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