move：移动action的目录
This commit is contained in:
SengokuCola
@@ -1,5 +1,5 @@
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from typing import Dict, List, Optional, Type, Any
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from src.chat.focus_chat.planners.actions.base_action import BaseAction, _ACTION_REGISTRY
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from src.chat.actions.base_action import BaseAction, _ACTION_REGISTRY
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from src.chat.heart_flow.observation.observation import Observation
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from src.chat.focus_chat.replyer.default_replyer import DefaultReplyer
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from src.chat.focus_chat.expressors.default_expressor import DefaultExpressor
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@@ -9,8 +9,8 @@ import importlib
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import pkgutil
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import os
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# 导入动作类，确保装饰器被执行
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import src.chat.focus_chat.planners.actions # noqa
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# 不再需要导入动作类，因为已经在main.py中导入
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# import src.chat.actions.default_actions # noqa
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logger = get_logger("action_manager")
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@@ -114,42 +114,13 @@ class ActionManager:
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def _load_plugin_actions(self) -> None:
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"""
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加载所有插件目录中的动作
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注意：插件动作的实际导入已经在main.py中完成，这里只需要从_ACTION_REGISTRY获取
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"""
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try:
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# 检查插件目录是否存在
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plugin_path = "src.plugins"
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plugin_dir = plugin_path.replace(".", os.path.sep)
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if not os.path.exists(plugin_dir):
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logger.info(f"插件目录 {plugin_dir} 不存在，跳过插件动作加载")
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return
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# 导入插件包
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try:
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plugins_package = importlib.import_module(plugin_path)
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except ImportError as e:
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logger.error(f"导入插件包失败: {e}")
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return
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# 遍历插件包中的所有子包
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for _, plugin_name, is_pkg in pkgutil.iter_modules(
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plugins_package.__path__, plugins_package.__name__ + "."
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):
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if not is_pkg:
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continue
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# 检查插件是否有actions子包
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plugin_actions_path = f"{plugin_name}.actions"
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try:
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# 尝试导入插件的actions包
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importlib.import_module(plugin_actions_path)
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logger.info(f"成功加载插件动作模块: {plugin_actions_path}")
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except ImportError as e:
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logger.debug(f"插件 {plugin_name} 没有actions子包或导入失败: {e}")
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continue
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# 再次从_ACTION_REGISTRY获取所有动作（包括刚刚从插件加载的）
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# 插件动作已在main.py中加载，这里只需要从_ACTION_REGISTRY获取
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self._load_registered_actions()
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logger.info(f"从注册表加载插件动作成功")
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except Exception as e:
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logger.error(f"加载插件动作失败: {e}")
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@@ -251,7 +222,7 @@ class ActionManager:
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else:
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logger.debug(f"动作 {action_name} 在模式 {mode} 下不可用 (mode_enable: {action_mode})")
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logger.info(f"模式 {mode} 下可用动作: {list(filtered_actions.keys())}")
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logger.debug(f"模式 {mode} 下可用动作: {list(filtered_actions.keys())}")
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return filtered_actions
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def add_action_to_using(self, action_name: str) -> bool:
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@@ -291,7 +262,7 @@ class ActionManager:
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return False
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del self._using_actions[action_name]
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logger.info(f"已从使用集中移除动作 {action_name}")
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logger.debug(f"已从使用集中移除动作 {action_name}")
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return True
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def add_action(self, action_name: str, description: str, parameters: Dict = None, require: List = None) -> bool:
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@@ -358,7 +329,7 @@ class ActionManager:
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for action_name in system_core_actions:
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if action_name in self._registered_actions and action_name not in self._using_actions:
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self._using_actions[action_name] = self._registered_actions[action_name]
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logger.info(f"添加系统核心动作到使用集: {action_name}")
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logger.debug(f"添加系统核心动作到使用集: {action_name}")
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def add_system_action_if_needed(self, action_name: str) -> bool:
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"""
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@@ -1,7 +0,0 @@
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# 导入所有动作模块以确保装饰器被执行
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from . import reply_action # noqa
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from . import no_reply_action # noqa
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from . import exit_focus_chat_action # noqa
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from . import emoji_action # noqa
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# 在此处添加更多动作模块导入
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@@ -1,124 +0,0 @@
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from abc import ABC, abstractmethod
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from typing import Tuple, Dict, Type
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from src.common.logger_manager import get_logger
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logger = get_logger("base_action")
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# 全局动作注册表
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_ACTION_REGISTRY: Dict[str, Type["BaseAction"]] = {}
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_DEFAULT_ACTIONS: Dict[str, str] = {}
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# 动作激活类型枚举
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class ActionActivationType:
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ALWAYS = "always" # 默认参与到planner
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LLM_JUDGE = "llm_judge" # LLM判定是否启动该action到planner
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RANDOM = "random" # 随机启用action到planner
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KEYWORD = "keyword" # 关键词触发启用action到planner
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# 聊天模式枚举
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class ChatMode:
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FOCUS = "focus" # Focus聊天模式
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NORMAL = "normal" # Normal聊天模式
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ALL = "all" # 所有聊天模式
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def register_action(cls):
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"""
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动作注册装饰器
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用法:
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@register_action
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class MyAction(BaseAction):
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action_name = "my_action"
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action_description = "我的动作"
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focus_activation_type = ActionActivationType.ALWAYS
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normal_activation_type = ActionActivationType.ALWAYS
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mode_enable = ChatMode.ALL
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parallel_action = False
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...
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"""
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# 检查类是否有必要的属性
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if not hasattr(cls, "action_name") or not hasattr(cls, "action_description"):
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logger.error(f"动作类 {cls.__name__} 缺少必要的属性: action_name 或 action_description")
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return cls
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action_name = cls.action_name
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action_description = cls.action_description
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is_enabled = getattr(cls, "enable_plugin", True) # 默认启用插件
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if not action_name or not action_description:
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logger.error(f"动作类 {cls.__name__} 的 action_name 或 action_description 为空")
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return cls
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# 将动作类注册到全局注册表
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_ACTION_REGISTRY[action_name] = cls
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# 如果启用插件，添加到默认动作集
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if is_enabled:
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_DEFAULT_ACTIONS[action_name] = action_description
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logger.info(f"已注册动作: {action_name} -> {cls.__name__}，插件启用: {is_enabled}")
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return cls
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class BaseAction(ABC):
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"""动作基类接口
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所有具体的动作类都应该继承这个基类，并实现handle_action方法。
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"""
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def __init__(self, action_data: dict, reasoning: str, cycle_timers: dict, thinking_id: str):
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"""初始化动作
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Args:
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action_name: 动作名称
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action_data: 动作数据
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reasoning: 执行该动作的理由
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cycle_timers: 计时器字典
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thinking_id: 思考ID
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"""
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# 每个动作必须实现
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self.action_name: str = "base_action"
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self.action_description: str = "基础动作"
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self.action_parameters: dict = {}
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self.action_require: list[str] = []
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# 动作激活类型设置
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# Focus模式下的激活类型，默认为always
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self.focus_activation_type: str = ActionActivationType.ALWAYS
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# Normal模式下的激活类型，默认为always
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self.normal_activation_type: str = ActionActivationType.ALWAYS
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# 随机激活的概率(0.0-1.0)，用于RANDOM激活类型
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self.random_activation_probability: float = 0.3
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# LLM判定的提示词，用于LLM_JUDGE激活类型
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self.llm_judge_prompt: str = ""
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# 关键词触发列表，用于KEYWORD激活类型
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self.activation_keywords: list[str] = []
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# 关键词匹配是否区分大小写
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self.keyword_case_sensitive: bool = False
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# 模式启用设置：指定在哪些聊天模式下启用此动作
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# 可选值: "focus"(仅Focus模式), "normal"(仅Normal模式), "all"(所有模式)
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self.mode_enable: str = ChatMode.ALL
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# 并行执行设置：仅在Normal模式下生效，设置为True的动作可以与回复动作并行执行
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# 而不是替代回复动作，适用于图片生成、TTS、禁言等不需要覆盖回复的动作
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self.parallel_action: bool = False
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self.associated_types: list[str] = []
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self.enable_plugin: bool = True # 是否启用插件，默认启用
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self.action_data = action_data
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self.reasoning = reasoning
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self.cycle_timers = cycle_timers
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self.thinking_id = thinking_id
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@abstractmethod
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async def handle_action(self) -> Tuple[bool, str]:
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"""处理动作的抽象方法，需要被子类实现
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Returns:
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Tuple[bool, str]: (是否执行成功, 回复文本)
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"""
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pass
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@@ -1,150 +0,0 @@
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from src.common.logger_manager import get_logger
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from src.chat.focus_chat.planners.actions.base_action import BaseAction, register_action, ActionActivationType, ChatMode
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from typing import Tuple, List
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from src.chat.heart_flow.observation.observation import Observation
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from src.chat.focus_chat.replyer.default_replyer import DefaultReplyer
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from src.chat.message_receive.chat_stream import ChatStream
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from src.chat.focus_chat.hfc_utils import create_empty_anchor_message
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from src.config.config import global_config
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logger = get_logger("action_taken")
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@register_action
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class EmojiAction(BaseAction):
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"""表情动作处理类
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处理构建和发送消息表情的动作。
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"""
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action_name: str = "emoji"
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action_description: str = "当你想单独发送一个表情包辅助你的回复表达"
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action_parameters: dict[str:str] = {
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"description": "文字描述你想要发送的表情包内容",
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}
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action_require: list[str] = [
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"表达情绪时可以选择使用",
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"重点：不要连续发，如果你已经发过[表情包]，就不要选择此动作"]
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associated_types: list[str] = ["emoji"]
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enable_plugin = True
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focus_activation_type = ActionActivationType.LLM_JUDGE
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normal_activation_type = ActionActivationType.RANDOM
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random_activation_probability = global_config.normal_chat.emoji_chance
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parallel_action = True
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llm_judge_prompt = """
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判定是否需要使用表情动作的条件：
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1. 用户明确要求使用表情包
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2. 这是一个适合表达强烈情绪的场合
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3. 不要发送太多表情包，如果你已经发送过多个表情包
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"""
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# 模式启用设置 - 表情动作只在Focus模式下使用
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mode_enable = ChatMode.ALL
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def __init__(
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self,
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action_data: dict,
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reasoning: str,
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cycle_timers: dict,
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thinking_id: str,
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observations: List[Observation],
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chat_stream: ChatStream,
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log_prefix: str,
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replyer: DefaultReplyer,
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**kwargs,
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):
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"""初始化回复动作处理器
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Args:
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action_name: 动作名称
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action_data: 动作数据，包含 message, emojis, target 等
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reasoning: 执行该动作的理由
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cycle_timers: 计时器字典
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thinking_id: 思考ID
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observations: 观察列表
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replyer: 回复器
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chat_stream: 聊天流
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log_prefix: 日志前缀
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"""
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super().__init__(action_data, reasoning, cycle_timers, thinking_id)
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self.observations = observations
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self.replyer = replyer
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self.chat_stream = chat_stream
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self.log_prefix = log_prefix
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async def handle_action(self) -> Tuple[bool, str]:
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"""
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处理回复动作
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Returns:
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Tuple[bool, str]: (是否执行成功, 回复文本)
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"""
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# 注意: 此处可能会使用不同的expressor实现根据任务类型切换不同的回复策略
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return await self._handle_reply(
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reasoning=self.reasoning,
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reply_data=self.action_data,
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cycle_timers=self.cycle_timers,
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thinking_id=self.thinking_id,
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)
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async def _handle_reply(
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self, reasoning: str, reply_data: dict, cycle_timers: dict, thinking_id: str
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) -> tuple[bool, str]:
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"""
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处理统一的回复动作 - 可包含文本和表情，顺序任意
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reply_data格式:
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{
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"description": "描述你想要发送的表情"
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}
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"""
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logger.info(f"{self.log_prefix} 决定发送表情")
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# 从聊天观察获取锚定消息
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# chatting_observation: ChattingObservation = next(
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# obs for obs in self.observations if isinstance(obs, ChattingObservation)
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# )
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# if reply_data.get("target"):
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# anchor_message = chatting_observation.search_message_by_text(reply_data["target"])
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# else:
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# anchor_message = None
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# 如果没有找到锚点消息，创建一个占位符
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# if not anchor_message:
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# logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
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# anchor_message = await create_empty_anchor_message(
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# self.chat_stream.platform, self.chat_stream.group_info, self.chat_stream
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# )
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# else:
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# anchor_message.update_chat_stream(self.chat_stream)
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logger.info(f"{self.log_prefix} 为了表情包创建占位符")
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anchor_message = await create_empty_anchor_message(
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self.chat_stream.platform, self.chat_stream.group_info, self.chat_stream
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)
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success, reply_set = await self.replyer.deal_emoji(
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cycle_timers=cycle_timers,
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action_data=reply_data,
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anchor_message=anchor_message,
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# reasoning=reasoning,
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thinking_id=thinking_id,
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)
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reply_text = ""
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if reply_set:
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for reply in reply_set:
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type = reply[0]
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data = reply[1]
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if type == "text":
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reply_text += data
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elif type == "emoji":
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reply_text += data
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return success, reply_text
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@@ -1,88 +0,0 @@
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import asyncio
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import traceback
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from src.common.logger_manager import get_logger
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from src.chat.focus_chat.planners.actions.base_action import BaseAction, register_action, ChatMode
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from typing import Tuple, List
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from src.chat.heart_flow.observation.observation import Observation
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from src.chat.message_receive.chat_stream import ChatStream
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logger = get_logger("action_taken")
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@register_action
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class ExitFocusChatAction(BaseAction):
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"""退出专注聊天动作处理类
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处理决定退出专注聊天的动作。
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执行后会将所属的sub heartflow转变为normal_chat状态。
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"""
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action_name = "exit_focus_chat"
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action_description = "退出专注聊天，转为普通聊天模式"
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action_parameters = {}
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action_require = [
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"很长时间没有回复，你决定退出专注聊天",
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"当前内容不需要持续专注关注，你决定退出专注聊天",
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"聊天内容已经完成，你决定退出专注聊天",
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]
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# 退出专注聊天是系统核心功能，不是插件，但默认不启用（需要特定条件触发）
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enable_plugin = False
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# 模式启用设置 - 退出专注聊天动作只在Focus模式下使用
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mode_enable = ChatMode.FOCUS
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def __init__(
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self,
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action_data: dict,
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reasoning: str,
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cycle_timers: dict,
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thinking_id: str,
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observations: List[Observation],
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log_prefix: str,
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chat_stream: ChatStream,
|
||||
shutting_down: bool = False,
|
||||
**kwargs,
|
||||
):
|
||||
"""初始化退出专注聊天动作处理器
|
||||
|
||||
Args:
|
||||
action_data: 动作数据
|
||||
reasoning: 执行该动作的理由
|
||||
cycle_timers: 计时器字典
|
||||
thinking_id: 思考ID
|
||||
observations: 观察列表
|
||||
log_prefix: 日志前缀
|
||||
shutting_down: 是否正在关闭
|
||||
"""
|
||||
super().__init__(action_data, reasoning, cycle_timers, thinking_id)
|
||||
self.observations = observations
|
||||
self.log_prefix = log_prefix
|
||||
self._shutting_down = shutting_down
|
||||
|
||||
async def handle_action(self) -> Tuple[bool, str]:
|
||||
"""
|
||||
处理退出专注聊天的情况
|
||||
|
||||
工作流程：
|
||||
1. 将sub heartflow转换为normal_chat状态
|
||||
2. 等待新消息、超时或关闭信号
|
||||
3. 根据等待结果更新连续不回复计数
|
||||
4. 如果达到阈值，触发回调
|
||||
|
||||
Returns:
|
||||
Tuple[bool, str]: (是否执行成功, 状态转换消息)
|
||||
"""
|
||||
try:
|
||||
# 转换状态
|
||||
status_message = ""
|
||||
command = "stop_focus_chat"
|
||||
return True, status_message, command
|
||||
|
||||
except asyncio.CancelledError:
|
||||
logger.info(f"{self.log_prefix} 处理 'exit_focus_chat' 时等待被中断 (CancelledError)")
|
||||
raise
|
||||
except Exception as e:
|
||||
error_msg = f"处理 'exit_focus_chat' 时发生错误: {str(e)}"
|
||||
logger.error(f"{self.log_prefix} {error_msg}")
|
||||
logger.error(traceback.format_exc())
|
||||
return False, "", ""
|
||||
@@ -1,139 +0,0 @@
|
||||
import asyncio
|
||||
import traceback
|
||||
from src.common.logger_manager import get_logger
|
||||
from src.chat.utils.timer_calculator import Timer
|
||||
from src.chat.focus_chat.planners.actions.base_action import BaseAction, register_action, ActionActivationType, ChatMode
|
||||
from typing import Tuple, List
|
||||
from src.chat.heart_flow.observation.observation import Observation
|
||||
from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
|
||||
from src.chat.focus_chat.hfc_utils import parse_thinking_id_to_timestamp
|
||||
|
||||
logger = get_logger("action_taken")
|
||||
|
||||
# 常量定义
|
||||
WAITING_TIME_THRESHOLD = 1200 # 等待新消息时间阈值，单位秒
|
||||
|
||||
|
||||
@register_action
|
||||
class NoReplyAction(BaseAction):
|
||||
"""不回复动作处理类
|
||||
|
||||
处理决定不回复的动作。
|
||||
"""
|
||||
|
||||
action_name = "no_reply"
|
||||
action_description = "暂时不回复消息"
|
||||
action_parameters = {}
|
||||
action_require = [
|
||||
"你连续发送了太多消息，且无人回复",
|
||||
"想要休息一下",
|
||||
]
|
||||
enable_plugin = True
|
||||
|
||||
# 激活类型设置
|
||||
focus_activation_type = ActionActivationType.ALWAYS
|
||||
|
||||
# 模式启用设置 - no_reply动作只在Focus模式下使用
|
||||
mode_enable = ChatMode.FOCUS
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
action_data: dict,
|
||||
reasoning: str,
|
||||
cycle_timers: dict,
|
||||
thinking_id: str,
|
||||
observations: List[Observation],
|
||||
log_prefix: str,
|
||||
shutting_down: bool = False,
|
||||
**kwargs,
|
||||
):
|
||||
"""初始化不回复动作处理器
|
||||
|
||||
Args:
|
||||
action_name: 动作名称
|
||||
action_data: 动作数据
|
||||
reasoning: 执行该动作的理由
|
||||
cycle_timers: 计时器字典
|
||||
thinking_id: 思考ID
|
||||
observations: 观察列表
|
||||
log_prefix: 日志前缀
|
||||
shutting_down: 是否正在关闭
|
||||
"""
|
||||
super().__init__(action_data, reasoning, cycle_timers, thinking_id)
|
||||
self.observations = observations
|
||||
self.log_prefix = log_prefix
|
||||
self._shutting_down = shutting_down
|
||||
|
||||
async def handle_action(self) -> Tuple[bool, str]:
|
||||
"""
|
||||
处理不回复的情况
|
||||
|
||||
工作流程：
|
||||
1. 等待新消息、超时或关闭信号
|
||||
2. 根据等待结果更新连续不回复计数
|
||||
3. 如果达到阈值，触发回调
|
||||
|
||||
Returns:
|
||||
Tuple[bool, str]: (是否执行成功, 空字符串)
|
||||
"""
|
||||
logger.info(f"{self.log_prefix} 决定不回复: {self.reasoning}")
|
||||
|
||||
observation = self.observations[0] if self.observations else None
|
||||
|
||||
try:
|
||||
with Timer("等待新消息", self.cycle_timers):
|
||||
# 等待新消息、超时或关闭信号，并获取结果
|
||||
await self._wait_for_new_message(observation, self.thinking_id, self.log_prefix)
|
||||
|
||||
return True, "" # 不回复动作没有回复文本
|
||||
|
||||
except asyncio.CancelledError:
|
||||
logger.info(f"{self.log_prefix} 处理 'no_reply' 时等待被中断 (CancelledError)")
|
||||
raise
|
||||
except Exception as e: # 捕获调用管理器或其他地方可能发生的错误
|
||||
logger.error(f"{self.log_prefix} 处理 'no_reply' 时发生错误: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
return False, ""
|
||||
|
||||
async def _wait_for_new_message(self, observation: ChattingObservation, thinking_id: str, log_prefix: str) -> bool:
|
||||
"""
|
||||
等待新消息 或 检测到关闭信号
|
||||
|
||||
参数:
|
||||
observation: 观察实例
|
||||
thinking_id: 思考ID
|
||||
log_prefix: 日志前缀
|
||||
|
||||
返回:
|
||||
bool: 是否检测到新消息 (如果因关闭信号退出则返回 False)
|
||||
"""
|
||||
wait_start_time = asyncio.get_event_loop().time()
|
||||
while True:
|
||||
# --- 在每次循环开始时检查关闭标志 ---
|
||||
if self._shutting_down:
|
||||
logger.info(f"{log_prefix} 等待新消息时检测到关闭信号，中断等待。")
|
||||
return False # 表示因为关闭而退出
|
||||
# -----------------------------------
|
||||
|
||||
thinking_id_timestamp = parse_thinking_id_to_timestamp(thinking_id)
|
||||
|
||||
# 检查新消息
|
||||
if await observation.has_new_messages_since(thinking_id_timestamp):
|
||||
logger.info(f"{log_prefix} 检测到新消息")
|
||||
return True
|
||||
|
||||
# 检查超时 (放在检查新消息和关闭之后)
|
||||
if asyncio.get_event_loop().time() - wait_start_time > WAITING_TIME_THRESHOLD:
|
||||
logger.warning(f"{log_prefix} 等待新消息超时({WAITING_TIME_THRESHOLD}秒)")
|
||||
return False
|
||||
|
||||
try:
|
||||
# 短暂休眠，让其他任务有机会运行，并能更快响应取消或关闭
|
||||
await asyncio.sleep(0.5) # 缩短休眠时间
|
||||
except asyncio.CancelledError:
|
||||
# 如果在休眠时被取消，再次检查关闭标志
|
||||
# 如果是正常关闭，则不需要警告
|
||||
if not self._shutting_down:
|
||||
logger.warning(f"{log_prefix} _wait_for_new_message 的休眠被意外取消")
|
||||
# 无论如何，重新抛出异常，让上层处理
|
||||
raise
|
||||
@@ -1,779 +0,0 @@
|
||||
import traceback
|
||||
from typing import Tuple, Dict, List, Any, Optional, Union, Type
|
||||
from src.chat.focus_chat.planners.actions.base_action import BaseAction, register_action, ActionActivationType, ChatMode # noqa F401
|
||||
from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
|
||||
from src.chat.focus_chat.hfc_utils import create_empty_anchor_message
|
||||
from src.common.logger_manager import get_logger
|
||||
from src.llm_models.utils_model import LLMRequest
|
||||
from src.person_info.person_info import person_info_manager
|
||||
from abc import abstractmethod
|
||||
from src.config.config import global_config
|
||||
import os
|
||||
import inspect
|
||||
import toml # 导入 toml 库
|
||||
from src.common.database.database_model import ActionRecords
|
||||
from src.common.database.database import db
|
||||
from peewee import Model, DoesNotExist
|
||||
import json
|
||||
import time
|
||||
|
||||
# 以下为类型注解需要
|
||||
from src.chat.message_receive.chat_stream import ChatStream
|
||||
from src.chat.focus_chat.expressors.default_expressor import DefaultExpressor
|
||||
from src.chat.focus_chat.replyer.default_replyer import DefaultReplyer
|
||||
from src.chat.focus_chat.info.obs_info import ObsInfo
|
||||
|
||||
logger = get_logger("plugin_action")
|
||||
|
||||
|
||||
class PluginAction(BaseAction):
|
||||
"""插件动作基类
|
||||
|
||||
封装了主程序内部依赖，提供简化的API接口给插件开发者
|
||||
"""
|
||||
|
||||
action_config_file_name: Optional[str] = None # 插件可以覆盖此属性来指定配置文件名
|
||||
|
||||
# 默认激活类型设置，插件可以覆盖
|
||||
focus_activation_type = ActionActivationType.ALWAYS
|
||||
normal_activation_type = ActionActivationType.ALWAYS
|
||||
random_activation_probability: float = 0.3
|
||||
llm_judge_prompt: str = ""
|
||||
activation_keywords: list[str] = []
|
||||
keyword_case_sensitive: bool = False
|
||||
|
||||
# 默认模式启用设置 - 插件动作默认在所有模式下可用，插件可以覆盖
|
||||
mode_enable = ChatMode.ALL
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
action_data: dict,
|
||||
reasoning: str,
|
||||
cycle_timers: dict,
|
||||
thinking_id: str,
|
||||
global_config: Optional[dict] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""初始化插件动作基类"""
|
||||
super().__init__(action_data, reasoning, cycle_timers, thinking_id)
|
||||
|
||||
# 存储内部服务和对象引用
|
||||
self._services = {}
|
||||
self.config: Dict[str, Any] = {} # 用于存储插件自身的配置
|
||||
|
||||
# 从kwargs提取必要的内部服务
|
||||
if "observations" in kwargs:
|
||||
self._services["observations"] = kwargs["observations"]
|
||||
if "expressor" in kwargs:
|
||||
self._services["expressor"] = kwargs["expressor"]
|
||||
if "chat_stream" in kwargs:
|
||||
self._services["chat_stream"] = kwargs["chat_stream"]
|
||||
if "replyer" in kwargs:
|
||||
self._services["replyer"] = kwargs["replyer"]
|
||||
|
||||
self.log_prefix = kwargs.get("log_prefix", "")
|
||||
self._load_plugin_config() # 初始化时加载插件配置
|
||||
|
||||
def _load_plugin_config(self):
|
||||
"""
|
||||
加载插件自身的配置文件。
|
||||
配置文件应与插件模块在同一目录下。
|
||||
插件可以通过覆盖 `action_config_file_name` 类属性来指定文件名。
|
||||
如果 `action_config_file_name` 未指定，则不加载配置。
|
||||
仅支持 TOML (.toml) 格式。
|
||||
"""
|
||||
if not self.action_config_file_name:
|
||||
logger.debug(
|
||||
f"{self.log_prefix} 插件 {self.__class__.__name__} 未指定 action_config_file_name，不加载插件配置。"
|
||||
)
|
||||
return
|
||||
|
||||
try:
|
||||
plugin_module_path = inspect.getfile(self.__class__)
|
||||
plugin_dir = os.path.dirname(plugin_module_path)
|
||||
config_file_path = os.path.join(plugin_dir, self.action_config_file_name)
|
||||
|
||||
if not os.path.exists(config_file_path):
|
||||
logger.warning(
|
||||
f"{self.log_prefix} 插件 {self.__class__.__name__} 的配置文件 {config_file_path} 不存在。"
|
||||
)
|
||||
return
|
||||
|
||||
file_ext = os.path.splitext(self.action_config_file_name)[1].lower()
|
||||
|
||||
if file_ext == ".toml":
|
||||
with open(config_file_path, "r", encoding="utf-8") as f:
|
||||
self.config = toml.load(f) or {}
|
||||
logger.info(f"{self.log_prefix} 插件 {self.__class__.__name__} 的配置已从 {config_file_path} 加载。")
|
||||
else:
|
||||
logger.warning(
|
||||
f"{self.log_prefix} 不支持的插件配置文件格式: {file_ext}。仅支持 .toml。插件配置未加载。"
|
||||
)
|
||||
self.config = {} # 确保未加载时为空字典
|
||||
return
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"{self.log_prefix} 加载插件 {self.__class__.__name__} 的配置文件 {self.action_config_file_name} 时出错: {e}"
|
||||
)
|
||||
self.config = {} # 出错时确保 config 是一个空字典
|
||||
|
||||
def get_global_config(self, key: str, default: Any = None) -> Any:
|
||||
"""
|
||||
安全地从全局配置中获取一个值。
|
||||
插件应使用此方法读取全局配置，以保证只读和隔离性。
|
||||
"""
|
||||
|
||||
return global_config.get(key, default)
|
||||
|
||||
async def get_user_id_by_person_name(self, person_name: str) -> Tuple[str, str]:
|
||||
"""根据用户名获取用户ID"""
|
||||
person_id = person_info_manager.get_person_id_by_person_name(person_name)
|
||||
user_id = await person_info_manager.get_value(person_id, "user_id")
|
||||
platform = await person_info_manager.get_value(person_id, "platform")
|
||||
return platform, user_id
|
||||
|
||||
# 提供简化的API方法
|
||||
async def send_message(self, type: str, data: str, target: Optional[str] = "", display_message: str = "") -> bool:
|
||||
"""发送消息的简化方法
|
||||
|
||||
Args:
|
||||
text: 要发送的消息文本
|
||||
target: 目标消息（可选）
|
||||
|
||||
Returns:
|
||||
bool: 是否发送成功
|
||||
"""
|
||||
try:
|
||||
expressor: DefaultExpressor = self._services.get("expressor")
|
||||
chat_stream: ChatStream = self._services.get("chat_stream")
|
||||
|
||||
if not expressor or not chat_stream:
|
||||
logger.error(f"{self.log_prefix} 无法发送消息：缺少必要的内部服务")
|
||||
return False
|
||||
|
||||
# 构造简化的动作数据
|
||||
# reply_data = {"text": text, "target": target or "", "emojis": []}
|
||||
|
||||
# 获取锚定消息（如果有）
|
||||
observations = self._services.get("observations", [])
|
||||
|
||||
if len(observations) > 0:
|
||||
chatting_observation: ChattingObservation = next(
|
||||
obs for obs in observations if isinstance(obs, ChattingObservation)
|
||||
)
|
||||
|
||||
anchor_message = chatting_observation.search_message_by_text(target)
|
||||
else:
|
||||
anchor_message = None
|
||||
|
||||
# 如果没有找到锚点消息，创建一个占位符
|
||||
if not anchor_message:
|
||||
logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
|
||||
anchor_message = await create_empty_anchor_message(
|
||||
chat_stream.platform, chat_stream.group_info, chat_stream
|
||||
)
|
||||
else:
|
||||
anchor_message.update_chat_stream(chat_stream)
|
||||
|
||||
response_set = [
|
||||
(type, data),
|
||||
]
|
||||
|
||||
# 调用内部方法发送消息
|
||||
success = await expressor.send_response_messages(
|
||||
anchor_message=anchor_message,
|
||||
response_set=response_set,
|
||||
display_message=display_message,
|
||||
)
|
||||
|
||||
return success
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 发送消息时出错: {e}")
|
||||
traceback.print_exc()
|
||||
return False
|
||||
|
||||
async def send_message_by_expressor(self, text: str, target: Optional[str] = None) -> bool:
|
||||
"""发送消息的简化方法
|
||||
|
||||
Args:
|
||||
text: 要发送的消息文本
|
||||
target: 目标消息（可选）
|
||||
|
||||
Returns:
|
||||
bool: 是否发送成功
|
||||
"""
|
||||
expressor: DefaultExpressor = self._services.get("expressor")
|
||||
chat_stream: ChatStream = self._services.get("chat_stream")
|
||||
|
||||
if not expressor or not chat_stream:
|
||||
logger.error(f"{self.log_prefix} 无法发送消息：缺少必要的内部服务")
|
||||
return False
|
||||
|
||||
# 构造简化的动作数据
|
||||
reply_data = {"text": text, "target": target or "", "emojis": []}
|
||||
|
||||
# 获取锚定消息（如果有）
|
||||
observations = self._services.get("observations", [])
|
||||
|
||||
# 查找 ChattingObservation 实例
|
||||
chatting_observation = None
|
||||
for obs in observations:
|
||||
if isinstance(obs, ChattingObservation):
|
||||
chatting_observation = obs
|
||||
break
|
||||
|
||||
if not chatting_observation:
|
||||
logger.warning(f"{self.log_prefix} 未找到 ChattingObservation 实例，创建占位符")
|
||||
anchor_message = await create_empty_anchor_message(
|
||||
chat_stream.platform, chat_stream.group_info, chat_stream
|
||||
)
|
||||
else:
|
||||
anchor_message = chatting_observation.search_message_by_text(reply_data["target"])
|
||||
if not anchor_message:
|
||||
logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
|
||||
anchor_message = await create_empty_anchor_message(
|
||||
chat_stream.platform, chat_stream.group_info, chat_stream
|
||||
)
|
||||
else:
|
||||
anchor_message.update_chat_stream(chat_stream)
|
||||
|
||||
# 调用内部方法发送消息
|
||||
success, _ = await expressor.deal_reply(
|
||||
cycle_timers=self.cycle_timers,
|
||||
action_data=reply_data,
|
||||
anchor_message=anchor_message,
|
||||
reasoning=self.reasoning,
|
||||
thinking_id=self.thinking_id,
|
||||
)
|
||||
|
||||
return success
|
||||
|
||||
async def send_message_by_replyer(self, target: Optional[str] = None, extra_info_block: Optional[str] = None) -> bool:
|
||||
"""通过 replyer 发送消息的简化方法
|
||||
|
||||
Args:
|
||||
text: 要发送的消息文本
|
||||
target: 目标消息（可选）
|
||||
|
||||
Returns:
|
||||
bool: 是否发送成功
|
||||
"""
|
||||
replyer: DefaultReplyer = self._services.get("replyer")
|
||||
chat_stream: ChatStream = self._services.get("chat_stream")
|
||||
|
||||
if not replyer or not chat_stream:
|
||||
logger.error(f"{self.log_prefix} 无法发送消息：缺少必要的内部服务")
|
||||
return False
|
||||
|
||||
# 构造简化的动作数据
|
||||
reply_data = {"target": target or "", "extra_info_block": extra_info_block}
|
||||
|
||||
# 获取锚定消息（如果有）
|
||||
observations = self._services.get("observations", [])
|
||||
|
||||
# 查找 ChattingObservation 实例
|
||||
chatting_observation = None
|
||||
for obs in observations:
|
||||
if isinstance(obs, ChattingObservation):
|
||||
chatting_observation = obs
|
||||
break
|
||||
|
||||
if not chatting_observation:
|
||||
logger.warning(f"{self.log_prefix} 未找到 ChattingObservation 实例，创建占位符")
|
||||
anchor_message = await create_empty_anchor_message(
|
||||
chat_stream.platform, chat_stream.group_info, chat_stream
|
||||
)
|
||||
else:
|
||||
anchor_message = chatting_observation.search_message_by_text(reply_data["target"])
|
||||
if not anchor_message:
|
||||
logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
|
||||
anchor_message = await create_empty_anchor_message(
|
||||
chat_stream.platform, chat_stream.group_info, chat_stream
|
||||
)
|
||||
else:
|
||||
anchor_message.update_chat_stream(chat_stream)
|
||||
|
||||
# 调用内部方法发送消息
|
||||
success, _ = await replyer.deal_reply(
|
||||
cycle_timers=self.cycle_timers,
|
||||
action_data=reply_data,
|
||||
anchor_message=anchor_message,
|
||||
reasoning=self.reasoning,
|
||||
thinking_id=self.thinking_id,
|
||||
)
|
||||
|
||||
return success
|
||||
|
||||
def get_chat_type(self) -> str:
|
||||
"""获取当前聊天类型
|
||||
|
||||
Returns:
|
||||
str: 聊天类型 ("group" 或 "private")
|
||||
"""
|
||||
chat_stream: ChatStream = self._services.get("chat_stream")
|
||||
if chat_stream and hasattr(chat_stream, "group_info"):
|
||||
return "group" if chat_stream.group_info else "private"
|
||||
return "unknown"
|
||||
|
||||
def get_recent_messages(self, count: int = 5) -> List[Dict[str, Any]]:
|
||||
"""获取最近的消息
|
||||
|
||||
Args:
|
||||
count: 要获取的消息数量
|
||||
|
||||
Returns:
|
||||
List[Dict]: 消息列表，每个消息包含发送者、内容等信息
|
||||
"""
|
||||
messages = []
|
||||
observations = self._services.get("observations", [])
|
||||
|
||||
if observations and len(observations) > 0:
|
||||
obs = observations[0]
|
||||
if hasattr(obs, "get_talking_message"):
|
||||
obs: ObsInfo
|
||||
raw_messages = obs.get_talking_message()
|
||||
# 转换为简化格式
|
||||
for msg in raw_messages[-count:]:
|
||||
simple_msg = {
|
||||
"sender": msg.get("sender", "未知"),
|
||||
"content": msg.get("content", ""),
|
||||
"timestamp": msg.get("timestamp", 0),
|
||||
}
|
||||
messages.append(simple_msg)
|
||||
|
||||
return messages
|
||||
|
||||
def get_available_models(self) -> Dict[str, Any]:
|
||||
"""获取所有可用的模型配置
|
||||
|
||||
Returns:
|
||||
Dict[str, Any]: 模型配置字典，key为模型名称，value为模型配置
|
||||
"""
|
||||
if not hasattr(global_config, "model"):
|
||||
logger.error(f"{self.log_prefix} 无法获取模型列表：全局配置中未找到 model 配置")
|
||||
return {}
|
||||
|
||||
models = global_config.model
|
||||
|
||||
return models
|
||||
|
||||
async def generate_with_model(
|
||||
self,
|
||||
prompt: str,
|
||||
model_config: Dict[str, Any],
|
||||
request_type: str = "plugin.generate",
|
||||
**kwargs
|
||||
) -> Tuple[bool, str]:
|
||||
"""使用指定模型生成内容
|
||||
|
||||
Args:
|
||||
prompt: 提示词
|
||||
model_config: 模型配置（从 get_available_models 获取的模型配置）
|
||||
temperature: 温度参数，控制随机性 (0-1)
|
||||
max_tokens: 最大生成token数
|
||||
request_type: 请求类型标识
|
||||
**kwargs: 其他模型特定参数
|
||||
|
||||
Returns:
|
||||
Tuple[bool, str]: (是否成功, 生成的内容或错误信息)
|
||||
"""
|
||||
try:
|
||||
|
||||
|
||||
logger.info(f"prompt: {prompt}")
|
||||
|
||||
llm_request = LLMRequest(
|
||||
model=model_config,
|
||||
request_type=request_type,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
response,(resoning , model_name) = await llm_request.generate_response_async(prompt)
|
||||
return True, response, resoning, model_name
|
||||
except Exception as e:
|
||||
error_msg = f"生成内容时出错: {str(e)}"
|
||||
logger.error(f"{self.log_prefix} {error_msg}")
|
||||
return False, error_msg
|
||||
|
||||
@abstractmethod
|
||||
async def process(self) -> Tuple[bool, str]:
|
||||
"""插件处理逻辑，子类必须实现此方法
|
||||
|
||||
Returns:
|
||||
Tuple[bool, str]: (是否执行成功, 回复文本)
|
||||
"""
|
||||
pass
|
||||
|
||||
async def handle_action(self) -> Tuple[bool, str]:
|
||||
"""实现BaseAction的抽象方法，调用子类的process方法
|
||||
|
||||
Returns:
|
||||
Tuple[bool, str]: (是否执行成功, 回复文本)
|
||||
"""
|
||||
return await self.process()
|
||||
|
||||
async def store_action_info(self, action_build_into_prompt: bool = False, action_prompt_display: str = "", action_done: bool = True) -> None:
|
||||
"""存储action执行信息到数据库
|
||||
|
||||
Args:
|
||||
action_build_into_prompt: 是否构建到提示中
|
||||
action_prompt_display: 动作显示内容
|
||||
"""
|
||||
try:
|
||||
chat_stream: ChatStream = self._services.get("chat_stream")
|
||||
if not chat_stream:
|
||||
logger.error(f"{self.log_prefix} 无法存储action信息：缺少chat_stream服务")
|
||||
return
|
||||
|
||||
action_time = time.time()
|
||||
action_id = f"{action_time}_{self.thinking_id}"
|
||||
|
||||
ActionRecords.create(
|
||||
action_id=action_id,
|
||||
time=action_time,
|
||||
action_name=self.__class__.__name__,
|
||||
action_data=str(self.action_data),
|
||||
action_done=action_done,
|
||||
action_build_into_prompt=action_build_into_prompt,
|
||||
action_prompt_display=action_prompt_display,
|
||||
chat_id=chat_stream.stream_id,
|
||||
chat_info_stream_id=chat_stream.stream_id,
|
||||
chat_info_platform=chat_stream.platform,
|
||||
user_id=chat_stream.user_info.user_id if chat_stream.user_info else "",
|
||||
user_nickname=chat_stream.user_info.user_nickname if chat_stream.user_info else "",
|
||||
user_cardname=chat_stream.user_info.user_cardname if chat_stream.user_info else ""
|
||||
)
|
||||
logger.debug(f"{self.log_prefix} 已存储action信息: {action_prompt_display}")
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 存储action信息时出错: {e}")
|
||||
traceback.print_exc()
|
||||
|
||||
async def db_query(
|
||||
self,
|
||||
model_class: Type[Model],
|
||||
query_type: str = "get",
|
||||
filters: Dict[str, Any] = None,
|
||||
data: Dict[str, Any] = None,
|
||||
limit: int = None,
|
||||
order_by: List[str] = None,
|
||||
single_result: bool = False
|
||||
) -> Union[List[Dict[str, Any]], Dict[str, Any], None]:
|
||||
"""执行数据库查询操作
|
||||
|
||||
这个方法提供了一个通用接口来执行数据库操作，包括查询、创建、更新和删除记录。
|
||||
|
||||
Args:
|
||||
model_class: Peewee 模型类，例如 ActionRecords, Messages 等
|
||||
query_type: 查询类型，可选值: "get", "create", "update", "delete", "count"
|
||||
filters: 过滤条件字典，键为字段名，值为要匹配的值
|
||||
data: 用于创建或更新的数据字典
|
||||
limit: 限制结果数量
|
||||
order_by: 排序字段列表，使用字段名，前缀'-'表示降序
|
||||
single_result: 是否只返回单个结果
|
||||
|
||||
Returns:
|
||||
根据查询类型返回不同的结果:
|
||||
- "get": 返回查询结果列表或单个结果（如果 single_result=True）
|
||||
- "create": 返回创建的记录
|
||||
- "update": 返回受影响的行数
|
||||
- "delete": 返回受影响的行数
|
||||
- "count": 返回记录数量
|
||||
|
||||
示例:
|
||||
# 查询最近10条消息
|
||||
messages = await self.db_query(
|
||||
Messages,
|
||||
query_type="get",
|
||||
filters={"chat_id": chat_stream.stream_id},
|
||||
limit=10,
|
||||
order_by=["-time"]
|
||||
)
|
||||
|
||||
# 创建一条记录
|
||||
new_record = await self.db_query(
|
||||
ActionRecords,
|
||||
query_type="create",
|
||||
data={"action_id": "123", "time": time.time(), "action_name": "TestAction"}
|
||||
)
|
||||
|
||||
# 更新记录
|
||||
updated_count = await self.db_query(
|
||||
ActionRecords,
|
||||
query_type="update",
|
||||
filters={"action_id": "123"},
|
||||
data={"action_done": True}
|
||||
)
|
||||
|
||||
# 删除记录
|
||||
deleted_count = await self.db_query(
|
||||
ActionRecords,
|
||||
query_type="delete",
|
||||
filters={"action_id": "123"}
|
||||
)
|
||||
|
||||
# 计数
|
||||
count = await self.db_query(
|
||||
Messages,
|
||||
query_type="count",
|
||||
filters={"chat_id": chat_stream.stream_id}
|
||||
)
|
||||
"""
|
||||
try:
|
||||
# 构建基本查询
|
||||
if query_type in ["get", "update", "delete", "count"]:
|
||||
query = model_class.select()
|
||||
|
||||
# 应用过滤条件
|
||||
if filters:
|
||||
for field, value in filters.items():
|
||||
query = query.where(getattr(model_class, field) == value)
|
||||
|
||||
# 执行查询
|
||||
if query_type == "get":
|
||||
# 应用排序
|
||||
if order_by:
|
||||
for field in order_by:
|
||||
if field.startswith("-"):
|
||||
query = query.order_by(getattr(model_class, field[1:]).desc())
|
||||
else:
|
||||
query = query.order_by(getattr(model_class, field))
|
||||
|
||||
# 应用限制
|
||||
if limit:
|
||||
query = query.limit(limit)
|
||||
|
||||
# 执行查询
|
||||
results = list(query.dicts())
|
||||
|
||||
# 返回结果
|
||||
if single_result:
|
||||
return results[0] if results else None
|
||||
return results
|
||||
|
||||
elif query_type == "create":
|
||||
if not data:
|
||||
raise ValueError("创建记录需要提供data参数")
|
||||
|
||||
# 创建记录
|
||||
record = model_class.create(**data)
|
||||
# 返回创建的记录
|
||||
return model_class.select().where(model_class.id == record.id).dicts().get()
|
||||
|
||||
elif query_type == "update":
|
||||
if not data:
|
||||
raise ValueError("更新记录需要提供data参数")
|
||||
|
||||
# 更新记录
|
||||
return query.update(**data).execute()
|
||||
|
||||
elif query_type == "delete":
|
||||
# 删除记录
|
||||
return query.delete().execute()
|
||||
|
||||
elif query_type == "count":
|
||||
# 计数
|
||||
return query.count()
|
||||
|
||||
else:
|
||||
raise ValueError(f"不支持的查询类型: {query_type}")
|
||||
|
||||
except DoesNotExist:
|
||||
# 记录不存在
|
||||
if query_type == "get" and single_result:
|
||||
return None
|
||||
return []
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 数据库操作出错: {e}")
|
||||
traceback.print_exc()
|
||||
|
||||
# 根据查询类型返回合适的默认值
|
||||
if query_type == "get":
|
||||
return None if single_result else []
|
||||
elif query_type in ["create", "update", "delete", "count"]:
|
||||
return None
|
||||
|
||||
async def db_raw_query(
|
||||
self,
|
||||
sql: str,
|
||||
params: List[Any] = None,
|
||||
fetch_results: bool = True
|
||||
) -> Union[List[Dict[str, Any]], int, None]:
|
||||
"""执行原始SQL查询
|
||||
|
||||
警告: 使用此方法需要小心，确保SQL语句已正确构造以避免SQL注入风险。
|
||||
|
||||
Args:
|
||||
sql: 原始SQL查询字符串
|
||||
params: 查询参数列表，用于替换SQL中的占位符
|
||||
fetch_results: 是否获取查询结果，对于SELECT查询设为True，对于
|
||||
UPDATE/INSERT/DELETE等操作设为False
|
||||
|
||||
Returns:
|
||||
如果fetch_results为True，返回查询结果列表；
|
||||
如果fetch_results为False，返回受影响的行数；
|
||||
如果出错，返回None
|
||||
"""
|
||||
try:
|
||||
cursor = db.execute_sql(sql, params or [])
|
||||
|
||||
if fetch_results:
|
||||
# 获取列名
|
||||
columns = [col[0] for col in cursor.description]
|
||||
|
||||
# 构建结果字典列表
|
||||
results = []
|
||||
for row in cursor.fetchall():
|
||||
results.append(dict(zip(columns, row)))
|
||||
|
||||
return results
|
||||
else:
|
||||
# 返回受影响的行数
|
||||
return cursor.rowcount
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 执行原始SQL查询出错: {e}")
|
||||
traceback.print_exc()
|
||||
return None
|
||||
|
||||
async def db_save(
|
||||
self,
|
||||
model_class: Type[Model],
|
||||
data: Dict[str, Any],
|
||||
key_field: str = None,
|
||||
key_value: Any = None
|
||||
) -> Union[Dict[str, Any], None]:
|
||||
"""保存数据到数据库（创建或更新）
|
||||
|
||||
如果提供了key_field和key_value，会先尝试查找匹配的记录进行更新；
|
||||
如果没有找到匹配记录，或未提供key_field和key_value，则创建新记录。
|
||||
|
||||
Args:
|
||||
model_class: Peewee模型类，如ActionRecords, Messages等
|
||||
data: 要保存的数据字典
|
||||
key_field: 用于查找现有记录的字段名，例如"action_id"
|
||||
key_value: 用于查找现有记录的字段值
|
||||
|
||||
Returns:
|
||||
Dict[str, Any]: 保存后的记录数据
|
||||
None: 如果操作失败
|
||||
|
||||
示例:
|
||||
# 创建或更新一条记录
|
||||
record = await self.db_save(
|
||||
ActionRecords,
|
||||
{
|
||||
"action_id": "123",
|
||||
"time": time.time(),
|
||||
"action_name": "TestAction",
|
||||
"action_done": True
|
||||
},
|
||||
key_field="action_id",
|
||||
key_value="123"
|
||||
)
|
||||
"""
|
||||
try:
|
||||
# 如果提供了key_field和key_value，尝试更新现有记录
|
||||
if key_field and key_value is not None:
|
||||
# 查找现有记录
|
||||
existing_records = list(model_class.select().where(
|
||||
getattr(model_class, key_field) == key_value
|
||||
).limit(1))
|
||||
|
||||
if existing_records:
|
||||
# 更新现有记录
|
||||
existing_record = existing_records[0]
|
||||
for field, value in data.items():
|
||||
setattr(existing_record, field, value)
|
||||
existing_record.save()
|
||||
|
||||
# 返回更新后的记录
|
||||
updated_record = model_class.select().where(
|
||||
model_class.id == existing_record.id
|
||||
).dicts().get()
|
||||
return updated_record
|
||||
|
||||
# 如果没有找到现有记录或未提供key_field和key_value，创建新记录
|
||||
new_record = model_class.create(**data)
|
||||
|
||||
# 返回创建的记录
|
||||
created_record = model_class.select().where(
|
||||
model_class.id == new_record.id
|
||||
).dicts().get()
|
||||
return created_record
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 保存数据库记录出错: {e}")
|
||||
traceback.print_exc()
|
||||
return None
|
||||
|
||||
async def db_get(
|
||||
self,
|
||||
model_class: Type[Model],
|
||||
filters: Dict[str, Any] = None,
|
||||
order_by: str = None,
|
||||
limit: int = None
|
||||
) -> Union[List[Dict[str, Any]], Dict[str, Any], None]:
|
||||
"""从数据库获取记录
|
||||
|
||||
这是db_query方法的简化版本，专注于数据检索操作。
|
||||
|
||||
Args:
|
||||
model_class: Peewee模型类
|
||||
filters: 过滤条件，字段名和值的字典
|
||||
order_by: 排序字段，前缀'-'表示降序，例如'-time'表示按时间降序
|
||||
limit: 结果数量限制，如果为1则返回单个记录而不是列表
|
||||
|
||||
Returns:
|
||||
如果limit=1，返回单个记录字典或None；
|
||||
否则返回记录字典列表或空列表。
|
||||
|
||||
示例:
|
||||
# 获取单个记录
|
||||
record = await self.db_get(
|
||||
ActionRecords,
|
||||
filters={"action_id": "123"},
|
||||
limit=1
|
||||
)
|
||||
|
||||
# 获取最近10条记录
|
||||
records = await self.db_get(
|
||||
Messages,
|
||||
filters={"chat_id": chat_stream.stream_id},
|
||||
order_by="-time",
|
||||
limit=10
|
||||
)
|
||||
"""
|
||||
try:
|
||||
# 构建查询
|
||||
query = model_class.select()
|
||||
|
||||
# 应用过滤条件
|
||||
if filters:
|
||||
for field, value in filters.items():
|
||||
query = query.where(getattr(model_class, field) == value)
|
||||
|
||||
# 应用排序
|
||||
if order_by:
|
||||
if order_by.startswith("-"):
|
||||
query = query.order_by(getattr(model_class, order_by[1:]).desc())
|
||||
else:
|
||||
query = query.order_by(getattr(model_class, order_by))
|
||||
|
||||
# 应用限制
|
||||
if limit:
|
||||
query = query.limit(limit)
|
||||
|
||||
# 执行查询
|
||||
results = list(query.dicts())
|
||||
|
||||
# 返回结果
|
||||
if limit == 1:
|
||||
return results[0] if results else None
|
||||
return results
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 获取数据库记录出错: {e}")
|
||||
traceback.print_exc()
|
||||
return None if limit == 1 else []
|
||||
@@ -1,196 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
# -*- coding: utf-8 -*-
|
||||
from src.common.logger_manager import get_logger
|
||||
from src.chat.focus_chat.planners.actions.base_action import BaseAction, register_action, ActionActivationType, ChatMode
|
||||
from typing import Tuple, List
|
||||
from src.chat.heart_flow.observation.observation import Observation
|
||||
from src.chat.focus_chat.replyer.default_replyer import DefaultReplyer
|
||||
from src.chat.message_receive.chat_stream import ChatStream
|
||||
from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
|
||||
from src.chat.focus_chat.hfc_utils import create_empty_anchor_message
|
||||
import time
|
||||
import traceback
|
||||
from src.common.database.database_model import ActionRecords
|
||||
import re
|
||||
|
||||
logger = get_logger("action_taken")
|
||||
|
||||
|
||||
@register_action
|
||||
class ReplyAction(BaseAction):
|
||||
"""回复动作处理类
|
||||
|
||||
处理构建和发送消息回复的动作。
|
||||
"""
|
||||
|
||||
action_name: str = "reply"
|
||||
action_description: str = "当你想要参与回复或者聊天"
|
||||
action_parameters: dict[str:str] = {
|
||||
"reply_to": "如果是明确回复某个人的发言，请在reply_to参数中指定，格式：（用户名:发言内容），如果不是，reply_to的值设为none"
|
||||
}
|
||||
action_require: list[str] = [
|
||||
"你想要闲聊或者随便附和",
|
||||
"有人提到你",
|
||||
"如果你刚刚进行了回复，不要对同一个话题重复回应"
|
||||
]
|
||||
|
||||
associated_types: list[str] = ["text"]
|
||||
|
||||
enable_plugin = True
|
||||
|
||||
# 激活类型设置
|
||||
focus_activation_type = ActionActivationType.ALWAYS
|
||||
|
||||
# 模式启用设置 - 回复动作只在Focus模式下使用
|
||||
mode_enable = ChatMode.FOCUS
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
action_data: dict,
|
||||
reasoning: str,
|
||||
cycle_timers: dict,
|
||||
thinking_id: str,
|
||||
observations: List[Observation],
|
||||
chat_stream: ChatStream,
|
||||
log_prefix: str,
|
||||
replyer: DefaultReplyer,
|
||||
**kwargs,
|
||||
):
|
||||
"""初始化回复动作处理器
|
||||
|
||||
Args:
|
||||
action_name: 动作名称
|
||||
action_data: 动作数据，包含 message, emojis, target 等
|
||||
reasoning: 执行该动作的理由
|
||||
cycle_timers: 计时器字典
|
||||
thinking_id: 思考ID
|
||||
observations: 观察列表
|
||||
replyer: 回复器
|
||||
chat_stream: 聊天流
|
||||
log_prefix: 日志前缀
|
||||
"""
|
||||
super().__init__(action_data, reasoning, cycle_timers, thinking_id)
|
||||
self.observations = observations
|
||||
self.replyer = replyer
|
||||
self.chat_stream = chat_stream
|
||||
self.log_prefix = log_prefix
|
||||
|
||||
async def handle_action(self) -> Tuple[bool, str]:
|
||||
"""
|
||||
处理回复动作
|
||||
|
||||
Returns:
|
||||
Tuple[bool, str]: (是否执行成功, 回复文本)
|
||||
"""
|
||||
# 注意: 此处可能会使用不同的expressor实现根据任务类型切换不同的回复策略
|
||||
success, reply_text = await self._handle_reply(
|
||||
reasoning=self.reasoning,
|
||||
reply_data=self.action_data,
|
||||
cycle_timers=self.cycle_timers,
|
||||
thinking_id=self.thinking_id,
|
||||
)
|
||||
|
||||
await self.store_action_info(
|
||||
action_build_into_prompt=False,
|
||||
action_prompt_display=f"{reply_text}",
|
||||
)
|
||||
|
||||
return success, reply_text
|
||||
|
||||
async def _handle_reply(
|
||||
self, reasoning: str, reply_data: dict, cycle_timers: dict, thinking_id: str
|
||||
) -> tuple[bool, str]:
|
||||
"""
|
||||
处理统一的回复动作 - 可包含文本和表情，顺序任意
|
||||
|
||||
reply_data格式:
|
||||
{
|
||||
"text": "你好啊" # 文本内容列表（可选）
|
||||
"target": "锚定消息", # 锚定消息的文本内容
|
||||
}
|
||||
"""
|
||||
logger.info(f"{self.log_prefix} 决定回复: {self.reasoning}")
|
||||
|
||||
# 从聊天观察获取锚定消息
|
||||
chatting_observation: ChattingObservation = next(
|
||||
obs for obs in self.observations if isinstance(obs, ChattingObservation)
|
||||
)
|
||||
|
||||
reply_to = reply_data.get("reply_to", "none")
|
||||
|
||||
# sender = ""
|
||||
target = ""
|
||||
if ":" in reply_to or "：" in reply_to:
|
||||
# 使用正则表达式匹配中文或英文冒号
|
||||
parts = re.split(pattern=r'[:：]', string=reply_to, maxsplit=1)
|
||||
if len(parts) == 2:
|
||||
# sender = parts[0].strip()
|
||||
target = parts[1].strip()
|
||||
anchor_message = chatting_observation.search_message_by_text(target)
|
||||
else:
|
||||
anchor_message = None
|
||||
|
||||
if anchor_message:
|
||||
anchor_message.update_chat_stream(self.chat_stream)
|
||||
else:
|
||||
logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
|
||||
anchor_message = await create_empty_anchor_message(
|
||||
self.chat_stream.platform, self.chat_stream.group_info, self.chat_stream
|
||||
)
|
||||
|
||||
|
||||
success, reply_set = await self.replyer.deal_reply(
|
||||
cycle_timers=cycle_timers,
|
||||
action_data=reply_data,
|
||||
anchor_message=anchor_message,
|
||||
reasoning=reasoning,
|
||||
thinking_id=thinking_id,
|
||||
)
|
||||
|
||||
reply_text = ""
|
||||
for reply in reply_set:
|
||||
type = reply[0]
|
||||
data = reply[1]
|
||||
if type == "text":
|
||||
reply_text += data
|
||||
elif type == "emoji":
|
||||
reply_text += data
|
||||
|
||||
return success, reply_text
|
||||
|
||||
|
||||
async def store_action_info(self, action_build_into_prompt: bool = False, action_prompt_display: str = "", action_done: bool = True) -> None:
|
||||
"""存储action执行信息到数据库
|
||||
|
||||
Args:
|
||||
action_build_into_prompt: 是否构建到提示中
|
||||
action_prompt_display: 动作显示内容
|
||||
"""
|
||||
try:
|
||||
chat_stream = self.chat_stream
|
||||
if not chat_stream:
|
||||
logger.error(f"{self.log_prefix} 无法存储action信息：缺少chat_stream服务")
|
||||
return
|
||||
|
||||
action_time = time.time()
|
||||
action_id = f"{action_time}_{self.thinking_id}"
|
||||
|
||||
ActionRecords.create(
|
||||
action_id=action_id,
|
||||
time=action_time,
|
||||
action_name=self.__class__.__name__,
|
||||
action_data=str(self.action_data),
|
||||
action_done=action_done,
|
||||
action_build_into_prompt=action_build_into_prompt,
|
||||
action_prompt_display=action_prompt_display,
|
||||
chat_id=chat_stream.stream_id,
|
||||
chat_info_stream_id=chat_stream.stream_id,
|
||||
chat_info_platform=chat_stream.platform,
|
||||
user_id=chat_stream.user_info.user_id if chat_stream.user_info else "",
|
||||
user_nickname=chat_stream.user_info.user_nickname if chat_stream.user_info else "",
|
||||
user_cardname=chat_stream.user_info.user_cardname if chat_stream.user_info else ""
|
||||
)
|
||||
logger.debug(f"{self.log_prefix} 已存储action信息: {action_prompt_display}")
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 存储action信息时出错: {e}")
|
||||
traceback.print_exc()
|
||||
@@ -6,7 +6,7 @@ from src.chat.heart_flow.observation.chatting_observation import ChattingObserva
|
||||
from src.chat.message_receive.chat_stream import chat_manager
|
||||
from src.config.config import global_config
|
||||
from src.llm_models.utils_model import LLMRequest
|
||||
from src.chat.focus_chat.planners.actions.base_action import ActionActivationType, ChatMode
|
||||
from src.chat.actions.base_action import ActionActivationType, ChatMode
|
||||
import random
|
||||
import asyncio
|
||||
import hashlib
|
||||
@@ -560,9 +560,9 @@ class ActionModifier:
|
||||
reply_sequence.append(action_type == "reply")
|
||||
|
||||
# 检查no_reply比例
|
||||
if len(recent_cycles) >= (5 * global_config.chat.exit_focus_threshold) and (
|
||||
if len(recent_cycles) >= (4 * global_config.chat.exit_focus_threshold) and (
|
||||
no_reply_count / len(recent_cycles)
|
||||
) >= (0.8 * global_config.chat.exit_focus_threshold):
|
||||
) >= (0.7 * global_config.chat.exit_focus_threshold):
|
||||
if global_config.chat.chat_mode == "auto":
|
||||
result["add"].append("exit_focus_chat")
|
||||
result["remove"].append("no_reply")
|
||||
|
||||
@@ -15,8 +15,7 @@ from src.common.logger_manager import get_logger
|
||||
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
|
||||
from src.individuality.individuality import individuality
|
||||
from src.chat.focus_chat.planners.action_manager import ActionManager
|
||||
from src.chat.focus_chat.planners.modify_actions import ActionModifier
|
||||
from src.chat.focus_chat.planners.actions.base_action import ChatMode
|
||||
from src.chat.actions.base_action import ChatMode
|
||||
from json_repair import repair_json
|
||||
from src.chat.focus_chat.planners.base_planner import BasePlanner
|
||||
from datetime import datetime
|
||||
|
||||
@@ -139,6 +139,8 @@ class DefaultReplyer:
|
||||
# 处理文本部分
|
||||
# text_part = action_data.get("text", [])
|
||||
# if text_part:
|
||||
sent_msg_list = []
|
||||
|
||||
with Timer("生成回复", cycle_timers):
|
||||
# 可以保留原有的文本处理逻辑或进行适当调整
|
||||
reply = await self.reply(
|
||||
|
||||
Reference in New Issue
Block a user