style(proxy): format anthropic messages hook fix

litellm/llms/anthropic/experimental_pass_through/messages/handler.py

@@ -128,7 +128,8 @@ async def _execute_pre_request_hooks(
 
         if (
             "async_pre_call_hook" in vars(callback.__class__)
-            and callback.__class__.async_pre_call_hook != _CustomLogger.async_pre_call_hook
+            and callback.__class__.async_pre_call_hook
+            != _CustomLogger.async_pre_call_hook
         ):
             # Keep the experimental Messages path in parity with the proxy
             # pre-call hook contract used by the standard /v1/messages path.
@@ -233,7 +234,9 @@ async def anthropic_messages(
     """
     Async: Make llm api request in Anthropic /messages API spec
     """
-    original_stream = stream or kwargs.get("_websearch_interception_converted_stream", False)
+    original_stream = stream or kwargs.get(
+        "_websearch_interception_converted_stream", False
+    )
 
     # Execute pre-request hooks to allow CustomLoggers to modify request
     request_kwargs = await _execute_pre_request_hooks(
@@ -272,7 +275,9 @@ async def anthropic_messages(
     # The litellm_params dict may have been overwritten by **kwargs in
     # _execute_pre_request_hooks, so fall back to get_llm_provider() if needed.
     if not custom_llm_provider:
-        custom_llm_provider = request_kwargs.get("litellm_params", {}).get("custom_llm_provider")
+        custom_llm_provider = request_kwargs.get("litellm_params", {}).get(
+            "custom_llm_provider"
+        )
         if not custom_llm_provider:
             try:
                 _, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
@@ -435,7 +440,9 @@ def anthropic_messages_handler(
         # Check if stream was converted for WebSearch interception
         # This is set in the async wrapper above when stream=True is converted to stream=False
         if kwargs.get("_websearch_interception_converted_stream", False):
-            litellm_logging_obj.model_call_details["websearch_interception_converted_stream"] = True
+            litellm_logging_obj.model_call_details[
+                "websearch_interception_converted_stream"
+            ] = True
 
     if litellm_params.mock_response and isinstance(litellm_params.mock_response, str):
         return mock_response(
@@ -447,10 +454,14 @@ def anthropic_messages_handler(
 
     anthropic_messages_provider_config: Optional[BaseAnthropicMessagesConfig] = None
 
-    if custom_llm_provider is not None and custom_llm_provider in [provider.value for provider in LlmProviders]:
-        anthropic_messages_provider_config = ProviderConfigManager.get_provider_anthropic_messages_config(
-            model=model,
-            provider=litellm.LlmProviders(custom_llm_provider),
+    if custom_llm_provider is not None and custom_llm_provider in [
+        provider.value for provider in LlmProviders
+    ]:
+        anthropic_messages_provider_config = (
+            ProviderConfigManager.get_provider_anthropic_messages_config(
+                model=model,
+                provider=litellm.LlmProviders(custom_llm_provider),
+            )
         )
     if anthropic_messages_provider_config is None:
         # Route to Responses API for OpenAI / Azure, chat/completions for everything else.
@@ -476,8 +487,14 @@ def anthropic_messages_handler(
             **kwargs,
         )
         if _should_route_to_responses_api(custom_llm_provider):
-            return LiteLLMMessagesToResponsesAPIHandler.anthropic_messages_handler(**_shared_kwargs)
-        return LiteLLMMessagesToCompletionTransformationHandler.anthropic_messages_handler(**_shared_kwargs)
+            return LiteLLMMessagesToResponsesAPIHandler.anthropic_messages_handler(
+                **_shared_kwargs
+            )
+        return (
+            LiteLLMMessagesToCompletionTransformationHandler.anthropic_messages_handler(
+                **_shared_kwargs
+            )
+        )
 
     if custom_llm_provider is None:
         raise ValueError(
@@ -486,11 +503,16 @@ def anthropic_messages_handler(
 
     local_vars.update(kwargs)
     anthropic_messages_optional_request_params = (
-        AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param(params=local_vars)
+        AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param(
+            params=local_vars
+        )
     )
     if is_reasoning_auto_summary_enabled():
         thinking_param = anthropic_messages_optional_request_params.get("thinking")
-        if isinstance(thinking_param, dict) and thinking_param.get("type") != "disabled":
+        if (
+            isinstance(thinking_param, dict)
+            and thinking_param.get("type") != "disabled"
+        ):
             anthropic_messages_optional_request_params["thinking"] = {
                 **thinking_param,
                 "display": "summarized",
@@ -500,7 +522,9 @@ def anthropic_messages_handler(
         model=model,
         messages=messages,
         anthropic_messages_provider_config=anthropic_messages_provider_config,
-        anthropic_messages_optional_request_params=dict(anthropic_messages_optional_request_params),
+        anthropic_messages_optional_request_params=dict(
+            anthropic_messages_optional_request_params
+        ),
         _is_async=is_async,
         client=client,
         custom_llm_provider=custom_llm_provider,

tests/proxy_unit_tests/test_anthropic_messages_pre_call_hook.py

@@ -50,11 +50,15 @@ def client_no_auth(fake_env_vars):
 
 
 @mock_patch_anthropic_messages()
-def test_anthropic_messages_runs_proxy_async_pre_call_hook(mock_anthropic_messages, client_no_auth):
+def test_anthropic_messages_runs_proxy_async_pre_call_hook(
+    mock_anthropic_messages, client_no_auth
+):
     hook_calls = []
 
     class AnthropicMessagesPreCallHook(CustomLogger):
-        async def async_pre_call_hook(self, user_api_key_dict, cache, data, call_type, **kwargs):
+        async def async_pre_call_hook(
+            self, user_api_key_dict, cache, data, call_type, **kwargs
+        ):
             hook_calls.append(call_type)
             data["metadata"] = {**(data.get("metadata") or {}), "source": "unit-test"}
             return data
@@ -76,7 +80,10 @@ def test_anthropic_messages_runs_proxy_async_pre_call_hook(mock_anthropic_messag
         assert response.json()["content"][0]["text"] == "Hello from LiteLLM"
         assert hook_calls == ["anthropic_messages"]
         mock_anthropic_messages.assert_called_once()
-        assert mock_anthropic_messages.call_args.kwargs["metadata"]["source"] == "unit-test"
+        assert (
+            mock_anthropic_messages.call_args.kwargs["metadata"]["source"]
+            == "unit-test"
+        )
     finally:
         litellm.callbacks = original_callbacks
 
@@ -90,7 +97,9 @@ async def test_experimental_anthropic_messages_runs_proxy_async_pre_call_hook():
     hook_calls = []
 
     class AnthropicMessagesPreCallHook(CustomLogger):
-        async def async_pre_call_hook(self, user_api_key_dict, cache, data, call_type, **kwargs):
+        async def async_pre_call_hook(
+            self, user_api_key_dict, cache, data, call_type, **kwargs
+        ):
             hook_calls.append((call_type, data["model"]))
             data["metadata"] = {
                 **(data.get("metadata") or {}),