Update app.py

app.py

@@ -261,27 +261,30 @@ elif selected_menu == "Extract Entities":
             st.markdown("""---""")
             
 elif selected_menu == "Detected Barriers":
-    st.subheader('Barriers Detected')
+    #st.subheader('Barriers Detected')
     barriers_to_detect = {"Chronic Pain":"Is the patint experiencing chronic pain?",
                           "Mental Health Issues":"Does he have any mental issues?",
                           "Prior History":"What is prior medical history?",
                           "Smoking":"Does he smoke?",
                           "Drinking":"Does he drink?",
                           "Comorbidities":"Does he have any comorbidities?"}
-                          
-    for barrier,question_text in barriers_to_detect.items():
     
-        context = get_text_from_ocr_engine()
-        if question_text:
-            result = pipeline_qa(question=question_text,  context=context)
-            st.subheader(barrier)
-            st.text(result['answer']) 
+    with st.spinner("Detecting Barriers..."):                                            
+        for barrier,question_text in barriers_to_detect.items():
+        
+            context = get_text_from_ocr_engine()
+            if question_text:
+                result = pipeline_qa(question=question_text,  context=context)
+                st.subheader(barrier)
+                st.text(result['answer']) 
 
 elif selected_menu == "Get Answers":
     st.subheader('Question')
     question_text = st.text_input("Type your question")
     context = get_text_from_ocr_engine()
+  
     if question_text:
-        result = pipeline_qa(question=question_text,  context=context)
-        st.subheader('Answer')
-        st.text(result['answer'])
+        with st.spinner("Finding Answer(s)..."):
+            result = pipeline_qa(question=question_text,  context=context)
+            st.subheader('Answer')
+            st.text(result['answer'])