Update app.py

app.py

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+from newspaper import Article
+from newspaper import Config
+import nltk
+nltk.download('punkt')
+
+from transformers import pipeline
+import gradio as gr
+from gradio.mix import Parallel, Series
+
+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://parstoday.com/en/news/iran-i163822-iran_condemns_terrorist_attack_in_pakistan_reaffirms_need_to_fight_terrorism_across_region/'],
+              ['https://parstoday.com/en/news/west_asia-i163734-ansarullah_yemenis_entitled_to_avenge_nation%E2%80%99s_sufferings_inflicted_due_to_war_siege/'],
+              ['https://parstoday.com/en/news/west_asia-i163684-saudi_led_warplanes_intensify_airstrikes_against_yemeni_capital/']]
+
+desc =  '''
+        Let Hugging Face models summarize articles for you. 
+        Note: Shorter articles generate faster summaries.
+        This summarizer uses bart-large-cnn model by Facebook
+        '''
+
+iface = Series(extractor, summarizer, 
+  inputs = gr.inputs.Textbox(
+      lines = 2,
+      label = 'URL'
+  ),
+  outputs = 'text',
+  title = 'News Summarizer',
+  theme = 'huggingface',
+  description = desc,
+  examples=sample_url)
+
+iface.launch()