[Bugfix] Pass effective chat template kwargs to reasoning parsers (vllm-project#40460)

Signed-off-by: Bugen Zhao <i@bugenzhao.com>

Author: BugenZhao

vllm/entrypoints/openai/chat_completion/batch_serving.py

@@ -114,12 +114,15 @@ async def create_batch_chat_completion(
         """
         tokenizer = self.renderer.tokenizer
         assert tokenizer is not None
+        single_requests = [
+            request.to_chat_completion_request(messages)
+            for messages in request.messages
+        ]
 
         reasoning_parser: ReasoningParser | None = None
         if self.reasoning_parser_cls:
-            chat_template_kwargs = self._prepare_extra_chat_template_kwargs(
-                request.chat_template_kwargs,
-                self.default_chat_template_kwargs,
+            chat_template_kwargs = self._effective_chat_template_kwargs(
+                single_requests[0]
             )
             reasoning_parser = self.reasoning_parser_cls(
                 tokenizer,
@@ -155,7 +158,7 @@ async def create_batch_chat_completion(
                 self.default_sampling_params,
                 self.override_max_tokens,
             )
-            single_request = request.to_chat_completion_request(request.messages[i])
+            single_request = single_requests[i]
             sampling_params = single_request.to_sampling_params(
                 max_tokens, self.default_sampling_params
             )

vllm/entrypoints/openai/chat_completion/serving.py

@@ -189,6 +189,18 @@ def warmup(self) -> None:
             )
         )
 
+    def _effective_chat_template_kwargs(
+        self, request: ChatCompletionRequest
+    ) -> dict[str, Any]:
+        return (
+            request.build_chat_params(
+                self.chat_template,
+                self.chat_template_content_format,
+            )
+            .with_defaults(self.default_chat_template_kwargs)
+            .chat_template_kwargs
+        )
+
     async def render_chat_request(
         self,
         request: ChatCompletionRequest,
@@ -231,10 +243,7 @@ async def create_chat_completion(
         # Streaming response
         tokenizer = self.renderer.tokenizer
         assert tokenizer is not None
-        chat_template_kwargs = self._prepare_extra_chat_template_kwargs(
-            request.chat_template_kwargs,
-            self.default_chat_template_kwargs,
-        )
+        chat_template_kwargs = self._effective_chat_template_kwargs(request)
         reasoning_parser: ReasoningParser | None = None
         if self.reasoning_parser_cls:
             reasoning_parser = self.reasoning_parser_cls(

vllm/entrypoints/openai/parser/responses_parser.py

@@ -1,7 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import logging
-from collections.abc import Callable
+from typing import Any
 
 from openai.types.responses import ResponseFunctionToolCall, ResponseOutputItem
 from openai.types.responses.response_function_tool_call_output_item import (
@@ -15,6 +15,7 @@
     ResponseReasoningItem,
 )
 
+from vllm.entrypoints.chat_utils import ChatTemplateContentFormatOption
 from vllm.entrypoints.constants import MCP_PREFIX
 from vllm.entrypoints.openai.responses.protocol import (
     ResponseInputOutputItem,
@@ -36,10 +37,12 @@ def __init__(
         self,
         *,
         tokenizer: TokenizerLike,
-        reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser],
+        reasoning_parser_cls: type[ReasoningParser],
         response_messages: list[ResponseInputOutputItem],
         request: ResponsesRequest,
         tool_parser_cls: type[ToolParser] | None,
+        chat_template: str | None,
+        chat_template_content_format: ChatTemplateContentFormatOption,
     ):
         self.response_messages: list[ResponseInputOutputItem] = (
             # TODO: initial messages may not be properly typed
@@ -49,7 +52,14 @@ 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=_effective_chat_template_kwargs(
+                request,
+                chat_template=chat_template,
+                chat_template_content_format=chat_template_content_format,
+            ),
+        )
         self.tool_parser_instance = None
         if tool_parser_cls is not None:
             self.tool_parser_instance = tool_parser_cls(tokenizer, request.tools)
@@ -159,10 +169,12 @@ 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: type[ReasoningParser],
     response_messages: list[ResponseInputOutputItem],
     request: ResponsesRequest,
     tool_parser_cls,
+    chat_template: str | None,
+    chat_template_content_format: ChatTemplateContentFormatOption,
 ) -> ResponsesParser:
     """Factory function to create a ResponsesParser with
     optional reasoning parser.
@@ -176,4 +188,17 @@ def get_responses_parser_for_simple_context(
         response_messages=response_messages,
         request=request,
         tool_parser_cls=tool_parser_cls,
+        chat_template=chat_template,
+        chat_template_content_format=chat_template_content_format,
     )
+
+
+def _effective_chat_template_kwargs(
+    request: ResponsesRequest,
+    chat_template: str | None,
+    chat_template_content_format: ChatTemplateContentFormatOption,
+) -> dict[str, Any]:
+    return request.build_chat_params(
+        default_template=chat_template,
+        default_template_content_format=chat_template_content_format,
+    ).chat_template_kwargs

vllm/entrypoints/openai/responses/context.py

@@ -6,7 +6,6 @@
 import json
 import logging
 from abc import ABC, abstractmethod
-from collections.abc import Callable
 from contextlib import AsyncExitStack
 from dataclasses import replace
 from typing import TYPE_CHECKING, Any, Final, Union
@@ -273,7 +272,7 @@ def __init__(
         *,
         response_messages: list[ResponseInputOutputItem],
         tokenizer: TokenizerLike,
-        reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser] | None,
+        reasoning_parser_cls: type[ReasoningParser] | None,
         request: ResponsesRequest,
         available_tools: list[str] | None,
         tool_parser_cls: type[ToolParser] | None,
@@ -296,6 +295,8 @@ def __init__(
             response_messages=response_messages,
             request=request,
             tool_parser_cls=tool_parser_cls,
+            chat_template=chat_template,
+            chat_template_content_format=chat_template_content_format,
         )
         self.tool_parser_cls = tool_parser_cls
         self.request = request

vllm/entrypoints/openai/responses/serving.py

@@ -267,6 +267,14 @@ def __init__(
 
         self.tool_server = tool_server
 
+    def _effective_chat_template_kwargs(
+        self, request: ResponsesRequest
+    ) -> dict[str, Any]:
+        return request.build_chat_params(
+            self.chat_template,
+            self.chat_template_content_format,
+        ).chat_template_kwargs
+
     def _validate_generator_input(
         self,
         engine_input: EngineInput,
@@ -464,7 +472,10 @@ async def create_responses(
                     context = SimpleContext()
 
             if self.parser and self.parser.reasoning_parser_cls is not None:
-                reasoning_parser = self.parser.reasoning_parser_cls(tokenizer)
+                reasoning_parser = self.parser.reasoning_parser_cls(
+                    tokenizer,
+                    chat_template_kwargs=self._effective_chat_template_kwargs(request),
+                )
                 if (
                     isinstance(
                         struct_out := sampling_params.structured_outputs,
@@ -835,7 +846,10 @@ async def responses_full_generator(
             and self.parser.reasoning_parser_cls is not None
             and isinstance(context, (SimpleContext, ParsableContext))
         ):
-            reasoning_parser = self.parser.reasoning_parser_cls(tokenizer)
+            reasoning_parser = self.parser.reasoning_parser_cls(
+                tokenizer,
+                chat_template_kwargs=self._effective_chat_template_kwargs(request),
+            )
             accumulated = getattr(context, "_accumulated_token_ids", []) or []
             num_reasoning_tokens = reasoning_parser.count_reasoning_tokens(accumulated)
 

vllm/entrypoints/serve/render/serving.py

@@ -566,7 +566,9 @@ async def preprocess_chat(
         if reasoning_parser is not None:
             tokenizer = renderer.get_tokenizer()
             request = reasoning_parser(
-                tokenizer, model_config=self.model_config
+                tokenizer,
+                model_config=self.model_config,
+                chat_template_kwargs=chat_params.chat_template_kwargs,
             ).adjust_request(request=request)
 
         # tool parsing is done only if a tool_parser has been set and if