class Glm4MoeModelToolParser(ToolParser):
"""Tool parser for GLM-4 models with incremental string streaming.
This parser emits tool-call deltas incrementally as arguments arrive.
For string-type parameters, content is streamed character-by-character
rather than waiting for the complete </arg_value> tag.
"""
def __init__(self, tokenizer: TokenizerLike):
super().__init__(tokenizer)
# Stateful streaming fields
self.current_tool_name_sent: bool = False
self.prev_tool_call_arr: list[dict[str, Any]] = []
self.current_tool_id: int = -1
self.streamed_args_for_tool: list[str] = []
self.tool_call_start_token: str = "<tool_call>"
self.tool_call_end_token: str = "</tool_call>"
self.arg_key_start: str = "<arg_key>"
self.arg_key_end: str = "</arg_key>"
self.arg_val_start: str = "<arg_value>"
self.arg_val_end: str = "</arg_value>"
self.tool_calls_start_token = self.tool_call_start_token
self.func_call_regex = re.compile(r"<tool_call>.*?</tool_call>", re.DOTALL)
self.func_detail_regex = re.compile(
r"<tool_call>([^\n]*)\n(.*)</tool_call>", re.DOTALL
)
self.func_arg_regex = re.compile(
r"<arg_key>(.*?)</arg_key>\s*<arg_value>(.*?)</arg_value>", re.DOTALL
)
if not self.model_tokenizer:
raise ValueError(
"The model tokenizer must be passed to the ToolParser "
"constructor during construction."
)
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)
self._buffer: str = ""
# Streaming state for incremental tool-call streaming
self._in_tool_call: bool = False
self._current_tool_name: str | None = None
self._pending_key: str | None = None
self._streaming_string_value: bool = False
self._tool_call_ids: list[str] = []
self._args_started: list[bool] = []
self._args_closed: list[bool] = []
self._seen_keys: list[set[str]] = []
@staticmethod
def _deserialize(value: str) -> Any:
try:
return json.loads(value)
except json.JSONDecodeError:
pass
try:
return ast.literal_eval(value)
except (ValueError, SyntaxError):
pass
return value
@staticmethod
def _json_escape_string_content(s: str) -> str:
"""JSON-escape string content for incremental streaming.
This escapes the content that goes INSIDE a JSON string (between quotes),
not including the surrounding quotes themselves.
"""
if not s:
return ""
return json.dumps(s, ensure_ascii=False)[1:-1]
@staticmethod
def _is_string_type(
tool_name: str,
arg_name: str,
tools: list[ChatCompletionToolsParam] | None,
) -> bool:
if tools is None:
return False
for tool in tools:
if tool.function.name != tool_name:
continue
if tool.function.parameters is None:
return False
arg_type = (
tool.function.parameters.get("properties", {})
.get(arg_name, {})
.get("type", None)
)
return arg_type == "string"
logger.debug("No tool named '%s'.", tool_name)
return False
@staticmethod
def _tools_enabled(request: ChatCompletionRequest) -> bool:
"""Return whether tool parsing should be applied for this request."""
try:
tools = getattr(request, "tools", None)
tool_choice = getattr(request, "tool_choice", None)
return bool(tools) and tool_choice != "none"
except Exception:
logger.exception("Failed to determine if tools are enabled.")
return False
def adjust_request(self, request: ChatCompletionRequest) -> ChatCompletionRequest:
"""Adjust request parameters for tool call token handling."""
request = super().adjust_request(request)
if request.tools and request.tool_choice != "none":
# Ensure tool call tokens (<tool_call>, </tool_call>) are not skipped
# during decoding. Even though they are not marked as special tokens,
# setting skip_special_tokens=False ensures proper handling in
# transformers 5.x where decoding behavior may have changed.
request.skip_special_tokens = False
return request
def extract_tool_calls(
self,
model_output: str,
request: ChatCompletionRequest,
) -> ExtractedToolCallInformation:
matched_tool_calls = self.func_call_regex.findall(model_output)
logger.debug("model_output: %s", model_output)
try:
tool_calls: list[ToolCall] = []
for match in matched_tool_calls:
tc_detail = self.func_detail_regex.search(match)
if not tc_detail:
logger.warning(
"Failed to parse tool call details from: %s",
match,
)
continue
tc_name = tc_detail.group(1).strip()
tc_args = tc_detail.group(2)
pairs = self.func_arg_regex.findall(tc_args) if tc_args else []
arg_dct: dict[str, Any] = {}
for key, value in pairs:
arg_key = key.strip()
arg_val = value.strip()
if not self._is_string_type(tc_name, arg_key, request.tools):
arg_val = self._deserialize(arg_val)
logger.debug("arg_key = %s, arg_val = %s", arg_key, arg_val)
arg_dct[arg_key] = arg_val
tool_calls.append(
ToolCall(
type="function",
function=FunctionCall(
name=tc_name,
arguments=json.dumps(arg_dct, ensure_ascii=False),
),
)
)
except Exception:
logger.exception("Failed to extract tool call spec")
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
else:
if len(tool_calls) > 0:
content = model_output[: model_output.find(self.tool_calls_start_token)]
return ExtractedToolCallInformation(
tools_called=True, tool_calls=tool_calls, content=content
)
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:
if not self._tools_enabled(request):
return DeltaMessage(content=delta_text) if delta_text else None
self._buffer += delta_text
while True:
if not self._in_tool_call:
start_idx = self._buffer.find(self.tool_call_start_token)
if start_idx == -1:
# Check for partial start token at end of buffer
for i in range(1, len(self.tool_call_start_token)):
if self._buffer.endswith(self.tool_call_start_token[:i]):
out = self._buffer[:-i]
self._buffer = self._buffer[-i:]
return DeltaMessage(content=out) if out else None
out = self._buffer
self._buffer = ""
return DeltaMessage(content=out) if out else None
if start_idx > 0:
out = self._buffer[:start_idx]
self._buffer = self._buffer[start_idx:]
return DeltaMessage(content=out) if out else None
self._buffer = self._buffer[len(self.tool_call_start_token) :]
self._begin_tool_call()
continue
# Parse tool name first
if not self.current_tool_name_sent:
nl = self._buffer.find("\n")
ak = self._buffer.find(self.arg_key_start)
end = self._buffer.find(self.tool_call_end_token)
candidates = [i for i in [nl, ak, end] if i != -1]
if not candidates:
return None
cut = min(candidates)
tool_name = self._buffer[:cut].strip()
if tool_name == "" and cut == end:
# Handle empty tool call like `<tool_call></tool_call>`.
# Consume the tokens and reset state to avoid infinite loop.
self._buffer = self._buffer[end + len(self.tool_call_end_token) :]
self._finish_tool_call()
self._revert_last_tool_call_state()
continue
if cut == nl:
self._buffer = self._buffer[nl + 1 :]
else:
self._buffer = self._buffer[cut:]
self._current_tool_name = tool_name
self.current_tool_name_sent = True
return self._emit_tool_name_delta(tool_name)
assert self._current_tool_name is not None
# Handle incremental string value streaming
if self._streaming_string_value:
val_end = self._buffer.find(self.arg_val_end)
if val_end != -1:
raw_content = self._buffer[:val_end]
self._buffer = self._buffer[val_end + len(self.arg_val_end) :]
self._streaming_string_value = False
self._pending_key = None
escaped = self._json_escape_string_content(raw_content)
frag = escaped + '"'
self.streamed_args_for_tool[self.current_tool_id] += frag
return self._emit_tool_args_delta(frag)
else:
# Check for partial </arg_value> at end
safe_len = len(self._buffer)
for i in range(1, len(self.arg_val_end)):
if self._buffer.endswith(self.arg_val_end[:i]):
safe_len = len(self._buffer) - i
break
if safe_len > 0:
to_emit = self._buffer[:safe_len]
self._buffer = self._buffer[safe_len:]
escaped = self._json_escape_string_content(to_emit)
if escaped:
self.streamed_args_for_tool[self.current_tool_id] += escaped
return self._emit_tool_args_delta(escaped)
return None
# If we have a pending key, parse its value
if self._pending_key is not None:
val_pos = self._buffer.find(self.arg_val_start)
if val_pos == -1:
return None
if val_pos > 0:
self._buffer = self._buffer[val_pos:]
key = (self._pending_key or "").strip()
is_string = self._is_string_type(
self._current_tool_name, key, request.tools
)
if is_string:
# String type: stream incrementally
self._buffer = self._buffer[len(self.arg_val_start) :]
if key in self._seen_keys[self.current_tool_id]:
self._pending_key = None
continue
self._seen_keys[self.current_tool_id].add(key)
key_json = json.dumps(key, ensure_ascii=False)
if not self._args_started[self.current_tool_id]:
frag = "{" + key_json + ':"'
self._args_started[self.current_tool_id] = True
else:
frag = "," + key_json + ':"'
self.streamed_args_for_tool[self.current_tool_id] += frag
self._streaming_string_value = True
return self._emit_tool_args_delta(frag)
else:
# Non-string type: wait for complete value
val_end = self._buffer.find(self.arg_val_end)
if val_end == -1:
return None
raw_val = self._buffer[len(self.arg_val_start) : val_end].strip()
self._buffer = self._buffer[val_end + len(self.arg_val_end) :]
self._pending_key = None
frag = self._append_arg_fragment(
key=key,
raw_val=raw_val,
)
if frag:
return self._emit_tool_args_delta(frag)
continue
# Parse next arg or close
end_pos = self._buffer.find(self.tool_call_end_token)
key_pos = self._buffer.find(self.arg_key_start)
if end_pos != -1 and (key_pos == -1 or end_pos < key_pos):
self._buffer = self._buffer[end_pos + len(self.tool_call_end_token) :]
frag = self._close_args_if_needed()
# Finalize prev_tool_call_arr with complete parsed arguments
if self._current_tool_name:
try:
full_args_str = self.streamed_args_for_tool[
self.current_tool_id
]
args_dict = json.loads(full_args_str)
self.prev_tool_call_arr[self.current_tool_id] = {
"name": self._current_tool_name,
"arguments": args_dict,
}
except (json.JSONDecodeError, IndexError) as e:
logger.warning(
"Failed to finalize tool call state for tool %d: %s",
self.current_tool_id,
e,
)
self._finish_tool_call()
return self._emit_tool_args_delta(frag) if frag else None
if key_pos == -1:
return None
if key_pos > 0:
self._buffer = self._buffer[key_pos:]
key_end = self._buffer.find(self.arg_key_end)
if key_end == -1:
return None
key = self._buffer[len(self.arg_key_start) : key_end]
self._buffer = self._buffer[key_end + len(self.arg_key_end) :]
self._pending_key = key
continue
def _ensure_tool_state(self) -> None:
while len(self._tool_call_ids) <= self.current_tool_id:
self._tool_call_ids.append(
make_tool_call_id(id_type="random", func_name=None, idx=None)
)
while len(self.streamed_args_for_tool) <= self.current_tool_id:
self.streamed_args_for_tool.append("")
while len(self.prev_tool_call_arr) <= self.current_tool_id:
self.prev_tool_call_arr.append({})
while len(self._args_started) <= self.current_tool_id:
self._args_started.append(False)
while len(self._args_closed) <= self.current_tool_id:
self._args_closed.append(False)
while len(self._seen_keys) <= self.current_tool_id:
self._seen_keys.append(set())
def _begin_tool_call(self) -> None:
if self.current_tool_id == -1:
self.current_tool_id = 0
else:
self.current_tool_id += 1
self._ensure_tool_state()
self.current_tool_name_sent = False
self._current_tool_name = None
self._pending_key = None
self._streaming_string_value = False
self._in_tool_call = True
def _finish_tool_call(self) -> None:
self._in_tool_call = False
self._current_tool_name = None
self._pending_key = None
self._streaming_string_value = False
def _revert_last_tool_call_state(self) -> None:
"""Revert the state allocation for the last tool call."""
if self.current_tool_id < 0:
return
self._tool_call_ids.pop()
self.streamed_args_for_tool.pop()
self.prev_tool_call_arr.pop()
self._args_started.pop()
self._args_closed.pop()
self._seen_keys.pop()
self.current_tool_id -= 1
def _emit_tool_name_delta(self, tool_name: str) -> DeltaMessage:
return DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_id,
id=self._tool_call_ids[self.current_tool_id],
type="function",
function=DeltaFunctionCall(
name=tool_name,
arguments="",
).model_dump(exclude_none=True),
)
]
)
def _emit_tool_args_delta(self, fragment: str) -> DeltaMessage:
return DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_id,
function=DeltaFunctionCall(arguments=fragment).model_dump(
exclude_none=True
),
)
]
)
def _append_arg_fragment(
self,
*,
key: str,
raw_val: str,
) -> str | None:
key = key.strip()
if not key:
return None
if key in self._seen_keys[self.current_tool_id]:
return None
# This function is only called for non-string types (already checked
# by _is_string_type in the caller), so we always deserialize.
val_obj: Any = self._deserialize(raw_val)
key_json = json.dumps(key, ensure_ascii=False)
val_json = json.dumps(val_obj, ensure_ascii=False)
if not self._args_started[self.current_tool_id]:
fragment = "{" + key_json + ":" + val_json
self._args_started[self.current_tool_id] = True
else:
fragment = "," + key_json + ":" + val_json
self._seen_keys[self.current_tool_id].add(key)
self.streamed_args_for_tool[self.current_tool_id] += fragment
return fragment
def _close_args_if_needed(self) -> str | None:
if self._args_closed[self.current_tool_id]:
return None
self._args_closed[self.current_tool_id] = True
if not self._args_started[self.current_tool_id]:
fragment = "{}"
self.streamed_args_for_tool[self.current_tool_id] = fragment
else:
fragment = "}"
self.streamed_args_for_tool[self.current_tool_id] += fragment
return fragment