Helpers¶

class ibm_watsonx_ai.foundation_models_manager.FoundationModelsManager(client)[source]¶

get_custom_model_specs(model_id=None, limit=None, asynchronous=False, get_all=False)[source]¶

Get details on available custom model(s) as dict or as generator (asynchronous). If asynchronous or get_all is set, then model_id is ignored.

Parameters:

model_id (str, optional) – Id of the model, defaults to None (all models specs are returned).
limit (int, optional) – limit number of fetched records
asynchronous (bool, optional) – if True, it will work as a generator
get_all (bool, optional) – if True, it will get all entries in ‘limited’ chunks

Returns:

details of supported custom models, None if for given model_id non is found

Return type:

dict or generator

Example

client.foundation_models.get_custom_models_spec()
client.foundation_models.get_custom_models_spec()
client.foundation_models.get_custom_models_spec(model_id='mistralai/Mistral-7B-Instruct-v0.2')
client.foundation_models.get_custom_models_spec(limit=20)
client.foundation_models.get_custom_models_spec(limit=20, get_all=True)
for spec in client.foundation_models.get_custom_model_specs(limit=20, asynchronous=True, get_all=True):
    print(spec, end="")

get_embeddings_model_specs(model_id=None, limit=None, asynchronous=False, get_all=False)[source]¶

Operation to retrieve the embeddings model specs.

Parameters:

model_id (str, optional) – Id of the model, defaults to None (all models specs are returned).
limit (int, optional) – limit number of fetched records
asynchronous (bool, optional) – if True, it will work as a generator
get_all (bool, optional) – if True, it will get all entries in ‘limited’ chunks

Returns:

embeddings model specs

Return type:

dict or generator

Example

client.foundation_models.get_embeddings_model_specs()
client.foundation_models.get_embeddings_model_specs('ibm/slate-125m-english-rtrvr')

get_model_lifecycle(model_id, **kwargs)[source]¶

Operation to retrieve the list of model lifecycle data.

Parameters:: model_id (str) – the type of model to use
Returns:: list of deployed foundation model lifecycle data
Return type:: list

Example

client.foundation_models.get_model_lifecycle(
    model_id="ibm/granite-13b-instruct-v2"
    )

get_model_specs(model_id=None, limit=None, asynchronous=False, get_all=False, **kwargs)[source]¶

Operations to retrieve the list of deployed foundation models specifications.

Parameters:

model_id (str or ModelTypes, optional) – Id of the model, defaults to None (all models specs are returned).
limit (int, optional) – limit number of fetched records
asynchronous (bool, optional) – if True, it will work as a generator
get_all (bool, optional) – if True, it will get all entries in ‘limited’ chunks

Returns:

list of deployed foundation model specs

Return type:

dict or generator

Example

# GET ALL MODEL SPECS
client.foundation_models.get_model_specs()

# GET MODEL SPECS BY MODEL_ID
client.foundation_models.get_model_specs(model_id="google/flan-ul2")

get_model_specs_with_prompt_tuning_support(model_id=None, limit=None, asynchronous=False, get_all=False)[source]¶

Operations to query the details of the deployed foundation models with prompt tuning support.

Parameters:

model_id (str, optional) – Id of the model, defaults to None (all models specs are returned).
limit (int, optional) – limit number of fetched records
asynchronous (bool, optional) – if True, it will work as a generator
get_all (bool, optional) – if True, it will get all entries in ‘limited’ chunks

Returns:

list of deployed foundation model specs with prompt tuning support

Return type:

dict or generator

Example

client.foundation_models.get_model_specs_with_prompt_tuning_support()
client.foundation_models.get_model_specs_with_prompt_tuning_support('google/flan-t5-xl')

ibm_watsonx_ai.foundation_models.get_model_specs(url, model_id=None)[source]¶

Operations to retrieve the list of deployed foundation models specifications.

Decrecated: get_model_specs() function is deprecated from 1.0, please use client.foundation_models.get_model_specs() function instead.

Parameters:

url (str) – environment url
model_id (Optional[str, ModelTypes], optional) – Id of the model, defaults to None (all models specs are returned).

Returns:

list of deployed foundation model specs

Return type:

dict

Example

from ibm_watsonx_ai.foundation_models import get_model_specs

# GET ALL MODEL SPECS
get_model_specs(
    url="https://us-south.ml.cloud.ibm.com"
    )

# GET MODEL SPECS BY MODEL_ID
get_model_specs(
    url="https://us-south.ml.cloud.ibm.com",
    model_id="google/flan-ul2"
    )

ibm_watsonx_ai.foundation_models.get_model_lifecycle(url, model_id)[source]¶

Operation to retrieve the list of model lifecycle data.

Decrecated: get_model_lifecycle() function is deprecated from 1.0, please use client.foundation_models.get_model_lifecycle() function instead.

Parameters:

url (str) – environment url
model_id (str) – the type of model to use

Returns:

list of deployed foundation model lifecycle data

Return type:

list

Example

from ibm_watsonx_ai.foundation_models import get_model_lifecycle

get_model_lifecycle(
    url="https://us-south.ml.cloud.ibm.com",
    model_id="ibm/granite-13b-instruct-v2"
    )

ibm_watsonx_ai.foundation_models.get_model_specs_with_prompt_tuning_support(url)[source]¶

Operations to query the details of the deployed foundation models with prompt tuning support.

Decrecated: get_model_specs_with_prompt_tuning_support() function is deprecated from 1.0, please use client.foundation_models.get_model_specs_with_prompt_tuning_support() function instead.

Parameters:: url (str) – environment url
Returns:: list of deployed foundation model specs with prompt tuning support
Return type:: dict

Example

from ibm_watsonx_ai.foundation_models import get_model_specs_with_prompt_tuning_support

get_model_specs_with_prompt_tuning_support(
    url="https://us-south.ml.cloud.ibm.com"
    )

ibm_watsonx_ai.foundation_models.get_supported_tasks(url)[source]¶

Operation to retrieve the list of tasks that are supported by the foundation models.

Parameters:: url (str) – environment url
Returns:: list of tasks that are supported by the foundation models
Return type:: dict

Example

from ibm_watsonx_ai.foundation_models import get_supported_tasks

get_supported_tasks(
    url="https://us-south.ml.cloud.ibm.com"
    )