[Frontend] Fix default_chat_template_kwargs handling in Responses API

docs/features/reasoning_outputs.md

@@ -240,9 +240,21 @@ response = client.chat.completions.create(
 )
 ```
 
+The same `chat_template_kwargs` override is also supported on the `/v1/responses`
+endpoint:
+
+```python
+response = client.responses.create(
+    model=model,
+    input="Compute 23 * 17 and explain briefly.",
+    reasoning={"effort": "low"},
+    extra_body={"chat_template_kwargs": {"enable_thinking": True}},
+)
+```
+
 ## Limitations
 
-- The reasoning content is only available for online serving's chat completion endpoint (`/v1/chat/completions`).
+- The reasoning content is only available for online serving's chat completion and responses endpoints (`/v1/chat/completions` and `/v1/responses`).
 
 ## How to support a new reasoning model
 

tests/entrypoints/openai/responses/test_chat_template_kwargs.py

@@ -0,0 +1,80 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import pytest
+import pytest_asyncio
+from openai import OpenAI
+
+from tests.utils import RemoteOpenAIServer
+
+from .conftest import BASE_TEST_ENV
+
+MODEL_NAME = "Qwen/Qwen3-0.6B"
+
+
+@pytest.fixture(scope="module")
+def server():
+    args = [
+        "--reasoning-parser",
+        "qwen3",
+        "--dtype",
+        "bfloat16",
+        "--enforce-eager",
+        "--max-model-len",
+        "4096",
+        "--default-chat-template-kwargs",
+        '{"enable_thinking": false}',
+    ]
+    env_dict = {
+        **BASE_TEST_ENV,
+        "VLLM_ENABLE_RESPONSES_API_STORE": "1",
+    }
+    with RemoteOpenAIServer(MODEL_NAME, args, env_dict=env_dict) as remote_server:
+        yield remote_server
+
+
+@pytest_asyncio.fixture
+async def client(server):
+    async with server.get_async_client() as async_client:
+        yield async_client
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+async def test_responses_honors_default_chat_template_kwargs(
+    client: OpenAI, model_name: str
+):
+    response = await client.responses.create(
+        model=model_name,
+        input="Compute 17 * 19 and explain briefly.",
+        reasoning={"effort": "low"},
+        temperature=0.0,
+    )
+
+    reasoning_items = [item for item in response.output if item.type == "reasoning"]
+
+    assert response.status == "completed"
+    assert response.output_text
+    assert not reasoning_items
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+async def test_responses_request_chat_template_kwargs_override_server_default(
+    client: OpenAI, model_name: str
+):
+    response = await client.responses.create(
+        model=model_name,
+        input="Compute 23 * 17 and explain briefly.",
+        reasoning={"effort": "low"},
+        temperature=0.0,
+        extra_body={"chat_template_kwargs": {"enable_thinking": True}},
+    )
+
+    reasoning_items = [item for item in response.output if item.type == "reasoning"]
+
+    assert response.status == "completed"
+    assert response.usage is not None
+    assert response.usage.output_tokens_details.reasoning_tokens > 0
+    assert reasoning_items
+    assert reasoning_items[0].content

tests/entrypoints/openai/responses/test_protocol.py

@@ -5,6 +5,7 @@
 )
 
 from vllm.entrypoints.openai.responses.protocol import (
+    ResponsesRequest,
     serialize_message,
     serialize_messages,
 )
@@ -37,3 +38,32 @@ def test_serialize_messages() -> None:
     }
     msg = Message.from_dict(msg_value)
     assert serialize_messages([msg, dict_value]) == [msg_value, dict_value]
+
+
+def test_responses_request_accepts_chat_template_kwargs() -> None:
+    request = ResponsesRequest(
+        input="Hello",
+        chat_template_kwargs={"enable_thinking": False},
+    )
+
+    assert request.chat_template_kwargs == {"enable_thinking": False}
+
+
+def test_build_chat_params_merges_responses_chat_template_kwargs() -> None:
+    request = ResponsesRequest(
+        input="Hello",
+        chat_template_kwargs={"enable_thinking": False},
+        reasoning={"effort": "low"},
+    )
+
+    chat_params = request.build_chat_params(
+        default_template=None,
+        default_template_content_format="auto",
+    )
+
+    assert chat_params.chat_template_kwargs == {
+        "enable_thinking": False,
+        "add_generation_prompt": True,
+        "continue_final_message": False,
+        "reasoning_effort": "low",
+    }

tests/entrypoints/openai/responses/test_serving_responses.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from contextlib import AsyncExitStack
-from unittest.mock import MagicMock
+from unittest.mock import AsyncMock, MagicMock
 
 import pytest
 import pytest_asyncio
@@ -619,6 +619,138 @@ def _make_serving_instance_with_reasoning():
     return serving
 
 
+@pytest.mark.asyncio
+async def test_make_request_passes_default_chat_template_kwargs():
+    engine_client = MagicMock()
+    model_config = MagicMock()
+    model_config.max_model_len = 100
+    model_config.hf_config.model_type = "test"
+    model_config.get_diff_sampling_param.return_value = {}
+    engine_client.model_config = model_config
+    engine_client.input_processor = MagicMock()
+    engine_client.io_processor = MagicMock()
+    engine_client.renderer = MagicMock()
+
+    openai_serving_render = MagicMock()
+    openai_serving_render.preprocess_chat = AsyncMock(return_value=([], [object()]))
+
+    serving = OpenAIServingResponses(
+        engine_client=engine_client,
+        models=MagicMock(),
+        openai_serving_render=openai_serving_render,
+        request_logger=None,
+        chat_template=None,
+        chat_template_content_format="auto",
+        default_chat_template_kwargs={"enable_thinking": False},
+    )
+
+    request = ResponsesRequest(
+        input="hi",
+        tools=[],
+        chat_template_kwargs={"enable_thinking": True},
+    )
+
+    await serving._make_request(request, None)
+
+    assert openai_serving_render.preprocess_chat.await_count == 1
+    assert openai_serving_render.preprocess_chat.await_args.kwargs[
+        "default_template_kwargs"
+    ] == {"enable_thinking": False}
+
+
+@pytest.mark.asyncio
+async def test_reasoning_parser_receives_merged_chat_template_kwargs():
+    serving = _make_serving_instance_with_reasoning()
+    serving.default_chat_template_kwargs = {"enable_thinking": False}
+
+    mock_parser = MagicMock()
+    mock_parser.count_reasoning_tokens.return_value = 0
+    serving.parser = MagicMock()
+    serving.parser.reasoning_parser_cls = MagicMock(return_value=mock_parser)
+    serving.parser.tool_parser_cls = None
+
+    tokenizer = MagicMock()
+    context = SimpleContext()
+    completion = CompletionOutput(
+        index=0,
+        text="final",
+        token_ids=[20],
+        cumulative_logprob=0.0,
+        logprobs=None,
+        finish_reason="stop",
+        stop_reason=None,
+    )
+    req_output = RequestOutput(
+        request_id="req",
+        prompt="hi",
+        prompt_token_ids=[7, 8],
+        prompt_logprobs=None,
+        outputs=[completion],
+        finished=True,
+        num_cached_tokens=0,
+    )
+    context.append_output(req_output)
+
+    async def dummy_result_generator():
+        yield None
+
+    request = ResponsesRequest(
+        input="hi",
+        tools=[],
+        stream=False,
+        chat_template_kwargs={"enable_thinking": True},
+    )
+    sampling_params = SamplingParams(max_tokens=16)
+    metadata = RequestResponseMetadata(request_id="req")
+
+    await serving.responses_full_generator(
+        request=request,
+        sampling_params=sampling_params,
+        result_generator=dummy_result_generator(),
+        context=context,
+        model_name="test-model",
+        tokenizer=tokenizer,
+        request_metadata=metadata,
+    )
+
+    serving.parser.reasoning_parser_cls.assert_called_once_with(
+        tokenizer,
+        chat_template_kwargs={"enable_thinking": True},
+    )
+
+
+def test_make_response_output_items_passes_merged_chat_template_kwargs():
+    serving = _make_serving_instance_with_reasoning()
+    serving.default_chat_template_kwargs = {"enable_thinking": False}
+
+    mock_parser = MagicMock()
+    mock_parser.extract_response_outputs.return_value = []
+    serving.parser = MagicMock(return_value=mock_parser)
+
+    request = ResponsesRequest(
+        input="hi",
+        tools=[],
+        chat_template_kwargs={"enable_thinking": True},
+    )
+    final_output = CompletionOutput(
+        index=0,
+        text="final",
+        token_ids=[20],
+        cumulative_logprob=0.0,
+        logprobs=None,
+        finish_reason="stop",
+        stop_reason=None,
+    )
+    tokenizer = MagicMock()
+
+    serving._make_response_output_items(request, final_output, tokenizer)
+
+    serving.parser.assert_called_once_with(
+        tokenizer,
+        chat_template_kwargs={"enable_thinking": True},
+    )
+
+
 def _identity_increment(event):
     """Simple identity callable for _increment_sequence_number_and_return."""
     seq = getattr(_identity_increment, "_counter", 0)

vllm/entrypoints/openai/generate/api_router.py

@@ -92,6 +92,7 @@ async def init_generate_state(
             enable_prompt_tokens_details=args.enable_prompt_tokens_details,
             enable_force_include_usage=args.enable_force_include_usage,
             enable_log_outputs=args.enable_log_outputs,
+            default_chat_template_kwargs=args.default_chat_template_kwargs,
         )
         if "generate" in supported_tasks
         else None

vllm/entrypoints/openai/parser/responses_parser.py

@@ -36,9 +36,10 @@ def __init__(
         self,
         *,
         tokenizer: TokenizerLike,
-        reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser],
+        reasoning_parser_cls: Callable[..., ReasoningParser],
         response_messages: list[ResponseInputOutputItem],
         request: ResponsesRequest,
+        chat_template_kwargs: dict | None,
         tool_parser_cls: Callable[[TokenizerLike], ToolParser] | None,
     ):
         self.response_messages: list[ResponseInputOutputItem] = (
@@ -49,7 +50,10 @@ def __init__(
         self.tokenizer = tokenizer
         self.request = request
 
-        self.reasoning_parser_instance = reasoning_parser_cls(tokenizer)
+        self.reasoning_parser_instance = reasoning_parser_cls(
+            tokenizer,
+            chat_template_kwargs=chat_template_kwargs,
+        )
         self.tool_parser_instance = None
         if tool_parser_cls is not None:
             self.tool_parser_instance = tool_parser_cls(tokenizer)
@@ -159,9 +163,10 @@ def make_response_output_items_from_parsable_context(
 def get_responses_parser_for_simple_context(
     *,
     tokenizer: TokenizerLike,
-    reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser],
+    reasoning_parser_cls: Callable[..., ReasoningParser],
     response_messages: list[ResponseInputOutputItem],
     request: ResponsesRequest,
+    chat_template_kwargs: dict | None,
     tool_parser_cls,
 ) -> ResponsesParser:
     """Factory function to create a ResponsesParser with
@@ -175,5 +180,6 @@ def get_responses_parser_for_simple_context(
         reasoning_parser_cls=reasoning_parser_cls,
         response_messages=response_messages,
         request=request,
+        chat_template_kwargs=chat_template_kwargs,
         tool_parser_cls=tool_parser_cls,
     )

vllm/entrypoints/openai/responses/context.py

@@ -273,8 +273,9 @@ def __init__(
         *,
         response_messages: list[ResponseInputOutputItem],
         tokenizer: TokenizerLike,
-        reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser] | None,
+        reasoning_parser_cls: Callable[..., ReasoningParser] | None,
         request: ResponsesRequest,
+        chat_template_kwargs: dict[str, Any] | None,
         available_tools: list[str] | None,
         tool_parser_cls: Callable[[TokenizerLike], ToolParser] | None,
         chat_template: str | None,
@@ -295,6 +296,7 @@ def __init__(
             reasoning_parser_cls=reasoning_parser_cls,
             response_messages=response_messages,
             request=request,
+            chat_template_kwargs=chat_template_kwargs,
             tool_parser_cls=tool_parser_cls,
         )
         self.tool_parser_cls = tool_parser_cls

vllm/entrypoints/openai/responses/protocol.py

@@ -181,6 +181,13 @@ class ResponsesRequest(OpenAIBaseModel):
             "and vLLM will ignore it."
         ),
     )
+    chat_template_kwargs: dict[str, Any] | None = Field(
+        default=None,
+        description=(
+            "Additional keyword args to pass to the template renderer. "
+            "Will be accessible by the chat template."
+        ),
+    )
 
     # --8<-- [start:responses-extra-params]
     request_id: str = Field(
@@ -276,7 +283,7 @@ def build_chat_params(
             chat_template=default_template,
             chat_template_content_format=default_template_content_format,
             chat_template_kwargs=merge_kwargs(  # To remove unset values
-                {},
+                self.chat_template_kwargs,
                 dict(
                     add_generation_prompt=not continue_final,
                     continue_final_message=continue_final,