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- 2026년 8월 25일 14:25
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/canonical/inference-snap-maker-sdk --skill github-workflows명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
| name | github-workflows |
| description | Create GitHub Actions workflow files for inference snap repositories. |
| trigger | Keywords like "add github workflows", "create CI/CD workflows", "set up github actions", "add workflow files" |
| scope | user |
Create the .github/workflows/ directory with proven CI/CD workflow files for inference snap repositories. These workflows handle building, testing, CLA checking, and engine validation.
Triggered on PR labels for building and testing pull requests.
# This workflow is used to build and test pull requests when specific labels are applied.
# Supported labels: trigger-build, trigger-tests
name: PR Label
on:
pull_request:
types: [ labeled ]
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number }}
cancel-in-progress: true
permissions:
contents: read
pull-requests: write
actions: read
jobs:
build-test:
name: ${{ github.event.label.name }}
uses: canonical/inference-snaps-dev/.github/workflows/reuse-pr-build-test.yaml@v2
with:
trigger-label: ${{ github.event.label.name }}
pr-number: "${{ github.event.pull_request.number }}"
build-runner: |
[
["amd64", "large", "noble", "self-hosted"],
["arm64", "noble", "self-hosted"]
]
test-jobs-matrix: |
[
{
"job-queue": "maas-systemtests-amd64",
"provision-data": "distro: noble",
"select-engine": "cpu",
"test-chat-tps": true,
"test-image-prompt": true
},
{
"job-queue": "anbox-nvidia-amd64",
"provision-data": "distro: noble",
"install-nvidia-driver-version": 595,
"select-engine": "nvidia-gpu",
"test-chat-tps": true,
"expected-tps": 9.4,
"test-image-prompt": true
}
]
snap-name: {{SNAP_NAME}}
testflinger-client-id: ${{ vars.TESTFLINGER_CLIENT_ID }}
secrets:
store-credentials: ${{ secrets.STORE_LOGIN_PR }}
github-token: ${{ secrets.GITHUB_TOKEN }}
testflinger-secret-key: ${{ secrets.TESTFLINGER_SECRET_KEY }}
# This workflow is used to validate pull requests.
# It includes the Canonical CLA check and engine validation.
name: PR Checks
on: [pull_request]
permissions:
contents: read
pull-requests: read
jobs:
cla:
runs-on: ubuntu-slim
steps:
- name: Check if CLA signed
uses: canonical/has-signed-canonical-cla@v2
validate:
runs-on: [ ubuntu-latest ]
steps:
- name: Checkout code
uses: actions/checkout@v7
with:
# Prevent usage of simulated merge commit of PR
ref: ${{ github.event.pull_request.head.sha || github.sha }}
- name: Checkout inference-snap-cli
uses: actions/checkout@v7
with:
repository: canonical/inference-snaps-cli
{{ }}
# This workflow is used to build and publish the snap to the store on every push to main.
name: CICD
on:
push:
branches:
- main
workflow_dispatch: # manual trigger
# Keep one CICD run active at a time so publish/test/promote happen in order
concurrency:
group: ${{ github.workflow }}
queue: max
jobs:
cicd:
if: github.repository == 'canonical/{{SNAP_REPOSITORY}}' # do not run on forks
uses: canonical/inference-snaps-dev/.github/workflows/reuse-cicd.yaml@v2
with:
build-runner: |
[
["amd64", "large", "noble", "self-hosted"],
["self-hosted", "arm64", "noble"]
]
store-track: latest
snap-name: {{SNAP_NAME}}
smoke-test-engine: cpu
.github/workflows/ directory in the target repository.snap-name in testflinger-tests.yaml to match the target snap namevalidate-engines.yaml, replace ref: {{ CLI_TAG }} with the SAME
inference-snaps-cli tag used by the cli part in snap/snapcraft.yamltest-image-prompt only for vision models; drop it (or set false) for
text-only models. Only set expected-tps when you have a real measured
baseline for that model+engine — do not copy another model's number.cpu, nvidia-gpu); keep unrelated example jobs commented out.<snap-name> with the actual snap name.validate-engines.yaml's inference-snaps-cli ref to the same version as
the cli part in snap/snapcraft.yaml; never leave the placeholder.test-image-prompt/expected-tps from the model's real capabilities and
measured baselines — do not carry over another model's values.