Refactor chat stream handling to use BotChatSession

- Updated imports and references from ChatStream to BotChatSession across multiple files.
- Adjusted method signatures and internal logic to accommodate the new session management.
- Ensured compatibility with existing functionality while improving code clarity and maintainability.

src/chat/replyer/group_generator.py

@@ -12,8 +12,11 @@ from src.common.data_models.info_data_model import ActionPlannerInfo
 from src.common.data_models.llm_data_model import LLMGenerationDataModel
 from src.config.config import global_config, model_config
 from src.llm_models.utils_model import LLMRequest
-from src.chat.message_receive.message import UserInfo, Seg, MessageRecv, MessageSending
-from src.chat.message_receive.chat_stream import ChatStream
+from maim_message import Seg
+
+from src.common.data_models.mai_message_data_model import MaiMessage, UserInfo
+from src.chat.message_receive.message import MessageSending
+from src.chat.message_receive.chat_manager import BotChatSession
 from src.chat.message_receive.uni_message_sender import UniversalMessageSender
 from src.chat.utils.timer_calculator import Timer  # <--- Import Timer
 from src.chat.utils.utils import get_chat_type_and_target_info, is_bot_self
@@ -45,17 +48,17 @@ logger = get_logger("replyer")
 class DefaultReplyer:
     def __init__(
         self,
-        chat_stream: ChatStream,
+        chat_stream: BotChatSession,
         request_type: str = "replyer",
     ):
         self.express_model = LLMRequest(model_set=model_config.model_task_config.replyer, request_type=request_type)
         self.chat_stream = chat_stream
-        self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.stream_id)
+        self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.session_id)
         self.heart_fc_sender = UniversalMessageSender()
 
         from src.plugin_system.core.tool_use import ToolExecutor  # 延迟导入ToolExecutor，不然会循环依赖
 
-        self.tool_executor = ToolExecutor(chat_id=self.chat_stream.stream_id, enable_cache=True, cache_ttl=3)
+        self.tool_executor = ToolExecutor(chat_id=self.chat_stream.session_id, enable_cache=True, cache_ttl=3)
 
     async def generate_reply_with_context(
         self,
@@ -132,7 +135,7 @@ class DefaultReplyer:
                 if log_reply:
                     try:
                         PlanReplyLogger.log_reply(
-                            chat_id=self.chat_stream.stream_id,
+                            chat_id=self.chat_stream.session_id,
                             prompt="",
                             output=None,
                             processed_output=None,
@@ -202,7 +205,7 @@ class DefaultReplyer:
                 try:
                     if log_reply:
                         PlanReplyLogger.log_reply(
-                            chat_id=self.chat_stream.stream_id,
+                            chat_id=self.chat_stream.session_id,
                             prompt=prompt,
                             output=content,
                             processed_output=None,
@@ -259,7 +262,7 @@ class DefaultReplyer:
                 if log_reply:
                     try:
                         PlanReplyLogger.log_reply(
-                            chat_id=self.chat_stream.stream_id,
+                            chat_id=self.chat_stream.session_id,
                             prompt=prompt or "",
                             output=None,
                             processed_output=None,
@@ -353,14 +356,14 @@ class DefaultReplyer:
             str: 表达习惯信息字符串
         """
         # 检查是否允许在此聊天流中使用表达
-        use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.stream_id)
+        use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.session_id)
         if not use_expression:
             return "", []
         style_habits = []
         # 使用从处理器传来的选中表达方式
         # 使用模型预测选择表达方式
         selected_expressions, selected_ids = await expression_selector.select_suitable_expressions(
-            self.chat_stream.stream_id,
+            self.chat_stream.session_id,
             chat_history,
             max_num=8,
             target_message=target,
@@ -702,10 +705,11 @@ class DefaultReplyer:
             # 判断是否为群聊
             is_group = stream_type == "group"
 
-            # 使用 ChatManager 提供的接口生成 chat_id，避免在此重复实现逻辑
-            from src.chat.message_receive.chat_stream import get_chat_manager
+            from src.common.utils.utils_session import SessionUtils
 
-            chat_id = get_chat_manager().get_stream_id(platform, str(id_str), is_group=is_group)
+            chat_id = SessionUtils.calculate_session_id(
+                platform, group_id=str(id_str) if is_group else None, user_id=str(id_str) if not is_group else None
+            )
             return chat_id, prompt_content
 
         except (ValueError, IndexError):
@@ -778,7 +782,7 @@ class DefaultReplyer:
         if available_actions is None:
             available_actions = {}
         chat_stream = self.chat_stream
-        chat_id = chat_stream.stream_id
+        chat_id = chat_stream.session_id
         _is_group_chat = bool(chat_stream.group_info)
         platform = chat_stream.platform
 
@@ -1005,7 +1009,7 @@ class DefaultReplyer:
         reply_to: str,
     ) -> str:  # sourcery skip: merge-else-if-into-elif, remove-redundant-if
         chat_stream = self.chat_stream
-        chat_id = chat_stream.stream_id
+        chat_id = chat_stream.session_id
         sender, target = self._parse_reply_target(reply_to)
         target = replace_user_references(target, chat_stream.platform, replace_bot_name=True)
 
@@ -1105,29 +1109,27 @@ class DefaultReplyer:
         is_emoji: bool,
         thinking_start_time: float,
         display_message: str,
-        anchor_message: Optional[MessageRecv] = None,
+        anchor_message: Optional[MaiMessage] = None,
     ) -> MessageSending:
         """构建单个发送消息"""
 
         bot_user_info = UserInfo(
             user_id=str(global_config.bot.qq_account),
             user_nickname=global_config.bot.nickname,
-            platform=self.chat_stream.platform,
         )
 
-        # await anchor_message.process()
         sender_info = anchor_message.message_info.user_info if anchor_message else None
 
         return MessageSending(
-            message_id=message_id,  # 使用片段的唯一ID
-            chat_stream=self.chat_stream,
+            message_id=message_id,
+            session=self.chat_stream,
             bot_user_info=bot_user_info,
             sender_info=sender_info,
             message_segment=message_segment,
-            reply=anchor_message,  # 回复原始锚点
+            reply=anchor_message,
             is_head=reply_to,
             is_emoji=is_emoji,
-            thinking_start_time=thinking_start_time,  # 传递原始思考开始时间
+            thinking_start_time=thinking_start_time,
             display_message=display_message,
         )
 

src/chat/replyer/private_generator.py

@@ -12,8 +12,11 @@ from src.common.data_models.info_data_model import ActionPlannerInfo
 from src.common.data_models.llm_data_model import LLMGenerationDataModel
 from src.config.config import global_config, model_config
 from src.llm_models.utils_model import LLMRequest
-from src.chat.message_receive.message import UserInfo, Seg, MessageRecv, MessageSending
-from src.chat.message_receive.chat_stream import ChatStream
+from maim_message import Seg
+
+from src.common.data_models.mai_message_data_model import MaiMessage, UserInfo
+from src.chat.message_receive.message import MessageSending
+from src.chat.message_receive.chat_manager import BotChatSession
 from src.chat.message_receive.uni_message_sender import UniversalMessageSender
 from src.chat.utils.timer_calculator import Timer
 from src.chat.utils.utils import get_chat_type_and_target_info, is_bot_self
@@ -43,18 +46,18 @@ logger = get_logger("replyer")
 class PrivateReplyer:
     def __init__(
         self,
-        chat_stream: ChatStream,
+        chat_stream: BotChatSession,
         request_type: str = "replyer",
     ):
         self.express_model = LLMRequest(model_set=model_config.model_task_config.replyer, request_type=request_type)
         self.chat_stream = chat_stream
-        self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.stream_id)
+        self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.session_id)
         self.heart_fc_sender = UniversalMessageSender()
         # self.memory_activator = MemoryActivator()
 
         from src.plugin_system.core.tool_use import ToolExecutor  # 延迟导入ToolExecutor，不然会循环依赖
 
-        self.tool_executor = ToolExecutor(chat_id=self.chat_stream.stream_id, enable_cache=True, cache_ttl=3)
+        self.tool_executor = ToolExecutor(chat_id=self.chat_stream.session_id, enable_cache=True, cache_ttl=3)
 
     async def generate_reply_with_context(
         self,
@@ -253,14 +256,14 @@ class PrivateReplyer:
             str: 表达习惯信息字符串
         """
         # 检查是否允许在此聊天流中使用表达
-        use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.stream_id)
+        use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.session_id)
         if not use_expression:
             return "", []
         style_habits = []
         # 使用从处理器传来的选中表达方式
         # 使用模型预测选择表达方式
         selected_expressions, selected_ids = await expression_selector.select_suitable_expressions(
-            self.chat_stream.stream_id, chat_history, max_num=8, target_message=target, reply_reason=reply_reason
+            self.chat_stream.session_id, chat_history, max_num=8, target_message=target, reply_reason=reply_reason
         )
 
         if selected_expressions:
@@ -550,10 +553,11 @@ class PrivateReplyer:
             # 判断是否为群聊
             is_group = stream_type == "group"
 
-            # 使用 ChatManager 提供的接口生成 chat_id，避免在此重复实现逻辑
-            from src.chat.message_receive.chat_stream import get_chat_manager
+            from src.common.utils.utils_session import SessionUtils
 
-            chat_id = get_chat_manager().get_stream_id(platform, str(id_str), is_group=is_group)
+            chat_id = SessionUtils.calculate_session_id(
+                platform, group_id=str(id_str) if is_group else None, user_id=str(id_str) if not is_group else None
+            )
             return chat_id, prompt_content
 
         except (ValueError, IndexError):
@@ -624,7 +628,7 @@ class PrivateReplyer:
         if available_actions is None:
             available_actions = {}
         chat_stream = self.chat_stream
-        chat_id = chat_stream.stream_id
+        chat_id = chat_stream.session_id
         platform = chat_stream.platform
 
         user_id = "用户ID"
@@ -843,7 +847,7 @@ class PrivateReplyer:
         reply_to: str,
     ) -> str:  # sourcery skip: merge-else-if-into-elif, remove-redundant-if
         chat_stream = self.chat_stream
-        chat_id = chat_stream.stream_id
+        chat_id = chat_stream.session_id
 
         sender, target = self._parse_reply_target(reply_to)
         target = replace_user_references(target, chat_stream.platform, replace_bot_name=True)
@@ -948,29 +952,27 @@ class PrivateReplyer:
         is_emoji: bool,
         thinking_start_time: float,
         display_message: str,
-        anchor_message: Optional[MessageRecv] = None,
+        anchor_message: Optional[MaiMessage] = None,
     ) -> MessageSending:
         """构建单个发送消息"""
 
         bot_user_info = UserInfo(
             user_id=str(global_config.bot.qq_account),
             user_nickname=global_config.bot.nickname,
-            platform=self.chat_stream.platform,
         )
 
-        # await anchor_message.process()
         sender_info = anchor_message.message_info.user_info if anchor_message else None
 
         return MessageSending(
-            message_id=message_id,  # 使用片段的唯一ID
-            chat_stream=self.chat_stream,
+            message_id=message_id,
+            session=self.chat_stream,
             bot_user_info=bot_user_info,
             sender_info=sender_info,
             message_segment=message_segment,
-            reply=anchor_message,  # 回复原始锚点
+            reply=anchor_message,
             is_head=reply_to,
             is_emoji=is_emoji,
-            thinking_start_time=thinking_start_time,  # 传递原始思考开始时间
+            thinking_start_time=thinking_start_time,
             display_message=display_message,
         )
 

src/chat/replyer/replyer_manager.py

@@ -1,7 +1,7 @@
 from typing import Dict, Optional
 
 from src.common.logger import get_logger
-from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager
+from src.chat.message_receive.chat_manager import BotChatSession, chat_manager as _chat_manager
 from src.chat.replyer.group_generator import DefaultReplyer
 from src.chat.replyer.private_generator import PrivateReplyer
 
@@ -14,7 +14,7 @@ class ReplyerManager:
 
     def get_replyer(
         self,
-        chat_stream: Optional[ChatStream] = None,
+        chat_stream: Optional[BotChatSession] = None,
         chat_id: Optional[str] = None,
         request_type: str = "replyer",
     ) -> Optional[DefaultReplyer | PrivateReplyer]:
@@ -24,7 +24,7 @@ class ReplyerManager:
         model_configs 仅在首次为某个 chat_id/stream_id 创建实例时有效。
         后续调用将返回已缓存的实例，忽略 model_configs 参数。
         """
-        stream_id = chat_stream.stream_id if chat_stream else chat_id
+        stream_id = chat_stream.session_id if chat_stream else chat_id
         if not stream_id:
             logger.warning("[ReplyerManager] 缺少 stream_id，无法获取回复器。")
             return None
@@ -39,15 +39,14 @@ class ReplyerManager:
 
         target_stream = chat_stream
         if not target_stream:
-            if chat_manager := get_chat_manager():
-                target_stream = chat_manager.get_stream(stream_id)
+            target_stream = _chat_manager.get_session_by_session_id(stream_id)
 
         if not target_stream:
             logger.warning(f"[ReplyerManager] 未找到 stream_id='{stream_id}' 的聊天流，无法创建回复器。")
             return None
 
         # model_configs 只在此时（初始化时）生效
-        if target_stream.group_info:
+        if target_stream.is_group_session:
             replyer = DefaultReplyer(
                 chat_stream=target_stream,
                 request_type=request_type,