diff --git a/flask_app/general/llm/qianwen_plus.py b/flask_app/general/llm/qianwen_plus.py
index 864e9e8..aaf63a8 100644
--- a/flask_app/general/llm/qianwen_plus.py
+++ b/flask_app/general/llm/qianwen_plus.py
@@ -149,5 +149,6 @@ if __name__ == "__main__":
         "偏离":"所有参数需在技术响应偏离表内响应，如应答有缺项，且无有效证明材料的，评标委员会有权不予认可，视同负偏离处理"
     }
         """
-    res = qianwen_plus(user_query1)
-    print(res)
\ No newline at end of file
+    res,a = qianwen_plus(user_query1,True)
+    print(res)
+    print(a)
\ No newline at end of file
diff --git a/flask_app/general/llm/大模型通用函数.py b/flask_app/general/llm/大模型通用函数.py
index 90e86c8..472a001 100644
--- a/flask_app/general/llm/大模型通用函数.py
+++ b/flask_app/general/llm/大模型通用函数.py
@@ -9,7 +9,7 @@ import requests
 from flask_app.general.读取文件.clean_pdf import extract_common_header, clean_page_content
 
 @sleep_and_retry
-@limits(calls=10, period=1)  # 每秒最多调用20次，qpm=1200万，两个服务器分流，每个10
+@limits(calls=9, period=1)  # 每秒最多调用20次，qpm=1200万，两个服务器分流，每个10  //吃满可能有问题，改为9
 def rate_limiter():
     pass  # 这个函数本身不执行任何操作，只用于限流
 
diff --git a/flask_app/test_case/test_函数并发限制.py b/flask_app/test_case/test_函数并发限制.py
index c6f9357..5ff27a9 100644
--- a/flask_app/test_case/test_函数并发限制.py
+++ b/flask_app/test_case/test_函数并发限制.py
@@ -1,72 +1,50 @@
 import time
+import concurrent.futures
 from ratelimit import limits, sleep_and_retry
-from threading import Thread
 from functools import wraps
 
-
-# 定义共享的限流器：每秒最多调用4次
+# 共享限流器：每秒最多允许 4 次调用
 @sleep_and_retry
 @limits(calls=4, period=1)
 def rate_limiter():
-    pass  # 此函数仅用于限流控制，不执行任何操作
+    current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
+    print(f"[限流器] {current_time} - Rate limiter invoked")
+    pass  # 此函数仅用于限流控制
 
-# 创建一个共享的装饰器，在被装饰函数 (func) 执行之前，先调用 rate_limiter()。
+# 创建一个共享装饰器，在被装饰函数执行之前先调用 rate_limiter()
 def shared_rate_limit(func):
     @wraps(func)
     def wrapper(*args, **kwargs):
-        rate_limiter()  # 应用共享的限流器
+        rate_limiter()  # 先调用限流器
         return func(*args, **kwargs)
-
     return wrapper
 
-
+# 被装饰的测试函数，每次调用会输出调用编号和当前时间
 @shared_rate_limit
-def limited_test_func(counter, thread_name):
-    print(f"Thread {thread_name} - limited_test_func called {counter}")
-    return f"Thread {thread_name} - limited_test_func result {counter}"
+def test_function(index):
+    current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
+    print(f"[测试函数] {current_time} - Test function {index} executed")
+    return current_time
 
-
-@shared_rate_limit
-def another_limited_func(counter, thread_name):
-    print(f"Thread {thread_name} - another_limited_func called {counter}")
-    return f"Thread {thread_name} - another_limited_func result {counter}"
-
-
-def thread_function(thread_name):
-    for i in range(1, 21):  # 每个线程序号从1到20
-        # 先调用 limited_test_func
-        try:
-            result = limited_test_func(counter=i, thread_name=thread_name)
-            print(result)
-        except Exception as e:
-            print(f"Thread {thread_name} - limited_test_func Error: {e}")
-            print("超时")
-
-        # 然后调用 another_limited_func
-        try:
-            result = another_limited_func(counter=i, thread_name=thread_name)
-            print(result)
-        except Exception as e:
-            print(f"Thread {thread_name} - another_limited_func Error: {e}")
-            print("超时")
-
-#1s执行4次，每个线程执行20*2次，5个线程。预计耗时50s
-if __name__ == "__main__":
-    # 定义多个线程，每个线程负责调用两个函数1到20的数字
-    threads = []
-    num_threads = 5  # 启动5个线程
+def main():
     start_time = time.time()
+    print("开始测试:", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(start_time)))
+    num_calls = 100
 
-    for thread_id in range(num_threads):
-        thread_name = f"Thread-{thread_id + 1}"
-        thread = Thread(target=thread_function, args=(thread_name,))
-        threads.append(thread)
-        thread.start()
-
-    # 等待所有线程完成
-    for thread in threads:
-        thread.join()
+    # 使用线程池模拟并发执行 100 次调用
+    with concurrent.futures.ThreadPoolExecutor(max_workers=100) as executor:
+        futures = [executor.submit(test_function, i) for i in range(num_calls)]
+        # 等待所有任务完成
+        results = [future.result() for future in concurrent.futures.as_completed(futures)]
 
     end_time = time.time()
-    print("所有线程完成。")
-    print("总共耗时: {:.2f} 秒".format(end_time - start_time))
+    duration = end_time - start_time
+
+    print("\n测试结束")
+    print("开始时间:", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(start_time)))
+    print("结束时间:", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(end_time)))
+    print(f"总执行时间: {duration:.2f} 秒")
+    print("预期：由于限流规则每秒执行 4 次，100 个调用预计需要约 25 秒。")
+
+if __name__ == '__main__':
+    main()