diff --git a/AI/WxMini/Start.py b/AI/WxMini/Start.py
index bd6d68f5..e08aca42 100644
--- a/AI/WxMini/Start.py
+++ b/AI/WxMini/Start.py
@@ -303,10 +303,10 @@ async def reply(person_id: str = Form(...),
         logger.info(f"历史交互提示词: {history_prompt}")
 
         # NBA与CBA
-        result = await get_news(client, prompt)
-        if result is not None:
-            history_prompt = result
-            print("新闻返回了下面的内容：" + result)
+        # result = await get_news(client, prompt)
+        # if result is not None:
+        #     history_prompt = result
+        #     print("新闻返回了下面的内容：" + result)
 
         # 调用大模型，将历史交互作为提示词
         try:
@@ -643,7 +643,8 @@ async def web_recognize_content(image_url: str,
 
             # 流式传输完成后，记录到数据库
             await save_chat_to_mysql(
-                app.state.mysql_pool, person_id, f'{image_url}', summary, "", 0, 2, 2, 2, image_width, image_height
+                app.state.mysql_pool, person_id, f'{image_url}', summary, "", 0, 2, 3,
+                2, image_width, image_height
             )
 
         except asyncio.CancelledError:
@@ -654,8 +655,8 @@ async def web_recognize_content(image_url: str,
                 "success": False,
                 "message": f"生成内容失败: {str(e)}"
             })
-            print(error_response)
             yield error_response.encode("utf-8")
+            #yield error_response
 
     # 使用 StreamingResponse 返回流式结果
     return StreamingResponse(
@@ -715,7 +716,7 @@ async def web_recognize_text(image_url: str,
                         summary += char  # 拼接字符
 
             # 流式传输完成后，记录到数据库
-            await save_chat_to_mysql(app.state.mysql_pool, person_id, f'{image_url}', summary, "", 0, 2, 2, 1,
+            await save_chat_to_mysql(app.state.mysql_pool, person_id, f'{image_url}', summary, "", 0, 2, 3, 1,
                                      image_width,
                                      image_height)
 
diff --git a/AI/WxMini/Utils/NewsUtil.py b/AI/WxMini/Utils/NewsUtil.py
index 65ded7ad..6cb9cfc3 100644
--- a/AI/WxMini/Utils/NewsUtil.py
+++ b/AI/WxMini/Utils/NewsUtil.py
@@ -17,7 +17,8 @@ def extract_keywords(user_input):
     # 使用 jieba 进行分词
     words = jieba.lcut(user_input)
     # 过滤掉无意义的词（如标点符号、停用词等）
-    stop_words = ['的', '了', '吗', '呢', '是', '在', '啊', '呀', '怎么', '怎么样', '今天','今日', '？', '，', '。']
+    stop_words = ['的', '了', '吗', '呢', '是', '在', '啊', '呀', '怎么', '怎么样', '最近', '今天', '今日', '？', '，',
+                  '。']
     keywords = [word for word in words if word not in stop_words]
     return keywords