Querying a Model List

Function

This API is used to query the models that meet the search criteria.

URI

GET /v1/{project_id}/models

Table 1 describes the required parameters.

Table 1 Parameters

Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details about how to obtain the project ID, see Obtaining a Project ID.

Table 2 Search parameters

Parameter	Mandatory	Type	Description
model_name	No	String	Model name. Fuzzy match is supported. Note If a model name contains an underscore (_), add the exact_match parameter to the request and set the parameter value to true because the underscore needs to be escaped. This ensures that the query operation can be performed properly.
model_version	No	String	Model version
model_status	No	String	Model status. You can query models based on the model status. Options: Publishing Published Failed Building Building_failed
model_type	No	String	Model type. The models of this type are queried. model_type and not_model_type are mutually exclusive and cannot co-exist.
not_model_type	No	String	Model type. A list of models of types except for this type are queried.
description	No	String	Description. Fuzzy match is supported.
offset	No	Integer	Index of the page to be queried. Default value: 0
limit	No	Integer	Maximum number of records returned on each page. The default value is 100. The recommended value ranges from 10 to 50.
sort_by	No	String	Sorting mode. The value can be create_at, model_version, or model_size. Default value: create_at
order	No	String	Sorting order. The value can be asc or desc, indicating ascending or descending order. Default value: desc
workspace_id	No	String	ID of the workspace to which a service belongs. The default value is 0, indicating the default workspace.

Request Body

None

Response Body

Table 3 describes the response parameters.

Table 3 Parameters

Parameter	Type	Description
total_count	Integer	Total number of models that meet the search criteria when no paging is implemented
count	Integer	Number of models
models	model array	Model metadata. For details, see Table 4.

Table 4 model parameters

Parameter	Type	Description
model_id	String	Model ID
model_name	String	Model name
model_version	String	Model version
model_status	String	Model status
model_type	String	Model type. The value can be TensorFlow, MXNet, Caffe, Spark_MLlib, Scikit_Learn, XGBoost, MindSpore, Image, or PyTorch.
model_size	Long	Model size, in bytes
tenant	String	Tenant to which a model belongs
project	String	Project to which a model belongs
owner	String	User to which a model belongs
create_at	Long	Time when a model is created, in milliseconds calculated from 1970.1.1 0:0:0 UTC
description	String	Model description
source_type	String	Model source type. This parameter is valid only when a model is deployed through ExeML. The value is auto. You do not need to set this parameter for a model deployed through a training job. By default, this parameter is left blank.
workspace_id	String	Workspace ID
model_source	String	Model source. Options: auto: ExeML algos: built-in algorithm custom: custom model
tunable	Boolean	Whether a model can be tuned. Options: true: yes false: no
market_flag	Boolean	Whether a model is subscribed from the marketplace. Options: true: yes false: no
publishable_flag	Boolean	Whether a model can be published to the marketplace. Options: true: yes false: no
install_type	String array	Model deployment type, determining which service a model can be deployed as. Possible values are real-time (real-time service) and batch (batch service).
subscription_id	String	Model subscription ID.
extra	String	Extended field.
specification	Object	Minimum deployment specifications. For details, see Table 5.

Table 5 Specification parameters

Parameter	Type	Description
min_cpu	String	Minimal CPU specifications
min_gpu	String	Minimal GPU specifications
min_memory	String	Minimum memory capacity

Samples

The following shows how to query models.

• Sample request

  GET    https://endpoint/v1/{project_id}/models
  

• Sample response

  {
    "total_count": 1,
    "count": 1,
    "models": [
      {
        "model_name": "mnist",
        "model_version": "1.0.0",
        "model_id": "10eb0091-887f-4839-9929-cbc884f1e20e",
        "model_type": "tensorflow",
        "model_size": 5012312,
        "tenant": "6d28e85aa78b4e1a9b4bd83501bcd4a1",
        "project": "d04c10db1f264cfeb1966deff1a3527c",
        "owner": "6d28e85aa78b4e1a9b4bd83501bcd4a1",
        "create_at": 1533041553000,
        "description": "mnist model",
        "workspace_id": "0",
        "specification":{}
      }
    ]
  }
  

Status Code

For details about the status code, see Table 1.

Error Codes

See Error Codes.

last updated: 2024-05-18 01:56