Update app.py

app.py

@@ -16,15 +16,15 @@ def get_classifier_model():
 
 #st.image("Suncorp-Bank-logo.png",width=255)
 
-st.title("Detecting Barriers from Conversations")
+st.title("Review Analyzer")
 st.markdown("***")
 
-text = st.text_area(label="Enter text to classify")
+text = st.text_area(label="Paste/Type the review here..")
 st.markdown("***")
 
 col1, col2, col3 = st.columns((1,1,1))
 col1.header("Select Sentiments")
-sentiments = col1.multiselect("",["Happy","Sad","Neutral"])
+sentiments = col1.multiselect("",["Happy","Sad","Neutral"],["Happy","Sad","Neutral"])
 col2.header("Select Topics")
 entities = col2.multiselect("",["Bank Account","Credit Card","Home Loan","Motor Loan"],
                             ["Bank Account","Credit Card","Home Loan","Motor Loan"])
@@ -32,8 +32,8 @@ entities = col2.multiselect("",["Bank Account","Credit Card","Home Loan","Motor
 
 col3.header("Select Reasons")
 
-reasons = col3.multiselect("",["Poor_Service","No_Empathy","Abuse"],
-                            ["Poor_Service","No_Empathy","Abuse"])
+reasons = col3.multiselect("",["Poor Service","No Empathy","Abuse"],
+                            ["Poor Service","No Empathy","Abuse"])
 
 is_multi_class =  st.checkbox("Can have more than one classes",value=True)
 
@@ -66,12 +66,15 @@ if classify_button_clicked:
                 #print(classification_output)
                 fig = get_classification(sentiments)
                 # col5, col6= st.columns((1, 1))
+                col1.markdown("***")
+                col1.markdown("***")
                 col1.write(fig)
 
             if entities:
                 #print(classification_output)
                 fig = get_classification(entities)
                 # col7, col8= st.columns((1, 1))
+                
                 col2.write(fig)
 
             if reasons: