Create app.py

app.py

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+from newspaper import Article
+from newspaper import Config
+import nltk
+nltk.download('punkt')
+from gradio.mix import Series
+import gradio as gr
+def extract_article_text(url):
+  USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:78.0) Gecko/20100101 Firefox/78.0'
+  config = Config()
+  config.browser_user_agent = USER_AGENT
+  config.request_timeout = 10
+
+  article = Article(url, config=config)
+  article.download()
+  article.parse()
+  text = article.text
+  return text
+extractor = gr.Interface(extract_article_text, 'text', 'text')
+summarizer = gr.Interface.load("huggingface/facebook/bart-large-cnn")
+
+sample_url = [['https://www.technologyreview.com/2021/07/22/1029973/deepmind-alphafold-protein-folding-biology-disease-drugs-proteome/'],
+              ['https://www.technologyreview.com/2021/07/21/1029860/disability-rights-employment-discrimination-ai-hiring/'],
+              ['https://www.technologyreview.com/2021/07/09/1028140/ai-voice-actors-sound-human/']]
+
+desc =  '''
+        Generate summary of an article using bart-large-cnn model by Facebook.
+        '''
+
+iface = Series(extractor, summarizer, 
+  inputs = gr.inputs.Textbox(
+      lines = 2,
+      label = 'URL'
+  ),
+  outputs = 'text',
+  title = 'Article Cortex: Transformers powered article summarization engine',
+  theme = 'huggingface',
+  description = desc,
+  examples=sample_url,allow_flagging="manual",flagging_options=["random summary", "useful summary"])
+
+iface.launch(share=True, debug=True)