[Feat][CLI] enforce-include-usage

vllm/entrypoints/openai/api_server.py

@@ -1190,13 +1190,15 @@ async def init_app_state(
         tool_parser=args.tool_call_parser,
         reasoning_parser=args.reasoning_parser,
         enable_prompt_tokens_details=args.enable_prompt_tokens_details,
+        enable_force_include_usage=args.enable_force_include_usage,
     ) if model_config.runner_type == "generate" else None
     state.openai_serving_completion = OpenAIServingCompletion(
         engine_client,
         model_config,
         state.openai_serving_models,
         request_logger=request_logger,
         return_tokens_as_token_ids=args.return_tokens_as_token_ids,
+        enable_force_include_usage=args.enable_force_include_usage,
     ) if model_config.runner_type == "generate" else None
     state.openai_serving_pooling = OpenAIServingPooling(
         engine_client,

vllm/entrypoints/openai/cli_args.py

@@ -272,6 +272,11 @@ def make_arg_parser(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
         action='store_true',
         default=False,
         help="If set to True, enable prompt_tokens_details in usage.")
+    parser.add_argument(
+        "--enable-force-include-usage",
+        action='store_true',
+        default=False,
+        help="If set to True, including usage on every request.")
     parser.add_argument(
         "--enable-server-load-tracking",
         action='store_true',

vllm/entrypoints/openai/serving_chat.py

@@ -64,12 +64,14 @@ def __init__(
         enable_auto_tools: bool = False,
         tool_parser: Optional[str] = None,
         enable_prompt_tokens_details: bool = False,
+        enable_force_include_usage: bool = False,
     ) -> None:
         super().__init__(engine_client=engine_client,
                          model_config=model_config,
                          models=models,
                          request_logger=request_logger,
-                         return_tokens_as_token_ids=return_tokens_as_token_ids)
+                         return_tokens_as_token_ids=return_tokens_as_token_ids,
+                         enable_force_include_usage=enable_force_include_usage)
 
         self.response_role = response_role
         self.chat_template = chat_template
@@ -110,6 +112,7 @@ def __init__(
                                 "been registered") from e
 
         self.enable_prompt_tokens_details = enable_prompt_tokens_details
+        self.enable_force_include_usage = enable_force_include_usage
         self.default_sampling_params = (
             self.model_config.get_diff_sampling_param())
         if self.default_sampling_params:
@@ -261,8 +264,14 @@ async def create_chat_completion(
         # Streaming response
         if request.stream:
             return self.chat_completion_stream_generator(
-                request, result_generator, request_id, model_name,
-                conversation, tokenizer, request_metadata)
+                request,
+                result_generator,
+                request_id,
+                model_name,
+                conversation,
+                tokenizer,
+                request_metadata,
+                enable_force_include_usage=self.enable_force_include_usage)
 
         try:
             return await self.chat_completion_full_generator(
@@ -405,6 +414,7 @@ async def chat_completion_stream_generator(
         conversation: list[ConversationMessage],
         tokenizer: AnyTokenizer,
         request_metadata: RequestResponseMetadata,
+        enable_force_include_usage: bool,
     ) -> AsyncGenerator[str, None]:
         created_time = int(time.time())
         chunk_object_type: Final = "chat.completion.chunk"
@@ -471,7 +481,8 @@ async def chat_completion_stream_generator(
 
         stream_options = request.stream_options
         if stream_options:
-            include_usage = stream_options.include_usage
+            include_usage = stream_options.include_usage \
+                            or enable_force_include_usage
             include_continuous_usage = include_usage and \
                                        stream_options.continuous_usage_stats
         else:

vllm/entrypoints/openai/serving_completion.py

@@ -52,12 +52,14 @@ def __init__(
         *,
         request_logger: Optional[RequestLogger],
         return_tokens_as_token_ids: bool = False,
+        enable_force_include_usage: bool = False,
     ):
         super().__init__(engine_client=engine_client,
                          model_config=model_config,
                          models=models,
                          request_logger=request_logger,
-                         return_tokens_as_token_ids=return_tokens_as_token_ids)
+                         return_tokens_as_token_ids=return_tokens_as_token_ids,
+                         enable_force_include_usage=enable_force_include_usage)
         self.default_sampling_params = (
             self.model_config.get_diff_sampling_param())
         if self.default_sampling_params:
@@ -227,7 +229,8 @@ async def create_completion(
                 model_name,
                 num_prompts=num_prompts,
                 tokenizer=tokenizer,
-                request_metadata=request_metadata)
+                request_metadata=request_metadata,
+                enable_force_include_usage=self.enable_force_include_usage)
 
         # Non-streaming response
         final_res_batch: list[Optional[RequestOutput]] = [None] * num_prompts
@@ -289,6 +292,7 @@ async def completion_stream_generator(
         num_prompts: int,
         tokenizer: AnyTokenizer,
         request_metadata: RequestResponseMetadata,
+        enable_force_include_usage: bool,
     ) -> AsyncGenerator[str, None]:
         num_choices = 1 if request.n is None else request.n
         previous_text_lens = [0] * num_choices * num_prompts
@@ -298,7 +302,8 @@ async def completion_stream_generator(
 
         stream_options = request.stream_options
         if stream_options:
-            include_usage = stream_options.include_usage
+            include_usage = stream_options.include_usage or \
+                            enable_force_include_usage
             include_continuous_usage = include_usage and \
                                        stream_options.continuous_usage_stats
         else:

vllm/entrypoints/openai/serving_engine.py

@@ -132,7 +132,7 @@ def is_embeds_prompt(prompt: RequestPrompt) -> TypeIs[EmbedsPrompt]:
 
 class RequestProcessingMixin(BaseModel):
     """
-    Mixin for request processing, 
+    Mixin for request processing,
     handling prompt preparation and engine input.
     """
     request_prompts: Optional[Sequence[RequestPrompt]] = []
@@ -144,7 +144,7 @@ class RequestProcessingMixin(BaseModel):
 
 class ResponseGenerationMixin(BaseModel):
     """
-    Mixin for response generation, 
+    Mixin for response generation,
     managing result generators and final batch results.
     """
     result_generator: Optional[AsyncGenerator[tuple[int, Union[
@@ -208,6 +208,7 @@ def __init__(
         *,
         request_logger: Optional[RequestLogger],
         return_tokens_as_token_ids: bool = False,
+        enable_force_include_usage: bool = False,
     ):
         super().__init__()
 
@@ -219,6 +220,7 @@ def __init__(
 
         self.request_logger = request_logger
         self.return_tokens_as_token_ids = return_tokens_as_token_ids
+        self.enable_force_include_usage = enable_force_include_usage
 
         self._tokenizer_executor = ThreadPoolExecutor(max_workers=1)