Onboard the GitHub Action based Issue-Labeler #115256
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Pull Request Overview
This PR implements GitHub Action workflows to replace the GitHub App-based issue labeler, enabling training, model promotion, prediction for pull requests and issues, as well as regular cache retention.
- Added workflows for training, promoting, predicting labels for PRs and issues, and maintaining cache retention.
- Configured input parameters, environment variables, and conditional jobs for different phases of the labeler pipeline.
Reviewed Changes
Copilot reviewed 5 out of 5 changed files in this pull request and generated no comments.
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| File | Description |
|---|---|
| .github/workflows/labeler-train.yml | Added workflow to train models for issues and pull requests. |
| .github/workflows/labeler-promote.yml | Added workflow to promote models from staging to active use. |
| .github/workflows/labeler-predict-pulls.yml | Added workflow to predict pull request labels using a trained model. |
| .github/workflows/labeler-predict-issues.yml | Added workflow to predict issue labels using a trained model. |
| .github/workflows/labeler-cache-retention.yml | Added workflow to periodically refresh cached models to prevent eviction. |
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Tagging subscribers to this area: @dotnet/runtime-infrastructure |
carlossanlop
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May 2, 2025
ericstj
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May 3, 2025
ericstj
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May 6, 2025
ericstj
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May 6, 2025
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/ba-g Helix Queue Insights (preview) is stuck, but not applicable here |
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These workflows replace the issue-labeler implementation that runs as a GitHub app, allowing training and prediction for the repository's labels without the need for an external service.
References:
Once this is merged, I'll run the 'Labeler: Training' workflow to train new prediction models, then 'Labeler: Promotion' workflow to promote the models into active use, and then decommission the integration of the issue-labeler app for this repo.