# This file was auto-generated by Fern from our API Definition.
from __future__ import annotations
import typing
from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
from ..core.request_options import RequestOptions
from ..types.batch_failed_predictions import BatchFailedPredictions
from ..types.batch_predictions import BatchPredictions
from ..types.model_interface import ModelInterface
from ..types.model_interface_serializer_get import ModelInterfaceSerializerGet
from ..types.paginated_all_roles_project_list_list import PaginatedAllRolesProjectListList
from ..types.paginated_project_subset_tasks_response_list import PaginatedProjectSubsetTasksResponseList
from ..types.project_subset_item import ProjectSubsetItem
from ..types.skill_name_enum import SkillNameEnum
from ..types.user_simple_request import UserSimpleRequest
from .raw_client import AsyncRawPromptsClient, RawPromptsClient
from .types.compatible_projects_prompts_request_project_type import CompatibleProjectsPromptsRequestProjectType
if typing.TYPE_CHECKING:
from .indicators.client import AsyncIndicatorsClient, IndicatorsClient
from .runs.client import AsyncRunsClient, RunsClient
from .versions.client import AsyncVersionsClient, VersionsClient
# this is used as the default value for optional parameters
OMIT = typing.cast(typing.Any, ...)
class PromptsClient:
def __init__(self, *, client_wrapper: SyncClientWrapper):
self._raw_client = RawPromptsClient(client_wrapper=client_wrapper)
self._client_wrapper = client_wrapper
self._indicators: typing.Optional[IndicatorsClient] = None
self._versions: typing.Optional[VersionsClient] = None
self._runs: typing.Optional[RunsClient] = None
@property
def with_raw_response(self) -> RawPromptsClient:
"""
Retrieves a raw implementation of this client that returns raw responses.
Returns
-------
RawPromptsClient
"""
return self._raw_client
def batch_failed_predictions(
self,
*,
failed_predictions: typing.Sequence[typing.Any],
modelrun_id: int,
num_failed_predictions: typing.Optional[int] = None,
job_id: typing.Optional[str] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> BatchFailedPredictions:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Create a new batch of failed predictions.
Parameters
----------
failed_predictions : typing.Sequence[typing.Any]
modelrun_id : int
num_failed_predictions : typing.Optional[int]
Number of failed predictions being sent (for telemetry only, has no effect)
job_id : typing.Optional[str]
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
BatchFailedPredictions
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.batch_failed_predictions(
failed_predictions=[],
modelrun_id=1,
)
"""
_response = self._raw_client.batch_failed_predictions(
failed_predictions=failed_predictions,
modelrun_id=modelrun_id,
num_failed_predictions=num_failed_predictions,
job_id=job_id,
request_options=request_options,
)
return _response.data
def batch_predictions(
self,
*,
modelrun_id: int,
results: typing.Sequence[typing.Any],
num_predictions: typing.Optional[int] = None,
job_id: typing.Optional[str] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> BatchPredictions:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Create a new batch prediction.
Parameters
----------
modelrun_id : int
results : typing.Sequence[typing.Any]
num_predictions : typing.Optional[int]
Number of predictions being sent (for telemetry only, has no effect)
job_id : typing.Optional[str]
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
BatchPredictions
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.batch_predictions(
modelrun_id=1,
results=[],
)
"""
_response = self._raw_client.batch_predictions(
modelrun_id=modelrun_id,
results=results,
num_predictions=num_predictions,
job_id=job_id,
request_options=request_options,
)
return _response.data
def subset_tasks(
self,
project_pk: int,
*,
include_total: typing.Optional[bool] = None,
model_run: typing.Optional[int] = None,
ordering: typing.Optional[str] = None,
page: typing.Optional[int] = None,
page_size: typing.Optional[int] = None,
parent_model: typing.Optional[int] = None,
project_subset: typing.Optional[str] = None,
request_options: typing.Optional[RequestOptions] = None,
) -> PaginatedProjectSubsetTasksResponseList:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Provides list of tasks, based on project subset. Includes predictions for tasks. For the 'HasGT' subset, accuracy metrics will also be provided.
Parameters
----------
project_pk : int
include_total : typing.Optional[bool]
If true (default), includes task_count in response; if false, omits it.
model_run : typing.Optional[int]
A unique ID of a ModelRun
ordering : typing.Optional[str]
Which field to use when ordering the results.
page : typing.Optional[int]
A page number within the paginated result set.
page_size : typing.Optional[int]
Number of results to return per page.
parent_model : typing.Optional[int]
The ID of the parent model (ModelInterface) for this Inference Run
project_subset : typing.Optional[str]
The project subset to retrieve tasks for
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
PaginatedProjectSubsetTasksResponseList
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.subset_tasks(
project_pk=1,
)
"""
_response = self._raw_client.subset_tasks(
project_pk,
include_total=include_total,
model_run=model_run,
ordering=ordering,
page=page,
page_size=page_size,
parent_model=parent_model,
project_subset=project_subset,
request_options=request_options,
)
return _response.data
def subsets(
self,
project_pk: int,
*,
ordering: typing.Optional[str] = None,
request_options: typing.Optional[RequestOptions] = None,
) -> typing.List[ProjectSubsetItem]:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Provides list of available subsets for a project along with count of tasks in each subset
Parameters
----------
project_pk : int
ordering : typing.Optional[str]
Which field to use when ordering the results.
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
typing.List[ProjectSubsetItem]
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.subsets(
project_pk=1,
)
"""
_response = self._raw_client.subsets(project_pk, ordering=ordering, request_options=request_options)
return _response.data
def list(
self, *, ordering: typing.Optional[str] = None, request_options: typing.Optional[RequestOptions] = None
) -> typing.List[ModelInterfaceSerializerGet]:
"""
List all prompts.
Parameters
----------
ordering : typing.Optional[str]
Which field to use when ordering the results.
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
typing.List[ModelInterfaceSerializerGet]
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.list()
"""
_response = self._raw_client.list(ordering=ordering, request_options=request_options)
return _response.data
def create(
self,
*,
title: str,
associated_projects: typing.Optional[typing.Sequence[int]] = OMIT,
created_by: typing.Optional[UserSimpleRequest] = OMIT,
description: typing.Optional[str] = OMIT,
input_fields: typing.Optional[typing.Any] = OMIT,
organization: typing.Optional[int] = OMIT,
output_classes: typing.Optional[typing.Any] = OMIT,
skill_name: typing.Optional[SkillNameEnum] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> ModelInterface:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Create a new prompt.
Parameters
----------
title : str
Model name
associated_projects : typing.Optional[typing.Sequence[int]]
created_by : typing.Optional[UserSimpleRequest]
User who created Dataset
description : typing.Optional[str]
Model description
input_fields : typing.Optional[typing.Any]
organization : typing.Optional[int]
output_classes : typing.Optional[typing.Any]
skill_name : typing.Optional[SkillNameEnum]
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
ModelInterface
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.create(
title="title",
)
"""
_response = self._raw_client.create(
title=title,
associated_projects=associated_projects,
created_by=created_by,
description=description,
input_fields=input_fields,
organization=organization,
output_classes=output_classes,
skill_name=skill_name,
request_options=request_options,
)
return _response.data
def compatible_projects(
self,
*,
ordering: typing.Optional[str] = None,
page: typing.Optional[int] = None,
page_size: typing.Optional[int] = None,
project_type: typing.Optional[CompatibleProjectsPromptsRequestProjectType] = None,
request_options: typing.Optional[RequestOptions] = None,
) -> PaginatedAllRolesProjectListList:
"""
Retrieve a list of compatible project for prompt.
Parameters
----------
ordering : typing.Optional[str]
Which field to use when ordering the results.
page : typing.Optional[int]
A page number within the paginated result set.
page_size : typing.Optional[int]
Number of results to return per page.
project_type : typing.Optional[CompatibleProjectsPromptsRequestProjectType]
Skill to filter by
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
PaginatedAllRolesProjectListList
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.compatible_projects()
"""
_response = self._raw_client.compatible_projects(
ordering=ordering,
page=page,
page_size=page_size,
project_type=project_type,
request_options=request_options,
)
return _response.data
def get(self, id: str, *, request_options: typing.Optional[RequestOptions] = None) -> ModelInterfaceSerializerGet:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Retrieve a specific prompt.
Parameters
----------
id : str
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
ModelInterfaceSerializerGet
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.get(
id="id",
)
"""
_response = self._raw_client.get(id, request_options=request_options)
return _response.data
def delete(self, id: str, *, request_options: typing.Optional[RequestOptions] = None) -> None:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Delete a prompt by ID
Parameters
----------
id : str
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
None
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.delete(
id="id",
)
"""
_response = self._raw_client.delete(id, request_options=request_options)
return _response.data
def update(
self,
id: str,
*,
associated_projects: typing.Optional[typing.Sequence[int]] = OMIT,
created_by: typing.Optional[UserSimpleRequest] = OMIT,
description: typing.Optional[str] = OMIT,
input_fields: typing.Optional[typing.Any] = OMIT,
organization: typing.Optional[int] = OMIT,
output_classes: typing.Optional[typing.Any] = OMIT,
skill_name: typing.Optional[SkillNameEnum] = OMIT,
title: typing.Optional[str] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> ModelInterface:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Update a specific prompt by ID.
Parameters
----------
id : str
associated_projects : typing.Optional[typing.Sequence[int]]
created_by : typing.Optional[UserSimpleRequest]
User who created Dataset
description : typing.Optional[str]
Model description
input_fields : typing.Optional[typing.Any]
organization : typing.Optional[int]
output_classes : typing.Optional[typing.Any]
skill_name : typing.Optional[SkillNameEnum]
title : typing.Optional[str]
Model name
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
ModelInterface
Examples
--------
from label_studio_sdk import LabelStudio
client = LabelStudio(
api_key="YOUR_API_KEY",
)
client.prompts.update(
id="id",
)
"""
_response = self._raw_client.update(
id,
associated_projects=associated_projects,
created_by=created_by,
description=description,
input_fields=input_fields,
organization=organization,
output_classes=output_classes,
skill_name=skill_name,
title=title,
request_options=request_options,
)
return _response.data
@property
def indicators(self):
if self._indicators is None:
from .indicators.client import IndicatorsClient # noqa: E402
self._indicators = IndicatorsClient(client_wrapper=self._client_wrapper)
return self._indicators
@property
def versions(self):
if self._versions is None:
from .versions.client import VersionsClient # noqa: E402
self._versions = VersionsClient(client_wrapper=self._client_wrapper)
return self._versions
@property
def runs(self):
if self._runs is None:
from .runs.client import RunsClient # noqa: E402
self._runs = RunsClient(client_wrapper=self._client_wrapper)
return self._runs
class AsyncPromptsClient:
def __init__(self, *, client_wrapper: AsyncClientWrapper):
self._raw_client = AsyncRawPromptsClient(client_wrapper=client_wrapper)
self._client_wrapper = client_wrapper
self._indicators: typing.Optional[AsyncIndicatorsClient] = None
self._versions: typing.Optional[AsyncVersionsClient] = None
self._runs: typing.Optional[AsyncRunsClient] = None
@property
def with_raw_response(self) -> AsyncRawPromptsClient:
"""
Retrieves a raw implementation of this client that returns raw responses.
Returns
-------
AsyncRawPromptsClient
"""
return self._raw_client
async def batch_failed_predictions(
self,
*,
failed_predictions: typing.Sequence[typing.Any],
modelrun_id: int,
num_failed_predictions: typing.Optional[int] = None,
job_id: typing.Optional[str] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> BatchFailedPredictions:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Create a new batch of failed predictions.
Parameters
----------
failed_predictions : typing.Sequence[typing.Any]
modelrun_id : int
num_failed_predictions : typing.Optional[int]
Number of failed predictions being sent (for telemetry only, has no effect)
job_id : typing.Optional[str]
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
BatchFailedPredictions
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.batch_failed_predictions(
failed_predictions=[],
modelrun_id=1,
)
asyncio.run(main())
"""
_response = await self._raw_client.batch_failed_predictions(
failed_predictions=failed_predictions,
modelrun_id=modelrun_id,
num_failed_predictions=num_failed_predictions,
job_id=job_id,
request_options=request_options,
)
return _response.data
async def batch_predictions(
self,
*,
modelrun_id: int,
results: typing.Sequence[typing.Any],
num_predictions: typing.Optional[int] = None,
job_id: typing.Optional[str] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> BatchPredictions:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Create a new batch prediction.
Parameters
----------
modelrun_id : int
results : typing.Sequence[typing.Any]
num_predictions : typing.Optional[int]
Number of predictions being sent (for telemetry only, has no effect)
job_id : typing.Optional[str]
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
BatchPredictions
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.batch_predictions(
modelrun_id=1,
results=[],
)
asyncio.run(main())
"""
_response = await self._raw_client.batch_predictions(
modelrun_id=modelrun_id,
results=results,
num_predictions=num_predictions,
job_id=job_id,
request_options=request_options,
)
return _response.data
async def subset_tasks(
self,
project_pk: int,
*,
include_total: typing.Optional[bool] = None,
model_run: typing.Optional[int] = None,
ordering: typing.Optional[str] = None,
page: typing.Optional[int] = None,
page_size: typing.Optional[int] = None,
parent_model: typing.Optional[int] = None,
project_subset: typing.Optional[str] = None,
request_options: typing.Optional[RequestOptions] = None,
) -> PaginatedProjectSubsetTasksResponseList:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Provides list of tasks, based on project subset. Includes predictions for tasks. For the 'HasGT' subset, accuracy metrics will also be provided.
Parameters
----------
project_pk : int
include_total : typing.Optional[bool]
If true (default), includes task_count in response; if false, omits it.
model_run : typing.Optional[int]
A unique ID of a ModelRun
ordering : typing.Optional[str]
Which field to use when ordering the results.
page : typing.Optional[int]
A page number within the paginated result set.
page_size : typing.Optional[int]
Number of results to return per page.
parent_model : typing.Optional[int]
The ID of the parent model (ModelInterface) for this Inference Run
project_subset : typing.Optional[str]
The project subset to retrieve tasks for
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
PaginatedProjectSubsetTasksResponseList
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.subset_tasks(
project_pk=1,
)
asyncio.run(main())
"""
_response = await self._raw_client.subset_tasks(
project_pk,
include_total=include_total,
model_run=model_run,
ordering=ordering,
page=page,
page_size=page_size,
parent_model=parent_model,
project_subset=project_subset,
request_options=request_options,
)
return _response.data
async def subsets(
self,
project_pk: int,
*,
ordering: typing.Optional[str] = None,
request_options: typing.Optional[RequestOptions] = None,
) -> typing.List[ProjectSubsetItem]:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Provides list of available subsets for a project along with count of tasks in each subset
Parameters
----------
project_pk : int
ordering : typing.Optional[str]
Which field to use when ordering the results.
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
typing.List[ProjectSubsetItem]
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.subsets(
project_pk=1,
)
asyncio.run(main())
"""
_response = await self._raw_client.subsets(project_pk, ordering=ordering, request_options=request_options)
return _response.data
async def list(
self, *, ordering: typing.Optional[str] = None, request_options: typing.Optional[RequestOptions] = None
) -> typing.List[ModelInterfaceSerializerGet]:
"""
List all prompts.
Parameters
----------
ordering : typing.Optional[str]
Which field to use when ordering the results.
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
typing.List[ModelInterfaceSerializerGet]
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.list()
asyncio.run(main())
"""
_response = await self._raw_client.list(ordering=ordering, request_options=request_options)
return _response.data
async def create(
self,
*,
title: str,
associated_projects: typing.Optional[typing.Sequence[int]] = OMIT,
created_by: typing.Optional[UserSimpleRequest] = OMIT,
description: typing.Optional[str] = OMIT,
input_fields: typing.Optional[typing.Any] = OMIT,
organization: typing.Optional[int] = OMIT,
output_classes: typing.Optional[typing.Any] = OMIT,
skill_name: typing.Optional[SkillNameEnum] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> ModelInterface:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Create a new prompt.
Parameters
----------
title : str
Model name
associated_projects : typing.Optional[typing.Sequence[int]]
created_by : typing.Optional[UserSimpleRequest]
User who created Dataset
description : typing.Optional[str]
Model description
input_fields : typing.Optional[typing.Any]
organization : typing.Optional[int]
output_classes : typing.Optional[typing.Any]
skill_name : typing.Optional[SkillNameEnum]
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
ModelInterface
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.create(
title="title",
)
asyncio.run(main())
"""
_response = await self._raw_client.create(
title=title,
associated_projects=associated_projects,
created_by=created_by,
description=description,
input_fields=input_fields,
organization=organization,
output_classes=output_classes,
skill_name=skill_name,
request_options=request_options,
)
return _response.data
async def compatible_projects(
self,
*,
ordering: typing.Optional[str] = None,
page: typing.Optional[int] = None,
page_size: typing.Optional[int] = None,
project_type: typing.Optional[CompatibleProjectsPromptsRequestProjectType] = None,
request_options: typing.Optional[RequestOptions] = None,
) -> PaginatedAllRolesProjectListList:
"""
Retrieve a list of compatible project for prompt.
Parameters
----------
ordering : typing.Optional[str]
Which field to use when ordering the results.
page : typing.Optional[int]
A page number within the paginated result set.
page_size : typing.Optional[int]
Number of results to return per page.
project_type : typing.Optional[CompatibleProjectsPromptsRequestProjectType]
Skill to filter by
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
PaginatedAllRolesProjectListList
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.compatible_projects()
asyncio.run(main())
"""
_response = await self._raw_client.compatible_projects(
ordering=ordering,
page=page,
page_size=page_size,
project_type=project_type,
request_options=request_options,
)
return _response.data
async def get(
self, id: str, *, request_options: typing.Optional[RequestOptions] = None
) -> ModelInterfaceSerializerGet:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Retrieve a specific prompt.
Parameters
----------
id : str
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
ModelInterfaceSerializerGet
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.get(
id="id",
)
asyncio.run(main())
"""
_response = await self._raw_client.get(id, request_options=request_options)
return _response.data
async def delete(self, id: str, *, request_options: typing.Optional[RequestOptions] = None) -> None:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Delete a prompt by ID
Parameters
----------
id : str
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
None
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.delete(
id="id",
)
asyncio.run(main())
"""
_response = await self._raw_client.delete(id, request_options=request_options)
return _response.data
async def update(
self,
id: str,
*,
associated_projects: typing.Optional[typing.Sequence[int]] = OMIT,
created_by: typing.Optional[UserSimpleRequest] = OMIT,
description: typing.Optional[str] = OMIT,
input_fields: typing.Optional[typing.Any] = OMIT,
organization: typing.Optional[int] = OMIT,
output_classes: typing.Optional[typing.Any] = OMIT,
skill_name: typing.Optional[SkillNameEnum] = OMIT,
title: typing.Optional[str] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> ModelInterface:
"""
This endpoint is not available in Label Studio Community Edition. [Learn more about Label Studio Enterprise](https://humansignal.com/goenterprise)
Update a specific prompt by ID.
Parameters
----------
id : str
associated_projects : typing.Optional[typing.Sequence[int]]
created_by : typing.Optional[UserSimpleRequest]
User who created Dataset
description : typing.Optional[str]
Model description
input_fields : typing.Optional[typing.Any]
organization : typing.Optional[int]
output_classes : typing.Optional[typing.Any]
skill_name : typing.Optional[SkillNameEnum]
title : typing.Optional[str]
Model name
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
ModelInterface
Examples
--------
import asyncio
from label_studio_sdk import AsyncLabelStudio
client = AsyncLabelStudio(
api_key="YOUR_API_KEY",
)
async def main() -> None:
await client.prompts.update(
id="id",
)
asyncio.run(main())
"""
_response = await self._raw_client.update(
id,
associated_projects=associated_projects,
created_by=created_by,
description=description,
input_fields=input_fields,
organization=organization,
output_classes=output_classes,
skill_name=skill_name,
title=title,
request_options=request_options,
)
return _response.data
@property
def indicators(self):
if self._indicators is None:
from .indicators.client import AsyncIndicatorsClient # noqa: E402
self._indicators = AsyncIndicatorsClient(client_wrapper=self._client_wrapper)
return self._indicators
@property
def versions(self):
if self._versions is None:
from .versions.client import AsyncVersionsClient # noqa: E402
self._versions = AsyncVersionsClient(client_wrapper=self._client_wrapper)
return self._versions
@property
def runs(self):
if self._runs is None:
from .runs.client import AsyncRunsClient # noqa: E402
self._runs = AsyncRunsClient(client_wrapper=self._client_wrapper)
return self._runs