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README.md

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# gaiaflow
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# Gaiaflow
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[![Pixi Badge](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/prefix-dev/pixi/main/assets/badge/v0.json)](https://pixi.sh)
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[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v0.json)](https://github.com/charliermarsh/ruff)
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[![Docs](https://img.shields.io/badge/docs-mkdocs-blue)](https://bcdev.github.io/gaiaflow/)
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![Static Badge](https://img.shields.io/badge/Airflow-3.0-8A2BE2?logo=apacheairflow)
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![Static Badge](https://img.shields.io/badge/MLFlow-darkblue?logo=mlflow)
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![Static Badge](https://img.shields.io/badge/MinIO-red?logo=minio)
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![Static Badge](https://img.shields.io/badge/Jupyter-grey?logo=jupyter)
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![Static Badge](https://img.shields.io/badge/Minikube-lightblue?logo=kubernetes)
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Gaiaflow is a local-first MLOps infrastructure python package tool that simplifies the process
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of building, testing, and deploying ML workflows.
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It provides an opinionated CLI for managing Airflow, MLflow, and other
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dependencies, abstracting away complex configurations, and giving you
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a smooth developer experience.
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Gaiaflow is a tool that
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- provides you with a local MLOps infrastructure via a CLI tool with
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some prerequisites already installed.
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- handles the complex Airflow configuration and [Xcom](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/xcoms.html)
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handling and provides the user a simpler interface for creating DAGs.
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- provides a [cookiecutter template](https://github.com/bcdev/gaiaflow-cookiecutter)
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to get started with your projects with a standardized structure.
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- provides tools to deploy models locally and in production (in future)
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- provides clear documentation on how to setup production environment to run your
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workflows at scale (in future, private?)
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Prerequisites:
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- Docker
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- Docker compose
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- Miniforge
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- Mamba/Conda
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To install it, you can do it via:
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`pip install gaiaflow`
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Check installation:
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`gaiaflow --help`
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You can read the documentation [here]()

docs/cli_ref.md

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# CLI Reference
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To see options for any command, add `--help` at the end of your command.
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```bash
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gaiaflow --help
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```
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## `gaiaflow dev`
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Manage local development services.
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```bash
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gaiaflow dev [OPTIONS] COMMAND [ARGS]...
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```
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**Commands**
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- `start` – Start Gaiaflow dev services
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- `stop` – Stop Gaiaflow dev services
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- `restart` – Restart services
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- `cleanup` – Remove temporary context and state
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- `dockerize` – Build a Docker image of your ML package
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**Example**
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```bash
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gaiaflow dev start -p /path/to/project --service airflow --jupyter-port 8888
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```
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## `gaiaflow prod-local`
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Manage **production-like services** (via Minikube).
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**Commands**
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- `start` – Start production-like services
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- `stop` – Stop services
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- `restart` – Restart services
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- `dockerize` – Build image inside Minikube
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- `create-config` – Generate Airflow K8s config (debugging only)
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- `create-secret` – Create Kubernetes (K8s) secrets
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- `cleanup` – Remove Minikube-specific resources
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```bash
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gaiaflow prod-local start -p /path/to/project --force-new
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```
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