Update app.py

app.py

@@ -6,45 +6,53 @@ classifier = pipeline("text-classification", model="Mpavan45/Telugu_Sentimental_
 
 # Define the Streamlit interface
 st.title("Sentiment Analysis with BERT")
-st.write("This app uses a fine-tuned BERT model to classify text as positive or negative sentiment.")
+st.write("This app uses a fine-tuned BERT model to classify text as positive, negative, or neutral sentiment.")
 
 # Example test cases
 st.subheader("Try one of the following examples:")
 examples = [
-   " ఈ song చాలా catchy గా ఉంది",
-   "నీ attitude చాల బాగుంది",
+    "ఈ song చాలా catchy గా ఉంది",
+    "నీ attitude చాల బాగుంది",
     "ఆమె behavior rude",
     "ఈ ఆహారం చాలా చెడుగా ఉంది",
     "నాకు ఈ రోజు చాలా సంతోషంగా ఉంది",
     "నేను ఈ వార్తలకు చాలా బాధపడ్డాను",
-
 ]
 
 for example in examples:
     if st.button(f"Test: {example[:30]}..."):
         result = classifier(example)
-        sentiment = result[0]['label']
+        raw_label = result[0]['label']
         confidence = result[0]['score']
+        
+        label_map = {
+            "LABEL_0": "Negative",
+            "LABEL_1": "Neutral",
+            "LABEL_2": "Positive"
+        }
+        sentiment = label_map.get(raw_label, raw_label)
+        
         st.write(f"Sentiment: {sentiment}")
         st.write(f"Confidence: {confidence:.4f}")
         st.text_area("Analysis of your text", example, height=150)
 
 # Take input text from the user
 text_input = st.text_area("Enter text to analyze sentiment:")
-label_map = {
-    "LABEL_0": "Negative",
-    "LABEL_1": "Neutral",
-    "LABEL_2": "Positive"
-}
-
 
 # When the user clicks the button, classify the sentiment
 if st.button("Analyze Sentiment"):
     if text_input:
         result = classifier(text_input)
-        sentiment = result[0]['label']
+        raw_label = result[0]['label']
         confidence = result[0]['score']
+        
+        label_map = {
+            "LABEL_0": "Negative",
+            "LABEL_1": "Neutral",
+            "LABEL_2": "Positive"
+        }
         sentiment = label_map.get(raw_label, raw_label)
+
         st.write(f"Sentiment: {sentiment}")
         st.write(f"Confidence: {confidence:.4f}")
     else: