diff --git a/src/chat/brain_chat/PFC/action_planner.py b/src/chat/brain_chat/PFC/action_planner.py index 7c8bbd79..94f68585 100644 --- a/src/chat/brain_chat/PFC/action_planner.py +++ b/src/chat/brain_chat/PFC/action_planner.py @@ -1,14 +1,16 @@ import time from typing import Tuple, Optional # 增加了 Optional + from src.common.logger import get_logger from src.llm_models.utils_model import LLMRequest from src.config.config import global_config, model_config import random from .chat_observer import ChatObserver from .pfc_utils import get_items_from_json -from .observation_info import ObservationInfo, dict_to_database_message +from src.services.message_service import build_readable_messages + +from .observation_info import ObservationInfo, dict_to_session_message from .conversation_info import ConversationInfo -from src.chat.utils.chat_message_builder import build_readable_messages logger = get_logger("pfc_action_planner") @@ -271,19 +273,17 @@ class ActionPlanner: # 获取聊天历史记录 (chat_history_text) try: if hasattr(observation_info, "chat_history") and observation_info.chat_history: - chat_history_text = observation_info.chat_history_str - if not chat_history_text: - chat_history_text = "还没有聊天记录。\n" + chat_history_text = observation_info.chat_history_str or "还没有聊天记录。\n" else: chat_history_text = "还没有聊天记录。\n" if hasattr(observation_info, "new_messages_count") and observation_info.new_messages_count > 0: if hasattr(observation_info, "unprocessed_messages") and observation_info.unprocessed_messages: new_messages_list = observation_info.unprocessed_messages - # Convert dict format to DatabaseMessages objects - db_messages = [dict_to_database_message(m) for m in new_messages_list] + # Convert dict format to SessionMessage objects. + session_messages = [dict_to_session_message(m) for m in new_messages_list] new_messages_str = build_readable_messages( - db_messages, + session_messages, replace_bot_name=True, timestamp_mode="relative", read_mark=0.0, diff --git a/src/chat/brain_chat/PFC/conversation.py b/src/chat/brain_chat/PFC/conversation.py index 119c4ecd..1e1e89b1 100644 --- a/src/chat/brain_chat/PFC/conversation.py +++ b/src/chat/brain_chat/PFC/conversation.py @@ -1,13 +1,14 @@ -import time import asyncio import datetime +import time + +from typing import Dict, Any, Optional + +from src.common.data_models.mai_message_data_model import MaiMessage +from src.services.message_service import build_readable_messages, get_messages_before_time_in_chat # from .message_storage import MongoDBMessageStorage -from src.chat.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat - # from src.config.config import global_config -from typing import Dict, Any, Optional -from src.common.data_models.mai_message_data_model import MaiMessage from .pfc_types import ConversationState from .pfc import ChatObserver, GoalAnalyzer from .message_sender import DirectMessageSender @@ -83,7 +84,7 @@ class Conversation: raise try: logger.info(f"[私聊][{self.private_name}]为 {self.stream_id} 加载初始聊天记录...") - initial_messages = get_raw_msg_before_timestamp_with_chat( # + initial_messages = get_messages_before_time_in_chat( chat_id=self.stream_id, timestamp=time.time(), limit=30, # 加载最近30条作为初始上下文，可以调整 @@ -95,22 +96,23 @@ class Conversation: read_mark=0.0, ) if initial_messages: - # 将 DatabaseMessages 列表转换为 PFC 期望的 dict 格式（保持嵌套结构） + # 将 SessionMessage 列表转换为 PFC 期望的 dict 格式（保持嵌套结构） initial_messages_dict: list[dict] = [] for msg in initial_messages: + user_info = msg.message_info.user_info msg_dict = { "message_id": msg.message_id, - "time": msg.time, - "chat_id": msg.chat_id, + "time": msg.timestamp.timestamp(), + "chat_id": msg.session_id, "processed_plain_text": msg.processed_plain_text, "display_message": msg.display_message, "is_mentioned": msg.is_mentioned, "is_command": msg.is_command, "user_info": { - "user_id": msg.user_info.user_id if msg.user_info else "", - "user_nickname": msg.user_info.user_nickname if msg.user_info else "", - "user_cardname": msg.user_info.user_cardname if msg.user_info else None, - "platform": msg.user_info.platform if msg.user_info else "", + "user_id": user_info.user_id, + "user_nickname": user_info.user_nickname, + "user_cardname": user_info.user_cardname, + "platform": msg.platform, }, } initial_messages_dict.append(msg_dict) diff --git a/src/chat/brain_chat/PFC/observation_info.py b/src/chat/brain_chat/PFC/observation_info.py index d04d1c0a..3d3b235a 100644 --- a/src/chat/brain_chat/PFC/observation_info.py +++ b/src/chat/brain_chat/PFC/observation_info.py @@ -1,40 +1,52 @@ -from typing import List, Optional, Dict, Any, Set +from datetime import datetime +from typing import Any, Dict, List, Optional, Set + from maim_message import UserInfo import time + +from src.chat.message_receive.message import SessionMessage from src.common.logger import get_logger +from src.common.data_models.mai_message_data_model import MessageInfo, UserInfo as MaiUserInfo +from src.services.message_service import build_readable_messages + from .chat_observer import ChatObserver from .chat_states import NotificationHandler, NotificationType, Notification -from src.chat.utils.chat_message_builder import build_readable_messages -from src.common.data_models.database_data_model import DatabaseMessages import traceback # 导入 traceback 用于调试 logger = get_logger("observation_info") -def dict_to_database_message(msg_dict: Dict[str, Any]) -> DatabaseMessages: - """Convert PFC dict format to DatabaseMessages object +def dict_to_session_message(msg_dict: Dict[str, Any]) -> SessionMessage: + """Convert PFC dict format to SessionMessage object. Args: msg_dict: Message in PFC dict format with nested user_info Returns: - DatabaseMessages object compatible with build_readable_messages() + SessionMessage object compatible with build_readable_messages() """ user_info_dict: Dict[str, Any] = msg_dict.get("user_info", {}) - - return DatabaseMessages( + timestamp = msg_dict.get("time", 0.0) + platform = user_info_dict.get("platform", "") + message = SessionMessage( message_id=msg_dict.get("message_id", ""), - time=msg_dict.get("time", 0.0), - chat_id=msg_dict.get("chat_id", ""), - processed_plain_text=msg_dict.get("processed_plain_text", ""), - display_message=msg_dict.get("display_message", ""), - is_mentioned=msg_dict.get("is_mentioned", False), - is_command=msg_dict.get("is_command", False), - user_id=user_info_dict.get("user_id", ""), - user_nickname=user_info_dict.get("user_nickname", ""), - user_cardname=user_info_dict.get("user_cardname"), - user_platform=user_info_dict.get("platform", ""), + timestamp=datetime.fromtimestamp(timestamp), + platform=platform, ) + message.message_info = MessageInfo( + user_info=MaiUserInfo( + user_id=user_info_dict.get("user_id", ""), + user_nickname=user_info_dict.get("user_nickname", ""), + user_cardname=user_info_dict.get("user_cardname"), + ) + ) + message.session_id = msg_dict.get("chat_id", "") + message.processed_plain_text = msg_dict.get("processed_plain_text", "") + message.display_message = msg_dict.get("display_message", "") + message.is_mentioned = msg_dict.get("is_mentioned", False) + message.is_command = msg_dict.get("is_command", False) + message.initialized = True + return message class ObservationInfoHandler(NotificationHandler): @@ -393,10 +405,10 @@ class ObservationInfo: # 更新历史记录字符串 (只使用最近一部分生成，例如20条) history_slice_for_str = self.chat_history[-20:] try: - # Convert dict format to DatabaseMessages objects - db_messages = [dict_to_database_message(m) for m in history_slice_for_str] + # Convert dict format to SessionMessage objects. + session_messages = [dict_to_session_message(m) for m in history_slice_for_str] self.chat_history_str = build_readable_messages( - db_messages, + session_messages, replace_bot_name=True, timestamp_mode="relative", read_mark=0.0, # read_mark 可能需要根据逻辑调整 diff --git a/src/chat/brain_chat/PFC/pfc.py b/src/chat/brain_chat/PFC/pfc.py index 7de6589b..5d051716 100644 --- a/src/chat/brain_chat/PFC/pfc.py +++ b/src/chat/brain_chat/PFC/pfc.py @@ -6,8 +6,9 @@ import random from .chat_observer import ChatObserver from .pfc_utils import get_items_from_json from .conversation_info import ConversationInfo -from .observation_info import ObservationInfo, dict_to_database_message -from src.chat.utils.chat_message_builder import build_readable_messages +from src.services.message_service import build_readable_messages + +from .observation_info import ObservationInfo, dict_to_session_message from rich.traceback import install install(extra_lines=3) @@ -103,9 +104,9 @@ class GoalAnalyzer: if observation_info.new_messages_count > 0: new_messages_list = observation_info.unprocessed_messages - db_messages = [dict_to_database_message(m) for m in new_messages_list] + session_messages = [dict_to_session_message(m) for m in new_messages_list] new_messages_str = build_readable_messages( - db_messages, + session_messages, replace_bot_name=True, timestamp_mode="relative", read_mark=0.0, @@ -238,9 +239,9 @@ class GoalAnalyzer: async def analyze_conversation(self, goal, reasoning): messages = self.chat_observer.get_cached_messages() - db_messages = [dict_to_database_message(m) for m in messages] + session_messages = [dict_to_session_message(m) for m in messages] chat_history_text = build_readable_messages( - db_messages, + session_messages, replace_bot_name=True, timestamp_mode="relative", read_mark=0.0, diff --git a/src/chat/brain_chat/PFC/reply_generator.py b/src/chat/brain_chat/PFC/reply_generator.py index 3636fe72..95853e26 100644 --- a/src/chat/brain_chat/PFC/reply_generator.py +++ b/src/chat/brain_chat/PFC/reply_generator.py @@ -5,9 +5,10 @@ from src.config.config import global_config, model_config import random from .chat_observer import ChatObserver from .reply_checker import ReplyChecker -from .observation_info import ObservationInfo, dict_to_database_message +from src.services.message_service import build_readable_messages + +from .observation_info import ObservationInfo, dict_to_session_message from .conversation_info import ConversationInfo -from src.chat.utils.chat_message_builder import build_readable_messages logger = get_logger("reply_generator") @@ -163,7 +164,7 @@ class ReplyGenerator: knowledge = knowledge_item.get("knowledge", "无知识内容") source = knowledge_item.get("source", "未知来源") # 只取知识内容的前 2000 个字 - knowledge_snippet = knowledge[:2000] + "..." if len(knowledge) > 2000 else knowledge + knowledge_snippet = f"{knowledge[:2000]}..." if len(knowledge) > 2000 else knowledge knowledge_info_str += ( f"{i + 1}. 关于 '{query}' (来源: {source}): {knowledge_snippet}\n" # 格式微调，更简洁 ) @@ -186,9 +187,9 @@ class ReplyGenerator: chat_history_text = observation_info.chat_history_str if observation_info.new_messages_count > 0 and observation_info.unprocessed_messages: new_messages_list = observation_info.unprocessed_messages - db_messages = [dict_to_database_message(m) for m in new_messages_list] + session_messages = [dict_to_session_message(m) for m in new_messages_list] new_messages_str = build_readable_messages( - db_messages, + session_messages, replace_bot_name=True, timestamp_mode="relative", read_mark=0.0, diff --git a/src/memory_system/chat_history_summarizer.py b/src/memory_system/chat_history_summarizer.py index 9a46f340..b984c66d 100644 --- a/src/memory_system/chat_history_summarizer.py +++ b/src/memory_system/chat_history_summarizer.py @@ -14,12 +14,11 @@ from typing import Any, Dict, List, Optional, Set from dataclasses import dataclass, field from json_repair import repair_json +from src.chat.message_receive.message import SessionMessage from src.common.logger import get_logger -from src.common.data_models.database_data_model import DatabaseMessages from src.config.config import model_config, global_config from src.llm_models.utils_model import LLMRequest from src.services import message_service as message_api -from src.chat.utils.chat_message_builder import build_readable_messages from src.chat.utils.utils import is_bot_self from src.person_info.person_info import Person from src.chat.message_receive.chat_manager import chat_manager as _chat_manager @@ -34,7 +33,7 @@ HIPPO_CACHE_DIR = Path(__file__).resolve().parents[2] / "data" / "hippo_memorize class MessageBatch: """消息批次（用于触发话题检查的原始消息累积）""" - messages: List[DatabaseMessages] + messages: List[SessionMessage] start_time: float end_time: float @@ -101,7 +100,7 @@ class ChatHistorySummarizer: def _get_chat_display_name(self) -> str: """获取聊天显示名称""" try: - chat_name = _chat_manager.get_session_name(self.chat_id) + chat_name = _chat_manager.get_session_name(self.session_id) if chat_name: return chat_name # 如果获取失败，使用简化的chat_id显示 @@ -268,7 +267,7 @@ class ChatHistorySummarizer: # 创建新批次 self.current_batch = MessageBatch( messages=new_messages, - start_time=new_messages[0].time if new_messages else current_time, + start_time=new_messages[0].timestamp.timestamp() if new_messages else current_time, end_time=current_time, ) logger.debug(f"{self.log_prefix} 新建聊天检查批次: {len(new_messages)} 条消息") @@ -340,7 +339,7 @@ class ChatHistorySummarizer: self.last_topic_check_time = current_time self._persist_topic_cache() - async def _run_topic_check_and_update_cache(self, messages: List[DatabaseMessages]): + async def _run_topic_check_and_update_cache(self, messages: List[SessionMessage]): """ 执行一次“话题检查”： 1. 首先确认这段消息里是否有 Bot 发言，没有则直接丢弃本次批次； @@ -355,8 +354,8 @@ class ChatHistorySummarizer: if not messages: return - start_time = messages[0].time - end_time = messages[-1].time + start_time = messages[0].timestamp.timestamp() + end_time = messages[-1].timestamp.timestamp() logger.info( f"{self.log_prefix} 开始话题检查 | 消息数: {len(messages)} | 时间范围: {start_time:.2f} - {end_time:.2f}" @@ -365,13 +364,9 @@ class ChatHistorySummarizer: # 1. 检查当前批次内是否有 bot 发言（只检查当前批次，不往前推） # 原因：我们要记录的是 bot 参与过的对话片段，如果当前批次内 bot 没有发言， # 说明 bot 没有参与这段对话，不应该记录 - has_bot_message = False - - for msg in messages: - # 使用统一的 is_bot_self 函数判断是否是机器人自己（支持多平台，包括 WebUI） - if is_bot_self(msg.user_info.platform, msg.user_info.user_id): - has_bot_message = True - break + has_bot_message = any( + is_bot_self(msg.platform, msg.message_info.user_info.user_id) for msg in messages + ) if not has_bot_message: logger.info( @@ -575,7 +570,7 @@ class ChatHistorySummarizer: return topic_mapping def _build_numbered_messages_for_llm( - self, messages: List[DatabaseMessages] + self, messages: List[SessionMessage] ) -> tuple[List[str], Dict[int, str], Dict[int, str], Dict[int, Set[str]]]: """ 将消息转为带编号的字符串，供 LLM 选择使用。 @@ -594,7 +589,7 @@ class ChatHistorySummarizer: for idx, msg in enumerate(messages, start=1): # 使用 build_readable_messages 生成可读文本 try: - text = build_readable_messages( + text = message_api.build_readable_messages( messages=[msg], replace_bot_name=True, timestamp_mode="normal_no_YMD", @@ -609,12 +604,8 @@ class ChatHistorySummarizer: # 获取发言人昵称 participants: Set[str] = set() try: - platform = ( - getattr(msg, "user_platform", None) - or (msg.user_info.platform if msg.user_info else None) - or msg.chat_info.platform - ) - user_id = msg.user_info.user_id if msg.user_info else None + platform = msg.platform + user_id = msg.message_info.user_info.user_id if platform and user_id: person = Person(platform=platform, user_id=user_id) if person.person_name: