103 lines
3.3 KiB
Python
103 lines
3.3 KiB
Python
from typing import List, Tuple, Type, Any
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# 导入新插件系统
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from src.plugin_system import BasePlugin, register_plugin, ComponentInfo
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from src.plugin_system.base.config_types import ConfigField
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from src.person_info.person_info import Person
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from src.plugin_system.base.base_tool import BaseTool, ToolParamType
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# 导入依赖的系统组件
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from src.common.logger import get_logger
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from src.plugins.built_in.relation.relation import BuildRelationAction
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from src.plugin_system.apis import llm_api
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logger = get_logger("relation_actions")
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class DeepThinkTool(BaseTool):
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"""获取用户信息"""
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name = "deep_think"
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description = "深度思考，对某个知识，概念或逻辑问题进行全面且深入的思考，当面临复杂环境或重要问题时，使用此获得更好的解决方案。"
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parameters = [
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("question", ToolParamType.STRING, "需要思考的问题，越具体越好（从上下文中总结）", True, None),
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]
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available_for_llm = True
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async def execute(self, function_args: dict[str, Any]) -> dict[str, Any]:
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"""执行比较两个数的大小
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Args:
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function_args: 工具参数
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Returns:
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dict: 工具执行结果
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"""
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question: str = function_args.get("question") # type: ignore
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print(f"question: {question}")
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prompt = f"""
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请你思考以下问题，以简洁的一段话回答：
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{question}
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"""
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models = llm_api.get_available_models()
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chat_model_config = models.get("replyer") # 使用字典访问方式
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success, thinking_result, _, _ = await llm_api.generate_with_model(
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prompt, model_config=chat_model_config, request_type="deep_think"
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)
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logger.info(f"{question}: {thinking_result}")
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thinking_result =f"思考结果：{thinking_result}\n**注意** 因为你进行了深度思考，最后的回复内容可以回复的长一些，更加详细一些，不用太简洁。\n"
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return {"content": thinking_result}
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@register_plugin
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class DeepThinkPlugin(BasePlugin):
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"""关系动作插件
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系统内置插件，提供基础的聊天交互功能：
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- Reply: 回复动作
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- NoReply: 不回复动作
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- Emoji: 表情动作
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注意：插件基本信息优先从_manifest.json文件中读取
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"""
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# 插件基本信息
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plugin_name: str = "deep_think" # 内部标识符
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enable_plugin: bool = True
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dependencies: list[str] = [] # 插件依赖列表
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python_dependencies: list[str] = [] # Python包依赖列表
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config_file_name: str = "config.toml"
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# 配置节描述
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config_section_descriptions = {
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"plugin": "插件启用配置",
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"components": "核心组件启用配置",
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}
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# 配置Schema定义
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config_schema: dict = {
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"plugin": {
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"enabled": ConfigField(type=bool, default=False, description="是否启用插件"),
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"config_version": ConfigField(type=str, default="2.0.0", description="配置文件版本"),
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}
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}
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def get_plugin_components(self) -> List[Tuple[ComponentInfo, Type]]:
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"""返回插件包含的组件列表"""
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# --- 根据配置注册组件 ---
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components = []
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components.append((DeepThinkTool.get_tool_info(), DeepThinkTool))
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return components
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