Key Concepts


A domain is how model store denotes a group of models, that are all intended for the same end-usage. When you upload a model to the store, you will add it to a domain.

The model store library then allows you to list the models that are in a domain and retrieve specific models (e.g., the latest one).

Under the hood, a domain is just a string, so it is up to you how you would like to use it.

Model State

A model state is a tag that you can use to control the lifecycle of a model in a given domain.

For example, you may want to have some models tagged as being in state “production” or state “shadow.” You can achieve this by creating a state and then setting a model’s state.

Under the hood, a model state name is just a string, so it is up to you how you would like to use it.

Model Archive

When you upload a model, an artifacts.tar.gz file is created and then uploaded to your storage. This archive contains:

  1. Files that are dumps from your model,

  2. A "python-info.json" file that enumerates the version of the Python library of the model you are exporting.

The upload() function returns a dictionary containing meta-data about the model.

Model Meta-data

The meta-data includes:

  • A unique id for your model;

  • Details about where the model is being uploaded to (the bucket and prefix);

  • The Python runtime that was used (e.g., “python:3.7.0”)

  • The user who ran the training.

  • Versions for the Python library and key dependencies.


When you pick a backend that stores data in files (e.g., Cloud Storage Buckets), the files are stored with a pre-defined structure.

The top-level, root prefix that this library hard-codes is operatorai-model-store.

When you create and upload a model archive, this library will upload three files to different places in the bucket.

  1. The artifacts archive will be uploaded to: root/<domain>/<datetime>/archive.tar.gz, where the datetime has the form "%Y/%m/%d/%H:%M:%S" - denoting the time when the model was uploaded.

  2. The library creates a dictionary of meta-data about your model. This will be uploaded to root/<domain>/versions/<model-id>.json.

  3. This same meta-data is also stored in root/<domain>/latest.json, which tracks the _last_ model that was uploaded to the model store.