根据开发组建议重命名，移除多余的Prompt后缀

src/chat/brain_chat/brain_chat.py

@@ -313,7 +313,7 @@ class BrainChatting:
                 current_available_actions=available_actions,
                 chat_content_block=chat_content_block,
                 message_id_list=message_id_list,
-                prompt_key="brain_planner_prompt_react",
+                prompt_key="brain_planner",
             )
             continue_flag, modified_message = await events_manager.handle_mai_events(
                 EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id

src/chat/brain_chat/brain_planner.py

@@ -200,7 +200,7 @@ class BrainPlanner:
 
         prompt_build_start = time.perf_counter()
         # 构建包含所有动作的提示词：使用统一的 ReAct Prompt
-        prompt_key = "brain_planner_prompt_react"
+        prompt_key = "brain_planner"
         # 这里不记录日志，避免重复打印，由调用方按需控制 log_prompt
         prompt, message_id_list = await self.build_planner_prompt(
             chat_target_info=chat_target_info,
@@ -254,7 +254,7 @@ class BrainPlanner:
         message_id_list: List[Tuple[str, "DatabaseMessages"]],
         chat_content_block: str = "",
         interest: str = "",
-        prompt_key: str = "brain_planner_prompt_react",
+        prompt_key: str = "brain_planner",
     ) -> tuple[str, List[Tuple[str, "DatabaseMessages"]]]:
         """构建 Planner LLM 的提示词 (获取模板并填充数据)"""
         try:
@@ -381,7 +381,7 @@ class BrainPlanner:
             require_text = require_text.rstrip("\n")
 
             # 获取动作提示模板并填充
-            using_action_prompt_template = prompt_manager.get_prompt("brain_action_prompt")
+            using_action_prompt_template = prompt_manager.get_prompt("brain_action")
             using_action_prompt_template.add_context("action_name", action_name)
             using_action_prompt_template.add_context("action_description", action_info.description)
             using_action_prompt_template.add_context("action_parameters", param_text)