Update app.py

app.py

@@ -2,6 +2,15 @@ import streamlit as st
 from transformers import pipeline
 
 sentiment_analysis = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")
+
+def convert_label_to_sentiment(label):
+    if label in ["4", "5"]:
+        return "Positive"
+    elif label in ["1", "2"]:
+        return "Negative"
+    else:
+        return "Neutral"
+
 def perform_sentiment_analysis(text):
     result = sentiment_analysis(text)
     return {'label': result[0]['label'], 'score': result[0]['score']}
@@ -14,15 +23,10 @@ def main():
 
     # Perform sentiment analysis on button click
     if st.button("Submit"):
-        sentiment="Neutral "
         if financial_content.strip():
             sentiment_result = perform_sentiment_analysis(financial_content)
-            
-            if sentiment_result['label'][0]=="5" or sentiment_result['label'][0]=="4" :
-                sentiment= "Positive"
-            elif sentiment_result['label'][0]=="1" or sentiment_result['label'][0]=="2" :
-                sentiment= "Negative"
-            st.success(f"Sentiment: {sentiment}     Score: {sentiment_result['score']:.2f}")
+            sentiment = convert_label_to_sentiment(sentiment_result['label'][0])
+            st.success(f"Sentiment: {sentiment} | Score: {sentiment_result['score']:.2f}")
         else:
             st.warning("Please enter financial content before submitting.")