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Co-authored-by: Gregory P. Smith <greg@krypto.org>
Co-authored-by: Donghee Na <donghee.na@python.org>
Co-authored-by: devdanzin <74280297+devdanzin@users.noreply.github.com>
Copy file name to clipboardExpand all lines: getting-started/generative-ai.rst
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Generative AI
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=============
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Generative AI tools have evolved rapidly, and their suggested results can be helpful. As with using any tool, the resulting contribution is
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the responsibility of the contributor. We value good code, concise accurate documentation, and avoiding unneeded code
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churn. Discretion, good judgment, and critical thinking are the foundation of all good contributions, regardless of the
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tools used in their creation.
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Generative AI tools are evolving rapidly, and their work can be helpful. As with using any tool, the resulting
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contribution is the responsibility of the contributor. We value good code, concise accurate documentation,
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and avoiding unneeded code churn. Discretion, good judgment, and critical thinking are the foundation of all good
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contributions, regardless of the tools used in their creation.
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Acceptable uses
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===============
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Unacceptable uses
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=================
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Maintainers may close issues and PRs that are not useful or productive, including
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those that are fully generated by AI. If a contributor repeatedly opens unproductive
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issues or PRs, they may be blocked.
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Maintainers may close issues and PRs that are not useful or productive, regardless whether
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AI was used or not.
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If a contributor repeatedly opens unproductive issues or PRs, they may be blocked.
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Sometimes AI assisted tools make failing unit tests pass by altering or bypassing the tests rather than addressing the
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underlying problem in the code. Such changes do not represent a real fix and are not acceptable.
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Considerations for success
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==========================
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- While AI assisted tools such as autocompletion can enhance productivity, they sometimes rewrite entire code blocks instead of making small, focused edits.
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This can make it more difficult to review changes and to fully understand both the original intent of the code and the rationale behind the new modifications.
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Maintaining consistency with the original code helps preserve clarity, traceability, and meaningful reviews and also helps us avoid unnecessary code churn.
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- Sometimes AI assisted tools make failing unit tests pass by altering or bypassing the tests rather than addressing the underlying problem in the code.
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Such changes do not represent a real fix. Authors must review the work done by AI tooling in detail to ensure it actually makes sense before proposing it as a PR.
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- Keep the following principles for the quality of your contributions in mind whether you use generative AI or not:
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- Consider whether the change is necessary
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- Make minimal, focused changes
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- Follow existing coding style and patterns
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- Write tests that exercise the change
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Authors must review the work done by AI tooling in detail to ensure it actually makes sense before proposing it as a PR.
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We expect PR authors to be able to explain their proposed changes in their own words.
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Disclose the use of AI tools in the PR description, and be prepared to explain how the tool was used and what
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changes it made.
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Whether you are using Generative AI or not, keep the following principles in mind for the quality
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