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https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 00:57:33 +08:00
[Feature] add tool parser (#3483)
* add tool parser * add x1 enable_thinking * restart ci * fix vl reasoning parser * modify call style * modify call style * add offline enablethinking * fix completion * fix * fix unit test * fix unit test * fix unit test * fix vl reasoning parser * fix vl reasoning parser
This commit is contained in:
luukunn
@@ -14,7 +14,6 @@
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import json
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import re
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import traceback
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import uuid
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from collections.abc import Sequence
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from typing import Union
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@@ -58,6 +57,16 @@ class ErnieX1ToolParser(ToolParser):
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self.current_tool_name_sent: bool = False
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self.streamed_args_for_tool: list[str] = [] # map what has been streamed for each tool so far to a list
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self.buffer: str = "" # buffer for accumulating unprocessed streaming content
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self.bracket_counts: dict = {"total_l": 0, "total_r": 0} # track bracket counts in streamed deltas
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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.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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if self.tool_call_start_token_id is None or self.tool_call_end_token_id is None:
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raise RuntimeError(
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"Hermes 2 Pro Tool parser could not locate tool call start/end " "tokens in the tokenizer!"
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)
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if not self.model_tokenizer:
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raise ValueError(
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@@ -163,12 +172,10 @@ class ErnieX1ToolParser(ToolParser):
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}
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)
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except Exception as e:
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data_processor_logger.error(
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f"Failed to parse tool call: {str(e)}, {str(traceback.format_exc())}"
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)
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data_processor_logger.debug(f"Failed to parse tool call: {str(e)}")
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continue
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except Exception as e:
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data_processor_logger.error(f"Failed to parse tool call: {str(e)}, {str(traceback.format_exc())}")
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data_processor_logger.debug(f"Failed to parse tool call: {str(e)}")
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continue
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if not function_call_arr:
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@@ -214,9 +221,7 @@ class ErnieX1ToolParser(ToolParser):
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)
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except Exception as e:
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data_processor_logger.error(
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f"Error in extracting tool call from response: {str(e)}, {str(traceback.format_exc())}"
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)
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data_processor_logger.error(f"Error in extracting tool call from response: {str(e)}")
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return ExtractedToolCallInformation(tools_called=False, tool_calls=None, content=model_output)
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def extract_tool_calls_streaming(
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@@ -229,6 +234,9 @@ class ErnieX1ToolParser(ToolParser):
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delta_token_ids: Sequence[int],
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request: dict,
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) -> Union[DeltaMessage, None]:
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if self.tool_call_start_token_id not in current_token_ids:
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return DeltaMessage(content=delta_text)
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# 忽略空chunk
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if len(delta_text.strip()) == 0:
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return None
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@@ -239,7 +247,7 @@ class ErnieX1ToolParser(ToolParser):
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self.buffer += delta_text
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# 处理增量中的新tool_call开始
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if "<tool_call>" in delta_text and "<tool_call>" not in previous_text:
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if "<tool_call>" in delta_text:
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self.current_tool_id = (
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max(self.current_tool_id, 0) if self.current_tool_id == -1 else self.current_tool_id + 1
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)
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@@ -248,8 +256,6 @@ class ErnieX1ToolParser(ToolParser):
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self.streamed_args_for_tool.append("")
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data_processor_logger.debug(f"New tool call started with ID: {self.current_tool_id}")
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# 增量解析逻辑
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# 1. 尝试解析name字段
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if not self.current_tool_name_sent and '"name"' in self.buffer:
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name_match = re.search(r'"name"\s*:\s*"([^"]*)"', self.buffer)
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@@ -266,7 +272,6 @@ class ErnieX1ToolParser(ToolParser):
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)
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]
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)
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print("delta name:", delta)
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# 删除已处理的name部分
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self.buffer = self.buffer[name_match.end() :]
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self.current_tool_name_sent = True
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@@ -276,54 +281,67 @@ class ErnieX1ToolParser(ToolParser):
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args_match = re.search(r'"arguments"\s*:\s*(\{.*)', self.buffer)
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if args_match:
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args_content = args_match.group(1)
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# 处理多余的大括号
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open_braces = args_content.count("{")
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close_braces = args_content.count("}")
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if close_braces > open_braces:
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args_content = args_content[: args_content.rfind("}")]
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try:
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# 增量解析arguments
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parsed_args = json.loads(args_content)
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if isinstance(parsed_args, dict):
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args_json = json.dumps(parsed_args, ensure_ascii=False)
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if len(args_json) > len(self.streamed_args_for_tool[self.current_tool_id]):
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argument_diff = args_json[len(self.streamed_args_for_tool[self.current_tool_id]) :]
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# 检查是否到达arguments结尾(括号完全匹配)
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if "}}" in args_content:
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# 逐个字符检查括号匹配状态
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matched_pos = -1
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for i, ch in enumerate(delta_text):
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if ch == "{":
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self.bracket_counts["total_l"] += 1
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elif ch == "}":
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self.bracket_counts["total_r"] += 1
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if self.bracket_counts["total_l"] == self.bracket_counts["total_r"]: # 括号完全匹配
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matched_pos = i
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break
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if matched_pos >= 0:
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# 找到匹配点，清理buffer并返回
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truncate_text = delta_text[: matched_pos + 1]
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delta = DeltaMessage(
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tool_calls=[
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DeltaToolCall(
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index=self.current_tool_id,
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function=DeltaFunctionCall(arguments=argument_diff).model_dump(
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function=DeltaFunctionCall(arguments=truncate_text).model_dump(
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exclude_none=True
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),
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)
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]
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)
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print("delta argument:", delta)
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# 删除已处理部分
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processed_pos = args_match.start() + len('"arguments":')
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self.buffer = (
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self.buffer[:processed_pos] + self.buffer[processed_pos + len(args_json) :]
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)
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self.streamed_args_for_tool[self.current_tool_id] = args_json
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self.buffer = self.buffer[args_match.end() :]
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return delta
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else:
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# 没有完全匹配，继续累积
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return None
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else:
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# 增量返回当前可解析的部分
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for ch in delta_text:
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if ch == "{":
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self.bracket_counts["total_l"] += 1
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elif ch == "}":
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self.bracket_counts["total_r"] += 1
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delta = DeltaMessage(
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tool_calls=[
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DeltaToolCall(
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index=self.current_tool_id,
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function=DeltaFunctionCall(arguments=delta_text).model_dump(exclude_none=True),
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)
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]
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)
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return delta
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except Exception as e:
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data_processor_logger.error(
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f"Partial arguments parsing: {str(e)}, {str(traceback.format_exc())}"
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)
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data_processor_logger.error(f"Error in streaming tool call extraction: {str(e)}")
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return None
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if "</tool_call>" in self.buffer:
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end_pos = self.buffer.find("</tool_call>")
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self.buffer = self.buffer[end_pos + len("</tool_call>") :]
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# 完成当前工具调用处理
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self.current_tool_id += 1
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self.current_tool_name_sent = False
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self.streamed_args_for_tool.append("")
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return delta
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except Exception as e:
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data_processor_logger.error(
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f"Error in streaming tool call extraction: {str(e)}, {str(traceback.format_exc())}"
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)
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data_processor_logger.error(f"Error in streaming tool call extraction: {str(e)}")
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return None
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