diff --git a/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py b/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py
index 0e7afd5da3f..696341598e5 100644
--- a/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py
+++ b/litellm/llms/vertex_ai/vertex_embeddings/embedding_handler.py
@@ -65,7 +65,9 @@ class VertexEmbedding(VertexBase):
                 litellm_params=litellm_params,
             )
 
-        should_use_v1beta1_features = self.is_using_v1beta1_features(optional_params=optional_params)
+        should_use_v1beta1_features = self.is_using_v1beta1_features(
+            optional_params=optional_params
+        )
 
         _auth_header, vertex_project = self._ensure_access_token(
             credentials=vertex_credentials,
@@ -128,10 +130,14 @@ class VertexEmbedding(VertexBase):
 
         _json_response = response.json()
         ## LOGGING POST-CALL
-        logging_obj.post_call(input=input, api_key=None, original_response=_json_response)
+        logging_obj.post_call(
+            input=input, api_key=None, original_response=_json_response
+        )
 
-        model_response = litellm.vertexAITextEmbeddingConfig.transform_vertex_response_to_openai(
-            response=_json_response, model=model, model_response=model_response
+        model_response = (
+            litellm.vertexAITextEmbeddingConfig.transform_vertex_response_to_openai(
+                response=_json_response, model=model, model_response=model_response
+            )
         )
 
         return model_response
@@ -160,7 +166,9 @@ class VertexEmbedding(VertexBase):
         """
         Async embedding implementation
         """
-        should_use_v1beta1_features = self.is_using_v1beta1_features(optional_params=optional_params)
+        should_use_v1beta1_features = self.is_using_v1beta1_features(
+            optional_params=optional_params
+        )
         _auth_header, vertex_project = await self._ensure_access_token_async(
             credentials=vertex_credentials,
             project_id=vertex_project,
@@ -197,7 +205,9 @@ class VertexEmbedding(VertexBase):
         if timeout:
             _async_client_params["timeout"] = timeout
         if client is None or not isinstance(client, AsyncHTTPHandler):
-            client = get_async_httpx_client(params=_async_client_params, llm_provider=litellm.LlmProviders.VERTEX_AI)
+            client = get_async_httpx_client(
+                params=_async_client_params, llm_provider=litellm.LlmProviders.VERTEX_AI
+            )
         else:
             client = client  # type: ignore
         ## LOGGING
@@ -222,10 +232,14 @@ class VertexEmbedding(VertexBase):
 
         _json_response = response.json()
         ## LOGGING POST-CALL
-        logging_obj.post_call(input=input, api_key=None, original_response=_json_response)
+        logging_obj.post_call(
+            input=input, api_key=None, original_response=_json_response
+        )
 
-        model_response = litellm.vertexAITextEmbeddingConfig.transform_vertex_response_to_openai(
-            response=_json_response, model=model, model_response=model_response
+        model_response = (
+            litellm.vertexAITextEmbeddingConfig.transform_vertex_response_to_openai(
+                response=_json_response, model=model, model_response=model_response
+            )
         )
 
         return model_response