updated app

app.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import streamlit as st
+from streamlit_text_rating.st_text_rater import st_text_rater
 from sentiment import classify_sentiment
 
 st.set_page_config(  # Alternate names: setup_page, page, layout
@@ -7,15 +8,16 @@ st.set_page_config(  # Alternate names: setup_page, page, layout
     initial_sidebar_state="auto",  # Can be "auto", "expanded", "collapsed"
     page_title='None',  # String or None. Strings get appended with "• Streamlit".
 )
-# padding_top = 0
-# st.markdown(f"""
-#     <style>
-#         .reportview-container .main .block-container{{
-#             padding-top: {padding_top}rem;
-#         }}
-#     </style>""",
-#     unsafe_allow_html=True,
-# )
+
+padding_top = 0
+st.markdown(f"""
+    <style>
+        .reportview-container .main .block-container{{
+            padding-top: {padding_top}rem;
+        }}
+    </style>""",
+    unsafe_allow_html=True,
+)
 
 def set_page_title(title):
     st.sidebar.markdown(unsafe_allow_html=True, body=f"""
@@ -69,4 +71,9 @@ if select_task=='Detect Sentiment':
     if input_texts!='':
         sentiments = classify_sentiment(input_texts)
         for i,t in enumerate(input_texts.split(',')):
-            st.write("** " + t + f"--> This statement is {sentiments[i]}")
+            if sentiments[i]=='Positive':
+                response=st_text_rater(t + f"--> This statement is {sentiments[i]}",
+                                       color_background='rgb(154,205,50)')
+            else:
+                response = st_text_rater(t + f"--> This statement is {sentiments[i]}",
+                                         color_background='rgb(233, 116, 81)')