{"id":26606850,"url":"https://github.com/kitops-ml/kitops","last_synced_at":"2025-05-15T11:09:28.544Z","repository":{"id":226462478,"uuid":"751983018","full_name":"kitops-ml/kitops","owner":"kitops-ml","description":"An open source DevOps tool for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI 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width=\"1270\" alt=\"KitOps\" src=\"https://github.com/kitops-ml/kitops/assets/10517533/41295471-fe49-4011-adf6-a215f29890c2\" id=\"top\"\u003e\n\n\n## Standards-based packaging and versioning system for AI/ML projects.\n\n[![LICENSE](https://img.shields.io/badge/License-Apache%202.0-yellow.svg)](https://github.com/myscale/myscaledb/blob/main/LICENSE)\n[![Language](https://img.shields.io/badge/Language-go-blue.svg)](https://go.dev/)\n[![Discord](https://img.shields.io/discord/1098133460310294528?logo=Discord)](https://discord.gg/Tapeh8agYy)\n[![Twitter](https://img.shields.io/twitter/url/http/shields.io.svg?style=social\u0026label=Twitter)](https://twitter.com/kit_ops)\n[![Hits](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%kitops-ml%2Fkitops\u0026count_bg=%2379C83D\u0026title_bg=%23555555\u0026icon=\u0026icon_color=%23E7E7E7\u0026title=hits\u0026edge_flat=false)](https://hits.seeyoufarm.com)\n\n[![Official Website](\u003chttps://img.shields.io/badge/-Visit%20the%20Official%20Website%20%E2%86%92-rgb(255,175,82)?style=for-the-badge\u003e)](https://kitops.org?utm_source=github\u0026utm_medium=kitops-readme)\n\n[![Use Cases](\u003chttps://img.shields.io/badge/-KitOps%20Quick%20Start%20%E2%86%92-rgb(122,140,225)?style=for-the-badge\u003e)](https://kitops.org/docs/get-started/?utm_source=github\u0026utm_medium=kitops-readme)\n\n### What is KitOps?\n\nKitOps 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. It's AI/ML platform engineering teams' preferred solution for securely packaging and versioning assets.\n\nKitOps creates a ModelKit for your AI/ML project which includes everything you need to reproduce it 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.\n\nModelKits [simplify the handoffs between data scientists, application developers, and SREs](https://www.youtube.com/watch?v=j2qjHf2HzSQ) working with LLMs and other AI/ML models. Teams and enterprises use KitOps as a secure storage throughout the AI/ML project lifecycle.\n\nUse KitOps to speed up and de-risk all types of AI/ML projects:\n* Predictive models\n* Large language models\n* Computer vision models\n* Multi-modal models\n* Audio models\n* etc...\n\n### 🇪🇺 EU AI Act Compliance 🔒\nFor our friends in the EU - ModelKits are the perfect way to create a library of model versions for EU AI Act compliance because they're tamper-proof, signable, and auditable.\n\n\n### 😍 What's New? ✨\n\n* 🚢 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.\n* 🥂 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).\n* 🛠️ Use KitOps with Dagger pipelines using our modules from the [Daggerverse](https://github.com/kitops-ml/daggerverse).\n* ⛑️ [KitOps works great with Red Hat](https://developers.redhat.com/articles/2024/09/16/enhance-llms-instructlab-kitops) InstructLab and Quay.io products.\n\n\n### Features\n\n* 🎁 **[Unified packaging](https://kitops.org/docs/modelkit/intro/):** A ModelKit package includes models, datasets, configurations, and code. Add as much or as little as your project needs.\n* 🏭 **[Versioning](https://kitops.org/docs/cli/cli-reference/#kit-tag):** Each ModelKit is tagged so everyone knows which dataset and model work together.\n* 🔒 **[Tamper-proofing](https://kitops.org/docs/modelkit/spec/):** Each ModelKit package includes an SHA digest for itself, and every artifact it holds.\n* 🤩 **[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.\n* 🤖 **[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://github.com/kitops-ml/daggerverse).\n* 🐳 **[Deploy containers](https://kitops.org/docs/deploy/):** Generate a basic or custom docker container from any ModelKit.\n* 🚢 **[Kubernetes-ready](https://kitops.org/docs/deploy/):** Generate a Kubernetes / KServe deployment config from any ModelKit.\n* 🪛 **[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.\n* 🎯 **[RAG pipelines](https://www.codeproject.com/Articles/5384392/A-Step-by-Step-Guide-to-Building-and-Distributing):** Create a RAG pipeline for tailoring an LLM with KitOps.\n* 📝 **[Artifact signing](https://kitops.org/docs/next-steps/):** ModelKits and their assets can be signed so you can be confident of their provenance.\n* 🌈 **[Standards-based](https://kitops.org/docs/modelkit/compatibility/):** Store ModelKits in any OCI 1.1-compliant container or artifact registry.\n* 🥧 **[Simple syntax](https://kitops.org/docs/kitfile/kf-overview/):** Kitfiles are easy to write and read, using a familiar YAML syntax.\n* 🩰 **[Flexible](https://kitops.org/docs/kitfile/format/#model):** Reference base models using `model parts`, or store key-value pairs (or any YAML-compatible JSON data) in your Kitfile - use it to keep features, hyperparameters, links to MLOps tool experiments, or validation output.\n* 🏃‍♂️‍➡️ **[Run locally](./docs/src/docs/deploy.md#running-llms-locally):** Kit's Dev Mode lets you run an LLM locally, configure it, and prompt/chat with it instantly.\n* 🤗 **Universal:** ModelKits can be used with any AI, ML, or LLM project - even multi-modal models.\n\n### See KitOps in Action\n\nThere's a video of KitOps in action on the [KitOps site](https://kitops.org/).\n\n## 🚀 Try KitOps in under 15 Minutes\n\n1. [Install the CLI](https://kitops.org/docs/cli/installation/) for your platform.\n2. Follow the [Getting Started](https://kitops.org/docs/get-started/) docs to learn to pack, unpack, and share a ModelKit.\n3. Test drive one of our [ModelKit Quick Starts](https://jozu.ml/organization/jozu-quickstarts) that includes everything you need to run your model including a codebase, dataset, documentation, and of course the model.\n\nFor those who prefer to build from the source, follow [these steps](https://kitops.org/docs/cli/installation/#🛠️-install-from-source) to get the latest version from our repository.\n\n## What is in the box?\n\n**[ModelKit](https://kitops.org/docs/modelkit/intro/):** At the heart of KitOps is the ModelKit, an OCI-compliant packaging format for sharing all AI project artifacts: datasets, code, configurations, and models. By standardizing the way these components are packaged, versioned, and shared, ModelKits facilitate a more streamlined and collaborative development process that is compatible with any MLOps or DevOps tool.\n\n**[Kitfile](https://kitops.org/docs/kitfile/kf-overview/):** A ModelKit is defined by a Kitfile - your AI/ML project's blueprint. It uses YAML to describe where to find each of the artifacts that will be packaged into the ModelKit. The Kitfile outlines what each part of the project is.\n\n**[Kit CLI](https://kitops.org/docs/cli/cli-reference/):** The Kit CLI not only enables users to create, manage, run, and deploy ModelKits -- it lets you pull only the pieces you need. Just need the serialized model for deployment? Use `unpack --model`, or maybe you just want the training datasets? `unpack --datasets`.\n\n## Need Help?\n\n### Join KitOps community\n\nFor support, release updates, and general KitOps discussion, please join the [KitOps Discord](https://discord.gg/Tapeh8agYy). Follow [KitOps on X](https://twitter.com/Kit_Ops) for daily updates.\n\nIf you need help there are several ways to reach our community and [Maintainers](./MAINTAINERS.md) outlined in our [support doc](./SUPPORT.md)\n\n### Reporting Issues and Suggesting Features\n\nYour insights help KitOps evolve as an open standard for AI/ML. We *deeply value* the issues and feature requests we get from users in our community :sparkling_heart:. To contribute your thoughts,navigate to the **Issues** tab and hitting the **New Issue** green button. Our templates guide you in providing essential details to address your request effectively.\n\n### Joining the KitOps Contributors\n\nWe ❤️ our KitOps community and contributors. To learn more about the many ways you can contribute (you don't need to be a coder) and how to get started see our [Contributor's Guide](./CONTRIBUTING.md). Please read our [Governance](./GOVERNANCE.md) and our [Code of Conduct](./CODE-OF-CONDUCT.md) before contributing.\n\n#### 📢 KitOps Community Calls (bi-weekly)\n\n**Wednesdays @ 13:30 – 14:00**\n**Time zone**: America/Toronto\n**Video call link**: [Google Meet](https://meet.google.com/zfq-uprp-csd)\nOr dial: (CA) +1 647-736-3184 PIN: 144 931 404#\nMore phone numbers: [Phone Numbers](https://tel.meet/zfq-uprp-csd?pin=1283456375953)\n\n### A Community Built on Respect\n\nAt KitOps, inclusivity, empathy, and responsibility are at our core. Please read our [Code of Conduct](./CODE-OF-CONDUCT.md) to understand the values guiding our community.\n\n## Roadmap\n\nWe [share our roadmap openly](./ROADMAP.md) so anyone in the community can provide feedback and ideas. Let us know what you'd like to see by pinging us on Discord or creating an issue.\n\n---\n\n\u003cdiv align=\"center\" style=\"align-items: center;\"\u003e\n        \u003ca href=\"#top\"\u003e\n            \u003cimg src=\"https://img.shields.io/badge/Back_to_Top-black?style=for-the-badge\u0026logo=github\u0026logoColor=white\" alt=\"Back to Top\"\u003e\n        \u003c/a\u003e\n\u003c/div\u003e\n\n\n\n","funding_links":[],"categories":["tensorflow","Go"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkitops-ml%2Fkitops","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkitops-ml%2Fkitops","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkitops-ml%2Fkitops/lists"}