fix of types

src/chat/brain_chat/brain_planner.py

@@ -305,8 +305,9 @@ class BrainPlanner:
             else:
                 actions_before_now_block = ""
 
-            # 构建聊天上下文描述
+            if chat_target_info:
-            chat_context_description = f"你正在和 {chat_target_info.person_name or chat_target_info.user_nickname or '对方'} 聊天中"
+                # 构建聊天上下文描述
+                chat_context_description = f"你正在和 {chat_target_info.person_name or chat_target_info.user_nickname or '对方'} 聊天中"
 
             # 构建动作选项块
             action_options_block = await self._build_action_options_block(current_available_actions)

src/chat/heart_flow/heartFC_chat.py

@@ -192,21 +192,18 @@ class HeartFChatting:
                     return True
 
             self.last_read_time = time.time()
-            
+
             # !此处使at或者提及必定回复
-            metioned_message = None
+            mentioned_message = None
             for message in recent_messages_list:
                 if (message.is_mentioned or message.is_at) and global_config.chat.mentioned_bot_reply:
-                    metioned_message = message
+                    mentioned_message = message
-            
+
             # *控制频率用
-            if not metioned_message:
+            if mentioned_message:
-                if random.random() > global_config.chat.talk_value:
+                await self._observe(recent_messages_list=recent_messages_list, force_reply_message=mentioned_message)
-                    return True
+            elif random.random() > global_config.chat.talk_value:
-            
+                return True
-            await self._observe(
-                recent_messages_list=recent_messages_list,force_reply_message=metioned_message
-            )
         else:
             # Normal模式：消息数量不足，等待
             await asyncio.sleep(0.2)
@@ -265,7 +262,8 @@ class HeartFChatting:
 
     async def _observe(
         self,  # interest_value: float = 0.0,
-        recent_messages_list: Optional[List["DatabaseMessages"]] = None, force_reply_message:"DatabaseMessages" = None
+        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 = []
@@ -542,7 +540,6 @@ class HeartFChatting:
         """执行单个动作的通用函数"""
         try:
             with Timer(f"动作{action_planner_info.action_type}", cycle_timers):
-                
                 if action_planner_info.action_type == "no_reply":
                     # 直接处理no_action逻辑，不再通过动作系统
                     reason = action_planner_info.reasoning or "选择不回复"
@@ -586,7 +583,9 @@ class HeartFChatting:
 
                         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")
+                                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, "reply_text": "", "loop_info": None}

src/chat/heart_flow/heartflow.py

@@ -23,17 +23,16 @@ class Heartflow:
                 if chat := self.heartflow_chat_list.get(chat_id):
                     return chat
             else:
-                chat_stream: ChatStream = get_chat_manager().get_stream(chat_id)
+                chat_stream: ChatStream | None = get_chat_manager().get_stream(chat_id)
+                if not chat_stream:
+                    raise ValueError(f"未找到 chat_id={chat_id} 的聊天流")
                 if chat_stream.group_info:
                     new_chat = HeartFChatting(chat_id=chat_id)
-                    await new_chat.start()
-                    self.heartflow_chat_list[chat_id] = new_chat
-                    return new_chat
                 else:
                     new_chat = BrainChatting(chat_id=chat_id)
-                    await new_chat.start()
+                await new_chat.start()
-                    self.heartflow_chat_list[chat_id] = new_chat
+                self.heartflow_chat_list[chat_id] = new_chat
-                    return new_chat
+                return new_chat
         except Exception as e:
             logger.error(f"创建心流聊天 {chat_id} 失败: {e}", exc_info=True)
             traceback.print_exc()

src/chat/message_receive/message.py

@@ -87,7 +87,7 @@ class Message(MessageBase):
                 processed_text = await self._process_message_segments(message.message_segment)
                 if processed_text:
                     segments_text.append(f"{global_config.bot.nickname}: {processed_text}")
-            return "[合并消息]: " + "\n".join(segments_text)
+            return "[合并消息]: " + "\n--  ".join(segments_text)
         else:
             # 处理单个消息段
             return await self._process_single_segment(segment)  # type: ignore

src/chat/utils/utils_image.py

@@ -222,6 +222,7 @@ class ImageManager:
                     img_obj.save()
                 except Images.DoesNotExist:  # type: ignore
                     Images.create(
+                        image_id=str(uuid.uuid4()),
                         emoji_hash=image_hash,
                         path=file_path,
                         type="emoji",

src/mood/mood_manager.py

@@ -75,7 +75,7 @@ class ChatMood:
         time_multiplier = 4 * (1 - math.exp(-0.01 * during_last_time))
 
         # 基于消息长度计算基础兴趣度
-        message_length = len(message.message_content.content or "")
+        message_length = len(message.processed_plain_text or "")
         interest_multiplier = min(2.0, 1.0 + message_length / 100)
 
         logger.debug(

src/plugin_system/apis/generator_api.py

@@ -14,6 +14,7 @@ from rich.traceback import install
 from src.common.logger import get_logger
 from src.common.data_models.message_data_model import ReplySetModel
 from src.chat.replyer.default_generator import DefaultReplyer
+from src.chat.replyer.private_generator import PrivateReplyer
 from src.chat.message_receive.chat_stream import ChatStream
 from src.chat.utils.utils import process_llm_response
 from src.chat.replyer.replyer_manager import replyer_manager
@@ -38,7 +39,7 @@ def get_replyer(
     chat_stream: Optional[ChatStream] = None,
     chat_id: Optional[str] = None,
     request_type: str = "replyer",
-) -> Optional[DefaultReplyer]:
+) -> Optional[DefaultReplyer | PrivateReplyer]:
     """获取回复器对象
 
     优先使用chat_stream，如果没有则使用chat_id直接查找。