import random import time from typing import Optional, Dict from src.common.logger import get_logger from src.common.database.database_model import Expression from src.config.config import global_config from src.chat.message_receive.chat_stream import get_chat_manager from src.plugin_system.apis import send_api logger = get_logger("expression_reflector") class ExpressionReflector: """表达反思器，管理单个聊天流的表达反思提问""" def __init__(self, chat_id: str): self.chat_id = chat_id self.last_ask_time: float = 0.0 async def check_and_ask(self) -> bool: """ 检查是否需要提问表达反思，如果需要则提问 Returns: bool: 是否执行了提问 """ try: logger.debug(f"[Expression Reflection] 开始检查是否需要提问 (stream_id: {self.chat_id})") if not global_config.expression.expression_self_reflect: logger.debug("[Expression Reflection] 表达反思功能未启用，跳过") return False operator_config = global_config.expression.manual_reflect_operator_id if not operator_config: logger.debug("[Expression Reflection] Operator ID 未配置，跳过") return False # 检查是否在允许列表中 allow_reflect = global_config.expression.allow_reflect if allow_reflect: # 将 allow_reflect 中的 platform:id:type 格式转换为 chat_id 列表 allow_reflect_chat_ids = [] for stream_config in allow_reflect: parsed_chat_id = global_config.expression._parse_stream_config_to_chat_id(stream_config) if parsed_chat_id: allow_reflect_chat_ids.append(parsed_chat_id) else: logger.warning(f"[Expression Reflection] 无法解析 allow_reflect 配置项: {stream_config}") if self.chat_id not in allow_reflect_chat_ids: logger.info(f"[Expression Reflection] 当前聊天流 {self.chat_id} 不在允许列表中，跳过") return False # 检查上一次提问时间 current_time = time.time() time_since_last_ask = current_time - self.last_ask_time # 5-10分钟间隔，随机选择 min_interval = 10 * 60 # 5分钟 max_interval = 15 * 60 # 10分钟 interval = random.uniform(min_interval, max_interval) logger.info( f"[Expression Reflection] 上次提问时间: {self.last_ask_time:.2f}, 当前时间: {current_time:.2f}, 已过时间: {time_since_last_ask:.2f}秒 ({time_since_last_ask / 60:.2f}分钟), 需要间隔: {interval:.2f}秒 ({interval / 60:.2f}分钟)" ) if time_since_last_ask < interval: remaining_time = interval - time_since_last_ask logger.info( f"[Expression Reflection] 距离上次提问时间不足，还需等待 {remaining_time:.2f}秒 ({remaining_time / 60:.2f}分钟)，跳过" ) return False # 检查是否已经有针对该 Operator 的 Tracker 在运行 logger.info(f"[Expression Reflection] 检查 Operator {operator_config} 是否已有活跃的 Tracker") if await _check_tracker_exists(operator_config): logger.info(f"[Expression Reflection] Operator {operator_config} 已有活跃的 Tracker，跳过本次提问") return False # 获取未检查的表达 try: logger.info("[Expression Reflection] 查询未检查且未拒绝的表达") expressions = Expression.select().where((~Expression.checked) & (~Expression.rejected)).limit(50) expr_list = list(expressions) logger.info(f"[Expression Reflection] 找到 {len(expr_list)} 个候选表达") if not expr_list: logger.info("[Expression Reflection] 没有可用的表达，跳过") return False target_expr: Expression = random.choice(expr_list) logger.info( f"[Expression Reflection] 随机选择了表达 ID: {target_expr.id}, Situation: {target_expr.situation}, Style: {target_expr.style}" ) # 生成询问文本 ask_text = _generate_ask_text(target_expr) if not ask_text: logger.warning("[Expression Reflection] 生成询问文本失败，跳过") return False logger.info(f"[Expression Reflection] 准备向 Operator {operator_config} 发送提问") # 发送给 Operator await _send_to_operator(operator_config, ask_text, target_expr) # 更新上一次提问时间 self.last_ask_time = current_time logger.info(f"[Expression Reflection] 提问成功，已更新上次提问时间为 {current_time:.2f}") return True except Exception as e: logger.error(f"[Expression Reflection] 检查或提问过程中出错: {e}") import traceback logger.error(traceback.format_exc()) return False except Exception as e: logger.error(f"[Expression Reflection] 检查或提问过程中出错: {e}") import traceback logger.error(traceback.format_exc()) return False class ExpressionReflectorManager: """表达反思管理器，管理多个聊天流的表达反思实例""" def __init__(self): self.reflectors: Dict[str, ExpressionReflector] = {} def get_or_create_reflector(self, chat_id: str) -> ExpressionReflector: """获取或创建指定聊天流的表达反思实例""" if chat_id not in self.reflectors: self.reflectors[chat_id] = ExpressionReflector(chat_id) return self.reflectors[chat_id] # 创建全局实例 expression_reflector_manager = ExpressionReflectorManager() async def _check_tracker_exists(operator_config: str) -> bool: """检查指定 Operator 是否已有活跃的 Tracker""" from src.bw_learner.reflect_tracker import reflect_tracker_manager chat_manager = get_chat_manager() chat_stream = None # 尝试解析配置字符串 "platform:id:type" parts = operator_config.split(":") if len(parts) == 3: platform = parts[0] id_str = parts[1] stream_type = parts[2] user_info = None group_info = None from maim_message import UserInfo, GroupInfo if stream_type == "group": group_info = GroupInfo(group_id=id_str, platform=platform) user_info = UserInfo(user_id="system", user_nickname="System", platform=platform) elif stream_type == "private": user_info = UserInfo(user_id=id_str, platform=platform, user_nickname="Operator") else: return False if user_info: try: chat_stream = await chat_manager.get_or_create_stream(platform, user_info, group_info) except Exception as e: logger.error(f"Failed to get or create chat stream for checking tracker: {e}") return False else: chat_stream = chat_manager.get_stream(operator_config) if not chat_stream: return False return reflect_tracker_manager.get_tracker(chat_stream.stream_id) is not None def _generate_ask_text(expr: Expression) -> Optional[str]: try: ask_text = ( f"我正在学习新的表达方式，请帮我看看这个是否合适？\n\n" f"**学习到的表达信息**\n" f"- 情景 (Situation): {expr.situation}\n" f"- 风格 (Style): {expr.style}\n" ) return ask_text except Exception as e: logger.error(f"Failed to generate ask text: {e}") return None async def _send_to_operator(operator_config: str, text: str, expr: Expression): chat_manager = get_chat_manager() chat_stream = None # 尝试解析配置字符串 "platform:id:type" parts = operator_config.split(":") if len(parts) == 3: platform = parts[0] id_str = parts[1] stream_type = parts[2] user_info = None group_info = None from maim_message import UserInfo, GroupInfo if stream_type == "group": group_info = GroupInfo(group_id=id_str, platform=platform) user_info = UserInfo(user_id="system", user_nickname="System", platform=platform) elif stream_type == "private": user_info = UserInfo(user_id=id_str, platform=platform, user_nickname="Operator") else: logger.warning(f"Unknown stream type in operator config: {stream_type}") return if user_info: try: chat_stream = await chat_manager.get_or_create_stream(platform, user_info, group_info) except Exception as e: logger.error(f"Failed to get or create chat stream for operator {operator_config}: {e}") return else: chat_stream = chat_manager.get_stream(operator_config) if not chat_stream: logger.warning(f"Could not find or create chat stream for operator: {operator_config}") return stream_id = chat_stream.stream_id # 注册 Tracker from src.bw_learner.reflect_tracker import ReflectTracker, reflect_tracker_manager tracker = ReflectTracker(chat_stream=chat_stream, expression=expr, created_time=time.time()) reflect_tracker_manager.add_tracker(stream_id, tracker) # 发送消息 await send_api.text_to_stream(text=text, stream_id=stream_id, typing=True) logger.info(f"Sent expression reflect query to operator {operator_config} for expr {expr.id}")