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Merge pull request #30916 from github/repo-sync

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Repo sync
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docs-bot
2024-01-03 12:29:46 -05:00
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parent c80a7788c8 59bc4cb9ae
commit aadcfc2f46
4 changed files with 4 additions and 3 deletions
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2
.github/workflows/sync-search-pr.yml vendored
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@@ -34,7 +34,7 @@ env:
jobs:
dryRunElasticsearchIndexes:
runs-on: ${{ fromJSON('["ubuntu-latest", "ubuntu-20.04-xl"]')[github.repository == 'github/docs-internal'] }}
if: github.repository == 'github/docs-internal' || github.repository == 'github/docs'
if: github.repository == 'github/docs-internal'
steps:
- name: Check out repo
uses: actions/checkout@3df4ab11eba7bda6032a0b82a6bb43b11571feac # v4.0.0

1
content/account-and-profile/setting-up-and-managing-your-personal-account-on-github/managing-your-personal-account/converting-a-user-into-an-organization.md
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@@ -33,6 +33,7 @@ shortTitle: User into an organization
- Since organizations cannot star repositories, you will no longer have access to your original list of starred repositories.
- You will no longer have access to the list of users you were following from your user account.
- Any followers of your user account will not automatically follow the new organization.
{% ifversion projects-v2 %}- Any existing collaborators on your projects will still have access to those projects in the new organization.{% endif %}
{% endwarning %}
{% ifversion fpt or ghec or ghes %}

2
content/code-security/code-scanning/managing-code-scanning-alerts/about-autofix-for-codeql-code-scanning.md
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@@ -49,7 +49,7 @@ Any autofix suggestions are generated and stored within the {% data variables.pr
{% data variables.product.prodname_dotcom %} uses an automated test harness to continuously monitor the quality of autofix suggestions. This allows us to understand how the autofix suggestions generated by the LLM change as the model develops.
The test harness includes a set of over 700 JavaScript/TypeScript alerts from a diverse set of public repositories where the highlighted code has test coverage. Autofix suggestions for these alerts are tested to see how good they are, that is, how much a developer would need to edit them before commiting them to the codebase. For many of the test alerts, autofixes generated by the LLM could be committed as-is to fix the alert while continuing to successfully pass all the existing CI tests.
The test harness includes a set of over 700 JavaScript/TypeScript alerts from a diverse set of public repositories where the highlighted code has test coverage. Autofix suggestions for these alerts are tested to see how good they are, that is, how much a developer would need to edit them before committing them to the codebase. For many of the test alerts, autofixes generated by the LLM could be committed as-is to fix the alert while continuing to successfully pass all the existing CI tests.
In addition, the system is stress-tested to check for any potential harm (often referred to as red teaming), and a filtering system on the LLM helps prevent potentially harmful suggestions being displayed to users.

2
content/code-security/secret-scanning/about-the-regular-expression-generator-for-custom-patterns.md
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@@ -51,7 +51,7 @@ The {% data variables.secret-scanning.custom-pattern-regular-expression-generato
## Limitations of the {% data variables.secret-scanning.custom-pattern-regular-expression-generator %}
Depending on factors such as your input description and examples, you may experience different levels of performance when using the {% data variables.secret-scanning.custom-pattern-regular-expression-generator %}. You need to be as specific as possible with your description, and provide different types of examples of tokens that match your pattern, to be sure that the regular expression incompasses all the patterns you want {% data variables.product.prodname_secret_scanning %} to search for.
Depending on factors such as your input description and examples, you may experience different levels of performance when using the {% data variables.secret-scanning.custom-pattern-regular-expression-generator %}. You need to be as specific as possible with your description, and provide different types of examples of tokens that match your pattern, to be sure that the regular expression encompasses all the patterns you want {% data variables.product.prodname_secret_scanning %} to search for.
Also, the model used by the {% data variables.secret-scanning.custom-pattern-regular-expression-generator %} has been trained on natural language content written predominantly in English. As a result, you may notice differing performance when providing the generator with natural language input prompts in languages other than English.