log:修改一些log

src/plugin_system/apis/llm_api.py

@@ -66,8 +66,8 @@ async def generate_with_model(
         Tuple[bool, str, str, str]: (是否成功, 生成的内容, 推理过程, 模型名称)
     """
     try:
-        model_name_list = model_config.model_list
-        logger.info(f"[LLMAPI] 使用模型集合 {model_name_list} 生成内容")
+        # model_name_list = model_config.model_list
+        # logger.info(f"[LLMAPI] 使用模型集合 {model_name_list} 生成内容")
         logger.debug(f"[LLMAPI] 完整提示词: {prompt}")
 
         llm_request = LLMRequest(model_set=model_config, request_type=request_type)

src/plugin_system/apis/send_api.py

@@ -100,7 +100,7 @@ async def _send_to_target(
         anchor_message: Union["MessageRecv", None] = None
         if reply_message:
             anchor_message = db_message_to_message_recv(reply_message)
-            logger.info(f"[SendAPI] 找到匹配的回复消息，发送者: {anchor_message.message_info.user_info.user_id}")  # type: ignore
+            logger.debug(f"[SendAPI] 找到匹配的回复消息，发送者: {anchor_message.message_info.user_info.user_id}")  # type: ignore
             if anchor_message:
                 anchor_message.update_chat_stream(target_stream)
                 assert anchor_message.message_info.user_info, "用户信息缺失"

src/plugin_system/core/tool_use.py

@@ -180,7 +180,6 @@ class ToolExecutor:
 
                     tool_results.append(tool_info)
                     used_tools.append(tool_name)
-                    logger.info(f"{self.log_prefix}工具{tool_name}执行成功，类型: {tool_info['type']}")
                     preview = content[:200]
                     logger.debug(f"{self.log_prefix}工具{tool_name}结果内容: {preview}...")
             except Exception as e: