@ToolParserManager.register_module("glm4_moe")
class Glm4MoeModelToolParser(ToolParser):
def __init__(self, tokenizer: AnyTokenizer):
super().__init__(tokenizer)
self.current_tool_name_sent = False
self.prev_tool_call_arr: list[dict] = []
self.current_tool_id = -1
self.streamed_args_for_tool: list[str] = []
self.tool_call_start_token = "<tool_call>"
self.tool_call_end_token = "</tool_call>"
self.tool_calls_start_token = self.tool_call_start_token
# Updated regex for the XML-based format
self.tool_call_regex = re.compile(
r"<tool_call>\s*"
r"(?P<function_name>[^\n<]+)\s*" # 函数名（到换行或 <）
r"(?P<arguments>(?:\s*<arg_key>[^<]+</arg_key>\s*"
r"<arg_value>[^<]*</arg_value>\s*)*)\s*"
r"</tool_call>",
re.DOTALL,
)
# Regex for parsing individual arguments
self.arg_regex = re.compile(
r"<arg_key>(?P<key>[^<]+)</arg_key>\s*<arg_value>(?P<value>[^<]*)</arg_value>",
re.DOTALL,
)
# Streaming regex
self.stream_tool_call_portion_regex = re.compile(
r"(?P<function_name>[^\n<]+)\s*"
r"(?P<arguments>(?:\s*<arg_key>[^<]+</arg_key>\s*"
r"<arg_value>[^<]*</arg_value>\s*)*)",
re.DOTALL,
)
# For streaming, we also need a regex to match just the function name
self.stream_tool_call_name_regex = re.compile(
r"(?P<function_name>[^\n<]+)",
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)
def _parse_arguments(self, args_text: str) -> str:
"""Parse XML-based arguments into JSON format."""
if not args_text or not args_text.strip():
return "{}"
args_dict = {}
matches = self.arg_regex.findall(args_text)
for key, value in matches:
args_dict[key.strip()] = value.strip()
import json
return json.dumps(args_dict, ensure_ascii=False)
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)
try:
# Find all tool calls in the output
function_call_matches = self.tool_call_regex.findall(model_output)
logger.debug("function_call_matches: %s", function_call_matches)
if not function_call_matches:
return ExtractedToolCallInformation(
tools_called=False,
tool_calls=[],
content=model_output,
)
tool_calls = []
for i, match in enumerate(function_call_matches):
function_name, function_args_xml = match
function_name = function_name.strip()
# Parse XML arguments to JSON
function_args_json = self._parse_arguments(function_args_xml)
tool_calls.append(
ToolCall(
id=f"call_{i}",
type='function',
function=FunctionCall(name=function_name,
arguments=function_args_json),
))
# Extract content before the first tool call
content = model_output[:model_output.find(self.
tool_calls_start_token)]
return ExtractedToolCallInformation(
tools_called=bool(tool_calls),
tool_calls=tool_calls,
content=content.strip() if content.strip() 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,
) -> Union[DeltaMessage, None]:
logger.debug("delta_text: %s", delta_text)
logger.debug("delta_token_ids: %s", delta_token_ids)
# check to see if we should be streaming a tool call - is there a
if self.tool_call_start_token_id not in current_token_ids:
logger.debug("No tool call tokens found!")
return DeltaMessage(content=delta_text)
delta_text = delta_text.replace(self.tool_calls_start_token,
"").replace(self.tool_call_end_token,
"")
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):
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")
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:
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
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:
text = delta_text.replace(self.tool_call_start_token, "")
text = text.replace(self.tool_call_end_token, "")
delta = DeltaMessage(tool_calls=[], content=text)
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('.')[1].split(':')[0]
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('.')[1].split(':')[0]
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: Union[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)
return delta
except Exception:
logger.exception("Error trying to handle streaming tool call.")
return None # do not stream a delta. skip this token ID.