680 lines
30 KiB
Python
680 lines
30 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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# Adapted from qwen3coder xml parser, All rights reserved.
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# ruff: noqa: E501
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import ast
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import json
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import uuid
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from collections.abc import Sequence
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from typing import Any, Optional, Union
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import regex as re
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from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
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ChatCompletionToolsParam,
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DeltaFunctionCall, DeltaMessage,
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DeltaToolCall,
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ExtractedToolCallInformation,
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FunctionCall, ToolCall)
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from vllm.entrypoints.openai.tool_parsers.abstract_tool_parser import (
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ToolParser, ToolParserManager)
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from vllm.logger import init_logger
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from vllm.transformers_utils.tokenizer import AnyTokenizer
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logger = init_logger(__name__)
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@ToolParserManager.register_module("seed_oss")
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class SeedOssToolParser(ToolParser):
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TOOL_CALL_START = "<seed:tool_call>"
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TOOL_CALL_END = "</seed:tool_call>"
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def __init__(self, tokenizer: AnyTokenizer):
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super().__init__(tokenizer)
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# --- streaming state ---
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self._reset_streaming_state()
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self.prev_tool_call_arr: list[dict] = []
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self.tool_call_start_token: str = self.TOOL_CALL_START
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self.tool_call_end_token: str = self.TOOL_CALL_END
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# Sentinel tokens for streaming mode
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self.tool_call_prefix: str = "<function="
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self.function_end_token: str = "</function>"
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self.parameter_prefix: str = "<parameter="
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self.parameter_end_token: str = "</parameter>"
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self.think_start_token: str = "<seed:think>"
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self.think_end_token: str = "</seed:think>"
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self.is_tool_call_started: bool = False
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self.is_thinking_end: bool = False
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self.failed_count: int = 0
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self._reset_streaming_state()
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self.tool_call_start_token_id = self.vocab.get(
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self.tool_call_start_token)
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self.tool_call_end_token_id = self.vocab.get(self.tool_call_end_token)
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self.think_end_token_id = self.vocab.get(self.think_end_token)
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if (self.tool_call_start_token_id is None
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or self.tool_call_end_token_id is None):
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raise RuntimeError(
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"Seed_Oss XML parser: tokenizer did not include "
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"<seed:tool_call> or its closing tag.")
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tool_start_re = re.escape(self.tool_call_start_token)
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tool_end_re = re.escape(self.tool_call_end_token)
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self.tool_call_complete_regex = re.compile(
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rf"{tool_start_re}(.*?){tool_end_re}", re.DOTALL)
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self.tool_call_regex = re.compile(
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rf"{tool_start_re}(.*?){tool_end_re}|{tool_start_re}(.*?)$",
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re.DOTALL)
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self.tool_call_function_regex = re.compile(
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r"<function=(.*?)</function>|<function=(.*)$", re.DOTALL)
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self.tool_call_parameter_regex = re.compile(
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r"<parameter=(.*?)</parameter>|<parameter=(.*?)$", re.DOTALL)
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logger.info("vLLM Seed-Oss XML tool parser loaded (%s).",
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self.__class__.__name__)
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def _generate_tool_call_id(self) -> str:
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"""Generate a unique tool call ID."""
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return f"call_{uuid.uuid4().hex[:24]}"
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def _reset_streaming_state(self):
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"""Reset all streaming state."""
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self.current_tool_index = 0
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self.is_tool_call_started = False
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self.header_sent = False
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self.current_tool_id = -1
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self.current_function_name = None
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self.current_param_name = None
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self.current_param_value = ""
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self.param_count = 0
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self.in_param = False
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self.in_function = False
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self.accumulated_text = ""
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self.json_started = False
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self.json_closed = False
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def _parse_xml_function_call(
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self, function_call_str: str,
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tools: Optional[list[ChatCompletionToolsParam]]
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) -> Optional[ToolCall]:
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def get_arguments_config(func_name: str) -> dict:
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if tools is None:
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return {}
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for config in tools:
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if not hasattr(config, "type") or not (
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hasattr(config, "function")
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and hasattr(config.function, "name")):
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continue
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if (config.type == "function"
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and config.function.name == func_name):
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if not hasattr(config.function, "parameters"):
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return {}
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params = config.function.parameters
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if isinstance(params, dict) and "properties" in params:
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return params["properties"]
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elif isinstance(params, dict):
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return params
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else:
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return {}
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logger.warning("Tool '%s' is not defined in the tools list.",
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func_name)
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return {}
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def convert_param_value(param_value: str, param_name: str,
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param_config: dict, func_name: str) -> Any:
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# Handle null value for any type
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if param_value.lower() == "null":
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return None
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if param_name not in param_config:
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if param_config != {}:
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logger.warning(
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"Parsed parameter '%s' is not defined in "
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"the tool parameters for tool '%s', "
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"directly returning the string value.", param_name,
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func_name)
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return param_value
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if (isinstance(param_config[param_name], dict)
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and "type" in param_config[param_name]):
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param_type = str(
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param_config[param_name]["type"]).strip().lower()
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else:
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param_type = "string"
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if param_type in [
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"string", "str", "text", "varchar", "char", "enum"
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]:
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return param_value
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elif (param_type.startswith("int") or param_type.startswith("uint")
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or param_type.startswith("long")
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or param_type.startswith("short")
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or param_type.startswith("unsigned")):
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try:
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param_value = int(param_value) # type: ignore
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except (ValueError, TypeError):
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logger.warning(
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"Parsed value '%s' of parameter '%s' is not an integer in tool "
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"'%s', degenerating to string.", param_value,
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param_name, func_name)
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return param_value
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elif param_type.startswith("num") or param_type.startswith(
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"float"):
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try:
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float_param_value = float(param_value)
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param_value = float_param_value if float_param_value - int(
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float_param_value) != 0 else int(
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float_param_value) # type: ignore
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except (ValueError, TypeError):
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logger.warning(
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"Parsed value '%s' of parameter '%s' is not a float in tool "
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"'%s', degenerating to string.", param_value,
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param_name, func_name)
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return param_value
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elif param_type in ["boolean", "bool", "binary"]:
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param_value = param_value.lower()
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if param_value not in ["true", "false"]:
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logger.warning(
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"Parsed value '%s' of parameter '%s' is not a boolean "
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"(`true` of `false`) in tool '%s', degenerating to false.",
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param_value, param_name, func_name)
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return param_value == "true"
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else:
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if param_type == "object" or param_type.startswith("dict"):
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try:
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param_value = json.loads(param_value)
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return param_value
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except (ValueError, TypeError, json.JSONDecodeError):
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logger.warning(
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"Parsed value '%s' of parameter '%s' is not a valid JSON "
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"object in tool '%s', will try other methods to parse it.",
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param_value, param_name, func_name)
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try:
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param_value = ast.literal_eval(param_value)
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except (ValueError, SyntaxError):
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logger.warning(
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"Parsed value '%s' of parameter '%s' cannot be converted via "
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"Python `ast.literal_eval()` in tool '%s', degenerating to string.",
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param_value, param_name, func_name)
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return param_value
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# Extract function name
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end_index = function_call_str.index(">")
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function_name = function_call_str[:end_index]
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param_config = get_arguments_config(function_name)
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parameters = function_call_str[end_index + 1:]
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param_dict = {}
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for match in self.tool_call_parameter_regex.findall(parameters):
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match_text = match[0] if match[0] else match[1]
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idx = match_text.index(">")
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param_name = match_text[:idx]
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param_value = str(match_text[idx + 1:])
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# Remove prefix and trailing \n
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if param_value.startswith("\n"):
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param_value = param_value[1:]
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if param_value.endswith("\n"):
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param_value = param_value[:-1]
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param_dict[param_name] = convert_param_value(
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param_value, param_name, param_config, function_name)
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return ToolCall(
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type="function",
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function=FunctionCall(name=function_name,
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arguments=json.dumps(param_dict,
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ensure_ascii=False)),
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)
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def _get_function_calls(self, model_output: str) -> list[str]:
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# Find all tool calls
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matched_ranges = self.tool_call_regex.findall(model_output)
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raw_tool_calls = [
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match[0] if match[0] else match[1] for match in matched_ranges
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]
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# Back-off strategy if no tool_call tags found
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if len(raw_tool_calls) == 0:
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raw_tool_calls = [model_output]
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raw_function_calls = []
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for tool_call in raw_tool_calls:
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raw_function_calls.extend(
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self.tool_call_function_regex.findall(tool_call))
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function_calls = [
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match[0] if match[0] else match[1] for match in raw_function_calls
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]
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return function_calls
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def extract_tool_calls(
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self,
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model_output: str,
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request: ChatCompletionRequest,
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) -> ExtractedToolCallInformation:
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# Quick check to avoid unnecessary processing
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if self.tool_call_prefix not in model_output:
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return ExtractedToolCallInformation(tools_called=False,
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tool_calls=[],
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content=model_output)
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# Check if both think start and end tokens are present
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if (self.think_start_token in model_output
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and self.think_end_token in model_output):
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# Find the position of think end token
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think_end_index = model_output.find(self.think_end_token) + len(
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self.think_end_token)
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# Extract content after think end token
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result_content = model_output[think_end_index:]
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thinking_content = model_output[:think_end_index]
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else:
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thinking_content = ""
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result_content = model_output
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try:
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function_calls = self._get_function_calls(result_content)
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if len(function_calls) == 0:
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return ExtractedToolCallInformation(tools_called=False,
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tool_calls=[],
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content=model_output)
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tool_calls = [
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self._parse_xml_function_call(function_call_str, request.tools)
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for function_call_str in function_calls
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]
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# Populate prev_tool_call_arr for serving layer to set finish_reason
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self.prev_tool_call_arr.clear() # Clear previous calls
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for tool_call in tool_calls:
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if tool_call:
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self.prev_tool_call_arr.append({
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"name":
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tool_call.function.name,
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"arguments":
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tool_call.function.arguments,
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})
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# Extract content before tool calls
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tool_call_start_index = result_content.find(
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self.tool_call_start_token)
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tool_call_start_index = (
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tool_call_start_index if tool_call_start_index >= 0 else
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result_content.find(self.tool_call_prefix))
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content = thinking_content + result_content[:tool_call_start_index]
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return ExtractedToolCallInformation(
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tools_called=(len(tool_calls) > 0),
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tool_calls=tool_calls,
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content=content if content else None,
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)
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except Exception:
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logger.exception("Error in extracting tool call from response.")
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return ExtractedToolCallInformation(tools_called=False,
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tool_calls=[],
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content=model_output)
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def extract_tool_calls_streaming(
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self,
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previous_text: str,
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current_text: str,
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delta_text: str,
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previous_token_ids: Sequence[int],
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current_token_ids: Sequence[int],
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delta_token_ids: Sequence[int],
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request: ChatCompletionRequest,
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) -> Union[DeltaMessage, None]:
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# If no delta text, return None unless
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# it's an EOS token after tool calls
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if not delta_text:
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# Check if this is an EOS token after all tool calls are complete
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# We check for tool calls in the text even if is_tool_call_started
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# is False because it might have been reset after processing all tools
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if (delta_token_ids
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and self.tool_call_end_token_id not in delta_token_ids):
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# Count complete tool calls
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complete_calls = len(
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self.tool_call_complete_regex.findall(current_text))
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# If we have completed tool calls and populated prev_tool_call_arr
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if complete_calls > 0 and len(self.prev_tool_call_arr) > 0:
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# Check if all tool calls are closed
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open_calls = current_text.count(
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self.tool_call_start_token) - current_text.count(
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self.tool_call_end_token)
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if open_calls == 0:
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# Return empty delta message to allow finish_reason processing
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return DeltaMessage(content="")
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elif not self.is_tool_call_started and current_text:
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# This is a regular content response that's now complete
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return DeltaMessage(content="")
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return None
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# Check if this is the first call (reset state if needed)
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if not previous_text:
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self._reset_streaming_state()
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# Update accumulated text
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self.accumulated_text = current_text
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# Check if we need to advance to next tool
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if self.json_closed and not self.in_function:
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# Check if this tool call has ended
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tool_ends = current_text.count(self.tool_call_end_token)
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if tool_ends > self.current_tool_index:
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# This tool has ended, advance to next
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self.current_tool_index += 1
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self.header_sent = False
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self.param_count = 0
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self.json_started = False
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self.json_closed = False
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# Check if there are more tool calls
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if self.current_tool_index >= current_text.count(
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self.tool_call_start_token):
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# No more tool calls
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self.is_tool_call_started = False
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# Continue processing next tool
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return None
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# Check if end thinking
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if (not self.is_thinking_end
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and (self.think_end_token_id in delta_token_ids
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or self.think_end_token in delta_text)):
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self.is_thinking_end = True
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# If thinking hasn't ended yet, don't process any tool calls
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if not self.is_thinking_end:
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return DeltaMessage(content=delta_text)
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# Handle normal content before tool calls
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if not self.is_tool_call_started:
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# Check if tool call is starting
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if (self.tool_call_start_token_id in delta_token_ids
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or self.tool_call_start_token in delta_text):
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self.is_tool_call_started = True
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# Return any content before the tool call
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if self.tool_call_start_token in delta_text:
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content_before = delta_text[:delta_text.index(
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self.tool_call_start_token)]
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if content_before:
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return DeltaMessage(content=content_before)
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return None
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else:
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# Check if we're between tool calls - skip whitespace
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if (current_text.rstrip().endswith(self.tool_call_end_token)
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and delta_text.strip() == ""):
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# We just ended a tool call, skip whitespace
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return None
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# Normal content, no tool call
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return DeltaMessage(content=delta_text)
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# Check if we're between tool calls (waiting for next one)
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# Count tool calls we've seen vs processed
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tool_starts_count = current_text.count(self.tool_call_start_token)
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if self.current_tool_index >= tool_starts_count:
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# We're past all tool calls, shouldn't be here
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return None
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# We're in a tool call, find the current tool call portion
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# Need to find the correct tool call based on current_tool_index
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# Only process tool calls after think_end_token
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think_end_index = current_text.find(self.think_end_token) + len(
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self.think_end_token
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) if self.think_end_token in current_text else 0
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tool_starts: list[int] = []
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idx = think_end_index
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while True:
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idx = current_text.find(self.tool_call_start_token, idx)
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if idx == -1:
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break
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tool_starts.append(idx)
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idx += len(self.tool_call_start_token)
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if self.current_tool_index >= len(tool_starts):
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# No more tool calls to process yet
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return None
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tool_start_idx = tool_starts[self.current_tool_index]
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# Find where this tool call ends (or current position if not ended yet)
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tool_end_idx = current_text.find(self.tool_call_end_token,
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tool_start_idx)
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if tool_end_idx == -1:
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tool_text = current_text[tool_start_idx:]
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else:
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tool_text = current_text[tool_start_idx:tool_end_idx +
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len(self.tool_call_end_token)]
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# Looking for function header
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if not self.header_sent:
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if self.tool_call_prefix in tool_text:
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func_start = tool_text.find(self.tool_call_prefix) + len(
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self.tool_call_prefix)
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func_end = tool_text.find(">", func_start)
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if func_end != -1:
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# Found complete function name
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self.current_function_name = tool_text[func_start:func_end]
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self.current_tool_id = self._generate_tool_call_id(
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) # type: ignore
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self.header_sent = True
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self.in_function = True
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# IMPORTANT: Add to prev_tool_call_arr immediately when we detect a tool call
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# This ensures finish_reason="tool_calls" even if parsing isn't complete
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already_added = any(
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tool.get("name") == self.current_function_name
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for tool in self.prev_tool_call_arr)
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if not already_added:
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self.prev_tool_call_arr.append({
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"name": self.current_function_name,
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"arguments":
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"{}", # Placeholder, will be updated later
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})
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# Send header with function info
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|
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 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:
|
|
logger.warning(
|
|
"Failed to parse tool arguments during streaming.",
|
|
exc_info=True)
|
|
|
|
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
|