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Signed-off-by: Ricardo Aravena <[email protected]>
Signed-off-by: Steven Zou <[email protected]>
Signed-off-by: Wang Yan <[email protected]>
Signed-off-by: Peng Tao <[email protected]>
Signed-off-by: Chlins Zhang <[email protected]>
Signed-off-by: Zhao Chen <[email protected]>
Signed-off-by: Gaius <[email protected]>
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36 changes: 36 additions & 0 deletions .github/workflows/lint.yml
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name: Lint

on:
push:
branches: [main, release-*]
pull_request:
branches: [main, release-*]

permissions:
contents: read

jobs:
lint:
name: Lint
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- name: Checkout code
uses: actions/checkout@692973e3d937129bcbf40652eb9f2f61becf3332

- uses: actions/setup-go@0a12ed9d6a96ab950c8f026ed9f722fe0da7ef32
with:
go-version-file: go.mod
cache: false

- name: Golangci lint
uses: golangci/golangci-lint-action@v6
with:
version: v1.61
args: --verbose

- name: Markdown lint
uses: docker://avtodev/markdown-lint:v1@sha256:6aeedc2f49138ce7a1cd0adffc1b1c0321b841dc2102408967d9301c031949ee
with:
config: '.markdownlint.yml'
args: '**/*.md'
56 changes: 56 additions & 0 deletions .gitignore
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# Binaries for programs and plugins
*.exe
*.exe~

# Test binary, built with `go test -c`
*.test

# Output of the go coverage tool, specifically when used with LiteIDE
*.out

# Dependency directories (remove the comment below to include it)
vendor/
.idea
.vscode
.cache
*.DS_Store
target/
scheduler/test/misc
manager/dist/*
!manager/dist/.gitkeep
.chglog

# vscode
.vscode/*
!.vscode/settings.json
!.vscode/tasks.json
!.vscode/launch.json
!.vscode/extensions.json
*.code-workspace

# General
.DS_Store
.AppleDouble
.LSOverride

# Icon must end with two \r
Icon

# Thumbnails
._*

# Files that might appear in the root of a volume
.DocumentRevisions-V100
.fseventsd
.Spotlight-V100
.TemporaryItems
.Trashes
.VolumeIcon.icns
.com.apple.timemachine.donotpresent

# Directories potentially created on remote AFP share
.AppleDB
.AppleDesktop
Network Trash Folder
Temporary Items
.apdisk
35 changes: 35 additions & 0 deletions .golangci.yml
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run:
deadline: 3m
modules-download-mode: readonly

linters-settings:
gocyclo:
min-complexity: 100
gci:
sections:
- standard
- default

issues:
new: true
exclude-rules:
- linters:
- staticcheck
text: "SA1019:"

linters:
disable-all: true
enable:
- gci
- gofmt
- misspell
- govet
- goconst
- gocyclo
- staticcheck
- errcheck

output:
format: colored-line-number
print-issued-lines: true
print-linter-name: true
6 changes: 6 additions & 0 deletions .markdownlint.yml
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MD010: false

MD013: false

MD046:
style: "fenced"
201 changes: 201 additions & 0 deletions LICENSE
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Apache License
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http://www.apache.org/licenses/

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32 changes: 32 additions & 0 deletions README.md
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# CNAI Model Format Specification

[![LICENSE](https://img.shields.io/github/license/CloudNativeAI/model-spec.svg?style=flat-square)](https://github.com/CloudNativeAI/model-spec/blob/main/LICENSE)
[![GoDoc](https://godoc.org/github.com/CloudNativeAI/model-spec?status.svg)](https://godoc.org/github.com/CloudNativeAI/model-spec)

The Cloud Native Artifacial Intelligence (CNAI) Model Specification aims to provide a standard way to package, distribute and run AI models in a cloud native environment.

## Rationale

Looking back in history, there are clear trends in the evolution of infrastructure. At first, there is the machine centric infrastructure age. GNU/Linux was born there and we saw a boom of Linux distributions then. Then comes the Virtual Machine centric infrastructure age, where we saw the rise of cloud computing and the development of virtualization technologies. The third age is the container centric infrastructure, and we saw the rise of container technologies like Docker and Kubernetes. The fourth age, which has just begun, is the AI model centric infrastructure age, where we will see a burst of technologies and projects around AI model development and deployment.

![img](docs/img/infra-trends.png)

Each of the new ages has brought new technologies and new ways of thinking. The container centric infrastructure has brought us the OCI image specification, which has become the standard for packaging and distributing software. The AI model centric infrastructure will bring us new ways of packaging and distributing AI models. The model specification is an attempt to define a standard to help package, distribute and run AI models in a cloud native environment.

## Current Work

The specification, provides a compatible way to package and distribute models based on the current [OCI image specification](https://github.com/opencontainers/image-spec/) and [the artifacts guidelines](https://github.com/opencontainers/image-spec/blob/main/manifest.md#guidelines-for-artifact-usage). For compatibility reasons, it only contains part of the model metadata, and handles model artifacts as opaque binaries. However, it provides a convient way to package AI models in the container image format and can be used as [OCI volume sources](https://github.com/kubernetes/enhancements/issues/4639) in Kubernetes environments.

For details, please see [the specification](docs/spec.md).

## LICENSE

Apache 2.0 License. Please see [LICENSE](LICENSE) for more information.

## Contributing

Any feedback, suggestions, and contributions are welcome. Please feel free to open an issue or pull request.

Especially, we look forward to integrating the model specification with different model registry implementations (like [Harbor](https://goharbor.io/) and [Kubeflow model registry](https://www.kubeflow.org/docs/components/model-registry/overview/)), as well as existing model centric infrastructure projects like [Huggingface](https://huggingface.co/), [KitOps](https://kitops.ml/), [Kubeflow](https://www.kubeflow.org/), [Lepton](https://www.lepton.ai/), [Ollama](https://github.com/ollama/ollama), [ORAS](https://oras.land/), and others.

Enjoy!
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