diff --git a/doc/接口文档code.md b/doc/接口文档code.md
index c8e14da..01c50cf 100644
--- a/doc/接口文档code.md
+++ b/doc/接口文档code.md
@@ -737,43 +737,28 @@ Content-Type: application/json
 
 Request:
 {
-    "run_id": "7970364d490f4e0aa0375c2db26215f3",
+    run_id": "bd3697dc238c4d1587e0f4f319d04448",
     "method": "GridSearchCV",
     "parameters": {
-        "param_grid": {
-            "max_depth": [3, 5, 7],
-            "learning_rate": [0.01, 0.1, 0.2],
-            "n_estimators": [100, 200, 300]
-        },
-        "scoring": "accuracy",
-        "cv": 5,
-        "n_jobs": -1,
-        "verbose": 1
+        "max_depth": [3, 5, 7],
+        "n_estimators": [50, 100, 200],
+        "min_samples_split": [2, 5, 10]
     },
-    "data_path": "dataset/dataset_processed/train_val_combined.csv",
-    "output_dir": "optimized_models/",
-    "experiment_name": "xgboost_optimization"
+    "data_path": "dataset/dataset_processed/test_optimize/train.csv",
+    "output_dir": None,
+    "experiment_name": "测试模型优化方法"
 }
 
 Response:
 {
     "status": "success",
     "optimization": {
-        "id": "opt_20250220_001",
-        "run_id": "7970364d490f4e0aa0375c2db26215f3",
-        "method": "GridSearchCV",
-        "original_model": "XGBClassifier",
-        "best_params": {
-            "max_depth": 5,
-            "learning_rate": 0.1,
-            "n_estimators": 200
-        },
-        "best_score": 0.968,
-        "cv_results_file": "optimized_models/opt_20250220_001/cv_results.csv",
-        "optimized_model_id": "8970364d490f4e0aa0375c2db26215f4",
-        "execution_time": "45m 23s",
-        "status": "completed",
-        "timestamp": "2025-02-20 10:45:30"
+        
+    "status": "success",
+    "message": "优化任务已执行",
+    "run_id": "903ab190690e496aa74e6aaefac8a7cb", # 新的运行id
+    "optimized_model_id": "bd3697dc238c4d1587e0f4f319d04448" # 被优化模型的运行id
+
     }
 }
 
@@ -790,38 +775,42 @@ Error Response:
 
 ### 3.4 获取优化任务列表
 ```http
-GET /optimize/tasks?experiment_name={experiment_name}&page={page}&page_size={page_size}
+GET /optimize/tasks?experiment_name={experiment_name}&page={page}&page_size={page_size}$status={status}
 
 Response:
 {
     "status": "success",
     "tasks": [
         {
-            "id": "opt_20250220_001",
-            "run_id": "7970364d490f4e0aa0375c2db26215f3",
-            "method": "GridSearchCV",
-            "original_model": "XGBClassifier",
-            "best_score": 0.968,
-            "status": "completed",
-            "start_time": "2025-02-20 09:30:15",
-            "end_time": "2025-02-20 10:45:30",
-            "optimized_model_id": "8970364d490f4e0aa0375c2db26215f4"
+          "id": "opt_20250318_b50499",
+          "run_id": "0e7f80468ba3451d98e2ed54dafe71a6",
+          "task_id": "opt_20250318_b50499",
+          "method": "GridSearchCV",
+          "original_model": "XGBClassifier",
+          "best_score": 0.9490196078431372,
+          "status": "completed",
+          "start_time": "2025-03-18T11:30:52.586156",
+          "end_time": "2025-03-18T11:30:56.488706",
+          "experiment_name": "测试模型优化方法",
+          "optimized_model_id": "bd3697dc238c4d1587e0f4f319d04448"
         },
         {
-            "id": "opt_20250220_002",
-            "run_id": "7970364d490f4e0aa0375c2db26215f5",
-            "method": "RandomizedSearchCV",
-            "original_model": "RandomForestClassifier",
-            "best_score": 0.942,
-            "status": "completed",
-            "start_time": "2025-02-20 11:15:20",
-            "end_time": "2025-02-20 12:05:45",
-            "optimized_model_id": "8970364d490f4e0aa0375c2db26215f6"
+          "id": "opt_20250318_8de4b3",
+          "run_id": "903ab190690e496aa74e6aaefac8a7cb",
+          "task_id": "opt_20250318_8de4b3",
+          "method": "GridSearchCV",
+          "original_model": "XGBClassifier",
+          "best_score": 0.9490196078431372,
+          "status": "completed",
+          "start_time": "2025-03-18T11:36:29.244644",
+          "end_time": "2025-03-18T11:36:33.021564",
+          "experiment_name": "测试模型优化方法",
+          "optimized_model_id": "bd3697dc238c4d1587e0f4f319d04448"
         }
-    ],
-    "total_count": 2,
-    "page": 1,
-    "page_size": 10
+      ],
+      "total_count": 2,
+      "page": 1,
+      "page_size": 10
 }
 ```
 
@@ -831,42 +820,50 @@ GET /optimize/task/{task_id}
 
 Response:
 {
-    "status": "success",
-    "task": {
-        "id": "opt_20250220_001",
-        "run_id": "7970364d490f4e0aa0375c2db26215f3",
-        "method": "GridSearchCV",
-        "original_model": "XGBClassifier",
-        "parameters": {
-            "param_grid": {
-                "max_depth": [3, 5, 7],
-                "learning_rate": [0.01, 0.1, 0.2],
-                "n_estimators": [100, 200, 300]
-            },
-            "scoring": "accuracy",
-            "cv": 5,
-            "n_jobs": -1,
-            "verbose": 1
-        },
-        "best_params": {
-            "max_depth": 5,
-            "learning_rate": 0.1,
-            "n_estimators": 200
-        },
-        "best_score": 0.968,
-        "cv_results_summary": {
-            "mean_fit_time": 12.5,
-            "mean_score_time": 0.8,
-            "param_combinations": 27,
-            "score_range": [0.912, 0.968]
-        },
-        "cv_results_file": "optimized_models/opt_20250220_001/cv_results.csv",
-        "optimized_model_id": "8970364d490f4e0aa0375c2db26215f4",
-        "execution_time": "45m 23s",
-        "status": "completed",
-        "start_time": "2025-02-20 09:30:15",
-        "end_time": "2025-02-20 10:45:30"
-    }
+  "status": "success",
+  "task": {
+    "id": "opt_20250318_8de4b3",
+    "run_id": "903ab190690e496aa74e6aaefac8a7cb",
+    "experiment_id": "780687096365534715",
+    "task_id": "opt_20250318_8de4b3",
+    "method": "GridSearchCV",
+    "original_model": "XGBClassifier",
+    "parameters": {
+      "max_depth": [
+        3,
+        5,
+        7
+      ],
+      "min_samples_split": [
+        2,
+        5,
+        10
+      ],
+      "n_estimators": [
+        50,
+        100,
+        200
+      ]
+    },
+    "best_params": {},
+    "best_score": 0.9490196078431372,
+    "cv_results_summary": {
+      "mean_fit_time": 0.12129182815551758,
+      "mean_score_time": 0.005704736709594727,
+      "param_combinations": 1,
+      "score_range": [
+        0.9490196078431372,
+        0.9490196078431372
+      ]
+    },
+    "cv_results_file": "optimized_models/opt_20250318_8de4b3/cv_results.csv",
+    "optimized_model_id": "bd3697dc238c4d1587e0f4f319d04448",
+    "execution_time": "0:00:03.776920",
+    "experiment_name": "测试模型优化方法",
+    "status": "completed",
+    "start_time": "2025-03-18T11:36:29.244644",
+    "end_time": "2025-03-18T11:36:33.021564"
+  }
 }
 ```
 
@@ -898,15 +895,15 @@ DELETE /optimize/task/{task_id}
 
 Response:
 {
-    "status": "success",
-    "message": "优化任务已删除",
-    "details": {
-        "task_id": "opt_20250220_001",
-        "deleted_files": [
-            "optimized_models/opt_20250220_001/cv_results.csv",
-            "optimized_models/opt_20250220_001/optimization_log.txt"
-        ]
-    }
+  "status": "success",
+  "message": "优化任务已删除",
+  "details": {
+    "task_id": "opt_20250318_8de4b3",
+    "deleted_files": [
+      "optimized_models/opt_20250318_8de4b3/task_info.json",
+      "optimized_models/opt_20250318_8de4b3/cv_results.csv"
+    ]
+  }
 }
 
 Error Response: