[Misc] Clean up flags in vllm bench serve

docs/contributing/benchmarks.md

@@ -156,7 +156,6 @@ vllm serve Qwen/Qwen2-VL-7B-Instruct
 ```bash
 vllm bench serve \
   --backend openai-chat \
-  --endpoint-type openai-chat \
   --model Qwen/Qwen2-VL-7B-Instruct \
   --endpoint /v1/chat/completions \
   --dataset-name hf \
@@ -230,7 +229,6 @@ vllm serve Qwen/Qwen2-VL-7B-Instruct
 ```bash
 vllm bench serve \
   --backend openai-chat \
-  --endpoint-type openai-chat \
   --model Qwen/Qwen2-VL-7B-Instruct \
   --endpoint /v1/chat/completions \
   --dataset-name hf \
@@ -245,7 +243,6 @@ vllm bench serve \
 ```bash
 vllm bench serve \
   --backend openai-chat \
-  --endpoint-type openai-chat \
   --model Qwen/Qwen2-VL-7B-Instruct \
   --endpoint /v1/chat/completions \
   --dataset-name hf \

tests/benchmarks/test_serve_cli.py

@@ -68,7 +68,7 @@ def test_bench_serve_chat(server):
         "5",
         "--endpoint",
         "/v1/chat/completions",
-        "--endpoint-type",
+        "--backend",
         "openai-chat",
     ]
     result = subprocess.run(command, capture_output=True, text=True)

vllm/benchmarks/datasets.py

@@ -1357,7 +1357,7 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
     elif args.dataset_name == "sonnet":
         dataset = SonnetDataset(dataset_path=args.dataset_path)
         # For the "sonnet" dataset, formatting depends on the backend.
-        if args.endpoint_type == "openai-chat":
+        if args.backend == "openai-chat":
             input_requests = dataset.sample(
                 num_requests=args.num_prompts,
                 input_len=args.sonnet_input_len,
@@ -1461,15 +1461,15 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
                 "Please consider contributing if you would "
                 "like to add support for additional dataset formats.")
 
-        if dataset_class.IS_MULTIMODAL and args.endpoint_type not in [
+        if dataset_class.IS_MULTIMODAL and args.backend not in [
                 "openai-chat",
                 "openai-audio",
         ]:
             # multi-modal benchmark is only available on OpenAI Chat
             # endpoint-type.
             raise ValueError(
                 "Multi-modal content is only supported on 'openai-chat' and "
-                "'openai-audio' endpoint-type.")
+                "'openai-audio' backends.")
         input_requests = dataset_class(
             dataset_path=args.dataset_path,
             dataset_subset=args.hf_subset,
@@ -1562,7 +1562,7 @@ def get_samples(args, tokenizer) -> list[SampleRequest]:
 
         try:
             # Enforce endpoint compatibility for multimodal datasets.
-            if args.dataset_name == "random-mm" and args.endpoint_type not in [
+            if args.dataset_name == "random-mm" and args.backend not in [
                     "openai-chat"]:
                 raise ValueError(
                     "Multi-modal content (images) is only supported on "

vllm/benchmarks/serve.py

@@ -8,8 +8,8 @@
 
 On the client side, run:
     vllm bench serve \
-        --endpoint-type <endpoint_type. Default 'openai'> \
-        --label <benchmark result label. Default using endpoint_type> \
+        --backend <backend or endpoint type. Default 'openai'> \
+        --label <benchmark result label. Default using backend> \
         --model <your_model> \
         --dataset-name <dataset_name. Default 'random'> \
         --request-rate <request_rate. Default inf> \
@@ -52,6 +52,21 @@
                           and (shutil.which("gnuplot") is not None))
 
 
+# TODO: Remove this in v0.11.0
+class DeprecatedEndpointTypeAction(argparse.Action):
+    """Argparse action for the deprecated --endpoint-type flag.
+    """
+
+    def __call__(self, _, namespace, values, option_string=None):
+        warnings.warn(
+            "'--endpoint-type' is deprecated and will be removed in v0.11.0. "
+            "Please use '--backend' instead or remove this argument if you "
+            "have already set it.",
+            stacklevel=1,
+        )
+        setattr(namespace, self.dest, values)
+
+
 class TaskType(Enum):
     GENERATION = "generation"
     EMBEDDING = "embedding"
@@ -470,7 +485,7 @@ async def benchmark(
         else:
             request_func = ASYNC_REQUEST_FUNCS[endpoint_type]
     else:
-        raise ValueError(f"Unknown endpoint_type: {endpoint_type}")
+        raise ValueError(f"Unknown backend: {endpoint_type}")
 
     # Reuses connections across requests to reduce TLS handshake overhead.
     connector = aiohttp.TCPConnector(
@@ -850,24 +865,28 @@ def save_to_pytorch_benchmark_format(args: argparse.Namespace,
 
 def add_cli_args(parser: argparse.ArgumentParser):
     add_dataset_parser(parser)
-    parser.add_argument(
-        "--endpoint-type",
-        type=str,
-        default="openai",
-        choices=list(ASYNC_REQUEST_FUNCS.keys()),
-    )
     parser.add_argument(
         "--label",
         type=str,
         default=None,
         help="The label (prefix) of the benchmark results. If not specified, "
-        "the endpoint type will be used as the label.",
+        "the value of '--backend' will be used as the label.",
     )
     parser.add_argument(
         "--backend",
         type=str,
-        default="vllm",
+        default="openai",
+        choices=list(ASYNC_REQUEST_FUNCS.keys()),
+        help="The type of backend or endpoint to use for the benchmark."
+    )
+    parser.add_argument(
+        "--endpoint-type",
+        type=str,
+        default=None,
         choices=list(ASYNC_REQUEST_FUNCS.keys()),
+        action=DeprecatedEndpointTypeAction,
+        help="'--endpoint-type' is deprecated and will be removed in v0.11.0. "
+        "Please use '--backend' instead.",
     )
     parser.add_argument(
         "--base-url",
@@ -1165,7 +1184,6 @@ async def main_async(args: argparse.Namespace) -> dict[str, Any]:
             raise ValueError(
                 "For exponential ramp-up, the start RPS cannot be 0.")
 
-    endpoint_type = args.endpoint_type
     label = args.label
     model_id = args.model
     model_name = args.served_model_name
@@ -1228,7 +1246,7 @@ async def main_async(args: argparse.Namespace) -> dict[str, Any]:
     gc.freeze()
 
     benchmark_result = await benchmark(
-        endpoint_type=args.endpoint_type,
+        endpoint_type=args.backend,
         api_url=api_url,
         base_url=base_url,
         model_id=model_id,
@@ -1262,7 +1280,8 @@ async def main_async(args: argparse.Namespace) -> dict[str, Any]:
     # Setup
     current_dt = datetime.now().strftime("%Y%m%d-%H%M%S")
     result_json["date"] = current_dt
-    result_json["endpoint_type"] = args.endpoint_type
+    result_json["endpoint_type"] = args.backend # for backward compatibility
+    result_json["backend"] = args.backend
     result_json["label"] = label
     result_json["model_id"] = model_id
     result_json["tokenizer_id"] = tokenizer_id
@@ -1312,7 +1331,7 @@ async def main_async(args: argparse.Namespace) -> dict[str, Any]:
         base_model_id = model_id.split("/")[-1]
         max_concurrency_str = (f"-concurrency{args.max_concurrency}"
                                if args.max_concurrency is not None else "")
-        label = label or endpoint_type
+        label = label or args.backend
         if args.ramp_up_strategy is not None:
             file_name = f"{label}-ramp-up-{args.ramp_up_strategy}-{args.ramp_up_start_rps}qps-{args.ramp_up_end_rps}qps{max_concurrency_str}-{base_model_id}-{current_dt}.json"  # noqa
         else: