Create app.py

app.py

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+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)