Update app.py

app.py

@@ -158,7 +158,7 @@ def added_token_hash_func(token):
     return token.__str__()
 
 # Define the function for sentiment analysis
-@st.cache(hash_funcs={tokenizers.Tokenizer: tokenizer_hash_func, tokenizers.AddedToken: added_token_hash_func})
+@st.cache_data(hash_funcs={tokenizers.Tokenizer: tokenizer_hash_func, tokenizers.AddedToken: added_token_hash_func})
 def predict_sentiment(text):
     # Load the pipeline
     pipeline = transformers.pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
@@ -170,7 +170,6 @@ def predict_sentiment(text):
 
     return sentiment, score
 
-
 # Setting the page configurations
 st.set_page_config(
     page_title="Sentiment Analysis App",
@@ -198,9 +197,9 @@ if predict_button and text:
     
     # Display individual percentages
     st.write("Sentiment Breakdown:")
-    st.write(f"- Negative: {score['NEGATIVE']*100:.2f}%")
-    st.write(f"- Positive: {score['POSITIVE']*100:.2f}%")
-    st.write(f"- Neutral: {score['NEUTRAL']*100:.2f}%")
+    st.write(f"- Negative: {score['LABEL_0']*100:.2f}%")
+    st.write(f"- Positive: {score['LABEL_1']*100:.2f}%")
+    st.write(f"- Neutral: {score['LABEL_2']*100:.2f}%")
 
 # Define the CSS style for the app
 st.markdown(
@@ -216,5 +215,4 @@ h1 {
 </style>
 """,
 unsafe_allow_html=True
-)
-
+)