wehub-resource-sync
268 lines
8.9 KiB
Python
268 lines
8.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Qwen3 parser for tool calls and reasoning.
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Qwen3 XML tool call format::
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<tool_call>
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<function=func_name>
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<parameter=key>value</parameter>
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</function>
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</tool_call>
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The argument body consists of ``<parameter=NAME>VALUE</parameter>`` tags.
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The ``_qwen3_arg_converter`` parses these into a JSON object.
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"""
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from __future__ import annotations
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import functools
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import json
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from typing import TYPE_CHECKING
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import regex as re
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from vllm.parser.engine.events import EventType
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from vllm.parser.engine.parser_engine import ParserEngine
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from vllm.parser.engine.parser_engine_config import (
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ParserEngineConfig,
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ParserState,
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Transition,
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)
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if TYPE_CHECKING:
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from vllm.entrypoints.openai.chat_completion.protocol import (
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ChatCompletionRequest,
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)
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from vllm.entrypoints.openai.responses.protocol import ResponsesRequest
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from vllm.tokenizers import TokenizerLike
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from vllm.tool_parsers.abstract_tool_parser import Tool
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THINK_START = "<think>"
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THINK_END = "</think>"
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TOOL_CALL_START = "<tool_call>"
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TOOL_CALL_END = "</tool_call>"
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FUNC_PREFIX = "<function="
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FUNC_END = "</function>"
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PARAM_START = "<parameter="
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PARAM_END = "</parameter>"
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_PARAM_RE = re.compile(
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r"<\s*parameter\s*=\s*([^>]*)>"
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r"(.*?)"
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r"(?:<\s*/\s*parameter\s*>|(?=<\s*parameter\s*=))",
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re.DOTALL,
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)
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_PARTIAL_PARAM_RE = re.compile(r"<\s*parameter\s*=\s*([^>]+)>(.*)$", re.DOTALL)
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def _qwen3_arg_converter(raw_args: str, partial: bool) -> str:
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params: dict[str, object] = {}
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for match in _PARAM_RE.finditer(raw_args):
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name = match.group(1)
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value = match.group(2)
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params[name] = value.strip()
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if partial:
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remaining = _PARAM_RE.sub("", raw_args)
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m = _PARTIAL_PARAM_RE.search(remaining)
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if m:
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name = m.group(1)
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value = m.group(2)
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if name:
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params[name] = value.strip()
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return json.dumps(params, ensure_ascii=False)
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@functools.cache
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def qwen3_config(
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thinking: bool = True,
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*,
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name: str = "qwen3",
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think_start: str = THINK_START,
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think_end: str = THINK_END,
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tool_start: str = TOOL_CALL_START,
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tool_end: str = TOOL_CALL_END,
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) -> ParserEngineConfig:
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return ParserEngineConfig(
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name=name,
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initial_state=ParserState.REASONING if thinking else ParserState.CONTENT,
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terminals={
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# Reasoning terminals
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"THINK_START": think_start,
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"THINK_END": think_end,
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# Tool call terminals
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"TOOL_START": tool_start,
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"TOOL_END": tool_end,
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"FUNC_PREFIX": FUNC_PREFIX,
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"FUNC_END": FUNC_END,
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"PARAM_START": PARAM_START,
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"PARAM_END": PARAM_END,
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"CLOSE_ANGLE": ">",
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},
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token_id_terminals={
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"THINK_START": think_start,
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"THINK_END": think_end,
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"TOOL_START": tool_start,
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"TOOL_END": tool_end,
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},
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transitions={
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# -- Reasoning transitions --
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(ParserState.REASONING, "THINK_START"): Transition(
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ParserState.REASONING,
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(),
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),
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(ParserState.REASONING, "THINK_END"): Transition(
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ParserState.CONTENT,
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(EventType.REASONING_END,),
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),
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# Absorb duplicate </think> — model may emit it after
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# already transitioning to CONTENT; drop it silently.
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(ParserState.CONTENT, "THINK_END"): Transition(
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ParserState.CONTENT,
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(),
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),
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# Tool call directly from reasoning (implicit end)
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(ParserState.REASONING, "TOOL_START"): Transition(
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ParserState.TOOL_PREAMBLE,
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(EventType.REASONING_END, EventType.TOOL_CALL_START),
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),
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# -- Tool call transitions --
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(ParserState.CONTENT, "TOOL_START"): Transition(
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ParserState.TOOL_PREAMBLE,
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(EventType.REASONING_END, EventType.TOOL_CALL_START),
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),
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# Fallback: <function= without a preceding <tool_call>
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(ParserState.CONTENT, "FUNC_PREFIX"): Transition(
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ParserState.TOOL_NAME,
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(EventType.TOOL_CALL_START,),
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),
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(ParserState.TOOL_PREAMBLE, "TOOL_END"): Transition(
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ParserState.CONTENT,
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(EventType.TOOL_CALL_END,),
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),
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(ParserState.TOOL_PREAMBLE, "FUNC_PREFIX"): Transition(
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ParserState.TOOL_NAME,
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(),
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),
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(ParserState.TOOL_NAME, "CLOSE_ANGLE"): Transition(
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ParserState.TOOL_ARGS,
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(),
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),
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# Malformed: </function> while still in TOOL_NAME (no closing >)
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(ParserState.TOOL_NAME, "FUNC_END"): Transition(
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ParserState.TOOL_BETWEEN,
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(EventType.TOOL_CALL_END,),
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),
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(ParserState.TOOL_ARGS, "FUNC_END"): Transition(
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ParserState.TOOL_BETWEEN,
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(EventType.TOOL_CALL_END,),
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),
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(ParserState.TOOL_ARGS, "PARAM_START"): Transition(
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ParserState.TOOL_ARGS,
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(EventType.ARG_VALUE_CHUNK,),
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),
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(ParserState.TOOL_ARGS, "PARAM_END"): Transition(
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ParserState.TOOL_ARGS,
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(EventType.ARG_VALUE_CHUNK,),
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),
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(ParserState.TOOL_BETWEEN, "TOOL_END"): Transition(
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ParserState.CONTENT,
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(),
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),
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# Consecutive tool call without closing </tool_call>
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(ParserState.TOOL_BETWEEN, "TOOL_START"): Transition(
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ParserState.TOOL_PREAMBLE,
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(EventType.TOOL_CALL_START,),
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),
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(ParserState.TOOL_BETWEEN, "FUNC_PREFIX"): Transition(
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ParserState.TOOL_NAME,
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(EventType.TOOL_CALL_START,),
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),
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},
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arg_converter=_qwen3_arg_converter,
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stream_arg_deltas=True,
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strip_trailing_reasoning_whitespace=False,
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tool_args_json=False,
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)
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class Qwen3Parser(ParserEngine):
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"""Qwen3 parser: ``<think>``/``</think>`` reasoning +
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``<tool_call>`` XML tool calls in a single engine.
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- ``<tool_call>`` as implicit reasoning end
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- Unpaired ``<tool_call>`` token ID detection for ``is_reasoning_end``
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Subclasses that share the grammar but differ only in the four wrapper
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token strings (reasoning + tool-call) override the class attributes
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below; everything else is inherited unchanged.
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"""
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CONFIG_NAME = "qwen3"
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THINK_START = THINK_START
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THINK_END = THINK_END
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TOOL_START = TOOL_CALL_START
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TOOL_END = TOOL_CALL_END
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def __init__(
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self,
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tokenizer: TokenizerLike,
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tools: list[Tool] | None = None,
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**kwargs,
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) -> None:
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chat_kwargs = kwargs.get("chat_template_kwargs", {}) or {}
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self.thinking_enabled = chat_kwargs.get("enable_thinking", True)
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kwargs.setdefault(
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"parser_engine_config",
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qwen3_config(
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thinking=self.thinking_enabled,
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name=self.CONFIG_NAME,
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think_start=self.THINK_START,
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think_end=self.THINK_END,
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tool_start=self.TOOL_START,
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tool_end=self.TOOL_END,
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),
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)
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super().__init__(
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tokenizer,
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tools,
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**kwargs,
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)
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vocab = self.vocab
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self._tool_call_token_id: int | None = vocab.get(self.TOOL_START)
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self._tool_call_end_token_id: int | None = vocab.get(self.TOOL_END)
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def extract_reasoning(
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self,
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model_output: str,
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request: ChatCompletionRequest | ResponsesRequest,
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) -> tuple[str | None, str | None]:
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if not self.thinking_enabled:
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return None, model_output
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return super().extract_reasoning(model_output, request)
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def is_reasoning_end(self, input_ids: list[int]) -> bool:
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if super().is_reasoning_end(input_ids):
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return True
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tool_call_id = self._tool_call_token_id
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tool_call_end_id = self._tool_call_end_token_id
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reasoning_start_id = self._reasoning_start_token_id
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if tool_call_id is not None:
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for i in range(len(input_ids) - 1, -1, -1):
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if (
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reasoning_start_id is not None
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and input_ids[i] == reasoning_start_id
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):
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return False
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if input_ids[i] == tool_call_id:
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if tool_call_end_id is not None and any(
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input_ids[j] == tool_call_end_id
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for j in range(i + 1, len(input_ids))
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):
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continue
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return True
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return False
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