Upload app.py

app.py

@@ -2,14 +2,14 @@ import streamlit as st
 from transformers import pipeline
 from transformers import AutoModelForQuestionAnswering, AutoTokenizer
 
-# set page title
-st.set_page_config(page_title="Automated Question Answering System")
 
-# heading and description
-st.markdown("<h2 style='text-align: center;'>Question Answering on Academic Essays</h2>", unsafe_allow_html=True)
-st.markdown("<h3 style='text-align: left; color:#F63366; font-size:18px;'><b>What is extractive question answering about?<b></h3>", unsafe_allow_html=True)
-st.write("Extractive question answering is a Natural Language Processing task where text is provided for a model so that the model can refer to it and make predictions about where the answer to a question is.")
+st.set_page_config(page_title="Automated Question Answering System")    # set page title
 
+# heading 
+st.markdown("<h2 style='text-align: center;'>Question Answering on Academic Essays</h2>", unsafe_allow_html=True)   
+# description
+st.markdown("<h3 style='text-align: left; color:#F63366; font-size:18px;'><b>What is extractive question answering about?<b></h3>", unsafe_allow_html=True)     
+st.write("Extractive question answering is a Natural Language Processing task where text is provided for a model so that the model can refer to it and make predictions about where the answer to a question is.")
 
 # store the model in cache resources to enhance efficiency (ref: https://docs.streamlit.io/library/advanced-features/caching)
 @st.cache_resource(show_spinner=True)
@@ -55,8 +55,9 @@ with tab1:
         with st.spinner(text="Getting answer..."):
             answer = question_answerer(context=context, question=question)
             answer = answer["answer"]
+            # display the result in container
             container = st.container(border=True)
-            container.write("<h5><b>Answer:</b></h5>" + answer, unsafe_allow_html=True)
+            container.write("<h5><b>Answer:</b></h5>" + answer + "<br>", unsafe_allow_html=True)
 
 
 # if upload file as input  
@@ -78,5 +79,9 @@ with tab2:
             with st.spinner(text="Getting answer..."):
                 answer = question_answerer(context=context, question=question)
                 answer = answer["answer"]
-                st.success(answer)
+                # display the result in container
+                container = st.container(border=True)
+                container.write("<h5><b>Answer:</b></h5>" + answer + "<br>", unsafe_allow_html=True)
+
+st.markdown("<br><br><br><br><br>", unsafe_allow_html=True)