A package for getting your models into production!
This repository contains templates for Model Orchestration/Experiment Evaluation and Inference server. Please refer to this template for Model Orchestration/Experiment Evaluation Flow and this template for an inference server.
You'll find a README in the src/mozmlops/templates directory!
You can install the library with pip install mozmlops.
Steps:
- Clone this repository
cdinto the repository- Start up a virtual environment:
python -m venv env
source env/bin/activate
python -m pip install poetrypoetry install
Linting:
Run ruff check to find style issues and ruff check --fix to fix many automatically.
Formatting:
Run ruff format
Unit tests:
Run pytest from the top-level directory.
Integration tests:
You need to be logged into GCP to run the integration tests; you can use the gcloud CLI command gcloud auth login.
Run the integration tests with pytest -m integration.
An example import line (in fact, the only one currently implemented) would be:
from mozmlops.cloud_storage_api_client import CloudStorageAPIClient
at the top of your favorite Python file, or in a python console.
From there, you can try running this line:
store = CloudStorageAPIClient('some-project-name', 'some-bucket-name')
To make sure the import worked.
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
mozmlops was created by Mozilla MLOps. It is licensed under the terms of the Mozilla Public License.
mozmlops was created with cookiecutter and the py-pkgs-cookiecutter template.