diff --git a/src/chat/express/expression_learner.py b/src/chat/express/expression_learner.py index 8a4b0986..d245ee25 100644 --- a/src/chat/express/expression_learner.py +++ b/src/chat/express/expression_learner.py @@ -8,7 +8,6 @@ from typing import List, Dict, Optional, Any, Tuple from src.common.logger import get_logger from src.common.database.database_model import Expression -from src.common.data_models.database_data_model import DatabaseMessages from src.llm_models.utils_model import LLMRequest from src.config.config import model_config, global_config from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat_inclusive, build_anonymous_messages diff --git a/src/chat/frequency_control/frequency_control.py b/src/chat/frequency_control/frequency_control.py index 77ad7849..323368d5 100644 --- a/src/chat/frequency_control/frequency_control.py +++ b/src/chat/frequency_control/frequency_control.py @@ -1,9 +1,8 @@ import time -from typing import Optional, Dict, List +from typing import Optional, Dict from src.plugin_system.apis import message_api from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager from src.common.logger import get_logger -from src.config.config import global_config from src.chat.frequency_control.talk_frequency_control import get_config_base_talk_frequency from src.chat.frequency_control.focus_value_control import get_config_base_focus_value diff --git a/src/chat/heart_flow/heartFC_chat.py b/src/chat/heart_flow/heartFC_chat.py index a2e85113..f3d9becb 100644 --- a/src/chat/heart_flow/heartFC_chat.py +++ b/src/chat/heart_flow/heartFC_chat.py @@ -5,7 +5,6 @@ import math import random from typing import List, Optional, Dict, Any, Tuple, TYPE_CHECKING from rich.traceback import install -from collections import deque from src.config.config import global_config from src.common.logger import get_logger @@ -101,7 +100,6 @@ class HeartFChatting: self.last_read_time = time.time() - 10 - async def start(self): """检查是否需要启动主循环，如果未激活则启动。""" @@ -178,7 +176,7 @@ class HeartFChatting: f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒" # type: ignore + (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "") ) - + async def caculate_interest_value(self, recent_messages_list: List["DatabaseMessages"]) -> float: total_interest = 0.0 for msg in recent_messages_list: @@ -197,10 +195,13 @@ class HeartFChatting: filter_mai=True, filter_command=True, ) - + if recent_messages_list: self.last_read_time = time.time() - await self._observe(interest_value=await self.caculate_interest_value(recent_messages_list),recent_messages_list=recent_messages_list) + await self._observe( + interest_value=await self.caculate_interest_value(recent_messages_list), + recent_messages_list=recent_messages_list, + ) else: # Normal模式：消息数量不足，等待 await asyncio.sleep(0.2) @@ -257,7 +258,7 @@ class HeartFChatting: return loop_info, reply_text, cycle_timers - async def _observe(self, interest_value: float = 0.0,recent_messages_list: List["DatabaseMessages"] = []) -> bool: + async def _observe(self, interest_value: float = 0.0, recent_messages_list: List["DatabaseMessages"] = []) -> bool: reply_text = "" # 初始化reply_text变量，避免UnboundLocalError # 使用sigmoid函数将interest_value转换为概率 @@ -274,12 +275,10 @@ class HeartFChatting: return 1.0 / (1.0 + math.exp(-k * (interest_val - x0))) normal_mode_probability = ( - calculate_normal_mode_probability(interest_value) - * 2 - * self.frequency_control.get_final_talk_frequency() + calculate_normal_mode_probability(interest_value) * 2 * self.frequency_control.get_final_talk_frequency() ) - - #对呼唤名字进行增幅 + + # 对呼唤名字进行增幅 for msg in recent_messages_list: if msg.reply_probability_boost is not None and msg.reply_probability_boost > 0.0: normal_mode_probability += msg.reply_probability_boost @@ -287,18 +286,15 @@ class HeartFChatting: normal_mode_probability += global_config.chat.mentioned_bot_reply if global_config.chat.at_bot_inevitable_reply and msg.is_at: normal_mode_probability += global_config.chat.at_bot_inevitable_reply - # 根据概率决定使用直接回复 interest_triggerd = False focus_triggerd = False - + if random.random() < normal_mode_probability: interest_triggerd = True - logger.info( - f"{self.log_prefix} 有新消息，在{normal_mode_probability * 100:.0f}%概率下选择回复" - ) + logger.info(f"{self.log_prefix} 有新消息，在{normal_mode_probability * 100:.0f}%概率下选择回复") if s4u_config.enable_s4u: await send_typing() @@ -307,21 +303,20 @@ class HeartFChatting: await self.expression_learner.trigger_learning_for_chat() available_actions: Dict[str, ActionInfo] = {} - - #如果兴趣度不足以激活 - if not interest_triggerd: - #看看专注值够不够 - if random.random() < self.frequency_control.get_final_focus_value(): - #专注值足够，仍然进入正式思考 - focus_triggerd = True #都没触发，路边 - + # 如果兴趣度不足以激活 + if not interest_triggerd: + # 看看专注值够不够 + if random.random() < self.frequency_control.get_final_focus_value(): + # 专注值足够，仍然进入正式思考 + focus_triggerd = True # 都没触发，路边 + # 任意一种触发都行 if interest_triggerd or focus_triggerd: # 进入正式思考模式 cycle_timers, thinking_id = self.start_cycle() logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考") - + # 第一步：动作检查 try: await self.action_modifier.modify_actions() @@ -353,17 +348,20 @@ class HeartFChatting: # actions_before_now_block=actions_before_now_block, message_id_list=message_id_list, ) - if not await events_manager.handle_mai_events( + continue_flag, modified_message = await events_manager.handle_mai_events( EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id - ): + ) + if not continue_flag: return False + if modified_message and modified_message._modify_flags.modify_llm_prompt: + prompt_info = (modified_message.llm_prompt, prompt_info[1]) with Timer("规划器", cycle_timers): # 根据不同触发，进入不同plan if focus_triggerd: mode = ChatMode.FOCUS else: mode = ChatMode.NORMAL - + action_to_use_info, _ = await self.action_planner.plan( mode=mode, loop_start_time=self.last_read_time, @@ -432,8 +430,7 @@ class HeartFChatting: }, } reply_text = action_reply_text - - + self.end_cycle(loop_info, cycle_timers) self.print_cycle_info(cycle_timers) diff --git a/src/chat/knowledge/embedding_store.py b/src/chat/knowledge/embedding_store.py index dec5b595..7e3695fe 100644 --- a/src/chat/knowledge/embedding_store.py +++ b/src/chat/knowledge/embedding_store.py @@ -25,7 +25,6 @@ from rich.progress import ( SpinnerColumn, TextColumn, ) -from src.chat.utils.utils import get_embedding from src.config.config import global_config diff --git a/src/chat/memory_system/Hippocampus.py b/src/chat/memory_system/Hippocampus.py index 82901a91..8c499843 100644 --- a/src/chat/memory_system/Hippocampus.py +++ b/src/chat/memory_system/Hippocampus.py @@ -7,7 +7,7 @@ import re import jieba import networkx as nx import numpy as np -from typing import List, Tuple, Set, Coroutine, Any, Dict +from typing import List, Tuple, Set, Coroutine, Any from collections import Counter import traceback @@ -21,7 +21,6 @@ from src.common.logger import get_logger from src.chat.utils.utils import cut_key_words from src.chat.utils.chat_message_builder import ( build_readable_messages, - get_raw_msg_by_timestamp_with_chat_inclusive, ) # 导入 build_readable_messages @@ -1183,9 +1182,7 @@ class ParahippocampalGyrus: # 规范化输入为列表[str] if isinstance(keywords, str): # 支持中英文逗号、顿号、空格分隔 - parts = ( - keywords.replace("，", ",").replace("、", ",").replace(" ", ",").strip(", ") - ) + parts = keywords.replace("，", ",").replace("、", ",").replace(" ", ",").strip(", ") keyword_list = [p.strip() for p in parts.split(",") if p.strip()] else: keyword_list = [k.strip() for k in keywords if isinstance(k, str) and k.strip()] diff --git a/src/chat/message_receive/bot.py b/src/chat/message_receive/bot.py index bb667cbf..d1c27af4 100644 --- a/src/chat/message_receive/bot.py +++ b/src/chat/message_receive/bot.py @@ -3,7 +3,7 @@ import os import re from typing import Dict, Any, Optional -from maim_message import UserInfo +from maim_message import UserInfo, Seg from src.common.logger import get_logger from src.config.config import global_config @@ -169,8 +169,12 @@ class ChatBot: # 处理消息内容 await message.process() - - _ = Person.register_person(platform=message.message_info.platform, user_id=message.message_info.user_info.user_id,nickname=user_info.user_nickname) # type: ignore + + _ = Person.register_person( + platform=message.message_info.platform, + user_id=message.message_info.user_info.user_id, + nickname=user_info.user_nickname, + ) # type: ignore await self.s4u_message_processor.process_message(message) @@ -220,10 +224,18 @@ class ChatBot: user_info = message.message_info.user_info if message.message_info.additional_config: sent_message = message.message_info.additional_config.get("echo", False) - if sent_message: # 这一段只是为了在一切处理前劫持上报的自身消息，用于更新message_id，需要ada支持上报事件，实际测试中不会对正常使用造成任何问题 + if sent_message: # 处理上报的自身消息，更新message_id，需要ada支持上报事件 await MessageStorage.update_message(message) return + continue_flag, modified_message = await events_manager.handle_mai_events( + EventType.ON_MESSAGE_PRE_PROCESS, message + ) + if not continue_flag: + return + if modified_message and modified_message._modify_flags.modify_message_segments: + message.message_segment = Seg(type="seglist", data=modified_message.message_segments) + get_chat_manager().register_message(message) chat = await get_chat_manager().get_or_create_stream( @@ -258,8 +270,11 @@ class ChatBot: logger.info(f"命令处理完成，跳过后续消息处理: {cmd_result}") return - if not await events_manager.handle_mai_events(EventType.ON_MESSAGE, message): + continue_flag, modified_message = await events_manager.handle_mai_events(EventType.ON_MESSAGE, message) + if not continue_flag: return + if modified_message and modified_message._modify_flags.modify_plain_text: + message.processed_plain_text = modified_message.plain_text # 确认从接口发来的message是否有自定义的prompt模板信息 if message.message_info.template_info and not message.message_info.template_info.template_default: diff --git a/src/chat/replyer/default_generator.py b/src/chat/replyer/default_generator.py index e09466a0..9163b1b4 100644 --- a/src/chat/replyer/default_generator.py +++ b/src/chat/replyer/default_generator.py @@ -202,10 +202,14 @@ class DefaultReplyer: from src.plugin_system.core.events_manager import events_manager if not from_plugin: - if not await events_manager.handle_mai_events( + continue_flag, modified_message = await events_manager.handle_mai_events( EventType.POST_LLM, None, prompt, None, stream_id=stream_id - ): + ) + if not continue_flag: raise UserWarning("插件于请求前中断了内容生成") + if modified_message and modified_message._modify_flags.modify_llm_prompt: + llm_response.prompt = modified_message.llm_prompt + prompt = str(modified_message.llm_prompt) # 4. 调用 LLM 生成回复 content = None @@ -219,10 +223,19 @@ class DefaultReplyer: llm_response.reasoning = reasoning_content llm_response.model = model_name llm_response.tool_calls = tool_call - if not from_plugin and not await events_manager.handle_mai_events( + continue_flag, modified_message = await events_manager.handle_mai_events( EventType.AFTER_LLM, None, prompt, llm_response, stream_id=stream_id - ): + ) + if not from_plugin and not continue_flag: raise UserWarning("插件于请求后取消了内容生成") + if modified_message: + if modified_message._modify_flags.modify_llm_prompt: + logger.warning("警告：插件在内容生成后才修改了prompt，此修改不会生效") + llm_response.prompt = modified_message.llm_prompt # 虽然我不知道为什么在这里需要改prompt + if modified_message._modify_flags.modify_llm_response_content: + llm_response.content = modified_message.llm_response_content + if modified_message._modify_flags.modify_llm_response_reasoning: + llm_response.reasoning = modified_message.llm_response_reasoning except UserWarning as e: raise e except Exception as llm_e: @@ -634,7 +647,7 @@ class DefaultReplyer: """构建动作提示""" action_descriptions = "" - skip_names = ["emoji","build_memory","build_relation","reply"] + skip_names = ["emoji", "build_memory", "build_relation", "reply"] if available_actions: action_descriptions = "除了进行回复之外，你可以做以下这些动作，不过这些动作由另一个模型决定，：\n" for action_name, action_info in available_actions.items(): @@ -671,9 +684,7 @@ class DefaultReplyer: else: bot_nickname = "" - prompt_personality = ( - f"{global_config.personality.personality};" - ) + prompt_personality = f"{global_config.personality.personality};" return f"你的名字是{bot_name}{bot_nickname}，你{prompt_personality}" async def build_prompt_reply_context( @@ -809,11 +820,6 @@ class DefaultReplyer: moderation_prompt_block = "请不要输出违法违规内容，不要输出色情，暴力，政治相关内容，如有敏感内容，请规避。" - - - - - if sender: if is_group_chat: reply_target_block = ( @@ -1016,7 +1022,7 @@ class DefaultReplyer: logger.info(f"使用模型集生成回复: {', '.join(map(str, self.express_model.model_for_task.model_list))}") logger.info(f"\n{prompt}\n") - + if global_config.debug.show_prompt: logger.info(f"\n{prompt}\n") else: diff --git a/src/plugin_system/base/base_events_handler.py b/src/plugin_system/base/base_events_handler.py index 130858e7..d248ef0a 100644 --- a/src/plugin_system/base/base_events_handler.py +++ b/src/plugin_system/base/base_events_handler.py @@ -37,19 +37,19 @@ class BaseEventHandler(ABC): @abstractmethod async def execute( self, message: MaiMessages | None - ) -> Tuple[bool, bool, Optional[str], Optional[CustomEventHandlerResult]]: + ) -> Tuple[bool, bool, Optional[str], Optional[CustomEventHandlerResult], Optional[MaiMessages]]: """执行事件处理的抽象方法，子类必须实现 Args: message (MaiMessages | None): 事件消息对象，当你注册的事件为ON_START和ON_STOP时message为None Returns: - Tuple[bool, bool, Optional[str], Optional[CustomEventHandlerResult]]: (是否执行成功, 是否需要继续处理, 可选的返回消息, 可选的自定义结果) + Tuple[bool, bool, Optional[str], Optional[CustomEventHandlerResult], Optional[MaiMessages]]: (是否执行成功, 是否需要继续处理, 可选的返回消息, 可选的自定义结果，可选的修改后消息) """ raise NotImplementedError("子类必须实现 execute 方法") @classmethod def get_handler_info(cls) -> "EventHandlerInfo": """获取事件处理器的信息""" - # 从类属性读取名称，如果没有定义则使用类名自动生成 + # 从类属性读取名称，如果没有定义则使用类名自动生成S name: str = getattr(cls, "handler_name", cls.__name__.lower().replace("handler", "")) if "." in name: logger.error(f"事件处理器名称 '{name}' 包含非法字符 '.'，请使用下划线替代") diff --git a/src/plugin_system/base/component_types.py b/src/plugin_system/base/component_types.py index 5473d7f0..cfd5a4b6 100644 --- a/src/plugin_system/base/component_types.py +++ b/src/plugin_system/base/component_types.py @@ -1,4 +1,5 @@ import copy +import warnings from enum import Enum from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass, field @@ -7,6 +8,7 @@ from maim_message import Seg from src.llm_models.payload_content.tool_option import ToolParamType as ToolParamType from src.llm_models.payload_content.tool_option import ToolCall as ToolCall + # 组件类型枚举 class ComponentType(Enum): """组件类型枚举""" @@ -56,6 +58,7 @@ class EventType(Enum): ON_START = "on_start" # 启动事件，用于调用按时任务 ON_STOP = "on_stop" # 停止事件，用于调用按时任务 + ON_MESSAGE_PRE_PROCESS = "on_message_pre_process" ON_MESSAGE = "on_message" ON_PLAN = "on_plan" POST_LLM = "post_llm" @@ -116,9 +119,9 @@ class ActionInfo(ComponentInfo): action_require: List[str] = field(default_factory=list) # 动作需求说明 associated_types: List[str] = field(default_factory=list) # 关联的消息类型 # 激活类型相关 - focus_activation_type: ActionActivationType = ActionActivationType.ALWAYS #已弃用 - normal_activation_type: ActionActivationType = ActionActivationType.ALWAYS #已弃用 - activation_type: ActionActivationType = ActionActivationType.ALWAYS + focus_activation_type: ActionActivationType = ActionActivationType.ALWAYS # 已弃用 + normal_activation_type: ActionActivationType = ActionActivationType.ALWAYS # 已弃用 + activation_type: ActionActivationType = ActionActivationType.ALWAYS random_activation_probability: float = 0.0 llm_judge_prompt: str = "" activation_keywords: List[str] = field(default_factory=list) # 激活关键词列表 @@ -154,7 +157,9 @@ class CommandInfo(ComponentInfo): class ToolInfo(ComponentInfo): """工具组件信息""" - tool_parameters: List[Tuple[str, ToolParamType, str, bool, List[str] | None]] = field(default_factory=list) # 工具参数定义 + tool_parameters: List[Tuple[str, ToolParamType, str, bool, List[str] | None]] = field( + default_factory=list + ) # 工具参数定义 tool_description: str = "" # 工具描述 def __post_init__(self): @@ -233,6 +238,15 @@ class PluginInfo: return [dep.get_pip_requirement() for dep in self.python_dependencies] +@dataclass +class ModifyFlag: + modify_message_segments: bool = False + modify_plain_text: bool = False + modify_llm_prompt: bool = False + modify_llm_response_content: bool = False + modify_llm_response_reasoning: bool = False + + @dataclass class MaiMessages: """MaiM插件消息""" @@ -263,31 +277,129 @@ class MaiMessages: llm_response_content: Optional[str] = None """LLM响应内容""" - + llm_response_reasoning: Optional[str] = None """LLM响应推理内容""" - + llm_response_model: Optional[str] = None """LLM响应模型名称""" - + llm_response_tool_call: Optional[List[ToolCall]] = None """LLM使用的工具调用""" - + action_usage: Optional[List[str]] = None """使用的Action""" additional_data: Dict[Any, Any] = field(default_factory=dict) """附加数据，可以存储额外信息""" + _modify_flags: ModifyFlag = field(default_factory=ModifyFlag) + def __post_init__(self): if self.message_segments is None: self.message_segments = [] - + def deepcopy(self): return copy.deepcopy(self) + def modify_message_segments(self, new_segments: List[Seg], suppress_warning: bool = False): + """ + 修改消息段列表 + + Warning: + 在生成了plain_text的情况下调用此方法，可能会导致plain_text内容与消息段不一致 + + Args: + new_segments (List[Seg]): 新的消息段列表 + """ + if self.plain_text and not suppress_warning: + warnings.warn( + "修改消息段后，plain_text可能与消息段内容不一致，建议同时更新plain_text", + UserWarning, + stacklevel=2, + ) + self.message_segments = new_segments + self._modify_flags.modify_message_segments = True + + def modify_llm_prompt(self, new_prompt: str, suppress_warning: bool = False): + """ + 修改LLM提示词 + + Warning: + 在没有生成llm_prompt的情况下调用此方法，可能会导致修改无效 + + Args: + new_prompt (str): 新的提示词内容 + """ + if self.llm_prompt is None and not suppress_warning: + warnings.warn( + "当前llm_prompt为空，此时调用方法可能导致修改无效", + UserWarning, + stacklevel=2, + ) + self.llm_prompt = new_prompt + self._modify_flags.modify_llm_prompt = True + + def modify_plain_text(self, new_text: str, suppress_warning: bool = False): + """ + 修改生成的plain_text内容 + + Warning: + 在未生成plain_text的情况下调用此方法，可能会导致plain_text为空或者修改无效 + + Args: + new_text (str): 新的纯文本内容 + """ + if not self.plain_text and not suppress_warning: + warnings.warn( + "当前plain_text为空，此时调用方法可能导致修改无效", + UserWarning, + stacklevel=2, + ) + self.plain_text = new_text + self._modify_flags.modify_plain_text = True + + def modify_llm_response_content(self, new_content: str, suppress_warning: bool = False): + """ + 修改生成的llm_response_content内容 + + Warning: + 在未生成llm_response_content的情况下调用此方法，可能会导致llm_response_content为空或者修改无效 + + Args: + new_content (str): 新的LLM响应内容 + """ + if not self.llm_response_content and not suppress_warning: + warnings.warn( + "当前llm_response_content为空，此时调用方法可能导致修改无效", + UserWarning, + stacklevel=2, + ) + self.llm_response_content = new_content + self._modify_flags.modify_llm_response_content = True + + def modify_llm_response_reasoning(self, new_reasoning: str, suppress_warning: bool = False): + """ + 修改生成的llm_response_reasoning内容 + + Warning: + 在未生成llm_response_reasoning的情况下调用此方法，可能会导致llm_response_reasoning为空或者修改无效 + + Args: + new_reasoning (str): 新的LLM响应推理内容 + """ + if not self.llm_response_reasoning and not suppress_warning: + warnings.warn( + "当前llm_response_reasoning为空，此时调用方法可能导致修改无效", + UserWarning, + stacklevel=2, + ) + self.llm_response_reasoning = new_reasoning + self._modify_flags.modify_llm_response_reasoning = True + + @dataclass class CustomEventHandlerResult: message: str = "" timestamp: float = 0.0 - extra_info: Optional[Dict] = None \ No newline at end of file + extra_info: Optional[Dict] = None diff --git a/src/plugin_system/core/events_manager.py b/src/plugin_system/core/events_manager.py index baada939..ed85e0f1 100644 --- a/src/plugin_system/core/events_manager.py +++ b/src/plugin_system/core/events_manager.py @@ -71,7 +71,7 @@ class EventsManager: llm_response: Optional["LLMGenerationDataModel"] = None, stream_id: Optional[str] = None, action_usage: Optional[List[str]] = None, - ) -> bool: + ) -> Tuple[bool, Optional[MaiMessages]]: """ 处理所有事件，根据事件类型分发给订阅的处理器。 """ @@ -89,10 +89,10 @@ class EventsManager: # 2. 获取并遍历处理器 handlers = self._events_subscribers.get(event_type, []) if not handlers: - return True + return True, None current_stream_id = transformed_message.stream_id if transformed_message else None - + modified_message: Optional[MaiMessages] = None for handler in handlers: # 3. 前置检查和配置加载 if ( @@ -107,15 +107,19 @@ class EventsManager: handler.set_plugin_config(plugin_config) # 4. 根据类型分发任务 - if handler.intercept_message or event_type == EventType.ON_STOP: # 让ON_STOP的所有事件处理器都发挥作用，防止还没执行即被取消 + if ( + handler.intercept_message or event_type == EventType.ON_STOP + ): # 让ON_STOP的所有事件处理器都发挥作用，防止还没执行即被取消 # 阻塞执行，并更新 continue_flag - should_continue = await self._dispatch_intercepting_handler(handler, event_type, transformed_message) + should_continue, modified_message = await self._dispatch_intercepting_handler_task( + handler, event_type, modified_message or transformed_message + ) continue_flag = continue_flag and should_continue else: # 异步执行，不阻塞 self._dispatch_handler_task(handler, event_type, transformed_message) - return continue_flag + return continue_flag, modified_message async def cancel_handler_tasks(self, handler_name: str) -> None: tasks_to_be_cancelled = self._handler_tasks.get(handler_name, []) @@ -327,16 +331,18 @@ class EventsManager: except Exception as e: logger.error(f"创建事件处理器任务 {handler.handler_name} 时发生异常: {e}", exc_info=True) - async def _dispatch_intercepting_handler( + async def _dispatch_intercepting_handler_task( self, handler: BaseEventHandler, event_type: EventType | str, message: Optional[MaiMessages] = None - ) -> bool: + ) -> Tuple[bool, Optional[MaiMessages]]: """分发并等待一个阻塞（同步）的事件处理器，返回是否应继续处理。""" if event_type == EventType.UNKNOWN: raise ValueError("未知事件类型") if event_type not in self._history_enable_map: raise ValueError(f"事件类型 {event_type} 未注册") try: - success, continue_processing, return_message, custom_result = await handler.execute(message) + success, continue_processing, return_message, custom_result, modified_message = await handler.execute( + message + ) if not success: logger.error(f"EventHandler {handler.handler_name} 执行失败: {return_message}") @@ -345,17 +351,17 @@ class EventsManager: if self._history_enable_map[event_type] and custom_result: self._events_result_history[event_type].append(custom_result) - return continue_processing + return continue_processing, modified_message except KeyError: logger.error(f"事件 {event_type} 注册的历史记录启用情况与实际不符合") - return True + return True, None except Exception as e: logger.error(f"EventHandler {handler.handler_name} 发生异常: {e}", exc_info=True) - return True # 发生异常时默认不中断其他处理 + return True, None # 发生异常时默认不中断其他处理 def _task_done_callback( self, - task: asyncio.Task[Tuple[bool, bool, str | None, CustomEventHandlerResult | None]], + task: asyncio.Task[Tuple[bool, bool, str | None, CustomEventHandlerResult | None, MaiMessages | None]], event_type: EventType | str, ): """任务完成回调""" @@ -365,7 +371,7 @@ class EventsManager: if event_type not in self._history_enable_map: raise ValueError(f"事件类型 {event_type} 未注册") try: - success, _, result, custom_result = task.result() # 忽略是否继续的标志，因为消息本身未被拦截 + success, _, result, custom_result, _ = task.result() # 忽略是否继续的标志和消息的修改，因为消息本身未被拦截 if success: logger.debug(f"事件处理任务 {task_name} 已成功完成: {result}") else: