Devo ML Model Manager Client#

The ML Model Manager is a service to register machine learning models on Devo platform. These models can be used through the query engine using the mlevalmodel(...) operation or through the FLOW correlation engine including in the context the MlSingleModelEval unit.

devo-mlmodelmanager provides an easy-to-use client for Devo’s ML Model Manager. Built on top of the widely used Requests library exposes a simplified interface for model management, allowing you to focus on the machine learning workflows and not worry about the integration with Devo platform.

A quick example#

That easy is to create a client:

>>> from devo_ml.modelmanager import create_client_from_token
>>> client = create_client_from_token("https://the_url", "the_token")

Here we use a client factory to create a client object, this is a convenient way of create a client ready to use.

Now we can start manage our models, e.g. to get a model called pokemon_onnx_regression:

>>> client.get_model("pokemon_onnx_regression")
{
   'id': 35,
   'name': 'pokemon_onnx_regression',
   'engine': 'ONNX',
   'description': 'A funny Pokemon prediction',
   ...
}

This is a simple example of the ML Model Manager Client is capable of. Explore the rest of the documentation to learn more.

Contents

Indices and tables#