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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("<h1><center>Youtube and Video File Upload with Whisper Transcription and Summary</center></h1>")
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)
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