添加--模型管理方法添加删除模型功能

doc/接口文档code.md

@@ -456,8 +456,26 @@ Response:
 }
 
 ```
-### 2.7 删除指定的训练好的模型.
+### 2.7 删除指定的训练好的模型
+```http
+DELETE /api/models/{run_id}
 
+Response:
+{
+    "status": "success",
+    "message": "模型删除成功",
+    "details": {
+        "run_id": "7970364d490f4e0aa0375c2db26215f3",
+        "experiment_id": "656341556838275234",
+        "model_name": "XGBClassifier",
+        "deleted_artifacts": [
+            "models/7970364d490f4e0aa0375c2db26215f3/model.pkl",
+            "models/7970364d490f4e0aa0375c2db26215f3/requirements.txt",
+            "models/7970364d490f4e0aa0375c2db26215f3/conda.yaml"
+        ]
+    }
+}
+```
 
 ### 2.8 获取训练状态
 ```http

doc/时间计划.md

@@ -10,6 +10,7 @@
     - 20250219~20250220
 - [x] 实现模型训练和注册 完成
 - [x] 实现获取已有模型 完成
+- [ ] 根据删除模型
 - [ ] 根据已有模型加载模型预测
     - 2天
     

function/model_manager.py

@@ -210,6 +210,62 @@ class ModelManager:
         except Exception as e:
             error_msg = f"Error getting experiments: {str(e)}"
             self.logger.error(error_msg)
+            return {
+                'status': 'error',
+                'message': error_msg
+            }
+
+    def delete_model(self, run_id: str) -> Dict:
+        """
+        删除指定的训练好的模型
+        
+        Args:
+            run_id: MLflow运行ID
+            
+        Returns:
+            删除操作的结果信息
+        """
+        try:
+            # 获取运行信息
+            run = self.client.get_run(run_id)
+            if not run:
+                return {
+                    'status': 'error',
+                    'message': f'未找到运行ID为 {run_id} 的模型'
+                }
+            
+            # 获取实验ID
+            experiment_id = run.info.experiment_id
+            
+            # 获取模型信息
+            run_data = mlflow.get_run(run_id)
+            model_name = run_data.data.params.get('algorithm', 'Unknown')
+            
+            # 获取工件列表
+            artifacts = []
+            for artifact in self.client.list_artifacts(run_id):
+                artifacts.append(artifact.path)
+            
+            # 删除运行记录
+            self.client.delete_run(run_id)
+            
+            # 记录日志
+            self.logger.info(f"已删除模型 - Run ID: {run_id}, 实验ID: {experiment_id}, 模型: {model_name}")
+            
+            return {
+                'status': 'success',
+                'message': '模型删除成功',
+                'details': {
+                    'run_id': run_id,
+                    'experiment_id': experiment_id,
+                    'model_name': model_name,
+                    'deleted_artifacts': artifacts
+                }
+            }
+            
+        except Exception as e:
+            error_msg = f"删除模型时发生错误: {str(e)}"
+            self.logger.error(error_msg)
             return {
                 'status': 'error',
                 'message': error_msg

mlruns/656341556838275234/7970364d490f4e0aa0375c2db26215f3/meta.yaml

@@ -1,8 +1,9 @@
 artifact_uri: mlflow-artifacts:/656341556838275234/7970364d490f4e0aa0375c2db26215f3/artifacts
+deleted_time: 1739959968072
 end_time: 1739954585256
 entry_point_name: ''
 experiment_id: '656341556838275234'
-lifecycle_stage: active
+lifecycle_stage: deleted
 run_id: 7970364d490f4e0aa0375c2db26215f3
 run_name: colorful-stoat-263
 run_uuid: 7970364d490f4e0aa0375c2db26215f3

mlruns/656341556838275234/c88c5a1db98f49db9d8793ad19a08809/meta.yaml

@@ -1,8 +1,9 @@
 artifact_uri: mlflow-artifacts:/656341556838275234/c88c5a1db98f49db9d8793ad19a08809/artifacts
+deleted_time: 1739959938908
 end_time: 1739954359528
 entry_point_name: ''
 experiment_id: '656341556838275234'
-lifecycle_stage: active
+lifecycle_stage: deleted
 run_id: c88c5a1db98f49db9d8793ad19a08809
 run_name: thoughtful-hawk-675
 run_uuid: c88c5a1db98f49db9d8793ad19a08809