Create new file

app.py

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+import wikipedia
+
+def wikipediaScrap(article_name, wikipedia_language = "en"):
+  if wikipedia_language:
+    wikipedia.set_lang(wikipedia_language)
+
+  et_page = wikipedia.page(article_name)
+  title = et_page.title
+  content = et_page.content
+  page_url = et_page.url
+  linked_pages = et_page.links
+  
+  text = content
+
+  # Create and generate a word cloud image:
+  #wordcloud = WordCloud(font_path="HelveticaWorld-Regular.ttf").generate(text)
+
+  # Display the generated image:
+  #plt.imshow(wordcloud, interpolation='bilinear')
+  #plt.axis("off")
+  return title, content, page_url, "\n". join(linked_pages)
+  
+def answer(text):
+  title,content,page_url,link = wikipediaScrap(text)
+  result = list(filter(lambda x : x != '', content.split('\n\n')))
+  answer = []
+  for i in range(2):
+    if len(result[i]) > 100:
+      r = requests.post(
+          url="https://hf.space/embed/jaimin/article-qa-summarizer/+/api/predict",
+          json={"data": [result[i]]},
+      )
+      response = r.json()
+      answer.append(response['data'][0])
+   return answer
+   
+iface = gr.Interface(fn=answer, inputs=[gr.inputs.Textbox(lines=5)],outputs="text")
+#iface1 = gr.Interface(fn=get_paraphrases_pytorchlight, inputs=[gr.inputs.Textbox(lines=5)],outputs="text")
+iface.launch()