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# Copyright 2025 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 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}"
)
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>"""
)
@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:
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:
function_text = ""
for name, arguments in functions:
function_text += f"Action: {name}\nAction Input: {arguments}\n"
return function_text
@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_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 = {"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:
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