feat：优化了auto切换聊天模式机制，修改取名prompt，不再处理temp

src/chat/focus_chat/heartflow_message_processor.py

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+import time
+import traceback
+from ..memory_system.Hippocampus import HippocampusManager
+from ...config.config import global_config
+from ..message_receive.message import MessageRecv
+from ..message_receive.storage import MessageStorage
+from ..utils.utils import is_mentioned_bot_in_message
+from src.chat.heart_flow.heartflow import heartflow
+from src.common.logger_manager import get_logger
+from ..message_receive.chat_stream import chat_manager
+
+# from ..message_receive.message_buffer import message_buffer
+from ..utils.timer_calculator import Timer
+from src.person_info.relationship_manager import relationship_manager
+from typing import Optional, Tuple, Dict, Any
+
+logger = get_logger("chat")
+
+
+async def _handle_error(error: Exception, context: str, message: Optional[MessageRecv] = None) -> None:
+    """统一的错误处理函数
+
+    Args:
+        error: 捕获到的异常
+        context: 错误发生的上下文描述
+        message: 可选的消息对象，用于记录相关消息内容
+    """
+    logger.error(f"{context}: {error}")
+    logger.error(traceback.format_exc())
+    if message and hasattr(message, "raw_message"):
+        logger.error(f"相关消息原始内容: {message.raw_message}")
+
+
+async def _process_relationship(message: MessageRecv) -> None:
+    """处理用户关系逻辑
+
+    Args:
+        message: 消息对象，包含用户信息
+    """
+    platform = message.message_info.platform
+    user_id = message.message_info.user_info.user_id
+    nickname = message.message_info.user_info.user_nickname
+    cardname = message.message_info.user_info.user_cardname or nickname
+
+    is_known = await relationship_manager.is_known_some_one(platform, user_id)
+
+    if not is_known:
+        logger.info(f"首次认识用户: {nickname}")
+        await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
+    elif not await relationship_manager.is_qved_name(platform, user_id):
+        logger.info(f"给用户({nickname},{cardname})取名: {nickname}")
+        await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
+
+
+async def _calculate_interest(message: MessageRecv) -> Tuple[float, bool]:
+    """计算消息的兴趣度
+
+    Args:
+        message: 待处理的消息对象
+
+    Returns:
+        Tuple[float, bool]: (兴趣度, 是否被提及)
+    """
+    is_mentioned, _ = is_mentioned_bot_in_message(message)
+    interested_rate = 0.0
+
+    with Timer("记忆激活"):
+        interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
+            message.processed_plain_text,
+            fast_retrieval=True,
+        )
+        logger.trace(f"记忆激活率: {interested_rate:.2f}")
+
+    if is_mentioned:
+        interest_increase_on_mention = 1
+        interested_rate += interest_increase_on_mention
+
+    return interested_rate, is_mentioned
+
+
+# def _get_message_type(message: MessageRecv) -> str:
+#     """获取消息类型
+
+#     Args:
+#         message: 消息对象
+
+#     Returns:
+#         str: 消息类型
+#     """
+#     if message.message_segment.type != "seglist":
+#         return message.message_segment.type
+
+#     if (
+#         isinstance(message.message_segment.data, list)
+#         and all(isinstance(x, Seg) for x in message.message_segment.data)
+#         and len(message.message_segment.data) == 1
+#     ):
+#         return message.message_segment.data[0].type
+
+#     return "seglist"
+
+
+def _check_ban_words(text: str, chat, userinfo) -> 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 = chat.group_info.group_name if chat.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, chat, userinfo) -> 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
+    """
+    for pattern in global_config.message_receive.ban_msgs_regex:
+        if pattern.search(text):
+            chat_name = chat.group_info.group_name if chat.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 HeartFCMessageReceiver:
+    """心流处理器，负责处理接收到的消息并计算兴趣度"""
+
+    def __init__(self):
+        """初始化心流处理器，创建消息存储实例"""
+        self.storage = MessageStorage()
+
+    async def process_message(self, message_data: Dict[str, Any]) -> None:
+        """处理接收到的原始消息数据
+
+        主要流程:
+        1. 消息解析与初始化
+        2. 消息缓冲处理
+        3. 过滤检查
+        4. 兴趣度计算
+        5. 关系处理
+
+        Args:
+            message_data: 原始消息字符串
+        """
+        message = None
+        try:
+            # 1. 消息解析与初始化
+            message = MessageRecv(message_data)
+            groupinfo = message.message_info.group_info
+            userinfo = message.message_info.user_info
+            messageinfo = message.message_info
+
+            # 2. 消息缓冲与流程序化
+            # await message_buffer.start_caching_messages(message)
+
+            chat = await chat_manager.get_or_create_stream(
+                platform=messageinfo.platform,
+                user_info=userinfo,
+                group_info=groupinfo,
+            )
+
+            subheartflow = await heartflow.get_or_create_subheartflow(chat.stream_id)
+            message.update_chat_stream(chat)
+            await message.process()
+
+            # 3. 过滤检查
+            if _check_ban_words(message.processed_plain_text, chat, userinfo) or _check_ban_regex(
+                message.raw_message, chat, userinfo
+            ):
+                return
+
+            # 4. 缓冲检查
+            # buffer_result = await message_buffer.query_buffer_result(message)
+            # if not buffer_result:
+            #     msg_type = _get_message_type(message)
+            #     type_messages = {
+            #         "text": f"触发缓冲，消息：{message.processed_plain_text}",
+            #         "image": "触发缓冲，表情包/图片等待中",
+            #         "seglist": "触发缓冲，消息列表等待中",
+            #     }
+            #     logger.debug(type_messages.get(msg_type, "触发未知类型缓冲"))
+            #     return
+
+            # 5. 消息存储
+            await self.storage.store_message(message, chat)
+            logger.trace(f"存储成功: {message.processed_plain_text}")
+
+            # 6. 兴趣度计算与更新
+            interested_rate, is_mentioned = await _calculate_interest(message)
+            await subheartflow.interest_chatting.increase_interest(value=interested_rate)
+            subheartflow.interest_chatting.add_interest_dict(message, interested_rate, is_mentioned)
+
+            # 7. 日志记录
+            mes_name = chat.group_info.group_name if chat.group_info else "私聊"
+            current_time = time.strftime("%H:%M:%S", time.localtime(message.message_info.time))
+            logger.info(
+                f"[{current_time}][{mes_name}]"
+                f"{userinfo.user_nickname}:"
+                f"{message.processed_plain_text}"
+                f"[激活: {interested_rate:.1f}]"
+            )
+
+            # 8. 关系处理
+            if global_config.relationship.give_name:
+                await _process_relationship(message)
+
+        except Exception as e:
+            await _handle_error(e, "消息处理失败", message)