[Tool Parser][1/3] Pass tools to ToolParser constructor

vllm/entrypoints/openai/chat_completion/serving.py

@@ -565,7 +565,7 @@ async def chat_completion_stream_generator(
                     )
 
                 tool_parsers: list[ToolParser | None] = [
-                    self.tool_parser(tokenizer)
+                    self.tool_parser(tokenizer, request.tools)
                 ] * num_choices
             else:
                 tool_parsers = [None] * num_choices
@@ -1331,7 +1331,7 @@ async def chat_completion_full_generator(
                             "Tokenizer not available when `skip_tokenizer_init=True`"
                         )
 
-                    tool_parser = self.tool_parser(tokenizer)
+                    tool_parser = self.tool_parser(tokenizer, request.tools)
                     # NOTE: We use token_ids for openai tool parser
                     tool_call_info = tool_parser.extract_tool_calls(
                         "",

vllm/entrypoints/openai/engine/serving.py

@@ -929,7 +929,7 @@ def _parse_tool_calls_from_content(
 
             # Automatic Tool Call Parsing
             try:
-                tool_parser = tool_parser_cls(tokenizer)
+                tool_parser = tool_parser_cls(tokenizer, request.tools)
             except RuntimeError as e:
                 logger.exception("Error in tool parser creation.")
                 raise e

vllm/entrypoints/openai/parser/responses_parser.py

@@ -52,7 +52,7 @@ def __init__(
         self.reasoning_parser_instance = reasoning_parser_cls(tokenizer)
         self.tool_parser_instance = None
         if tool_parser_cls is not None:
-            self.tool_parser_instance = tool_parser_cls(tokenizer)
+            self.tool_parser_instance = tool_parser_cls(tokenizer, request.tools)
 
         # Store the last finish_reason to determine response status
         self.finish_reason: str | None = None

vllm/entrypoints/openai/responses/serving.py

@@ -1348,7 +1348,7 @@ async def _process_simple_streaming_events(
             reasoning_parser = self.parser.reasoning_parser_cls(tokenizer)
         tool_parser = None
         if self.parser and self.parser.tool_parser_cls:
-            tool_parser = self.parser.tool_parser_cls(tokenizer)
+            tool_parser = self.parser.tool_parser_cls(tokenizer, request.tools)
         reasoning_ended = False
         tool_call_text_started = False
         previous_text = ""

vllm/entrypoints/serve/render/serving.py

@@ -544,6 +544,8 @@ async def preprocess_chat(
                     )
                     raise NotImplementedError(msg)
                 tokenizer = renderer.get_tokenizer()
-                request = tool_parser(tokenizer).adjust_request(request=request)  # type: ignore[arg-type]
+                request = tool_parser(tokenizer, request.tools).adjust_request(
+                    request=request  # type: ignore[arg-type]
+                )
 
         return conversation, [engine_prompt]

vllm/tool_parsers/abstract_tool_parser.py

@@ -5,13 +5,18 @@
 import os
 from collections.abc import Callable, Sequence
 from functools import cached_property
+from typing import TypeAlias
 
 from openai.types.responses import (
     ResponseFormatTextJSONSchemaConfig,
     ResponseTextConfig,
 )
+from openai.types.responses.tool import Tool as ResponsesTool
 
-from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
+from vllm.entrypoints.openai.chat_completion.protocol import (
+    ChatCompletionRequest,
+    ChatCompletionToolsParam,
+)
 from vllm.entrypoints.openai.engine.protocol import (
     DeltaMessage,
     ExtractedToolCallInformation,
@@ -30,6 +35,8 @@
 
 logger = init_logger(__name__)
 
+Tool: TypeAlias = ChatCompletionToolsParam | ResponsesTool
+
 
 class ToolParser:
     """
@@ -38,14 +45,19 @@ class ToolParser:
     derived classes.
     """
 
-    def __init__(self, tokenizer: TokenizerLike):
+    def __init__(
+        self,
+        tokenizer: TokenizerLike,
+        tools: list[Tool] | None = None,
+    ):
         self.prev_tool_call_arr: list[dict] = []
         # the index of the tool call that is currently being parsed
         self.current_tool_id: int = -1
         self.current_tool_name_sent: bool = False
         self.streamed_args_for_tool: list[str] = []
 
         self.model_tokenizer = tokenizer
+        self.tools = tools
 
     @cached_property
     def vocab(self) -> dict[str, int]:

vllm/tool_parsers/deepseekv31_tool_parser.py

@@ -19,14 +19,14 @@
 )
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
-from vllm.tool_parsers.abstract_tool_parser import ToolParser
+from vllm.tool_parsers.abstract_tool_parser import Tool, ToolParser
 
 logger = init_logger(__name__)
 
 
 class DeepSeekV31ToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         self.current_tool_name_sent: bool = False
         self.prev_tool_call_arr: list[dict] = []

vllm/tool_parsers/deepseekv32_tool_parser.py

@@ -22,6 +22,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 
@@ -43,8 +44,8 @@ class DeepSeekV32ToolParser(ToolParser):
     </｜DSML｜function_calls>
     """
 
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         self.prev_tool_call_arr: list[dict] = []
 

vllm/tool_parsers/deepseekv3_tool_parser.py

@@ -20,15 +20,16 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 
 logger = init_logger(__name__)
 
 
 class DeepSeekV3ToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         self.current_tool_name_sent: bool = False
         self.prev_tool_call_arr: list[dict] = []

vllm/tool_parsers/ernie45_tool_parser.py

@@ -20,19 +20,20 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 
 logger = init_logger(__name__)
 
 
 class Ernie45ToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
         """
         Ernie thinking model format:
         abc\n</think>\n\n\n<tool_call>\ndef\n</tool_call>\n
         """
-        super().__init__(tokenizer)
+        super().__init__(tokenizer, tools)
         self.current_tool_name_sent = False
         self.prev_tool_call_arr: list[dict] = []
         self.current_tool_id = -1

vllm/tool_parsers/functiongemma_tool_parser.py

@@ -20,7 +20,7 @@
 )
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
-from vllm.tool_parsers.abstract_tool_parser import ToolParser
+from vllm.tool_parsers.abstract_tool_parser import Tool, ToolParser
 
 logger = init_logger(__name__)
 
@@ -33,8 +33,8 @@ class FunctionGemmaToolParser(ToolParser):
     <start_function_call>call:func_name{param:<escape>value<escape>}<end_function_call>
     """
 
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         # Streaming state
         self.current_tool_name_sent: bool = False

vllm/tool_parsers/gigachat3_tool_parser.py

@@ -20,7 +20,7 @@
 )
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
-from vllm.tool_parsers.abstract_tool_parser import ToolParser
+from vllm.tool_parsers.abstract_tool_parser import Tool, ToolParser
 
 logger = init_logger(__name__)
 
@@ -46,8 +46,8 @@
 
 
 class GigaChat3ToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
         self.tool_started: bool = False
         self.tool_name_sent: bool = False
         self.tool_id: str | None = None

vllm/tool_parsers/glm47_moe_tool_parser.py

@@ -16,14 +16,15 @@
 
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
+from vllm.tool_parsers.abstract_tool_parser import Tool
 from vllm.tool_parsers.glm4_moe_tool_parser import Glm4MoeModelToolParser
 
 logger = init_logger(__name__)
 
 
 class Glm47MoeModelToolParser(Glm4MoeModelToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
         # GLM-4.7 format: <tool_call>func_name[<arg_key>...]*</tool_call>
         # The function name can be followed by a newline, whitespace, or
         # directly by <arg_key> tags (no separator).  The arg section is

vllm/tool_parsers/glm4_moe_tool_parser.py

@@ -21,7 +21,6 @@
 from vllm.entrypoints.chat_utils import make_tool_call_id
 from vllm.entrypoints.openai.chat_completion.protocol import (
     ChatCompletionRequest,
-    ChatCompletionToolsParam,
 )
 from vllm.entrypoints.openai.engine.protocol import (
     DeltaFunctionCall,
@@ -34,6 +33,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 
@@ -48,8 +48,8 @@ class Glm4MoeModelToolParser(ToolParser):
     rather than waiting for the complete </arg_value> tag.
     """
 
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
         # Stateful streaming fields
         self.current_tool_name_sent: bool = False
         self.prev_tool_call_arr: list[dict[str, Any]] = []
@@ -122,7 +122,7 @@ def _json_escape_string_content(s: str) -> str:
     def _is_string_type(
         tool_name: str,
         arg_name: str,
-        tools: list[ChatCompletionToolsParam] | None,
+        tools: list[Tool] | None,
     ) -> bool:
         if tools is None:
             return False

vllm/tool_parsers/granite4_tool_parser.py

@@ -22,6 +22,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 
@@ -43,8 +44,8 @@ def __init__(self, *, name: str, arguments: str | None): ...
 
 
 class Granite4ToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         self.prev_tool_call_arr: list[dict] = []
         self.current_tool_id: int = -1

vllm/tool_parsers/granite_20b_fc_tool_parser.py

@@ -24,6 +24,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 from vllm.tool_parsers.utils import (
@@ -46,8 +47,8 @@ class Granite20bFCToolParser(ToolParser):
     are all set
     """
 
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         self.bot_token = "<function_call>"
         self.tool_start_token = self.bot_token

vllm/tool_parsers/granite_tool_parser.py

@@ -22,6 +22,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 from vllm.tool_parsers.utils import (
@@ -44,8 +45,8 @@ class GraniteToolParser(ToolParser):
     are all set
     """
 
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
         # for granite 3.0, the token `<|tool_call|>`
         self.bot_token = "<|tool_call|>"
         # for granite 3.1, the string `<tool_call>`

vllm/tool_parsers/hermes_tool_parser.py

@@ -23,6 +23,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 from vllm.utils.mistral import is_mistral_tokenizer
@@ -31,8 +32,8 @@
 
 
 class Hermes2ProToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         if is_mistral_tokenizer(tokenizer):
             logger.error("Detected Mistral tokenizer when using a Hermes model")

vllm/tool_parsers/hunyuan_a13b_tool_parser.py

@@ -22,6 +22,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 from vllm.tool_parsers.utils import consume_space
@@ -31,8 +32,8 @@
 
 
 class HunyuanA13BToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
 
         # Initialize state for streaming mode
         self.prev_tool_calls: list[dict] = []

vllm/tool_parsers/internlm2_tool_parser.py

@@ -22,6 +22,7 @@
 from vllm.logger import init_logger
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import (
+    Tool,
     ToolParser,
 )
 from vllm.tool_parsers.utils import extract_intermediate_diff
@@ -30,8 +31,8 @@
 
 
 class Internlm2ToolParser(ToolParser):
-    def __init__(self, tokenizer: TokenizerLike):
-        super().__init__(tokenizer)
+    def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
+        super().__init__(tokenizer, tools)
         self.position = 0
 
     def adjust_request(self, request: ChatCompletionRequest) -> ChatCompletionRequest: