Querying the AI Application List

Function

This API is used to query the AI application list based on different search parameters.

URI

GET /v1/{project_id}/models

**Table 1** Path Parameters
Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details, see Obtaining a Project ID and Name.

**Table 2** Query Parameters
Parameter	Mandatory	Type	Description
model_name	No	String	Model name. Fuzzy match is supported. 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.
exact_match	No	String	Whether to escape underscores (). If a model name contains underscores (), set this parameter to true to ensure that the query operation can be performed properly. By default, this parameter is left blank.
model_version	No	String	Model version The format is Digit:Digit:Digit, where Digit is a one-digit or two-digit positive integer. Note that the version number cannot start with 0, for example, 01.01.01.
model_status	No	String	Model status. You can obtain models based on model statuses. Options: publishing: The model is being published. published: The model has been published. failed: Publishing the model failed. building: The image is being created. building_failed: Creating an image failed.
description	No	String	Description. Fuzzy match is supported.
offset	No	Integer	Index of the query page, which defaults to 0
limit	No	Integer	Maximum number of records returned on each page. Default value: 1000
sort_by	No	String	Sorting field. Options: create_at: time when an AI application is created (default value) model_version: AI application version model_size: AI application size
order	No	String	Sorting mode. Options: asc: ascending order desc: descending order (default value)
workspace_id	No	String	Workspace ID, which defaults to 0
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. The value can be TensorFlow, PyTorch, MindSpore, Image, Custom or Template.
not_model_type	No	String	Model type, which is used for obtaining models of types except for this type The value can be TensorFlow, PyTorch, MindSpore, Image, Custom or Template.

Request Parameters

**Table 3** Request header parameters
Parameter	Mandatory	Type	Description
X-Auth-Token	Yes	String	User token. It can be obtained by calling the IAM API that is used to obtain a user token. The value of X-Subject-Token in the response header is the user token.

Response Parameters

Status code: 200

**Table 4** Response body parameters
Parameter	Type	Description
models	Array of ModelListItem objects	Model metadata
total_count	Integer	Total number of models that meet the search criteria when no paging is performed
count	Integer	Total number of models that meet the search criteria

**Table 5** ModelListItem
Parameter	Type	Description
owner	String	User ID of the tenant to which a model belongs
model_version	String	Model version
model_type	String	Model type
description	String	Model description
project	String	Project ID of the tenant to which a model belongs
source_type	String	Model source type. This parameter is valid and its value is auto only if the model is deployed using ExeML.
model_id	String	Model ID
model_source	String	Model source. Options: auto: ExeML algos: built-in algorithm custom: custom model
install_type	Array of strings	Deployment types supported by a model
model_size	Integer	Model size, in bytes
workspace_id	String	Workspace ID. Value 0 indicates the default workspace.
model_status	String	Model status
market_flag	Boolean	Whether a model is subscribed from AI Gallery
tunable	Boolean	Whether a model can be tuned. true indicates that the model can be tuned, and false indicates not.
model_name	String	Model name
create_at	Long	Time when a model is created, in milliseconds calculated from 1970.1.1 0:0:0 UTC.
publishable_flag	Boolean	Whether a model can be published to AI Gallery
source_copy	String	Whether to enable image replication. This parameter is valid only when model_type is set to Image. true: Image replication is enabled. After this function is enabled, AI applications cannot be rapidly created, and modifying or deleting an image in the SWR source directory will not affect service deployment. false: Image replication is not enabled. After this function is disabled, AI applications can be rapidly created, but modifying or deleting an image in the SWR source directory will affect service deployment. If this parameter is not configured, image replication is enabled by default.
tenant	String	Account ID of the tenant to which a model belongs
subscription_id	String	Model subscription ID
extra	String	Extended parameter
specification	ModelSpecification object	Minimum specifications for model deployment

**Table 6** ModelSpecification
Parameter	Type	Description
min_cpu	String	Minimal CPU specifications
min_gpu	String	Minimal GPU specifications
min_memory	String	Minimum memory
min_ascend	String	Minimal Ascend specifications

Example Requests

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

Example Responses

Status code: 200

Models

{
  "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" : { }
  } ]
}