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1 | | -# gaiaflow |
| 1 | +# Gaiaflow |
| 2 | + |
| 3 | +[](https://pixi.sh) |
| 4 | +[](https://github.com/charliermarsh/ruff) |
| 5 | +[](https://bcdev.github.io/gaiaflow/) |
| 6 | + |
| 7 | + |
| 8 | + |
| 9 | + |
| 10 | + |
| 11 | + |
| 12 | + |
| 13 | +Gaiaflow is a local-first MLOps infrastructure python package tool that simplifies the process |
| 14 | +of building, testing, and deploying ML workflows. |
| 15 | +It provides an opinionated CLI for managing Airflow, MLflow, and other |
| 16 | +dependencies, abstracting away complex configurations, and giving you |
| 17 | +a smooth developer experience. |
| 18 | + |
| 19 | +Gaiaflow is a tool that |
| 20 | +- provides you with a local MLOps infrastructure via a CLI tool with |
| 21 | +some prerequisites already installed. |
| 22 | +- handles the complex Airflow configuration and [Xcom](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/xcoms.html) |
| 23 | +handling and provides the user a simpler interface for creating DAGs. |
| 24 | +- provides a [cookiecutter template](https://github.com/bcdev/gaiaflow-cookiecutter) |
| 25 | +to get started with your projects with a standardized structure. |
| 26 | + |
| 27 | +- provides tools to deploy models locally and in production (in future) |
| 28 | +- provides clear documentation on how to setup production environment to run your |
| 29 | +workflows at scale (in future, private?) |
| 30 | + |
| 31 | + |
| 32 | +Prerequisites: |
| 33 | +- Docker |
| 34 | +- Docker compose |
| 35 | +- Miniforge |
| 36 | +- Mamba/Conda |
| 37 | + |
| 38 | +To install it, you can do it via: |
| 39 | + |
| 40 | +`pip install gaiaflow` |
| 41 | + |
| 42 | +Check installation: |
| 43 | + |
| 44 | +`gaiaflow --help` |
| 45 | + |
| 46 | +You can read the documentation [here]() |
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