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OpenAI o1-preview and o1-mini are now available to all users in GitHub Copilot Chat in VS Code, Visual Studio, and on github.com/copilot.

OpenAI o1 is a new series of AI models equipped with advanced reasoning capabilities, trained to think through complex tasks using an internal thought process. During our exploration of o1-preview with GitHub Copilot, we found the models better understood code constraints and edge cases, producing more efficient and higher quality results.

Now, you can test these models for yourself. You can power GitHub Copilot Chat with o1-preview, o1-mini, or the default GPT-4o model. By switching models during a conversation, you can quickly move from explaining APIs or generating boilerplate code to designing complex algorithms or analyzing logic bugs.

With this preview, we’re excited to bring OpenAI’s latest advancements to you, whether you’re developing software with Copilot or building the next great LLM-based product. We can’t wait to see what you build!

Join the discussion within GitHub Community.

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Code reviews and suggestions from colleagues, integrators, and AI agents like Copilot code review and Copilot autofix increase your code’s quality, but at times they can get overwhelming. You can now use Copilot Workspace directly in the context of your pull request to quickly refine, test, and incorporate code review feedback and suggestions from teammates and AI agents. Ship faster without compromising quality.

To get access, sign up for the waitlist here. This will also give you access to Copilot code review.

Copilot workspace with Copilot Review task

Using Copilot Workspace in your PRs, you can:

  • Review and incorporate code suggestions from teammates and AI agents in the context of the PR with an improved diff-viewing experience.
  • Refine and address merge-blocking feedback from directly within the PR with an improved code editing experience complete with language services and Copilot completions.
  • Build, test, and run proposed changes in the PR without affecting your personal build and test environment.

Validating an applied security autofix in Copilot Workspace

For more information see our documentation, or join the discussion within GitHub Community.

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In the latest versions of Visual Studio 2022, GitHub Copilot Completions now automatically considers semantically relevant C# files as additional context, even if those files are not open in your editor. This enhancement helps reduce hallucinations and provides more accurate, relevant suggestions.

GitHub Copilot provides autocomplete suggestions inline as you code. These suggestions are generated based on the content in your currently active file and any other open files in your editor. However, we’ve found that incorporating more relevant context leads to better suggestions.

To get started in Visual Studio 2022, ensure you’re using version 17.11 or later and have an active GitHub Copilot subscription. We hope this enhancement improves your experience with GitHub Copilot in Visual Studio. Our team is committed to improving Copilot support for C# developers in both Visual Studio and VS Code, with similar updates coming to VS Code soon.

For more details, visit the .NET team blog here.

Join our dedicated Community Discussions to discuss this update, share tips, and connect with other coders.

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A list of the GitHub Copilot Chat updates in the October VS Code release.

In the latest Visual Studio Code release, you will find a suite of enhancements to GitHub Copilot Chat, designed to streamline your coding, debugging, and testing processes. These features are now available for you to try out in the latest version of Visual Studio Code.

Start a code editing session with multi-file editing (Preview)

Setting: github.copilot.chat.edits.enabled

With multi-file editing, currently in preview, you can start an AI-powered code editing session where you can quickly iterate on code changes. Use multi-file editing to prompt GitHub Copilot to propose code changes across multiple files in your workspace. These edits are applied directly in the editor, so you can quickly review them in place, with the full context of the surrounding code.

Multi-file editing is great for iterating on large changes across multiple files. It brings the conversational flow of Copilot Chat and fast feedback from inline chat together in one experience. You can have an ongoing, multi-turn chat conversation on the side, while benefiting from inline code suggestions.

Get started with multi-file editing with these steps:

  1. Start an edit session by selecting Open Copilot Edits from the Chat menu.

Screenshot showing the Copilot menu in the Command Center, highlighting the Open Edit Session item

  1. Add relevant files to the working set to indicate to GitHub Copilot which files you want to work on.
  2. Enter a prompt to tell GitHub Copilot about the edit you want to make! For example, Add a simple navigation bar to all pages or Use vitest instead of jest.

Get more details about multi-file editing in the VS Code documentation. Try it out now and provide your feedback through our issues!

A new place to chat: Secondary Side Bar

The new default location for GitHub Copilot Chat view is the Secondary Side Bar. By using the Secondary Side Bar, you can have chat open at any time, while you still have other views available to you like the File Explorer or Source Control. This provides a more integrated AI experience in VS Code. You can quickly get to chat by using the Chat menu in the Command Center.

Chat view in its new location after having moved

With the introduction of the new Chat menu next to the Command Center, bringing up the Secondary Side Bar with chat is just a click away:

The Chat menu gives you access to the most common tasks for Copilot Chat. We provided a new setting, chat.commandCenter.enabled, that you can use to hide this menu if you wish.

Chat Menu

Note: If you had previously installed GitHub Copilot, a view will show up at the location you had Copilot Chat before that enables you to restore the Chat view to the old location.

Chat view in its old location after having moved

Code review (Preview)

With Copilot-powered code review in Visual Studio Code, you can now get fast, AI-powered feedback on your code as you write it, or request a review of all your changes before you push. Code review in Visual Studio Code is currently in preview. Try it out and provide feedback through our issues.

There are two ways to use code review in VS Code:

  • Review selection: For a quick review pass, select code in the editor and either select Copilot > Review and Comment from the editor context menu, or use the GitHub Copilot: Review and Comment command from the Command Palette. (This feature is in preview.)
  • Review changes: For a deeper review of all uncommitted changes, select the Copilot Code Review button in the Source Control view, which you can also do in your pull request on GitHub. (Join the waitlist, open to all Copilot subscribers)

Request review of uncommitted changes

Copilot’s feedback shows up as comments in the editor, attached to lines of your code. Where possible, the comments include actionable code suggestions, which you can apply.

Screenshot showing a comment reviewing a code selection

Head to the code review documentation to learn more.

GitHub Copilot’s quick review on code selection can provide feedback that matches the specific practices of your team or project, provided you give it the right context. When reviewing selections with custom review instructions, you can define those specific requirements via the github.copilot.chat.reviewSelection.instructions setting. Similar to code-generation and test-generation instructions, you can either define the instructions directly in the setting, or you can store them in a separate file and reference it in the setting.

The following code snippet shows an example of review instructions:

"github.copilot.chat.reviewSelection.instructions": [
{
"text": "Logging should be done with the Log4j ."
},
{
"text": "Always use the Polly library for fault-handling."
},
{
"file": "code-style.md" // import instructions from file `code-style.md`
}
],

Here is an example of the contents of the code-style.md file:

Private fields should start with an underscore.

A file can only contain one class declaration.

Sort by relevance in semantic search (Experimental)

Setting: github.copilot.chat.search.semanticTextResults

Last milestone, we introduced the ability to perform a semantic search using GitHub Copilot to get search results that are semantically relevant to your query. We have now improved the search results by sorting them by their relevance. Keyword matches from more relevant snippets are deemed more relevant overall.

File-based custom instructions enabled by default (Preview)

Setting: github.copilot.chat.codeGeneration.useInstructionFiles

The newly introduced .github/copilot-instructions.md file lets you document code-specific conventions for GitHub Copilot in your workspace or repository. With this release, the setting is enabled by default in VS Code, so chat conversations automatically include this file if it is present in the workspace. You can verify which instructions are added to a chat request in the Used references list. Learn more about customizing Copilot with instructions.

Intent detection in Copilot Chat

Setting: chat.experimental.detectParticipant.enabled

GitHub Copilot has several built-in chat participants, such as @workspace, which also contribute commands to the Chat view. Previously, you had to explicitly specify the chat participant and command in a chat prompt. To make it easier to use chat participants with natural language, we’ve enabled Copilot Chat to automatically route your question to a suitable participant or chat command.

Screenshot of Chat view that shows how the '@workspace' participant is automatically detected.

If the automatically selected participant is not appropriate for your question, you can select the rerun without link at the top of the chat response to resend your question to GitHub Copilot.

Control current editor context

Copilot Chat has always automatically included your current selection or the currently visible code as context with your chat request. Large Language Models (LLMs) are generally good at understanding whether a piece of context is relevant. But sometimes, when you ask a question that is not about your current editor, including this context might affect how the model interprets your question.

We now show a special attachment control in the chat input that gives a hint about the editor context. It also enables you to toggle whether or not to include the editor context.

The current editor context control in the chat input, which shows that the context is not included.

There are no changes to the behavior of the editor context. When the active editor has a selection, then just the selection is included. Otherwise, just the code that is scrolled into view is included. You can still attach other files or the full file by using the paperclip button or by typing # in the chat prompt.

A common use case of Copilot Chat is asking questions about the code in your workspace, such as using /tests to generate new unit tests for the selected code or asking @workspace to find some specific class or function in your project. This milestone, we added enhanced links for any workspace symbols that GitHub Copilot mentions in chat responses. These symbol links can help you better understand Copilot responses and learn more about the symbols used in them.

Symbol links are rendered as little pills in the response, just like the file links we added last milestone. To learn more about a symbol, select the symbol link to jump to that symbol’s definition:

You can also hover over the symbol link to see which file the symbol is defined in:

Hovering over a symbol link to see the file it's defined in

To start exploring a symbol in more detail, right-click on the symbol link to bring up a context menu with options, such as Go to Implementations or Go to References:

Using the context menu on a symbol link to learn more about a symbol

Basic symbol links should work for any language that supports Go to Definition. More advanced IntelliSense options, such as Go to Implementations, also require support for that language. Make sure to install language extensions to get the best symbol support for any programming languages used in GitHub Copilot responses.

Workspace indexing

@workspace lets you ask questions about code in your current project. This is implemented using either GitHub’s code search or a smart local index that VS Code constructs. This milestone, we added a few more UI elements that let you understand how this workspace index is being used.

First up, the new GitHub Copilot: Build Local Workspace index command lets you explicitly start indexing the current workspace. Normally, this indexing is automatically kicked off the first time you ask a @workspace question. With the new command, you can start indexing at any time. The command also enables indexing larger workspaces, currently up to 2000 files (not including ignored files, such as the node_modules or out directories).

While the index is being built, we now show a progress item in the status bar:

A status bar item showing the progress of indexing the current workspace

Indexing workspaces with many hundreds of files can take a little time. If you try to ask an @workspace question while indexing is being constructed, instead of waiting, GitHub Copilot will try to respond quickly by using a simpler local index that doesn’t take as long to build. We now show a warning in the response when this happens:

A warning showing on a response telling the user the Copilot user

Notice that Copilot was still able to answer the question in this case, even though it used the simpler local index. That’s often the case, although more ambiguous or complex questions might only be answerable once the more complex index has been constructed. Also keep in mind that if your workspace is backed by a GitHub repository, we can instead use GitHub’s code search to answer questions. In this case, GitHub Copilot uses code search instead of the simpler local index.

Fix using Copilot action in the Problem hover

The Problem hover now includes the action to fix the problem using GitHub Copilot. You can use this action with problems that have a fix available, and the fix is generated by Copilot.

The Problem hover showing a fix using Copilot action

Chat settings updates

As we continue to add new features to GitHub Copilot, we want to make it easier to check out what’s new and ready to try out. We’ve restructured our settings and added support for tagging preview and experimental settings.

New features may go through the following early access stages, which are described in the settings editor as follows:

Experimental: This setting controls a new feature that is actively being developed and may be unstable. It is subject to change or removal.

Preview: This setting controls a new feature that is still under refinement but is ready to use. Feedback is welcome.

You can check out all of GitHub Copilot’s preview features using @tag:preview in the Settings editor and all of the experimental features using @tag:experimental.

Discuss this and more in our dedicated community discussion.

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To reduce hallucinations, improve contextually-relevant suggestions, and provide a consistent C++ experience across Visual Studio and Visual Studio Code, related files such as headers are now automatically considered when gathering additional context for Copilot completions, even if they’re not open in the editor.

This is available to C++ users with an active GitHub Copilot subscription on Visual Studio 2022 17.12 or greater.

Discuss this update and swap tips with other developers in our dedicated Community Discussions.

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Enterprise owners can now create GitHub Apps owned by their enterprise, with access restricted to just the organizations and members in the enterprise. Previously, if you wanted to share an app across multiple organizations within your enterprise, you had to either:

  • Duplicate the app for each organization, leading to management overhead and potential inconsistencies, or
  • Make the app public, potentially exposing it to users outside your enterprise.

With this update, you can now safely share an app across your entire enterprise without exposing it to the rest of GitHub.com, and manage your critical apps in a more secure and centralized location.

This also simplifies distribution and management for Copilot Extensions. You can now build custom extensions and share them across your enterprise without making them public – allowing you to create tools specific to your company’s needs and workflows, while keeping them private. Use of a single app across your enterprise ensures consistency and makes it easier to update extensions across all of your teams.

A screenshot of the GitHub app creation page, showing a single visibility option that reads "Only avocado-corp-owned organizations"

These apps can only be installed on organizations in your enterprise, and only members of your enterprise can sign in to them. To ensure the security of your app, user accounts cannot install these apps, only sign in to them. When users or organizations leave your enterprise, they immediately lose access to enterprise-owned apps, and the apps lose access to those users and organizations.

Besides the limitations on where they can be installed and who can sign in, these are standard GitHub Apps. Organization and repository administrators can install them depending on the permissions requested, and they have access to all of the organization and repository APIs that other apps do. Like other apps, they support Copilot Extensions and can be used in Copilot Chat.

Today, only enterprise owners can create and manage these applications. In the future we’ll add support for the App Manager role that exists for organization-owned applications as well, to make it easier for administrators to delegate access to apps in a secure manner.

To learn more about this public beta, see our documentation on GitHub Apps and the enterprise.

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When using Copilot Autofix for historical alerts, you can now choose the branch to which you want to commit an autofix. You can also decide whether to then open a pull request, check out the branch locally, or open it in GitHub Desktop.

Copilot Autofix provides automatic fix suggestions for code scanning alerts in your codebase.

Example of committing Copilot Autofix to branch

This update integrates Autofix more closely within the developer workflow, so you can quickly iterate on fix suggestions and collaborate on those with your team.

For more information, see: About Copilot Autofix for CodeQL code scanning. If you have feedback for Copilot Autofix for code scanning, please join the discussion here.

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Enterprise admins can now manage and apply content exclusions at the enterprise level. This expands upon previous capabilities where only org admins and repo admins could apply exclusions. Enterprise admins can now implement exclusions that apply to all users within the enterprise, providing a more comprehensive and centralized approach to managing content exclusions.

How to get started?

Enterprise admins can access Copilot Content Exclusions by navigating to the Policies tab, clicking on Copilot, and then selecting the Content Exclusions tab.

Enterprise admin Copilot Content Exclusions

Enterprise admins can learn more about excluding content with Copilot in our detailed documentation: Configuring Content Exclusions For GitHub Copilot

How will repo-level rules change with the introduction of enterprise-level rules?

There are no changes to repo-level rules with the introduction of enterprise-level settings. If a repo admin has excluded certain files from that repository, those exclusions will continue to apply to all users working on that repo within the enterprise.

How will org-level rules change with the introduction of enterprise-level rules?

Currently, org-level rules apply to all users across the enterprise. However, once enterprise-level settings are available and applied by enterprise admins, org-level rules will only affect users who are assigned Copilot seats from that specific org. This change allows for more targeted control within each organization, ensuring that org rules are scoped more precisely.

Important Details for Org Admins

If you haven’t set any rules at the org level yet, any rules you set going forward will only apply to users getting Copilot seats from your org.

If you are an existing org with rules already set up for content exclusions, here’s what you need to know:

Before November 8th:

  • If Enterprise Admins Do Not Set Rules: Org-level rules will continue to apply to all users across the enterprise, functioning as they do today.
  • If Enterprise Admins Set Rules: Once enterprise-level rules are applied, org-level rules will only apply to users with Copilot seats from your specific org.

After November 8th:

  • Org-level rules will no longer apply enterprise-wide. They will be limited to users who are assigned Copilot seats from your org, regardless of whether enterprise-level rules are applied.

Please coordinate with your enterprise admins to ensure that rules are set correctly for your organization.

Read Copilot content exclusions document to learn more about our exclusion rules.

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New skills have been added to Copilot Chat in VS Code, enabling you to search across GitHub to find commits, issues, pull requests, repositories, and topics. GitHub Copilot will either automatically infer when to use the @github agent, or you can invoke it directly by asking questions like:
@github What are all of the open PRs assigned to me?
@github What are the latest issues assigned to me?
@github When was the latest release?
@github Show me the recent merged pr's from @dancing-mona

This functionality is available to all Copilot users, with Copilot Chat v0.20.3 or later and VS Code or VS Code Insiders 1.93 or later. Learn more about asking questions in Copilot Chat on VS Code and available skills

Let us know your feedback and join the discussion within the GitHub Community!

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A list of the GitHub Copilot Chat updates in the September VS Code release.

In the latest Visual Studio Code release, you will find a suite of enhancements to GitHub Copilot Chat, designed to streamline your coding, debugging, and testing processes.

These features are now available for you to try out in the latest version of Visual Studio Code.

Pick your language model

Sign up for early access to the latest OpenAI o1 models for more precise and efficient coding assistance. Once you have access, you will have the model picker control in Copilot Chat in VS Code. You can then choose which model version to use for your chat conversations.

Screenshot of the language model picker control in Cpilot Chat.

Enhanced code quality with GPT-4o

Copilot Inline Chat now uses GPT-4o, giving you faster, more accurate, and higher-quality code and explanations when you use Chat in the editor.

Public code matching in chat

You can allow GitHub Copilot to return code that could match publicly available code on GitHub.com. When this functionality is enabled for your organization subscription or personal subscription, Copilot code completions already provided you with details about the matches that were detected. We now show you these matches for public code in Copilot Chat as well.

If this is enabled for your organization or subscription, you might see a message at the end of the response with a View matches link. If you select the link, an editor opens that shows you the details of the matching code references with more details.

Screenshot of GitHub Chat in VS Code. A red rectangle highlights the end of a response that reads "Similar code found with 2 license types - View matches."

File suggestions in chat

In chat input fields, you can now type # to get file name suggestions and quickly attach them to your prompt as context. This works in chat locations that support file attachments, such as the Chat view, Quick Chat, Inline Chat, and Notebook Chat.

Drag and drop files to add chat context

You can now attach additional files as context for a chat prompt by dragging files or editor tabs from the workbench directly into chat. For Inline Chat, hold Shift and drop a file to add it as context instead of opening it in the editor.

File attachments included in history

When you attach a file or editor selection as relevant context to your chat request, Copilot Chat will include them in the history of follow-on requests so that you can keep referring to them without having to reattach them. Previously, this context was added only for the current request and was not included in the history of follow-on requests.

Chat conversation shows that Copilot keeps track of attached files across multiple prompts.

Inline Chat and completions in Python native REPL

The native REPL editor, used by the Python extension, now supports Copilot Inline Chat and code completions directly in the input box.

Semantic search results (Preview)

Setting: github.copilot.chat.search.semanticTextResults

You can perform an exact search across your files with the Search view. It also now uses Copilot to give search results that are semantically relevant.

This functionality is still in preview and by default, the setting is not enabled. Try it out and let us know what you think!

Fix test failure (Preview)

Setting: github.copilot.chat.fixTestFailure.enabled

New fix test logic now helps you diagnose failing unit tests. This logic is triggered in some scenarios by the /fix slash command, and you can also invoke it directly with the /fixTestFailure slash command. The command is enabled in chat by default but can be disabled via the setting github.copilot.chat.fixTestFailure.enabled.

Automated test setup (Experimental)

Setting: github.copilot.chat.experimental.setupTests.enabled

You can now use an experimental /setupTests slash command to configure the testing set up for your workspace. This command can recommend a testing framework, provide steps to set up and configure it, and suggest a VS Code extension to provide testing integration in VS Code.

When you use the /tests command to generate tests for your code, Copilot Chat can recommend /setupTests and testing extensions if it looks like such an integration has not been set up yet in your workspace.

Start debugging from Chat (Experimental)

Setting: github.copilot.chat.experimental.startDebugging.enabled

You can use the /startDebugging slash command to find or create a launch configuration and start debugging your application. When you use @vscode in Copilot Chat, /startDebugging is now available by default.

A user types /startDebugging flask app port 3000 in the panel chat and is provided with the launch configuration.

Chat in Command Center (Experimental)

Setting: chat.commandCenter.enabled

You can now access chat via the Command Center, which provides access to all relevant chat commands, like starting the different chat experiences or attaching context to your prompt. Note that the Command Center itself needs to be enabled for the chat Command Center entry to show.

Chat Command Center button and the drop-down menu with relevant chat actions.

Custom test generation instructions (Experimental)

Generating tests with Copilot helps you write code that is more robust. With custom instructions you can ensure that the generated tests meet your specific coding style and requirements.

Setting: github.copilot.chat.experimental.testGeneration.instructions

In addition, you can now define instructions for test generation in settings or import them from a file. For example, if you always want to use a particular unit testing framework for your tests. Configure the test-generation instructions in the github.copilot.chat.experimental.testGeneration.instructions setting.

✍️ We want your feedback

Try out these new features and share your experiences and feedback in our issues.

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With a subscription to Copilot Individual or Copilot Business, you can now access Copilot in GitHub.com, allowing you to:

  • Discover codebases on GitHub effortlessly using powerful natural language code search using Copilot Chat.
  • Streamline development processes by receiving suggestions to resolve build failures and summarizing changes in pull requests.
  • Quickly get up to speed with the help of Copilot through summaries and key takeaways from discussions, issues, pull requests and more.
    These features are also now available in GitHub Mobile for all Copilot users.

If you’re enrolled into our recently announced o1 model limited beta, you can experiment with o1-preview and o1-mini directly in GitHub.com. To gain access to o1, please visit the waitlist.

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Finally, you can now open Copilot Chat by clicking on the floating Copilot icon in the bottom left corner of the GitHub.com interface.
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Join the discussion and let us know what you think on the  GitHub Community.

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You can now join the waitlist for early access to OpenAI o1 for use in GitHub Copilot in Visual Studio Code and GitHub Models. The waitlist is currently available to all Copilot users.

Join the waitlist for access to OpenAI o1 on GitHub.

In Visual Studio Code, you can choose to use o1-preview or o1-mini to power GitHub Copilot Chat in place of the current default model, GPT-4o.

Note: to access this feature, you’ll need to be on VS Code Insiders with the latest pre-release version of the Copilot Chat extension.

Model Picker in Visual Studio Code

In GitHub Models, you can use o1 models both in the playground and via the API. GitHub Models is currently in limited preview and you can sign up for access today.

OpenAI o1 in GitHub Models Playground

Access to these models will roll out progressively while in preview and usage will be rate-limited.

Join the discussion and share feedback with us via Discussions.

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Now you can remediate existing security issues in your public repositories faster with Copilot Autofix for CodeQL alerts. Following our general availability release for all Advanced Security customers, Copilot Autofix for CodeQL alerts is now generally available (GA) for all public repositories, for free.

Powered by GitHub Copilot, this feature provides automatic fixes for vulnerabilities found by CodeQL, both on pull requests and for historical alerts that already exist in a codebase.

Importantly, you stay in full control of your codebase: Copilot Autofix will try and suggest fixes for CodeQL alerts in pull requests, but it’s ultimately up to you to decide whether you wish to accept Copilot’s suggestion wholly, partially, or not at all. The same applies to historical alerts in a codebase: you can request an autofix from Copilot, then review it, and decide whether you want to open a PR with the fix suggestion or commit straight to the affected branch (or neither).

Example of Copilot Autofix generation on the alert page

Copilot Autofix is available for all public repositories that use code scanning CodeQL, and is enabled by default for alerts on PRs. It does not generate additional notifications. If you would like to enable Copilot Autofix on your organization’s private repositories, please have a look at this blog post where we announce Autofix for GitHub Advanced Security.

For more information, see: About Copilot Autofix for CodeQL code scanning. If you have feedback for Copilot Autofix for code scanning, please join the discussion here.

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Copilot Extensions header image

GitHub Copilot Extensions are now available in public beta 🚀 to all GitHub Copilot users and open for any developer or organization to create extensions. Alongside, we’re introducing a comprehensive Copilot Extensions Toolkit,
designed to equip developers by centralizing the information they need
to build quality extensions.

💡 What are Copilot Extensions and how to use them

Copilot Extensions integrate with your favorite dev tools directly into Copilot Chat across Visual Studio, VS Code, and GitHub.com (with support for JetBrains IDE coming soon!). Interact with databases, testing frameworks, deployment tools, and more — all without leaving your flow. For example:
Docker’s extension can help you generate the right Docker assets for your project
New Relic’s extension can help instrument your system and onboard with New Relic from within your editor

Docker extension being invoked in chat

Additionally, enterprises and organizations have the ability to build private extensions. Copilot can interact with context from your internal developer tooling, execute workflows, and adhere to your organization’s best practices.

🏁 Getting Started

To use extensions
– If you have access to Copilot through a Copilot Business or Copilot Enterprise subscription, an organization or enterprise owner needs to enable the Copilot Extensions policy for your organization or enterprise.
– Visit the GitHub Marketplace to install extensions.
– Get started with our documentation and start using extensions in Copilot Chat in GitHub.com or in the VS Code and Visual Studio editors.

To build extensions
– Access our documentation and Copilot Extensions Toolkit for tutorials and tools
– Develop your extension, and decide whether you want to keep it private to your organization or submit it to the GitHub Marketplace.
– VS Code extension developers can also add Copilot functionality to their existing VS Code extensions. Learn more here.

Share your experiences to help us improve the platform!
– Join the discussion within the GitHub Community.
– To share feedback on specific extensions, let us know in our Copilot Extensions feedback hub.
– If you’re building extensions, fill out the Extension Developer Survey for detailed feedback and feature requests.

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You can now interact with GitHub Copilot directly within your active code file with Inline Chat for GitHub Copilot in JetBrains! This new feature is designed to enhance your coding experience by integrating interactive assistance directly within your code editor.

To start using it, ensure you have the GitHub Copilot plugin version 1.5.21.6667 or above installed in your JetBrains IDEs.

How to get started?

  1. Open Your File: Begin by opening the file you want to work on.
  2. Place Your Cursor: Position your cursor on the specific line or code block you want to discuss.
  3. Use the Shortcut: To access GitHub Copilot’s inline chat feature, press Shift+Ctrl+I (Mac) or Shift+Ctrl+G (Windows). Alternatively, right-click and choose “GitHub Copilot > Copilot: Inline Chat”. You can also simply click on the Copilot icon that appears when you select a line or section of code

How Inline Chat enhances your coding experience

  • Enhanced Workflow: Keep your focus on coding while receiving suggestions directly within the editor.
  • Contextual Awareness: Provide Copilot with specific code snippets for more relevant recommendations.
  • Focused Interaction: Enjoy a streamlined experience without the need for frequent context switching.

When to use Inline Chat

  • Refactoring: Request alternative methods to achieve the same functionality with cleaner, more maintainable code.
  • Testing: Get help generating unit tests for specific sections of your code.
  • Code Improvement: Seek assistance with restructuring complex logic, renaming variables, or adding comments for better readability.
  • Vulnerability Assessment: Consult Copilot about potential vulnerabilities, but remember to use established security tools for a comprehensive evaluation.
  • Performance Optimization: Obtain suggestions for improving your code’s efficiency.

How Inline Chat differs from Side Panel Chat

While both Inline Chat and Side Panel Chat allow interaction with Copilot, Inline Chat provides a more focused experience by integrating conversations directly with your active file. The Side Panel Chat, on the other hand, offers a dedicated space for broader discussions and tracking past interactions.

Start leveraging the power of Inline Chat in JetBrains Copilot today and make your coding experience more seamless and efficient!

Join the discussion within GitHub Community.

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