Merge branch 'master' of https://github.com/MaiBot-Plus/MaiMbot-Pro-Max

src/chat/memory_system/instant_memory.py

@@ -109,7 +109,7 @@ class InstantMemory:
             memory_id=memory_item.memory_id,
             chat_id=memory_item.chat_id,
             memory_text=memory_item.memory_text,
-            keywords=memory_item.keywords,
+            keywords=json.dumps(memory_item.keywords, ensure_ascii=False),
             create_time=memory_item.create_time,
             last_view_time=memory_item.last_view_time,
         )
@@ -171,11 +171,10 @@ class InstantMemory:
                         query = session.execute(select(Memory).where(Memory.chat_id == self.chat_id)).scalars()
                 for mem in query:
                     # 对每条记忆
-                    mem_keywords = mem.keywords or ""
-                    parsed = ast.literal_eval(mem_keywords)
-                    if isinstance(parsed, list):
-                        mem_keywords = [str(k).strip() for k in parsed if str(k).strip()]
-                    else:
+                    mem_keywords_str = mem.keywords or "[]"
+                    try:
+                        mem_keywords = json.loads(mem_keywords_str)
+                    except json.JSONDecodeError:
                         mem_keywords = []
                     # logger.info(f"mem_keywords: {mem_keywords}")
                     # logger.info(f"keywords_list: {keywords_list}")

src/llm_models/utils_model.py

@@ -287,6 +287,7 @@ class LLMRequest:
         # 模型选择和请求准备
         start_time = time.time()
         model_info, api_provider, client = self._select_model()
+        model_name = model_info.name
         
         # 检查是否启用反截断
         use_anti_truncation = getattr(self.model_for_task, "anti_truncation", False)
@@ -403,7 +404,7 @@ class LLMRequest:
         # 重试失败
         if raise_when_empty:
             raise RuntimeError(f"经过 {max_empty_retry} 次重试后仍然无法生成有效回复")
-        return "生成的响应为空，请检查模型配置或输入内容是否正确", ("", model_info.name, None)
+        return "生成的响应为空，请检查模型配置或输入内容是否正确", ("", model_name, None)
 
     async def get_embedding(self, embedding_input: str) -> Tuple[List[float], str]:
         """获取嵌入向量
@@ -565,7 +566,7 @@ class LLMRequest:
         Returns:
             (等待间隔（如果为0则不等待，为-1则不再请求该模型）, 新的消息列表（适用于压缩消息）)
         """
-        model_name = model_info.name
+        model_name = model_info.name if model_info else "unknown"
 
         if isinstance(e, NetworkConnectionError):  # 网络连接错误
             return self._check_retry(

src/plugins/built_in/maizone_refactored/services/cookie_service.py

@@ -58,7 +58,7 @@ class CookieService:
             else:
                 response = await send_api.adapter_command_to_stream(action="get_cookies", params=params, platform="qq", timeout=40.0)
 
-            if response.get("status") == "ok":
+            if response and response.get("status") == "ok":
                 cookie_str = response.get("data", {}).get("cookies", "")
                 if cookie_str:
                     return {k.strip(): v.strip() for k, v in (p.split('=', 1) for p in cookie_str.split('; ') if '=' in p)}