应要求提交上未完成的HFC, expression部分
This commit is contained in:
UnCLAS-Prommer
60
src/bw_learner/expression_reflect_tracker.py
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60
src/bw_learner/expression_reflect_tracker.py
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@@ -0,0 +1,60 @@
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from typing import TYPE_CHECKING, Optional
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import time
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from src.common.logger import get_logger
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from src.common.database.database import get_db_session
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from src.llm_models.utils_model import LLMRequest
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from src.config.config import model_config
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if TYPE_CHECKING:
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from src.common.data_models.expression_data_model import MaiExpression
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# TODO: 这个LLMRequest实例被更优雅的方式替换掉
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judge_model = LLMRequest(model_set=model_config.model_task_config.tool_use, request_type="reflect.tracker")
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logger = get_logger("reflect_tracker")
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class ReflectTracker:
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def __init__(self, session_id: str):
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self.session_id = session_id
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self.last_check_msg_count = 0
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self.max_msg_count = 30
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self.max_duration = 15 * 60 # 15 分钟
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self.expression: Optional["MaiExpression"] = None # 当前正在追踪的表达，由外部设置
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# 运行状态
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self.tracking = False
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self.tracking_start_time: float = 0.0
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def register_expression_and_track(self, expression: "MaiExpression"):
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"""注册需要追踪的表达"""
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if self.tracking:
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raise RuntimeError("ReflectTracker is already tracking an expression.")
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self.expression = expression
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self.tracking = True
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self.tracking_start_time = time.time()
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def _reset_tracker(self):
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"""重置追踪状态"""
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self.expression = None
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self.tracking = False
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self.last_check_msg_count = 0
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async def trigger_tracker(self) -> bool:
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"""
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触发追踪检查
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Returns:
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return (bool): 如果返回True，表示追踪完成，Tracker运行结束（运行状态置为`False`）；如果返回False，表示继续追踪
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"""
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# 对于没有正在追踪的表达，直接返回False
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if not self.tracking:
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return False
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# 检查是否超时（无论是消息数量还是时间）
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if time.time() - self.tracking_start_time > self.max_duration:
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self._reset_tracker()
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return True
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# TODO: 完成追踪检查逻辑
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@@ -1,22 +1,35 @@
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from rich.traceback import install
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from sqlmodel import select
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from typing import TYPE_CHECKING
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import random
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import time
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from typing import Optional, Dict
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from src.common.logger import get_logger
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from src.common.database.database_model import Expression
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from src.config.config import global_config
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from src.chat.message_receive.chat_stream import get_chat_manager
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from src.plugin_system.apis import send_api
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from src.common.database.database_model import Expression
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from src.common.database.database import get_db_session
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from src.common.data_models.expression_data_model import MaiExpression
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from src.common.utils.utils_session import SessionUtils
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from .expression_reflect_tracker import ReflectTracker
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if TYPE_CHECKING:
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from src.config.official_configs import TargetItem
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logger = get_logger("expression_reflector")
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install(extra_lines=3)
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LOG_PREFIX = "[Expression Reflector]"
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class ExpressionReflector:
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"""表达反思器，管理单个聊天流的表达反思提问"""
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"""表达反思器，管理单个聊天流的表达反思提问，使用每个session_id独立的实例"""
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def __init__(self, chat_id: str):
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self.chat_id = chat_id
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self.last_ask_time: float = 0.0
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def __init__(self, session_id: str):
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self.session_id = session_id
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self.last_ask_time: float = time.time()
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self.reflect_tracker: ReflectTracker = ReflectTracker(session_id)
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async def check_and_ask(self) -> bool:
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"""
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@@ -25,226 +38,99 @@ class ExpressionReflector:
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Returns:
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bool: 是否执行了提问
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"""
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try:
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logger.debug(f"[Expression Reflection] 开始检查是否需要提问 (stream_id: {self.chat_id})")
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if not global_config.expression.expression_manual_reflect:
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logger.debug("[Expression Reflection] 表达反思功能未启用，跳过")
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return False
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operator_config = global_config.expression.manual_reflect_operator_id
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if not operator_config:
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logger.debug("[Expression Reflection] Operator ID 未配置，跳过")
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return False
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# 检查是否在允许列表中
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allow_reflect = global_config.expression.allow_reflect
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if allow_reflect:
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# 将 allow_reflect 中的 platform:id:type 格式转换为 chat_id 列表
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allow_reflect_chat_ids = []
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for stream_config in allow_reflect:
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parsed_chat_id = global_config.expression._parse_stream_config_to_chat_id(stream_config)
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if parsed_chat_id:
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allow_reflect_chat_ids.append(parsed_chat_id)
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else:
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logger.warning(f"[Expression Reflection] 无法解析 allow_reflect 配置项: {stream_config}")
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if self.chat_id not in allow_reflect_chat_ids:
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logger.info(f"[Expression Reflection] 当前聊天流 {self.chat_id} 不在允许列表中，跳过")
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return False
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# 检查上一次提问时间
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current_time = time.time()
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time_since_last_ask = current_time - self.last_ask_time
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# 5-10分钟间隔，随机选择
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min_interval = 10 * 60 # 5分钟
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max_interval = 15 * 60 # 10分钟
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interval = random.uniform(min_interval, max_interval)
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logger.info(
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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)"
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)
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if time_since_last_ask < interval:
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remaining_time = interval - time_since_last_ask
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logger.info(
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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"
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)
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return False
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# 检查是否已经有针对该 Operator 的 Tracker 在运行
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logger.info(f"[Expression Reflection] 检查 Operator {operator_config} 是否已有活跃的 Tracker")
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if await _check_tracker_exists(operator_config):
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logger.info(f"[Expression Reflection] Operator {operator_config} 已有活跃的 Tracker，跳过本次提问")
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return False
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# 获取未检查的表达
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try:
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logger.info("[Expression Reflection] 查询未检查且未拒绝的表达")
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expressions = Expression.select().where((~Expression.checked) & (~Expression.rejected)).limit(50)
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expr_list = list(expressions)
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logger.info(f"[Expression Reflection] 找到 {len(expr_list)} 个候选表达")
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if not expr_list:
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logger.info("[Expression Reflection] 没有可用的表达，跳过")
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return False
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target_expr: Expression = random.choice(expr_list)
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logger.info(
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f"[Expression Reflection] 随机选择了表达 ID: {target_expr.id}, Situation: {target_expr.situation}, Style: {target_expr.style}"
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)
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# 生成询问文本
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ask_text = _generate_ask_text(target_expr)
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if not ask_text:
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logger.warning("[Expression Reflection] 生成询问文本失败，跳过")
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return False
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logger.info(f"[Expression Reflection] 准备向 Operator {operator_config} 发送提问")
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# 发送给 Operator
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await _send_to_operator(operator_config, ask_text, target_expr)
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# 更新上一次提问时间
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self.last_ask_time = current_time
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logger.info(f"[Expression Reflection] 提问成功，已更新上次提问时间为 {current_time:.2f}")
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return True
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except Exception as e:
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logger.error(f"[Expression Reflection] 检查或提问过程中出错: {e}")
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import traceback
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logger.error(traceback.format_exc())
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return False
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except Exception as e:
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logger.error(f"[Expression Reflection] 检查或提问过程中出错: {e}")
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import traceback
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logger.error(traceback.format_exc())
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if not await self.check_need_ask():
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return False
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class ExpressionReflectorManager:
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"""表达反思管理器，管理多个聊天流的表达反思实例"""
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def __init__(self):
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self.reflectors: Dict[str, ExpressionReflector] = {}
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def get_or_create_reflector(self, chat_id: str) -> ExpressionReflector:
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"""获取或创建指定聊天流的表达反思实例"""
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if chat_id not in self.reflectors:
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self.reflectors[chat_id] = ExpressionReflector(chat_id)
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return self.reflectors[chat_id]
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# 创建全局实例
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expression_reflector_manager = ExpressionReflectorManager()
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async def _check_tracker_exists(operator_config: str) -> bool:
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"""检查指定 Operator 是否已有活跃的 Tracker"""
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from src.bw_learner.reflect_tracker import reflect_tracker_manager
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chat_manager = get_chat_manager()
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chat_stream = None
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# 尝试解析配置字符串 "platform:id:type"
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parts = operator_config.split(":")
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if len(parts) == 3:
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platform = parts[0]
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id_str = parts[1]
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stream_type = parts[2]
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user_info = None
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group_info = None
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from maim_message import UserInfo, GroupInfo
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if stream_type == "group":
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group_info = GroupInfo(group_id=id_str, platform=platform)
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user_info = UserInfo(user_id="system", user_nickname="System", platform=platform)
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elif stream_type == "private":
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user_info = UserInfo(user_id=id_str, platform=platform, user_nickname="Operator")
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else:
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operator_config = global_config.expression.manual_reflect_operator_id
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if not operator_config:
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logger.debug(f"{LOG_PREFIX} Operator ID 未配置，跳过")
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return False
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if user_info:
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try:
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chat_stream = await chat_manager.get_or_create_stream(platform, user_info, group_info)
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except Exception as e:
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logger.error(f"Failed to get or create chat stream for checking tracker: {e}")
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return False
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else:
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chat_stream = chat_manager.get_stream(operator_config)
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if not chat_stream:
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if await self.ask_reflection(operator_config):
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self.last_ask_time = time.time()
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return True
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return False
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return reflect_tracker_manager.get_tracker(chat_stream.stream_id) is not None
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async def check_need_ask(self) -> bool:
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"""
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检查是否需要提问表达反思
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Returns:
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bool: 是否执行了提问
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"""
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if not global_config.expression.expression_manual_reflect:
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logger.debug(f"{LOG_PREFIX} 表达反思功能未启用，跳过")
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return False
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logger.debug(f"{LOG_PREFIX} 开始检查是否需要提问 (session_id: {self.session_id})")
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operator_config = global_config.expression.manual_reflect_operator_id
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if not operator_config:
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logger.debug(f"{LOG_PREFIX} Operator ID 未配置，跳过")
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return False
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if allow_reflect_list := global_config.expression.allow_reflect:
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# 转换配置项为session_id列表
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allow_reflect_session_ids = [
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self._parse_config_item_2_session_id(stream_config) for stream_config in allow_reflect_list
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]
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if self.session_id not in allow_reflect_session_ids:
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logger.info(f"{LOG_PREFIX} 当前聊天流 {self.session_id} 不在允许列表中，跳过")
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return False
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# 检查上一次提问时间
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current_time = time.time()
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time_since_last_ask = current_time - self.last_ask_time
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# 随机选择10-15分钟间隔
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ask_interval = random.uniform(10 * 60, 15 * 60)
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if time_since_last_ask < ask_interval:
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logger.info(
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f"{LOG_PREFIX} 距离上次提问时间 {time_since_last_ask:.2f} 秒，未达到随机间隔 {ask_interval:.2f} 秒，跳过"
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)
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return False
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if self.reflect_tracker.tracking:
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logger.info(f"{LOG_PREFIX} Operator {operator_config} 已有活跃的 Tracker，跳过本次提问")
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return False
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return True
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async def ask_reflection(self, operator_config: "TargetItem") -> bool:
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"""执行提问表达反思的操作"""
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# 选取未检查过的表达
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logger.info(f"{LOG_PREFIX} 查询未检查且未拒绝的表达")
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try:
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with get_db_session() as session:
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statement = select(Expression).filter_by(checked=False, rejected=False).limit(50)
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results = session.exec(statement).all()
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if not results:
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logger.info(f"{LOG_PREFIX} 未找到未检查且未拒绝的表达")
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return False
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logger.info(f"{LOG_PREFIX} 找到 {len(results)} 个未检查且未拒绝的表达")
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except Exception as selected_expression:
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logger.error(f"{LOG_PREFIX} 查询表达时发生错误: {selected_expression}")
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return False
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# 随机选取一个表达进行提问
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selected_expression = MaiExpression.from_db_instance(random.choice(results))
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item_id = selected_expression.item_id
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situation = selected_expression.situation
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style = selected_expression.style
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logger.info(f"{LOG_PREFIX} 随机选择了表达 ID: {item_id}, Situation: {situation}, Style: {style}")
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def _generate_ask_text(expr: Expression) -> Optional[str]:
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try:
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ask_text = (
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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"
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f"**学习到的表达信息**\n"
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f"- 情景 (Situation): {expr.situation}\n"
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f"- 风格 (Style): {expr.style}\n"
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f"- 情景 (Situation): {situation}\n"
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f"- 风格 (Style): {style}\n"
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)
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return ask_text
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except Exception as e:
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logger.error(f"Failed to generate ask text: {e}")
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return None
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# TODO: 在发送相关API重构完成后完成发送给operator的逻辑
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async def _send_to_operator(operator_config: str, text: str, expr: Expression):
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chat_manager = get_chat_manager()
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chat_stream = None
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self.reflect_tracker.register_expression_and_track(selected_expression)
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return True
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# 尝试解析配置字符串 "platform:id:type"
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parts = operator_config.split(":")
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if len(parts) == 3:
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platform = parts[0]
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id_str = parts[1]
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stream_type = parts[2]
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user_info = None
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group_info = None
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from maim_message import UserInfo, GroupInfo
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if stream_type == "group":
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group_info = GroupInfo(group_id=id_str, platform=platform)
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user_info = UserInfo(user_id="system", user_nickname="System", platform=platform)
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elif stream_type == "private":
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user_info = UserInfo(user_id=id_str, platform=platform, user_nickname="Operator")
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def _parse_config_item_2_session_id(self, config_item: "TargetItem") -> str:
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if config_item.rule_type == "group":
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return SessionUtils.calculate_session_id(config_item.platform, group_id=str(config_item.item_id))
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else:
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logger.warning(f"Unknown stream type in operator config: {stream_type}")
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return
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if user_info:
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try:
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chat_stream = await chat_manager.get_or_create_stream(platform, user_info, group_info)
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except Exception as e:
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logger.error(f"Failed to get or create chat stream for operator {operator_config}: {e}")
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return
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else:
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chat_stream = chat_manager.get_stream(operator_config)
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if not chat_stream:
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logger.warning(f"Could not find or create chat stream for operator: {operator_config}")
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return
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stream_id = chat_stream.stream_id
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# 注册 Tracker
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from src.bw_learner.reflect_tracker import ReflectTracker, reflect_tracker_manager
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tracker = ReflectTracker(chat_stream=chat_stream, expression=expr, created_time=time.time())
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reflect_tracker_manager.add_tracker(stream_id, tracker)
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# 发送消息
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await send_api.text_to_stream(text=text, stream_id=stream_id, typing=True)
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logger.info(f"Sent expression reflect query to operator {operator_config} for expr {expr.id}")
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return SessionUtils.calculate_session_id(config_item.platform, user_id=str(config_item.item_id))
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|
||||
@@ -1,148 +1,169 @@
|
||||
from rich.traceback import install
|
||||
from typing import Optional, List, TYPE_CHECKING
|
||||
|
||||
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.bw_learner.expression_learner import expression_learner_manager
|
||||
from src.chat.heart_flow.frequency_control import frequency_control_manager
|
||||
from src.bw_learner.reflect_tracker import reflect_tracker_manager
|
||||
from src.bw_learner.expression_reflector import expression_reflector_manager
|
||||
from src.bw_learner.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
|
||||
from src.common.utils.utils_session import SessionUtils
|
||||
from src.config.config import global_config
|
||||
from src.chat.message_receive.chat_manager import chat_manager
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from src.common.data_models.database_data_model import DatabaseMessages
|
||||
from src.common.data_models.message_data_model import ReplySetModel
|
||||
from src.chat.message_receive.message import SessionMessage
|
||||
|
||||
install(extra_lines=5)
|
||||
|
||||
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
|
||||
logger = get_logger("heartFC_chat")
|
||||
|
||||
|
||||
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。
|
||||
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, chat_id: str):
|
||||
def __init__(self, session_id: str):
|
||||
"""
|
||||
HeartFChatting 初始化函数
|
||||
初始化 HeartFChatting 实例
|
||||
|
||||
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
|
||||
Args:
|
||||
session_id: 聊天会话ID
|
||||
"""
|
||||
# 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.session_id = session_id
|
||||
session_name = chat_manager.get_session_name(session_id) or session_id
|
||||
self.log_prefix = f"[{session_name}]"
|
||||
|
||||
self.expression_learner = expression_learner_manager.get_expression_learner(self.stream_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
|
||||
|
||||
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)
|
||||
# HFC内消息缓存
|
||||
self.message_cache: List[SessionMessage] = []
|
||||
|
||||
# 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)
|
||||
# Asyncio Event 用于控制循环的开始和结束
|
||||
self._cycle_event = asyncio.Event()
|
||||
|
||||
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")
|
||||
"""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} 已经在运行中，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._running = True
|
||||
self._cycle_event.clear() # 确保事件初始状态为未设置
|
||||
|
||||
self._loop_task = asyncio.create_task(self._main_chat_loop())
|
||||
self._loop_task = asyncio.create_task(self.main_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}")
|
||||
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 已经停止，无需重复停止")
|
||||
return
|
||||
|
||||
self._running = False
|
||||
self._cycle_event.set() # 触发事件，通知循环结束
|
||||
|
||||
if self._loop_task:
|
||||
self._loop_task.cancel() # 取消主循环任务
|
||||
try:
|
||||
await self._loop_task # 等待任务完成
|
||||
except asyncio.CancelledError:
|
||||
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 # 确保任务引用被清理
|
||||
|
||||
logger.info(f"{self.log_prefix} HeartFChatting 已停止")
|
||||
|
||||
async 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:
|
||||
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:
|
||||
# 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: # 确保主循环逻辑的互斥访问
|
||||
await self._hfc_func()
|
||||
await asyncio.sleep(5)
|
||||
except asyncio.CancelledError:
|
||||
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() # 尝试重新启动
|
||||
|
||||
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(self.message_cache) < threshold:
|
||||
await asyncio.sleep(0.2)
|
||||
return True
|
||||
|
||||
talk_value_threshold = random.random() * self._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):
|
||||
"""判定和生成回复"""
|
||||
# TODO: 在expression和reflector重构完成后完成这里的逻辑
|
||||
|
||||
def _handle_loop_completion(self, task: asyncio.Task):
|
||||
"""当 _hfc_loop 任务完成时执行的回调。"""
|
||||
"""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: 脱离了聊天(异常): {exception}")
|
||||
@@ -152,657 +173,54 @@ class HeartFChatting:
|
||||
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: {TempMethods.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()
|
||||
< TempMethodsHFC.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
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# ReflectTracker Check
|
||||
# 在每次回复前检查一次上下文，看是否有反思问题得到了解答
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
reflector = expression_reflector_manager.get_or_create_reflector(self.stream_id)
|
||||
await reflector.check_and_ask()
|
||||
tracker = reflect_tracker_manager.get_tracker(self.stream_id)
|
||||
if tracker:
|
||||
resolved = await tracker.trigger_tracker()
|
||||
if resolved:
|
||||
reflect_tracker_manager.remove_tracker(self.stream_id)
|
||||
logger.info(f"{self.log_prefix} ReflectTracker resolved and removed.")
|
||||
|
||||
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: {TempMethodsHFC.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),
|
||||
}
|
||||
|
||||
|
||||
class TempMethodsHFC:
|
||||
@staticmethod
|
||||
def get_talk_value(chat_id: Optional[str]) -> float:
|
||||
result = global_config.chat.talk_value or 0.0000001
|
||||
def _get_talk_value(self, session_id: Optional[str]) -> float:
|
||||
result = global_config.chat.talk_value or 0.0
|
||||
if not global_config.chat.enable_talk_value_rules or not global_config.chat.talk_value_rules:
|
||||
return result
|
||||
import time
|
||||
|
||||
local_time = time.localtime()
|
||||
now_min = local_time.tm_hour * 60 + local_time.tm_min
|
||||
# 先处理特定规则
|
||||
if chat_id:
|
||||
|
||||
# 优先匹配会话相关的规则
|
||||
if session_id:
|
||||
for rule in global_config.chat.talk_value_rules:
|
||||
if not rule.platform and not rule.item_id:
|
||||
continue # 一起留空表示全局，跳过
|
||||
is_group = rule.rule_type == "group"
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
|
||||
stream_id = get_chat_manager().get_stream_id(rule.platform, str(rule.item_id), is_group)
|
||||
if stream_id != chat_id:
|
||||
continue
|
||||
parsed_range = TempMethodsHFC._parse_range(rule.time)
|
||||
continue # 一起留空表示全局
|
||||
if rule.rule_type == "group":
|
||||
rule_session_id = SessionUtils.calculate_session_id(rule.platform, group_id=str(rule.item_id))
|
||||
else:
|
||||
rule_session_id = SessionUtils.calculate_session_id(rule.platform, user_id=str(rule.item_id))
|
||||
if rule_session_id != session_id:
|
||||
continue # 不匹配的会话ID，跳过
|
||||
parsed_range = self._parse_range(rule.time)
|
||||
if not parsed_range:
|
||||
continue
|
||||
continue # 无法解析的时间范围，跳过
|
||||
start_min, end_min = parsed_range
|
||||
in_range: bool = False
|
||||
if start_min <= end_min:
|
||||
in_range = start_min <= now_min <= end_min
|
||||
else:
|
||||
else: # 跨天的时间范围
|
||||
in_range = now_min >= start_min or now_min <= end_min
|
||||
if in_range:
|
||||
return rule.value or 0.0
|
||||
# 再处理全局规则
|
||||
return rule.value or 0.0 # 如果规则生效但没有设置值，返回0.0
|
||||
|
||||
# 没有匹配到会话相关的规则，继续匹配全局规则
|
||||
for rule in global_config.chat.talk_value_rules:
|
||||
if rule.platform or rule.item_id:
|
||||
continue # 有指定表示特定，跳过
|
||||
parsed_range = TempMethodsHFC._parse_range(rule.time)
|
||||
continue # 只匹配全局规则
|
||||
parsed_range = self._parse_range(rule.time)
|
||||
if not parsed_range:
|
||||
continue
|
||||
continue # 无法解析的时间范围，跳过
|
||||
start_min, end_min = parsed_range
|
||||
in_range: bool = False
|
||||
if start_min <= end_min:
|
||||
in_range = start_min <= now_min <= end_min
|
||||
else:
|
||||
else: # 跨天的时间范围
|
||||
in_range = now_min >= start_min or now_min <= end_min
|
||||
if in_range:
|
||||
return rule.value or 0.0000001
|
||||
return result
|
||||
return rule.value or 0.0 # 如果规则生效但没有设置值，返回0.0
|
||||
return result # 如果没有任何规则生效，返回默认值
|
||||
|
||||
@staticmethod
|
||||
def _parse_range(range_str: str) -> Optional[tuple[int, int]]:
|
||||
def _parse_range(self, range_str: str) -> Optional[tuple[int, int]]:
|
||||
"""解析 "HH:MM-HH:MM" 到 (start_min, end_min)。"""
|
||||
try:
|
||||
start_str, end_str = [s.strip() for s in range_str.split("-")]
|
||||
|
||||
@@ -1,6 +1,8 @@
|
||||
import time
|
||||
from dataclasses import dataclass
|
||||
from typing import Optional, Dict, Any
|
||||
|
||||
import time
|
||||
|
||||
from src.config.config import global_config
|
||||
from src.common.logger import get_logger
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
@@ -11,6 +13,13 @@ from src.common.message_repository import count_messages
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
@dataclass
|
||||
class CyclePlanInfo:
|
||||
...
|
||||
|
||||
@dataclass
|
||||
class CycleActionInfo:
|
||||
...
|
||||
|
||||
class CycleDetail:
|
||||
"""循环信息记录类"""
|
||||
@@ -22,8 +31,8 @@ class CycleDetail:
|
||||
self.end_time: Optional[float] = None
|
||||
self.timers: Dict[str, float] = {}
|
||||
|
||||
self.loop_plan_info: Dict[str, Any] = {}
|
||||
self.loop_action_info: Dict[str, Any] = {}
|
||||
self.loop_plan_info: CyclePlanInfo = CyclePlanInfo()
|
||||
self.loop_action_info: CycleActionInfo = CycleActionInfo()
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""将循环信息转换为字典格式"""
|
||||
|
||||
@@ -1,10 +1,5 @@
|
||||
from src.chat.emoji_system.emoji_manager import emoji_manager
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
from src.chat.message_receive.storage import MessageStorage
|
||||
from src.chat.message_receive.chat_manager import chat_manager
|
||||
|
||||
|
||||
__all__ = [
|
||||
"get_chat_manager",
|
||||
"MessageStorage",
|
||||
"emoji_manager",
|
||||
]
|
||||
__all__ = ["chat_manager", "emoji_manager"]
|
||||
|
||||
@@ -1,21 +1,23 @@
|
||||
import traceback
|
||||
import os
|
||||
import re
|
||||
|
||||
from typing import Dict, Any, Optional
|
||||
from maim_message import UserInfo, Seg, GroupInfo
|
||||
from maim_message import MessageBase
|
||||
from typing import Dict, Any
|
||||
|
||||
|
||||
from src.common.logger import get_logger
|
||||
from src.config.config import global_config
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
from src.chat.message_receive.message import MessageRecv
|
||||
from src.chat.message_receive.storage import MessageStorage
|
||||
from src.common.utils.utils_message import MessageUtils
|
||||
from src.common.utils.utils_session import SessionUtils
|
||||
from src.chat.message_receive.message_old import MessageRecv
|
||||
from src.chat.heart_flow.heartflow_message_processor import HeartFCMessageReceiver
|
||||
from src.chat.brain_chat.PFC.pfc_manager import PFCManager
|
||||
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
|
||||
from src.plugin_system.core import component_registry, events_manager, global_announcement_manager
|
||||
from src.plugin_system.base import BaseCommand, EventType
|
||||
|
||||
from .message import SessionMessage
|
||||
from .chat_manager import chat_manager
|
||||
|
||||
# 定义日志配置
|
||||
|
||||
# 获取项目根目录（假设本文件在src/chat/message_receive/下，根目录为上上上级目录）
|
||||
@@ -25,50 +27,6 @@ PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../..
|
||||
logger = get_logger("chat")
|
||||
|
||||
|
||||
def _check_ban_words(text: str, userinfo: UserInfo, group_info: Optional[GroupInfo] = None) -> bool:
|
||||
"""检查消息是否包含过滤词
|
||||
|
||||
Args:
|
||||
text: 待检查的文本
|
||||
chat: 聊天对象
|
||||
userinfo: 用户信息
|
||||
|
||||
Returns:
|
||||
bool: 是否包含过滤词
|
||||
"""
|
||||
for word in global_config.message_receive.ban_words:
|
||||
if word in text:
|
||||
chat_name = group_info.group_name if group_info else "私聊"
|
||||
logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
|
||||
logger.info(f"[过滤词识别]消息中含有{word}，filtered")
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def _check_ban_regex(text: str, userinfo: UserInfo, group_info: Optional[GroupInfo] = None) -> bool:
|
||||
"""检查消息是否匹配过滤正则表达式
|
||||
|
||||
Args:
|
||||
text: 待检查的文本
|
||||
chat: 聊天对象
|
||||
userinfo: 用户信息
|
||||
|
||||
Returns:
|
||||
bool: 是否匹配过滤正则
|
||||
"""
|
||||
# 检查text是否为None或空字符串
|
||||
if text is None or not text:
|
||||
return False
|
||||
|
||||
for pattern in global_config.message_receive.ban_msgs_regex:
|
||||
if re.search(pattern, text):
|
||||
chat_name = group_info.group_name if group_info else "私聊"
|
||||
logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
|
||||
logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
class ChatBot:
|
||||
def __init__(self):
|
||||
self.bot = None # bot 实例引用
|
||||
@@ -100,9 +58,11 @@ class ChatBot:
|
||||
logger.error(f"创建PFC聊天失败: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
|
||||
async def _process_commands(self, message: MessageRecv):
|
||||
async def _process_commands(self, message: SessionMessage):
|
||||
# sourcery skip: use-named-expression
|
||||
"""使用新插件系统处理命令"""
|
||||
if not message.processed_plain_text:
|
||||
return False, None, True # 没有文本内容，继续处理消息
|
||||
try:
|
||||
text = message.processed_plain_text
|
||||
|
||||
@@ -112,11 +72,8 @@ class ChatBot:
|
||||
command_class, matched_groups, command_info = command_result
|
||||
plugin_name = command_info.plugin_name
|
||||
command_name = command_info.name
|
||||
if (
|
||||
message.chat_stream
|
||||
and message.chat_stream.stream_id
|
||||
and command_name
|
||||
in global_announcement_manager.get_disabled_chat_commands(message.chat_stream.stream_id)
|
||||
if message.session_id and command_name in global_announcement_manager.get_disabled_chat_commands(
|
||||
message.session_id
|
||||
):
|
||||
logger.info("用户禁用的命令，跳过处理")
|
||||
return False, None, True
|
||||
@@ -269,97 +226,115 @@ class ChatBot:
|
||||
)
|
||||
# print(message_data)
|
||||
# logger.debug(str(message_data))
|
||||
message = MessageRecv(message_data)
|
||||
maim_raw_message = MessageBase.from_dict(message_data)
|
||||
message = SessionMessage.from_maim_message(maim_raw_message)
|
||||
group_info = message.message_info.group_info
|
||||
user_info = message.message_info.user_info
|
||||
|
||||
continue_flag, modified_message = await events_manager.handle_mai_events(
|
||||
EventType.ON_MESSAGE_PRE_PROCESS, message
|
||||
session_id = SessionUtils.calculate_session_id(
|
||||
message.platform,
|
||||
user_id=message.message_info.user_info.user_id,
|
||||
group_id=group_info.group_id if group_info else None,
|
||||
)
|
||||
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)
|
||||
|
||||
if await self.handle_notice_message(message):
|
||||
pass
|
||||
message.session_id = session_id # 正确初始化session_id
|
||||
|
||||
# 处理消息内容，生成纯文本
|
||||
# TODO: 修复事件预处理部分
|
||||
# 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)
|
||||
|
||||
# TODO: notice消息处理
|
||||
# if await self.handle_notice_message(message):
|
||||
# pass
|
||||
|
||||
# 处理消息内容，识别表情包等二进制数据并转化为文本描述
|
||||
await message.process()
|
||||
|
||||
# 平台层的 @ 检测由底层 is_mentioned_bot_in_message 统一处理；此处不做用户名硬编码匹配
|
||||
|
||||
# 过滤检查
|
||||
if _check_ban_words(
|
||||
message.processed_plain_text,
|
||||
user_info, # type: ignore
|
||||
group_info,
|
||||
) or _check_ban_regex(
|
||||
message.raw_message, # type: ignore
|
||||
user_info, # type: ignore
|
||||
group_info,
|
||||
):
|
||||
text = message.processed_plain_text or ""
|
||||
is_banned, word = MessageUtils.check_ban_words(text)
|
||||
if is_banned:
|
||||
chat_name = group_info.group_name if group_info else "私聊"
|
||||
logger.info(f"[{chat_name}]{user_info.user_nickname}:{text}")
|
||||
logger.info(f"[过滤词识别]消息中含有{word}，filtered")
|
||||
return
|
||||
is_banned_regex, pattern = MessageUtils.check_ban_regex(text)
|
||||
if is_banned_regex:
|
||||
chat_name = group_info.group_name if group_info else "私聊"
|
||||
logger.info(f"[{chat_name}]{user_info.user_nickname}:{text}")
|
||||
logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
|
||||
return
|
||||
|
||||
get_chat_manager().register_message(message)
|
||||
chat_manager.register_message(message)
|
||||
|
||||
chat = await get_chat_manager().get_or_create_stream(
|
||||
platform=message.message_info.platform, # type: ignore
|
||||
user_info=user_info, # type: ignore
|
||||
group_info=group_info,
|
||||
)
|
||||
platform = message.platform
|
||||
user_id = user_info.user_id
|
||||
group_id = group_info.group_id if group_info else None
|
||||
_ = await chat_manager.get_or_create_session(platform, user_id, group_id) # 确保会话存在
|
||||
|
||||
message.update_chat_stream(chat)
|
||||
|
||||
# if await self.check_ban_content(message):
|
||||
# logger.warning(f"检测到消息中含有违法，色情，暴力，反动，敏感内容，消息内容：{message.processed_plain_text}，发送者：{message.message_info.user_info.user_nickname}")
|
||||
# return
|
||||
# message.update_chat_stream(chat)
|
||||
|
||||
# TODO: 在新命令系统完成后恢复这里
|
||||
# 命令处理 - 使用新插件系统检查并处理命令
|
||||
is_command, cmd_result, continue_process = await self._process_commands(message)
|
||||
# is_command, cmd_result, continue_process = await self._process_commands(message)
|
||||
|
||||
# 如果是命令且不需要继续处理，则直接返回
|
||||
if is_command and not continue_process:
|
||||
await MessageStorage.store_message(message, chat)
|
||||
logger.info(f"命令处理完成，跳过后续消息处理: {cmd_result}")
|
||||
return
|
||||
# if is_command and not continue_process:
|
||||
# await MessageStorage.store_message(message, chat)
|
||||
# logger.info(f"命令处理完成，跳过后续消息处理: {cmd_result}")
|
||||
# return
|
||||
|
||||
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
|
||||
# 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:
|
||||
template_group_name: Optional[str] = message.message_info.template_info.template_name # type: ignore
|
||||
template_items = message.message_info.template_info.template_items
|
||||
async with global_prompt_manager.async_message_scope(template_group_name):
|
||||
if isinstance(template_items, dict):
|
||||
for k in template_items.keys():
|
||||
await Prompt.create_async(template_items[k], k)
|
||||
logger.debug(f"注册{template_items[k]},{k}")
|
||||
else:
|
||||
template_group_name = None
|
||||
# # 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:
|
||||
# template_group_name: Optional[str] = message.message_info.template_info.template_name # type: ignore
|
||||
# template_items = message.message_info.template_info.template_items
|
||||
# async with global_prompt_manager.async_message_scope(template_group_name):
|
||||
# if isinstance(template_items, dict):
|
||||
# for k in template_items.keys():
|
||||
# await Prompt.create_async(template_items[k], k)
|
||||
# logger.debug(f"注册{template_items[k]},{k}")
|
||||
# else:
|
||||
# template_group_name = None
|
||||
|
||||
# async def preprocess():
|
||||
# # 根据聊天类型路由消息
|
||||
# if group_info is None:
|
||||
# # 私聊消息 -> PFC系统
|
||||
# logger.debug("[私聊]检测到私聊消息，路由到PFC系统")
|
||||
# await MessageStorage.store_message(message, chat)
|
||||
# await self._create_pfc_chat(message)
|
||||
# else:
|
||||
# # 群聊消息 -> HeartFlow系统
|
||||
# logger.debug("[群聊]检测到群聊消息，路由到HeartFlow系统")
|
||||
# await self.heartflow_message_receiver.process_message(message)
|
||||
|
||||
# if template_group_name:
|
||||
# async with global_prompt_manager.async_message_scope(template_group_name):
|
||||
# await preprocess()
|
||||
# else:
|
||||
# await preprocess()
|
||||
async def preprocess():
|
||||
# 根据聊天类型路由消息
|
||||
if group_info is None:
|
||||
# 私聊消息 -> PFC系统
|
||||
logger.debug("[私聊]检测到私聊消息，路由到PFC系统")
|
||||
await MessageStorage.store_message(message, chat)
|
||||
MessageUtils.store_message_to_db(message) # 存储消息到数据库
|
||||
await self._create_pfc_chat(message)
|
||||
else:
|
||||
# 群聊消息 -> HeartFlow系统
|
||||
logger.debug("[群聊]检测到群聊消息，路由到HeartFlow系统")
|
||||
await self.heartflow_message_receiver.process_message(message)
|
||||
|
||||
if template_group_name:
|
||||
async with global_prompt_manager.async_message_scope(template_group_name):
|
||||
await preprocess()
|
||||
else:
|
||||
await preprocess()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"预处理消息失败: {e}")
|
||||
traceback.print_exc()
|
||||
|
||||
Reference in New Issue
Block a user