Update app.py

app.py

@@ -29,15 +29,13 @@ tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
 sentiment_model = AutoModelForSequenceClassification.from_pretrained("SamanthaStorm/tether-sentiment").to(device)
 sentiment_tokenizer = AutoTokenizer.from_pretrained("SamanthaStorm/tether-sentiment", use_fast=False)
 
-# Emotion pipeline
-emotion_pipeline = hf_pipeline(
+emotion_pipeline = pipeline(
     "text-classification",
     model="j-hartmann/emotion-english-distilroberta-base",
-    top_k=6,
-    truncation=True,
-    device=0 if torch.cuda.is_available() else -1
+    tokenizer="j-hartmann/emotion-english-distilroberta-base",
+    return_all_scores=True,     # ← ensure we get all six scores, not just top-1
+    top_k=None                  # ← ensure no automatic top-k truncation (so you see all labels)
 )
-
 # DARVO model
 darvo_model = AutoModelForSequenceClassification.from_pretrained("SamanthaStorm/tether-darvo-regressor-v1").to(device)
 darvo_tokenizer = AutoTokenizer.from_pretrained("SamanthaStorm/tether-darvo-regressor-v1", use_fast=False)