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README.txt

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+---
+title: 📺NLP Video Summary📝
+emoji: 📺📝
+colorFrom: red
+colorTo: green
+sdk: gradio
+sdk_version: 2.9.1
+app_file: app.py
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

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+import gradio as gr
+from summarize import Summarizer
+
+interface = gr.Interface(fn = Summarizer,
+                        inputs = [gr.inputs.Textbox(lines=2, 
+                                                    placeholder="Enter your link...",
+                                                    label='YouTube Video Link'),
+                                  gr.inputs.Radio(["mT5", "BART"], type="value", label='Model')],
+                        outputs = [gr.outputs.Textbox(
+                                                      label="Summary")],
+                         
+                        title = "Video Summary Generator",
+                        examples = [
+                                   ['https://www.youtube.com/watch?v=cdiD-9MMpb0', 'BART'],
+                                   ['https://www.youtube.com/watch?v=p3lsYlod5OU&t=5202s', 'BART'],
+                                   ['https://www.youtube.com/watch?v=Gfr50f6ZBvo&t=1493s', 'BART'],
+                                   ['https://www.youtube.com/watch?v=4oDZyOf6CW4&t=3149s', 'BART'],
+                                   ['https://www.youtube.com/watch?v=lvh3g7eszVQ&t=291s', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=OaeYUm06in0', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=ZecQ64l-gKM&t=545s', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=5zOHSysMmH0&t=5798s', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=X0-SXS6zdEQ&t=23s', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=gFEE3w7F0ww&t=18s', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=Z1KwkpTUbkg&t=30s', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=rIpUf-Vy2JA&t=3542s', 'mT5'],
+                                   ['https://www.youtube.com/watch?v=bgNzUxyS-kQ&t=3631s', 'mT5']
+                                   ],
+                        enable_queue=True)
+
+interface.launch(debug=True) 

requirements.txt

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+torch
+transformers
+sentencepiece
+youtube-transcript-api

summarize.py

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+import traceback
+import sys
+
+from youtube_transcript_api import YouTubeTranscriptApi
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+def Summarizer(link, model):
+  
+  video_id = link.split("=")[1]
+
+  try:
+    transcript = YouTubeTranscriptApi.get_transcript(video_id)
+    FinalTranscript = ' '.join([i['text'] for i in transcript])
+    
+    if model == "Pegasus":
+      checkpoint = "google/pegasus-large"
+    elif model == "mT5":
+      checkpoint = "csebuetnlp/mT5_multilingual_XLSum"
+    elif model == "BART":
+      checkpoint = "sshleifer/distilbart-cnn-12-6"
+      
+    tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+    model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
+
+
+    inputs = tokenizer(FinalTranscript, 
+                    max_length=1024, 
+                    truncation=True,
+                    return_tensors="pt")
+    
+    summary_ids = model.generate(inputs["input_ids"])
+    summary = tokenizer.batch_decode(summary_ids, 
+                                  skip_special_tokens=True, 
+                                  clean_up_tokenization_spaces=False)
+    
+
+    return summary[0]
+    
+
+  except Exception:
+    print(traceback.format_exc())
+    # or
+    print(sys.exc_info()[2])