Create app.py

app.py

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+import whisper
+from pytube import YouTube
+from pydub import AudioSegment
+import gradio as gr
+import os
+import re
+
+model = whisper.load_model("small")
+
+# def compress_audio(file_path, bitrate='32k'):
+#     try:
+#         audio = AudioSegment.from_file(file_path)
+#         output_format = os.path.splitext(file_path)[1][1:]
+#         compressed_audio = audio.export(file_path, format=output_format, bitrate=bitrate)
+#         return True
+#     except Exception as e:
+#         print(f"Error: {e}")
+#         return False
+
+def url_to_text(url):
+    if url != '':
+        output_text_transcribe = ''
+
+    yt = YouTube(url)
+    video = yt.streams.filter(only_audio=True).first()
+    out_file=video.download(output_path=".")
+    file_stats = os.stat(out_file)
+    
+    if file_stats.st_size <= 30_000_000:
+    
+        base, ext = os.path.splitext(out_file)
+        os.rename(out_file, base+'.mp3')
+        file_path = base+'.mp3'
+        # compress_audio(file_path)
+        
+        result = model.transcribe(file_path)
+        return result['text'].strip()
+    else:
+        raise gr.Error("Exception: Problems with the audio transcription.")
+
+def get_summary(article):
+    first_sentences = ' '.join(re.split(r'(?<=[.:;])\s', article)[:5])
+    b = summarizer(first_sentences, min_length = 20, max_length = 120, do_sample = False)
+    b = b[0]['summary_text'].replace(' .', '.').strip()
+    return b
+
+with gr.Blocks() as demo:
+    gr.Markdown("<h1><center>Samir's AI Model Implementation -  Automatic Speech Recognition</center></h1>")
+    gr.Markdown("<h2><center>YouTube Audio AutoTranscribe: Effortless Transcription</center></h2>")
+    gr.Markdown("<center><b>This application is using <a href=https://openai.com/blog/whisper/ target=_blank>OpenAI's Whisper</a>. Whisper is an intricately designed <br>neural network aiming to achieve the highest precision in the field of multilingual speech recognition.</b></center>")
+    gr.Markdown("<center><b>The time for the model to perform transcription typically takes around 10 seconds for every 1 minute of video. <br>For example, a 12-minute video would take approximately 120 seconds to transcribe the audio content.</b></center>")
+    
+    input_text_url = gr.Textbox(placeholder='👇Youtube Video URL👇', label='YouTube URL')
+    result_button_transcribe = gr.Button('Transcribe Now')
+    output_text_transcribe = gr.Textbox(placeholder='Transcription of the YouTube video.', label='Transcript')
+    
+    result_button_transcribe.click(url_to_text, inputs = input_text_url, outputs = output_text_transcribe)
+
+demo.queue(default_enabled = True).launch(debug = True)