Label Studio Subpackage Ml API
The subpackage_ml API from Label Studio — 6 operation(s) for subpackage_ml.
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OpenAPI Specification
openapi: 3.2.0
info:
title: Reference Subpackage Ml API
version: 1.0.0
servers:
- url: http://localhost:8000
tags:
- name: subpackage_ml
paths:
/api/ml/:
get:
operationId: list
summary: List ML backends
description: 'List all configured ML backends for a specific project by ID.
Use the following cURL command:
```bash
curl http://localhost:8000/api/ml?project={project_id} -H ''Authorization: Token abc123'''
tags:
- subpackage_ml
parameters:
- name: project
in: query
description: Project ID
required: false
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: ''
content:
application/json:
schema:
type: array
items:
$ref: '#/components/schemas/MLBackend'
post:
operationId: create
summary: Add ML Backend
description: 'Add an ML backend to a project using the Label Studio UI or by sending a POST request using the following cURL
command:
```bash
curl -X POST -H ''Content-type: application/json'' http://localhost:8000/api/ml -H ''Authorization: Token abc123''\
--data ''{"url": "http://localhost:9090", "project": {project_id}}'''
tags:
- subpackage_ml
parameters:
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'201':
description: ''
content:
application/json:
schema:
$ref: '#/components/schemas/MLBackend'
requestBody:
content:
application/json:
schema:
type: object
properties:
auth_method:
$ref: '#/components/schemas/ApiMlPostRequestBodyContentApplicationJsonSchemaAuthMethod'
description: Auth method
basic_auth_pass:
type: string
description: Basic auth password
basic_auth_user:
type: string
description: Basic auth user
description:
type: string
description: Description
extra_params:
$ref: '#/components/schemas/ApiMlPostRequestBodyContentApplicationJsonSchemaExtraParams'
description: Extra parameters
is_interactive:
type: boolean
description: Is interactive
project:
type: integer
description: Project ID
timeout:
type: integer
description: Response model timeout
title:
type: string
description: Title
url:
type: string
description: ML backend URL
/api/ml/{id}:
get:
operationId: get
summary: Get ML Backend
description: 'Get details about a specific ML backend connection by ID. For example, make a GET request using the
following cURL command:
```bash
curl http://localhost:8000/api/ml/{ml_backend_ID} -H ''Authorization: Token abc123'''
tags:
- subpackage_ml
parameters:
- name: id
in: path
required: true
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: ''
content:
application/json:
schema:
$ref: '#/components/schemas/MLBackend'
delete:
operationId: delete
summary: Remove ML Backend
description: 'Remove an existing ML backend connection by ID. For example, use the
following cURL command:
```bash
curl -X DELETE http://localhost:8000/api/ml/{ml_backend_ID} -H ''Authorization: Token abc123'''
tags:
- subpackage_ml
parameters:
- name: id
in: path
required: true
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: Successful response
patch:
operationId: update
summary: Update ML Backend
description: 'Update ML backend parameters using the Label Studio UI or by sending a PATCH request using the following cURL command:
```bash
curl -X PATCH -H ''Content-type: application/json'' http://localhost:8000/api/ml/{ml_backend_ID} -H ''Authorization: Token abc123''\
--data ''{"url": "http://localhost:9091"}'''
tags:
- subpackage_ml
parameters:
- name: id
in: path
required: true
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: ''
content:
application/json:
schema:
$ref: '#/components/schemas/MLBackend'
requestBody:
content:
application/json:
schema:
type: object
properties:
auth_method:
$ref: '#/components/schemas/ApiMlIdPatchRequestBodyContentApplicationJsonSchemaAuthMethod'
description: Auth method
basic_auth_pass:
type: string
description: Basic auth password
basic_auth_user:
type: string
description: Basic auth user
description:
type: string
description: Description
extra_params:
$ref: '#/components/schemas/ApiMlIdPatchRequestBodyContentApplicationJsonSchemaExtraParams'
description: Extra parameters
is_interactive:
type: boolean
description: Is interactive
project:
type: integer
description: Project ID
timeout:
type: integer
description: Response model timeout
title:
type: string
description: Title
url:
type: string
description: ML backend URL
/api/ml/{id}/interactive-annotating:
post:
operationId: predict-interactive
summary: Request Interactive Annotation
description: 'Send a request to the machine learning backend set up to be used for interactive preannotations to retrieve a
predicted region based on annotator input.
See set up machine learning for more.'
tags:
- subpackage_ml
parameters:
- name: id
in: path
description: A unique integer value identifying this ML backend.
required: true
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: Interactive annotation has succeeded.
content:
application/json:
schema:
$ref: '#/components/schemas/ml_predict_interactive_Response_200'
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/MLInteractiveAnnotatingRequestRequest'
/api/ml/{id}/predict:
post:
operationId: predict-all-tasks
summary: ✨ Create predictions for all tasks
description: 'This endpoint is not available in Label Studio Community Edition. Learn more about Label Studio Enterprise
Create predictions for all tasks using a specific ML backend so that you can set up an active learning strategy based on the confidence or uncertainty scores associated with the predictions. Creating predictions requires a Label Studio ML backend set up and configured for your project.
See Set up machine learning for more details about a Label Studio ML backend.
Reference the ML backend ID in the path of this API call. Get the ML backend ID by listing the ML backends for a project.'
tags:
- subpackage_ml
parameters:
- name: id
in: path
description: A unique integer value identifying this ML backend.
required: true
schema:
type: integer
- name: batch_size
in: query
description: Computed number of tasks without predictions that the ML backend needs to predict.
required: false
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: Predictions have successfully started.
content:
application/json:
schema:
$ref: '#/components/schemas/ml_predict_all_tasks_Response_200'
/api/ml/{id}/train:
post:
operationId: train
summary: Train
description: 'After you add an ML backend, call this API with the ML backend ID to start training with
already-labeled tasks.
Get the ML backend ID by listing the ML backends for a project.'
tags:
- subpackage_ml
parameters:
- name: id
in: path
description: A unique integer value identifying this ML backend.
required: true
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: Training has successfully started.
content:
application/json:
schema:
$ref: '#/components/schemas/ml_train_Response_200'
'500':
description: Training error
content:
application/json:
schema:
type: string
requestBody:
content:
application/json:
schema:
type: object
properties:
use_ground_truth:
type: boolean
description: Whether to include ground truth annotations in training
/api/ml/{id}/versions:
get:
operationId: list-model-versions
summary: Get model versions
description: Get available versions of the model.
tags:
- subpackage_ml
parameters:
- name: id
in: path
required: true
schema:
type: integer
- name: Authorization
in: header
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'
required: true
schema:
type: string
responses:
'200':
description: List of available versions.
content:
application/json:
schema:
$ref: '#/components/schemas/ml_list_model_versions_Response_200'
components:
schemas:
ApiMlIdPatchRequestBodyContentApplicationJsonSchemaExtraParams:
type: object
properties: {}
description: Extra parameters
title: ApiMlIdPatchRequestBodyContentApplicationJsonSchemaExtraParams
ApiMlIdPatchRequestBodyContentApplicationJsonSchemaAuthMethod:
type: string
enum:
- NONE
- BASIC_AUTH
description: Auth method
title: ApiMlIdPatchRequestBodyContentApplicationJsonSchemaAuthMethod
ApiMlPostRequestBodyContentApplicationJsonSchemaExtraParams:
type: object
properties: {}
description: Extra parameters
title: ApiMlPostRequestBodyContentApplicationJsonSchemaExtraParams
AuthMethodEnum:
type: string
enum:
- NONE
- BASIC_AUTH
description: '* `NONE` - None
* `BASIC_AUTH` - Basic Auth'
title: AuthMethodEnum
ml_train_Response_200:
type: object
properties: {}
description: Empty response body
title: ml_train_Response_200
ml_predict_all_tasks_Response_200:
type: object
properties: {}
description: Empty response body
title: ml_predict_all_tasks_Response_200
MLInteractiveAnnotatingRequestRequest:
type: object
properties:
context:
oneOf:
- description: Any type
- type: 'null'
description: Context for ML model
task:
type: integer
description: ID of task to annotate
required:
- task
description: Serializer for ML interactive annotating request.
title: MLInteractiveAnnotatingRequestRequest
ml_predict_interactive_Response_200:
type: object
properties: {}
description: Empty response body
title: ml_predict_interactive_Response_200
ml_list_model_versions_Response_200:
type: object
properties:
message:
type: string
versions:
type: array
items:
type: string
title: ml_list_model_versions_Response_200
ApiMlPostRequestBodyContentApplicationJsonSchemaAuthMethod:
type: string
enum:
- NONE
- BASIC_AUTH
description: Auth method
title: ApiMlPostRequestBodyContentApplicationJsonSchemaAuthMethod
StateEnum:
type: string
enum:
- CO
- DI
- ER
- TR
- PR
description: '* `CO` - Connected
* `DI` - Disconnected
* `ER` - Error
* `TR` - Training
* `PR` - Predicting'
title: StateEnum
MLBackend:
type: object
properties:
auth_method:
$ref: '#/components/schemas/AuthMethodEnum'
auto_update:
type: boolean
description: If false, model version is set by the user, if true - getting latest version from backend.
basic_auth_pass_is_set:
type: boolean
basic_auth_user:
type:
- string
- 'null'
description: HTTP Basic Auth user
created_at:
type: string
format: date-time
description:
type:
- string
- 'null'
description: Description for the machine learning backend
error_message:
type:
- string
- 'null'
description: Error message in error state
extra_params:
oneOf:
- description: Any type
- type: 'null'
description: Any extra parameters passed to the ML Backend during the setup
id:
type: integer
is_interactive:
type: boolean
description: Used to interactively annotate tasks. If true, model returns one list with results
model_version:
type:
- string
- 'null'
description: Current model version associated with this machine learning backend
project:
type: integer
readable_state:
type: string
state:
$ref: '#/components/schemas/StateEnum'
timeout:
type: number
format: double
description: Response model timeout
title:
type:
- string
- 'null'
description: Name of the machine learning backend
updated_at:
type: string
format: date-time
url:
type: string
description: URL for the machine learning model server
required:
- basic_auth_pass_is_set
- created_at
- id
- project
- readable_state
- updated_at
- url
description: Serializer for MLBackend model.
title: MLBackend
securitySchemes:
Token:
type: apiKey
in: header
name: Authorization
description: 'The token (or API key) must be passed as a request header. You can find your user token on the User Account page in Label Studio. Example: <br><pre><code class="language-bash">curl https://label-studio-host/api/projects -H "Authorization: Token [your-token]"</code></pre>'