diff --git a/litellm/google_genai/adapters/handler.py b/litellm/google_genai/adapters/handler.py
index c15d0cb9deb..ee9083cbbf0 100644
--- a/litellm/google_genai/adapters/handler.py
+++ b/litellm/google_genai/adapters/handler.py
@@ -38,8 +38,8 @@ class GenerateContentToCompletionHandler:
         completion_kwargs: Dict[str, Any] = dict(completion_request)
 
         # feed metadata for custom callback
-        if 'metadata' in extra_kwargs:
-            completion_kwargs['metadata'] = extra_kwargs['metadata']
+        if "metadata" in extra_kwargs:
+            completion_kwargs["metadata"] = extra_kwargs["metadata"]
 
         if stream:
             completion_kwargs["stream"] = stream
diff --git a/litellm/proxy/google_endpoints/endpoints.py b/litellm/proxy/google_endpoints/endpoints.py
index 4f57e1e7ce8..eb481b0a4f0 100644
--- a/litellm/proxy/google_endpoints/endpoints.py
+++ b/litellm/proxy/google_endpoints/endpoints.py
@@ -181,9 +181,11 @@ async def google_count_tokens(request: Request, model_name: str):
     from litellm.proxy._types import TokenCountRequest
 
     # Translate contents to openai format messages using the adapter
-    messages = (GoogleGenAIAdapter()
-                .translate_generate_content_to_completion(model_name, contents)
-                .get("messages", []))
+    messages = (
+        GoogleGenAIAdapter()
+        .translate_generate_content_to_completion(model_name, contents)
+        .get("messages", [])
+    )
 
     token_request = TokenCountRequest(
         model=model_name,
@@ -209,7 +211,7 @@ async def google_count_tokens(request: Request, model_name: str):
                 totalTokens=token_response.total_tokens or 0,
                 promptTokensDetails=[],
             )
-    
+
     #########################################################
     # Return the response in the well known format
     #########################################################