Developers have long struggled with concerns about data privacy, restrictive cloud dependencies, and limited control over their AI tools—especially when working on sensitive projects or within regulated industries. Now, with the excitement surrounding local models, you can harness AI directly on your device, ensuring your data stays private and your workflow remains fully customizable. The big breakthrough: Foundry Local empowers you to use local AI models seamlessly with GitHub Copilot in Visual Studio Code, giving you privacy, flexibility, and offline capabilities without compromise.

Foundry Local is a cutting-edge solution that integrates local AI models into your development environment, making it easy to manage and switch between your favorite models locally. Learn more about Foundry Local here.

How to Set Up the Foundry Local Integration for GitHub Copilot in VS Code

1. Install Visual Studio Code (VS Code) on your computer.
2. Add the GitHub Copilot extension from the VS Code Marketplace.
3. Add the AI Toolkit extension from the VS Code Marketplace.
4. Open GitHub Copilot chat, use the model picker to add a model, and select “Foundry Local via AI Toolkit” as the provider.
5. AI Toolkit will prompt you to download the models to your local machine if they have not been downloaded.

The process is designed to be quick and intuitive, allowing you to add and switch between models as needed.

Supported and Recommended Models

Foundry Local offers a variety of models optimized for code-related tasks that can be run locally on your hardware. For example:

• Qwen models are multilingual models that support code generation and natural language tasks.
• Microsoft Phi models are small, efficient models designed for reasoning, code generation, and natural language understanding.
• OpenAI GPT models – Offers advanced capabilities and broad compatibility.

Key Benefits

• Privacy-Preserving Development: The Foundry Local Integration prioritize privacy by ensuring that all queries and data remain securely on your device.
• Cost Efficiency: By leveraging local resources, developers can avoid expenses related to cloud computation and data transfer. The AI Toolkit supports both local and cloud-based models, allowing you to choose the most cost-effective solution for your needs.
• Model Flexibility and Management: Enjoy the freedom to choose from a wide range of supported models or add your own, The AI Toolkit offers a unified interface for managing, adding, updating, or switching between models, all within your development environment.
• Seamless Integration: Setup is straightforward and designed to work smoothly with both VS Code and GitHub Copilot extensions. The AI Toolkit’s compatibility with popular extensions empowers developers to experiment with different models and configurations, streamlining workflow and enhancing productivity.
• Unified and User-Friendly Experience: This solution features intuitive design and integration features that simplify setup, maintenance, and model management. Developers can focus on coding rather than technical overhead, making these tools essential companions for modern, AI-enhanced development.

Power GitHub Copilot chat with your Foundry Local models in VS Code.

Learn more about VSCode

For details on how VS Code can enhance your coding workflow, visit the release notes here.

Get Started

The Foundry Local integration for GitHub Copilot in VS Code is a significant step forward for developers seeking privacy, flexibility, and powerful AI features without the need to rely on cloud infrastructure. With straightforward setup and support for a wide range of models, this integration puts you in control of your AI development environment. Additionally, the included AI toolkit empowers users with practical utilities and resources to streamline model selection, configuration, and integration. By leveraging the AI toolkit, developers can quickly adapt to new AI features, experiment with different models, and customize their coding workflows to maximize efficiency and productivity. Get started today by installing the AI toolkit at https://aka.ms/aitoolkit.