Update app.py

app.py

@@ -208,13 +208,8 @@ def classify_emotion(text, classifier):
         all_scores = []
         for chunk in chunks:
             try:
-                inputs = classifier.tokenizer(
-                    chunk,
-                    truncation=True,
-                    max_length=512,
-                    return_tensors="pt"
-                )
-                result = classifier(chunk, truncation=True, max_length=512)
+                # Direct classification without additional tokenization
+                result = classifier(chunk)
                 scores = result[0]
                 all_scores.append(scores)
             except Exception as chunk_error:
@@ -226,11 +221,10 @@ def classify_emotion(text, classifier):
             count = len(all_scores)
             
             for scores in all_scores:
-                for score in scores:
-                    label = score['label']
-                    if label not in label_scores:
-                        label_scores[label] = 0
-                    label_scores[label] += score['score']
+                label = scores['label']
+                if label not in label_scores:
+                    label_scores[label] = 0
+                label_scores[label] += scores['score']
             
             avg_scores = {label: score/count for label, score in label_scores.items()}
             final_emotion = max(avg_scores.items(), key=lambda x: x[1])[0]
@@ -241,7 +235,7 @@ def classify_emotion(text, classifier):
     except Exception as e:
         st.warning(f"Error in emotion classification: {str(e)}")
         return "LABEL_2"
-
+        
 def get_embedding_for_text(text, tokenizer, model):
     """Get embedding for complete text."""
     chunks = split_text(text)