Building blocks and infrastructure for developers

electron-store is a JSON-file persistence module for Electron applications, intended for user settings, application state, and small caches. It supports dot-notation access, defaults, JSON Schema validation, migrations, and atomic writes, and can be configured for the main or renderer process as documented. It is not a database because every change reads and writes the whole file. The current package requires Electron 30 or later and provides native ESM only.

MockServer lets developers replace unavailable APIs with configurable responses, proxy live traffic for inspection and modification, and inject latency, dropped connections, or errors to test failure handling. One endpoint can cover HTTP, gRPC, WebSockets, and raw TCP, with additional support for JSON-RPC, message brokers, and mocked AI chat APIs. A live dashboard and request assertions help inspect test behavior.

electron-vite-vue provides a small, extensible starting point for desktop applications built with Electron, Vue, and Vite. Clone the repository, install dependencies, and launch the development workflow, then extend it for multiple windows or native C/C++ add-ons when needed. Direct Node.js access in the renderer is not enabled merely by the adapter; turning on Node integration is an explicit choice with security implications.

Nextron combines Next.js and Electron so developers can create desktop applications using familiar React and web-development workflows. It supplies project conventions, development commands, and packaging through electron-builder, with configuration for application metadata, resources, output, and platform targets. ESM projects are supported, but packaging still follows host-platform constraints—for example, macOS binaries must be built on macOS.

OpenMemory adds persistent memory to LLM applications through Python and Node SDKs or a multi-user backend with an HTTP API, dashboard, and MCP endpoint. It models different memory sectors, temporal relationships, decay, and reinforcement rather than relying only on similarity search, and exposes traces showing why a memory was recalled. Storage can remain self-hosted in SQLite or PostgreSQL, making it useful for agents and copilots that need durable memory under their own control.

gophernotes adds a Go kernel to Jupyter Notebook and nteract, allowing live Go code to sit alongside equations, visualizations, and explanatory text in shareable documents. It evaluates code through the gomacro interpreter. On Windows, gomacro cannot use the required plugin support for third-party packages, so those notebooks should be run through the documented Docker setup.

Triangula uses an iterative evolutionary algorithm to approximate an image with triangles or other polygons. Users can work through the separate graphical application or the companion CLI, which generates an intermediate JSON result and later renders it to SVG or PNG. The number of points and optimization settings can be adjusted for different styles and detail levels. Unlike instant geometric filters, the algorithm improves over repeated iterations and may need meaningful processing time before the result reaches the desired fitness.

100ProjectsOfCode is a categorized collection of hands-on programming ideas ranging from web and networking tools to applications, AI, computer science, cryptography, and games. Pick a project, create a repository, implement and test it, then use the finished work as a portfolio piece before moving to another challenge. Many entries include suggested languages, tools, or example implementations, although that guidance is still incomplete in places.

AgentBench measures how well LLMs act autonomously across eight interactive environments, including database and operating-system tasks. The current repository carries a function-calling version integrated with AgentRL, while the older benchmark remains available as v0.1. Running the suite requires Docker, and Python 3.9 is recommended because several scientific dependencies are pinned to older versions.

Flexx is a pure-Python GUI toolkit that renders interfaces with web technology and uses PScript to generate the required browser-side JavaScript. Developers can target cross-platform desktop applications, web applications, standalone HTML documents, and Jupyter notebooks with the same toolkit. It requires Python 3.5 or newer; desktop mode also needs Firefox or NW.js, and projects should keep regular Python and PScript code clearly separated.

BeeAI Framework supplies Python and TypeScript components for agents, multi-agent handoffs, model backends, tools, and RAG, helping developers assemble applications that reason, act, and collaborate. Requirements can constrain agent behavior consistently across different models, while MCP, ACP, and custom tools extend the system. Examples work with hosted providers and can also run locally through Ollama.

VideoRAG is an open-source framework for retrieving and answering questions over long-form video, with the Vimo desktop interface for importing one or more videos and chatting about their contents. It also includes the LongerVideos benchmark and evaluation code for researchers working on long-context video understanding. Prebuilt Vimo downloads are still marked as coming soon, so current users generally need to start the Python backend and Electron frontend from source.

vite-electron-builder is a project template that separates the Electron main process, preload layer, and renderer so developers can pair it with their preferred web framework. Its initialization workflow creates and integrates the renderer, after which the project can run in development or compile distributable applications. Packaging, end-to-end testing, continuous integration, and update workflows are preconfigured, while Node.js capabilities are exposed through preload rather than used directly in the renderer.

@electron/asar is an archive format and Node.js tool for packaging Electron application files without compression while retaining random access. Its CLI can pack directories, list entries, extract a file, or unpack an archive, and the JavaScript API supports programmatic creation with optional transforms. The current command-line package requires Node.js 22.12 or newer, and the API does not provide built-in error handling.

Start an Electron desktop project with a Vite and React TypeScript setup that is ready for development, testing, and packaging. The template includes main-process and preload structure, debugger configuration, Vitest and Playwright tests, electron-builder packaging, native Node module support, and room for multiple windows. Its renderer adapter exposes compatibility helpers but does not enable Node integration by itself; direct Node access requires an explicit Electron setting and a careful security review.

awesome-local-llm is a categorized directory for researching local and self-hosted language-model stacks. It groups inference platforms and engines, user interfaces, models, benchmarks, RAG projects, agent frameworks, MCP servers, safeguards, and other supporting tools so users can compare options before building a setup. The repository is a navigation resource rather than an application, and each entry links to an external project or reference.

Inspect is an evaluation framework created by the UK AI Security Institute for testing large language models. It includes components for prompt construction, tool use, multi-turn dialogue, and model-graded evaluation, plus more than 200 pre-built evaluations. Researchers can compose these capabilities into tasks and extend the framework through Python packages that add new elicitation or scoring techniques.

Electron Release Server is a self-hosted release service for Electron and other Squirrel-based applications. It provides a management interface, download URLs organized by platform, channel, and flavor, and endpoints compatible with Squirrel auto-updates. It supports Docker, LDAP, local disk storage, and multiple database backends, while Amazon S3 storage requires minor modifications. Existing deployments should review the documented database and configuration migrations before upgrading.