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| # 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}" | |
| ) | |
| class ToolUtils(ABC): | |
| def get_function_slots() -> SLOTS: ... | |
| def tool_formatter(tools: List[Dict[str, Any]]) -> str: ... | |
| def tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]: ... | |
| class DefaultToolUtils(ToolUtils): | |
| def get_function_slots() -> SLOTS: | |
| return ["Action: {{name}}\nAction Input: {{arguments}}\n"] | |
| 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)) | |
| 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): | |
| def get_function_slots() -> SLOTS: | |
| return ["{{name}}\n{{arguments}}"] | |
| 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) | |
| 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))] | |