Upload app.py

app.py

@@ -11,6 +11,7 @@ st.write("Extractive question answering is a Natural Language Processing task wh
 # st.markdown('___')
 
 # store the model in cache resources to enhance efficiency
+# ref: https://docs.streamlit.io/library/advanced-features/caching 
 @st.cache_resource(show_spinner=True)
 def question_model():
     # call my model for question answering
@@ -30,12 +31,14 @@ with tab1:
         sample_text = text_file.read()
 
     example = st.button("Try example")
-    context = st.text_area("Enter the essay below:", height=330)
-    question = st.text_input(label="Enter the question: ")
+
+    context = st.text_area("Enter the essay below:", key="context", height=330)
+    question = st.text_input(label="Enter the question: ", key="question")
+
     if example:
-        context = st.text_area("Enter the essay below:", value= sample_text,height=330)
-        question = st.text_input(label="Enter the question: ", value= sample_question)
-        
+        st.session_state.context = sample_text
+        st.session_state.question = sample_question
+
     button = st.button("Get answer")
     if button:
         with st.spinner(text="Loading question model..."):