Update app.py

app.py

@@ -68,12 +68,7 @@ with gr.Blocks() as demo:
     
         with gr.Tabs():
             with gr.TabItem("The Summarization App"):
-                gr.Markdown("""
-                <h3>The Summarization Task</h3>
-                <p>
-                The goal of text summarization is to extract or generate concise and accurate summaries of a given text document while maintaining key information found                             within the original text document. Text summarization methods can either be used as an extractive or abstractive model. An Extractive method does what it sounds like, it concatenates different important sentences or paragraphs without understanding the meaning of those parts. Extractive summarization does not create any new word phrases. For instance,  if you presented a page of text to an extractive model, it would just act as a text “highlighter”. However, Abstractive summarization generates text in a fashion that tries to guess the meaning in a summarised way of the page of text it is presented. It would put words together in a meaningful way and add the most important fact found in the text. 
-                bl </p>
-                """)              
+                gr.Markdown(sum_app_text_tab_1)              
 
             with gr.TabItem("The Summarization Engine"):
                 gr.Markdown("""