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*[Builds and CI/CD](https://github.com/kitops-ml/kitops/issues?q=is%3Aopen+is%3Aissue+label%3Abuild)
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* Release management
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* Issue triage
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* Answering questions on Discord, or the mailing list
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* Web design
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* Communications, social media, blog posts, or other marketing
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If you think there's something else you can help with please contact us in the [#general channel of our Discord server](https://discord.gg/Tapeh8agYy) or during our [office hours meeting](https://github.com/jozu-ai/kitops/blob/main/GOVERNANCE.md#-meetings) and let's discuss how we can work together.
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If you think there's something else you can help with please contact us in the [#general channel of our Discord server](https://discord.gg/Tapeh8agYy) or during our [office hours meeting](https://github.com/kitops-ml/kitops/blob/main/GOVERNANCE.md#-meetings) and let's discuss how we can work together.
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## Development Environment Setup
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1. Clone the Repository: Clone the KitOps source code to your local machine:
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```shell
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git clone https://github.com/jozu-ai/kitops.git
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git clone https://github.com/kitops-ml/kitops.git
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cd kitops
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```
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* Write good commit messages
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* Break large changes into a logical series of smaller patches which individually make easily understandable changes, and in aggregate solve a broader issue
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Reviewers, the people giving the review, are highly encouraged to revisit our [Code of Conduct](https://github.com/jozu-ai/kitops/blob/main/CODE-OF-CONDUCT.md) and must go above and beyond to promote a collaborative, respectful community. When reviewing PRs from others [The Gentle Art of Patch Review](https://sage.thesharps.us/2014/09/01/the-gentle-art-of-patch-review/) suggests an iterative series of focuses which is designed to lead new contributors to positive collaboration without inundating them initially with a pile of suggestions:
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Reviewers, the people giving the review, are highly encouraged to revisit our [Code of Conduct](https://github.com/kitops-ml/kitops/blob/main/CODE-OF-CONDUCT.md) and must go above and beyond to promote a collaborative, respectful community. When reviewing PRs from others [The Gentle Art of Patch Review](https://sage.thesharps.us/2014/09/01/the-gentle-art-of-patch-review/) suggests an iterative series of focuses which is designed to lead new contributors to positive collaboration without inundating them initially with a pile of suggestions:
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1. Is the idea behind the contribution sound?
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1. Is the contribution architected correctly?
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Copy file name to clipboardExpand all lines: GOVERNANCE.md
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## 👥 Maintainers
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KitOps maintainers have write access to the [project GitHub repository](https://github.com/jozu-ai/kitops). They can merge patches and are expected to review large or critical patches personally. The current maintainers can be found in [MAINTAINERS.md](./MAINTAINERS.md). Maintainers collectively manage the project's resources and contributors.
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KitOps maintainers have write access to the [project GitHub repository](https://github.com/kitops-ml/kitops). They can merge patches and are expected to review large or critical patches personally. The current maintainers can be found in [MAINTAINERS.md](./MAINTAINERS.md). Maintainers collectively manage the project's resources and contributors.
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This privilege is granted with some expectation of responsibility: maintainers are people who care about the KitOps project and want to help it grow and improve. A maintainer is not just someone who can make changes, but someone who has demonstrated good judgement and an ability to collaborate with the team, get the most knowledgeable people to review code and docs, contribute high-quality code, and follow through to fix issues (in code or tests).
## Standards-based packaging and versioning system for AI/ML projects.
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* 🚢 Create a **[runnable container from a ModelKit](https://tinyurl.com/5b76p5u3)** with one command! Read [KitOps deploy docs](https://kitops.org/docs/deploy/) for details.
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* 🥂 Get the most out of KitOps' ModelKits by using them with the **[Jozu Hub](https://jozu.ml/)** repository. Or, continue using ModelKits with your existing OCI registry (even on-premises and air-gapped).
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* 🛠️ Use KitOps with Dagger pipelines using our modules from the [Daggerverse](https://daggerverse.dev/mod/github.com/jozu-ai/daggerverse/kit).
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* 🛠️ Use KitOps with Dagger pipelines using our modules from the [Daggerverse](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit).
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* ⛑️ [KitOps works great with Red Hat](https://developers.redhat.com/articles/2024/09/16/enhance-llms-instructlab-kitops) InstructLab and Quay.io products.
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* 🏭 **[Versioning](https://kitops.org/docs/cli/cli-reference/#kit-tag):** Each ModelKit is tagged so everyone knows which dataset and model work together.
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* 🔒 **[Tamper-proofing](https://kitops.org/docs/modelkit/spec/):** Each ModelKit package includes an SHA digest for itself, and every artifact it holds.
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* 🤩 **[Selective-unpacking](https://kitops.org/docs/cli/cli-reference/#kit-unpack):** Unpack only what you need from a ModelKit with the `kit unpack --filter` command - just the model, just the dataset and code, or any other combination.
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* 🤖 **[Automation](https://github.com/marketplace/actions/setup-kit-cli):** Pack or unpack a ModelKit locally or as part of your CI/CD workflow for testing, integration, or deployment (e.g. [GitHub Actions](https://github.com/marketplace/actions/setup-kit-cli) or [Dagger](https://daggerverse.dev/mod/github.com/jozu-ai/daggerverse/kit).
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* 🤖 **[Automation](https://github.com/marketplace/actions/setup-kit-cli):** Pack or unpack a ModelKit locally or as part of your CI/CD workflow for testing, integration, or deployment (e.g. [GitHub Actions](https://github.com/marketplace/actions/setup-kit-cli) or [Dagger](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit).
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* 🐳 **[Deploy containers](https://kitops.org/docs/deploy/):** Generate a basic or custom docker container from any ModelKit.
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* 🚢 **[Kubernetes-ready](https://kitops.org/docs/deploy/):** Generate a Kubernetes / KServe deployment config from any ModelKit.
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* 🪛 **[LLM fine-tuning](https://dev.to/kitops/fine-tune-your-first-large-language-model-llm-with-lora-llamacpp-and-kitops-in-5-easy-steps-1g7f):** Use KitOps to fine-tune a large language model using LoRA.
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As a public community project the KitOps roadmap is always open to feedback. If you think a feature lower in the list is more important, or feel that we've missed an important feature please:
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*[Open an issue](https://github.com/jozu-ai/kitops/issues) in the repo
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*[Open an issue](https://github.com/kitops-ml/kitops/issues) in the repo
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* Tell us in the [KitOps Discord](https://discord.gg/Tapeh8agYy) channel
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* Send us a message on [X / Twitter](https://twitter.com/Kit_Ops)
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## In-Progress
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* Create a [Homebrew cask for KitOps](https://github.com/jozu-ai/homebrew-kitops/issues/6)
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* Create [Python SDK for KitOps](https://github.com/jozu-ai/kitops/issues/118)
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*[Improve handling of TAR files](https://github.com/jozu-ai/kitops/issues/489) generated by Kit
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* Demo: using [ModelKits with MLFlow](https://github.com/jozu-ai/kitops/issues/545)
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* Convert a model from [Hugging Face to ModelKit](https://github.com/jozu-ai/kitops/issues/564)
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* Create a [Homebrew cask for KitOps](https://github.com/kitops-ml/homebrew-kitops/issues/6)
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* Create [Python SDK for KitOps](https://github.com/kitops-ml/kitops/issues/118)
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*[Improve handling of TAR files](https://github.com/kitops-ml/kitops/issues/489) generated by Kit
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* Demo: using [ModelKits with MLFlow](https://github.com/kitops-ml/kitops/issues/545)
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* Convert a model from [Hugging Face to ModelKit](https://github.com/kitops-ml/kitops/issues/564)
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## Recently Completed
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See the full changelog from [0.4](https://github.com/jozu-ai/kitops/releases/tag/v0.4.0) and [0.34](https://github.com/jozu-ai/kitops/releases/tag/v0.3.4)
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See the full changelog from [0.4](https://github.com/kitops-ml/kitops/releases/tag/v0.4.0) and [0.34](https://github.com/kitops-ml/kitops/releases/tag/v0.3.4)
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* Demo: using [ModelKits with Jupyter Notebooks](https://youtu.be/OQPp7QEvk7Q?feature=shared)
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* Add [Windows & Linux for `kit dev`](https://github.com/jozu-ai/kitops/releases/tag/v0.4.0) command
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*[Add `--filter` option](https://github.com/jozu-ai/kitops/releases/tag/v0.4.0) to `kit info` command
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* Add [Windows & Linux for `kit dev`](https://github.com/kitops-ml/kitops/releases/tag/v0.4.0) command
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*[Add `--filter` option](https://github.com/kitops-ml/kitops/releases/tag/v0.4.0) to `kit info` command
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* Deploy [ModelKits as containers](https://kitops.org/docs/deploy/)
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*[Added parameters field](https://github.com/jozu-ai/kitops/pull/514) to datasets and code
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*[Enhanced proxy](https://github.com/jozu-ai/kitops/pull/512) support
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*[Added parameters field](https://github.com/kitops-ml/kitops/pull/514) to datasets and code
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*[Enhanced proxy](https://github.com/kitops-ml/kitops/pull/512) support
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## Roadmap Themes
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### UX Improvements
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*[Pack and convert](https://github.com/jozu-ai/kitops/issues/564) models directly from Hugging Face
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*[Pack and convert](https://github.com/kitops-ml/kitops/issues/564) models directly from Hugging Face
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### Deployment
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Users want to be able to deploy their models through existing CI/CD/CT pipelines. Since KitOps doesn't know the details of a user's deployment pipeline or process we will `unpack` a ModelKit into an appropriate directory structure for one of several deployment targets.
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*[Enhance unpack for deployment-specific directory structures](https://github.com/jozu-ai/kitops/issues/131)
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*[Enhance unpack for deployment-specific directory structures](https://github.com/kitops-ml/kitops/issues/131)
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