diff --git a/vllm/entrypoints/openai/tool_parsers/glm4_moe_tool_parser.py b/vllm/entrypoints/openai/tool_parsers/glm4_moe_tool_parser.py
index 40cdf7275a8f6..8fd14f171d0af 100644
--- a/vllm/entrypoints/openai/tool_parsers/glm4_moe_tool_parser.py
+++ b/vllm/entrypoints/openai/tool_parsers/glm4_moe_tool_parser.py
@@ -1,13 +1,15 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-# code modified from deepseekv3_tool_parser.py
+import ast
+import json
from collections.abc import Sequence
-from typing import Union
+from typing import Any, Optional, Union
import regex as re
from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
+ ChatCompletionToolsParam,
DeltaFunctionCall, DeltaMessage,
DeltaToolCall,
ExtractedToolCallInformation,
@@ -34,36 +36,13 @@ class Glm4MoeModelToolParser(ToolParser):
self.tool_calls_start_token = self.tool_call_start_token
- # Updated regex for the XML-based format
- self.tool_call_regex = re.compile(
- r"\s*"
- r"(?P[^\n<]+)\s*" # 函数名（到换行或 <）
- r"(?P(?:\s*[^<]+\s*"
- r"[^<]*\s*)*)\s*"
- r"",
- re.DOTALL,
- )
-
- # Regex for parsing individual arguments
- self.arg_regex = re.compile(
- r"(?P[^<]+)\s*(?P[^<]*)",
- re.DOTALL,
- )
-
- # Streaming regex
- self.stream_tool_call_portion_regex = re.compile(
- r"(?P[^\n<]+)\s*"
- r"(?P(?:\s*[^<]+\s*"
- r"[^<]*\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[^\n<]+)",
- re.DOTALL,
- )
-
+ self.func_call_regex = re.compile(r".*?",
+ re.DOTALL)
+ self.func_detail_regex = re.compile(
+ r"([^\n]*)\n(.*)", re.DOTALL)
+ self.func_arg_regex = re.compile(
+ r"(.*?)\s*(.*?)",
+ re.DOTALL)
if not self.model_tokenizer:
raise ValueError(
"The model tokenizer must be passed to the ToolParser "
@@ -72,20 +51,7 @@ class Glm4MoeModelToolParser(ToolParser):
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)
+ self._buffer = ""
def extract_tool_calls(
self,
@@ -93,52 +59,67 @@ class Glm4MoeModelToolParser(ToolParser):
request: ChatCompletionRequest,
) -> ExtractedToolCallInformation:
- # sanity check; avoid unnecessary processing
- if self.tool_calls_start_token not in model_output:
+ def _is_string_type(
+ tool_name: str, arg_name: str,
+ tools: Optional[list[ChatCompletionToolsParam]]) -> bool:
+ if tools is None:
+ return False
+ for tool in tools:
+ if tool.function.name == tool_name:
+ 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.warning("No tool named '%s'.", tool_name)
+ return False
+
+ def _deserialize(value: str) -> Any:
+ try:
+ return json.loads(value)
+ except Exception:
+ pass
+
+ try:
+ return ast.literal_eval(value)
+ except Exception:
+ pass
+ return value
+
+ matched_tool_calls = self.func_call_regex.findall(model_output)
+ logger.debug("model_output: %s", model_output)
+ try:
+ tool_calls = []
+ for match in matched_tool_calls:
+ tc_detail = self.func_detail_regex.search(match)
+ tc_name = tc_detail.group(1)
+ tc_args = tc_detail.group(2)
+ pairs = self.func_arg_regex.findall(tc_args)
+ arg_dct = {}
+ for key, value in pairs:
+ arg_key = key.strip()
+ arg_val = value.strip()
+ if not _is_string_type(tc_name, arg_key, request.tools):
+ arg_val = _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))))
+ except Exception:
+ logger.exception("Failed to extract tool call spec")
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.")
+ 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)
@@ -153,250 +134,52 @@ class Glm4MoeModelToolParser(ToolParser):
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._buffer += delta_text
+ cur_text = self._buffer
+ start_idx = cur_text.find(self.tool_call_start_token)
+ if start_idx == -1:
+ self._buffer = ""
+ if self.current_tool_id > 0:
+ cur_text = ""
+ return DeltaMessage(content=cur_text)
+ logger.debug("cur_text = %s", cur_text)
+ end_idx = cur_text.find(self.tool_call_end_token)
+ if end_idx != -1:
+ if self.current_tool_id == -1:
+ self.current_tool_id = 0
+ self.prev_tool_call_arr = []
+ self.streamed_args_for_tool = []
+ while len(self.prev_tool_call_arr) <= self.current_tool_id:
self.prev_tool_call_arr.append({})
+ while len(self.streamed_args_for_tool) <= self.current_tool_id:
+ self.streamed_args_for_tool.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")
+ extracted_tool_calls = self.extract_tool_calls(
+ cur_text[:end_idx + len(self.tool_call_end_token)], request)
- 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),
- )
+ if len(extracted_tool_calls.tool_calls) == 0:
+ logger.warning("Failed to extract any tool calls.")
+ return None
+ tool_call = extracted_tool_calls.tool_calls[0]
+ self.prev_tool_call_arr[self.current_tool_id] = {
+ "name": tool_call.function.name,
+ "arguments": json.loads(tool_call.function.arguments)
+ }
+ self.streamed_args_for_tool[
+ self.current_tool_id] = tool_call.function.arguments
+ delta = DeltaMessage(
+ content=extracted_tool_calls.content,
+ tool_calls=[
+ DeltaToolCall(index=self.current_tool_id,
+ id=tool_call.id,
+ type=tool_call.type,
+ function=DeltaFunctionCall(
+ name=tool_call.function.name,
+ arguments=tool_call.function.arguments))
])
- 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)
-
+ self.current_tool_id += 1
+ self._buffer = cur_text[end_idx + len(self.tool_call_end_token):]
return delta
- except Exception:
- logger.exception("Error trying to handle streaming tool call.")
- return None # do not stream a delta. skip this token ID.
+ self._buffer = cur_text[start_idx:]
+ return DeltaMessage(content=cur_text[:start_idx])