aixplain.factories.model_factory

__author__

Copyright 2022 The aiXplain SDK authors

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Author: Duraikrishna Selvaraju, Thiago Castro Ferreira, Shreyas Sharma and Lucas Pavanelli Date: September 1st 2022 Description: Model Factory Class

ModelFactory Objects

class ModelFactory(ModelGetterMixin, ModelListMixin)

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Factory class for creating, managing, and exploring models.

This class provides functionality for creating various types of models, managing model repositories, and interacting with the aiXplain platform's model-related features.

Attributes:

• backend_url str - Base URL for the aiXplain backend API.

create_utility_model

@classmethod
def create_utility_model(cls,
                         name: Optional[Text] = None,
                         code: Union[Text, Callable] = None,
                         inputs: List[UtilityModelInput] = [],
                         description: Optional[Text] = None,
                         output_examples: Text = "",
                         api_key: Optional[Text] = None) -> UtilityModel

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Create a new utility model for custom functionality.

This method creates a utility model that can execute custom code or functions with specified inputs and outputs.

Arguments:

• name Optional[Text] - Name of the utility model.
• code Union[Text, Callable] - Python code as string or callable function implementing the model's functionality.
• inputs List[UtilityModelInput], optional - List of input specifications. Defaults to empty list.
• description Optional[Text], optional - Description of what the model does. Defaults to None.
• output_examples Text, optional - Examples of expected outputs. Defaults to empty string.
• api_key Optional[Text], optional - API key for authentication. Defaults to None, using the configured TEAM_API_KEY.

Returns:

• UtilityModel - Created and registered utility model instance.

Raises:

• Exception - If model creation fails or validation fails.

list_host_machines

@classmethod
def list_host_machines(cls, api_key: Optional[Text] = None) -> List[Dict]

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Lists available hosting machines for model.

Arguments:

• api_key Text, optional - Team API key. Defaults to None.

Returns:

• List[Dict] - List of dictionaries containing information about each hosting machine.

list_gpus

@classmethod
def list_gpus(cls, api_key: Optional[Text] = None) -> List[List[Text]]

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List GPU names on which you can host your language model.

Arguments:

• api_key Text, optional - Team API key. Defaults to None.

Returns:

• List[List[Text]] - List of all available GPUs and their prices.

list_functions

@classmethod
def list_functions(cls,
                   verbose: Optional[bool] = False,
                   api_key: Optional[Text] = None) -> List[Dict]

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Lists supported model functions on platform.

Arguments:

• verbose Boolean, optional - Set to True if a detailed response is desired; is otherwise False by default.
• api_key Text, optional - Team API key. Defaults to None.

Returns:

• List[Dict] - List of dictionaries containing information about each supported function.

create_asset_repo

@classmethod
def create_asset_repo(cls,
                      name: Text,
                      description: Text,
                      function: Text,
                      source_language: Text,
                      input_modality: Text,
                      output_modality: Text,
                      documentation_url: Optional[Text] = "",
                      api_key: Optional[Text] = None) -> Dict

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Create a new model repository in the platform.

This method creates and registers a new model repository, setting up the necessary infrastructure for model deployment.

Arguments:

• name Text - Name of the model.
• description Text - Description of the model's functionality.
• function Text - Function name from list_functions() defining model's task.
• source_language Text - Language code in ISO 639-1 (2-char) or 639-3 (3-char) format.
• input_modality Text - Type of input the model accepts (e.g., text, audio).
• output_modality Text - Type of output the model produces (e.g., text, audio).
• documentation_url Optional[Text], optional - URL to model documentation. Defaults to empty string.
• api_key Optional[Text], optional - API key for authentication. Defaults to None, using the configured TEAM_API_KEY.

Returns:

• Dict - Repository creation response containing model ID and other details.

Raises:

• Exception - If function name is invalid.
• description0 - If response status code is not 201.

asset_repo_login

@classmethod
def asset_repo_login(cls, api_key: Optional[Text] = None) -> Dict

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Return login credentials for the image repository that corresponds with the given API_KEY.

Arguments:

• api_key Text, optional - Team API key. Defaults to None.

Returns:

• Dict - Backend response

onboard_model

@classmethod
def onboard_model(cls,
                  model_id: Text,
                  image_tag: Text,
                  image_hash: Text,
                  host_machine: Optional[Text] = "",
                  api_key: Optional[Text] = None) -> Dict

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Onboard a model after its image has been pushed to ECR.

Arguments:

• model_id Text - Model ID obtained from CREATE_ASSET_REPO.
• image_tag Text - Image tag to be onboarded.
• image_hash Text - Image digest.
• host_machine Text, optional - Machine on which to host model.
• api_key Text, optional - Team API key. Defaults to None.

Returns:

• Dict - Backend response

deploy_huggingface_model

@classmethod
def deploy_huggingface_model(cls,
                             name: Text,
                             hf_repo_id: Text,
                             revision: Optional[Text] = "",
                             hf_token: Optional[Text] = "",
                             api_key: Optional[Text] = None) -> Dict

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Deploy a model from Hugging Face Hub to the aiXplain platform.

This method handles the deployment of a Hugging Face model, including authentication and configuration setup.

Arguments:

• name Text - Display name for the deployed model.
• hf_repo_id Text - Hugging Face repository ID in 'author/model-name' format.
• revision Optional[Text], optional - Specific model revision/commit hash. Defaults to empty string (latest version).
• hf_token Optional[Text], optional - Hugging Face access token for private models. Defaults to empty string.
• api_key Optional[Text], optional - API key for authentication. Defaults to None, using the configured TEAM_API_KEY.

Returns:

• Dict - Deployment response containing model ID and status information.

get_huggingface_model_status

@classmethod
def get_huggingface_model_status(cls,
                                 model_id: Text,
                                 api_key: Optional[Text] = None) -> Dict

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Check the deployment status of a Hugging Face model.

This method retrieves the current status and details of a deployed Hugging Face model.

Arguments:

• model_id Text - Model ID returned by deploy_huggingface_model.
• api_key Optional[Text], optional - API key for authentication. Defaults to None, using the configured TEAM_API_KEY.

Returns:

• Dict - Status response containing:
  • status: Current deployment status
  • name: Model name
  • id: Model ID
  • pricing: Pricing information