517 lines
20 KiB
Python
517 lines
20 KiB
Python
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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GLM-4 Tool Call Parser with incremental string streaming support.
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This parser fixes the streaming issue reported in Issue #32829 where long string
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parameters (e.g., file content with 4000+ characters of code) are buffered until
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complete, causing multi-second delays before the user sees any content.
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The fix streams string values incrementally as they arrive, providing a true
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streaming experience for long content.
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"""
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import ast
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import json
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from collections.abc import Sequence
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from typing import Any
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import regex as re
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from vllm.entrypoints.chat_utils import make_tool_call_id
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from vllm.entrypoints.openai.chat_completion.protocol import (
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ChatCompletionRequest,
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ChatCompletionToolsParam,
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)
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from vllm.entrypoints.openai.engine.protocol import (
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DeltaFunctionCall,
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DeltaMessage,
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DeltaToolCall,
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ExtractedToolCallInformation,
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FunctionCall,
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ToolCall,
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)
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from vllm.logger import init_logger
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from vllm.tokenizers import TokenizerLike
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from vllm.tool_parsers.abstract_tool_parser import (
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ToolParser,
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)
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logger = init_logger(__name__)
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class Glm4MoeModelToolParser(ToolParser):
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"""Tool parser for GLM-4 models with incremental string streaming.
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This parser emits tool-call deltas incrementally as arguments arrive.
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For string-type parameters, content is streamed character-by-character
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rather than waiting for the complete </arg_value> tag.
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"""
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def __init__(self, tokenizer: TokenizerLike):
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super().__init__(tokenizer)
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# Stateful streaming fields
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self.current_tool_name_sent: bool = False
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self.prev_tool_call_arr: list[dict[str, Any]] = []
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self.current_tool_id: int = -1
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self.streamed_args_for_tool: list[str] = []
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self.tool_call_start_token: str = "<tool_call>"
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self.tool_call_end_token: str = "</tool_call>"
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self.arg_key_start: str = "<arg_key>"
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self.arg_key_end: str = "</arg_key>"
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self.arg_val_start: str = "<arg_value>"
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self.arg_val_end: str = "</arg_value>"
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self.tool_calls_start_token = self.tool_call_start_token
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self.func_call_regex = re.compile(r"<tool_call>.*?</tool_call>", re.DOTALL)
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self.func_detail_regex = re.compile(
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r"<tool_call>([^\n]*)\n(.*)</tool_call>", re.DOTALL
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)
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self.func_arg_regex = re.compile(
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r"<arg_key>(.*?)</arg_key>\s*<arg_value>(.*?)</arg_value>", re.DOTALL
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)
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if not self.model_tokenizer:
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raise ValueError(
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"The model tokenizer must be passed to the ToolParser "
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"constructor during construction."
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)
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self.tool_call_start_token_id = self.vocab.get(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._buffer: str = ""
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# Streaming state for incremental tool-call streaming
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self._in_tool_call: bool = False
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self._current_tool_name: str | None = None
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self._pending_key: str | None = None
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self._streaming_string_value: bool = False
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self._tool_call_ids: list[str] = []
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self._args_started: list[bool] = []
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self._args_closed: list[bool] = []
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self._seen_keys: list[set[str]] = []
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@staticmethod
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def _deserialize(value: str) -> Any:
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try:
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return json.loads(value)
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except json.JSONDecodeError:
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pass
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try:
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return ast.literal_eval(value)
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except (ValueError, SyntaxError):
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pass
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return value
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@staticmethod
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def _json_escape_string_content(s: str) -> str:
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"""JSON-escape string content for incremental streaming.
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This escapes the content that goes INSIDE a JSON string (between quotes),
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not including the surrounding quotes themselves.
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"""
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if not s:
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return ""
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return json.dumps(s, ensure_ascii=False)[1:-1]
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@staticmethod
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def _is_string_type(
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tool_name: str,
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arg_name: str,
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tools: list[ChatCompletionToolsParam] | None,
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) -> bool:
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if tools is None:
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return False
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for tool in tools:
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if tool.function.name != tool_name:
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continue
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if tool.function.parameters is None:
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return False
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arg_type = (
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tool.function.parameters.get("properties", {})
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.get(arg_name, {})
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.get("type", None)
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)
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return arg_type == "string"
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logger.debug("No tool named '%s'.", tool_name)
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return False
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@staticmethod
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def _tools_enabled(request: ChatCompletionRequest) -> bool:
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"""Return whether tool parsing should be applied for this request."""
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try:
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tools = getattr(request, "tools", None)
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tool_choice = getattr(request, "tool_choice", None)
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return bool(tools) and tool_choice != "none"
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except Exception:
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logger.exception("Failed to determine if tools are enabled.")
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return False
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def adjust_request(self, request: ChatCompletionRequest) -> ChatCompletionRequest:
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"""Adjust request parameters for tool call token handling."""
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request = super().adjust_request(request)
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if request.tools and request.tool_choice != "none":
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# Ensure tool call tokens (<tool_call>, </tool_call>) are not skipped
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# during decoding. Even though they are not marked as special tokens,
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# setting skip_special_tokens=False ensures proper handling in
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# transformers 5.x where decoding behavior may have changed.
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request.skip_special_tokens = False
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return request
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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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matched_tool_calls = self.func_call_regex.findall(model_output)
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logger.debug("model_output: %s", model_output)
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try:
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tool_calls: list[ToolCall] = []
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for match in matched_tool_calls:
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tc_detail = self.func_detail_regex.search(match)
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if not tc_detail:
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logger.warning(
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"Failed to parse tool call details from: %s",
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match,
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)
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continue
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tc_name = tc_detail.group(1).strip()
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tc_args = tc_detail.group(2)
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pairs = self.func_arg_regex.findall(tc_args) if tc_args else []
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arg_dct: dict[str, Any] = {}
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for key, value in pairs:
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arg_key = key.strip()
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arg_val = value.strip()
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if not self._is_string_type(tc_name, arg_key, request.tools):
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arg_val = self._deserialize(arg_val)
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logger.debug("arg_key = %s, arg_val = %s", arg_key, arg_val)
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arg_dct[arg_key] = arg_val
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tool_calls.append(
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ToolCall(
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type="function",
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function=FunctionCall(
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name=tc_name,
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arguments=json.dumps(arg_dct, ensure_ascii=False),
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),
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)
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)
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except Exception:
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logger.exception("Failed to extract tool call spec")
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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else:
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if len(tool_calls) > 0:
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content = model_output[: model_output.find(self.tool_calls_start_token)]
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return ExtractedToolCallInformation(
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tools_called=True, tool_calls=tool_calls, content=content
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)
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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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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) -> DeltaMessage | None:
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if not self._tools_enabled(request):
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return DeltaMessage(content=delta_text) if delta_text else None
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self._buffer += delta_text
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while True:
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if not self._in_tool_call:
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start_idx = self._buffer.find(self.tool_call_start_token)
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if start_idx == -1:
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# Check for partial start token at end of buffer
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for i in range(1, len(self.tool_call_start_token)):
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if self._buffer.endswith(self.tool_call_start_token[:i]):
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out = self._buffer[:-i]
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self._buffer = self._buffer[-i:]
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return DeltaMessage(content=out) if out else None
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out = self._buffer
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self._buffer = ""
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return DeltaMessage(content=out) if out else None
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if start_idx > 0:
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out = self._buffer[:start_idx]
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self._buffer = self._buffer[start_idx:]
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return DeltaMessage(content=out) if out else None
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self._buffer = self._buffer[len(self.tool_call_start_token) :]
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self._begin_tool_call()
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continue
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# Parse tool name first
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if not self.current_tool_name_sent:
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nl = self._buffer.find("\n")
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ak = self._buffer.find(self.arg_key_start)
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end = self._buffer.find(self.tool_call_end_token)
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candidates = [i for i in [nl, ak, end] if i != -1]
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if not candidates:
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return None
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cut = min(candidates)
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tool_name = self._buffer[:cut].strip()
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if tool_name == "" and cut == end:
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# Handle empty tool call like `<tool_call></tool_call>`.
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# Consume the tokens and reset state to avoid infinite loop.
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self._buffer = self._buffer[end + len(self.tool_call_end_token) :]
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self._finish_tool_call()
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self._revert_last_tool_call_state()
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continue
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if cut == nl:
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self._buffer = self._buffer[nl + 1 :]
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else:
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self._buffer = self._buffer[cut:]
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self._current_tool_name = tool_name
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self.current_tool_name_sent = True
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return self._emit_tool_name_delta(tool_name)
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assert self._current_tool_name is not None
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# Handle incremental string value streaming
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if self._streaming_string_value:
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val_end = self._buffer.find(self.arg_val_end)
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if val_end != -1:
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raw_content = self._buffer[:val_end]
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self._buffer = self._buffer[val_end + len(self.arg_val_end) :]
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self._streaming_string_value = False
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self._pending_key = None
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escaped = self._json_escape_string_content(raw_content)
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frag = escaped + '"'
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self.streamed_args_for_tool[self.current_tool_id] += frag
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return self._emit_tool_args_delta(frag)
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else:
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# Check for partial </arg_value> at end
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safe_len = len(self._buffer)
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for i in range(1, len(self.arg_val_end)):
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if self._buffer.endswith(self.arg_val_end[:i]):
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safe_len = len(self._buffer) - i
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break
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if safe_len > 0:
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to_emit = self._buffer[:safe_len]
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self._buffer = self._buffer[safe_len:]
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escaped = self._json_escape_string_content(to_emit)
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if escaped:
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self.streamed_args_for_tool[self.current_tool_id] += escaped
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return self._emit_tool_args_delta(escaped)
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return None
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# If we have a pending key, parse its value
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if self._pending_key is not None:
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val_pos = self._buffer.find(self.arg_val_start)
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if val_pos == -1:
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return None
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if val_pos > 0:
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self._buffer = self._buffer[val_pos:]
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key = (self._pending_key or "").strip()
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is_string = self._is_string_type(
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self._current_tool_name, key, request.tools
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)
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if is_string:
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# String type: stream incrementally
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self._buffer = self._buffer[len(self.arg_val_start) :]
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if key in self._seen_keys[self.current_tool_id]:
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self._pending_key = None
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continue
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self._seen_keys[self.current_tool_id].add(key)
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key_json = json.dumps(key, ensure_ascii=False)
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if not self._args_started[self.current_tool_id]:
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frag = "{" + key_json + ':"'
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self._args_started[self.current_tool_id] = True
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else:
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frag = "," + key_json + ':"'
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self.streamed_args_for_tool[self.current_tool_id] += frag
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self._streaming_string_value = True
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return self._emit_tool_args_delta(frag)
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else:
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# Non-string type: wait for complete value
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val_end = self._buffer.find(self.arg_val_end)
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if val_end == -1:
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return None
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raw_val = self._buffer[len(self.arg_val_start) : val_end].strip()
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self._buffer = self._buffer[val_end + len(self.arg_val_end) :]
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self._pending_key = None
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frag = self._append_arg_fragment(
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key=key,
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raw_val=raw_val,
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)
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if frag:
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return self._emit_tool_args_delta(frag)
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continue
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|
|
|
||
|
|
# Parse next arg or close
|
||
|
|
end_pos = self._buffer.find(self.tool_call_end_token)
|
||
|
|
key_pos = self._buffer.find(self.arg_key_start)
|
||
|
|
if end_pos != -1 and (key_pos == -1 or end_pos < key_pos):
|
||
|
|
self._buffer = self._buffer[end_pos + len(self.tool_call_end_token) :]
|
||
|
|
frag = self._close_args_if_needed()
|
||
|
|
# Finalize prev_tool_call_arr with complete parsed arguments
|
||
|
|
if self._current_tool_name:
|
||
|
|
try:
|
||
|
|
full_args_str = self.streamed_args_for_tool[
|
||
|
|
self.current_tool_id
|
||
|
|
]
|
||
|
|
args_dict = json.loads(full_args_str)
|
||
|
|
self.prev_tool_call_arr[self.current_tool_id] = {
|
||
|
|
"name": self._current_tool_name,
|
||
|
|
"arguments": args_dict,
|
||
|
|
}
|
||
|
|
except (json.JSONDecodeError, IndexError) as e:
|
||
|
|
logger.warning(
|
||
|
|
"Failed to finalize tool call state for tool %d: %s",
|
||
|
|
self.current_tool_id,
|
||
|
|
e,
|
||
|
|
)
|
||
|
|
self._finish_tool_call()
|
||
|
|
return self._emit_tool_args_delta(frag) if frag else None
|
||
|
|
|
||
|
|
if key_pos == -1:
|
||
|
|
return None
|
||
|
|
if key_pos > 0:
|
||
|
|
self._buffer = self._buffer[key_pos:]
|
||
|
|
key_end = self._buffer.find(self.arg_key_end)
|
||
|
|
if key_end == -1:
|
||
|
|
return None
|
||
|
|
key = self._buffer[len(self.arg_key_start) : key_end]
|
||
|
|
self._buffer = self._buffer[key_end + len(self.arg_key_end) :]
|
||
|
|
self._pending_key = key
|
||
|
|
continue
|
||
|
|
|
||
|
|
def _ensure_tool_state(self) -> None:
|
||
|
|
while len(self._tool_call_ids) <= self.current_tool_id:
|
||
|
|
self._tool_call_ids.append(
|
||
|
|
make_tool_call_id(id_type="random", func_name=None, idx=None)
|
||
|
|
)
|
||
|
|
while len(self.streamed_args_for_tool) <= self.current_tool_id:
|
||
|
|
self.streamed_args_for_tool.append("")
|
||
|
|
while len(self.prev_tool_call_arr) <= self.current_tool_id:
|
||
|
|
self.prev_tool_call_arr.append({})
|
||
|
|
while len(self._args_started) <= self.current_tool_id:
|
||
|
|
self._args_started.append(False)
|
||
|
|
while len(self._args_closed) <= self.current_tool_id:
|
||
|
|
self._args_closed.append(False)
|
||
|
|
while len(self._seen_keys) <= self.current_tool_id:
|
||
|
|
self._seen_keys.append(set())
|
||
|
|
|
||
|
|
def _begin_tool_call(self) -> None:
|
||
|
|
if self.current_tool_id == -1:
|
||
|
|
self.current_tool_id = 0
|
||
|
|
else:
|
||
|
|
self.current_tool_id += 1
|
||
|
|
self._ensure_tool_state()
|
||
|
|
self.current_tool_name_sent = False
|
||
|
|
self._current_tool_name = None
|
||
|
|
self._pending_key = None
|
||
|
|
self._streaming_string_value = False
|
||
|
|
self._in_tool_call = True
|
||
|
|
|
||
|
|
def _finish_tool_call(self) -> None:
|
||
|
|
self._in_tool_call = False
|
||
|
|
self._current_tool_name = None
|
||
|
|
self._pending_key = None
|
||
|
|
self._streaming_string_value = False
|
||
|
|
|
||
|
|
def _revert_last_tool_call_state(self) -> None:
|
||
|
|
"""Revert the state allocation for the last tool call."""
|
||
|
|
if self.current_tool_id < 0:
|
||
|
|
return
|
||
|
|
self._tool_call_ids.pop()
|
||
|
|
self.streamed_args_for_tool.pop()
|
||
|
|
self.prev_tool_call_arr.pop()
|
||
|
|
self._args_started.pop()
|
||
|
|
self._args_closed.pop()
|
||
|
|
self._seen_keys.pop()
|
||
|
|
self.current_tool_id -= 1
|
||
|
|
|
||
|
|
def _emit_tool_name_delta(self, tool_name: str) -> DeltaMessage:
|
||
|
|
return DeltaMessage(
|
||
|
|
tool_calls=[
|
||
|
|
DeltaToolCall(
|
||
|
|
index=self.current_tool_id,
|
||
|
|
id=self._tool_call_ids[self.current_tool_id],
|
||
|
|
type="function",
|
||
|
|
function=DeltaFunctionCall(
|
||
|
|
name=tool_name,
|
||
|
|
arguments="",
|
||
|
|
).model_dump(exclude_none=True),
|
||
|
|
)
|
||
|
|
]
|
||
|
|
)
|
||
|
|
|
||
|
|
def _emit_tool_args_delta(self, fragment: str) -> DeltaMessage:
|
||
|
|
return DeltaMessage(
|
||
|
|
tool_calls=[
|
||
|
|
DeltaToolCall(
|
||
|
|
index=self.current_tool_id,
|
||
|
|
function=DeltaFunctionCall(arguments=fragment).model_dump(
|
||
|
|
exclude_none=True
|
||
|
|
),
|
||
|
|
)
|
||
|
|
]
|
||
|
|
)
|
||
|
|
|
||
|
|
def _append_arg_fragment(
|
||
|
|
self,
|
||
|
|
*,
|
||
|
|
key: str,
|
||
|
|
raw_val: str,
|
||
|
|
) -> str | None:
|
||
|
|
key = key.strip()
|
||
|
|
if not key:
|
||
|
|
return None
|
||
|
|
if key in self._seen_keys[self.current_tool_id]:
|
||
|
|
return None
|
||
|
|
|
||
|
|
# This function is only called for non-string types (already checked
|
||
|
|
# by _is_string_type in the caller), so we always deserialize.
|
||
|
|
val_obj: Any = self._deserialize(raw_val)
|
||
|
|
|
||
|
|
key_json = json.dumps(key, ensure_ascii=False)
|
||
|
|
val_json = json.dumps(val_obj, ensure_ascii=False)
|
||
|
|
|
||
|
|
if not self._args_started[self.current_tool_id]:
|
||
|
|
fragment = "{" + key_json + ":" + val_json
|
||
|
|
self._args_started[self.current_tool_id] = True
|
||
|
|
else:
|
||
|
|
fragment = "," + key_json + ":" + val_json
|
||
|
|
|
||
|
|
self._seen_keys[self.current_tool_id].add(key)
|
||
|
|
self.streamed_args_for_tool[self.current_tool_id] += fragment
|
||
|
|
return fragment
|
||
|
|
|
||
|
|
def _close_args_if_needed(self) -> str | None:
|
||
|
|
if self._args_closed[self.current_tool_id]:
|
||
|
|
return None
|
||
|
|
self._args_closed[self.current_tool_id] = True
|
||
|
|
if not self._args_started[self.current_tool_id]:
|
||
|
|
fragment = "{}"
|
||
|
|
self.streamed_args_for_tool[self.current_tool_id] = fragment
|
||
|
|
else:
|
||
|
|
fragment = "}"
|
||
|
|
self.streamed_args_for_tool[self.current_tool_id] += fragment
|
||
|
|
return fragment
|