging
+
+logging.basicConfig(level=logging.INFO)
+model = whisper.load_model("medium")
+def get_text(url):
+    #try:
+    if url != '':
+        output_text_transcribe = ''
+
+    with yt_dlp.YoutubeDL({'format': 'bestaudio', 'audio-format': 'wav', 'outtmpl': '%(id)s.%(ext)s'}) as ydl:
+        # Extract information from the given YouTube URL and download the best audio format available
+        info_dict = ydl.extract_info(url, download=True)
+        # Prepare the filename of the downloaded audio file
+        audio_file = ydl.prepare_filename(info_dict)    #finally:
+    #    raise gr.Error("Exception: There was a problem transcribing the audio.")
+        result = model.transcribe(audio_file, task="transcribe")
+        return result['text'].strip()
+
+with gr.Blocks() as demo:
+    gr.Markdown("<h1><center>YouTube Video-to-Text using Whisper</center></h1>")
+    gr.Markdown("<center>Enter the link of any YouTube video to generate a text transcript of the video.</center>")
+    
+    input_text_url = gr.Textbox(placeholder='Youtube video URL', label='YouTube URL')
+    result_button_transcribe = gr.Button('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)