diff --git a/api_send_evaluate.py b/api_send_evaluate.py
index 95d8009..fb877db 100644
--- a/api_send_evaluate.py
+++ b/api_send_evaluate.py
@@ -45,7 +45,7 @@ def classify_features(features_data_list):
     返回:
     dict: 包含分类结果和模型文件信息的字典
     """
-    response = requests.post("http://p2p1.melulu.top:3397/evaluate/", json=features_data_list)
+    response = requests.post("http://127.0.0.1:8088/evaluate/", json=features_data_list)
     if response.status_code == 200:
         results = response.json()
         print("Precision:", results["classification_result"]["precision"])
diff --git a/api_send_inference.py b/api_send_inference.py
index a6813c4..0e3dbb7 100644
--- a/api_send_inference.py
+++ b/api_send_inference.py
@@ -87,7 +87,7 @@ if __name__ == "__main__":
     features_data_list = [features_data4, features_data2, features_data3, features_data1]
 
     # 发送 POST 请求
-    response = requests.post("http://p2p1.melulu.top:3397/inference/", json=features_data_list)
+    response = requests.post("http://127.0.0.1:8088/inference/", json=features_data_list)
 
     if response.status_code == 200:
         # 获取分类结果列表
diff --git a/api_send_train.py b/api_send_train.py
index 99b5a87..bbe383a 100644
--- a/api_send_train.py
+++ b/api_send_train.py
@@ -54,7 +54,7 @@ def classify_features(features_data_list):
     返回:
     dict: 包含分类结果和模型文件信息的字典
     """
-    response = requests.post("http://127.0.0.1:3397/train/", json=features_data_list)
+    response = requests.post("http://127.0.0.1:8088/train/", json=features_data_list)
     if response.status_code == 200:
         results = response.json()
         print("Precision:", results["classification_result"]["precision"])
diff --git a/psy_api.py b/psy_api.py
index 7630949..acf6bd6 100644
--- a/psy_api.py
+++ b/psy_api.py
@@ -4,6 +4,8 @@ import datetime
 import logging
 import shutil
 import uvicorn
+import schedule
+import threading
 import yaml
 import numpy as np
 from fastapi import FastAPI, Request, File, UploadFile
@@ -20,6 +22,12 @@ app = FastAPI()
 # 控制是否打印的宏定义
 PRINT_LOG = True
 
+# 日志保留天数
+DAYS = 1
+
+# 清理文件夹
+DIRS = ["train_api", "inference_api", "evaluate_api"]
+
 # 初始化配置文件
 config_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "config/config.yaml"))
 
@@ -69,6 +77,32 @@ def update_log_handler(log_path):
     file_handler.setFormatter(logging.Formatter('%(asctime)s %(levelname)s: %(message)s', datefmt='%Y-%m-%d %H:%M:%S'))
     logger.addHandler(file_handler)
 
+# 定义清理旧文件的函数
+def clean_old_files(directory, days=DAYS):
+    now = time.time()
+    cutoff = now - (days * 86400)  # 1天前的时间戳
+
+    for root, dirs, files in os.walk(directory):
+        for file in files:
+            file_path = os.path.join(root, file)
+            if os.path.getmtime(file_path) < cutoff:
+                os.remove(file_path)
+                log_print(f"Removed old file: {file_path}")
+
+# 定期清理任务
+def schedule_cleanup():
+    directories = DIRS
+    for directory in directories:
+        abs_directory = os.path.abspath(os.path.join(os.path.dirname(__file__), directory))
+        clean_old_files(abs_directory)
+
+# 启动定时任务
+def start_scheduler():
+    schedule.every(1).hours.do(schedule_cleanup)
+    while True:
+        schedule.run_pending()
+        time.sleep(1)
+
 # 定义训练接口
 @app.post("/train/")
 async def train_model(request: Request, features_list: List[Features]):
@@ -344,4 +378,10 @@ if __name__ == "__main__":
     app.mount("/evaluate_api", StaticFiles(directory=static_dir_evaluate), name="static_dir_evaluate")
     app.mount("/inference_api", StaticFiles(directory=static_dir_inference), name="static_dir_inference")
     app.mount("/models", StaticFiles(directory=static_dir_models), name="static_dir_models")
-    uvicorn.run(app, host="0.0.0.0", port=8088, reload=False)
\ No newline at end of file
+
+    # 启动定时任务
+    scheduler_thread = threading.Thread(target=start_scheduler)
+    scheduler_thread.daemon = True
+    scheduler_thread.start()
+
+    uvicorn.run(app, host="0.0.0.0", port=8089, reload=False)
\ No newline at end of file