# Copyright 2024 the LlamaFactory team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import json import re from abc import ABC, abstractmethod from dataclasses import dataclass from typing import Any, Dict, List, Tuple, Union from .data_utils import SLOTS DEFAULT_TOOL_PROMPT = ( "You have access to the following tools:\n{tool_text}" "Use the following format if using a tool:\n" "```\n" "Action: tool name (one of [{tool_names}]).\n" "Action Input: the input to the tool, in a JSON format representing the kwargs " """(e.g. ```{{"input": "hello world", "num_beams": 5}}```).\n""" "```\n" ) GLM4_TOOL_PROMPT = ( "你是一个名为 ChatGLM 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的," "你的任务是针对用户的问题和要求提供适当的答复和支持。# 可用工具{tool_text}" ) @dataclass class ToolUtils(ABC): @staticmethod @abstractmethod def get_function_slots() -> SLOTS: ... @staticmethod @abstractmethod def tool_formatter(tools: List[Dict[str, Any]]) -> str: ... @staticmethod @abstractmethod def tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]: ... class DefaultToolUtils(ToolUtils): @staticmethod def get_function_slots() -> SLOTS: return ["Action: {{name}}\nAction Input: {{arguments}}\n"] @staticmethod def tool_formatter(tools: List[Dict[str, Any]]) -> str: tool_text = "" tool_names = [] for tool in tools: param_text = "" for name, param in tool["parameters"]["properties"].items(): required, enum, items = "", "", "" if name in tool["parameters"].get("required", []): required = ", required" if param.get("enum", None): enum = ", should be one of [{}]".format(", ".join(param["enum"])) if param.get("items", None): items = ", where each item should be {}".format(param["items"].get("type", "")) param_text += " - {name} ({type}{required}): {desc}{enum}{items}\n".format( name=name, type=param.get("type", ""), required=required, desc=param.get("description", ""), enum=enum, items=items, ) tool_text += "> Tool Name: {name}\nTool Description: {desc}\nTool Args:\n{args}\n".format( name=tool["name"], desc=tool.get("description", ""), args=param_text ) tool_names.append(tool["name"]) return DEFAULT_TOOL_PROMPT.format(tool_text=tool_text, tool_names=", ".join(tool_names)) @staticmethod def tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]: regex = re.compile(r"Action:\s*([a-zA-Z0-9_]+)\s*Action Input:\s*(.+?)(?=\s*Action:|\s*$)", re.DOTALL) action_match: List[Tuple[str, str]] = re.findall(regex, content) if not action_match: return content results = [] for match in action_match: tool_name = match[0].strip() tool_input = match[1].strip().strip('"').strip("```") try: arguments = json.loads(tool_input) results.append((tool_name, json.dumps(arguments, ensure_ascii=False))) except json.JSONDecodeError: return content return results class GLM4ToolUtils(ToolUtils): @staticmethod def get_function_slots() -> SLOTS: return ["{{name}}\n{{arguments}}"] @staticmethod def tool_formatter(tools: List[Dict[str, Any]]) -> str: tool_text = "" for tool in tools: tool_text += "\n\n## {name}\n\n{body}\n在调用上述函数时,请使用 Json 格式表示调用的参数。".format( name=tool["name"], body=json.dumps(tool, indent=4, ensure_ascii=False) ) return GLM4_TOOL_PROMPT.format(tool_text=tool_text) @staticmethod def tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]: if "\n" not in content: return content tool_name, tool_input = content.split("\n", maxsplit=1) try: arguments = json.loads(tool_input) except json.JSONDecodeError: return content return [(tool_name, json.dumps(arguments, ensure_ascii=False))]