Update handler.py

handler.py

@@ -13,27 +13,29 @@ class EndpointHandler():
       Return:
             A :obj:`list` | `dict`: will be serialized and returned
         """
+
+        def normalize_vectors(vectors):
+            """
+            Normalize a single vector or a list of vectors.
+        
+            Parameters:
+                vectors (Union[np.ndarray, List[np.ndarray]]): Input vector or list of vectors.
+        
+            Returns:
+                Union[np.ndarray, List[np.ndarray]]: Normalized vector or list of normalized vectors.
+            """
+            if isinstance(vectors, np.ndarray):
+                # If it's a single vector, normalize it
+                return vectors / np.linalg.norm(vectors)
+            elif isinstance(vectors, list):
+                # If it's a list of vectors, normalize each vector in the list
+                return [vector / np.linalg.norm(vector) for vector in vectors]
+            else:
+                raise ValueError("Input must be a numpy array or a list of numpy arrays.")
+        
         inputs = data.pop("inputs",data)
         prediction = self.pipeline(inputs)
         normalized_prediction = normalize_vectors(prediction)
         
-        return normalized_prediction
-
-    def normalize_vectors(vectors):
-    """
-    Normalize a single vector or a list of vectors.
-
-    Parameters:
-        vectors (Union[np.ndarray, List[np.ndarray]]): Input vector or list of vectors.
+        return {"embeddings":  normalized_prediction}
 
-    Returns:
-        Union[np.ndarray, List[np.ndarray]]: Normalized vector or list of normalized vectors.
-    """
-    if isinstance(vectors, np.ndarray):
-        # If it's a single vector, normalize it
-        return vectors / np.linalg.norm(vectors)
-    elif isinstance(vectors, list):
-        # If it's a list of vectors, normalize each vector in the list
-        return [vector / np.linalg.norm(vector) for vector in vectors]
-    else:
-        raise ValueError("Input must be a numpy array or a list of numpy arrays.")