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Add model workflows (#9462)
* Add GitHub workflows for issue completeness, duplicate detection, onboarding, and contribution quality checks * Fix indentation * Refactor GitHub workflows for issue handling * Consolidate to two triage workflows * Update .github/workflows/models_pr_triage.yml Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
Ben Meadors
GitHub
138
.github/workflows/models_pr_triage.yml
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138
.github/workflows/models_pr_triage.yml
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name: PR Triage (Models)
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on:
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pull_request_target:
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types: [opened]
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permissions:
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pull-requests: write
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issues: write
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models: read
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concurrency:
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group: ${{ github.workflow }}-${{ github.event.pull_request.number }}
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cancel-in-progress: true
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jobs:
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triage:
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if: ${{ github.repository == 'meshtastic/firmware' && github.event.pull_request.user.type != 'Bot' }}
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runs-on: ubuntu-latest
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steps:
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# ─────────────────────────────────────────────────────────────────────────
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# Step 1: Check if PR already has automation/type labels (skip if so)
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# ─────────────────────────────────────────────────────────────────────────
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- name: Check existing labels
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uses: actions/github-script@v8
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id: check-labels
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with:
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script: |
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const skipLabels = new Set(['automation']);
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const typeLabels = new Set(['bugfix', 'hardware-support', 'enhancement', 'dependencies', 'submodules', 'github_actions', 'trunk', 'cleanup']);
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const prLabels = context.payload.pull_request.labels.map(l => l.name);
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const shouldSkipAll = prLabels.some(l => skipLabels.has(l));
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const hasTypeLabel = prLabels.some(l => typeLabels.has(l));
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core.setOutput('skip_all', shouldSkipAll ? 'true' : 'false');
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core.setOutput('has_type_label', hasTypeLabel ? 'true' : 'false');
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# ─────────────────────────────────────────────────────────────────────────
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# Step 2: Quality check (spam/AI-slop detection)
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# ─────────────────────────────────────────────────────────────────────────
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- name: Detect spam or low-quality content
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if: steps.check-labels.outputs.skip_all != 'true'
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uses: actions/ai-inference@v2
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id: quality
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continue-on-error: true
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with:
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max-tokens: 20
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prompt: |
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Is this GitHub pull request spam, AI-generated slop, or low quality?
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Title: ${{ github.event.pull_request.title }}
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Body: ${{ github.event.pull_request.body }}
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Respond with exactly one of: spam, ai-generated, needs-review, ok
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system-prompt: You detect spam and low-quality contributions. Be conservative - only flag obvious spam or AI slop.
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model: openai/gpt-4o-mini
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- name: Apply quality label if needed
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if: steps.check-labels.outputs.skip_all != 'true' && steps.quality.outputs.response != '' && steps.quality.outputs.response != 'ok'
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uses: actions/github-script@v8
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id: quality-label
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env:
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QUALITY_LABEL: ${{ steps.quality.outputs.response }}
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with:
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script: |
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const label = (process.env.QUALITY_LABEL || '').trim().toLowerCase();
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const labelMeta = {
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'spam': { color: 'd73a4a', description: 'Possible spam' },
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'ai-generated': { color: 'fbca04', description: 'Possible AI-generated low-quality content' },
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'needs-review': { color: 'f9d0c4', description: 'Needs human review' },
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};
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const meta = labelMeta[label];
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if (!meta) return;
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// Ensure label exists
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try {
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await github.rest.issues.getLabel({ owner: context.repo.owner, repo: context.repo.repo, name: label });
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} catch (e) {
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if (e.status !== 404) throw e;
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await github.rest.issues.createLabel({ owner: context.repo.owner, repo: context.repo.repo, name: label, color: meta.color, description: meta.description });
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}
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// Apply label
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await github.rest.issues.addLabels({ owner: context.repo.owner, repo: context.repo.repo, issue_number: context.payload.pull_request.number, labels: [label] });
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core.setOutput('is_spam', 'true');
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# ─────────────────────────────────────────────────────────────────────────
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# Step 3: Auto-label PR type (bugfix/hardware-support/enhancement)
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# ─────────────────────────────────────────────────────────────────────────
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- name: Classify PR for labeling
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if: steps.check-labels.outputs.skip_all != 'true' && steps.check-labels.outputs.has_type_label != 'true' && (steps.quality.outputs.response == 'ok' || steps.quality.outputs.response == '')
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uses: actions/ai-inference@v2
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id: classify
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continue-on-error: true
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with:
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max-tokens: 30
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prompt: |
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Classify this pull request into exactly one category.
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Return exactly one of: bugfix, hardware-support, enhancement
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Use bugfix if it fixes a bug, crash, or incorrect behavior.
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Use hardware-support if it adds or improves support for a specific hardware device/variant.
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Use enhancement if it adds a new feature, improves performance, or refactors code.
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Title: ${{ github.event.pull_request.title }}
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Body: ${{ github.event.pull_request.body }}
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system-prompt: You classify pull requests into categories. Be conservative and pick the most appropriate single label.
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model: openai/gpt-4o-mini
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- name: Apply type label
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if: steps.check-labels.outputs.skip_all != 'true' && steps.check-labels.outputs.has_type_label != 'true' && steps.classify.outputs.response != ''
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uses: actions/github-script@v8
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env:
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TYPE_LABEL: ${{ steps.classify.outputs.response }}
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with:
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script: |
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const label = (process.env.TYPE_LABEL || '').trim().toLowerCase();
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const labelMeta = {
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'bugfix': { color: 'd73a4a', description: 'Bug fix' },
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'hardware-support': { color: '0e8a16', description: 'Hardware support addition or improvement' },
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'enhancement': { color: 'a2eeef', description: 'New feature or enhancement' },
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};
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const meta = labelMeta[label];
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if (!meta) return;
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// Ensure label exists
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try {
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await github.rest.issues.getLabel({ owner: context.repo.owner, repo: context.repo.repo, name: label });
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} catch (e) {
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if (e.status !== 404) throw e;
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await github.rest.issues.createLabel({ owner: context.repo.owner, repo: context.repo.repo, name: label, color: meta.color, description: meta.description });
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}
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// Apply label
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await github.rest.issues.addLabels({ owner: context.repo.owner, repo: context.repo.repo, issue_number: context.payload.pull_request.number, labels: [label] });
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