From 7bdd394bf01a8120bd8d67233b3cd5b62f8cca30 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=A2=A8=E6=A2=93=E6=9F=92?= <1787882683@qq.com> Date: Fri, 16 Jan 2026 03:36:25 +0800 Subject: [PATCH] =?UTF-8?q?=E5=B0=86PFC=E5=8A=A0=E5=9B=9E=E6=9D=A5?= =?UTF-8?q?=EF=BC=8C=E4=BF=AE=E5=A4=8D=E4=B8=80=E5=A4=A7=E5=A0=86PFC?= =?UTF-8?q?=E7=9A=84=E7=A5=9E=E7=A7=98=E6=8A=A5=E9=94=99?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/chat/brain_chat/PFC/action_planner.py | 40 +++--- src/chat/brain_chat/PFC/chat_observer.py | 98 ++++++++------- src/chat/brain_chat/PFC/conversation.py | 43 +++++-- src/chat/brain_chat/PFC/conversation_info.py | 8 +- src/chat/brain_chat/PFC/message_sender.py | 8 +- src/chat/brain_chat/PFC/message_storage.py | 119 ------------------ src/chat/brain_chat/PFC/observation_info.py | 38 +++++- src/chat/brain_chat/PFC/pfc.py | 30 ++--- .../brain_chat/PFC/pfc_KnowledgeFetcher.py | 65 +++++----- src/chat/brain_chat/PFC/pfc_manager.py | 4 +- src/chat/brain_chat/PFC/pfc_utils.py | 4 +- src/chat/brain_chat/PFC/reply_checker.py | 34 +++-- src/chat/brain_chat/PFC/reply_generator.py | 18 ++- src/chat/brain_chat/PFC/waiter.py | 6 +- src/chat/message_receive/bot.py | 30 ++++- src/config/config.py | 38 ++++++ src/llm_models/utils_model.py | 6 +- 17 files changed, 303 insertions(+), 286 deletions(-) delete mode 100644 src/chat/brain_chat/PFC/message_storage.py diff --git a/src/chat/brain_chat/PFC/action_planner.py b/src/chat/brain_chat/PFC/action_planner.py index 3b71d2b9..13b76f8b 100644 --- a/src/chat/brain_chat/PFC/action_planner.py +++ b/src/chat/brain_chat/PFC/action_planner.py @@ -1,12 +1,12 @@ import time -from typing import Tuple, Optional # 增加了 Optional +from typing import Tuple, Optional, Dict, Any # 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 +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 +from .observation_info import ObservationInfo, dict_to_database_message from .conversation_info import ConversationInfo from src.chat.utils.chat_message_builder import build_readable_messages @@ -108,13 +108,11 @@ class ActionPlanner: def __init__(self, stream_id: str, private_name: str): self.llm = LLMRequest( - model=global_config.llm_PFC_action_planner, - temperature=global_config.llm_PFC_action_planner["temp"], - max_tokens=1500, + model_set=model_config.model_task_config.planner, request_type="action_planning", ) self.personality_info = self._get_personality_prompt() - self.name = global_config.BOT_NICKNAME + self.name = global_config.bot.nickname self.private_name = private_name self.chat_observer = ChatObserver.get_instance(stream_id, private_name) # self.action_planner_info = ActionPlannerInfo() # 移除未使用的变量 @@ -131,7 +129,7 @@ class ActionPlanner: ): prompt_personality = random.choice(global_config.personality.states) - bot_name = global_config.BOT_NICKNAME + bot_name = global_config.bot.nickname return f"你的名字是{bot_name},你{prompt_personality};" # 修改 plan 方法签名，增加 last_successful_reply_action 参数 @@ -152,13 +150,13 @@ class ActionPlanner: Tuple[str, str]: (行动类型, 行动原因) """ # --- 获取 Bot 上次发言时间信息 --- - # (这部分逻辑不变) time_since_last_bot_message_info = "" try: - bot_id = str(global_config.BOT_QQ) - if hasattr(observation_info, "chat_history") and observation_info.chat_history: - for i in range(len(observation_info.chat_history) - 1, -1, -1): - msg = observation_info.chat_history[i] + bot_id = str(global_config.bot.qq_account) + chat_history = getattr(observation_info, "chat_history", None) + if chat_history and len(chat_history) > 0: + for i in range(len(chat_history) - 1, -1, -1): + msg = chat_history[i] if not isinstance(msg, dict): continue sender_info = msg.get("user_info", {}) @@ -173,14 +171,11 @@ class ActionPlanner: break else: logger.debug( - f"[私聊][{self.private_name}]Observation info chat history is empty or not available for bot time check." + f"[私聊][{self.private_name}]聊天历史为空或尚未加载，跳过 Bot 发言时间检查。" ) - except AttributeError: - logger.warning( - f"[私聊][{self.private_name}]ObservationInfo object might not have chat_history attribute yet for bot time check." - ) except Exception as e: - logger.warning(f"[私聊][{self.private_name}]获取 Bot 上次发言时间时出错: {e}") + logger.debug(f"[私聊][{self.private_name}]获取 Bot 上次发言时间时出错: {e}") + # --- 获取超时提示信息 --- # (这部分逻辑不变) @@ -288,10 +283,11 @@ class ActionPlanner: 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 - new_messages_str = await build_readable_messages( - new_messages_list, + # Convert dict format to DatabaseMessages objects + db_messages = [dict_to_database_message(m) for m in new_messages_list] + new_messages_str = build_readable_messages( + db_messages, replace_bot_name=True, - merge_messages=False, timestamp_mode="relative", read_mark=0.0, ) diff --git a/src/chat/brain_chat/PFC/chat_observer.py b/src/chat/brain_chat/PFC/chat_observer.py index 22cbf27d..91df8333 100644 --- a/src/chat/brain_chat/PFC/chat_observer.py +++ b/src/chat/brain_chat/PFC/chat_observer.py @@ -2,16 +2,43 @@ import time import asyncio import traceback from typing import Optional, Dict, Any, List -from src.common.logger import get_module_logger +from src.common.logger import get_logger +from src.common.database.database_model import Messages from maim_message import UserInfo -from ...config.config import global_config +from src.config.config import global_config from .chat_states import NotificationManager, create_new_message_notification, create_cold_chat_notification -from .message_storage import MongoDBMessageStorage from rich.traceback import install install(extra_lines=3) -logger = get_module_logger("chat_observer") +logger = get_logger("chat_observer") + + +def _message_to_dict(message: Messages) -> Dict[str, Any]: + """Convert Peewee Message model to dict for PFC compatibility + + Args: + message: Peewee Messages model instance + + Returns: + Dict[str, Any]: Message dictionary + """ + return { + "message_id": message.message_id, + "time": message.time, + "chat_id": message.chat_id, + "user_id": message.user_id, + "user_nickname": message.user_nickname, + "processed_plain_text": message.processed_plain_text, + "display_message": message.display_message, + "is_mentioned": message.is_mentioned, + "is_command": message.is_command, + # Add user_info dict for compatibility with existing code + "user_info": { + "user_id": message.user_id, + "user_nickname": message.user_nickname, + } + } class ChatObserver: @@ -49,12 +76,8 @@ class ChatObserver: self.stream_id = stream_id self.private_name = private_name - self.message_storage = MongoDBMessageStorage() - # self.last_user_speak_time: Optional[float] = None # 对方上次发言时间 - # self.last_bot_speak_time: Optional[float] = None # 机器人上次发言时间 - # self.last_check_time: float = time.time() # 上次查看聊天记录时间 - self.last_message_read: Optional[Dict[str, Any]] = None # 最后读取的消息ID + self.last_message_read: Optional[Dict[str, Any]] = None self.last_message_time: float = time.time() self.waiting_start_time: float = time.time() # 等待开始时间，初始化为当前时间 @@ -86,7 +109,10 @@ class ChatObserver: """ logger.debug(f"[私聊][{self.private_name}]检查距离上一次观察之后是否有了新消息: {self.last_check_time}") - new_message_exists = await self.message_storage.has_new_messages(self.stream_id, self.last_check_time) + new_message_exists = Messages.select().where( + (Messages.chat_id == self.stream_id) & + (Messages.time > self.last_check_time) + ).exists() if new_message_exists: logger.debug(f"[私聊][{self.private_name}]发现新消息") @@ -157,41 +183,7 @@ class ChatObserver: ) return has_new - def get_message_history( - self, - start_time: Optional[float] = None, - end_time: Optional[float] = None, - limit: Optional[int] = None, - user_id: Optional[str] = None, - ) -> List[Dict[str, Any]]: - """获取消息历史 - Args: - start_time: 开始时间戳 - end_time: 结束时间戳 - limit: 限制返回消息数量 - user_id: 指定用户ID - - Returns: - List[Dict[str, Any]]: 消息列表 - """ - filtered_messages = self.message_history - - if start_time is not None: - filtered_messages = [m for m in filtered_messages if m["time"] >= start_time] - - if end_time is not None: - filtered_messages = [m for m in filtered_messages if m["time"] <= end_time] - - if user_id is not None: - filtered_messages = [ - m for m in filtered_messages if UserInfo.from_dict(m.get("user_info", {})).user_id == user_id - ] - - if limit is not None: - filtered_messages = filtered_messages[-limit:] - - return filtered_messages async def _fetch_new_messages(self) -> List[Dict[str, Any]]: """获取新消息 @@ -199,7 +191,12 @@ class ChatObserver: Returns: List[Dict[str, Any]]: 新消息列表 """ - new_messages = await self.message_storage.get_messages_after(self.stream_id, self.last_message_time) + query = Messages.select().where( + (Messages.chat_id == self.stream_id) & + (Messages.time > self.last_message_time) + ).order_by(Messages.time.asc()) + + new_messages = [_message_to_dict(msg) for msg in query] if new_messages: self.last_message_read = new_messages[-1] @@ -218,7 +215,14 @@ class ChatObserver: Returns: List[Dict[str, Any]]: 最多5条消息 """ - new_messages = await self.message_storage.get_messages_before(self.stream_id, time_point) + query = Messages.select().where( + (Messages.chat_id == self.stream_id) & + (Messages.time < time_point) + ).order_by(Messages.time.desc()).limit(5) + + messages = list(query) + messages.reverse() # 需要按时间正序排列 + new_messages = [_message_to_dict(msg) for msg in messages] if new_messages: self.last_message_read = new_messages[-1]["message_id"] @@ -319,7 +323,7 @@ class ChatObserver: for msg in messages: try: user_info = UserInfo.from_dict(msg.get("user_info", {})) - if user_info.user_id == global_config.BOT_QQ: + if user_info.user_id == global_config.bot.qq_account: self.update_bot_speak_time(msg["time"]) else: self.update_user_speak_time(msg["time"]) diff --git a/src/chat/brain_chat/PFC/conversation.py b/src/chat/brain_chat/PFC/conversation.py index 8553ee96..1bab27fb 100644 --- a/src/chat/brain_chat/PFC/conversation.py +++ b/src/chat/brain_chat/PFC/conversation.py @@ -4,6 +4,7 @@ import datetime # 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.common.data_models import transform_class_to_dict # from src.config.config import global_config from typing import Dict, Any, Optional @@ -89,33 +90,53 @@ class Conversation: timestamp=time.time(), limit=30, # 加载最近30条作为初始上下文，可以调整 ) - chat_talking_prompt = await build_readable_messages( + chat_talking_prompt = build_readable_messages( initial_messages, replace_bot_name=True, - merge_messages=False, timestamp_mode="relative", 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） + initial_messages_dict: list[dict] = [] + for msg in initial_messages: + msg_dict = { + "message_id": msg.message_id, + "time": msg.time, + "chat_id": msg.chat_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 "", + } + } + initial_messages_dict.append(msg_dict) + # 将加载的消息填充到 ObservationInfo 的 chat_history - self.observation_info.chat_history = initial_messages + self.observation_info.chat_history = initial_messages_dict self.observation_info.chat_history_str = chat_talking_prompt + "\n" - self.observation_info.chat_history_count = len(initial_messages) + self.observation_info.chat_history_count = len(initial_messages_dict) # 更新 ObservationInfo 中的时间戳等信息 - last_msg = initial_messages[-1] - self.observation_info.last_message_time = last_msg.get("time") - last_user_info = UserInfo.from_dict(last_msg.get("user_info", {})) + last_msg_dict: dict = initial_messages_dict[-1] + self.observation_info.last_message_time = last_msg_dict.get("time") + last_user_info = UserInfo.from_dict(last_msg_dict.get("user_info", {})) self.observation_info.last_message_sender = last_user_info.user_id - self.observation_info.last_message_content = last_msg.get("processed_plain_text", "") + self.observation_info.last_message_content = last_msg_dict.get("processed_plain_text", "") logger.info( - f"[私聊][{self.private_name}]成功加载 {len(initial_messages)} 条初始聊天记录。最后一条消息时间: {self.observation_info.last_message_time}" + f"[私聊][{self.private_name}]成功加载 {len(initial_messages_dict)} 条初始聊天记录。最后一条消息时间: {self.observation_info.last_message_time}" ) # 让 ChatObserver 从加载的最后一条消息之后开始同步 - self.chat_observer.last_message_time = self.observation_info.last_message_time - self.chat_observer.last_message_read = last_msg # 更新 observer 的最后读取记录 + if self.observation_info.last_message_time: + self.chat_observer.last_message_time = self.observation_info.last_message_time + self.chat_observer.last_message_read = last_msg_dict # 更新 observer 的最后读取记录 else: logger.info(f"[私聊][{self.private_name}]没有找到初始聊天记录。") diff --git a/src/chat/brain_chat/PFC/conversation_info.py b/src/chat/brain_chat/PFC/conversation_info.py index 04524b69..d9afd6ac 100644 --- a/src/chat/brain_chat/PFC/conversation_info.py +++ b/src/chat/brain_chat/PFC/conversation_info.py @@ -3,8 +3,8 @@ from typing import Optional class ConversationInfo: def __init__(self): - self.done_action = [] - self.goal_list = [] - self.knowledge_list = [] - self.memory_list = [] + self.done_action: list = [] + self.goal_list: list = [] + self.knowledge_list: list = [] + self.memory_list: list = [] self.last_successful_reply_action: Optional[str] = None diff --git a/src/chat/brain_chat/PFC/message_sender.py b/src/chat/brain_chat/PFC/message_sender.py index 0e2b96cb..8febe763 100644 --- a/src/chat/brain_chat/PFC/message_sender.py +++ b/src/chat/brain_chat/PFC/message_sender.py @@ -1,6 +1,6 @@ import time from typing import Optional -from src.common.logger import get_module_logger +from src.common.logger import get_logger from src.chat.message_receive.chat_stream import ChatStream from src.chat.message_receive.message import Message, MessageSending from maim_message import UserInfo, Seg @@ -11,7 +11,7 @@ from rich.traceback import install install(extra_lines=3) -logger = get_module_logger("message_sender") +logger = get_logger("message_sender") class DirectMessageSender: @@ -40,8 +40,8 @@ class DirectMessageSender: # 获取麦麦的信息 bot_user_info = UserInfo( - user_id=global_config.BOT_QQ, - user_nickname=global_config.BOT_NICKNAME, + user_id=global_config.bot.qq_account, + user_nickname=global_config.bot.nickname, platform=chat_stream.platform, ) diff --git a/src/chat/brain_chat/PFC/message_storage.py b/src/chat/brain_chat/PFC/message_storage.py deleted file mode 100644 index cd6a01e3..00000000 --- a/src/chat/brain_chat/PFC/message_storage.py +++ /dev/null @@ -1,119 +0,0 @@ -from abc import ABC, abstractmethod -from typing import List, Dict, Any -from src.common.database import db - - -class MessageStorage(ABC): - """消息存储接口""" - - @abstractmethod - async def get_messages_after(self, chat_id: str, message: Dict[str, Any]) -> List[Dict[str, Any]]: - """获取指定消息ID之后的所有消息 - - Args: - chat_id: 聊天ID - message: 消息 - - Returns: - List[Dict[str, Any]]: 消息列表 - """ - pass - - @abstractmethod - async def get_messages_before(self, chat_id: str, time_point: float, limit: int = 5) -> List[Dict[str, Any]]: - """获取指定时间点之前的消息 - - Args: - chat_id: 聊天ID - time_point: 时间戳 - limit: 最大消息数量 - - Returns: - List[Dict[str, Any]]: 消息列表 - """ - pass - - @abstractmethod - async def has_new_messages(self, chat_id: str, after_time: float) -> bool: - """检查是否有新消息 - - Args: - chat_id: 聊天ID - after_time: 时间戳 - - Returns: - bool: 是否有新消息 - """ - pass - - -class MongoDBMessageStorage(MessageStorage): - """MongoDB消息存储实现""" - - async def get_messages_after(self, chat_id: str, message_time: float) -> List[Dict[str, Any]]: - query = {"chat_id": chat_id, "time": {"$gt": message_time}} - # print(f"storage_check_message: {message_time}") - - return list(db.messages.find(query).sort("time", 1)) - - async def get_messages_before(self, chat_id: str, time_point: float, limit: int = 5) -> List[Dict[str, Any]]: - query = {"chat_id": chat_id, "time": {"$lt": time_point}} - - messages = list(db.messages.find(query).sort("time", -1).limit(limit)) - - # 将消息按时间正序排列 - messages.reverse() - return messages - - async def has_new_messages(self, chat_id: str, after_time: float) -> bool: - query = {"chat_id": chat_id, "time": {"$gt": after_time}} - - return db.messages.find_one(query) is not None - - -# # 创建一个内存消息存储实现，用于测试 -# class InMemoryMessageStorage(MessageStorage): -# """内存消息存储实现，主要用于测试""" - -# def __init__(self): -# self.messages: Dict[str, List[Dict[str, Any]]] = {} - -# async def get_messages_after(self, chat_id: str, message_id: Optional[str] = None) -> List[Dict[str, Any]]: -# if chat_id not in self.messages: -# return [] - -# messages = self.messages[chat_id] -# if not message_id: -# return messages - -# # 找到message_id的索引 -# try: -# index = next(i for i, m in enumerate(messages) if m["message_id"] == message_id) -# return messages[index + 1:] -# except StopIteration: -# return [] - -# async def get_messages_before(self, chat_id: str, time_point: float, limit: int = 5) -> List[Dict[str, Any]]: -# if chat_id not in self.messages: -# return [] - -# messages = [ -# m for m in self.messages[chat_id] -# if m["time"] < time_point -# ] - -# return messages[-limit:] - -# async def has_new_messages(self, chat_id: str, after_time: float) -> bool: -# if chat_id not in self.messages: -# return False - -# return any(m["time"] > after_time for m in self.messages[chat_id]) - -# # 测试辅助方法 -# def add_message(self, chat_id: str, message: Dict[str, Any]): -# """添加测试消息""" -# if chat_id not in self.messages: -# self.messages[chat_id] = [] -# self.messages[chat_id].append(message) -# self.messages[chat_id].sort(key=lambda m: m["time"]) diff --git a/src/chat/brain_chat/PFC/observation_info.py b/src/chat/brain_chat/PFC/observation_info.py index d72f8207..296505a5 100644 --- a/src/chat/brain_chat/PFC/observation_info.py +++ b/src/chat/brain_chat/PFC/observation_info.py @@ -1,13 +1,40 @@ from typing import List, Optional, Dict, Any, Set from maim_message import UserInfo import time -from src.common.logger import get_module_logger +from src.common.logger import get_logger 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, DatabaseUserInfo import traceback # 导入 traceback 用于调试 -logger = get_module_logger("observation_info") +logger = get_logger("observation_info") + + +def dict_to_database_message(msg_dict: Dict[str, Any]) -> DatabaseMessages: + """Convert PFC dict format to DatabaseMessages object + + Args: + msg_dict: Message in PFC dict format with nested user_info + + Returns: + DatabaseMessages object compatible with build_readable_messages() + """ + user_info_dict: Dict[str, Any] = msg_dict.get("user_info", {}) + + return DatabaseMessages( + 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", ""), + ) class ObservationInfoHandler(NotificationHandler): @@ -366,10 +393,11 @@ 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: - self.chat_history_str = await build_readable_messages( - history_slice_for_str, + # Convert dict format to DatabaseMessages objects + db_messages = [dict_to_database_message(m) for m in history_slice_for_str] + self.chat_history_str = build_readable_messages( + db_messages, replace_bot_name=True, - merge_messages=False, 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 7095a7a2..c618df93 100644 --- a/src/chat/brain_chat/PFC/pfc.py +++ b/src/chat/brain_chat/PFC/pfc.py @@ -1,12 +1,12 @@ from typing import List, Tuple, TYPE_CHECKING -from src.common.logger import get_module_logger +from src.common.logger import get_logger from src.llm_models.utils_model import LLMRequest -from src.config.config import global_config +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 .conversation_info import ConversationInfo -from .observation_info import ObservationInfo +from .observation_info import ObservationInfo, dict_to_database_message from src.chat.utils.chat_message_builder import build_readable_messages from rich.traceback import install @@ -15,7 +15,7 @@ install(extra_lines=3) if TYPE_CHECKING: pass -logger = get_module_logger("pfc") +logger = get_logger("pfc") def _calculate_similarity(goal1: str, goal2: str) -> float: @@ -43,12 +43,12 @@ class GoalAnalyzer: def __init__(self, stream_id: str, private_name: str): self.llm = LLMRequest( - model=global_config.llm_normal, temperature=0.7, max_tokens=1000, request_type="conversation_goal" + model_set=model_config.model_task_config.planner, request_type="conversation_goal" ) self.personality_info = self._get_personality_prompt() - self.name = global_config.BOT_NICKNAME - self.nick_name = global_config.BOT_ALIAS_NAMES + self.name = global_config.bot.nickname + self.nick_name = global_config.bot.alias_names self.private_name = private_name self.chat_observer = ChatObserver.get_instance(stream_id, private_name) @@ -105,10 +105,10 @@ class GoalAnalyzer: if observation_info.new_messages_count > 0: new_messages_list = observation_info.unprocessed_messages - new_messages_str = await build_readable_messages( - new_messages_list, + db_messages = [dict_to_database_message(m) for m in new_messages_list] + new_messages_str = build_readable_messages( + db_messages, replace_bot_name=True, - merge_messages=False, timestamp_mode="relative", read_mark=0.0, ) @@ -189,7 +189,9 @@ class GoalAnalyzer: else: # 单个目标的情况 conversation_info.goal_list.append(result) - return goal, "", reasoning + goal_value = result.get("goal", "") + reasoning_value = result.get("reasoning", "") + return goal_value, "", reasoning_value # 如果解析失败，返回默认值 return "", "", "" @@ -238,10 +240,10 @@ class GoalAnalyzer: async def analyze_conversation(self, goal, reasoning): messages = self.chat_observer.get_cached_messages() - chat_history_text = await build_readable_messages( - messages, + db_messages = [dict_to_database_message(m) for m in messages] + chat_history_text = build_readable_messages( + db_messages, replace_bot_name=True, - merge_messages=False, timestamp_mode="relative", read_mark=0.0, ) diff --git a/src/chat/brain_chat/PFC/pfc_KnowledgeFetcher.py b/src/chat/brain_chat/PFC/pfc_KnowledgeFetcher.py index 2954b063..afdc6943 100644 --- a/src/chat/brain_chat/PFC/pfc_KnowledgeFetcher.py +++ b/src/chat/brain_chat/PFC/pfc_KnowledgeFetcher.py @@ -1,13 +1,15 @@ -from typing import List, Tuple -from src.common.logger import get_module_logger -from src.plugins.memory_system.Hippocampus import HippocampusManager +from typing import List, Tuple, Dict, Any +from src.common.logger import get_logger +# NOTE: HippocampusManager doesn't exist in v0.12.2 - memory system was redesigned +# from src.plugins.memory_system.Hippocampus import HippocampusManager from src.llm_models.utils_model import LLMRequest -from src.config.config import global_config +from src.config.config import global_config, model_config from src.chat.message_receive.message import Message -from src.chat.knowledge.knowledge_lib import qa_manager +from src.chat.knowledge import qa_manager from src.chat.utils.chat_message_builder import build_readable_messages +from src.chat.brain_chat.PFC.observation_info import dict_to_database_message -logger = get_module_logger("knowledge_fetcher") +logger = get_logger("knowledge_fetcher") class KnowledgeFetcher: @@ -15,10 +17,7 @@ class KnowledgeFetcher: def __init__(self, private_name: str): self.llm = LLMRequest( - model=global_config.llm_normal, - temperature=global_config.llm_normal["temp"], - max_tokens=1000, - request_type="knowledge_fetch", + model_set=model_config.model_task_config.utils ) self.private_name = private_name @@ -41,42 +40,46 @@ class KnowledgeFetcher: logger.error(f"[私聊][{self.private_name}]LPMM知识库搜索工具执行失败: {str(e)}") return "未找到匹配的知识" - async def fetch(self, query: str, chat_history: List[Message]) -> Tuple[str, str]: + async def fetch(self, query: str, chat_history: List[Dict[str, Any]]) -> Tuple[str, str]: """获取相关知识 Args: query: 查询内容 - chat_history: 聊天历史 + chat_history: 聊天历史 (PFC dict format) Returns: Tuple[str, str]: (获取的知识, 知识来源) """ - # 构建查询上下文 - chat_history_text = await build_readable_messages( - chat_history, + db_messages = [dict_to_database_message(m) for m in chat_history] + chat_history_text = build_readable_messages( + db_messages, replace_bot_name=True, - merge_messages=False, timestamp_mode="relative", read_mark=0.0, ) - # 从记忆中获取相关知识 - related_memory = await HippocampusManager.get_instance().get_memory_from_text( - text=f"{query}\n{chat_history_text}", - max_memory_num=3, - max_memory_length=2, - max_depth=3, - fast_retrieval=False, - ) + # NOTE: Hippocampus memory system was redesigned in v0.12.2 + # The old get_memory_from_text API no longer exists + # For now, we'll skip the memory retrieval part and only use LPMM knowledge + # TODO: Integrate with new memory system if needed knowledge_text = "" sources_text = "无记忆匹配" # 默认值 - if related_memory: - sources = [] - for memory in related_memory: - knowledge_text += memory[1] + "\n" - sources.append(f"记忆片段{memory[0]}") - knowledge_text = knowledge_text.strip() - sources_text = "，".join(sources) + + # # 从记忆中获取相关知识 (DISABLED - old Hippocampus API) + # related_memory = await HippocampusManager.get_instance().get_memory_from_text( + # text=f"{query}\n{chat_history_text}", + # max_memory_num=3, + # max_memory_length=2, + # max_depth=3, + # fast_retrieval=False, + # ) + # if related_memory: + # sources = [] + # for memory in related_memory: + # knowledge_text += memory[1] + "\n" + # sources.append(f"记忆片段{memory[0]}") + # knowledge_text = knowledge_text.strip() + # sources_text = "，".join(sources) knowledge_text += "\n现在有以下**知识**可供参考：\n " knowledge_text += self._lpmm_get_knowledge(query) diff --git a/src/chat/brain_chat/PFC/pfc_manager.py b/src/chat/brain_chat/PFC/pfc_manager.py index 7837606c..174be78b 100644 --- a/src/chat/brain_chat/PFC/pfc_manager.py +++ b/src/chat/brain_chat/PFC/pfc_manager.py @@ -1,10 +1,10 @@ import time from typing import Dict, Optional -from src.common.logger import get_module_logger +from src.common.logger import get_logger from .conversation import Conversation import traceback -logger = get_module_logger("pfc_manager") +logger = get_logger("pfc_manager") class PFCManager: diff --git a/src/chat/brain_chat/PFC/pfc_utils.py b/src/chat/brain_chat/PFC/pfc_utils.py index 2f7bd5e0..b9e93ee5 100644 --- a/src/chat/brain_chat/PFC/pfc_utils.py +++ b/src/chat/brain_chat/PFC/pfc_utils.py @@ -1,9 +1,9 @@ import json import re from typing import Dict, Any, Optional, Tuple, List, Union -from src.common.logger import get_module_logger +from src.common.logger import get_logger -logger = get_module_logger("pfc_utils") +logger = get_logger("pfc_utils") def get_items_from_json( diff --git a/src/chat/brain_chat/PFC/reply_checker.py b/src/chat/brain_chat/PFC/reply_checker.py index 182c0ab5..0ab88495 100644 --- a/src/chat/brain_chat/PFC/reply_checker.py +++ b/src/chat/brain_chat/PFC/reply_checker.py @@ -1,12 +1,13 @@ import json +import random from typing import Tuple, List, Dict, Any -from src.common.logger import get_module_logger +from src.common.logger import get_logger from src.llm_models.utils_model import LLMRequest -from src.config.config import global_config +from src.config.config import global_config, model_config from .chat_observer import ChatObserver from maim_message import UserInfo -logger = get_module_logger("reply_checker") +logger = get_logger("reply_checker") class ReplyChecker: @@ -14,13 +15,30 @@ class ReplyChecker: def __init__(self, stream_id: str, private_name: str): self.llm = LLMRequest( - model=global_config.llm_PFC_reply_checker, temperature=0.50, max_tokens=1000, request_type="reply_check" + model_set=model_config.model_task_config.utils, + request_type="reply_check" ) - self.name = global_config.BOT_NICKNAME + self.personality_info = self._get_personality_prompt() + self.name = global_config.bot.nickname self.private_name = private_name self.chat_observer = ChatObserver.get_instance(stream_id, private_name) self.max_retries = 3 # 最大重试次数 + def _get_personality_prompt(self) -> str: + """获取个性提示信息""" + prompt_personality = global_config.personality.personality + + # 检查是否需要随机替换为状态 + if ( + global_config.personality.states + and global_config.personality.state_probability > 0 + and random.random() < global_config.personality.state_probability + ): + prompt_personality = random.choice(global_config.personality.states) + + bot_name = global_config.bot.nickname + return f"你的名字是{bot_name},你{prompt_personality};" + async def check( self, reply: str, goal: str, chat_history: List[Dict[str, Any]], chat_history_text: str, retry_count: int = 0 ) -> Tuple[bool, str, bool]: @@ -43,7 +61,7 @@ class ReplyChecker: bot_messages = [] for msg in reversed(chat_history): user_info = UserInfo.from_dict(msg.get("user_info", {})) - if str(user_info.user_id) == str(global_config.BOT_QQ): # 确保比较的是字符串 + if str(user_info.user_id) == str(global_config.bot.qq_account): bot_messages.append(msg.get("processed_plain_text", "")) if len(bot_messages) >= 2: # 只和最近的两条比较 break @@ -129,7 +147,7 @@ class ReplyChecker: content = content.strip() try: # 尝试直接解析 - result = json.loads(content) + result: dict = json.loads(content) except json.JSONDecodeError: # 如果直接解析失败，尝试查找和提取JSON部分 import re @@ -138,7 +156,7 @@ class ReplyChecker: json_match = re.search(json_pattern, content) if json_match: try: - result = json.loads(json_match.group()) + result: dict = json.loads(json_match.group()) except json.JSONDecodeError: # 如果JSON解析失败，尝试从文本中提取结果 is_suitable = "不合适" not in content.lower() and "违规" not in content.lower() diff --git a/src/chat/brain_chat/PFC/reply_generator.py b/src/chat/brain_chat/PFC/reply_generator.py index e1bd65e2..ad801de1 100644 --- a/src/chat/brain_chat/PFC/reply_generator.py +++ b/src/chat/brain_chat/PFC/reply_generator.py @@ -1,11 +1,11 @@ from typing import Tuple, List, Dict, Any from src.common.logger import get_logger from src.llm_models.utils_model import LLMRequest -from src.config.config import global_config +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 +from .observation_info import ObservationInfo, dict_to_database_message from .conversation_info import ConversationInfo from src.chat.utils.chat_message_builder import build_readable_messages @@ -87,13 +87,11 @@ class ReplyGenerator: def __init__(self, stream_id: str, private_name: str): self.llm = LLMRequest( - model=global_config.llm_PFC_chat, - temperature=global_config.llm_PFC_chat["temp"], - max_tokens=300, + model_set=model_config.model_task_config.replyer, request_type="reply_generation", ) self.personality_info = self._get_personality_prompt() - self.name = global_config.BOT_NICKNAME + self.name = global_config.bot.nickname self.private_name = private_name self.chat_observer = ChatObserver.get_instance(stream_id, private_name) self.reply_checker = ReplyChecker(stream_id, private_name) @@ -110,7 +108,7 @@ class ReplyGenerator: ): prompt_personality = random.choice(global_config.personality.states) - bot_name = global_config.BOT_NICKNAME + bot_name = global_config.bot.nickname return f"你的名字是{bot_name},你{prompt_personality};" # 修改 generate 方法签名，增加 action_type 参数 @@ -188,10 +186,10 @@ 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 - new_messages_str = await build_readable_messages( - new_messages_list, + db_messages = [dict_to_database_message(m) for m in new_messages_list] + new_messages_str = build_readable_messages( + db_messages, replace_bot_name=True, - merge_messages=False, timestamp_mode="relative", read_mark=0.0, ) diff --git a/src/chat/brain_chat/PFC/waiter.py b/src/chat/brain_chat/PFC/waiter.py index af5cf7ad..b93b84d9 100644 --- a/src/chat/brain_chat/PFC/waiter.py +++ b/src/chat/brain_chat/PFC/waiter.py @@ -1,4 +1,4 @@ -from src.common.logger import get_module_logger +from src.common.logger import get_logger from .chat_observer import ChatObserver from .conversation_info import ConversationInfo @@ -7,7 +7,7 @@ from src.config.config import global_config import time import asyncio -logger = get_module_logger("waiter") +logger = get_logger("waiter") # --- 在这里设定你想要的超时时间（秒） --- # 例如： 120 秒 = 2 分钟 @@ -19,7 +19,7 @@ class Waiter: def __init__(self, stream_id: str, private_name: str): self.chat_observer = ChatObserver.get_instance(stream_id, private_name) - self.name = global_config.BOT_NICKNAME + self.name = global_config.bot.nickname self.private_name = private_name # self.wait_accumulated_time = 0 # 不再需要累加计时 diff --git a/src/chat/message_receive/bot.py b/src/chat/message_receive/bot.py index c45ec105..13a538bb 100644 --- a/src/chat/message_receive/bot.py +++ b/src/chat/message_receive/bot.py @@ -11,6 +11,7 @@ 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.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 @@ -73,6 +74,7 @@ class ChatBot: self.bot = None # bot 实例引用 self._started = False self.heartflow_message_receiver = HeartFCMessageReceiver() # 新增 + self.pfc_manager = PFCManager.get_instance() # PFC管理器 async def _ensure_started(self): """确保所有任务已启动""" @@ -81,6 +83,23 @@ class ChatBot: self._started = True + async def _create_pfc_chat(self, message: MessageRecv): + """创建或获取PFC对话实例 + + Args: + message: 消息对象 + """ + try: + chat_id = str(message.chat_stream.stream_id) + private_name = str(message.message_info.user_info.user_nickname) + + logger.debug(f"[私聊][{private_name}]创建或获取PFC对话: {chat_id}") + await self.pfc_manager.get_or_create_conversation(chat_id, private_name) + + except Exception as e: + logger.error(f"创建PFC聊天失败: {e}") + logger.error(traceback.format_exc()) + async def _process_commands(self, message: MessageRecv): # sourcery skip: use-named-expression """使用新插件系统处理命令""" @@ -324,7 +343,16 @@ class ChatBot: template_group_name = None async def preprocess(): - await self.heartflow_message_receiver.process_message(message) + # 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): diff --git a/src/config/config.py b/src/config/config.py index 9c1987ac..d6397a66 100644 --- a/src/config/config.py +++ b/src/config/config.py @@ -162,6 +162,44 @@ class ModelConfig(ConfigBase): return super().model_post_init(context) +def get_model_info_by_name(model_config: ModelConfig, model_name: str) -> ModelInfo: + """根据模型名称获取模型信息 + + Args: + model_config: ModelConfig实例 + model_name: 模型名称 + + Returns: + ModelInfo: 模型信息 + + Raises: + ValueError: 未找到指定模型 + """ + for model in model_config.models: + if model.name == model_name: + return model + raise ValueError(f"未找到名为 '{model_name}' 的模型") + + +def get_provider_by_name(model_config: ModelConfig, provider_name: str) -> APIProvider: + """根据提供商名称获取提供商信息 + + Args: + model_config: ModelConfig实例 + provider_name: 提供商名称 + + Returns: + APIProvider: API提供商信息 + + Raises: + ValueError: 未找到指定提供商 + """ + for provider in model_config.api_providers: + if provider.name == provider_name: + return provider + raise ValueError(f"未找到名为 '{provider_name}' 的API提供商") + + class ConfigManager: """总配置管理类""" diff --git a/src/llm_models/utils_model.py b/src/llm_models/utils_model.py index 121e152e..4cde5c1a 100644 --- a/src/llm_models/utils_model.py +++ b/src/llm_models/utils_model.py @@ -9,7 +9,7 @@ from typing import Tuple, List, Dict, Optional, Callable, Any, Set import traceback from src.common.logger import get_logger -from src.config.config import model_config +from src.config.config import model_config, get_model_info_by_name, get_provider_by_name from src.config.model_configs import APIProvider, ModelInfo, TaskConfig from .payload_content.message import MessageBuilder, Message from .payload_content.resp_format import RespFormat @@ -296,8 +296,8 @@ class LLMRequest: key=lambda k: available_models[k][0] + available_models[k][1] * 300 + available_models[k][2] * 1000, ) - model_info = model_config.get_model_info(selected_model_name) - api_provider = model_config.get_provider(model_info.api_provider) + model_info = get_model_info_by_name(model_config, selected_model_name) + api_provider = get_provider_by_name(model_config, model_info.api_provider) force_new_client = self.request_type == "embedding" client = client_registry.get_client_class_instance(api_provider, force_new=force_new_client) logger.debug(f"选择请求模型: {model_info.name} (策略: {strategy})")