Getting started

pip install label-studio-sdk

poetry add label-studio-sdk

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# Define the URL where Label Studio is accessible and the API key for your user account
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LABEL_STUDIO_URL = 'http://localhost:8080'
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# API key is available at the Account & Settings > Access Tokens page in Label Studio UI
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API_KEY = 'd6f8a2622d39e9d89ff0dfef1a80ad877f4ee9e3'
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# Import the SDK and the client module
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from label_studio_sdk.client import LabelStudio
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# Connect to the Label Studio API and check the connection
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ls = LabelStudio(base_url=LABEL_STUDIO_URL, api_key=API_KEY)

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from label_studio_sdk.labeling_interface import LabelInterface
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from label_studio_sdk.labeling_interface.create import choices
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# Define labeling interface
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label_config = LabelInterface.create({
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    'text': 'Text',
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    'label': choices(['Positive', 'Negative'])
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})
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# Create a project with the specified title and labeling configuration
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project = ls.projects.create(
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    title='Text Classification',
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    label_config=label_config
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)

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from label_studio_sdk.label_interface import LabelInterface
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from label_studio_sdk.label_interface.objects import PredictionValue
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project = ls.projects.get(id=123)
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# LabelInterface provides a handy way to validate Label Studio JSON format for annotations and predictions
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li = project.get_label_interface()
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tasks = ls.tasks.list(project=project.id, include='id')
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for task in tasks:
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    # create predicted label per task, using `label` control tag name
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    predicted_label = li.get_control('label').label(choices=['Positive'])
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    prediction = PredictionValue(
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        model_version='my-super-ai',
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        score=0.99,
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        result=[predicted_label]
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    )
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    ls.predictions.create(task=task.id, **prediction.model_dump())

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from label_studio_sdk.data_manager import Filters, Column, Type, Operator
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filters = Filters.create(Filters.AND, [
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    Filters.item(
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        Column.id,
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        Operator.GREATER_OR_EQUAL,
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        Type.Number,
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        Filters.value(1)
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    ),
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        Filters.item(
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        Column.id,
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        Operator.LESS_OR_EQUAL,
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        Type.Number,
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        Filters.value(1000)
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    ),
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    Filters.item(
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        Column.data("text"),
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        Operator.CONTAINS,
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        Type.String,
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        Filters.value("Hello")
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    )
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])

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from label_studio_sdk.data_manager import Filters, Column, Type, Operator
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filters = Filters.create(Filters.AND, [
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    Filters.item(
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        Column.completed_at,
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        Operator.EMPTY,
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        Type.Boolean,
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        Filters.value(False)
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    )
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])

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view = ls.views.create(
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    project=project.id,
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    data={
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        'title': 'Tasks Sample',
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        'filters': filters
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    }
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)
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tab = ls.views.get(id=view.id)

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tasks = ls.tasks.list(view=tab.id, fields='all')
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for task in tasks:
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    # You can access annotations in Label Studio JSON format
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    print(task.annotations)
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    # And also annotation drafts and predictions
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    print(task.predictions)
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    print(task.drafts)

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git clone https://github.com/HumanSignal/label-studio-sdk.git
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cd label-studio-sdk
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git fetch origin
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git checkout release/0.0.34

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from label_studio_sdk._legacy import Client
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from label_studio_sdk.data_manager import Filters, Column, Operator, Type
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from label_studio_sdk._legacy import Project

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from label_studio_sdk.core.api_error import ApiError
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try:
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    for annotated_task in annotated_tasks:
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        print(annotated_task.annotations)
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except ApiError as e:
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    print(e)

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from label_studio_sdk.client import LabelStudio
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ls = LabelStudio(
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    # All timeouts set to 20 seconds
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    timeout=20.0
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)
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ls.projects.create(..., {
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    # Override timeout for a specific method
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    timeout=20.0
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})

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import httpx
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from label_studio_sdk.client import LabelStudio
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ls = LabelStudio(
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    http_client=httpx.Client(
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        proxies="http://my.test.proxy.example.com",
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        transport=httpx.HTTPTransport(local_address="0.0.0.0"),
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    ),
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)