vLLM has remote code execution vulnerability in the tool call parser for Qwen3-Coder
Description
Summary
An unsafe deserialization vulnerability allows any authenticated user to execute arbitrary code on the server if they are able to get the model to pass the code as an argument to a tool call.
### Details vLLM's Qwen3 Coder tool parser contains a code execution path that uses Python's eval() function to parse tool call parameters. This occurs during the parameter conversion process when the parser attempts to handle unknown data types.
This code path is reached when: 1. Tool calling is enabled (--enable-auto-tool-choice) 2. The qwen3_coder parser is specified (--tool-call-parser qwen3_coder) 3. The parameter type is not explicitly defined or recognized
Impact
Remote Code Execution via Python's eval() function.
Affected packages
Versions sourced from the GitHub Security Advisory.
| Package | Affected versions | Patched versions |
|---|---|---|
vllmPyPI | >= 0.10.0, < 0.10.1.1 | 0.10.1.1 |
Affected products
1Patches
14594fc3b2817[Model] Add Qwen3CoderToolParser (#21396)
3 files changed · +1289 −0
tests/tool_use/test_qwen3coder_tool_parser.py+618 −0 added@@ -0,0 +1,618 @@ +# SPDX-License-Identifier: Apache-2.0 +# SPDX-FileCopyrightText: Copyright contributors to the vLLM project + +import json +from collections.abc import Generator +from typing import Optional + +import pytest + +from vllm.entrypoints.openai.protocol import (ChatCompletionRequest, + ChatCompletionToolsParam, + DeltaMessage, FunctionCall, + ToolCall) +from vllm.entrypoints.openai.tool_parsers.qwen3coder_tool_parser import ( + Qwen3CoderToolParser) +from vllm.transformers_utils.detokenizer import detokenize_incrementally +from vllm.transformers_utils.tokenizer import AnyTokenizer, get_tokenizer + +MODEL = "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8" + + +@pytest.fixture(scope="module") +def qwen3_tokenizer(): + return get_tokenizer(tokenizer_name=MODEL) + + +@pytest.fixture +def qwen3_tool_parser(qwen3_tokenizer): + return Qwen3CoderToolParser(qwen3_tokenizer) + + +@pytest.fixture +def sample_tools(): + return [ + ChatCompletionToolsParam(type="function", + function={ + "name": "get_current_weather", + "description": "Get the current weather", + "parameters": { + "type": "object", + "properties": { + "city": { + "type": "string", + "description": "The city name" + }, + "state": { + "type": "string", + "description": + "The state code" + }, + "unit": { + "type": "string", + "enum": + ["fahrenheit", "celsius"] + } + }, + "required": ["city", "state"] + } + }), + ChatCompletionToolsParam(type="function", + function={ + "name": "calculate_area", + "description": + "Calculate area of a shape", + "parameters": { + "type": "object", + "properties": { + "shape": { + "type": "string" + }, + "dimensions": { + "type": "object" + }, + "precision": { + "type": "integer" + } + } + } + }) + ] + + +def assert_tool_calls(actual_tool_calls: list[ToolCall], + expected_tool_calls: list[ToolCall]): + assert len(actual_tool_calls) == len(expected_tool_calls) + + for actual_tool_call, expected_tool_call in zip(actual_tool_calls, + expected_tool_calls): + # Qwen3 parser doesn't generate IDs during extraction + assert actual_tool_call.type == "function" + assert ( + actual_tool_call.function.name == expected_tool_call.function.name) + assert (json.loads(actual_tool_call.function.arguments) == json.loads( + expected_tool_call.function.arguments)) + + +def stream_delta_message_generator( + qwen3_tool_parser: Qwen3CoderToolParser, + qwen3_tokenizer: AnyTokenizer, + model_output: str, + request: Optional[ChatCompletionRequest] = None +) -> Generator[DeltaMessage, None, None]: + all_token_ids = qwen3_tokenizer.encode(model_output, + add_special_tokens=False) + + previous_text = "" + previous_tokens = None + prefix_offset = 0 + read_offset = 0 + for i, delta_token in enumerate(all_token_ids): + delta_token_ids = [delta_token] + previous_token_ids = all_token_ids[:i] + current_token_ids = all_token_ids[:i + 1] + + (new_tokens, delta_text, new_prefix_offset, + new_read_offset) = detokenize_incrementally( + tokenizer=qwen3_tokenizer, + all_input_ids=current_token_ids, + prev_tokens=previous_tokens, + prefix_offset=prefix_offset, + read_offset=read_offset, + skip_special_tokens=False, + spaces_between_special_tokens=True, + ) + + current_text = previous_text + delta_text + + delta_message = qwen3_tool_parser.extract_tool_calls_streaming( + previous_text, + current_text, + delta_text, + previous_token_ids, + current_token_ids, + delta_token_ids, + request=request, + ) + if delta_message: + yield delta_message + + previous_text = current_text + previous_tokens = (previous_tokens + + new_tokens if previous_tokens else new_tokens) + prefix_offset = new_prefix_offset + read_offset = new_read_offset + + +def test_extract_tool_calls_no_tools(qwen3_tool_parser): + model_output = "This is a test response without any tool calls" + extracted_tool_calls = qwen3_tool_parser.extract_tool_calls( + model_output, request=None) # type: ignore[arg-type] + assert not extracted_tool_calls.tools_called + assert extracted_tool_calls.tool_calls == [] + assert extracted_tool_calls.content == model_output + + +@pytest.mark.parametrize( + ids=[ + "single_tool", + "single_tool_with_content", + "single_tool_multiline_param", + "parallel_tools", + "tool_with_typed_params", + ], + argnames=["model_output", "expected_tool_calls", "expected_content"], + argvalues=[ + ('''<tool_call> +<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +<parameter=unit> +fahrenheit +</parameter> +</function> +</tool_call>''', [ + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Dallas", + "state": "TX", + "unit": "fahrenheit" + }))) + ], None), + ('''Sure! Let me check the weather for you.<tool_call> +<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +<parameter=unit> +fahrenheit +</parameter> +</function> +</tool_call>''', [ + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Dallas", + "state": "TX", + "unit": "fahrenheit" + }))) + ], "Sure! Let me check the weather for you."), + ('''<tool_call> +<function=calculate_area> +<parameter=shape> +rectangle +</parameter> +<parameter=dimensions> +{"width": 10, + "height": 20} +</parameter> +<parameter=precision> +2 +</parameter> +</function> +</tool_call>''', [ + ToolCall(function=FunctionCall(name="calculate_area", + arguments=json.dumps({ + "shape": "rectangle", + "dimensions": { + "width": 10, + "height": 20 + }, + "precision": 2 + }))) + ], None), + ('''<tool_call> +<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +<parameter=unit> +fahrenheit +</parameter> +</function> +</tool_call> +<tool_call> +<function=get_current_weather> +<parameter=city> +Orlando +</parameter> +<parameter=state> +FL +</parameter> +<parameter=unit> +fahrenheit +</parameter> +</function> +</tool_call>''', [ + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Dallas", + "state": "TX", + "unit": "fahrenheit" + }))), + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Orlando", + "state": "FL", + "unit": "fahrenheit" + }))) + ], None), + ('''Let me calculate that area for you.<tool_call> +<function=calculate_area> +<parameter=shape> +circle +</parameter> +<parameter=dimensions> +{"radius": 15.5} +</parameter> +<parameter=precision> +3 +</parameter> +</function> +</tool_call>''', [ + ToolCall(function=FunctionCall(name="calculate_area", + arguments=json.dumps({ + "shape": "circle", + "dimensions": { + "radius": 15.5 + }, + "precision": 3 + }))) + ], "Let me calculate that area for you."), + ], +) +def test_extract_tool_calls(qwen3_tool_parser, sample_tools, model_output, + expected_tool_calls, expected_content): + request = ChatCompletionRequest(model=MODEL, + messages=[], + tools=sample_tools) + extracted_tool_calls = qwen3_tool_parser.extract_tool_calls( + model_output, request=request) + assert extracted_tool_calls.tools_called + + assert_tool_calls(extracted_tool_calls.tool_calls, expected_tool_calls) + + assert extracted_tool_calls.content == expected_content + + +def test_extract_tool_calls_fallback_no_tags(qwen3_tool_parser, sample_tools): + """Test fallback parsing when XML tags are missing""" + model_output = '''<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +</function>''' + + request = ChatCompletionRequest(model=MODEL, + messages=[], + tools=sample_tools) + extracted_tool_calls = qwen3_tool_parser.extract_tool_calls( + model_output, request=request) + + assert extracted_tool_calls.tools_called + assert len(extracted_tool_calls.tool_calls) == 1 + assert (extracted_tool_calls.tool_calls[0].function.name == + "get_current_weather") + + +def test_extract_tool_calls_type_conversion(qwen3_tool_parser): + """Test parameter type conversion based on tool schema""" + tools = [ + ChatCompletionToolsParam(type="function", + function={ + "name": "test_types", + "parameters": { + "type": "object", + "properties": { + "int_param": { + "type": "integer" + }, + "float_param": { + "type": "float" + }, + "bool_param": { + "type": "boolean" + }, + "str_param": { + "type": "string" + }, + "obj_param": { + "type": "object" + } + } + } + }) + ] + + model_output = '''<tool_call> +<function=test_types> +<parameter=int_param> +42 +</parameter> +<parameter=float_param> +3.14 +</parameter> +<parameter=bool_param> +true +</parameter> +<parameter=str_param> +hello world +</parameter> +<parameter=obj_param> +{"key": "value"} +</parameter> +</function> +</tool_call>''' + + request = ChatCompletionRequest(model=MODEL, messages=[], tools=tools) + extracted_tool_calls = qwen3_tool_parser.extract_tool_calls( + model_output, request=request) + + args = json.loads(extracted_tool_calls.tool_calls[0].function.arguments) + assert args["int_param"] == 42 + assert args["float_param"] == 3.14 + assert args["bool_param"] is True + assert args["str_param"] == "hello world" + assert args["obj_param"] == {"key": "value"} + + +@pytest.mark.parametrize( + ids=[ + "no_tools", + "single_tool", + "single_tool_with_content", + "parallel_tools", + ], + argnames=["model_output", "expected_tool_calls", "expected_content"], + argvalues=[ + ("This is a test without tools", [], "This is a test without tools"), + ('''<tool_call> +<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +<parameter=unit> +fahrenheit +</parameter> +</function> +</tool_call>''', [ + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Dallas", + "state": "TX", + "unit": "fahrenheit" + }))) + ], ""), + ('''Sure! Let me check the weather for you.<tool_call> +<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +<parameter=unit> +fahrenheit +</parameter> +</function> +</tool_call>''', [ + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Dallas", + "state": "TX", + "unit": "fahrenheit" + }))) + ], "Sure! Let me check the weather for you."), + ('''<tool_call> +<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +<parameter=unit> +fahrenheit +</parameter> +</function> +</tool_call> +<tool_call> +<function=get_current_weather> +<parameter=city> +Orlando +</parameter> +<parameter=state> +FL +</parameter> +<parameter=unit> +celsius +</parameter> +</function> +</tool_call>''', [ + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Dallas", + "state": "TX", + "unit": "fahrenheit" + }))), + ToolCall( + function=FunctionCall(name="get_current_weather", + arguments=json.dumps({ + "city": "Orlando", + "state": "FL", + "unit": "celsius" + }))) + ], ""), + ], +) +def test_extract_tool_calls_streaming(qwen3_tool_parser, qwen3_tokenizer, + sample_tools, model_output, + expected_tool_calls, expected_content): + """Test incremental streaming behavior""" + request = ChatCompletionRequest(model=MODEL, + messages=[], + tools=sample_tools) + + other_content = '' + tool_states = {} # Track state per tool index + + for delta_message in stream_delta_message_generator( + qwen3_tool_parser, qwen3_tokenizer, model_output, request): + # role should never be streamed from tool parser + assert not delta_message.role + + if delta_message.content: + other_content += delta_message.content + + if delta_message.tool_calls: + for tool_call in delta_message.tool_calls: + idx = tool_call.index + + # Initialize state for new tool + if idx not in tool_states: + tool_states[idx] = { + "id": None, + "name": None, + "arguments": "", + "type": None + } + + # First chunk should have id, name, and type + if tool_call.id: + tool_states[idx]["id"] = tool_call.id + + if tool_call.type: + assert tool_call.type == "function" + tool_states[idx]["type"] = tool_call.type + + if tool_call.function: + if tool_call.function.name: + # Should only be set once + assert tool_states[idx]["name"] is None + tool_states[idx]["name"] = tool_call.function.name + + if tool_call.function.arguments is not None: + # Accumulate arguments incrementally + tool_states[idx][ + "arguments"] += tool_call.function.arguments + + # Verify final content + assert other_content == expected_content + + # Verify we got all expected tool calls + assert len(tool_states) == len(expected_tool_calls) + + # Verify each tool call + for idx, expected_tool in enumerate(expected_tool_calls): + state = tool_states[idx] + assert state["id"] is not None + assert state["type"] == "function" + assert state["name"] == expected_tool.function.name + + # Parse accumulated arguments + arguments_str = state["arguments"] + assert arguments_str is not None + actual_args = json.loads(arguments_str) + expected_args = json.loads(expected_tool.function.arguments) + assert actual_args == expected_args + + +def test_extract_tool_calls_streaming_incremental(qwen3_tool_parser, + qwen3_tokenizer, + sample_tools): + """Test that streaming is truly incremental""" + model_output = '''I'll check the weather.<tool_call> +<function=get_current_weather> +<parameter=city> +Dallas +</parameter> +<parameter=state> +TX +</parameter> +</function> +</tool_call>''' + + request = ChatCompletionRequest(model=MODEL, + messages=[], + tools=sample_tools) + + chunks = [] + for delta_message in stream_delta_message_generator( + qwen3_tool_parser, qwen3_tokenizer, model_output, request): + chunks.append(delta_message) + + # Should have multiple chunks + assert len(chunks) > 3 + + # First chunk(s) should be content + assert chunks[0].content is not None + assert chunks[0].tool_calls is None or chunks[0].tool_calls == [] + + # Should have a chunk with tool header (id, name, type) + header_found = False + for chunk in chunks: + if chunk.tool_calls and chunk.tool_calls[0].id: + header_found = True + assert (chunk.tool_calls[0].function.name == "get_current_weather") + assert chunk.tool_calls[0].type == "function" + # Empty initially + assert chunk.tool_calls[0].function.arguments == "" + break + assert header_found + + # Should have chunks with incremental arguments + arg_chunks = [] + for chunk in chunks: + if chunk.tool_calls and chunk.tool_calls[0].function.arguments: + arg_chunks.append(chunk.tool_calls[0].function.arguments) + + # Arguments should be streamed incrementally + assert len(arg_chunks) > 1 + + # Concatenated arguments should form valid JSON + full_args = "".join(arg_chunks) + parsed_args = json.loads(full_args) + assert parsed_args["city"] == "Dallas" + assert parsed_args["state"] == "TX"
vllm/entrypoints/openai/tool_parsers/__init__.py+2 −0 modified@@ -17,6 +17,7 @@ from .mistral_tool_parser import MistralToolParser from .phi4mini_tool_parser import Phi4MiniJsonToolParser from .pythonic_tool_parser import PythonicToolParser +from .qwen3coder_tool_parser import Qwen3CoderToolParser from .xlam_tool_parser import xLAMToolParser __all__ = [ @@ -38,4 +39,5 @@ "KimiK2ToolParser", "HunyuanA13BToolParser", "Glm4MoeModelToolParser", + "Qwen3CoderToolParser", ]
vllm/entrypoints/openai/tool_parsers/qwen3coder_tool_parser.py+669 −0 added@@ -0,0 +1,669 @@ +# SPDX-License-Identifier: Apache-2.0 +# SPDX-FileCopyrightText: Copyright contributors to the vLLM project + +import json +import uuid +from collections.abc import Sequence +from typing import Any, Optional, Union + +import regex as re + +from vllm.entrypoints.openai.protocol import (ChatCompletionRequest, + ChatCompletionToolsParam, + DeltaFunctionCall, DeltaMessage, + DeltaToolCall, + ExtractedToolCallInformation, + FunctionCall, ToolCall) +from vllm.entrypoints.openai.tool_parsers.abstract_tool_parser import ( + ToolParser, ToolParserManager) +from vllm.logger import init_logger +from vllm.transformers_utils.tokenizer import AnyTokenizer + +logger = init_logger(__name__) + + +@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] = [] + 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 + + # Streaming state variables + self.current_tool_index: int = 0 + self.header_sent: bool = False + self.current_tool_string_id: Optional[str] = None + self.current_function_name: Optional[str] = None + self.current_param_name: Optional[str] = None + self.current_param_value: str = "" + self.param_count: int = 0 + self.in_param: bool = False + self.in_function: bool = False + self.accumulated_text: str = "" + self.json_started: bool = False + self.json_closed: bool = False + + # 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=(.*?)$", 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.debug("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_string_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 + + def _parse_xml_function_call( + self, function_call_str: str, + tools: Optional[list[ChatCompletionToolsParam]] + ) -> Optional[ToolCall]: + + def get_arguments_config(func_name: str) -> dict: + 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(param_value: str, param_name: str, + param_config: dict, func_name: str) -> Any: + # Handle null value for any type + if param_value.lower() == "null": + return None + + converted_value: Any + + 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: + converted_value = int(param_value) + return converted_value + except ValueError: + 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) + converted_value = (float_param_value if float_param_value - + int(float_param_value) != 0 else + int(float_param_value)) + return converted_value + except ValueError: + 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` of `false`) in tool '%s', " + "degenerating to false.", param_value, param_name, + func_name) + return param_value == "true" + else: + if param_type == "object" or param_type.startswith("dict"): + try: + converted_value = json.loads(param_value) + return converted_value + except json.JSONDecodeError: + logger.warning( + "Parsed value '%s' of parameter '%s' is not a " + "valid JSON object in tool '%s', will try other " + "methods to parse it.", param_value, param_name, + func_name) + try: + converted_value = eval(param_value) + return converted_value + except Exception: + logger.warning( + "Parsed value '%s' of parameter '%s' cannot be " + "converted via Python `eval()` in tool '%s', " + "degenerating to string.", param_value, param_name, + func_name) + return param_value + + # Extract function name + end_index = function_call_str.index(">") + function_name = function_call_str[:end_index] + param_config = get_arguments_config(function_name) + parameters = function_call_str[end_index + 1:] + param_dict = {} + for match in self.tool_call_parameter_regex.findall(parameters): + match_text = match[0] if match[0] else match[1] + 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] = 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) + content_index = (content_index if content_index >= 0 else + model_output.find(self.tool_call_prefix)) + 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, + ) -> Union[DeltaMessage, None]: + # If no delta text, return None unless it's an EOS token after tool + # calls + if not delta_text: + # Check if this is an EOS token after all tool calls are complete + # We check for tool calls in the text even if is_tool_call_started + # is False because it 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 message to allow 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 + + # Check if this is the first call (reset state if needed) + if not previous_text: + self._reset_streaming_state() + + # 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 + + # Check if there are more tool calls + tool_starts_count = current_text.count( + self.tool_call_start_token) + if self.current_tool_index >= tool_starts_count: + # 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_starts: list[int] = [] + idx = 0 + while True: + idx = current_text.find(self.tool_call_start_token, idx) + if idx == -1: + break + tool_starts.append(idx) + idx += len(self.tool_call_start_token) + + if self.current_tool_index >= len(tool_starts): + # No more tool calls to process yet + return None + + tool_start_idx = tool_starts[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_string_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_string_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 the 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, request.tools if request else None) + if parsed_tool: + # Update existing entry in prev_tool_call_arr with + # complete arguments + for i, tool in enumerate(self.prev_tool_call_arr): + if (tool.get("name") == + parsed_tool.function.name): + self.prev_tool_call_arr[i]["arguments"] = ( + parsed_tool.function.arguments) + 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 + + return result + + # Look for parameters + # Count how many complete parameters we have processed + complete_params = tool_text.count(self.parameter_end_token) + + # Check if we should start a new parameter + if not self.in_param and self.param_count < complete_params: + # Find the unprocessed parameter + # Count 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) + + if 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: + # Complete parameter found + param_value = value_text[:param_end_idx] + if param_value.endswith("\n"): + param_value = param_value[:-1] + + # Build complete JSON fragment for this parameter + if self.param_count == 0: + json_fragment = ( + '"' + self.current_param_name + '": "' + + json.dumps(param_value)[1:-1] + '"') + else: + json_fragment = ( + ', "' + self.current_param_name + '": "' + + json.dumps(param_value)[1:-1] + '"') + + self.param_count += 1 + + return DeltaMessage(tool_calls=[ + DeltaToolCall( + index=self.current_tool_index, + function=DeltaFunctionCall( + arguments=json_fragment), + ) + ]) + + # Continue parameter value + 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:] + + # Calculate incremental JSON + full_value = self.current_param_value + value_chunk + prev_escaped = (json.dumps(self.current_param_value)[1:-1] + if self.current_param_value else "") + full_escaped = json.dumps(full_value)[1:-1] + delta_escaped = full_escaped[len(prev_escaped):] + + self.in_param = False + self.current_param_value = "" + + return DeltaMessage(tool_calls=[ + DeltaToolCall( + index=self.current_tool_index, + function=DeltaFunctionCall( + arguments=delta_escaped + '"'), + ) + ]) + 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)[1:-1] + if self.current_param_value else "") + self.current_param_value += value_chunk + full_escaped = json.dumps( + self.current_param_value)[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
Vulnerability mechanics
Generated by null/stub on May 9, 2026. Inputs: CWE entries + fix-commit diffs from this CVE's patches. Citations validated against bundle.
References
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