diff --git a/tests/test_config.py b/tests/test_config.py
index c45cbb367326c..dc1cddd45c34e 100644
--- a/tests/test_config.py
+++ b/tests/test_config.py
@@ -35,7 +35,7 @@ def test_ambiguous_task(model_id):
             seed=0,
             dtype="float16",
         )
-    
+
 
 MODEL_IDS_EXPECTED = [
     ("Qwen/Qwen1.5-7B", 32768),
diff --git a/vllm/config.py b/vllm/config.py
index 8efa48483765a..b04bcf9be8c06 100644
--- a/vllm/config.py
+++ b/vllm/config.py
@@ -33,7 +33,6 @@
 _EMBEDDING_MODEL_MAX_NUM_BATCHED_TOKENS = 32768
 _MULTIMODAL_MODEL_MAX_NUM_BATCHED_TOKENS = 5120
 
-
 Task = Literal["generate", "embed"]
 TaskOption = Literal["auto", Task]
 
@@ -264,22 +263,25 @@ def _resolve_task(
             "embed": ModelRegistry.is_embedding_model(architectures)
         }
         supported_tasks: Set[Task] = {
-            task for task, is_supported in task_support.items() if is_supported
+            task
+            for task, is_supported in task_support.items() if is_supported
         }
 
         if task_option == "auto":
             if len(supported_tasks) > 1:
-                msg = (f"This model supports multiple tasks: {supported_tasks}."
-                       " Please specify one explicitly via `--task`.")
+                msg = (
+                    f"This model supports multiple tasks: {supported_tasks}."
+                    " Please specify one explicitly via `--task`.")
                 raise ValueError(msg)
-            
+
             task = next(iter(supported_tasks))
         else:
             if task_option not in supported_tasks:
-                msg = (f"This model does not support the '{task_option}' task. "
-                       f"Supported tasks: {supported_tasks}")
+                msg = (
+                    f"This model does not support the '{task_option}' task. "
+                    f"Supported tasks: {supported_tasks}")
                 raise ValueError(msg)
-            
+
             task = task_option
 
         return task
diff --git a/vllm/engine/arg_utils.py b/vllm/engine/arg_utils.py
index 16f7a106bc1c8..ba2fec65a4762 100644
--- a/vllm/engine/arg_utils.py
+++ b/vllm/engine/arg_utils.py
@@ -10,10 +10,9 @@
 import vllm.envs as envs
 from vllm.config import (CacheConfig, ConfigFormat, DecodingConfig,
                          DeviceConfig, EngineConfig, LoadConfig, LoadFormat,
-                         LoRAConfig, ModelConfig, TaskOption,
-                         ObservabilityConfig, ParallelConfig,
-                         PromptAdapterConfig, SchedulerConfig,
-                         SpeculativeConfig, TokenizerPoolConfig)
+                         LoRAConfig, ModelConfig, ObservabilityConfig,
+                         ParallelConfig, PromptAdapterConfig, SchedulerConfig,
+                         SpeculativeConfig, TaskOption, TokenizerPoolConfig)
 from vllm.executor.executor_base import ExecutorBase
 from vllm.logger import init_logger
 from vllm.model_executor.layers.quantization import QUANTIZATION_METHODS
diff --git a/vllm/entrypoints/openai/serving_embedding.py b/vllm/entrypoints/openai/serving_embedding.py
index 4cdb7ac745d8a..00cfaae6bc83d 100644
--- a/vllm/entrypoints/openai/serving_embedding.py
+++ b/vllm/entrypoints/openai/serving_embedding.py
@@ -83,7 +83,8 @@ def __init__(
                          lora_modules=None,
                          prompt_adapters=None,
                          request_logger=request_logger)
-        self._enabled = self._check_embedding_mode(model_config.task == "embed")
+        self._enabled = self._check_embedding_mode(
+            model_config.task == "embed")
 
     async def create_embedding(
         self,