diff --git a/src/chat/express/expression_selector.py b/src/chat/express/expression_selector.py
index 781b1152..8716d6bc 100644
--- a/src/chat/express/expression_selector.py
+++ b/src/chat/express/expression_selector.py
@@ -303,4 +303,4 @@ init_prompt()
 try:
     expression_selector = ExpressionSelector()
 except Exception as e:
-    print(f"ExpressionSelector初始化失败: {e}")
+    logger.error(f"ExpressionSelector初始化失败: {e}")
diff --git a/src/chat/knowledge/qa_manager.py b/src/chat/knowledge/qa_manager.py
index b8b31efb..6bbc1dd5 100644
--- a/src/chat/knowledge/qa_manager.py
+++ b/src/chat/knowledge/qa_manager.py
@@ -60,7 +60,7 @@ class QAManager:
         for res in relation_search_res:
             if store_item := self.embed_manager.relation_embedding_store.store.get(res[0]):
                 rel_str = store_item.str
-            print(f"找到相关关系，相似度：{(res[1] * 100):.2f}%  -  {rel_str}")
+            logger.info(f"找到相关关系，相似度：{(res[1] * 100):.2f}%  -  {rel_str}")
 
         # TODO: 使用LLM过滤三元组结果
         # logger.info(f"LLM过滤三元组用时：{time.time() - part_start_time:.2f}s")
@@ -94,7 +94,7 @@ class QAManager:
 
         for res in result:
             raw_paragraph = self.embed_manager.paragraphs_embedding_store.store[res[0]].str
-            print(f"找到相关文段，相关系数：{res[1]:.8f}\n{raw_paragraph}\n\n")
+            logger.info(f"找到相关文段，相关系数：{res[1]:.8f}\n{raw_paragraph}\n\n")
 
         return result, ppr_node_weights
 
diff --git a/src/chat/memory_system/instant_memory.py b/src/chat/memory_system/instant_memory.py
index a6be80ef..48122f88 100644
--- a/src/chat/memory_system/instant_memory.py
+++ b/src/chat/memory_system/instant_memory.py
@@ -11,7 +11,7 @@ from datetime import datetime, timedelta
 from src.llm_models.utils_model import LLMRequest
 from src.common.logger import get_logger
 from src.common.database.database_model import Memory  # Peewee Models导入
-from src.config.config import model_config
+from src.config.config import model_config, global_config
 
 
 logger = get_logger(__name__)
@@ -42,7 +42,7 @@ class InstantMemory:
             request_type="memory.summary",
         )
 
-    async def if_need_build(self, text):
+    async def if_need_build(self, text: str):
         prompt = f"""
 请判断以下内容中是否有值得记忆的信息，如果有，请输出1，否则输出0
 {text}
@@ -51,8 +51,9 @@ class InstantMemory:
 
         try:
             response, _ = await self.summary_model.generate_response_async(prompt, temperature=0.5)
-            print(prompt)
-            print(response)
+            if global_config.debug.show_prompt:
+                print(prompt)
+                print(response)
 
             return "1" in response
         except Exception as e:
@@ -94,7 +95,7 @@ class InstantMemory:
             logger.error(f"构建记忆出现错误：{str(e)} {traceback.format_exc()}")
             return None
 
-    async def create_and_store_memory(self, text):
+    async def create_and_store_memory(self, text: str):
         if_need = await self.if_need_build(text)
         if if_need:
             logger.info(f"需要记忆：{text}")
@@ -142,8 +143,9 @@ class InstantMemory:
         """
         try:
             response, _ = await self.summary_model.generate_response_async(prompt, temperature=0.5)
-            print(prompt)
-            print(response)
+            if global_config.debug.show_prompt:
+                print(prompt)
+                print(response)
             if not response:
                 return None
             try: