Update app.py

app.py

@@ -1,8 +1,6 @@
-pip install googletrans==4.0.0rc1
 import streamlit as st
 from transformers import pipeline
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
-from googletrans import Translator
 
 # Load the sentiment analysis model from our BERT model
 classifier = pipeline("text-classification", model = "MarieAngeA13/Sentiment-Analysis-BERT")
@@ -15,21 +13,11 @@ st.write('Enter some text and we will predict its sentiment!')
 translator = Translator()
 text_input = st.text_input('Enter text here')
 
-detected_language = translator.detect(text_input).lang
-
-if detected_language == 'fr':
-    translation = translator.translate(text_input, src='fr', dest='en')
-    translated_text = translation.text
-else:
-    translated_text = text_input
-print(translated_text)
-
-
 
 # When the user submits text, run the sentiment analysis model on it
 if st.button('Submit'):
     # Predict the sentiment of the text using our own BERT model
-    output = classifier(translated_text)
+    output = classifier(text_input)
 
     best_prediction = output[0]
     sentiment = best_prediction['label']