avis_client.MlApi

Authorization

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HTTP request headers

Content-Type: application/json, application/x-www-form-urlencoded, multipart/form-data
Accept: application/json

HTTP response details

Status code	Description	Response headers
201		-

ml_model_destroy

ml_model_destroy(id)

A viewset for ML models. It filters results based on the permissions granted to all the user's team(s). A user will only be able to interact with an ML models if at least one of the teams they are a member of has access to it.

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model.

    try:
        api_instance.ml_model_destroy(id)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_destroy: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model.

Return type

void (empty response body)

Authorization

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HTTP request headers

Content-Type: Not defined
Accept: Not defined

HTTP response details

Status code	Description	Response headers
204	No response body	-

ml_model_inference

MLModel ml_model_inference(id, azure_ml_inference_request)

Infer a result from the model. This is a passthrough to the model's inference endpoint running somewhere else. The request body is passed through to the model.

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.azure_ml_inference_request import AzureMLInferenceRequest
from avis_client.models.ml_model import MLModel
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model.
    azure_ml_inference_request = avis_client.AzureMLInferenceRequest() # AzureMLInferenceRequest | 

    try:
        api_response = api_instance.ml_model_inference(id, azure_ml_inference_request)
        print("The response of MlApi->ml_model_inference:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_inference: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model.
azure_ml_inference_request	AzureMLInferenceRequest

Return type

Authorization

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HTTP request headers

Content-Type: application/json, application/x-www-form-urlencoded, multipart/form-data
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_list

PaginatedMLModelList ml_model_list(page=page, page_size=page_size)

A viewset for ML models. It filters results based on the permissions granted to all the user's team(s). A user will only be able to interact with an ML models if at least one of the teams they are a member of has access to it.

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.paginated_ml_model_list import PaginatedMLModelList
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    page = 56 # int | A page number within the paginated result set. (optional)
    page_size = 56 # int | Number of results to return per page. (optional)

    try:
        api_response = api_instance.ml_model_list(page=page, page_size=page_size)
        print("The response of MlApi->ml_model_list:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_list: %s\n" % e)

Parameters

Name	Type	Description	Notes
page	int	A page number within the paginated result set.	[optional]
page_size	int	Number of results to return per page.	[optional]

Return type

PaginatedMLModelList

Authorization

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HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_partial_update

MLModel ml_model_partial_update(id, patched_ml_model_request=patched_ml_model_request)

A viewset for ML models. It filters results based on the permissions granted to all the user's team(s). A user will only be able to interact with an ML models if at least one of the teams they are a member of has access to it.

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.ml_model import MLModel
from avis_client.models.patched_ml_model_request import PatchedMLModelRequest
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model.
    patched_ml_model_request = avis_client.PatchedMLModelRequest() # PatchedMLModelRequest |  (optional)

    try:
        api_response = api_instance.ml_model_partial_update(id, patched_ml_model_request=patched_ml_model_request)
        print("The response of MlApi->ml_model_partial_update:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_partial_update: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model.
patched_ml_model_request	PatchedMLModelRequest		[optional]

Return type

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: application/json, application/x-www-form-urlencoded, multipart/form-data
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_retrieve

MLModel ml_model_retrieve(id)

A viewset for ML models. It filters results based on the permissions granted to all the user's team(s). A user will only be able to interact with an ML models if at least one of the teams they are a member of has access to it.

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.ml_model import MLModel
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model.

    try:
        api_response = api_instance.ml_model_retrieve(id)
        print("The response of MlApi->ml_model_retrieve:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model.

Return type

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_type_create

MLModelType ml_model_type_create(ml_model_type_request=ml_model_type_request)

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.ml_model_type import MLModelType
from avis_client.models.ml_model_type_request import MLModelTypeRequest
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    ml_model_type_request = avis_client.MLModelTypeRequest() # MLModelTypeRequest |  (optional)

    try:
        api_response = api_instance.ml_model_type_create(ml_model_type_request=ml_model_type_request)
        print("The response of MlApi->ml_model_type_create:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_type_create: %s\n" % e)

Parameters

Name	Type	Description	Notes
ml_model_type_request	MLModelTypeRequest		[optional]

Return type

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: application/json, application/x-www-form-urlencoded, multipart/form-data
Accept: application/json

HTTP response details

Status code	Description	Response headers
201		-

ml_model_type_destroy

ml_model_type_destroy(id)

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model type.

    try:
        api_instance.ml_model_type_destroy(id)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_type_destroy: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model type.

Return type

void (empty response body)

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: Not defined
Accept: Not defined

HTTP response details

Status code	Description	Response headers
204	No response body	-

ml_model_type_list

PaginatedMLModelTypeList ml_model_type_list(page=page, page_size=page_size)

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.paginated_ml_model_type_list import PaginatedMLModelTypeList
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    page = 56 # int | A page number within the paginated result set. (optional)
    page_size = 56 # int | Number of results to return per page. (optional)

    try:
        api_response = api_instance.ml_model_type_list(page=page, page_size=page_size)
        print("The response of MlApi->ml_model_type_list:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_type_list: %s\n" % e)

Parameters

Name	Type	Description	Notes
page	int	A page number within the paginated result set.	[optional]
page_size	int	Number of results to return per page.	[optional]

Return type

PaginatedMLModelTypeList

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_type_partial_update

MLModelType ml_model_type_partial_update(id, patched_ml_model_type_request=patched_ml_model_type_request)

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.ml_model_type import MLModelType
from avis_client.models.patched_ml_model_type_request import PatchedMLModelTypeRequest
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model type.
    patched_ml_model_type_request = avis_client.PatchedMLModelTypeRequest() # PatchedMLModelTypeRequest |  (optional)

    try:
        api_response = api_instance.ml_model_type_partial_update(id, patched_ml_model_type_request=patched_ml_model_type_request)
        print("The response of MlApi->ml_model_type_partial_update:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_type_partial_update: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model type.
patched_ml_model_type_request	PatchedMLModelTypeRequest		[optional]

Return type

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: application/json, application/x-www-form-urlencoded, multipart/form-data
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_type_retrieve

MLModelType ml_model_type_retrieve(id)

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.ml_model_type import MLModelType
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model type.

    try:
        api_response = api_instance.ml_model_type_retrieve(id)
        print("The response of MlApi->ml_model_type_retrieve:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_type_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model type.

Return type

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_type_update

MLModelType ml_model_type_update(id, ml_model_type_request=ml_model_type_request)

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.ml_model_type import MLModelType
from avis_client.models.ml_model_type_request import MLModelTypeRequest
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model type.
    ml_model_type_request = avis_client.MLModelTypeRequest() # MLModelTypeRequest |  (optional)

    try:
        api_response = api_instance.ml_model_type_update(id, ml_model_type_request=ml_model_type_request)
        print("The response of MlApi->ml_model_type_update:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_type_update: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model type.
ml_model_type_request	MLModelTypeRequest		[optional]

Return type

Authorization

[Back to top] [Back to API list] [Back to Model list] [Back to README]

HTTP request headers

Content-Type: application/json, application/x-www-form-urlencoded, multipart/form-data
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

ml_model_update

MLModel ml_model_update(id, ml_model_request)

A viewset for ML models. It filters results based on the permissions granted to all the user's team(s). A user will only be able to interact with an ML models if at least one of the teams they are a member of has access to it.

Example

Api Key Authentication (cookieAuth):
Api Key Authentication (ApiKeyAuth):

import time
import os
import avis_client
from avis_client.models.ml_model import MLModel
from avis_client.models.ml_model_request import MLModelRequest
from avis_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:8000
# See configuration.py for a list of all supported configuration parameters.
configuration = avis_client.Configuration(
    host = "http://localhost:8000"
)

# 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: cookieAuth
configuration.api_key['cookieAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['cookieAuth'] = 'Bearer'

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with avis_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = avis_client.MlApi(api_client)
    id = 56 # int | A unique integer value identifying this ml model.
    ml_model_request = avis_client.MLModelRequest() # MLModelRequest | 

    try:
        api_response = api_instance.ml_model_update(id, ml_model_request)
        print("The response of MlApi->ml_model_update:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling MlApi->ml_model_update: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	int	A unique integer value identifying this ml model.
ml_model_request	MLModelRequest

Return type

Authorization