Metadata-Version: 2.4
Name: kitops
Version: 1.4.0
Summary: A package for managing KitOps ModelKits and Kitfiles
License-Expression: Apache-2.0
License-File: LICENSE
Keywords: kitfile,modelkit,kitops,jozu,jozu.ml
Author: Jacob Fuss
Author-email: jacob@jozu.com
Requires-Python: >=3.10
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Requires-Dist: pydantic (>=2.12,<3.0)
Requires-Dist: python-dotenv (>=1.2,<2.0)
Requires-Dist: pyyaml (>=6.0,<7.0)
Project-URL: Documentation, https://kitops.org/docs/pykitops/reference/
Project-URL: Homepage, https://github.com/jozu-ai/pykitops
Project-URL: Issues, https://github.com/jozu-ai/pykitops/issues
Project-URL: Repository, https://github.com/jozu-ai/pykitops
Description-Content-Type: text/markdown

# PyKitOps

PyKitOps is an open source Python SDK for managing [KitOps](https://kitops.org) ModelKits.

Please file issues in [the main KitOps repository](https://github.com/kitops-ml/kitops).

## What is KitOps?
[KitOps](https://kitops.org/) is a packaging, versioning, and sharing system for AI/ML projects that uses open standards so it works with the AI/ML, development, and DevOps tools you are already using, and can be stored in your enterprise container registry. 

PyKitOps makes it easy to create a KitOps ModelKit for your AI/ML project directly in code. This makes PyKitOps preferred when assembling a ModelKit from:

* A Jupyter Notebook or other code editor
* An experimentation tracking tool like MLflow
* Or anywhere else you need

ModelKits typically include everything someone needs to reproduce an AI/ML project locally or deploy it into production. You can even selectively unpack a ModelKit so different team members can save time and storage space by only grabbing what they need for a task. Because ModelKits are immutable, signable, and live in your existing container registry they're easy for organizations to track, control, and audit.

## Installation:

```bash
pip install kitops
```

## Documentation:
[PyKitOps documentation is part of the KitOps Docs](https://kitops.org/docs/pykitops/)

