Update app.py

app.py

@@ -1,46 +0,0 @@
-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()