Keep K3 suite selection and report-schema scoring in bash, merge K3/vision dataset_args into dpv4 yamls, and pin EvalScope at 735d920ee911 with local patches. Co-authored-by: Cursor <cursoragent@cursor.com>
34 lines
867 B
YAML
34 lines
867 B
YAML
name: release
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on:
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push:
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tags:
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- 'v**'
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concurrency:
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group: ${{ github.workflow }}-${{ github.ref }}-publish
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cancel-in-progress: true
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jobs:
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build-n-publish:
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runs-on: ubuntu-22.04
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env:
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FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: true
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#if: startsWith(github.event.ref, 'refs/tags')
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python 3.10
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uses: actions/setup-python@v5
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with:
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python-version: '3.10'
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- name: Set up Node.js
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uses: actions/setup-node@v4
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with:
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node-version: '22'
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- name: Install build dependencies
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run: pip install build twine '.[service]'
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- name: Build and verify EvalScope
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run: make package
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- name: Publish package to PyPI
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run: twine upload dist/* --skip-existing -u __token__ -p ${{ secrets.PYPI_TOKEN }}
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