Requirements for using custom components with ML models

Package requirements

• The package type must be: source distribution (distributions of type Wheel and Egg are not supported)
• The package file format must be: .zip
• Any third-party dependencies for your custom components must be installable by pip and must be passed to the install_requires argument of the setup function of the setuptools library.

Refer to: Creating a source distribution

Storing your custom package

You must take extra steps when you store your trained model in the watsonx.ai Runtime repository:

• Store your custom package in the watsonx.ai Runtime repository (use the runtimes.store_library function from the watsonx.ai Python client, or the store libraries watsonx.ai Runtime CLI command.)
• Create a runtime resource object that references your stored custom package, and then store the runtime resource object in the watsonx.ai Runtime repository (use the runtimes.store function, or the store runtimes command.)
• When you store your trained model in the watsonx.ai Runtime repository, reference your stored runtime resource in the metadata that is passed to the store_model function (or the store command.)