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Create app.py
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import re
from youtube_transcript_api import YouTubeTranscriptApi
from youtube_transcript_api.formatters import TextFormatter
import torch
import gradio as gr
from transformers import pipeline
text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
# model_path = ("../Models/models--sshleifer--distilbart-cnn-12-6/snapshots"
# "/a4f8f3ea906ed274767e9906dbaede7531d660ff")
# text_summary = pipeline("summarization", model=model_path,
# torch_dtype=torch.bfloat16)
def summary (input):
output = text_summary(input)
return output[0]['summary_text']
def extract_video_id(url):
# Regex to extract the video ID from various YouTube URL formats
regex = r"(?:youtube\.com\/(?:[^\/\n\s]+\/\S+\/|(?:v|e(?:mbed)?)\/|\S*?[?&]v=)|youtu\.be\/)([a-zA-Z0-9_-]{11})"
match = re.search(regex, url)
if match:
return match.group(1)
return None
def get_youtube_transcript(video_url):
video_id = extract_video_id(video_url)
if not video_id:
return "Video ID could not be extracted."
try:
# Fetch the transcript
transcript = YouTubeTranscriptApi.get_transcript(video_id)
# Format the transcript into plain text
formatter = TextFormatter()
text_transcript = formatter.format_transcript(transcript)
summary_text = summary(text_transcript)
return summary_text
except Exception as e:
return f"An error occurred: {e}"
# Example URL (Replace this with the actual URL when using the script)
# video_url = "https://youtu.be/5PibknhIsTc"
# print(get_youtube_transcript(video_url))
gr.close_all()
# demo = gr.Interface(fn=summary, inputs="text",outputs="text")
demo = gr.Interface(fn=get_youtube_transcript,
inputs=[gr.Textbox(label="Input YouTube Url to summarize",lines=1)],
outputs=[gr.Textbox(label="Summarized text",lines=4)],
title="@GenAILearniverse Project 2: YouTube Script Summarizer",
description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE YOUTUBE VIDEO SCRIPT.")
demo.launch()