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591 lines
26 KiB
Python
591 lines
26 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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# code modified from deepseekv3_tool_parser.py
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from collections.abc import Sequence
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import regex as re
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from vllm.entrypoints.openai.protocol import (
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ChatCompletionRequest,
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DeltaFunctionCall,
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DeltaMessage,
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DeltaToolCall,
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ExtractedToolCallInformation,
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FunctionCall,
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ToolCall,
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)
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from vllm.entrypoints.openai.tool_parsers.abstract_tool_parser import (
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ToolParser,
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)
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from vllm.logger import init_logger
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from vllm.tokenizers import TokenizerLike
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logger = init_logger(__name__)
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class KimiK2ToolParser(ToolParser):
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def __init__(self, tokenizer: TokenizerLike):
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super().__init__(tokenizer)
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self.current_tool_name_sent: bool = False
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self.prev_tool_call_arr: list[dict] = []
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self.current_tool_id: int = -1
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self.streamed_args_for_tool: list[
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str
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] = [] # map what has been streamed for each tool so far to a list
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# Section-level state management to prevent token leakage
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self.in_tool_section: bool = False
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self.token_buffer: str = ""
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# Buffer size: empirical worst-case for longest marker (~30 chars) * 2
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# + safety margin for unicode + partial overlap. Prevents unbounded growth.
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self.buffer_max_size: int = 1024
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self.section_char_count: int = 0 # Track characters processed in tool section
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self.max_section_chars: int = 8192 # Force exit if section exceeds this
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self._buffer_overflow_logged: bool = False # Log overflow once per session
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# Support both singular and plural variants
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self.tool_calls_start_token: str = "<|tool_calls_section_begin|>"
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self.tool_calls_end_token: str = "<|tool_calls_section_end|>"
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self.tool_calls_start_token_variants: list[str] = [
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"<|tool_calls_section_begin|>",
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"<|tool_call_section_begin|>", # singular variant
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]
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self.tool_calls_end_token_variants: list[str] = [
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"<|tool_calls_section_end|>",
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"<|tool_call_section_end|>", # singular variant
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]
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self.tool_call_start_token: str = "<|tool_call_begin|>"
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self.tool_call_end_token: str = "<|tool_call_end|>"
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self.tool_call_regex = re.compile(
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r"<\|tool_call_begin\|>\s*(?P<tool_call_id>[^<]+:\d+)\s*<\|tool_call_argument_begin\|>\s*(?P<function_arguments>(?:(?!<\|tool_call_begin\|>).)*?)\s*<\|tool_call_end\|>",
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re.DOTALL,
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)
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self.stream_tool_call_portion_regex = re.compile(
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r"(?P<tool_call_id>.+:\d+)\s*<\|tool_call_argument_begin\|>\s*(?P<function_arguments>.*)"
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)
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self.stream_tool_call_name_regex = re.compile(r"(?P<tool_call_id>.+:\d+)\s*")
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if not self.model_tokenizer:
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raise ValueError(
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"The model tokenizer must be passed to the ToolParser "
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"constructor during construction."
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)
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self.tool_calls_start_token_id = self.vocab.get(self.tool_calls_start_token)
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self.tool_calls_end_token_id = self.vocab.get(self.tool_calls_end_token)
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# Get token IDs for all variants
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self.tool_calls_start_token_ids: list[int] = [
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tid
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for variant in self.tool_calls_start_token_variants
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if (tid := self.vocab.get(variant)) is not None
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]
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self.tool_calls_end_token_ids: list[int] = [
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tid
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for variant in self.tool_calls_end_token_variants
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if (tid := self.vocab.get(variant)) is not None
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]
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self.tool_call_start_token_id = self.vocab.get(self.tool_call_start_token)
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self.tool_call_end_token_id = self.vocab.get(self.tool_call_end_token)
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if (
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self.tool_calls_start_token_id is None
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or self.tool_calls_end_token_id is None
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):
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raise RuntimeError(
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"Kimi-K2 Tool parser could not locate tool call start/end "
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"tokens in the tokenizer!"
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)
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def _check_and_strip_markers(self, text: str) -> tuple[str, bool, bool]:
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"""
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Check for section begin/end markers in text and strip them.
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Returns: (cleaned_text, found_section_begin, found_section_end)
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"""
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found_begin = False
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found_end = False
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cleaned = text
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# Check for section begin markers (any variant)
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for variant in self.tool_calls_start_token_variants:
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if variant in cleaned:
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cleaned = cleaned.replace(variant, "")
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found_begin = True
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# Check for section end markers (any variant)
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for variant in self.tool_calls_end_token_variants:
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if variant in cleaned:
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cleaned = cleaned.replace(variant, "")
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found_end = True
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return cleaned, found_begin, found_end
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def _reset_section_state(self) -> None:
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"""Reset state when exiting tool section."""
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self.in_tool_section = False
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self.token_buffer = ""
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self.section_char_count = 0
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def reset_streaming_state(self) -> None:
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"""
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Reset all streaming state. Call this between requests to prevent
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state leakage when parser instance is reused.
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"""
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# Reset section state
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self._reset_section_state()
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# Reset parent class state
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self.current_tool_name_sent = False
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self.prev_tool_call_arr = []
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self.current_tool_id = -1
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self.streamed_args_for_tool = []
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logger.debug("Streaming state reset")
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def extract_tool_calls(
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self,
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model_output: str,
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request: ChatCompletionRequest,
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) -> ExtractedToolCallInformation:
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# sanity check; avoid unnecessary processing
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if self.tool_calls_start_token not in model_output:
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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else:
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try:
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# there are two possible captures - between tags, or between a
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# tag and end-of-string so the result of
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# findall is an array of tuples where one is a function call and
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# the other is None
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function_call_tuples = self.tool_call_regex.findall(model_output)
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logger.debug("function_call_tuples: %s", function_call_tuples)
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tool_calls = []
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for match in function_call_tuples:
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function_id, function_args = match
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# function_id: functions.get_weather:0 or get_weather:0
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function_name = function_id.split(":")[0].split(".")[-1]
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tool_calls.append(
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ToolCall(
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id=function_id,
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type="function",
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function=FunctionCall(
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name=function_name, arguments=function_args
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),
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)
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)
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content = model_output[: model_output.find(self.tool_calls_start_token)]
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return ExtractedToolCallInformation(
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tools_called=True,
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tool_calls=tool_calls,
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content=content if content else None,
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)
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except Exception:
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logger.exception("Error in extracting tool call from response.")
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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def extract_tool_calls_streaming(
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self,
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previous_text: str,
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current_text: str,
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delta_text: str,
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previous_token_ids: Sequence[int],
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current_token_ids: Sequence[int],
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delta_token_ids: Sequence[int],
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request: ChatCompletionRequest,
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) -> DeltaMessage | None:
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logger.debug("delta_text: %s", delta_text)
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logger.debug("delta_token_ids: %s", delta_token_ids)
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# Flag to defer section exit until after tool parsing completes
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deferred_section_exit = False
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# Add delta to buffer for split marker detection
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self.token_buffer += delta_text
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# Enforce buffer size limit to prevent memory issues
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if len(self.token_buffer) > self.buffer_max_size:
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if not self._buffer_overflow_logged:
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logger.warning(
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"Token buffer exceeded max size (%d bytes), flushing excess. "
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"This may indicate very long markers or unusual tokenization.",
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self.buffer_max_size,
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)
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self._buffer_overflow_logged = True
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# Keep only the most recent content that might contain partial markers
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self.token_buffer = self.token_buffer[-self.buffer_max_size // 2 :]
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# Check buffer for section markers (handles split tokens)
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buffered_text, found_section_begin, found_section_end = (
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self._check_and_strip_markers(self.token_buffer)
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)
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# Track section state transitions
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if found_section_begin and not self.in_tool_section:
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logger.debug("Entering tool section")
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self.in_tool_section = True
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self.token_buffer = buffered_text # Use cleaned buffer
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self.section_char_count = 0 # Reset counter for new section
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if found_section_end and self.in_tool_section:
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logger.debug("Detected section end marker")
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# CRITICAL: Don't exit early if tool_call_end is in this chunk.
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# Tool parser must emit final arguments/close first to avoid dropping
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# the final tool update and leaking tokens into reasoning channel.
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has_tool_end = self.tool_call_end_token_id in delta_token_ids
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if has_tool_end:
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# Defer exit until after tool parsing completes
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deferred_section_exit = True
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logger.debug("Deferring section exit: tool_call_end in same chunk")
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self.token_buffer = buffered_text
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else:
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# No tool call ending, safe to exit immediately
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logger.debug("Exiting tool section")
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remaining = buffered_text
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self._reset_section_state()
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# Return remaining text as reasoning content if non-empty
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if remaining.strip():
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return DeltaMessage(content=remaining)
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# Return empty delta to maintain function contract
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# (always returns DeltaMessage)
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return DeltaMessage(content="")
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else:
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self.token_buffer = buffered_text
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# Check if any variant of section start token is in current_token_ids
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has_section_token = any(
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tid in current_token_ids for tid in self.tool_calls_start_token_ids
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)
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# Early return: if no section token detected yet, return as reasoning content
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if not has_section_token and not self.in_tool_section:
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logger.debug("No tool call tokens found!")
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# Don't clear buffer - it needs to accumulate partial markers across deltas
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# Buffer overflow is already protected by lines 215-224
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return DeltaMessage(content=delta_text)
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# Strip section markers from delta_text for subsequent processing
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# NOTE: This preprocessing happens BEFORE the regex-based tool call
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# parsing (from PR #24847) to ensure markers are removed cleanly
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# before pattern matching. No double-stripping occurs because
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# section markers and tool call markers are distinct.
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delta_text, _, _ = self._check_and_strip_markers(delta_text)
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# Error recovery: If in tool section for too long, force exit
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if self.in_tool_section:
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self.section_char_count += len(delta_text)
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if self.section_char_count > self.max_section_chars:
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logger.warning(
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"Tool section exceeded max length (%d chars), forcing exit. "
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"This may indicate malformed model output.",
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self.max_section_chars,
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)
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self._reset_section_state()
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# Deferred exit already handled by forced exit above
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# Return remaining content as reasoning (or empty delta if no content)
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return DeltaMessage(content=delta_text if delta_text.strip() else "")
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try:
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# figure out where we are in the parsing by counting tool call
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# start & end tags
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prev_tool_start_count = previous_token_ids.count(
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self.tool_call_start_token_id
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)
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prev_tool_end_count = previous_token_ids.count(self.tool_call_end_token_id)
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cur_tool_start_count = current_token_ids.count(
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self.tool_call_start_token_id
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)
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cur_tool_end_count = current_token_ids.count(self.tool_call_end_token_id)
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tool_call_portion = None
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text_portion = None
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# case: if we're generating text, OR rounding out a tool call
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if (
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cur_tool_start_count == cur_tool_end_count
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and prev_tool_end_count == cur_tool_end_count
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and self.tool_call_end_token not in delta_text
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):
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# CRITICAL FIX: Suppress content if in tool section but
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# no tool calls started
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if self.in_tool_section and cur_tool_start_count == 0:
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logger.debug(
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"In tool section but no tool calls started yet. "
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"Suppressing: %s",
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delta_text,
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)
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# Return empty delta to maintain iterator contract
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return DeltaMessage(content="")
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logger.debug("Generating text content! skipping tool parsing.")
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return DeltaMessage(content=delta_text)
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if self.tool_call_end_token in delta_text:
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logger.debug("tool_call_end_token in delta_text")
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full_text = current_text + delta_text
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tool_call_portion = (
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full_text.split(self.tool_call_start_token)[-1]
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.split(self.tool_call_end_token)[0]
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.rstrip()
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)
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delta_text = delta_text.split(self.tool_call_end_token)[0].rstrip()
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text_portion = delta_text.split(self.tool_call_end_token)[-1].lstrip()
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# case -- we're starting a new tool call
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if (
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cur_tool_start_count > cur_tool_end_count
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and cur_tool_start_count > prev_tool_start_count
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):
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if len(delta_token_ids) > 1:
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tool_call_portion = current_text.split(self.tool_call_start_token)[
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-1
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]
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else:
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tool_call_portion = None
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delta = None
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text_portion = None
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# set cursors and state appropriately
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self.current_tool_id += 1
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self.current_tool_name_sent = False
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self.streamed_args_for_tool.append("")
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logger.debug("Starting on a new tool %s", self.current_tool_id)
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# case -- we're updating an existing tool call
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elif (
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cur_tool_start_count > cur_tool_end_count
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and cur_tool_start_count == prev_tool_start_count
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):
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# get the portion of the text that's the tool call
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tool_call_portion = current_text.split(self.tool_call_start_token)[-1]
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text_portion = None
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# case -- the current tool call is being closed.
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elif (
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cur_tool_start_count == cur_tool_end_count
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and cur_tool_end_count >= prev_tool_end_count
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):
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if self.prev_tool_call_arr is None or len(self.prev_tool_call_arr) == 0:
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logger.debug("attempting to close tool call, but no tool call")
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# Handle deferred section exit before returning
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if deferred_section_exit and self.in_tool_section:
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self._reset_section_state()
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return None
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diff = self.prev_tool_call_arr[self.current_tool_id].get("arguments")
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if diff:
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diff = (
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diff.encode("utf-8").decode("unicode_escape")
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if diff is str
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else diff
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)
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if '"}' not in delta_text:
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# Handle deferred section exit before returning
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if deferred_section_exit and self.in_tool_section:
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self._reset_section_state()
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return None
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end_loc = delta_text.rindex('"}')
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diff = delta_text[:end_loc] + '"}'
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logger.debug(
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"Finishing tool and found diff that had not "
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"been streamed yet: %s",
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diff,
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)
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self.streamed_args_for_tool[self.current_tool_id] += diff
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# Handle deferred section exit before returning
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if deferred_section_exit and self.in_tool_section:
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logger.debug("Completing deferred section exit")
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self._reset_section_state()
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return DeltaMessage(
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tool_calls=[
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DeltaToolCall(
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index=self.current_tool_id,
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function=DeltaFunctionCall(arguments=diff).model_dump(
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exclude_none=True
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),
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)
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]
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)
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# case -- otherwise we're just generating text
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else:
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# Check if we're in tool section - if so, suppress
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if self.in_tool_section:
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logger.debug("In tool section, suppressing text generation")
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# Handle deferred section exit before returning
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if deferred_section_exit:
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self._reset_section_state()
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return DeltaMessage(content="")
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text = delta_text.replace(self.tool_call_start_token, "")
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text = text.replace(self.tool_call_end_token, "")
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delta = DeltaMessage(tool_calls=[], content=text)
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# Handle deferred section exit before returning
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if deferred_section_exit and self.in_tool_section:
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self._reset_section_state()
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return delta
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current_tool_call = dict()
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if tool_call_portion:
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current_tool_call_matches = self.stream_tool_call_portion_regex.match(
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tool_call_portion
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)
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if current_tool_call_matches:
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tool_id, tool_args = current_tool_call_matches.groups()
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tool_name = tool_id.split(":")[0].split(".")[-1]
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current_tool_call["id"] = tool_id
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current_tool_call["name"] = tool_name
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current_tool_call["arguments"] = tool_args
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else:
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current_tool_call_name_matches = (
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self.stream_tool_call_name_regex.match(tool_call_portion)
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)
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if current_tool_call_name_matches:
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(tool_id_str,) = current_tool_call_name_matches.groups()
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tool_name = tool_id_str.split(":")[0].split(".")[-1]
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current_tool_call["id"] = tool_id_str
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current_tool_call["name"] = tool_name
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current_tool_call["arguments"] = ""
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else:
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logger.debug("Not enough token")
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return None
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# case - we haven't sent the tool name yet. If it's available, send
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# it. otherwise, wait until it's available.
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if not self.current_tool_name_sent:
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if current_tool_call is None:
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return None
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function_name: str | None = current_tool_call.get("name")
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tool_id = current_tool_call.get("id")
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if function_name:
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self.current_tool_name_sent = True
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return DeltaMessage(
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tool_calls=[
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DeltaToolCall(
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index=self.current_tool_id,
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type="function",
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id=tool_id,
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function=DeltaFunctionCall(
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name=function_name
|
|
).model_dump(exclude_none=True),
|
|
)
|
|
]
|
|
)
|
|
else:
|
|
return None
|
|
|
|
# case -- otherwise, send the tool call delta
|
|
|
|
# if the tool call portion is None, send the delta as text
|
|
if tool_call_portion is None:
|
|
# if there's text but not tool calls, send that -
|
|
# otherwise None to skip chunk
|
|
delta = (
|
|
DeltaMessage(content=delta_text)
|
|
if text_portion is not None
|
|
else None
|
|
)
|
|
return delta
|
|
|
|
# now, the nitty-gritty of tool calls
|
|
# now we have the portion to parse as tool call.
|
|
|
|
logger.debug(
|
|
"Trying to parse current tool call with ID %s", self.current_tool_id
|
|
)
|
|
|
|
# if we're starting a new tool call, push an empty object in as
|
|
# a placeholder for the arguments
|
|
if len(self.prev_tool_call_arr) <= self.current_tool_id:
|
|
self.prev_tool_call_arr.append({})
|
|
|
|
# main logic for tool parsing here - compare prev. partially-parsed
|
|
# JSON to the current partially-parsed JSON
|
|
prev_arguments = self.prev_tool_call_arr[self.current_tool_id].get(
|
|
"arguments"
|
|
)
|
|
cur_arguments = current_tool_call.get("arguments")
|
|
|
|
logger.debug("diffing old arguments: %s", prev_arguments)
|
|
logger.debug("against new ones: %s", cur_arguments)
|
|
|
|
# case -- no arguments have been created yet. skip sending a delta.
|
|
if not cur_arguments and not prev_arguments:
|
|
logger.debug("Skipping text %s - no arguments", delta_text)
|
|
delta = None
|
|
|
|
# case -- prev arguments are defined, but non are now.
|
|
# probably impossible, but not a fatal error - just keep going
|
|
elif not cur_arguments and prev_arguments:
|
|
logger.error(
|
|
"should be impossible to have arguments reset "
|
|
"mid-call. skipping streaming anything."
|
|
)
|
|
delta = None
|
|
|
|
# case -- we now have the first info about arguments available from
|
|
# autocompleting the JSON
|
|
elif cur_arguments and not prev_arguments:
|
|
delta = DeltaMessage(
|
|
tool_calls=[
|
|
DeltaToolCall(
|
|
index=self.current_tool_id,
|
|
function=DeltaFunctionCall(
|
|
arguments=cur_arguments
|
|
).model_dump(exclude_none=True),
|
|
)
|
|
]
|
|
)
|
|
self.streamed_args_for_tool[self.current_tool_id] = cur_arguments
|
|
|
|
# last case -- we have an update to existing arguments.
|
|
elif cur_arguments and prev_arguments:
|
|
if (
|
|
isinstance(delta_text, str)
|
|
and cur_arguments != prev_arguments
|
|
and len(cur_arguments) > len(prev_arguments)
|
|
and cur_arguments.startswith(prev_arguments)
|
|
):
|
|
delta_arguments = cur_arguments[len(prev_arguments) :]
|
|
logger.debug("got diff %s", delta_text)
|
|
|
|
delta = DeltaMessage(
|
|
tool_calls=[
|
|
DeltaToolCall(
|
|
index=self.current_tool_id,
|
|
function=DeltaFunctionCall(
|
|
arguments=delta_arguments
|
|
).model_dump(exclude_none=True),
|
|
)
|
|
]
|
|
)
|
|
self.streamed_args_for_tool[self.current_tool_id] = cur_arguments
|
|
else:
|
|
delta = None
|
|
|
|
# handle saving the state for the current tool into
|
|
# the "prev" list for use in diffing for the next iteration
|
|
if self.current_tool_id == len(self.prev_tool_call_arr) - 1:
|
|
self.prev_tool_call_arr[self.current_tool_id] = current_tool_call
|
|
else:
|
|
self.prev_tool_call_arr.append(current_tool_call)
|
|
|
|
# Handle deferred section exit after tool parsing completes
|
|
if deferred_section_exit and self.in_tool_section:
|
|
logger.debug("Completing deferred section exit")
|
|
self._reset_section_state()
|
|
|
|
return delta
|
|
|
|
except Exception:
|
|
logger.exception("Error trying to handle streaming tool call.")
|
|
return None # do not stream a delta. skip this token ID.
|