ri.apiclient.RegistryServiceApi

All URIs are relative to http://<platform-domain>.rbst.io

Method	HTTP request	Description
delete_dataset	DELETE /v1/registry/dataset/{datasetId}	DeleteDataset
delete_model	DELETE /v1/registry/model/{modelId.uuid}	DeleteModel
delete_prediction_set	DELETE /v1/registry/prediction/{modelId.uuid}/{datasetId}	DeletePredictionSet
get_dataset	GET /v1/registry/dataset	GetDataset
get_model	GET /v1/registry/model	GetModel
get_prediction_set	GET /v1/registry/prediction/{modelId.uuid}/{datasetId}	GetPredictionSet
list_datasets	GET /v1/registry/{projectId.uuid}/dataset	ListDatasets
list_models	GET /v1/registry/{projectId.uuid}/model	ListModels
list_prediction_sets	GET /v1/registry/{projectId.uuid}/prediction	ListPredictionSets
register_dataset	POST /v1/registry/{projectId.uuid}/dataset	RegisterDataset
register_model	POST /v1/registry/{projectId.uuid}/model	RegisterModel
register_prediction_set	POST /v1/registry/{projectId.uuid}/model/{modelId.uuid}/dataset/{datasetId}/prediction	RegisterPredictionSet

delete_dataset

object = delete_dataset()

DeleteDataset

Delete a Dataset from the Registry.

Parameters

Name	Type	Description	Notes
dataset_id	str	Uniquely specifies a Dataset.

Return type

object

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

dataset_id = 'dataset_id_example'  # str 

try:
    # DeleteDataset
    api_response: object = client.RegistryServiceApi.delete_dataset(dataset_id)
    print("The response of RegistryServiceApi->delete_dataset:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->delete_dataset: %s\n" % e)

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delete_model

object = delete_model()

DeleteModel

Delete a Model from the Registry.

Parameters

Name	Type	Description	Notes
model_id_uuid	str	Unique object ID.

Return type

object

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

model_id_uuid = 'model_id_uuid_example'  # str 

try:
    # DeleteModel
    api_response: object = client.RegistryServiceApi.delete_model(model_id_uuid)
    print("The response of RegistryServiceApi->delete_model:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->delete_model: %s\n" % e)

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delete_prediction_set

object = delete_prediction_set()

DeletePredictionSet

Delete the Prediction set corresponding to a specified Model and Dataset.

Parameters

Name	Type	Description	Notes
model_id_uuid	str	Unique object ID.
dataset_id	str	Uniquely specifies a Dataset.

Return type

object

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

model_id_uuid = 'model_id_uuid_example'  # str 
dataset_id = 'dataset_id_example'  # str 

try:
    # DeletePredictionSet
    api_response: object = client.RegistryServiceApi.delete_prediction_set(model_id_uuid, dataset_id)
    print("The response of RegistryServiceApi->delete_prediction_set:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->delete_prediction_set: %s\n" % e)

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get_dataset

GetDatasetResponse = get_dataset()

GetDataset

Returns information about a registered Dataset. Allows for searching by ID or name.

Parameters

Name	Type	Description	Notes
dataset_id	str	Uniquely specifies a Dataset.	[optional]
dataset_name	str	Unique name of a Dataset.	[optional]

Return type

GetDatasetResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.get_dataset_response import GetDatasetResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

dataset_id = 'dataset_id_example'  # str  (optional)
dataset_name = 'dataset_name_example'  # str  (optional)

try:
    # GetDataset
    api_response: GetDatasetResponse = client.RegistryServiceApi.get_dataset(dataset_id=dataset_id, dataset_name=dataset_name)
    print("The response of RegistryServiceApi->get_dataset:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->get_dataset: %s\n" % e)

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get_model

GetModelResponse = get_model()

GetModel

Returns information about a registered Model. Allows for searching by ID or name.

Parameters

Name	Type	Description	Notes
model_id_uuid	str	Unique object ID.	[optional]
model_name	str	Unique name of a Model.	[optional]

Return type

GetModelResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.get_model_response import GetModelResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

model_id_uuid = 'model_id_uuid_example'  # str  (optional)
model_name = 'model_name_example'  # str  (optional)

try:
    # GetModel
    api_response: GetModelResponse = client.RegistryServiceApi.get_model(model_id_uuid=model_id_uuid, model_name=model_name)
    print("The response of RegistryServiceApi->get_model:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->get_model: %s\n" % e)

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get_prediction_set

GetPredictionSetResponse = get_prediction_set()

GetPredictionSet

Returns information about a registered Prediction set.

Parameters

Name	Type	Description	Notes
model_id_uuid	str	Unique object ID.
dataset_id	str	Uniquely specifies a Dataset.

Return type

GetPredictionSetResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.get_prediction_set_response import GetPredictionSetResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

model_id_uuid = 'model_id_uuid_example'  # str 
dataset_id = 'dataset_id_example'  # str 

try:
    # GetPredictionSet
    api_response: GetPredictionSetResponse = client.RegistryServiceApi.get_prediction_set(model_id_uuid, dataset_id)
    print("The response of RegistryServiceApi->get_prediction_set:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->get_prediction_set: %s\n" % e)

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list_datasets

ListDatasetsResponse = list_datasets()

ListDatasets

List all Datasets in the Registry with optional filters.

Parameters

Name	Type	Description	Notes
project_id_uuid	str	Unique object ID.
first_page_req_scheduled_ct_intervals_start_time	datetime		[optional]
first_page_req_scheduled_ct_intervals_end_time	datetime		[optional]
page_token	str	Specifies a page of the list returned by a ListDatasets query. The ListDatasets query returns a pageToken when there is more than one page of results. Specify either this field or the firstPageReq field.	[optional]
page_size	str	The maximum number of Dataset objects to return in a single page.	[optional]

Return type

ListDatasetsResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.list_datasets_response import ListDatasetsResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

project_id_uuid = 'project_id_uuid_example'  # str 
first_page_req_scheduled_ct_intervals_start_time = '2013-10-20T19:20:30+01:00'  # datetime  (optional)
first_page_req_scheduled_ct_intervals_end_time = '2013-10-20T19:20:30+01:00'  # datetime  (optional)
page_token = 'page_token_example'  # str  (optional)
page_size = 'page_size_example'  # str  (optional)

try:
    # ListDatasets
    api_response: ListDatasetsResponse = client.RegistryServiceApi.list_datasets(project_id_uuid, first_page_req_scheduled_ct_intervals_start_time=first_page_req_scheduled_ct_intervals_start_time, first_page_req_scheduled_ct_intervals_end_time=first_page_req_scheduled_ct_intervals_end_time, page_token=page_token, page_size=page_size)
    print("The response of RegistryServiceApi->list_datasets:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->list_datasets: %s\n" % e)

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list_models

ListModelsResponse = list_models()

ListModels

List all Models in the Registry of the specified Project.

Parameters

Name	Type	Description	Notes
project_id_uuid	str	Unique object ID.
page_token	str	Specifies a page of the list returned by a ListModels query. The ListModels query returns a pageToken when there is more than one page of results. Specify either this field or the firstPageReq field.	[optional]
page_size	str	The maximum number of Model objects to return in a single page.	[optional]

Return type

ListModelsResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.list_models_response import ListModelsResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

project_id_uuid = 'project_id_uuid_example'  # str 
page_token = 'page_token_example'  # str  (optional)
page_size = 'page_size_example'  # str  (optional)

try:
    # ListModels
    api_response: ListModelsResponse = client.RegistryServiceApi.list_models(project_id_uuid, page_token=page_token, page_size=page_size)
    print("The response of RegistryServiceApi->list_models:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->list_models: %s\n" % e)

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list_prediction_sets

ListPredictionSetsResponse = list_prediction_sets()

ListPredictionSets

List all Prediction sets in the Registry with optional filters.

Parameters

Name	Type	Description	Notes
project_id_uuid	str	Unique object ID.
first_page_req_model_id	str	Uniquely specifies a Model.	[optional]
first_page_req_dataset_id	str	Uniquely specifies a Dataset.	[optional]
page_token	str	Specifies a page of the list returned by a ListPredictions query. The ListPredictions query returns a pageToken when there is more than one page of results. Specify either this field or the firstPageReq field.	[optional]
page_size	str	The maximum number of Prediction objects to return in a single page.	[optional]

Return type

ListPredictionSetsResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: Not defined
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.list_prediction_sets_response import ListPredictionSetsResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

project_id_uuid = 'project_id_uuid_example'  # str 
first_page_req_model_id = 'first_page_req_model_id_example'  # str  (optional)
first_page_req_dataset_id = 'first_page_req_dataset_id_example'  # str  (optional)
page_token = 'page_token_example'  # str  (optional)
page_size = 'page_size_example'  # str  (optional)

try:
    # ListPredictionSets
    api_response: ListPredictionSetsResponse = client.RegistryServiceApi.list_prediction_sets(project_id_uuid, first_page_req_model_id=first_page_req_model_id, first_page_req_dataset_id=first_page_req_dataset_id, page_token=page_token, page_size=page_size)
    print("The response of RegistryServiceApi->list_prediction_sets:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->list_prediction_sets: %s\n" % e)

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register_dataset

RegisterDatasetResponse = register_dataset()

RegisterDataset

Parameters

Name	Type	Description	Notes
project_id_uuid	str	Unique object ID.
project_id	object	Uniquely specifies a Project.	[optional]
name	str	Unique name of the Dataset.
metadata	Metadata		[optional]
integration_id	ID		[optional]
data_info	DataInfo
ct_info	CTInfo		[optional]
skip_validation	bool	The parameter is deprecated since 2.7, and does not have any effect. Will always validate the dataset you are registering. Validation ensures that the dataset is valid for Robust Intelligence's systems.	[optional]
agent_id	ID		[optional]

Return type

RegisterDatasetResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: application/json
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.register_dataset_request import RegisterDatasetRequest
from ri.apiclient.models.register_dataset_response import RegisterDatasetResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

project_id_uuid = 'project_id_uuid_example'  # str 
project_id = ri.apiclient.models.uniquely_specifies_a_project/.Uniquely specifies a Project.()  # object  (optional)
name = ''  # str 
metadata = Metadata()  # Metadata  (optional)
integration_id = ID()  # ID  (optional)
data_info = DataInfo()  # DataInfo 
ct_info = CTInfo()  # CTInfo  (optional)
skip_validation = True  # bool  (optional)
agent_id = ID()  # ID  (optional)

try:
    # RegisterDataset
    api_response: RegisterDatasetResponse = client.RegistryServiceApi.register_dataset(project_id_uuid, project_id=project_id, name, metadata=metadata, integration_id=integration_id, data_info, ct_info=ct_info, skip_validation=skip_validation, agent_id=agent_id)
    print("The response of RegistryServiceApi->register_dataset:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->register_dataset: %s\n" % e)

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register_model

RegisterModelResponse = register_model()

RegisterModel

Parameters

Name	Type	Description	Notes
project_id_uuid	str	Unique object ID.
project_id	object	Uniquely specifies a Project.	[optional]
name	str	Unique name of the Model.
metadata	Metadata		[optional]
external_id	str	External ID that can be used to identify the model.	[optional]
model_info	ModelInfo		[optional]
integration_id	ID		[optional]
skip_validation	bool	The parameter is deprecated since 2.7, and does not have any effect. Will always validate the model you are registering. Validation ensures that the model is valid for Robust Intelligence's systems.	[optional]
agent_id	ID		[optional]
model_endpoint_integration_id	ID		[optional]

Return type

RegisterModelResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: application/json
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.register_model_request import RegisterModelRequest
from ri.apiclient.models.register_model_response import RegisterModelResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

project_id_uuid = 'project_id_uuid_example'  # str 
project_id = ri.apiclient.models.uniquely_specifies_a_project/.Uniquely specifies a Project.()  # object  (optional)
name = ''  # str 
metadata = Metadata()  # Metadata  (optional)
external_id = ''  # str  (optional)
model_info = ModelInfo()  # ModelInfo  (optional)
integration_id = ID()  # ID  (optional)
skip_validation = True  # bool  (optional)
agent_id = ID()  # ID  (optional)
model_endpoint_integration_id = ID()  # ID  (optional)

try:
    # RegisterModel
    api_response: RegisterModelResponse = client.RegistryServiceApi.register_model(project_id_uuid, project_id=project_id, name, metadata=metadata, external_id=external_id, model_info=model_info, integration_id=integration_id, skip_validation=skip_validation, agent_id=agent_id, model_endpoint_integration_id=model_endpoint_integration_id)
    print("The response of RegistryServiceApi->register_model:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->register_model: %s\n" % e)

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register_prediction_set

RegisterPredictionSetResponse = register_prediction_set()

RegisterPredictionSet

Parameters

Name	Type	Description	Notes
project_id_uuid	str	Unique object ID.
model_id_uuid	str	Unique object ID.
dataset_id	str	Uniquely specifies a Dataset.
project_id	object	Uniquely specifies a Project.	[optional]
model_id	object	Uniquely specifies a Model.	[optional]
metadata	Metadata		[optional]
integration_id	ID		[optional]
pred_info	PredInfo		[optional]
skip_validation	bool	The parameter is deprecated since 2.7, and does not have any effect. Will always validate the predictions you are registering. Validation ensures that the predictions is valid for Robust Intelligence's systems.	[optional]
agent_id	ID		[optional]

Return type

RegisterPredictionSetResponse

Authorization

rime-api-key

HTTP request headers

Content-Type: application/json
Accept: application/json

Example

host_name = "http://<platform-domain>.rbst.io"

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure API key authorization: rime-api-key
rime_api_key = os.environ["API_KEY"]

import ri.apiclient
from ri import RIClient
from ri.apiclient.models.register_prediction_set_request import RegisterPredictionSetRequest
from ri.apiclient.models.register_prediction_set_response import RegisterPredictionSetResponse
from ri.apiclient.models import *
from ri.apiclient.rest import ApiException
from pprint import pprint

# Configure the client
domain = "https://api.example.com"
api_key = "your_api_key"
client = RIClient(domain=domain, api_key=api_key)

project_id_uuid = 'project_id_uuid_example'  # str 
model_id_uuid = 'model_id_uuid_example'  # str 
dataset_id = 'dataset_id_example'  # str 
project_id = ri.apiclient.models.uniquely_specifies_a_project/.Uniquely specifies a Project.()  # object  (optional)
model_id = ri.apiclient.models.uniquely_specifies_a_model/.Uniquely specifies a Model.()  # object  (optional)
metadata = Metadata()  # Metadata  (optional)
integration_id = ID()  # ID  (optional)
pred_info = PredInfo()  # PredInfo  (optional)
skip_validation = True  # bool  (optional)
agent_id = ID()  # ID  (optional)

try:
    # RegisterPredictionSet
    api_response: RegisterPredictionSetResponse = client.RegistryServiceApi.register_prediction_set(project_id_uuid, model_id_uuid, dataset_id, project_id=project_id, model_id=model_id, metadata=metadata, integration_id=integration_id, pred_info=pred_info, skip_validation=skip_validation, agent_id=agent_id)
    print("The response of RegistryServiceApi->register_prediction_set:\n")
    pprint(api_response)

except ApiException as e:
    print("Exception when calling RegistryServiceApi->register_prediction_set: %s\n" % e)

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ri.apiclient.RegistryServiceApi

delete_dataset

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Example

delete_model

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delete_prediction_set

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get_dataset

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get_model

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get_prediction_set

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list_datasets

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list_models

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list_prediction_sets

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register_dataset

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HTTP request headers

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register_model

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Authorization

HTTP request headers

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register_prediction_set

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Authorization

HTTP request headers

Example