KitOps is your ultimate toolkit for transforming how you build, package, and deploy AI/ML models. Designed to enhance collaboration among data scientists, application developers, and SREs working on developing, integrating or managing self-hosted AI/ML models. KitOps simplifies bundling models with their dependencies, configurations, and environments into a standardized, portable package. Say goodbye to compatibility concerns and hello to smooth model sharing.
ModelKit: At the heart of KitOps is the ModelKit, an OCI-compliant packaging format that enables the seamless sharing of all necessary artifacts involved in the AI/ML model lifecycle. This includes datasets, code, configurations, and the models themselves. By standardizing the way these components are packaged, ModelKit facilitates a more streamlined and collaborative development process that is compatible with nearly any tool.
Kitfile: Complementing the ModelKit is the Kitfile, AI/ML project's blueprint, a YAML-based configuration file that simplifies the sharing of model, dataset, and code configurations. The Kitfile is designed with both ease of use and security in mind, ensuring that configurations can be efficiently packaged and shared without compromising on safety or governance.
Kit CLI: Your magic wand for AI/ML collaboration. The Kit CLI is a powerful tool that enables users to create, manage, run, and deploy ModelKits using Kitfiles. Whether you are packaging a new model for development or deploying an existing model into production, the Kit CLI provides the necessary commands and functionalities to streamline your workflow.
KitOps enhances the end-to-end lifecycle of AI/ML model management, making it as streamlined as managing containerized applications. It's about enhancing collaboration, streamlining processes, and unlocking a world of possibilities for AI/ML innovation.
Dive into the world of KitOps with ease! Whether you're looking to streamline your AI/ML workflows or explore the power of ModelKits, getting started with Kit is straightforward.
Get started with the Kit CLI by downloading a pre-built binary. Choose the latest tagged version for the most stable release, or explore the next tag for our development builds.
For installation instructions and selecting the right binary for your platform, please refer to our Installation Guide.
To launch Kit, simply open a terminal and type:
kitThis command will display a list of available actions to supercharge your AI/ML projects.
For those who prefer to build from the source, follow these steps to get the latest version directly from our repository:
- Clone the Repository: Clone the KitOps source code to your local machine:
git clone https://github.com/jozu-ai/kitops.git
cd kitops- Build the Kit CLI: Compile the source code into an executable named kit:
go build -o kit- Run Your Build: Execute the built CLI to see all available commands:
./kitOr, for direct execution during development:
go run .Your insights help Kit evolve as an open standard for AI/ML. We deeply value the issues and feature requests we get from users in our community 💖. 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.
We ❤️ our Kit 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. Please read our Governance and our Code of Conduct before contributing.
If you need help there are several ways to reach our community and Maintainers outlined in our support doc
At KitOps, inclusivity, empathy, and responsibility are at our core. Please read our Code of Conduct to understand the values guiding our community..