DescribeAIDBClusterTaskAttribute - PolarDB - Alibaba Cloud Documentation Center

Retrieves the details of a task instance.

Try it now

Try this API in OpenAPI Explorer, no manual signing needed. Successful calls auto-generate SDK code matching your parameters. Download it with built-in credential security for local usage.

Test

RAM authorization

The table below describes the authorization required to call this API. You can define it in a Resource Access Management (RAM) policy. The table's columns are detailed below:

Action: The actions can be used in the Action element of RAM permission policy statements to grant permissions to perform the operation.
API: The API that you can call to perform the action.
Access level: The predefined level of access granted for each API. Valid values: create, list, get, update, and delete.
Resource type: The type of the resource that supports authorization to perform the action. It indicates if the action supports resource-level permission. The specified resource must be compatible with the action. Otherwise, the policy will be ineffective.
- For APIs with resource-level permissions, required resource types are marked with an asterisk (*). Specify the corresponding Alibaba Cloud Resource Name (ARN) in the Resource element of the policy.
- For APIs without resource-level permissions, it is shown as All Resources. Use an asterisk (*) in the Resource element of the policy.
Condition key: The condition keys defined by the service. The key allows for granular control, applying to either actions alone or actions associated with specific resources. In addition to service-specific condition keys, Alibaba Cloud provides a set of common condition keys applicable across all RAM-supported services.
Dependent action: The dependent actions required to run the action. To complete the action, the RAM user or the RAM role must have the permissions to perform all dependent actions.

Action

Access level

Resource type

Condition key

Dependent action

polardb:DescribeAIDBClusterTaskAttribute

none

*All Resource

*

None

Request syntax

POST  HTTP/1.1

Request parameters

Parameter	Type	Required	Description	Example
RegionId	string	No	The region ID.	cn-beijing
DBClusterId	string	No	The task ID.	pm-2ze99***
DescribeType	string	No	The query mode. Valid values: RelatedAITask: queries task details.	RelatedAITask

Response elements

Element	Type	Description	Example
	object	Schema of Response
RequestId	string	Id of the request	45D24263-7E3A-4140-9472-************
DBType	string	The engine type.	polardb_ai
DBVersion	string	The version. Valid values: 3.1: model operator tuning.	3.1
DBClusterId	string	The task ID.	pm-2ze99***
DBClusterStatus	string	The training status. Valid values: ACTIVATION: Training in progress. COMPLETED: Training succeeded. FAILED: Training failed.	COMPLETED
ClusterNetworkType	string	The network type of the cluster.	VPC
ModelPath	string	The list of model paths output in the model fine-tuning scenario.	/models_train/pm-2ze9*/merged_models_checkpoint-10,/models_train/pm-2ze9*/merged_models_checkpoint-5
CreateTime	string	The creation time.	2025-11-12T03:45:13Z
KindCode	integer	The type of the instance. Valid values: 18.	18
MaintainStartTime	string	The maintenance start time.	8:00Z
MaintainEndTime	string	The maintenance end time.	12:00Z
DataSets	array<object>	The datasets.
	object	The datasets.
DatasetName	string	The dataset name.	dataset02
Path	string	The dataset path.	polardb_ai/datasets/train/grpo/dataset02/test-**.jsonl#1000
SplitDatasetRatio	string	The ratio split from the training set.	0.1
Type	string	The type. Valid values: train: training set. eval: validation set.	train
TaskInfo	array<object>	The task information.
	object	The task information.
ModelName	string	The foundation model.	Qwen-1.7B
TrainType	string	The training method. Valid values: lora full: full-parameter fine-tuning.	lora
TrainMode	string	The task type. Valid values: sft: SFT efficient training. grpo: GRPO reinforcement learning.	stf
ModelPath	string	The path of the custom model.	Qwen-1.7B
ModelSource	string	The model source. Valid values: public: pre-trained model. custom: custom model.	public
RunningTimes	string	The runtime parameters.	{"split_dataset_ratio": 0.1,"train_mode": "grpo","train_type": "lora","num_epochs": 1,"batch_size": 2,"eval_batch_size": 2, "num_generations": 2, "learning_rate": "1e-6", "data_file_list": "test-00000-of-00001.jsonl#1000", "lora_rank": 8, "lora_alpha": 32, "external_plugins": "/plugin/train/plugin.py", "reward_funcs": "format,external_countdown", "gpu_memory_utilization": 0.4}
StartTime	string	The task start time.	2025-09-10T01:56:00Z
CompletedTime	string	The task completion time.	2025-09-10T01:56:00Z
LockMode	string	The lock mode. Valid values: 0: locked. 1: unlocked.	1
DBClusterStatusDesc	string	The training status. Valid values: ACTIVATION: Training in progress. COMPLETED: Training succeeded. FAILED: Training failed.	COMPLETED
AccessInfo	string	The access information of the model in the test deployment scenario.	{\"networkInterfaceId\":\"eni-2zea*\",\"port\":\"8000\",\"host\":\"192...\"}
ExtraInfo	array<object>	The additional information, including runtime parameters.
	object	The additional information, including runtime parameters.	{"outputPath":"/output/models_train/pm-2ze9***"}
VPCId	string	The VPC ID.	vpc-**********
VSwitchId	string	The vSwitch ID.	vsw-*********************
DBClusterDescription	string	The task name.	task01
TuneArch	string
CustomBucketInfo	object
CustomOssBucketName	string		my-bucket

Examples

Success response

JSON format

{
  "RequestId": "45D24263-7E3A-4140-9472-************",
  "DBType": "polardb_ai",
  "DBVersion": "3.1",
  "DBClusterId": "pm-2ze99***\n",
  "DBClusterStatus": "COMPLETED",
  "ClusterNetworkType": "VPC",
  "ModelPath": "/models_train/pm-2ze9***/merged_models_checkpoint-10,/models_train/pm-2ze9***/merged_models_checkpoint-5",
  "CreateTime": "2025-11-12T03:45:13Z",
  "KindCode": 18,
  "MaintainStartTime": "8:00Z",
  "MaintainEndTime": "12:00Z",
  "DataSets": [
    {
      "DatasetName": "dataset02",
      "Path": "polardb_ai/datasets/train/grpo/dataset02/test-**.jsonl#1000",
      "SplitDatasetRatio": "0.1",
      "Type": "train"
    }
  ],
  "TaskInfo": [
    {
      "ModelName": "Qwen-1.7B",
      "TrainType": "lora",
      "TrainMode": "stf",
      "ModelPath": "Qwen-1.7B",
      "ModelSource": "public",
      "RunningTimes": "{\"split_dataset_ratio\": 0.1,\"train_mode\": \"grpo\",\"train_type\": \"lora\",\"num_epochs\": 1,\"batch_size\": 2,\"eval_batch_size\": 2, \"num_generations\": 2, \"learning_rate\": \"1e-6\", \"data_file_list\": \"test-00000-of-00001.jsonl#1000\", \"lora_rank\": 8, \"lora_alpha\": 32, \"external_plugins\": \"/plugin/train/plugin.py\", \"reward_funcs\": \"format,external_countdown\", \"gpu_memory_utilization\": 0.4}\n",
      "StartTime": "2025-09-10T01:56:00Z",
      "CompletedTime": "2025-09-10T01:56:00Z"
    }
  ],
  "LockMode": "1",
  "DBClusterStatusDesc": "COMPLETED",
  "AccessInfo": "{\\\"networkInterfaceId\\\":\\\"eni-2zea***\\\",\\\"port\\\":\\\"8000\\\",\\\"host\\\":\\\"192.**.**.**\\\"}",
  "ExtraInfo": [
    {
      "outputPath": "/output/models_train/pm-2ze9***"
    }
  ],
  "VPCId": "vpc-**********",
  "VSwitchId": "vsw-*********************",
  "DBClusterDescription": "task01",
  "TuneArch": "",
  "CustomBucketInfo": {
    "CustomOssBucketName": "my-bucket"
  }
}

Error codes

HTTP status code	Error code	Error message	Description
404	InvalidDBClusterId.NotFound	The DBInstanceId provided does not exist in our records.	The specified DBClusterId parameter does not exist in the current record.

See Error Codes for a complete list.

Release notes

See Release Notes for a complete list.