feat：表达方式根据不同thinking level进分别处理

src/chat/replyer/group_generator.py

@@ -229,7 +229,7 @@ class DefaultReplyer:
             return False, llm_response
 
     async def build_expression_habits(
-        self, chat_history: str, target: str, reply_reason: str = ""
+        self, chat_history: str, target: str, reply_reason: str = "", think_level: int = 1
     ) -> Tuple[str, List[int]]:
         # sourcery skip: for-append-to-extend
         """构建表达习惯块
@@ -238,6 +238,7 @@ class DefaultReplyer:
             chat_history: 聊天历史记录
             target: 目标消息内容
             reply_reason: planner给出的回复理由
+            think_level: 思考级别，0/1/2
 
         Returns:
             str: 表达习惯信息字符串
@@ -250,7 +251,7 @@ class DefaultReplyer:
         # 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.stream_id, chat_history, max_num=8, target_message=target, reply_reason=reply_reason, think_level=think_level
         )
 
         if selected_expressions:
@@ -788,7 +789,7 @@ class DefaultReplyer:
         # 并行执行八个构建任务（包括黑话解释）
         task_results = await asyncio.gather(
             self._time_and_run_task(
-                self.build_expression_habits(chat_talking_prompt_short, target, reply_reason), "expression_habits"
+                self.build_expression_habits(chat_talking_prompt_short, target, reply_reason, think_level=think_level), "expression_habits"
             ),
             self._time_and_run_task(
                 self.build_tool_info(chat_talking_prompt_short, sender, target, enable_tool=enable_tool), "tool_info"