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