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|
| | import json |
| | import re |
| | from abc import ABC, abstractmethod |
| | from collections import namedtuple |
| | from dataclasses import dataclass |
| | from typing import Any, Dict, List, Tuple, Union |
| |
|
| | from typing_extensions import override |
| |
|
| | 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}" |
| | ) |
| |
|
| |
|
| | FunctionCall = namedtuple("FunctionCall", ["name", "arguments"]) |
| |
|
| |
|
| | @dataclass |
| | class ToolUtils(ABC): |
| | """ |
| | Base class for tool utilities. |
| | """ |
| |
|
| | @staticmethod |
| | @abstractmethod |
| | def get_function_slots() -> SLOTS: |
| | r""" |
| | Gets a list of slots corresponding to a single function call. |
| | """ |
| | ... |
| |
|
| | @staticmethod |
| | @abstractmethod |
| | def tool_formatter(tools: List[Dict[str, Any]]) -> str: |
| | r""" |
| | Generates the system message describing all the available tools. |
| | """ |
| | ... |
| |
|
| | @staticmethod |
| | @abstractmethod |
| | def tool_extractor(content: str) -> Union[str, List["FunctionCall"]]: |
| | r""" |
| | Extracts all the function calls from the response message. |
| | """ |
| | ... |
| |
|
| |
|
| | class DefaultToolUtils(ToolUtils): |
| | @override |
| | @staticmethod |
| | def get_function_slots() -> SLOTS: |
| | return ["Action: {{name}}\nAction Input: {{arguments}}\n"] |
| |
|
| | @override |
| | @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)) |
| |
|
| | @override |
| | @staticmethod |
| | def tool_extractor(content: str) -> Union[str, List["FunctionCall"]]: |
| | 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): |
| | @override |
| | @staticmethod |
| | def get_function_slots() -> SLOTS: |
| | return ["{{name}}\n{{arguments}}"] |
| |
|
| | @override |
| | @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) |
| |
|
| | @override |
| | @staticmethod |
| | def tool_extractor(content: str) -> Union[str, List["FunctionCall"]]: |
| | 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))] |
| |
|
| |
|
| | TOOLS = { |
| | "default": DefaultToolUtils(), |
| | "glm4": GLM4ToolUtils(), |
| | } |
| |
|
| |
|
| | def get_tool_utils(name: str) -> "ToolUtils": |
| | tool_utils = TOOLS.get(name, None) |
| | if tool_utils is None: |
| | raise ValueError("Tool utils `{}` not found.".format(name)) |
| |
|
| | return tool_utils |
| |
|