Working with the model management API

[ 1 Overview ] [ 2 Endpoints and methods ]

Overview

Check the list of available endpoints and methods in the model management API:

Endpoints and methods	Description

Endpoints and methods	Description
GET `/models/{name}`^{see below}	Get detailed information about a model.
PUT `/models/{name}`^{see below}	Replace the data of an existing model.
POST `/models/{name}`^{see below}	Create a new model.
DELETE `/models/{name}` ^{see below}	Delete a model.
PATCH `/models/{name}` ^{see below}	Update an existing model.
GET `/models/{name}` ^{see below}	List the available models in the current domain.
GET `/images/{name}` ^{see below}	Get the binary image of a model.

Endpoints and methods

GET `/models/{name}`

Get detailed information about a model.

In order to work with Model Management you need to activate Machine Learning permissions in your role. Go to Administration → Roles → Permissions → Machine Learning and activate the view and manage permissions in Models.

Learn more about roles and permissions in Role permissions.

Path parameters

Add the following path parameters as part of the endpoint:

Parameter	Type	Description

Parameter	Type	Description
`name` ^required	`string`	Enter the name of the model you want to get information about.

Query string parameters

Query string parameters are optionally added after the path parameters, preceded by a question mark (?) and separated by an ampersand (&)

Parameter	Type	Description

Parameter

Type

Description

fast

boolean

If it is true, it does not show the model image in details.

Default value is -.

Example

Find below a request example in cURL language:

curl -X 'GET' \
  'https://api.stage.devo.com/mlmodelmanager/v3/models/fresh%20model' \
  -H 'accept: application/json' \
  -H 'standAloneToken: YOUR-TOKEN'

Code	Description

Code	Description
200	Returns the retrieved model. { "id": 24, "name": "fresh model", "engine": "H2O", "location": "domains/self/123456", "description": "fresh", "updateDate": 1683723909000, "creationDate": 1683723625000, "domainName": "self", "outputType": "float8", "image": { "image": 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}, "category": "Regression", "fields": [ { "id": 0, "name": "length", "description": "", "type": "float8" }, { "id": 1, "name": "entropy", "description": "", "type": "float8" }, { "id": 2, "name": "p_vowels", "description": "", "type": "float8" } ], "clusters": [], "parentId": null, "hidden": false, "runtimeSize": 78608, "fileSize": 77728 }
404	Returns a message when the model name is not found in the server.
500	Returned when an error occurred internally in the server.

PUT `/models/{name}`

Replace the data of an existing model.

In order to work with Model Management you need to activate Machine Learning permissions in your role. Go to Administration → Roles → Permissions → Machine Learning and active the view and manage permissions in Models.

Learn more about roles and permissions in Role permissions.

Path parameters

Add the following path parameters as part of the endpoint:

Parameter	Type	Description

Parameter	Type	Description
`name` ^required	`string`	Enter the name of the model you want to replace the data of.

Request body

The request JSON body must include an object with the following key-value pairs:

Parameter	Type	Description

Parameter	Type	Description
`engine`	`string`	The engine used to train and execute the model.
`fileName`	`string`
`description`	`string`	The description of the model.

Example

Find below a request example in cURL language:

curl -X 'PUT' \
  'https://api.stage.devo.com/mlmodelmanager/v3/models/fresh%20model' \
  -H 'accept: application/json' \
  -H 'standAloneToken: YOUR-TOKEN' \
  -H 'Content-Type: multipart/form-data' \
  -F 'engine=H2O' \
  -F 'fileName=@Example_test (1).zip;type=application/zip' \
  -F 'description=fresh'

Code	Description

Code	Description
200	Returns a replaced model.
500	Returned when an error occurred internally in the server.

POST `/models/{name}`

Create a model.

In order to work with Model Management you need to activate Machine Learning permissions in your role. Go to Administration → Roles → Permissions → Machine Learning and activate the view and manage permissions in Models.

Learn more about roles and permissions in Role permissions.

Path parameters

Add the following path parameters as part of the endpoint:

Parameter	Type	Description

Parameter	Type	Description
`name` ^required	`string`	Enter the name of the model you want to create.

Request body

The request JSON body must include an object with the following key-value pairs:

Parameter	Type	Description

Parameter	Type	Description
`engine`	`string`	The engine used to train and execute the model.
`fileName`	`string`
`description`	`string`	The description of the model.

Example

Find below a request example in cURL language:

DELETE `/models/{name}`

Delete a model.

PATCH `/models/{name}`

Update an existing model.

GET `/models/{name}`

List the available models in the current domain.

GET `/images/{name}`

Get the binary image of a model.

Working with the model management API

Overview

Endpoints and methods

GET /models/{name}

Path parameters

Query string parameters

Example

PUT /models/{name}

Path parameters

Request body

Example

POST /models/{name}

Path parameters

Request body

Example

DELETE /models/{name}

PATCH /models/{name}

GET /models/{name}

GET /images/{name}

GET `/models/{name}`

PUT `/models/{name}`

POST `/models/{name}`

DELETE `/models/{name}`

PATCH `/models/{name}`

GET `/models/{name}`

GET `/images/{name}`