diff --git a/.gitignore b/.gitignore
index 60635b8..d91fc0a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -160,4 +160,5 @@ cython_debug/
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
 
-uploads
\ No newline at end of file
+uploads
+scores.csv
\ No newline at end of file
diff --git a/app.py b/app.py
index 3f3df04..e91cab6 100644
--- a/app.py
+++ b/app.py
@@ -48,7 +48,7 @@ def write_to_csv(data):
     """
     file_exists = os.path.isfile(csv_file_path)
     with open(csv_file_path, mode="a", newline="", encoding="utf-8") as csvfile:
-        fieldnames = ["id", "name", "score", "details"]
+        fieldnames = ["time", "id", "name", "score", "running_time", "details"]
         writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
 
         if not file_exists:
@@ -61,7 +61,15 @@ def write_to_csv(data):
 def upload_score():
     try:
         data = request.json
-        if "name" in data and "id" in data and "score" in data and "details" in data:
+        if (
+            "name" in data
+            and "id" in data
+            and "score" in data
+            and "details" in data
+            and "running_time" in data
+            and "time" in data
+        ):
+            data["details"] = data["details"].replace("\n", "<br>")
             write_to_csv(data)
             return jsonify({"message": "成绩记录上传成功！"}), 200
         else:
diff --git a/exp/knn/main.py b/exp/knn/main.py
index 9280673..7728d67 100755
--- a/exp/knn/main.py
+++ b/exp/knn/main.py
@@ -1,7 +1,8 @@
-import requests
-import numpy as np
-import traceback
 import importlib.util
+import numpy as np
+import requests
+import time
+import traceback
 
 
 def load_user_function(file_path, function_name):
@@ -14,7 +15,9 @@ def load_user_function(file_path, function_name):
     return getattr(user_code, function_name)
 
 
-def evaluate_knn(user_func, train_data, train_labels, test_data, test_labels):
+def evaluate_knn(
+    user_func, train_data, train_labels, test_data, test_labels, log_details
+):
     """
     使用学生编写的 KNN 函数对测试集进行分类，并计算准确率。
 
@@ -24,6 +27,7 @@ def evaluate_knn(user_func, train_data, train_labels, test_data, test_labels):
     - train_labels (numpy array): 训练标签集。
     - test_data (numpy array): 测试数据集。
     - test_labels (numpy array): 测试标签集。
+    - log_details (list): 日志记录列表。
 
     Returns:
     - float: 分类准确率。
@@ -38,15 +42,22 @@ def evaluate_knn(user_func, train_data, train_labels, test_data, test_labels):
             if result == test_labels[i]:
                 correct += 1
             else:
+                log_details.append(
+                    f"第 {i+1} 次测试错误，数据 {test_data[i]} 被分类到 {result} 实际是 {test_labels[i]}"
+                )
                 print(
                     f"第 {i+1} 次测试错误，数据 {test_data[i]} 被分类到 {result} 实际是 {test_labels[i]}"
                 )
 
         accuracy = correct / total
+        log_details.append(f"分类准确率: {accuracy * 100:.2f}%")
         return accuracy
     except Exception as e:
+        log_details.append(f"评测期间发生错误: {e}")
         print(f"评测期间发生错误: {e}")
+        log_details.append(traceback.format_exc())
         print(traceback.format_exc())
+        log_details.append("成绩为零！")
         print("成绩为零！")
         return 0.0
 
@@ -71,21 +82,23 @@ def upload_score(name, id, score_data):
     """
     上传成绩到服务器。
     """
-    url = "http://10.2.1.195:5000/upload_score"
+    url = "http://10.2.1.195:880/upload_score"
     try:
         print("上传成绩中...")
-        print(score_data)
+        # print(score_data)
         response = requests.post(
             url,
             json={
                 "id": id,
                 "name": name,
                 "score": score_data["score"],
+                "running_time": score_data["running_time"],
+                "time": time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()),
                 "details": score_data["details"],
             },
         )
         if response.status_code == 200:
-            print("上传成绩成功")
+            print("上传成绩成功!")
         else:
             print("上传成绩失败:", response.json())
     except Exception as e:
@@ -93,8 +106,8 @@ def upload_score(name, id, score_data):
 
 
 def main(name, id):
-    user_code_file = "function.py"  # 学生代码文件
-    user_function_name = "classify0"  # 学生需要实现的 KNN 函数
+    user_code_file = "function.py"  # 代码文件
+    user_function_name = "classify0"  # KNN 函数名
 
     # 加载训练集和测试集
     train_file = "datingTrainSet2.tsv"
@@ -103,27 +116,52 @@ def main(name, id):
     train_data, train_labels = load_data(train_file)
     test_data, test_labels = load_data(test_file)
 
-    # 加载学生的 KNN 函数
+    # 加载自定义函数
+    log_details = []
     try:
         user_func = load_user_function(user_code_file, user_function_name)
     except Exception as e:
-        print(f"Error loading user function: {e}")
+        log_details.append(f"Error loading user function: {e}")
+        print("\n".join(log_details))
         return
 
+    # 记录评估时间
+    start_time = time.time()
+
     # 评估分类准确率
-    accuracy = evaluate_knn(user_func, train_data, train_labels, test_data, test_labels)
+    accuracy = evaluate_knn(
+        user_func, train_data, train_labels, test_data, test_labels, log_details
+    )
+
+    # 计算运行时间
+    running_time = time.time() - start_time
 
     # 输出结果
-    print(f"得分: {accuracy * 100:.2f}")
+    log_details.append(f"得分: {accuracy * 100:.2f}%")
+    log_details.append(f"运行时间: {running_time * 1000:.10f}ms")
+    print("\n".join(log_details))
+
+    # 上传成绩
+    score_data = {
+        "score": accuracy,
+        "running_time": f"{running_time * 1000:.10f}ms",
+        "details": "\n".join(log_details),  # 将日志记录加入 details 中
+    }
+
+    upload_score(name, id, score_data)
 
 
 if __name__ == "__main__":
     try:
         from function import name, id
 
+        print(f"正在评测 {name}@{id} 的代码...\n")
         main(name, id)
     except Exception as e:
-        print(f"评测出错: {e}")
-        print(traceback.format_exc())
-        print("请检查代码和返回值类型是否正确！")
-        print("本次评测无效！")
+        log_details = [
+            f"评测出错: {e}",
+            traceback.format_exc(),
+            "请检查代码和返回值类型是否正确！",
+            "本次评测无效！",
+        ]
+        print("\n".join(log_details))