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import re |
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from typing import TYPE_CHECKING, List, Optional, Tuple, Union |
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import json |
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from .base import BaseAgentTemplate |
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if TYPE_CHECKING: |
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from swift.llm.infer import Function |
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from swift.llm.template import Prompt |
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class GLM4AgentTemplate(BaseAgentTemplate): |
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is_glm4_0414 = False |
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@staticmethod |
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def _find_function_call(single_content: str) -> Optional['Function']: |
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from swift.llm.infer import Function |
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single_content = single_content.replace('<|observation|>', '') |
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pattern = re.compile(r'([^\n`]*?)\n({.*?})(?=\w*\n|$)', re.DOTALL) |
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matches = pattern.findall(single_content) |
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if not matches: |
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return |
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name, arguments = matches[0] |
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return Function(name=name, arguments=arguments) |
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def get_toolcall(self, response: str) -> List['Function']: |
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toolcall_list = response.split('<|assistant|>') |
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functions = [] |
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for toolcall in toolcall_list: |
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function = self._find_function_call(toolcall) |
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if function: |
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functions.append(function) |
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if len(functions) == 0: |
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return super().get_toolcall(response) |
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return functions |
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def _format_tools(self, tools: List[Union[str, dict]], system: str, user_message=None) -> str: |
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tool_descs = [] |
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for tool in tools: |
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tool = self.unwrap_tool(tool) |
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name = self._get_tool_name(tool) |
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tool_descs.append(f'## {name}\n\n{json.dumps(tool, ensure_ascii=False, indent=4)}\n' |
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'在调用上述函数时，请使用 Json 格式表示调用的参数。') |
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glm4_system = '你是一个名为 GLM-4 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。\n\n' |
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return ('' if self.is_glm4_0414 else glm4_system) + """# 可用工具 |
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""" + '\n'.join(tool_descs) |
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def _format_tool_responses( |
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self, |
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assistant_content: str, |
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tool_messages, |
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) -> Tuple[str, 'Prompt']: |
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with_action = self.keyword.action in assistant_content and self.keyword.action_input in assistant_content |
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if with_action: |
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return super()._format_tool_responses(assistant_content, tool_messages) |
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res = ['\n'] |
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for i, tool_message in enumerate(tool_messages): |
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tool_content = tool_message['content'] |
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if i > 0: |
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res.append('<|observation|>\n') |
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res.append(tool_content) |
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res.append('<|assistant|>\n') |
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return assistant_content, res |
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def _format_tool_calls(self, tool_call_messages) -> str: |
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tool_calls = [] |
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for message in tool_call_messages: |
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tool_call = self._parse_tool_call(message['content']) |
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tool_calls.append(f'{tool_call["name"]}\n{tool_call["arguments"]}') |
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return '<|assistant|>'.join(tool_calls) + '<|observation|>' |
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class GLM4_0414AgentTemplate(GLM4AgentTemplate): |
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is_glm4_0414 = True |
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