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|
| | import json |
| | import re |
| | from abc import ABC, abstractmethod |
| | from dataclasses import dataclass |
| | from datetime import datetime |
| | from typing import Any, NamedTuple, Union |
| |
|
| | from typing_extensions import override |
| |
|
| |
|
| | class FunctionCall(NamedTuple): |
| | name: str |
| | arguments: str |
| |
|
| |
|
| | 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 公司训练的语言模型 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。\n\n# 可用工具{tool_text}" |
| | ) |
| |
|
| | GLM4_MOE_TOOL_PROMPT = ( |
| | "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\n" |
| | "You are provided with function signatures within <tools></tools> XML tags:\n<tools>{tool_text}" |
| | "\n</tools>\n\nFor each function call, output the function name and arguments within the following XML format:" |
| | "\n<tool_call>{{function-name}}" |
| | "\n<arg_key>{{arg-key-1}}</arg_key>" |
| | "\n<arg_value>{{arg-value-1}}</arg_value>" |
| | "\n<arg_key>{{arg-key-2}}</arg_key>" |
| | "\n<arg_value>{{arg-value-2}}</arg_value>" |
| | "\n...\n</tool_call>\n" |
| | ) |
| |
|
| | LLAMA3_TOOL_PROMPT = ( |
| | "Cutting Knowledge Date: December 2023\nToday Date: {date}\n\n" |
| | "You have access to the following functions. To call a function, please respond with JSON for a function call. " |
| | """Respond in the format {{"name": function name, "parameters": dictionary of argument name and its value}}. """ |
| | "Do not use variables.\n\n{tool_text}" |
| | ) |
| |
|
| | QWEN_TOOL_PROMPT = ( |
| | "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\n" |
| | "You are provided with function signatures within <tools></tools> XML tags:\n<tools>{tool_text}" |
| | "\n</tools>\n\nFor each function call, return a json object with function name and arguments within " |
| | """<tool_call></tool_call> XML tags:\n<tool_call>\n{{"name": <function-name>, """ |
| | """"arguments": <args-json-object>}}\n</tool_call>""" |
| | ) |
| |
|
| | SEED_TOOL_PROMPT = ( |
| | "system\nYou are Doubao, a helpful AI assistant. You may call one or more functions to assist with the user query." |
| | "Tool List:\nYou are authorized to use the following tools (described in JSON Schema format). Before performing " |
| | "any task, you must decide how to call them based on the descriptions and parameters of these tools.{tool_text}\n" |
| | "工具调用请遵循如下格式:\n<seed:tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>value_1" |
| | "</parameter>\n<parameter=example_parameter_2>This is the value for the second parameter\nthat can span\nmultiple " |
| | "lines</parameter>\n</function>\n</seed:tool_call>\n" |
| | ) |
| |
|
| | LING_TOOL_PROMPT = ( |
| | "# Tools\n\nYou may call one or more functions to assist with the user query.\n\n" |
| | "You are provided with function signatures within <tools></tools> XML tags:\n<tools>{tool_text}" |
| | "\n</tools>\n\nFor each function call, return a json object with function name and arguments within " |
| | """<tool_call></tool_call> XML tags:\n<tool_call>\n{{"name": <function-name>, """ |
| | """"arguments": <args-json-object>}}\n</tool_call>""" |
| | ) |
| |
|
| |
|
| | @dataclass |
| | class ToolUtils(ABC): |
| | """Base class for tool utilities.""" |
| |
|
| | @staticmethod |
| | @abstractmethod |
| | def tool_formatter(tools: list[dict[str, Any]]) -> str: |
| | r"""Generate the system message describing all the available tools.""" |
| | ... |
| |
|
| | @staticmethod |
| | @abstractmethod |
| | def function_formatter(functions: list["FunctionCall"]) -> str: |
| | r"""Generate the assistant message including all the tool calls.""" |
| | ... |
| |
|
| | @staticmethod |
| | @abstractmethod |
| | def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]: |
| | r"""Extract all the function calls from the assistant message. |
| | |
| | It should be an inverse function of `function_formatter`. |
| | """ |
| | ... |
| |
|
| |
|
| | class DefaultToolUtils(ToolUtils): |
| | r"""Default tool using template.""" |
| |
|
| | @override |
| | @staticmethod |
| | def tool_formatter(tools: list[dict[str, Any]]) -> str: |
| | tool_text = "" |
| | tool_names = [] |
| | for tool in tools: |
| | tool = tool.get("function", "") if tool.get("type") == "function" else tool |
| | 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 function_formatter(functions: list["FunctionCall"]) -> str: |
| | return "\n".join([f"Action: {name}\nAction Input: {arguments}" for name, arguments in functions]) |
| |
|
| | @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(FunctionCall(tool_name, json.dumps(arguments, ensure_ascii=False))) |
| | except json.JSONDecodeError: |
| | return content |
| |
|
| | return results |
| |
|
| |
|
| | class GLM4ToolUtils(ToolUtils): |
| | r"""GLM-4 tool using template.""" |
| |
|
| | @override |
| | @staticmethod |
| | def tool_formatter(tools: list[dict[str, Any]]) -> str: |
| | tool_text = "" |
| | for tool in tools: |
| | tool = tool.get("function", "") if tool.get("type") == "function" else tool |
| | 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 function_formatter(functions: list["FunctionCall"]) -> str: |
| | if len(functions) > 1: |
| | 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: |
| | return content |
| |
|
| | tool_name, tool_input = content.split("\n", maxsplit=1) |
| | try: |
| | arguments = json.loads(tool_input.strip()) |
| | except json.JSONDecodeError: |
| | return content |
| |
|
| | return [FunctionCall(tool_name, json.dumps(arguments, ensure_ascii=False))] |
| |
|
| |
|
| | 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 = tool if tool.get("type") == "function" else {"type": "function", "function": tool} |
| | tool_text += json.dumps(wrapped_tool, indent=4, ensure_ascii=False) + "\n\n" |
| |
|
| | return LLAMA3_TOOL_PROMPT.format(date=date, tool_text=tool_text) |
| |
|
| | @override |
| | @staticmethod |
| | def function_formatter(functions: list["FunctionCall"]) -> str: |
| | function_objects = [{"name": name, "parameters": json.loads(arguments)} for name, arguments in functions] |
| | return json.dumps(function_objects[0] if len(function_objects) == 1 else function_objects, ensure_ascii=False) |
| |
|
| | @override |
| | @staticmethod |
| | def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]: |
| | try: |
| | tools = json.loads(content.strip()) |
| | except json.JSONDecodeError: |
| | return content |
| |
|
| | tools = [tools] if not isinstance(tools, list) else tools |
| | try: |
| | return [FunctionCall(tool["name"], json.dumps(tool["parameters"], ensure_ascii=False)) for tool in tools] |
| | except KeyError: |
| | return content |
| |
|
| |
|
| | 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(tool if tool.get("type") == "function" else {"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: |
| | return json.dumps( |
| | [{"name": name, "arguments": json.loads(arguments)} for name, arguments in functions], ensure_ascii=False |
| | ) |
| |
|
| | @override |
| | @staticmethod |
| | def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]: |
| | try: |
| | tools = json.loads(content.strip()) |
| | except json.JSONDecodeError: |
| | return content |
| |
|
| | tools = [tools] if not isinstance(tools, list) else tools |
| | try: |
| | return [FunctionCall(tool["name"], json.dumps(tool["arguments"], ensure_ascii=False)) for tool in tools] |
| | except KeyError: |
| | return content |
| |
|
| |
|
| | 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 = tool if tool.get("type") == "function" else {"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 = [ |
| | json.dumps({"name": name, "arguments": json.loads(arguments)}, ensure_ascii=False) |
| | for name, arguments in functions |
| | ] |
| | return "\n".join([f"<tool_call>\n{text}\n</tool_call>" for text in 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 |
| |
|
| |
|
| | class GLM4MOEToolUtils(QwenToolUtils): |
| | r"""GLM-4-MOE tool using template.""" |
| |
|
| | @override |
| | @staticmethod |
| | def tool_formatter(tools: list[dict[str, Any]]) -> str: |
| | tool_text = "" |
| | for tool in tools: |
| | wrapped_tool = tool if tool.get("type") == "function" else {"type": "function", "function": tool} |
| | tool_text += "\n" + json.dumps(wrapped_tool, ensure_ascii=False) |
| |
|
| | return GLM4_MOE_TOOL_PROMPT.format(tool_text=tool_text) |
| |
|
| | @override |
| | @staticmethod |
| | def function_formatter(functions: list["FunctionCall"]) -> str: |
| | function_json = [ |
| | {"func_name": name, "func_key_values": json.loads(arguments)} for name, arguments in functions |
| | ] |
| | function_texts = [] |
| | for func in function_json: |
| | prompt = "\n<tool_call>" + func["func_name"] |
| | for key, value in func["func_key_values"].items(): |
| | prompt += "\n<arg_key>" + key + "</arg_key>" |
| | if not isinstance(value, str): |
| | value = json.dumps(value, ensure_ascii=False) |
| | prompt += "\n<arg_value>" + value + "</arg_value>" |
| | function_texts.append(prompt) |
| |
|
| | return "\n".join(function_texts) |
| |
|
| |
|
| | class SeedToolUtils(ToolUtils): |
| | r"""Seed tool using template.""" |
| |
|
| | @override |
| | @staticmethod |
| | def tool_formatter(tools: list[dict[str, Any]]) -> str: |
| | return SEED_TOOL_PROMPT.format(tool_text="\n" + json.dumps(tools, ensure_ascii=False)) |
| |
|
| | @override |
| | @staticmethod |
| | def function_formatter(functions: list["FunctionCall"]) -> str: |
| | function_json = [ |
| | {"func_name": name, "func_key_values": json.loads(arguments)} for name, arguments in functions |
| | ] |
| | function_texts = [] |
| | for func in function_json: |
| | prompt = "\n<seed:tool_call>\n<function=" + func["func_name"] |
| | for key, value in func["func_key_values"].items(): |
| | prompt += "\n<parameter=" + key + ">" |
| | if not isinstance(value, str): |
| | value = json.dumps(value, ensure_ascii=False) |
| | prompt += value + "</parameter>" |
| | prompt += "\n</function>\n</seed:tool_call>" |
| | function_texts.append(prompt) |
| |
|
| | return "\n".join(function_texts) |
| |
|
| | @override |
| | @staticmethod |
| | def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]: |
| | results = [] |
| | regex = re.compile( |
| | r"<seed:tool_call>\s*<function=\s*([^\s<]+)\s*(.*?)\s*</function>\s*</seed:tool_call>", re.DOTALL |
| | ) |
| | for func_name, params_block in re.findall(regex, content): |
| | args_dict = {} |
| | param_pattern = re.compile(r"<parameter=(.*?)>(.*?)</parameter>", re.DOTALL) |
| | for key, raw_value in re.findall(param_pattern, params_block.strip()): |
| | value = raw_value.strip() |
| | try: |
| | parsed_value = json.loads(value) |
| | except json.JSONDecodeError: |
| | parsed_value = raw_value |
| | args_dict[key] = parsed_value |
| |
|
| | results.append(FunctionCall(func_name.strip(), json.dumps(args_dict, ensure_ascii=False))) |
| |
|
| | return results |
| |
|
| |
|
| | class LingToolUtils(QwenToolUtils): |
| | r"""Ling v2 tool using template.""" |
| |
|
| | @override |
| | @staticmethod |
| | def tool_formatter(tools: list[dict[str, Any]]) -> str: |
| | tool_text = "" |
| | for tool in tools: |
| | wrapped_tool = tool if tool.get("type") == "function" else {"type": "function", "function": tool} |
| | tool_text += "\n" + json.dumps(wrapped_tool, ensure_ascii=False) |
| |
|
| | return LING_TOOL_PROMPT.format(tool_text=tool_text) + "\n" + "detailed thinking off" |
| |
|
| |
|
| | TOOLS = { |
| | "default": DefaultToolUtils(), |
| | "glm4": GLM4ToolUtils(), |
| | "llama3": Llama3ToolUtils(), |
| | "mistral": MistralToolUtils(), |
| | "qwen": QwenToolUtils(), |
| | "glm4_moe": GLM4MOEToolUtils(), |
| | "seed_oss": SeedToolUtils(), |
| | "ling": LingToolUtils(), |
| | } |
| |
|
| |
|
| | 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 |
| |
|