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content/code-security/code-scanning/managing-your-code-scanning-configuration/enabling-delegated-alert-dismissal-for-code-scanning.md

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## About enabling delegated alert dismissal
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{% data reusables.advanced-security.delegated-alert-dismissal-beta %}
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{% data reusables.security.delegated-alert-dismissal-intro %}
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## Configuring delegated dismissal for a repository
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1. Click **Save configuration**.
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1. Apply the security configuration to all (or selected) repositories in your organization. See [AUTOTITLE](/code-security/securing-your-organization/enabling-security-features-in-your-organization/applying-a-custom-security-configuration).
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## Configuring delegated dismissal for an enterprise
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You must configure delegated dismissal for your enterprise using a custom security configuration. You can then apply the security configuration to all (or selected) repositories in your enterprise.
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1. Create a new custom security configuration, or edit an existing one. See [AUTOTITLE](/admin/managing-code-security/securing-your-enterprise/creating-a-custom-security-configuration-for-your-enterprise).
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1. When creating the custom security configuration, under "{% data variables.product.prodname_code_scanning %}", ensure that the dropdown menu for "Prevent direct alert dismissals" is set to **Enabled**.
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1. Click **Save configuration**.
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1. Apply the security configuration to all (or selected) repositories in your enterprise. See [AUTOTITLE](/admin/managing-code-security/securing-your-enterprise/applying-a-custom-security-configuration-to-your-enterprise).
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To learn more about security configurations, see [AUTOTITLE](/code-security/securing-your-organization/introduction-to-securing-your-organization-at-scale/about-enabling-security-features-at-scale).

content/copilot/concepts/about-assigning-tasks-to-copilot.md

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## Further reading
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* **Hands-on practice**: Try the [Expand your team with {% data variables.copilot.copilot_coding_agent %}](https://github.com/skills/expand-your-team-with-copilot/) Skills course for practical experience with {% data variables.copilot.copilot_coding_agent %}.
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* [AUTOTITLE](/copilot/using-github-copilot/coding-agent)
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* [AUTOTITLE](/copilot/responsible-use-of-github-copilot-features/responsible-use-of-copilot-coding-agent-on-githubcom)
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* [AUTOTITLE](/copilot/customizing-copilot/customizing-the-development-environment-for-copilot-coding-agent)

content/copilot/how-tos/agents/copilot-coding-agent/best-practices-for-using-copilot-to-work-on-tasks.md

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To do that, it will need your project's dependencies. {% data variables.product.prodname_copilot_short %} can discover and install these dependencies itself via a process of trial and error - but this can be slow and unreliable, given the non-deterministic nature of large language models (LLMs).
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You can configure a `copilot-setup-steps.yml` file to pre-install these dependencies before the agent starts working so it can hit the ground running. For more information, see [AUTOTITLE](/copilot/customizing-copilot/customizing-the-development-environment-for-copilot-coding-agent#preinstalling-tools-or-dependencies-in-copilots-environment).
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## Further reading
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* **Hands-on practice**: Try the [Expand your team with {% data variables.copilot.copilot_coding_agent %}](https://github.com/skills/expand-your-team-with-copilot/) Skills course for practical experience with {% data variables.copilot.copilot_coding_agent %}.

content/copilot/how-tos/ai-models/configuring-access-to-ai-models-in-copilot.md

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For information about the AI models available in {% data variables.product.prodname_copilot_short %}, see [AUTOTITLE](/copilot/using-github-copilot/ai-models/supported-ai-models-in-copilot).
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To learn how {% data variables.copilot.copilot_chat_short %} serves different AI models, see [AUTOTITLE](/copilot/reference/ai-models/how-copilot-serves-ai-models).
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## Setup for individual use
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If you have a {% data variables.copilot.copilot_free_short %}, {% data variables.copilot.copilot_pro_short %}, or {% data variables.copilot.copilot_pro_plus_short %} plan, you may need to enable access to certain models before using them.

content/copilot/how-tos/ai-models/index.md

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redirect_from:
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- /copilot/using-github-copilot/ai-models
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---
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content/copilot/reference/ai-models/choosing-the-right-ai-model-for-your-task.md

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* For detailed model specs and pricing, see [AUTOTITLE](/copilot/using-github-copilot/ai-models/supported-ai-models-in-copilot).
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* For more examples of how to use different models, see [AUTOTITLE](/copilot/using-github-copilot/ai-models/comparing-ai-models-using-different-tasks).
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* To switch between models, refer to [AUTOTITLE](/copilot/using-github-copilot/ai-models/changing-the-ai-model-for-copilot-chat) or [AUTOTITLE](/copilot/using-github-copilot/ai-models/changing-the-ai-model-for-copilot-code-completion).
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* To learn how {% data variables.copilot.copilot_chat_short %} serves different AI models, see [AUTOTITLE](/copilot/reference/ai-models/how-copilot-serves-ai-models).
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---
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title: How Copilot serves AI models
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intro: 'Learn how {% data variables.copilot.copilot_chat_short %} serves different AI models.'
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versions:
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feature: copilot
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topics:
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- Copilot
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---
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{% data variables.product.prodname_copilot %} can use a variety of AI models. This article explains how {% data variables.product.prodname_copilot_short %} serves these models.
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## OpenAI models
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Used for:
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* {% data variables.copilot.copilot_o3 %}
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* {% data variables.copilot.copilot_o4_mini %}
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These models are hosted by OpenAI and {% data variables.product.github %}'s Azure tenant when used in {% data variables.product.prodname_copilot %}. OpenAI makes the [following data commitment](https://openai.com/enterprise-privacy/): _We [OpenAI] do not train our models on your business data by default_. {% data variables.product.github %} maintains a [zero data retention agreement](https://platform.openai.com/docs/guides/your-data) with OpenAI.
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When using OpenAI's models, input requests and output responses continue to run through {% data variables.product.prodname_copilot %}'s content filters for public code matching, when applied, along with those for harmful or offensive content.
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## Anthropic models
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Used for:
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* {% data variables.copilot.copilot_claude_opus %}
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* {% data variables.copilot.copilot_claude_sonnet_35 %}
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* {% data variables.copilot.copilot_claude_sonnet_37 %}
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* {% data variables.copilot.copilot_claude_sonnet_37 %} Thinking
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* {% data variables.copilot.copilot_claude_sonnet_40 %}
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{% data variables.copilot.copilot_claude_opus %} and {% data variables.copilot.copilot_claude_sonnet_40 %} are hosted by Anthropic PBC and Google Cloud Platform. {% data variables.copilot.copilot_claude_sonnet_37 %} is hosted by Amazon Web Services, Anthropic PBC, and Google Cloud Platform. {% data variables.copilot.copilot_claude_sonnet_35 %} is hosted exclusively by Amazon Web Services. {% data variables.product.github %} has provider agreements in place to ensure data is not used for training. Additional details for each provider are included below:
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* Amazon Bedrock: Amazon makes the [following data commitments](https://docs.aws.amazon.com/bedrock/latest/userguide/data-protection.html): _Amazon Bedrock doesn't store or log your prompts and completions. Amazon Bedrock doesn't use your prompts and completions to train any AWS models and doesn't distribute them to third parties_.
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* Anthropic PBC: {% data variables.product.github %} maintains a [zero data retention agreement](https://privacy.anthropic.com/en/articles/8956058-i-have-a-zero-retention-agreement-with-anthropic-what-products-does-it-apply-to) with Anthropic.
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* Google Cloud: [Google commits to not training on {% data variables.product.github %} data as part of their service terms](https://cloud.google.com/vertex-ai/generative-ai/docs/data-governance). {% data variables.product.github %} is additionally not subject to prompt logging for abuse monitoring.
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To provide better service quality and reduce latency, {% data variables.product.github %} uses [prompt caching](https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching). You can read more about prompt caching on [Anthropic PBC](https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching), [Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-caching.html), and [Google Cloud](https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/claude-prompt-caching).
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When using {% data variables.copilot.copilot_claude %}, input prompts and output completions continue to run through {% data variables.product.prodname_copilot %}'s content filters for public code matching, when applied, along with those for harmful or offensive content.
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## Google models
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Used for:
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* {% data variables.copilot.copilot_gemini_25_pro %}
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* {% data variables.copilot.copilot_gemini_flash %}
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{% data variables.product.prodname_copilot %} uses {% data variables.copilot.copilot_gemini_flash %} and {% data variables.copilot.copilot_gemini_25_pro %} hosted on Google Cloud Platform (GCP). When using {% data variables.copilot.copilot_gemini %} models, prompts and metadata are sent to GCP, which makes the [following data commitment](https://cloud.google.com/vertex-ai/generative-ai/docs/data-governance): _{% data variables.copilot.copilot_gemini %} doesn't use your prompts, or its responses, as data to train its models._
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When using {% data variables.copilot.copilot_gemini %} models, input prompts and output completions continue to run through {% data variables.product.prodname_copilot %}'s content filters for public code matching, when applied, along with those for harmful or offensive content.

content/copilot/reference/ai-models/index.md

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content/copilot/reference/ai-models/supported-ai-models-in-copilot.md

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* To configure which models are available to you, see [AUTOTITLE](/copilot/using-github-copilot/ai-models/configuring-access-to-ai-models-in-copilot).
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* To learn how to change your current model, see [AUTOTITLE](/copilot/using-github-copilot/ai-models/changing-the-ai-model-for-copilot-chat) or [AUTOTITLE](/copilot/using-github-copilot/ai-models/changing-the-ai-model-for-copilot-code-completion).
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* To learn more about Responsible Use and Responsible AI, see [{% data variables.product.prodname_copilot_short %} Trust Center](https://copilot.github.trust.page/) and [AUTOTITLE](/copilot/responsible-use-of-github-copilot-features).
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* To learn how {% data variables.copilot.copilot_chat_short %} serves different AI models, see [AUTOTITLE](/copilot/reference/ai-models/how-copilot-serves-ai-models).

content/repositories/configuring-branches-and-merges-in-your-repository/managing-protected-branches/about-protected-branches.md

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## About branch protection rules
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> [!TIP] If you use branch protection rules that require specific status checks, make sure that job names are unique across all workflows. Using the same job name in multiple workflows can cause ambiguous status check results and block pull requests from being merged. See [AUTOTITLE](/pull-requests/collaborating-with-pull-requests/collaborating-on-repositories-with-code-quality-features/about-status-checks).
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You can enforce certain workflows or requirements before a collaborator can push changes to a branch in your repository, including merging a pull request into the branch, by creating a branch protection rule. Actors may only be added to bypass lists when the repository belongs to an organization.
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By default, each branch protection rule disables force pushes to the matching branches and prevents the matching branches from being deleted. You can optionally disable these restrictions and enable additional branch protection settings.

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