Class hierarchy of user-facing classes

superduper

superduper is the entry point to connect and be able to use key functionality. It returns a built Datalayer.

Datalayer

The Datalayer class, an instance of which we refer to throughout this documentation as db, is the key entrypoint via which developers may connect to their data-infrastructure and additional connect AI functionality to their data-infrastructure:

The Datalayer connects to data, with the superduper function.

.apply

AI Component instances may be applied to the built Datalayer with .apply.

.execute

The data and AI outputs are accessible with queries and AI models using the .execute method. This can include standard database queries, vector-search queries (which include model inference) and pure model computations. See here.

Component

AI functionality is packaged as a Component. Key implementations are Model, Listener and VectorIndex.

Document

Document is a wrapper around standard Python dict instances, but which can encode their contained fields as a mixture of JSON and pure bytes. This mechanism can in principle handle any information which Python can handle.

Since most databases can handle this type of information, this makes Document a crucial piece in connecting AI (which operates over a range of information) and the database.

_BaseEncodable

This is the base class, which allows superduperdb to decide how to save "special" data.

Serializable

An extension of Python dataclasses, but easier to get the original class back from the serialized dictionary form. This is the base class underlying all superduperdb queries and predictions as well as mixing into Component.

Job

Component instances applied with Datalayer.apply create compute-jobs in response to incoming data, and on initialization via the Job class.

The interface on Component is Component.schedule_jobs.