import whisper from pytube import YouTube from transformers import pipeline import gradio as gr import os model = whisper.load_model("base") summarizer = pipeline("summarization") def get_audio(url): yt = YouTube(url) video = yt.streams.filter(only_audio=True).first() out_file = video.download(output_path=".") base, ext = os.path.splitext(out_file) new_file = base + '.mp3' os.rename(out_file, new_file) return new_file def get_text_from_url(url): result = model.transcribe(get_audio(url)) return result['text'] def get_text_from_file(file): # Assuming the uploaded file is already in MP3 format result = model.transcribe(file.name) return result['text'] def get_summary_from_url(url): article = get_text_from_url(url) b = summarizer(article) return b[0]['summary_text'] def get_summary_from_file(file): article = get_text_from_file(file) b = summarizer(article) return b[0]['summary_text'] def process_url(url): transcription = get_text_from_url(url) summary = get_summary_from_url(url) return summary, transcription def process_file(file): transcription = get_text_from_file(file) summary = get_summary_from_file(file) return summary, transcription with gr.Blocks() as demo: gr.Markdown("

Youtube and Video File Upload with Whisper Transcription and Summary

") gr.Warning("Enter the link of any youtube video or upload an MP4 file to get the transcription and a summary in text form. Note: I'm using a git trick in the requirements file to run this without an openai API Key, if you wnat a little more speed and want to do it with an openai API Key check out the code base at https://huggingface.co/spaces/eaglelandsonce/ChatGPT_Enhanced, if you want to interact live with folks on line check out my Meetup at https://www.meetup.com/florence-aws-user-group-meetup/.") with gr.Tab('Youtube Video'): with gr.Row(): input_text = gr.Textbox(placeholder='Enter the Youtube video URL', label='URL') output_summary = gr.Textbox(placeholder='Summary text of the Youtube Video', label='Summary') output_transcription = gr.Textbox(placeholder='Transcription of the video', label='Transcription') result_button = gr.Button('Process Youtube Video') with gr.Tab('Uploaded MP4'): with gr.Row(): input_file = gr.File(label='Upload MP4') output_file_summary = gr.Textbox(placeholder='Summary text of the video', label='Summary') output_file_transcription = gr.Textbox(placeholder='Transcription of the video', label='Transcription') result_button_file = gr.Button('Process Uploaded MP4') result_button.click(process_url, inputs=input_text, outputs=[output_summary, output_transcription]) result_button_file.click(process_file, inputs=input_file, outputs=[output_file_summary, output_file_transcription]) demo.launch(debug=True)