From 2c279f703ca386306a4f066cd8a6b33df5510adb Mon Sep 17 00:00:00 2001 From: DrSmoothl <1787882683@qq.com> Date: Tue, 24 Mar 2026 15:32:09 +0800 Subject: [PATCH] =?UTF-8?q?Revert=20"feat=EF=BC=9A=E5=B0=9D=E8=AF=95?= =?UTF-8?q?=E5=BB=BA=E7=AB=8Bhfc=E9=80=BB=E8=BE=91"?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit This reverts commit bfc9781c4f10212ecfffc3129115ecc6fbd3fa89. --- src/chat/heart_flow/heartFC_chat - 副本.py | 734 ------------------ src/chat/heart_flow/heartFC_chat.py | 823 ++++----------------- src/chat/heart_flow/heartflow.py | 42 -- 3 files changed, 160 insertions(+), 1439 deletions(-) delete mode 100644 src/chat/heart_flow/heartFC_chat - 副本.py delete mode 100644 src/chat/heart_flow/heartflow.py diff --git a/src/chat/heart_flow/heartFC_chat - 副本.py b/src/chat/heart_flow/heartFC_chat - 副本.py deleted file mode 100644 index 02f70281..00000000 --- a/src/chat/heart_flow/heartFC_chat - 副本.py +++ /dev/null @@ -1,734 +0,0 @@ -import asyncio -import time -import traceback -import random -from typing import List, Optional, Dict, Any, Tuple, TYPE_CHECKING -from rich.traceback import install - -from src.config.config import global_config -from src.common.logger import get_logger -from src.common.data_models.info_data_model import ActionPlannerInfo -from src.common.data_models.message_data_model import ReplyContentType -from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager -from src.chat.utils.prompt_builder import global_prompt_manager -from src.chat.utils.timer_calculator import Timer -from src.chat.planner_actions.planner import ActionPlanner -from src.chat.planner_actions.action_modifier import ActionModifier -from src.chat.planner_actions.action_manager import ActionManager -from src.chat.heart_flow.hfc_utils import CycleDetail -from src.learners.expression_learner import expression_learner_manager -from src.chat.heart_flow.frequency_control import frequency_control_manager -from src.learners.message_recorder import extract_and_distribute_messages -from src.person_info.person_info import Person -from src.plugin_system.base.component_types import EventType, ActionInfo -from src.plugin_system.core import events_manager -from src.plugin_system.apis import generator_api, send_api, message_api, database_api -from src.chat.utils.chat_message_builder import ( - build_readable_messages_with_id, - get_raw_msg_before_timestamp_with_chat, -) -from src.chat.utils.utils import record_replyer_action_temp -from src.memory_system.chat_history_summarizer import ChatHistorySummarizer - -if TYPE_CHECKING: - from src.common.data_models.database_data_model import DatabaseMessages - from src.common.data_models.message_data_model import ReplySetModel - - -ERROR_LOOP_INFO = { - "loop_plan_info": { - "action_result": { - "action_type": "error", - "action_data": {}, - "reasoning": "循环处理失败", - }, - }, - "loop_action_info": { - "action_taken": False, - "reply_text": "", - "command": "", - "taken_time": time.time(), - }, -} - - -install(extra_lines=3) - -# 注释：原来的动作修改超时常量已移除，因为改为顺序执行 - -logger = get_logger("hfc") # Logger Name Changed - - -class HeartFChatting: - """ - 管理一个连续的Focus Chat循环 - 用于在特定聊天流中生成回复。 - 其生命周期现在由其关联的 SubHeartflow 的 FOCUSED 状态控制。 - """ - - def __init__(self, chat_id: str): - """ - HeartFChatting 初始化函数 - - 参数: - chat_id: 聊天流唯一标识符(如stream_id) - on_stop_focus_chat: 当收到stop_focus_chat命令时调用的回调函数 - performance_version: 性能记录版本号，用于区分不同启动版本 - """ - # 基础属性 - self.stream_id: str = chat_id # 聊天流ID - self.chat_stream: ChatStream = get_chat_manager().get_stream(self.stream_id) # type: ignore - if not self.chat_stream: - raise ValueError(f"无法找到聊天流: {self.stream_id}") - self.log_prefix = f"[{get_chat_manager().get_stream_name(self.stream_id) or self.stream_id}]" - - self.expression_learner = expression_learner_manager.get_expression_learner(self.stream_id) - - self.action_manager = ActionManager() - self.action_planner = ActionPlanner(chat_id=self.stream_id, action_manager=self.action_manager) - self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.stream_id) - - # 循环控制内部状态 - self.running: bool = False - self._loop_task: Optional[asyncio.Task] = None # 主循环任务 - - # 添加循环信息管理相关的属性 - self.history_loop: List[CycleDetail] = [] - self._cycle_counter = 0 - self._current_cycle_detail: CycleDetail = None # type: ignore - - self.last_read_time = time.time() - 2 - - self.is_mute = False - - self.last_active_time = time.time() # 记录上一次非noreply时间 - - self.question_probability_multiplier = 1 - self.questioned = False - - # 跟踪连续 no_reply 次数，用于动态调整阈值 - self.consecutive_no_reply_count = 0 - - # 聊天内容概括器 - self.chat_history_summarizer = ChatHistorySummarizer(chat_id=self.stream_id) - - async def start(self): - """检查是否需要启动主循环，如果未激活则启动。""" - - # 如果循环已经激活，直接返回 - if self.running: - logger.debug(f"{self.log_prefix} HeartFChatting 已激活，无需重复启动") - return - - try: - # 标记为活动状态，防止重复启动 - self.running = True - - self._loop_task = asyncio.create_task(self._main_chat_loop()) - self._loop_task.add_done_callback(self._handle_loop_completion) - - # 启动聊天内容概括器的后台定期检查循环 - await self.chat_history_summarizer.start() - - logger.info(f"{self.log_prefix} HeartFChatting 启动完成") - - except Exception as e: - # 启动失败时重置状态 - self.running = False - self._loop_task = None - logger.error(f"{self.log_prefix} HeartFChatting 启动失败: {e}") - raise - - def _handle_loop_completion(self, task: asyncio.Task): - """当 _hfc_loop 任务完成时执行的回调。""" - try: - if exception := task.exception(): - logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}") - logger.error(traceback.format_exc()) # Log full traceback for exceptions - else: - logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)") - except asyncio.CancelledError: - logger.info(f"{self.log_prefix} HeartFChatting: 结束了聊天") - - def start_cycle(self) -> Tuple[Dict[str, float], str]: - self._cycle_counter += 1 - self._current_cycle_detail = CycleDetail(self._cycle_counter) - self._current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}" - cycle_timers = {} - return cycle_timers, self._current_cycle_detail.thinking_id - - def end_cycle(self, loop_info, cycle_timers): - self._current_cycle_detail.set_loop_info(loop_info) - self.history_loop.append(self._current_cycle_detail) - self._current_cycle_detail.timers = cycle_timers - self._current_cycle_detail.end_time = time.time() - - def print_cycle_info(self, cycle_timers): - # 记录循环信息和计时器结果 - timer_strings = [] - for name, elapsed in cycle_timers.items(): - if elapsed < 0.1: - # 不显示小于0.1秒的计时器 - continue - formatted_time = f"{elapsed:.2f}秒" - timer_strings.append(f"{name}: {formatted_time}") - - logger.info( - f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考," - f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒;" # type: ignore - + (f"详情: {'; '.join(timer_strings)}" if timer_strings else "") - ) - - async def _loopbody(self): - recent_messages_list = message_api.get_messages_by_time_in_chat( - chat_id=self.stream_id, - start_time=self.last_read_time, - end_time=time.time(), - limit=20, - limit_mode="latest", - filter_mai=True, - filter_command=False, - filter_intercept_message_level=0, - ) - - # 根据连续 no_reply 次数动态调整阈值 - # 3次 no_reply 时，阈值调高到 1.5（50%概率为1，50%概率为2） - # 5次 no_reply 时，提高到 2（大于等于两条消息的阈值） - if self.consecutive_no_reply_count >= 5: - threshold = 2 - elif self.consecutive_no_reply_count >= 3: - # 1.5 的含义：50%概率为1，50%概率为2 - threshold = 2 if random.random() < 0.5 else 1 - else: - threshold = 1 - - if len(recent_messages_list) >= threshold: - # for message in recent_messages_list: - # print(message.processed_plain_text) - - self.last_read_time = time.time() - - # !此处使at或者提及必定回复 - mentioned_message = None - for message in recent_messages_list: - if (message.is_mentioned or message.is_at) and global_config.chat.mentioned_bot_reply: - mentioned_message = message - - # logger.info(f"{self.log_prefix} 当前talk_value: {global_config.chat.get_talk_value(self.stream_id)}") - - # *控制频率用 - if mentioned_message: - await self._observe(recent_messages_list=recent_messages_list, force_reply_message=mentioned_message) - elif ( - random.random() - < global_config.chat.get_talk_value(self.stream_id) - * frequency_control_manager.get_or_create_frequency_control(self.stream_id).get_talk_frequency_adjust() - ): - await self._observe(recent_messages_list=recent_messages_list) - else: - # 没有提到，继续保持沉默，等待5秒防止频繁触发 - await asyncio.sleep(10) - return True - else: - await asyncio.sleep(0.2) - return True - return True - - async def _send_and_store_reply( - self, - response_set: "ReplySetModel", - action_message: "DatabaseMessages", - cycle_timers: Dict[str, float], - thinking_id, - actions, - selected_expressions: Optional[List[int]] = None, - quote_message: Optional[bool] = None, - ) -> Tuple[Dict[str, Any], str, Dict[str, float]]: - with Timer("回复发送", cycle_timers): - reply_text = await self._send_response( - reply_set=response_set, - message_data=action_message, - selected_expressions=selected_expressions, - quote_message=quote_message, - ) - - # 获取 platform，如果不存在则从 chat_stream 获取，如果还是 None 则使用默认值 - platform = action_message.chat_info.platform - if platform is None: - platform = getattr(self.chat_stream, "platform", "unknown") - - person = Person(platform=platform, user_id=action_message.user_info.user_id) - person_name = person.person_name - action_prompt_display = f"你对{person_name}进行了回复：{reply_text}" - - await database_api.store_action_info( - chat_stream=self.chat_stream, - action_build_into_prompt=False, - action_prompt_display=action_prompt_display, - action_done=True, - thinking_id=thinking_id, - action_data={"reply_text": reply_text}, - action_name="reply", - ) - - # 构建循环信息 - loop_info: Dict[str, Any] = { - "loop_plan_info": { - "action_result": actions, - }, - "loop_action_info": { - "action_taken": True, - "reply_text": reply_text, - "command": "", - "taken_time": time.time(), - }, - } - - return loop_info, reply_text, cycle_timers - - async def _observe( - self, # interest_value: float = 0.0, - recent_messages_list: Optional[List["DatabaseMessages"]] = None, - force_reply_message: Optional["DatabaseMessages"] = None, - ) -> bool: # sourcery skip: merge-else-if-into-elif, remove-redundant-if - if recent_messages_list is None: - recent_messages_list = [] - _reply_text = "" # 初始化reply_text变量，避免UnboundLocalError - - start_time = time.time() - async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()): - # 通过 MessageRecorder 统一提取消息并分发给 expression_learner 和 jargon_miner - # 在 replyer 执行时触发，统一管理时间窗口，避免重复获取消息 - asyncio.create_task(extract_and_distribute_messages(self.stream_id)) - - # 添加curious检测任务 - 检测聊天记录中的矛盾、冲突或需要提问的内容 - # asyncio.create_task(check_and_make_question(self.stream_id)) - # 添加聊天内容概括任务 - 累积、打包和压缩聊天记录 - # 注意：后台循环已在start()中启动，这里作为额外触发点，在有思考时立即处理 - # asyncio.create_task(self.chat_history_summarizer.process()) - - cycle_timers, thinking_id = self.start_cycle() - logger.info( - f"{self.log_prefix} 开始第{self._cycle_counter}次思考(频率: {global_config.chat.get_talk_value(self.stream_id)})" - ) - - # 第一步：动作检查 - available_actions: Dict[str, ActionInfo] = {} - try: - await self.action_modifier.modify_actions() - available_actions = self.action_manager.get_using_actions() - except Exception as e: - logger.error(f"{self.log_prefix} 动作修改失败: {e}") - - # 执行planner - is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info() - - message_list_before_now = get_raw_msg_before_timestamp_with_chat( - chat_id=self.stream_id, - timestamp=time.time(), - limit=int(global_config.chat.max_context_size * 0.6), - filter_intercept_message_level=1, - ) - chat_content_block, message_id_list = build_readable_messages_with_id( - messages=message_list_before_now, - timestamp_mode="normal_no_YMD", - read_mark=self.action_planner.last_obs_time_mark, - truncate=True, - show_actions=True, - ) - - prompt_info = await self.action_planner.build_planner_prompt( - is_group_chat=is_group_chat, - chat_target_info=chat_target_info, - current_available_actions=available_actions, - chat_content_block=chat_content_block, - message_id_list=message_id_list, - ) - 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): - action_to_use_info = await self.action_planner.plan( - loop_start_time=self.last_read_time, - available_actions=available_actions, - force_reply_message=force_reply_message, - ) - - logger.info( - f"{self.log_prefix} 决定执行{len(action_to_use_info)}个动作: {' '.join([a.action_type for a in action_to_use_info])}" - ) - - # 3. 并行执行所有动作 - action_tasks = [ - asyncio.create_task( - self._execute_action(action, action_to_use_info, thinking_id, available_actions, cycle_timers) - ) - for action in action_to_use_info - ] - - # 并行执行所有任务 - results = await asyncio.gather(*action_tasks, return_exceptions=True) - - # 处理执行结果 - reply_loop_info = None - reply_text_from_reply = "" - action_success = False - action_reply_text = "" - - excute_result_str = "" - for result in results: - excute_result_str += f"{result['action_type']} 执行结果:{result['result']}\n" - - if isinstance(result, BaseException): - logger.error(f"{self.log_prefix} 动作执行异常: {result}") - continue - - if result["action_type"] != "reply": - action_success = result["success"] - action_reply_text = result["result"] - elif result["action_type"] == "reply": - if result["success"]: - reply_loop_info = result["loop_info"] - reply_text_from_reply = result["result"] - else: - logger.warning(f"{self.log_prefix} 回复动作执行失败") - - self.action_planner.add_plan_excute_log(result=excute_result_str) - - # 构建最终的循环信息 - if reply_loop_info: - # 如果有回复信息，使用回复的loop_info作为基础 - loop_info = reply_loop_info - # 更新动作执行信息 - loop_info["loop_action_info"].update( - { - "action_taken": action_success, - "taken_time": time.time(), - } - ) - _reply_text = reply_text_from_reply - else: - # 没有回复信息，构建纯动作的loop_info - loop_info = { - "loop_plan_info": { - "action_result": action_to_use_info, - }, - "loop_action_info": { - "action_taken": action_success, - "reply_text": action_reply_text, - "taken_time": time.time(), - }, - } - _reply_text = action_reply_text - - self.end_cycle(loop_info, cycle_timers) - self.print_cycle_info(cycle_timers) - - end_time = time.time() - if end_time - start_time < global_config.chat.planner_smooth: - wait_time = global_config.chat.planner_smooth - (end_time - start_time) - await asyncio.sleep(wait_time) - else: - await asyncio.sleep(0.1) - return True - - async def _main_chat_loop(self): - """主循环，持续进行计划并可能回复消息，直到被外部取消。""" - try: - while self.running: - # 主循环 - success = await self._loopbody() - await asyncio.sleep(0.1) - if not success: - break - except asyncio.CancelledError: - # 设置了关闭标志位后被取消是正常流程 - logger.info(f"{self.log_prefix} 麦麦已关闭聊天") - except Exception: - logger.error(f"{self.log_prefix} 麦麦聊天意外错误，将于3s后尝试重新启动") - print(traceback.format_exc()) - await asyncio.sleep(3) - self._loop_task = asyncio.create_task(self._main_chat_loop()) - logger.error(f"{self.log_prefix} 结束了当前聊天循环") - - async def _handle_action( - self, - action: str, - action_reasoning: str, - action_data: dict, - cycle_timers: Dict[str, float], - thinking_id: str, - action_message: Optional["DatabaseMessages"] = None, - ) -> tuple[bool, str, str]: - """ - 处理规划动作，使用动作工厂创建相应的动作处理器 - - 参数: - action: 动作类型 - action_reasoning: 决策理由 - action_data: 动作数据，包含不同动作需要的参数 - cycle_timers: 计时器字典 - thinking_id: 思考ID - action_message: 消息数据 - 返回: - tuple[bool, str, str]: (是否执行了动作, 思考消息ID, 命令) - """ - try: - # 使用工厂创建动作处理器实例 - try: - action_handler = self.action_manager.create_action( - action_name=action, - action_data=action_data, - cycle_timers=cycle_timers, - thinking_id=thinking_id, - chat_stream=self.chat_stream, - log_prefix=self.log_prefix, - action_reasoning=action_reasoning, - action_message=action_message, - ) - except Exception as e: - logger.error(f"{self.log_prefix} 创建动作处理器时出错: {e}") - traceback.print_exc() - return False, "" - - # 处理动作并获取结果（固定记录一次动作信息） - result = await action_handler.execute() - success, action_text = result - - return success, action_text - - except Exception as e: - logger.error(f"{self.log_prefix} 处理{action}时出错: {e}") - traceback.print_exc() - return False, "" - - async def _send_response( - self, - reply_set: "ReplySetModel", - message_data: "DatabaseMessages", - selected_expressions: Optional[List[int]] = None, - quote_message: Optional[bool] = None, - ) -> str: - # 根据 llm_quote 配置决定是否使用 quote_message 参数 - if global_config.chat.llm_quote: - # 如果配置为 true，使用 llm_quote 参数决定是否引用回复 - if quote_message is None: - logger.warning(f"{self.log_prefix} quote_message 参数为空，不引用") - need_reply = False - else: - need_reply = quote_message - if need_reply: - logger.info(f"{self.log_prefix} LLM 决定使用引用回复") - else: - # 如果配置为 false，使用原来的模式 - new_message_count = message_api.count_new_messages( - chat_id=self.chat_stream.stream_id, start_time=self.last_read_time, end_time=time.time() - ) - need_reply = new_message_count >= random.randint(2, 3) or time.time() - self.last_read_time > 90 - if need_reply: - logger.info(f"{self.log_prefix} 从思考到回复，共有{new_message_count}条新消息，使用引用回复，或者上次回复时间超过90秒") - - reply_text = "" - first_replied = False - for reply_content in reply_set.reply_data: - if reply_content.content_type != ReplyContentType.TEXT: - continue - data: str = reply_content.content # type: ignore - if not first_replied: - await send_api.text_to_stream( - text=data, - stream_id=self.chat_stream.stream_id, - reply_message=message_data, - set_reply=need_reply, - typing=False, - selected_expressions=selected_expressions, - ) - first_replied = True - else: - await send_api.text_to_stream( - text=data, - stream_id=self.chat_stream.stream_id, - reply_message=message_data, - set_reply=False, - typing=True, - selected_expressions=selected_expressions, - ) - reply_text += data - - return reply_text - - async def _execute_action( - self, - action_planner_info: ActionPlannerInfo, - chosen_action_plan_infos: List[ActionPlannerInfo], - thinking_id: str, - available_actions: Dict[str, ActionInfo], - cycle_timers: Dict[str, float], - ): - """执行单个动作的通用函数""" - try: - with Timer(f"动作{action_planner_info.action_type}", cycle_timers): - # 直接当场执行no_reply逻辑 - if action_planner_info.action_type == "no_reply": - # 直接处理no_reply逻辑，不再通过动作系统 - reason = action_planner_info.reasoning or "选择不回复" - # logger.info(f"{self.log_prefix} 选择不回复，原因: {reason}") - - # 增加连续 no_reply 计数 - self.consecutive_no_reply_count += 1 - - await database_api.store_action_info( - chat_stream=self.chat_stream, - action_build_into_prompt=False, - action_prompt_display=reason, - action_done=True, - thinking_id=thinking_id, - action_data={}, - action_name="no_reply", - action_reasoning=reason, - ) - - return {"action_type": "no_reply", "success": True, "result": "选择不回复", "command": ""} - - elif action_planner_info.action_type == "reply": - # 直接当场执行reply逻辑 - self.questioned = False - # 刷新主动发言状态 - # 重置连续 no_reply 计数 - self.consecutive_no_reply_count = 0 - - reason = action_planner_info.reasoning or "" - # 根据 think_mode 配置决定 think_level 的值 - think_mode = global_config.chat.think_mode - if think_mode == "default": - think_level = 0 - elif think_mode == "deep": - think_level = 1 - elif think_mode == "dynamic": - # dynamic 模式：从 planner 返回的 action_data 中获取 - think_level = action_planner_info.action_data.get("think_level", 1) - else: - # 默认使用 default 模式 - think_level = 0 - # 使用 action_reasoning（planner 的整体思考理由）作为 reply_reason - planner_reasoning = action_planner_info.action_reasoning or reason - - record_replyer_action_temp( - chat_id=self.stream_id, - reason=reason, - think_level=think_level, - ) - - await database_api.store_action_info( - chat_stream=self.chat_stream, - action_build_into_prompt=False, - action_prompt_display=reason, - action_done=True, - thinking_id=thinking_id, - action_data={}, - action_name="reply", - action_reasoning=reason, - ) - - # 从 Planner 的 action_data 中提取未知词语列表（仅在 reply 时使用） - unknown_words = None - quote_message = None - if isinstance(action_planner_info.action_data, dict): - uw = action_planner_info.action_data.get("unknown_words") - if isinstance(uw, list): - cleaned_uw: List[str] = [] - for item in uw: - if isinstance(item, str): - s = item.strip() - if s: - cleaned_uw.append(s) - if cleaned_uw: - unknown_words = cleaned_uw - - # 从 Planner 的 action_data 中提取 quote_message 参数 - qm = action_planner_info.action_data.get("quote") - if qm is not None: - # 支持多种格式：true/false, "true"/"false", 1/0 - if isinstance(qm, bool): - quote_message = qm - elif isinstance(qm, str): - quote_message = qm.lower() in ("true", "1", "yes") - elif isinstance(qm, (int, float)): - quote_message = bool(qm) - - logger.info(f"{self.log_prefix} {qm}引用回复设置: {quote_message}") - - success, llm_response = await generator_api.generate_reply( - chat_stream=self.chat_stream, - reply_message=action_planner_info.action_message, - available_actions=available_actions, - chosen_actions=chosen_action_plan_infos, - reply_reason=planner_reasoning, - unknown_words=unknown_words, - enable_tool=global_config.tool.enable_tool, - request_type="replyer", - from_plugin=False, - reply_time_point=action_planner_info.action_data.get("loop_start_time", time.time()), - think_level=think_level, - ) - - if not success or not llm_response or not llm_response.reply_set: - if action_planner_info.action_message: - logger.info(f"对 {action_planner_info.action_message.processed_plain_text} 的回复生成失败") - else: - logger.info("回复生成失败") - return {"action_type": "reply", "success": False, "result": "回复生成失败", "loop_info": None} - - response_set = llm_response.reply_set - selected_expressions = llm_response.selected_expressions - loop_info, reply_text, _ = await self._send_and_store_reply( - response_set=response_set, - action_message=action_planner_info.action_message, # type: ignore - cycle_timers=cycle_timers, - thinking_id=thinking_id, - actions=chosen_action_plan_infos, - selected_expressions=selected_expressions, - quote_message=quote_message, - ) - self.last_active_time = time.time() - return { - "action_type": "reply", - "success": True, - "result": f"你使用reply动作，对' {action_planner_info.action_message.processed_plain_text} '这句话进行了回复，回复内容为: '{reply_text}'", - "loop_info": loop_info, - } - - else: - # 执行普通动作 - with Timer("动作执行", cycle_timers): - success, result = await self._handle_action( - action=action_planner_info.action_type, - action_reasoning=action_planner_info.action_reasoning or "", - action_data=action_planner_info.action_data or {}, - cycle_timers=cycle_timers, - thinking_id=thinking_id, - action_message=action_planner_info.action_message, - ) - - self.last_active_time = time.time() - return { - "action_type": action_planner_info.action_type, - "success": success, - "result": result, - } - - except Exception as e: - logger.error(f"{self.log_prefix} 执行动作时出错: {e}") - logger.error(f"{self.log_prefix} 错误信息: {traceback.format_exc()}") - return { - "action_type": action_planner_info.action_type, - "success": False, - "result": "", - "loop_info": None, - "error": str(e), - } diff --git a/src/chat/heart_flow/heartFC_chat.py b/src/chat/heart_flow/heartFC_chat.py index 2c1eb162..74d94773 100644 --- a/src/chat/heart_flow/heartFC_chat.py +++ b/src/chat/heart_flow/heartFC_chat.py @@ -1,377 +1,231 @@ -from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple +from rich.traceback import install +from typing import List, Optional, TYPE_CHECKING import asyncio import random import time import traceback -from rich.traceback import install - -from src.learners.expression_learner import ExpressionLearner -from src.learners.jargon_miner import JargonMiner -from src.chat.event_helpers import build_event_message -from src.chat.logger.plan_reply_logger import PlanReplyLogger -from src.chat.message_receive.chat_manager import BotChatSession -from src.chat.message_receive.chat_manager import chat_manager as _chat_manager -from src.chat.planner_actions.action_manager import ActionManager -from src.chat.planner_actions.action_modifier import ActionModifier -from src.chat.planner_actions.planner import ActionPlanner -from src.chat.utils.prompt_builder import global_prompt_manager -from src.chat.utils.timer_calculator import Timer -from src.chat.utils.utils import record_replyer_action_temp -from src.common.data_models.info_data_model import ActionPlannerInfo -from src.common.data_models.message_component_data_model import MessageSequence, TextComponent +from src.chat.message_receive.chat_manager import chat_manager from src.common.logger import get_logger from src.common.utils.utils_config import ChatConfigUtils, ExpressionConfigUtils from src.config.config import global_config from src.config.file_watcher import FileChange -from src.core.event_bus import event_bus -from src.core.types import ActionInfo, EventType -from src.person_info.person_info import Person -from src.services import ( - database_service as database_api, - generator_service as generator_api, - message_service as message_api, - send_service as send_api, -) -from src.services.message_service import build_readable_messages_with_id, get_messages_before_time_in_chat +from src.learners.expression_learner import ExpressionLearner +from src.learners.jargon_miner import JargonMiner from .heartFC_utils import CycleDetail if TYPE_CHECKING: from src.chat.message_receive.message import SessionMessage - install(extra_lines=5) logger = get_logger("heartFC_chat") class HeartFChatting: - """管理一个持续运行的 Focus Chat 会话。""" + """ + 管理一个连续的Focus Chat聊天会话 + 用于在特定的聊天会话里面生成回复 + """ def __init__(self, session_id: str): - self.session_id = session_id - self.chat_stream: BotChatSession = _chat_manager.get_session_by_session_id(self.session_id) # type: ignore[assignment] - if not self.chat_stream: - raise ValueError(f"无法找到聊天会话 {self.session_id}") + """ + 初始化 HeartFChatting 实例 - session_name = _chat_manager.get_session_name(session_id) or session_id + Args: + session_id: 聊天会话ID + """ + # 基础属性 + self.session_id = session_id + session_name = chat_manager.get_session_name(session_id) or session_id self.log_prefix = f"[{session_name}]" self.session_name = session_name - self.action_manager = ActionManager() - self.action_planner = ActionPlanner(chat_id=self.session_id, action_manager=self.action_manager) - self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.session_id) - + # 系统运行状态 self._running: bool = False self._loop_task: Optional[asyncio.Task] = None + self._cycle_counter: int = 0 + self._hfc_lock: asyncio.Lock = asyncio.Lock() # 用于保护 _hfc_func 的并发访问 + # 聊天频率相关 + self._consecutive_no_reply_count = 0 # 跟踪连续 no_reply 次数，用于动态调整阈值 + self._talk_frequency_adjust: float = 1.0 # 发言频率修正值，默认为1.0，可以根据需要调整 + + # HFC内消息缓存 + self.message_cache: List[SessionMessage] = [] + + # Asyncio Event 用于控制循环的开始和结束 self._cycle_event = asyncio.Event() - self._hfc_lock = asyncio.Lock() - - self._cycle_counter = 0 - self._current_cycle_detail: Optional[CycleDetail] = None - self.history_loop: List[CycleDetail] = [] - - self.last_read_time = time.time() - 2 - self.last_active_time = time.time() - self._talk_frequency_adjust = 1.0 - self._consecutive_no_reply_count = 0 - - self.message_cache: List["SessionMessage"] = [] - - self._min_messages_for_extraction = 30 - self._min_extraction_interval = 60 - self._last_extraction_time = 0.0 + # 表达方式相关内容 + self._min_messages_for_extraction = 30 # 最少提取消息数 + self._min_extraction_interval = 60 # 最小提取时间间隔，单位为秒 + self._last_extraction_time: float = 0.0 # 上次提取的时间戳 expr_use, jargon_learn, expr_learn = ExpressionConfigUtils.get_expression_config_for_chat(session_id) - self._enable_expression_use = expr_use - self._enable_expression_learning = expr_learn - self._enable_jargon_learning = jargon_learn - self._expression_learner = ExpressionLearner(session_id) - self._jargon_miner = JargonMiner(session_id, session_name=session_name) + self._enable_expression_use = expr_use # 允许使用表达方式，但不一定启用学习 + self._enable_expression_learning = expr_learn # 允许学习表达方式 + self._enable_jargon_learning = jargon_learn # 允许学习黑话 + # 表达学习器 + self._expression_learner: ExpressionLearner = ExpressionLearner(session_id) + # 黑话挖掘器 + self._jargon_miner: JargonMiner = JargonMiner(session_id, session_name=session_name) + + # TODO: ChatSummarizer 聊天总结器重构 + + # ====== 公开方法 ====== async def start(self): + """启动 HeartFChatting 的主循环""" + # 先检查是否已经启动运行 if self._running: - logger.debug(f"{self.log_prefix} HeartFChatting 已在运行中") + logger.debug(f"{self.log_prefix} 已经在运行中，无需重复启动") return try: self._running = True - self._cycle_event.clear() + self._cycle_event.clear() # 确保事件初始状态为未设置 + self._loop_task = asyncio.create_task(self.main_loop()) self._loop_task.add_done_callback(self._handle_loop_completion) + logger.info(f"{self.log_prefix} HeartFChatting 启动完成") - except Exception as exc: - logger.error(f"{self.log_prefix} HeartFChatting 启动失败: {exc}", exc_info=True) - self._running = False - self._cycle_event.set() - self._loop_task = None + except Exception as e: + logger.error(f"{self.log_prefix} 启动 HeartFChatting 失败: {e}", exc_info=True) + self._running = False # 确保状态正确 + self._cycle_event.set() # 确保事件被设置，避免死锁 + self._loop_task = None # 确保任务引用被清理 raise async def stop(self): + """停止 HeartFChatting 的主循环""" if not self._running: - logger.debug(f"{self.log_prefix} HeartFChatting 已停止") + logger.debug(f"{self.log_prefix} HeartFChatting 已经停止，无需重复停止") return self._running = False - self._cycle_event.set() + self._cycle_event.set() # 触发事件，通知循环结束 if self._loop_task: - self._loop_task.cancel() + self._loop_task.cancel() # 取消主循环任务 try: - await self._loop_task + await self._loop_task # 等待任务完成 except asyncio.CancelledError: - logger.info(f"{self.log_prefix} HeartFChatting 主循环已取消") - except Exception as exc: - logger.error(f"{self.log_prefix} 停止 HeartFChatting 时发生错误: {exc}", exc_info=True) + logger.info(f"{self.log_prefix} HeartFChatting 主循环已成功取消") + except Exception as e: + logger.error(f"{self.log_prefix} 停止 HeartFChatting 时发生错误: {e}", exc_info=True) finally: - self._loop_task = None + self._loop_task = None # 确保任务引用被清理 logger.info(f"{self.log_prefix} HeartFChatting 已停止") def adjust_talk_frequency(self, new_value: float): + """调整发言频率的调整值 + + Args: + new_value: 新的修正值，必须为非负数。值越大，修正发言频率越高；值越小，修正发言频率越低。 + """ self._talk_frequency_adjust = max(0.0, new_value) async def register_message(self, message: "SessionMessage"): + """注册一条消息到 HeartFChatting 的缓存中，并检测其是否产生提及，决定是否唤醒聊天 + + Args: + message: 待注册的消息对象 + """ self.message_cache.append(message) - + # 先检查at必回复 if global_config.chat.inevitable_at_reply and message.is_at: - self.last_read_time = time.time() - async with self._hfc_lock: - await self._judge_and_response(mentioned_message=message, recent_messages_list=[message]) - return - + async with self._hfc_lock: # 确保与主循环逻辑的互斥访问 + await self._judge_and_response(message) + return # 直接返回，避免同一条消息被主循环再次处理 + # 再检查提及必回复 if global_config.chat.mentioned_bot_reply and message.is_mentioned: - self.last_read_time = time.time() - async with self._hfc_lock: - await self._judge_and_response(mentioned_message=message, recent_messages_list=[message]) + # 直接获取锁，确保一定一定触发回复逻辑，不受当前是否正在执行主循环的影响 + async with self._hfc_lock: # 确保与主循环逻辑的互斥访问 + await self._judge_and_response(message) return async def main_loop(self): try: while self._running and not self._cycle_event.is_set(): if not self._hfc_lock.locked(): - async with self._hfc_lock: + async with self._hfc_lock: # 确保主循环逻辑的互斥访问 await self._hfc_func() - await asyncio.sleep(0.1) + await asyncio.sleep(5) except asyncio.CancelledError: - logger.info(f"{self.log_prefix} HeartFChatting: 主循环被取消") - except Exception as exc: - logger.error(f"{self.log_prefix} HeartFChatting: 主循环异常: {exc}", exc_info=True) - await self.stop() + logger.info(f"{self.log_prefix} HeartFChatting: 主循环被取消，正在关闭") + except Exception as e: + logger.error(f"{self.log_prefix} 麦麦聊天意外错误: {e}，将于3s后尝试重新启动") + await self.stop() # 确保状态正确 await asyncio.sleep(3) - await self.start() + await self.start() # 尝试重新启动 async def _config_callback(self, file_change: Optional[FileChange] = None): - del file_change - expr_use, jargon_learn, expr_learn = ExpressionConfigUtils.get_expression_config_for_chat(self.session_id) - self._enable_expression_use = expr_use - self._enable_expression_learning = expr_learn - self._enable_jargon_learning = jargon_learn + """配置文件变更回调函数""" + # TODO: 根据配置文件变动重新计算相关参数： + """ + 需要计算的参数： + self._enable_expression_use = expr_use # 允许使用表达方式，但不一定启用学习 + self._enable_expression_learning = expr_learn # 允许学习表达方式 + self._enable_jargon_learning = jargon_learn # 允许学习黑话 + """ - async def _hfc_func(self): - recent_messages_list = message_api.get_messages_by_time_in_chat( - chat_id=self.session_id, - start_time=self.last_read_time, - end_time=time.time(), - limit=20, - limit_mode="latest", - filter_mai=True, - filter_command=False, - filter_intercept_message_level=1, - ) + # ====== 心流聊天核心逻辑 ====== + async def _hfc_func(self, mentioned_message: Optional["SessionMessage"] = None): + """心流聊天的主循环逻辑""" + if self._consecutive_no_reply_count >= 5: + threshold = 2 + elif self._consecutive_no_reply_count >= 3: + threshold = 2 if random.random() < 0.5 else 1 + else: + threshold = 1 - if len(recent_messages_list) < 1: + if len(self.message_cache) < threshold: await asyncio.sleep(0.2) return True - self.last_read_time = time.time() - - mentioned_message: Optional["SessionMessage"] = None - for message in recent_messages_list: - if global_config.chat.inevitable_at_reply and message.is_at: - mentioned_message = message - elif global_config.chat.mentioned_bot_reply and message.is_mentioned: - mentioned_message = message - - talk_value = ChatConfigUtils.get_talk_value(self.session_id) * self._talk_frequency_adjust - if mentioned_message: - await self._judge_and_response(mentioned_message=mentioned_message, recent_messages_list=recent_messages_list) - elif random.random() < talk_value: - await self._judge_and_response(recent_messages_list=recent_messages_list) + talk_value_threshold = ( + random.random() * ChatConfigUtils.get_talk_value(self.session_id) * self._talk_frequency_adjust + ) + if mentioned_message and global_config.chat.mentioned_bot_reply: + await self._judge_and_response(mentioned_message) + elif random.random() < talk_value_threshold: + await self._judge_and_response() return True - async def _judge_and_response( - self, - mentioned_message: Optional["SessionMessage"] = None, - recent_messages_list: Optional[List["SessionMessage"]] = None, - ): - recent_messages = list(recent_messages_list or self.message_cache[-20:]) - if recent_messages: - asyncio.create_task(self._trigger_expression_learning(recent_messages)) - - cycle_timers, thinking_id = self._start_cycle() + async def _judge_and_response(self, mentioned_message: Optional["SessionMessage"] = None): + """判定和生成回复""" + asyncio.create_task(self._trigger_expression_learning(self.message_cache)) + # TODO: 完成反思器之后的逻辑 + start_time = time.time() + current_cycle_detail = self._start_cycle() logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考") - try: - async with global_prompt_manager.async_message_scope(self._get_template_name()): - available_actions: Dict[str, ActionInfo] = {} - try: - await self.action_modifier.modify_actions() - available_actions = self.action_manager.get_using_actions() - except Exception as exc: - logger.error(f"{self.log_prefix} 动作修改失败: {exc}", exc_info=True) + # TODO: 动作检查逻辑 + # TODO: Planner逻辑 + # TODO: 动作执行逻辑 - is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info() - message_list_before_now = get_messages_before_time_in_chat( - chat_id=self.session_id, - timestamp=time.time(), - limit=int(global_config.chat.max_context_size * 0.6), - filter_intercept_message_level=1, - ) - chat_content_block, message_id_list = build_readable_messages_with_id( - messages=message_list_before_now, - timestamp_mode="normal_no_YMD", - read_mark=self.action_planner.last_obs_time_mark, - truncate=True, - show_actions=True, - ) - - prompt, filtered_actions = await self._build_planner_prompt_with_event( - available_actions=available_actions, - is_group_chat=is_group_chat, - chat_target_info=chat_target_info, - chat_content_block=chat_content_block, - message_id_list=message_id_list, - ) - if prompt is None: - return False - - with Timer("规划器", cycle_timers): - reasoning, action_to_use_info, llm_raw_output, llm_reasoning, llm_duration_ms = ( - await self.action_planner._execute_main_planner( - prompt=prompt, - message_id_list=message_id_list, - filtered_actions=filtered_actions, - available_actions=available_actions, - loop_start_time=self.last_read_time, - ) - ) - - action_to_use_info = self._ensure_force_reply_action( - actions=action_to_use_info, - force_reply_message=mentioned_message, - available_actions=available_actions, - ) - self.action_planner.add_plan_log(reasoning, action_to_use_info) - self.action_planner.last_obs_time_mark = time.time() - self._log_plan( - prompt=prompt, - reasoning=reasoning, - llm_raw_output=llm_raw_output, - llm_reasoning=llm_reasoning, - llm_duration_ms=llm_duration_ms, - actions=action_to_use_info, - ) - - logger.info( - f"{self.log_prefix} 决定执行{len(action_to_use_info)}个动作: {' '.join([a.action_type for a in action_to_use_info])}" - ) - - action_tasks = [ - asyncio.create_task( - self._execute_action( - action, - action_to_use_info, - thinking_id, - available_actions, - cycle_timers, - ) - ) - for action in action_to_use_info - ] - results = await asyncio.gather(*action_tasks, return_exceptions=True) - - reply_loop_info = None - reply_text_from_reply = "" - action_success = False - action_reply_text = "" - execute_result_str = "" - - for result in results: - if isinstance(result, BaseException): - logger.error(f"{self.log_prefix} 动作执行异常: {result}", exc_info=True) - continue - - execute_result_str += f"{result['action_type']} 执行结果:{result['result']}\n" - if result["action_type"] == "reply": - if result["success"]: - reply_loop_info = result["loop_info"] - reply_text_from_reply = result["result"] - else: - logger.warning(f"{self.log_prefix} reply 动作执行失败") - else: - action_success = result["success"] - action_reply_text = result["result"] - - self.action_planner.add_plan_excute_log(result=execute_result_str) - - if reply_loop_info: - loop_info = reply_loop_info - loop_info["loop_action_info"].update( - { - "action_taken": action_success, - "taken_time": time.time(), - } - ) - else: - loop_info = { - "loop_plan_info": { - "action_result": action_to_use_info, - }, - "loop_action_info": { - "action_taken": action_success, - "reply_text": action_reply_text, - "taken_time": time.time(), - }, - } - reply_text_from_reply = action_reply_text - - current_cycle_detail = self._end_cycle(self._current_cycle_detail, loop_info) - logger.debug(f"{self.log_prefix} 本轮最终输出: {reply_text_from_reply}") - return current_cycle_detail is not None - except Exception as exc: - logger.error(f"{self.log_prefix} 判定与回复流程失败: {exc}", exc_info=True) - if self._current_cycle_detail: - self._end_cycle( - self._current_cycle_detail, - { - "loop_plan_info": {"action_result": []}, - "loop_action_info": { - "action_taken": False, - "reply_text": "", - "taken_time": time.time(), - "error": str(exc), - }, - }, - ) - return False + cycle_detail = self._end_cycle(current_cycle_detail) + if wait_time := global_config.chat.planner_smooth - (time.time() - start_time) > 0: + await asyncio.sleep(wait_time) + else: + await asyncio.sleep(0.1) # 最小等待时间，避免过快循环 + return True def _handle_loop_completion(self, task: asyncio.Task): + """当 _hfc_func 任务完成时执行的回调。""" try: if exception := task.exception(): - logger.error(f"{self.log_prefix} HeartFChatting: 主循环异常退出: {exception}") - logger.error(traceback.format_exc()) + logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}") + logger.error(traceback.format_exc()) # Log full traceback for exceptions else: - logger.info(f"{self.log_prefix} HeartFChatting: 主循环已退出") + logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)") except asyncio.CancelledError: - logger.info(f"{self.log_prefix} HeartFChatting: 聊天已结束") + logger.info(f"{self.log_prefix} HeartFChatting: 结束了聊天") + # ====== 学习器触发逻辑 ====== async def _trigger_expression_learning(self, messages: List["SessionMessage"]): - if not messages: - return - self._expression_learner.add_messages(messages) if time.time() - self._last_extraction_time < self._min_extraction_interval: return @@ -379,14 +233,12 @@ class HeartFChatting: return if not self._enable_expression_learning: return - extraction_end_time = time.time() logger.info( f"聊天流 {self.session_name} 提取到 {len(messages)} 条消息，" f"时间窗口: {self._last_extraction_time:.2f} - {extraction_end_time:.2f}" ) self._last_extraction_time = extraction_end_time - try: jargon_miner = self._jargon_miner if self._enable_jargon_learning else None learnt_style = await self._expression_learner.learn(jargon_miner) @@ -394,398 +246,43 @@ class HeartFChatting: logger.info(f"{self.log_prefix} 表达学习完成") else: logger.debug(f"{self.log_prefix} 表达学习未获得有效结果") - except Exception as exc: - logger.error(f"{self.log_prefix} 表达学习失败: {exc}", exc_info=True) + except Exception as e: + logger.error(f"{self.log_prefix} 表达学习失败: {e}", exc_info=True) - def _start_cycle(self) -> Tuple[Dict[str, float], str]: + # ====== 记录循环执行信息相关逻辑 ====== + def _start_cycle(self) -> CycleDetail: self._cycle_counter += 1 - self._current_cycle_detail = CycleDetail(cycle_id=self._cycle_counter) - self._current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}" - return self._current_cycle_detail.time_records, self._current_cycle_detail.thinking_id + current_cycle_detail = CycleDetail(cycle_id=self._cycle_counter) + current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}" + return current_cycle_detail - def _end_cycle(self, cycle_detail: Optional[CycleDetail], loop_info: Optional[Dict[str, Any]] = None): - if cycle_detail is None: - return None - - cycle_detail.loop_plan_info = (loop_info or {}).get("loop_plan_info") - cycle_detail.loop_action_info = (loop_info or {}).get("loop_action_info") + def _end_cycle(self, cycle_detail: CycleDetail, only_long_execution: bool = True): cycle_detail.end_time = time.time() - self.history_loop.append(cycle_detail) - - timer_strings = [ + timer_strings: List[str] = [ f"{name}: {duration:.2f}s" for name, duration in cycle_detail.time_records.items() - if duration >= 0.1 + if not only_long_execution or duration >= 0.1 ] logger.info( - f"{self.log_prefix} 第{cycle_detail.cycle_id} 个心流循环完成，" - f"耗时: {cycle_detail.end_time - cycle_detail.start_time:.2f}s；" + f"{self.log_prefix} 第 {cycle_detail.cycle_id} 个心流循环完成" + f"耗时: {cycle_detail.end_time - cycle_detail.start_time:.2f}秒\n" f"详细计时: {', '.join(timer_strings) if timer_strings else '无'}" ) + return cycle_detail - async def _execute_action( - self, - action_planner_info: ActionPlannerInfo, - chosen_action_plan_infos: List[ActionPlannerInfo], - thinking_id: str, - available_actions: Dict[str, ActionInfo], - cycle_timers: Dict[str, float], - ): - try: - with Timer(f"动作{action_planner_info.action_type}", cycle_timers): - if action_planner_info.action_type == "no_reply": - reason = action_planner_info.reasoning or "选择不回复" - self._consecutive_no_reply_count += 1 - await database_api.store_action_info( - chat_stream=self.chat_stream, - display_prompt=reason, - thinking_id=thinking_id, - action_data={}, - action_name="no_reply", - action_reasoning=reason, - ) - return { - "action_type": "no_reply", - "success": True, - "result": "选择不回复", - "loop_info": None, - } + # ====== Action相关逻辑 ====== + async def _execute_action(self, *args, **kwargs): + """原ExecuteAction""" + raise NotImplementedError("执行动作的逻辑尚未实现") # TODO: 实现动作执行的逻辑，替换掉*args, **kwargs*占位符 - if action_planner_info.action_type == "reply": - self._consecutive_no_reply_count = 0 - reason = action_planner_info.reasoning or "" - think_level = self._get_think_level(action_planner_info) - planner_reasoning = action_planner_info.action_reasoning or reason + async def _execute_other_actions(self, *args, **kwargs): + """原HandleAction""" + raise NotImplementedError( + "执行其他动作的逻辑尚未实现" + ) # TODO: 实现其他动作执行的逻辑, 替换掉*args, **kwargs*占位符 - record_replyer_action_temp( - chat_id=self.session_id, - reason=reason, - think_level=think_level, - ) - await database_api.store_action_info( - chat_stream=self.chat_stream, - display_prompt=reason, - thinking_id=thinking_id, - action_data={}, - action_name="reply", - action_reasoning=reason, - ) - - unknown_words, quote_message = self._extract_reply_metadata(action_planner_info) - success, llm_response = await generator_api.generate_reply( - chat_stream=self.chat_stream, - reply_message=action_planner_info.action_message, - available_actions=available_actions, - chosen_actions=chosen_action_plan_infos, - reply_reason=planner_reasoning, - unknown_words=unknown_words, - enable_tool=global_config.tool.enable_tool, - request_type="replyer", - from_plugin=False, - reply_time_point=action_planner_info.action_data.get("loop_start_time", time.time()) - if action_planner_info.action_data - else time.time(), - think_level=think_level, - ) - if not success or not llm_response or not llm_response.reply_set: - if action_planner_info.action_message: - logger.info( - f"对 {action_planner_info.action_message.processed_plain_text} 的回复生成失败" - ) - else: - logger.info(f"{self.log_prefix} 回复生成失败") - return { - "action_type": "reply", - "success": False, - "result": "回复生成失败", - "loop_info": None, - } - - loop_info, reply_text, _ = await self._send_and_store_reply( - response_set=llm_response.reply_set, - action_message=action_planner_info.action_message, # type: ignore[arg-type] - cycle_timers=cycle_timers, - thinking_id=thinking_id, - actions=chosen_action_plan_infos, - selected_expressions=llm_response.selected_expressions, - quote_message=quote_message, - ) - self.last_active_time = time.time() - return { - "action_type": "reply", - "success": True, - "result": reply_text, - "loop_info": loop_info, - } - - with Timer("动作执行", cycle_timers): - success, result = await self._handle_action( - action=action_planner_info.action_type, - action_reasoning=action_planner_info.action_reasoning or "", - action_data=action_planner_info.action_data or {}, - cycle_timers=cycle_timers, - thinking_id=thinking_id, - action_message=action_planner_info.action_message, - ) - if success: - self.last_active_time = time.time() - return { - "action_type": action_planner_info.action_type, - "success": success, - "result": result, - "loop_info": None, - } - except Exception as exc: - logger.error(f"{self.log_prefix} 执行动作时出错: {exc}", exc_info=True) - return { - "action_type": action_planner_info.action_type, - "success": False, - "result": "", - "loop_info": None, - "error": str(exc), - } - - async def _handle_action( - self, - action: str, - action_reasoning: str, - action_data: dict, - cycle_timers: Dict[str, float], - thinking_id: str, - action_message: Optional["SessionMessage"] = None, - ) -> Tuple[bool, str]: - try: - action_handler = self.action_manager.create_action( - action_name=action, - action_data=action_data, - action_reasoning=action_reasoning, - cycle_timers=cycle_timers, - thinking_id=thinking_id, - chat_stream=self.chat_stream, - log_prefix=self.log_prefix, - action_message=action_message, - ) - if not action_handler: - logger.warning(f"{self.log_prefix} 未能创建动作处理器: {action}") - return False, "" - - success, action_text = await action_handler.execute() - return success, action_text - except Exception as exc: - logger.error(f"{self.log_prefix} 处理动作 {action} 时出错: {exc}", exc_info=True) - return False, "" - - async def _send_and_store_reply( - self, - response_set: MessageSequence, - action_message: "SessionMessage", - cycle_timers: Dict[str, float], - thinking_id: str, - actions: List[ActionPlannerInfo], - selected_expressions: Optional[List[int]] = None, - quote_message: Optional[bool] = None, - ) -> Tuple[Dict[str, Any], str, Dict[str, float]]: - with Timer("回复发送", cycle_timers): - reply_text = await self._send_response( - reply_set=response_set, - message_data=action_message, - selected_expressions=selected_expressions, - quote_message=quote_message, - ) - - platform = action_message.platform or getattr(self.chat_stream, "platform", "unknown") - person = Person(platform=platform, user_id=action_message.message_info.user_info.user_id) - action_prompt_display = f"你对{person.person_name}进行了回复：{reply_text}" - await database_api.store_action_info( - chat_stream=self.chat_stream, - display_prompt=action_prompt_display, - thinking_id=thinking_id, - action_data={"reply_text": reply_text}, - action_name="reply", - ) - - loop_info: Dict[str, Any] = { - "loop_plan_info": { - "action_result": actions, - }, - "loop_action_info": { - "action_taken": True, - "reply_text": reply_text, - "command": "", - "taken_time": time.time(), - }, - } - return loop_info, reply_text, cycle_timers - - async def _send_response( - self, - reply_set: MessageSequence, - message_data: "SessionMessage", - selected_expressions: Optional[List[int]] = None, - quote_message: Optional[bool] = None, - ) -> str: - if global_config.chat.llm_quote: - need_reply = bool(quote_message) - else: - new_message_count = message_api.count_new_messages( - chat_id=self.session_id, - start_time=self.last_read_time, - end_time=time.time(), - ) - need_reply = new_message_count >= random.randint(2, 3) or time.time() - self.last_read_time > 90 - - reply_text = "" - first_replied = False - for component in reply_set.components: - if not isinstance(component, TextComponent): - continue - data = component.text - if not first_replied: - await send_api.text_to_stream( - text=data, - stream_id=self.session_id, - reply_message=message_data, - set_reply=need_reply, - typing=False, - selected_expressions=selected_expressions, - ) - first_replied = True - else: - await send_api.text_to_stream( - text=data, - stream_id=self.session_id, - reply_message=message_data, - set_reply=False, - typing=True, - selected_expressions=selected_expressions, - ) - reply_text += data - return reply_text - - async def _build_planner_prompt_with_event( - self, - available_actions: Dict[str, ActionInfo], - is_group_chat: bool, - chat_target_info: Any, - chat_content_block: str, - message_id_list: List[Tuple[str, "SessionMessage"]], - ) -> Tuple[Optional[str], Dict[str, ActionInfo]]: - filtered_actions = self.action_planner._filter_actions_by_activation_type(available_actions, chat_content_block) - prompt, _ = await self.action_planner.build_planner_prompt( - is_group_chat=is_group_chat, - chat_target_info=chat_target_info, - current_available_actions=filtered_actions, - chat_content_block=chat_content_block, - message_id_list=message_id_list, - ) - event_message = build_event_message(EventType.ON_PLAN, llm_prompt=prompt, stream_id=self.session_id) - continue_flag, modified_message = await event_bus.emit(EventType.ON_PLAN, event_message) - if not continue_flag: - logger.info(f"{self.log_prefix} ON_PLAN 事件中止了本轮 HFC") - return None, filtered_actions - if modified_message and modified_message._modify_flags.modify_llm_prompt and modified_message.llm_prompt: - prompt = modified_message.llm_prompt - return prompt, filtered_actions - - def _ensure_force_reply_action( - self, - actions: List[ActionPlannerInfo], - force_reply_message: Optional["SessionMessage"], - available_actions: Dict[str, ActionInfo], - ) -> List[ActionPlannerInfo]: - if not force_reply_message: - return actions - - has_reply_to_force_message = any( - action.action_type == "reply" - and action.action_message - and action.action_message.message_id == force_reply_message.message_id - for action in actions - ) - if has_reply_to_force_message: - return actions - - actions = [action for action in actions if action.action_type != "no_reply"] - actions.insert( - 0, - ActionPlannerInfo( - action_type="reply", - reasoning="用户提及了我，必须回复该消息", - action_data={"loop_start_time": self.last_read_time}, - action_message=force_reply_message, - available_actions=available_actions, - action_reasoning=None, - ), - ) - logger.info(f"{self.log_prefix} 检测到强制回复消息，已补充 reply 动作") - return actions - - def _log_plan( - self, - prompt: str, - reasoning: str, - llm_raw_output: Optional[str], - llm_reasoning: Optional[str], - llm_duration_ms: Optional[float], - actions: List[ActionPlannerInfo], - ) -> None: - try: - PlanReplyLogger.log_plan( - chat_id=self.session_id, - prompt=prompt, - reasoning=reasoning, - raw_output=llm_raw_output, - raw_reasoning=llm_reasoning, - actions=actions, - timing={ - "llm_duration_ms": round(llm_duration_ms, 2) if llm_duration_ms is not None else None, - "loop_start_time": self.last_read_time, - }, - extra=None, - ) - except Exception: - logger.exception(f"{self.log_prefix} 记录 plan 日志失败") - - def _extract_reply_metadata( - self, - action_planner_info: ActionPlannerInfo, - ) -> Tuple[Optional[List[str]], Optional[bool]]: - unknown_words: Optional[List[str]] = None - quote_message: Optional[bool] = None - action_data = action_planner_info.action_data or {} - - raw_unknown_words = action_data.get("unknown_words") - if isinstance(raw_unknown_words, list): - cleaned_unknown_words = [] - for item in raw_unknown_words: - if isinstance(item, str) and (cleaned_item := item.strip()): - cleaned_unknown_words.append(cleaned_item) - if cleaned_unknown_words: - unknown_words = cleaned_unknown_words - - raw_quote = action_data.get("quote") - if isinstance(raw_quote, bool): - quote_message = raw_quote - elif isinstance(raw_quote, str): - quote_message = raw_quote.lower() in {"true", "1", "yes"} - elif isinstance(raw_quote, (int, float)): - quote_message = bool(raw_quote) - - return unknown_words, quote_message - - def _get_think_level(self, action_planner_info: ActionPlannerInfo) -> int: - think_mode = global_config.chat.think_mode - if think_mode == "default": - return 0 - if think_mode == "deep": - return 1 - if think_mode == "dynamic": - action_data = action_planner_info.action_data or {} - return int(action_data.get("think_level", 1)) - return 0 - - def _get_template_name(self) -> Optional[str]: - if self.chat_stream.context: - return self.chat_stream.context.template_name - return None + # ====== 响应发送相关方法 ====== + async def _send_response(self, *args, **kwargs): + raise NotImplementedError("发送回复的逻辑尚未实现") # TODO: 实现发送回复的逻辑，替换掉*args, **kwargs*占位符 + # 传入的消息至少应该是个MessageSequence实例，最好是SessionMessage实例，随后可直接转化为MessageSending实例 diff --git a/src/chat/heart_flow/heartflow.py b/src/chat/heart_flow/heartflow.py deleted file mode 100644 index febff2d5..00000000 --- a/src/chat/heart_flow/heartflow.py +++ /dev/null @@ -1,42 +0,0 @@ -import traceback -from typing import Any, Optional, Dict - -from src.chat.message_receive.chat_stream import get_chat_manager -from src.common.logger import get_logger -from src.chat.heart_flow.heartFC_chat import HeartFChatting -from src.chat.brain_chat.brain_chat import BrainChatting -from src.chat.message_receive.chat_stream import ChatStream - -logger = get_logger("heartflow") - - -class Heartflow: - """主心流协调器，负责初始化并协调聊天""" - - def __init__(self): - self.heartflow_chat_list: Dict[Any, HeartFChatting | BrainChatting] = {} - - async def get_or_create_heartflow_chat(self, chat_id: Any) -> Optional[HeartFChatting | BrainChatting]: - """获取或创建一个新的HeartFChatting实例""" - try: - if chat_id in self.heartflow_chat_list: - if chat := self.heartflow_chat_list.get(chat_id): - return chat - else: - chat_stream: ChatStream | None = get_chat_manager().get_stream(chat_id) - if not chat_stream: - raise ValueError(f"未找到 chat_id={chat_id} 的聊天流") - if chat_stream.group_info: - new_chat = HeartFChatting(chat_id=chat_id) - else: - new_chat = BrainChatting(chat_id=chat_id) - await new_chat.start() - self.heartflow_chat_list[chat_id] = new_chat - return new_chat - except Exception as e: - logger.error(f"创建心流聊天 {chat_id} 失败: {e}", exc_info=True) - traceback.print_exc() - return None - - -heartflow = Heartflow()