import gradio as gr  
from tqdm import tqdm
from transformers import pipeline 
from IPython.display import YouTubeVideo  
from youtube_transcript_api import YouTubeTranscriptApi 

def video2Summarizer(link): 
  youtube_video = link
  video_id = youtube_video.split('=')[1]  
  transcript = YouTubeTranscriptApi.get_transcript(video_id)  

  result = ""
  for i in transcript:
      result += ' ' + i['text']

  summarizer = pipeline('summarization')

  num_iters = int(len(result)/1000)
  summarized_text = []
  for i in tqdm(range(0, num_iters + 1)):
    start = 0
    start = i * 1000
    end = (i + 1) * 1000
    out = summarizer(result[start:end])
    out = out[0]
    out = out['summary_text']
    summarized_text.append(out)

  return summarized_text
  
  
 iface = gr.Interface(fn = video2Summarizer, 
                     inputs = 'text', 
                    outputs = gr.outputs.Textbox(label = "Summarized output"),
                     title = 'Video To Text Summarizer', 
                     description = 'Just give the url of the YouTube video, then the app will give you the summarized format of the video in 5 to 10 Min, its based on the video length what you have given. Use this example and try to run the same example by clicking that',
                     examples = [['https://www.youtube.com/watch?v=kEN2Omq9mwk']]
                     )

iface.launch(inline = False)