AI prompts
base on An open source DevOps tool for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI artifact.
<img width="1270" alt="KitOps" src="https://github.com/kitops-ml/kitops/assets/10517533/41295471-fe49-4011-adf6-a215f29890c2" id="top">
## KitOps: Standards-based packaging & versioning for AI/ML projects
[](./LICENSE)
[](https://discord.gg/Tapeh8agYy)
[](https://twitter.com/kit_ops)
## π Table of Contents
- [What is KitOps?](#what-is-kitops)
- [KitOps Architecture](#kitops-architecture)
- [Try KitOps](#try-kitops-in-under-15-minutes)
- [Benefits](#key-benefits)
- [Community & Support](#join-kitops-community)
## What is KitOps?
KitOps is a CNCF open standards project for packaging, versioning, and securely sharing AI/ML projects. Built on the OCI ([Open Container Initiative](https://opencontainers.org/)) standard, it integrates seamlessly with your existing AI/ML, software development, and DevOps tools.
Itβs the preferred solution for packaging, versioning, and managing assets in security-conscious enterprises, governments, and cloud operators who need to self-host AI models and agents.
### KitOps and the CNCF
KitOps is a CNCF project, and is governed by the same organization and policies that manage Kubernetes, OpenTelemetry, and Prometheus. [This video provides an outline of KitOps in the CNCF](https://youtu.be/iK9mnU0prRU?feature=shared).
KitOps is also the reference implementation of the [CNCF's ModelPack specification](https://github.com/modelpack/model-spec) for a vendor-neutral AI/ML interchange format.
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## KitOps Architecture
### ModelKit
KitOps packages your project into a [ModelKit](https://kitops.org/docs/modelkit/intro/) β a self-contained, immutable bundle that includes everything required to reproduce, test, or deploy your AI/ML model.
ModelKits can include code, model weights, datasets, prompts, experiment run results and hyperparameters, metadata, environment configurations, and more.
ModelKits are:
* Tamper-proof β Ensuring consistency and traceability
* Signable β Enabling trust and verification
* Compatible β Natively stored and retrieved in all major container registries
> *ModelKits elevate AI artifacts to first-class, governed assets β just like application code.*
### Kitfile
A [Kitfile](https://kitops.org/docs/kitfile/kf-overview/) defines your ModelKit. Written in YAML, it maps where each artifact lives and how it fits into the project.
### Kit CLI
The [Kit CLI](https://kitops.org/docs/cli/cli-reference/) not only enables you to create, manage, run, and deploy ModelKits -- it lets you pull only the pieces you need.
### π₯ Watch KitOps in Action
[](https://www.youtube.com/watch?v=j2qjHf2HzSQ)
This video shows how KitOps streamlines collaboration between data scientists, developers, and SREs using ModelKits.
## π Try KitOps in under 15 Minutes
1. **Install the CLI**: [for MacOS, Windows, and Linux](https://kitops.org/docs/cli/installation/).
2. **Pack your first ModelKit**: Learn how to pack, push, and pull using our [Getting Started](...) guide.
3. **Explore a Quick Start**: [Try pre-built ModelKits](https://jozu.ml/organization/jozu-quickstarts) for LLMs, CVs, and more.
For those who prefer to build from the source, follow [these steps](https://kitops.org/docs/cli/installation/#π οΈ-install-from-source) to get the latest version from our repository.
## Key Benefits
KitOps was built to bring discipline to productizing AI/ML projects, with:
* π¦ Unified packaging and versioning of AI/ML assets
* π Secure, signed distribution
* π οΈ Toolchain compatibility via OCI
* βοΈ Production-ready for enterprise ML workflows
* π’ Create runnable containers for Kubernetes or docker
* π Audit-ready lineage tracking
To get the most out of KitOps' ModelKits, use them with the **[Jozu Hub](https://jozu.com/)**. Jozu Hub can be installed behind your firewall and use your existing OCI registry in a private cloud, datacenter, or even in an air-gapped environment.
### Simplify Team Collaboration
ModelKits streamline handoffs between:
* Data scientists preparing and training models
* Application developers integrating models into services
* SREs deploying and maintaining models in production
This ensures reliable, repeatable workflows for both development and operations.
### Use KitOps to Speed Up and De-risk AI/ML Projects
KitOps supports packaging for a wide variety of models:
* Large language models
* Computer vision models
* Multi-modal models
* Predictive models
* Audio models
* etc...
> πͺπΊ EU AI Act Compliance π
>
> For 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.
## Join KitOps Community
For 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.
If you need help there are several ways to reach our community and [Maintainers](./MAINTAINERS.md) outlined in our [support doc](./SUPPORT.md)
### Joining the KitOps Contributors
We β€οΈ 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.
### Reporting Issues and Suggesting Features
Your 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 click the **New Issue** button.
### KitOps Community Calls (bi-weekly)
**π
Wednesdays @ 13:30 β 14:00 (America/Toronto)**
- π [Google Meet](https://meet.google.com/zfq-uprp-csd)
- βοΈ +1 647-736-3184 (PIN: 144 931 404#)
- π [More numbers](https://tel.meet/zfq-uprp-csd?pin=1283456375953)
</details>
### A Community Built on Respect
At 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.
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", Assign "at most 3 tags" to the expected json: {"id":"12080","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"