Folder Structure

• rafiki/

  Rafiki’s Python package

  • admin/

    Rafiki’s static Admin component

  • advisor/

    Rafiki’s advisors

  • client/

    Rafiki’s client-side SDK

    See also

    rafiki.client

  • worker/

    Rafiki’s train, inference & advisor workers

  • predictor/

    Rafiki’s predictor

  • meta_store/

    Abstract data access layer for Rafiki’s main metadata store (backed by PostgreSQL)

  • param_store/

    Abstract data access layer for Rafiki’s store of model parameters (backed by filesystem)

  • data_store/

    Abstract data access layer for Rafiki’s store of datasets (backed by filesystem)

  • cache/

    Abstract data access layer for Rafiki’s temporary store of model parameters, train job metadata and queries & predictions in train & inference jobs (backed by Redis)

  • container/

    Abstract access layer for dynamic deployment of workers

  • utils/

    Collection of Rafiki-internal utility methods (e.g. for logging, authentication)

  • model/

    Definition of abstract rafiki.model.BaseModel that all Rafiki models should extend, programming abstractions used in model development, as well as a collection of utility methods for model developers in the implementation of their own models

  • constants.py

    Rafiki’s programming abstractions & constants (e.g. valid values for user types, job statuses)

• web/

  Rafiki’s Web Admin component

• dockerfiles/

  Stores Dockerfiles for customized components of Rafiki

• examples/

  Sample usage code for Rafiki.

• docs/

  Source documentation for Rafiki (e.g. Sphinx documentation files)

• test/

  Test code for Rafiki

• scripts/

  Shell & python scripts for initializing, starting and stopping various components of Rafiki’s stack

• .env.sh

  Stores configuration variables for Rafiki