$ show blackboardsh/colab
Colab is a desktop IDE built with Electrobun (Bun + native Zig binaries) that combines a code editor (Monaco), integrated web browser, terminal, Git client, and local AI code completions (llama.cpp) into a single workspace. It features a plugin system that allows third-party extensions to contribute commands, custom UI slates, file decorations, context menus, and more. The application uses a main process (Bun) for system operations (file system, Git, terminal, AI) and a renderer process (SolidJS webview) for the UI, communicating via typed RPC. It includes a local database (GoldfishDB) for workspace and settings persistence, cloud sync with encryption, and analytics tracking. The architecture is modular with a focus on extensibility, though some components (store, main index) are monolithic and contain technical debt.
The LLM identified 5 files worth highlighting for reuse:
Registers and manages custom UI slates contributed by plugins. Each slate is a SolidJS component or HTML element that can be mounted/unmounted for specific file types. Demonstrates a clean pattern for extending the editor's UI without modifying core code.
Implements a lightweight JSON-based database with incremental schema migrations. Each migration is a versioned step that transforms the database object. The pattern is self-contained and could be reused in any project needing simple local persistence with schema evolution.
Provides AES-GCM encryption with PBKDF2 key derivation for syncing settings to a cloud service. The module is isolated, well-structured, and demonstrates a secure pattern for encrypting user data before transmission.
A custom PTY (pseudo-terminal) implementation in Zig that spawns a shell, handles input/output, and tracks the current working directory via macOS proc_pidinfo. Communicates with the main process via JSON over stdin/stdout. Demonstrates low-level system programming and could be extracted as a standalone PTY server.
Zig bindings for the llama.cpp C API, providing tokenization, sampling, and text generation. Includes a mock mode for testing without the actual library. The bindings are cleanly separated and could be reused in other Zig projects needing local LLM inference.