@ToolParserManager.register_module("qwen3_coder")
class Qwen3CoderToolParser(ToolParser):
def __init__(self, tokenizer: AnyTokenizer):
super().__init__(tokenizer)
self.current_tool_name_sent: bool = False
self.prev_tool_call_arr: list[dict] = []
# Override base class type - we use string IDs for tool calls
self.current_tool_id: str | None = None # type: ignore
self.streamed_args_for_tool: list[str] = []
# Sentinel tokens for streaming mode
self.tool_call_start_token: str = "<tool_call>"
self.tool_call_end_token: str = "</tool_call>"
self.tool_call_prefix: str = "<function="
self.function_end_token: str = "</function>"
self.parameter_prefix: str = "<parameter="
self.parameter_end_token: str = "</parameter>"
self.is_tool_call_started: bool = False
self.failed_count: int = 0
# Enhanced streaming state - reset for each new message
self._reset_streaming_state()
# Regex patterns
self.tool_call_complete_regex = re.compile(
r"<tool_call>(.*?)</tool_call>", re.DOTALL
)
self.tool_call_regex = re.compile(
r"<tool_call>(.*?)</tool_call>|<tool_call>(.*?)$", re.DOTALL
)
self.tool_call_function_regex = re.compile(
r"<function=(.*?)</function>|<function=(.*)$", re.DOTALL
)
self.tool_call_parameter_regex = re.compile(
r"<parameter=(.*?)(?:</parameter>|(?=<parameter=)|(?=</function>)|$)",
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)
if self.tool_call_start_token_id is None or self.tool_call_end_token_id is None:
raise RuntimeError(
"Qwen3 XML Tool parser could not locate tool call start/end "
"tokens in the tokenizer!"
)
logger.info(
"vLLM Successfully import tool parser %s !", self.__class__.__name__
)
def _generate_tool_call_id(self) -> str:
"""Generate a unique tool call ID."""
return f"call_{uuid.uuid4().hex[:24]}"
def _reset_streaming_state(self):
"""Reset all streaming state."""
self.current_tool_index = 0
self.is_tool_call_started = False
self.header_sent = False
self.current_tool_id = None
self.current_function_name = None
self.current_param_name = None
self.current_param_value = ""
self.param_count = 0
self.in_param = False
self.in_function = False
self.accumulated_text = ""
self.json_started = False
self.json_closed = False
# Store accumulated parameters for type conversion
self.accumulated_params = {}
self.streaming_request = None
def _get_arguments_config(
self, func_name: str, tools: list[ChatCompletionToolsParam] | None
) -> dict:
"""Extract argument configuration for a function."""
if tools is None:
return {}
for config in tools:
if not hasattr(config, "type") or not (
hasattr(config, "function") and hasattr(config.function, "name")
):
continue
if config.type == "function" and config.function.name == func_name:
if not hasattr(config.function, "parameters"):
return {}
params = config.function.parameters
if isinstance(params, dict) and "properties" in params:
return params["properties"]
elif isinstance(params, dict):
return params
else:
return {}
logger.warning("Tool '%s' is not defined in the tools list.", func_name)
return {}
def _convert_param_value(
self, param_value: str, param_name: str, param_config: dict, func_name: str
) -> Any:
"""Convert parameter value based on its type in the schema."""
# Handle null value for any type
if param_value.lower() == "null":
return None
if param_name not in param_config:
if param_config != {}:
logger.warning(
"Parsed parameter '%s' is not defined in the tool "
"parameters for tool '%s', directly returning the "
"string value.",
param_name,
func_name,
)
return param_value
if (
isinstance(param_config[param_name], dict)
and "type" in param_config[param_name]
):
param_type = str(param_config[param_name]["type"]).strip().lower()
else:
param_type = "string"
if param_type in ["string", "str", "text", "varchar", "char", "enum"]:
return param_value
elif (
param_type.startswith("int")
or param_type.startswith("uint")
or param_type.startswith("long")
or param_type.startswith("short")
or param_type.startswith("unsigned")
):
try:
return int(param_value)
except (ValueError, TypeError):
logger.warning(
"Parsed value '%s' of parameter '%s' is not an "
"integer in tool '%s', degenerating to string.",
param_value,
param_name,
func_name,
)
return param_value
elif param_type.startswith("num") or param_type.startswith("float"):
try:
float_param_value = float(param_value)
return (
float_param_value
if float_param_value - int(float_param_value) != 0
else int(float_param_value)
)
except (ValueError, TypeError):
logger.warning(
"Parsed value '%s' of parameter '%s' is not a float "
"in tool '%s', degenerating to string.",
param_value,
param_name,
func_name,
)
return param_value
elif param_type in ["boolean", "bool", "binary"]:
param_value = param_value.lower()
if param_value not in ["true", "false"]:
logger.warning(
"Parsed value '%s' of parameter '%s' is not a boolean "
"(`true` or `false`) in tool '%s', degenerating to "
"false.",
param_value,
param_name,
func_name,
)
return param_value == "true"
else:
if (
param_type in ["object", "array", "arr"]
or param_type.startswith("dict")
or param_type.startswith("list")
):
try:
param_value = json.loads(param_value)
return param_value
except (json.JSONDecodeError, TypeError, ValueError):
logger.warning(
"Parsed value '%s' of parameter '%s' cannot be "
"parsed with json.loads in tool '%s', will try "
"other methods to parse it.",
param_value,
param_name,
func_name,
)
try:
param_value = ast.literal_eval(param_value) # safer
except (ValueError, SyntaxError, TypeError):
logger.warning(
"Parsed value '%s' of parameter '%s' cannot be "
"converted via Python `ast.literal_eval()` in tool "
"'%s', degenerating to string.",
param_value,
param_name,
func_name,
)
return param_value
def _parse_xml_function_call(
self, function_call_str: str, tools: list[ChatCompletionToolsParam] | None
) -> ToolCall | None:
# Extract function name
end_index = function_call_str.index(">")
function_name = function_call_str[:end_index]
param_config = self._get_arguments_config(function_name, tools)
parameters = function_call_str[end_index + 1 :]
param_dict = {}
for match_text in self.tool_call_parameter_regex.findall(parameters):
idx = match_text.index(">")
param_name = match_text[:idx]
param_value = str(match_text[idx + 1 :])
# Remove prefix and trailing \n
if param_value.startswith("\n"):
param_value = param_value[1:]
if param_value.endswith("\n"):
param_value = param_value[:-1]
param_dict[param_name] = self._convert_param_value(
param_value, param_name, param_config, function_name
)
return ToolCall(
type="function",
function=FunctionCall(
name=function_name, arguments=json.dumps(param_dict, ensure_ascii=False)
),
)
def _get_function_calls(self, model_output: str) -> list[str]:
# Find all tool calls
matched_ranges = self.tool_call_regex.findall(model_output)
raw_tool_calls = [
match[0] if match[0] else match[1] for match in matched_ranges
]
# Back-off strategy if no tool_call tags found
if len(raw_tool_calls) == 0:
raw_tool_calls = [model_output]
raw_function_calls = []
for tool_call in raw_tool_calls:
raw_function_calls.extend(self.tool_call_function_regex.findall(tool_call))
function_calls = [
match[0] if match[0] else match[1] for match in raw_function_calls
]
return function_calls
def extract_tool_calls(
self,
model_output: str,
request: ChatCompletionRequest,
) -> ExtractedToolCallInformation:
# Quick check to avoid unnecessary processing
if self.tool_call_prefix not in model_output:
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
try:
function_calls = self._get_function_calls(model_output)
if len(function_calls) == 0:
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
tool_calls = [
self._parse_xml_function_call(function_call_str, request.tools)
for function_call_str in function_calls
]
# Populate prev_tool_call_arr for serving layer to set finish_reason
self.prev_tool_call_arr.clear() # Clear previous calls
for tool_call in tool_calls:
if tool_call:
self.prev_tool_call_arr.append(
{
"name": tool_call.function.name,
"arguments": tool_call.function.arguments,
}
)
# Extract content before tool calls
content_index = model_output.find(self.tool_call_start_token)
idx = model_output.find(self.tool_call_prefix)
content_index = content_index if content_index >= 0 else idx
content = model_output[:content_index] # .rstrip()
return ExtractedToolCallInformation(
tools_called=(len(tool_calls) > 0),
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:
# Store request for type conversion
if not previous_text:
self._reset_streaming_state()
self.streaming_request = request
# If no delta text, return None unless it's an EOS token after tools
if not delta_text:
# Check if this is an EOS token after all tool calls are complete
# Check for tool calls in text even if is_tool_call_started
# is False (might have been reset after processing all tools)
if delta_token_ids and self.tool_call_end_token_id not in delta_token_ids:
# Count complete tool calls
complete_calls = len(
self.tool_call_complete_regex.findall(current_text)
)
# If we have completed tool calls and populated
# prev_tool_call_arr
if complete_calls > 0 and len(self.prev_tool_call_arr) > 0:
# Check if all tool calls are closed
open_calls = current_text.count(
self.tool_call_start_token
) - current_text.count(self.tool_call_end_token)
if open_calls == 0:
# Return empty delta for finish_reason processing
return DeltaMessage(content="")
elif not self.is_tool_call_started and current_text:
# This is a regular content response that's now complete
return DeltaMessage(content="")
return None
# Update accumulated text
self.accumulated_text = current_text
# Check if we need to advance to next tool
if self.json_closed and not self.in_function:
# Check if this tool call has ended
tool_ends = current_text.count(self.tool_call_end_token)
if tool_ends > self.current_tool_index:
# This tool has ended, advance to next
self.current_tool_index += 1
self.header_sent = False
self.param_count = 0
self.json_started = False
self.json_closed = False
self.accumulated_params = {}
# Check if there are more tool calls
tool_starts = current_text.count(self.tool_call_start_token)
if self.current_tool_index >= tool_starts:
# No more tool calls
self.is_tool_call_started = False
# Continue processing next tool
return None
# Handle normal content before tool calls
if not self.is_tool_call_started:
# Check if tool call is starting
if (
self.tool_call_start_token_id in delta_token_ids
or self.tool_call_start_token in delta_text
):
self.is_tool_call_started = True
# Return any content before the tool call
if self.tool_call_start_token in delta_text:
content_before = delta_text[
: delta_text.index(self.tool_call_start_token)
]
if content_before:
return DeltaMessage(content=content_before)
return None
else:
# Check if we're between tool calls - skip whitespace
if (
current_text.rstrip().endswith(self.tool_call_end_token)
and delta_text.strip() == ""
):
# We just ended a tool call, skip whitespace
return None
# Normal content, no tool call
return DeltaMessage(content=delta_text)
# Check if we're between tool calls (waiting for next one)
# Count tool calls we've seen vs processed
tool_starts_count = current_text.count(self.tool_call_start_token)
if self.current_tool_index >= tool_starts_count:
# We're past all tool calls, shouldn't be here
return None
# We're in a tool call, find the current tool call portion
# Need to find the correct tool call based on current_tool_index
tool_start_positions: list[int] = []
idx = 0
while True:
idx = current_text.find(self.tool_call_start_token, idx)
if idx == -1:
break
tool_start_positions.append(idx)
idx += len(self.tool_call_start_token)
if self.current_tool_index >= len(tool_start_positions):
# No more tool calls to process yet
return None
tool_start_idx = tool_start_positions[self.current_tool_index]
# Find where this tool call ends (or current position if not ended yet)
tool_end_idx = current_text.find(self.tool_call_end_token, tool_start_idx)
if tool_end_idx == -1:
tool_text = current_text[tool_start_idx:]
else:
tool_text = current_text[
tool_start_idx : tool_end_idx + len(self.tool_call_end_token)
]
# Looking for function header
if not self.header_sent:
if self.tool_call_prefix in tool_text:
func_start = tool_text.find(self.tool_call_prefix) + len(
self.tool_call_prefix
)
func_end = tool_text.find(">", func_start)
if func_end != -1:
# Found complete function name
self.current_function_name = tool_text[func_start:func_end]
self.current_tool_id = self._generate_tool_call_id()
self.header_sent = True
self.in_function = True
# IMPORTANT: Add to prev_tool_call_arr immediately when
# we detect a tool call. This ensures
# finish_reason="tool_calls" even if parsing isn't complete
already_added = any(
tool.get("name") == self.current_function_name
for tool in self.prev_tool_call_arr
)
if not already_added:
self.prev_tool_call_arr.append(
{
"name": self.current_function_name,
"arguments": "{}", # Placeholder, will be updated later
}
)
# Send header with function info
return DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_index,
id=self.current_tool_id,
function=DeltaFunctionCall(
name=self.current_function_name, arguments=""
),
type="function",
)
]
)
return None
# We've sent header, now handle function body
if self.in_function:
# Send opening brace if not sent yet
if not self.json_started and self.parameter_prefix not in delta_text:
self.json_started = True
return DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_index,
function=DeltaFunctionCall(arguments="{"),
)
]
)
# Make sure json_started is set if we're processing parameters
if not self.json_started:
self.json_started = True
# Check for function end in accumulated text
if not self.json_closed and self.function_end_token in tool_text:
# Close JSON
self.json_closed = True
# Extract complete tool call to update
# prev_tool_call_arr with final arguments
# Find the function content
func_start = tool_text.find(self.tool_call_prefix) + len(
self.tool_call_prefix
)
func_content_end = tool_text.find(self.function_end_token, func_start)
if func_content_end != -1:
func_content = tool_text[func_start:func_content_end]
# Parse to get the complete arguments
try:
parsed_tool = self._parse_xml_function_call(
func_content,
self.streaming_request.tools
if self.streaming_request
else None,
)
if parsed_tool:
# Update existing entry in
# prev_tool_call_arr with complete args
for i, tool in enumerate(self.prev_tool_call_arr):
if tool.get("name") == parsed_tool.function.name:
args = parsed_tool.function.arguments
self.prev_tool_call_arr[i]["arguments"] = args
break
except Exception:
pass # Ignore parsing errors during streaming
result = DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_index,
function=DeltaFunctionCall(arguments="}"),
)
]
)
# Reset state for next tool
self.in_function = False
self.json_closed = True
self.accumulated_params = {}
return result
# Look for parameters
# Find all parameter starts
param_starts = []
idx = 0
while True:
idx = tool_text.find(self.parameter_prefix, idx)
if idx == -1:
break
param_starts.append(idx)
idx += len(self.parameter_prefix)
# Check if we should start a new parameter
if (
not self.in_param
and self.param_count < len(param_starts)
and len(param_starts) > self.param_count
):
# Process the next parameter
param_idx = param_starts[self.param_count]
param_start = param_idx + len(self.parameter_prefix)
remaining = tool_text[param_start:]
if ">" in remaining:
# We have the complete parameter name
name_end = remaining.find(">")
self.current_param_name = remaining[:name_end]
# Find the parameter value
value_start = param_start + name_end + 1
value_text = tool_text[value_start:]
if value_text.startswith("\n"):
value_text = value_text[1:]
# Find where this parameter ends
param_end_idx = value_text.find(self.parameter_end_token)
if param_end_idx == -1:
# No closing tag, look for next parameter or
# function end
next_param_idx = value_text.find(self.parameter_prefix)
func_end_idx = value_text.find(self.function_end_token)
if next_param_idx != -1 and (
func_end_idx == -1 or next_param_idx < func_end_idx
):
param_end_idx = next_param_idx
elif func_end_idx != -1:
param_end_idx = func_end_idx
else:
# Neither found, check if tool call is complete
if self.tool_call_end_token in tool_text:
# Tool call is complete, so parameter
# must be complete too. Use all
# remaining text before function end
param_end_idx = len(value_text)
else:
# Still streaming, wait for more content
return None
if param_end_idx != -1:
# Complete parameter found
param_value = value_text[:param_end_idx]
if param_value.endswith("\n"):
param_value = param_value[:-1]
# Store raw value for later processing
self.accumulated_params[self.current_param_name] = param_value
# Get parameter configuration for type conversion
param_config = self._get_arguments_config(
self.current_function_name or "",
self.streaming_request.tools
if self.streaming_request
else None,
)
# Convert param value to appropriate type
converted_value = self._convert_param_value(
param_value,
self.current_param_name,
param_config,
self.current_function_name or "",
)
# Build JSON fragment based on the converted type
# Use json.dumps to properly serialize the value
serialized_value = json.dumps(
converted_value, ensure_ascii=False
)
if self.param_count == 0:
json_fragment = (
f'"{self.current_param_name}": {serialized_value}'
)
else:
json_fragment = (
f', "{self.current_param_name}": {serialized_value}'
)
self.param_count += 1
return DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_index,
function=DeltaFunctionCall(arguments=json_fragment),
)
]
)
# Continue parameter value - Not used in the current implementation
# since we process complete parameters above
if self.in_param:
if self.parameter_end_token in delta_text:
# End of parameter
end_idx = delta_text.find(self.parameter_end_token)
value_chunk = delta_text[:end_idx]
# Skip past > if at start
if not self.current_param_value and ">" in value_chunk:
gt_idx = value_chunk.find(">")
value_chunk = value_chunk[gt_idx + 1 :]
if not self.current_param_value and value_chunk.startswith("\n"):
value_chunk = value_chunk[1:]
# Store complete value
full_value = self.current_param_value + value_chunk
self.accumulated_params[self.current_param_name] = full_value
# Get parameter configuration for type conversion
param_config = self._get_arguments_config(
self.current_function_name or "",
self.streaming_request.tools
if self.streaming_request
else None,
)
# Convert the parameter value to the appropriate type
converted_value = self._convert_param_value(
full_value,
self.current_param_name or "",
param_config,
self.current_function_name or "",
)
# Serialize the converted value
serialized_value = json.dumps(converted_value, ensure_ascii=False)
# Since we've been streaming the quoted version,
# we need to close it properly
# This is complex - for now just complete the value
self.in_param = False
self.current_param_value = ""
# Just close the current parameter string
return DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_index,
function=DeltaFunctionCall(
arguments='"'
), # Close the string quote
)
]
)
else:
# Continue accumulating value
value_chunk = delta_text
# Handle first chunk after param name
if not self.current_param_value and ">" in value_chunk:
gt_idx = value_chunk.find(">")
value_chunk = value_chunk[gt_idx + 1 :]
if not self.current_param_value and value_chunk.startswith("\n"):
value_chunk = value_chunk[1:]
if value_chunk:
# Stream the escaped delta
prev_escaped = (
json.dumps(self.current_param_value, ensure_ascii=False)[
1:-1
]
if self.current_param_value
else ""
)
self.current_param_value += value_chunk
full_escaped = json.dumps(
self.current_param_value, ensure_ascii=False
)[1:-1]
delta_escaped = full_escaped[len(prev_escaped) :]
if delta_escaped:
return DeltaMessage(
tool_calls=[
DeltaToolCall(
index=self.current_tool_index,
function=DeltaFunctionCall(
arguments=delta_escaped
),
)
]
)
return None