OpenSCAD is a mature, script-based 3D CAD modeler. It provides a declarative language for defining solid geometry through Constructive Solid Geometry (CSG) operations, extrusions, and transformations. The application consists of a C++ core that parses the custom scripting language, builds an AST, and evaluates geometry using either the CGAL or Manifold library for boolean operations. Rendering is handled via OpenGL with both preview (OpenCSG) and final render modes. The GUI, built on Qt, includes a code editor with syntax highlighting, a 3D viewport, parameter customizer, and an integrated AI assistant for code generation. Exports to STL, OBJ, SVG, 3MF, PDF, and other formats. The codebase demonstrates strong engineering with clear module separation (core, geometry, glview, gui, io, utils), extensive regression tests, and reusable patterns such as visitors, builders, and self-contained geometry utilities.
This is a monorepo centered on `@google/model-viewer`, a production web component that renders glTF/GLB 3D models in the browser using Three.js and Lit. The core package provides a `<model-viewer>` custom element with a rich feature surface: WebXR/Scene Viewer/Quick Look AR, animation controls, camera orbit/perspective controls, environment lighting, hotspots/annotations, a mutable scene-graph API, lazy loading, and post-processing via a companion `model-viewer-effects` package. In addition to the library itself, the repo contains `space-opera`, a Redux + Lit-based interactive editor for configuring model-viewer snippets and editing glTF materials, plus a full documentation/examples site and render-fidelity tooling that performs golden-image screenshot comparisons across renderers. Although the dominant character is an application/library monorepo, it also includes research-grade visual fidelity workflows and color science work around tone mapping.
This repository is an interactive, cyberpunk-styled periodic table of elements web application. It displays all 118 elements with detailed data, supports multiple visualization modes (standard, heatmap for properties like radius, electronegativity, ionization energy, melting point, boiling point, density), category filtering, real-time search, and a 3D atomic model viewer. The application is fully bilingual (Chinese/English) and responsive across devices. The architecture is a single-page application built with TypeScript and Vite. The codebase is modular, with clear separation into modules for table rendering, heatmap, 3D atom, modal, media loading, search, and legend. State is managed centrally, and internationalization is handled via typed translation dictionaries. The project includes unit tests using Vitest and a CI/CD pipeline for GitHub Pages deployment. Key technical highlights include a pure-function electron configuration algorithm (Aufbau principle with exceptions), CSS 3D transforms for the atom model, and a lightweight i18n system. The code is type-safe with strict TypeScript and follows modern frontend best practices.
Clarvis AI is a Docker-based orchestration system that combines OpenClaw, claw3d, and curaengine-slicer-api to create an AI-powered 3D printing assistant accessible via Telegram, Discord, or WhatsApp. Users can interact through natural language to generate 3D models from text/images, search existing models, slice them to G-code, and send them to compatible printers. The system features a two-service architecture: a gateway handling AI and chat integrations, and a slicer service providing REST API access to CuraEngine for model slicing. The setup process is automated via a comprehensive bash script that builds Docker images, runs interactive configuration wizards for both OpenClaw and claw3d components, and starts all services. A notable reusable component is the Node.js-based configuration script for claw3d, which uses @clack/prompts to create a polished terminal user interface for gathering settings and outputting JSON configuration. This script exemplifies strong CLI tool design with clear separation of concerns, error handling, and adaptability for reuse in other projects.
This repository is a static asset dump of extracted Pokémon GO game files, not a software application. It contains 3D models (FBX/OBJ), textures (PNG), app icons, and text strings organized under top-level directories such as '3D Assets', 'Images', and 'Texts'. The assets are grouped by category (Pokémon, costumes, addressable assets) and by in-game event (e.g., Halloween 2021, New Years 2020/2021), with consistent naming conventions based on Pokémon IDs (pm####) and costume descriptors. There is no source code, ETL pipeline, or analytical schema; the repository serves as a raw data source for fan projects, 3D artists, and game data miners.