vader test

app.py

@@ -2,12 +2,13 @@ import streamlit as st
 import tensorflow as tf
 from transformers import pipeline
 from textblob import TextBlob
+from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
 
 classifier = pipeline(task="sentiment-analysis")
 
 textIn = st.text_input("Input Text Here:", "I really like the color of your car!")
 
-option = st.selectbox('Which pre-trained model would you like for your sentiment analysis?',('Pipeline', 'TextBlob', ''))
+option = st.selectbox('Which pre-trained model would you like for your sentiment analysis?',('Pipeline', 'TextBlob', 'Vader'))
 
 st.write('You selected:', option)
 
@@ -30,5 +31,9 @@ if option == 'TextBlob':
     else:
         sentiment = 'Positive'
 
-    st.write('According to textblob, input text is ', sentiment, ' and a subjectivity score (from 0 being objective to 1 being subjective) of ', subjectivity)
+    st.write('According to TextBlob, input text is ', sentiment, ' and a subjectivity score (from 0 being objective to 1 being subjective) of ', subjectivity)
 
+if option == 'Vader':
+    #  vader
+    sentiment = SentimentIntensityAnalyzer().polarity_scores(textIn)['compound']
+    st.write('According to Vader, input text is ', sentiment)