o

inference.py

@@ -80,9 +80,6 @@ def infer_araberta(text):
     clean_tokens = [t for t in tokens if t not in tokenizer.all_special_tokens]
     clean_labels = [l for t, l in zip(tokens, predicted_labels) if t not in tokenizer.all_special_tokens]
 
-    # Horizontal output
-    pairs = [f"{token}: {label}" for token, label in zip(clean_tokens, clean_labels)]
-    horizontal_output = " | ".join(pairs)
 
     # Group by aspect span
     aspects = []
@@ -115,13 +112,19 @@ def infer_araberta(text):
             "sentiment": current_sentiment
         })
 
+    token_predictions = [
+        {"token": token, "label": label}
+        for token, label in zip(clean_tokens, clean_labels)
+    ]
+
     return {
-        "token_predictions": horizontal_output,
+        "token_predictions": token_predictions,
         "aspects": aspects
     }
 
 
 
+
 def load_model(model_key):
     if model_key in cached_models:
         return cached_models[model_key]