Void Your Concerns: A Guide to Private AI in Void Editor

If you’re a VS Code user itching to try something new (or just feel like hopping into the multiverse of editor forks), Void might be your next great adventure. As a fork of VS Code, Void brings the familiar interface you already know while sprinkling in unique features that set it apart. Pair that with local AI tools, and you’ve got yourself a productivity power couple.

Let’s dive into how to install Void, migrate your existing VS Code settings, and integrate local AI models for a cutting-edge dev experience—all without surrendering your data to the cloud.

Why Void?
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Void is shaping up to be an exciting alternative to VS Code for several reasons:

Open Source: Transparent, community-driven development with fewer (or no) baked-in telemetry.
One-Click VS Code Settings Transfer: Import your existing settings, extensions, and keybindings effortlessly.
Local AI Support: Easily integrate and run AI models directly on your hardware.
Privacy-Friendly: Perfect for developers working with sensitive code or data.

Installing Void Editor
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Step 1: Download and Install
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**Please Note: Void is in beta. So there will be bugs.**

Visit the Void Editor GitHub Releases Page: Grab the latest release for your operating system.
Install: Run the installer just like you would for VS Code.
Launch: Open Void Editor to confirm it’s installed correctly. The interface will feel familiar, minus the Microsoft branding.

Step 2: Import VS Code Settings with One Click
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If you’re switching over from VS Code, Void offers a seamless one-click import process:

Click the gear icon in the top-right corner of Void to open Void Settings.
Navigate to the General tab.
Under the One-Click Switch section, click the Transfer my Settings.
Void will automatically import your settings, keybindings, themes, and extensions from your VS Code installation.

This migration saves you the hassle of manually re-configuring everything.

**Hot tip if you use a Vim extension for Vim Motions**

To enable key-repeating, execute the following in your Terminal, log out and back in, and then restart Void Editor:

defaults write com.voideditor.code ApplePressAndHoldEnabled -bool false

Setting Up Local AI
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Void’s local AI integration is a game-changer for developers who want GPT-like assistance without relying on cloud services.

Step 1: Download Ollama
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Ollama provides an easy way to run local AI models on your system. Follow these steps to get started:

Download Ollama: On macOS, I prefer installing Ollama via Homebrew.

brew install ollama
brew services start ollama

Or visit the Ollama website to download the installer.

Step 2: Run AI Models with Ollama
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Run the Llama 3.1 Model: For chat and inline edits, execute:
```
ollama run llama3.1
```
This model requires 5GB of memory.
Run the Qwen 2.5 Coder Model: For faster autocomplete, use:
```
ollama run qwen2.5-coder:1.5b
```
This model requires 1GB of memory.

Step 3: Connect Void to Your Model
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Void automatically detects locally running models on Ollama at the endpoint http://127.0.0.1:11434. Once configured, Void will provide AI-powered code completions, suggestions, and explanations—entirely powered by your local machine.

Configure other AI providers like OpenAI, Anthropic, OpenRouter, and more in the Void Settings (click the gear icon in the top-right corner of the editor).

Using AI Features with Void
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Void introduces powerful keyboard shortcuts that unlock its private AI capabilities:

CMD + K: Opens a pop-up window for inline code edits using your selected AI model.
CMD + L: Activates the chat interface, allowing you to ask questions and receive context-aware responses with attached files.
TAB: Provides auto-completion suggestions powered by your locally configured AI models.

These shortcuts integrate seamlessly with Void’s AI configuration, enabling developers to maintain full control over their data while accessing cutting-edge productivity tools.

Performance Considerations
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Running large AI models locally can be resource-intensive. Here are some tips:

Model Size: Choose a model that fits your hardware’s RAM and GPU capabilities.
Batching: Reduce the context window size or batch queries to improve performance.
Hardware Upgrades: Adding RAM or using a GPU-compatible model (via CUDA or ROCm) can significantly enhance speed.

Final Thoughts
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Void is more than just another VS Code alternative. Its focus on privacy, customization, and local AI integration gives it a strong edge—especially for developers who need or prefer offline tooling.

Whether you’re migrating from VS Code in one click, setting up your first local model, or simply looking to reduce telemetry in your workflow, Void offers a compelling new space to explore.