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| import json
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| import re
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| from abc import ABC, abstractmethod
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| from dataclasses import dataclass
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| from datetime import datetime
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| from typing import Any, NamedTuple, Union
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|
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| from typing_extensions import override
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|
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|
|
| class FunctionCall(NamedTuple):
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| name: str
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| arguments: str
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|
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|
|
| DEFAULT_TOOL_PROMPT = (
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| "You have access to the following tools:\n{tool_text}"
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| "Use the following format if using a tool:\n"
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| "```\n"
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| "Action: tool name (one of [{tool_names}])\n"
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| "Action Input: the input to the tool, in a JSON format representing the kwargs "
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| """(e.g. ```{{"input": "hello world", "num_beams": 5}}```)\n"""
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| "```\n"
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| )
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|
|
| GLM4_TOOL_PROMPT = (
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| "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,"
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| "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}"
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| )
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|
|
| LLAMA3_TOOL_PROMPT = (
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| "Cutting Knowledge Date: December 2023\nToday Date: {date}\n\n"
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| "You have access to the following functions. To call a function, please respond with JSON for a function call. "
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| """Respond in the format {{"name": function name, "parameters": dictionary of argument name and its value}}. """
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| "Do not use variables.\n\n{tool_text}"
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| )
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|
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| QWEN_TOOL_PROMPT = (
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| "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\n"
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| "You are provided with function signatures within <tools></tools> XML tags:\n<tools>{tool_text}"
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| "\n</tools>\n\nFor each function call, return a json object with function name and arguments within "
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| """<tool_call></tool_call> XML tags:\n<tool_call>\n{{"name": <function-name>, """
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| """"arguments": <args-json-object>}}\n</tool_call>"""
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| )
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|
|
|
|
| @dataclass
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| class ToolUtils(ABC):
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| """Base class for tool utilities."""
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|
|
| @staticmethod
|
| @abstractmethod
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| def tool_formatter(tools: list[dict[str, Any]]) -> str:
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| r"""Generate the system message describing all the available tools."""
|
| ...
|
|
|
| @staticmethod
|
| @abstractmethod
|
| def function_formatter(functions: list["FunctionCall"]) -> str:
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| r"""Generate the assistant message including all the tool calls."""
|
| ...
|
|
|
| @staticmethod
|
| @abstractmethod
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| def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]:
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| r"""Extract all the function calls from the assistant message.
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|
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| It should be an inverse function of `function_formatter`.
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| """
|
| ...
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|
|
|
|
| class DefaultToolUtils(ToolUtils):
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| r"""Default tool using template."""
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|
|
| @override
|
| @staticmethod
|
| def tool_formatter(tools: list[dict[str, Any]]) -> str:
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| tool_text = ""
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| tool_names = []
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| for tool in tools:
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| param_text = ""
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| for name, param in tool["parameters"]["properties"].items():
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| required, enum, items = "", "", ""
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| if name in tool["parameters"].get("required", []):
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| required = ", required"
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|
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| if param.get("enum", None):
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| enum = ", should be one of [{}]".format(", ".join(param["enum"]))
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|
|
| if param.get("items", None):
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| items = ", where each item should be {}".format(param["items"].get("type", ""))
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|
|
| param_text += " - {name} ({type}{required}): {desc}{enum}{items}\n".format(
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| name=name,
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| type=param.get("type", ""),
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| required=required,
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| desc=param.get("description", ""),
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| enum=enum,
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| items=items,
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| )
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|
|
| tool_text += "> Tool Name: {name}\nTool Description: {desc}\nTool Args:\n{args}\n".format(
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| name=tool["name"], desc=tool.get("description", ""), args=param_text
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| )
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| tool_names.append(tool["name"])
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|
|
| return DEFAULT_TOOL_PROMPT.format(tool_text=tool_text, tool_names=", ".join(tool_names))
|
|
|
| @override
|
| @staticmethod
|
| def function_formatter(functions: list["FunctionCall"]) -> str:
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| function_text = ""
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| for name, arguments in functions:
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| function_text += f"Action: {name}\nAction Input: {arguments}\n"
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|
|
| return function_text
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|
|
| @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)
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| if not action_match:
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| return content
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|
|
| results = []
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| for match in action_match:
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| tool_name = match[0].strip()
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| tool_input = match[1].strip().strip('"').strip("```")
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| try:
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| arguments = json.loads(tool_input)
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| results.append(FunctionCall(tool_name, json.dumps(arguments, ensure_ascii=False)))
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| except json.JSONDecodeError:
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| return content
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|
|
| return results
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|
|
|
|
| class GLM4ToolUtils(ToolUtils):
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| r"""GLM-4 tool using template."""
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|
|
| @override
|
| @staticmethod
|
| def tool_formatter(tools: list[dict[str, Any]]) -> str:
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| tool_text = ""
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| for tool in tools:
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| 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(
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| name=tool["name"], body=json.dumps(tool, indent=4, ensure_ascii=False)
|
| )
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|
|
| return GLM4_TOOL_PROMPT.format(tool_text=tool_text)
|
|
|
| @override
|
| @staticmethod
|
| def function_formatter(functions: list["FunctionCall"]) -> str:
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| if len(functions) > 1:
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| raise ValueError("GLM-4 does not support parallel functions.")
|
|
|
| return f"{functions[0].name}\n{functions[0].arguments}"
|
|
|
| @override
|
| @staticmethod
|
| def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]:
|
| if "\n" not in content:
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| return content
|
|
|
| tool_name, tool_input = content.split("\n", maxsplit=1)
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| try:
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| arguments = json.loads(tool_input.strip())
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| except json.JSONDecodeError:
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| return content
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|
|
| return [FunctionCall(tool_name, json.dumps(arguments, ensure_ascii=False))]
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|
|
|
|
| class Llama3ToolUtils(ToolUtils):
|
| r"""Llama 3.x tool using template with `tools_in_user_message=False`.
|
|
|
| Reference: https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1/#json-based-tool-calling
|
| """
|
|
|
| @override
|
| @staticmethod
|
| def tool_formatter(tools: list[dict[str, Any]]) -> str:
|
| date = datetime.now().strftime("%d %b %Y")
|
| tool_text = ""
|
| for tool in tools:
|
| wrapped_tool = {"type": "function", "function": tool}
|
| tool_text += json.dumps(wrapped_tool, indent=4, ensure_ascii=False) + "\n\n"
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|
|
| return LLAMA3_TOOL_PROMPT.format(date=date, tool_text=tool_text)
|
|
|
| @override
|
| @staticmethod
|
| def function_formatter(functions: list["FunctionCall"]) -> str:
|
| if len(functions) > 1:
|
| raise ValueError("Llama-3 does not support parallel functions.")
|
|
|
| return f'{{"name": "{functions[0].name}", "parameters": {functions[0].arguments}}}'
|
|
|
| @override
|
| @staticmethod
|
| def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]:
|
| try:
|
| tool = json.loads(content.strip())
|
| except json.JSONDecodeError:
|
| return content
|
|
|
| if "name" not in tool or "parameters" not in tool:
|
| return content
|
|
|
| return [FunctionCall(tool["name"], json.dumps(tool["parameters"], ensure_ascii=False))]
|
|
|
|
|
| class MistralToolUtils(ToolUtils):
|
| r"""Mistral v0.3 tool using template."""
|
|
|
| @override
|
| @staticmethod
|
| def tool_formatter(tools: list[dict[str, Any]]) -> str:
|
| wrapped_tools = []
|
| for tool in tools:
|
| wrapped_tools.append({"type": "function", "function": tool})
|
|
|
| return "[AVAILABLE_TOOLS] " + json.dumps(wrapped_tools, ensure_ascii=False) + "[/AVAILABLE_TOOLS]"
|
|
|
| @override
|
| @staticmethod
|
| def function_formatter(functions: list["FunctionCall"]) -> str:
|
| function_texts = []
|
| for name, arguments in functions:
|
| function_texts.append(f'{{"name": "{name}", "arguments": {arguments}}}')
|
|
|
| return "[" + ", ".join(function_texts) + "]"
|
|
|
| @override
|
| @staticmethod
|
| def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]:
|
| try:
|
| tools = json.loads(content.strip())
|
| except json.JSONDecodeError:
|
| return content
|
|
|
| if not isinstance(tools, list):
|
| tools = [tools]
|
|
|
| results = []
|
| for tool in tools:
|
| if "name" not in tool or "arguments" not in tool:
|
| return content
|
|
|
| results.append(FunctionCall(tool["name"], json.dumps(tool["arguments"], ensure_ascii=False)))
|
|
|
| return results
|
|
|
|
|
| class QwenToolUtils(ToolUtils):
|
| r"""Qwen 2.5 tool using template."""
|
|
|
| @override
|
| @staticmethod
|
| def tool_formatter(tools: list[dict[str, Any]]) -> str:
|
| tool_text = ""
|
| for tool in tools:
|
| wrapped_tool = {"type": "function", "function": tool}
|
| tool_text += "\n" + json.dumps(wrapped_tool, ensure_ascii=False)
|
|
|
| return QWEN_TOOL_PROMPT.format(tool_text=tool_text)
|
|
|
| @override
|
| @staticmethod
|
| def function_formatter(functions: list["FunctionCall"]) -> str:
|
| function_texts = []
|
| for name, arguments in functions:
|
| function_texts.append(
|
| "<tool_call>\n" + f'{{"name": "{name}", "arguments": {arguments}}}' + "\n</tool_call>"
|
| )
|
|
|
| return "\n".join(function_texts)
|
|
|
| @override
|
| @staticmethod
|
| def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]:
|
| regex = re.compile(r"<tool_call>(.+?)</tool_call>(?=\s*<tool_call>|\s*$)", re.DOTALL)
|
| tool_match: list[str] = re.findall(regex, content)
|
| if not tool_match:
|
| return content
|
|
|
| results = []
|
| for tool in tool_match:
|
| try:
|
| tool = json.loads(tool.strip())
|
| except json.JSONDecodeError:
|
| return content
|
|
|
| if "name" not in tool or "arguments" not in tool:
|
| return content
|
|
|
| results.append(FunctionCall(tool["name"], json.dumps(tool["arguments"], ensure_ascii=False)))
|
|
|
| return results
|
|
|
|
|
| TOOLS = {
|
| "default": DefaultToolUtils(),
|
| "glm4": GLM4ToolUtils(),
|
| "llama3": Llama3ToolUtils(),
|
| "mistral": MistralToolUtils(),
|
| "qwen": QwenToolUtils(),
|
| }
|
|
|
|
|
| def get_tool_utils(name: str) -> "ToolUtils":
|
| tool_utils = TOOLS.get(name, None)
|
| if tool_utils is None:
|
| raise ValueError(f"Tool utils `{name}` not found.")
|
|
|
| return tool_utils
|
|
|