thehardwarestore.ai

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.

Solar Wanderer is a browser-based 1:1 real-time solar system explorer powered by NASA JPL ephemerides. Built with Three.js 0.165 and Vite 5, it renders the entire solar system at true scale (0.5m to 1e15 km) using a floating-origin world engine, logarithmic depth buffer, and Keplerian orbital mechanics. Users can seamlessly fly through space, walk on planetary surfaces (including real DEM terrain for Earth, Moon, Mars), dive into Earth's oceans, or orbit from a Google Earth-style camera. The application includes a bilingual (Chinese/English) interface with 7-language i18n, search, guided tours, educational facts with NASA sources, mobile touch controls, and shareable URLs. All ephemeris data—planets, 21 moons, 28 TNOs, 4 comets, and ~5400 small bodies—is generated offline via scripts that fetch from NASA JPL and fitted to Horizons state vectors. The architecture is a client-only SPA with modular ES modules; no backend, no registration, no cookies. The codebase demonstrates high craftsmanship in its floating-origin precision, pure-function ephemeris, procedural terrain generation, and real-time atmosphere scattering, though it carries technical debt from a monolithic main.js and incomplete i18n for half its languages.

Yave is a C++20 Vulkan-based real-time graphics engine paired with a custom ImGui-driven editor and a self-contained core utility library named `y`. The repository is structured as three layers: `y` provides reusable containers, math, concurrency, IO, serialization, and a test framework; `yave` implements the engine itself (Vulkan device/window management, frame graph, render passes, ECS, asset pipeline, physics, animation, and scripting); and `editor` is a full 3D scene editor application with workspaces, widgets, gizmos, importers, thumbnails, and undo/redo. The renderer supports deferred PBR, cascaded shadow maps, TAA, bloom, SSAO/RTAO, RTGI, atmosphere scattering, and tone mapping, and it runs through a declarative frame graph with automatic resource pooling and barrier insertion. The editor is not a separate toy: it provides asset browsing, glTF/image import, material editing, scene outliner, inspector, file system views, performance metrics, GPU profiling, and RenderDoc integration. The engine uses a modern ECS with component groups, async asset pointers, and a serialization framework that supports schema evolution. The `y` library is particularly notable for its clean, high-performance primitives: SSO strings, flat hash maps with SIMD probing, sparse component sets, dependency-aware job system, and a forward/backward-compatible binary serialization layer. Externally, it depends on Vulkan, VMA, Volk, Dear ImGui, JoltPhysics, LuaJIT, tinygltf, stb, Tracy, and spirv_reflect, mostly vendored. While the project is described by its author as a learning/pet engine, the code is generally well-structured and professionally organized. However, it is a single-author codebase with many `Y_TODO` markers, some stubbed platform paths, global device singletons, and an explicit compiler-dependent serialization format. Tests exist mainly for the `y` core containers and math, not for the engine or editor. The repository is active and uses current C++/Vulkan practices, but should be treated as an evolving research-quality engine, not a stable library.

This repository is the official collection of Godot Engine demo projects, maintained by the Godot Foundation. It contains hundreds of self-contained, runnable demo projects that showcase specific engine features across 2D, 3D, audio, GUI, networking, XR, mobile, compute shaders, and editor plugins. Each demo is a standalone Godot project with its own project.godot, scenes, scripts, and assets. The repository serves as both a learning resource for developers and a testbed for engine capabilities. While not a single application, it demonstrates a wide range of game development patterns and engine APIs. Notable highlights include a generic state machine implementation, a 2.5D node system, a virtual joystick for touch input, a custom logger with UI integration, and a JSON-driven dialogue system. The codebase is actively maintained with recent commits, low technical drift, and consistent use of modern Godot 4.x APIs.

This repository contains the source code and assets for ActionRoguelike, a roguelike action game built with Unreal Engine 5. The game features procedural enemy spawning, a variety of player actions (such as dashing, magic projectiles, and parrying), and performance-optimized systems for managing actors and significance. The codebase is organized into modular subsystems, including AI, action systems, core game mechanics, player controls, and UI. The architecture follows Unreal Engine best practices, with clear separation of concerns. Notable reusable systems include a custom action system that allows developers to define and manage player abilities, and an actor pooling subsystem that optimizes performance by reusing instances of frequently spawned objects. The project also implements a save system for persisting game state and a significance system to prioritize updates for important actors. While the project is tailored to a specific roguelike game, several of its systems are designed with reusability in mind. The ActionSystem and Performance modules, in particular, could be extracted and adapted for use in other Unreal Engine projects with minimal modification. The recent commit activity indicates active maintenance, and the use of a recent Unreal Engine version suggests low technical drift. Overall, the codebase demonstrates solid engineering practices and provides a foundation for learning and building similar action-oriented games in Unreal Engine.

GrowSP is an unsupervised semantic segmentation framework for 3D point clouds that learns from growing superpoints. The system processes raw point cloud data through preparation pipelines, generates initial superpoints using voxelization and region growing, then trains a Feature Pyramid Network (Res16FPN18) to learn discriminative features. During training, superpoints are progressively merged (growing superpoints strategy) to create hierarchical representations, with pseudo-labels generated via clustering of superpoint features. The framework includes specialized dataset classes for S3DIS, ScanNet, and SemanticKITTI, evaluation scripts using Hungarian matching for unsupervised performance measurement, and utility libraries for 3D augmentations and PLY file handling. The architecture follows a modular design with clear separation between data preparation, dataset handling, model definitions, and training/evaluation logic.

Cocos Creator engine runtime is a cross-platform 2D/3D game engine framework written in TypeScript and C++. It provides a component-entity architecture with scene graph, rendering pipelines (forward/deferred/custom), physics (PhysX, Bullet, Box2D, builtin), animation (marionette state machine, pose graph, Spine, DragonBones), audio, UI, particle systems, and asset management. The engine is designed to be used with the Cocos Creator editor but can run standalone. It abstracts platform-specific APIs (graphics, input, audio, system) behind a common interface, supporting Web, iOS, Android, Windows, macOS, Linux, and various mini-game platforms. Key entry points include the Director, Scene, Node, Component, and the rendering pipeline. External dependencies include graphics APIs (Vulkan, Metal, GLES, WebGPU), physics libraries (PhysX, Bullet, Box2D), and scripting engines (V8, SpiderMonkey, JavaScriptCore).

Three-forcegraph is a reusable JavaScript library for creating 3D force-directed graph visualizations using Three.js. It implements a reactive component that takes graph data (nodes and links) and renders them in 3D space using either d3-force-3d or ngraph.forcelayout for physics simulation. The library provides extensive customization options for node/link appearance, behavior, and layout constraints including DAG modes, directional arrows, and particle effects. Built with the Kapsule pattern for state management, it follows a modular architecture separating core logic, utilities, and Three.js object management. The library handles proper resource disposal to prevent WebGL memory leaks and offers both imperative and declarative APIs for integration into web applications.

threeify is a TypeScript monorepo providing a WebGL2-based 3D rendering library with a focus on physically-based rendering (PBR), glTF support, and modular architecture. It is loosely derived from three.js but aims for a more modern, tree-shakeable design with native WebGL2 abstractions. The library includes a comprehensive math package (vectors, matrices, quaternions, colors, bounding volumes), a scene graph with cameras, lights, and materials (including clearcoat, sheen, transmission, and anisotropic extensions), a renderer with post-processing effects (tone mapping, Gaussian blur, bloom, cubemap background), a 2D layer compositor with blend modes and panorama support, and a custom GLSL-to-TypeScript transpiler for shader management. The codebase is organized into packages (core, math, scene, layer-compositor) and tools, with over 50 interactive examples demonstrating various rendering techniques. External dependencies include WebGL2 and browser APIs; the library is still in development and not yet recommended for production use.

This repository is not a software application, service, or data pipeline. It is an "awesome list": a manually curated Markdown directory of WebGPU resources. The only substantive content is readme.md, which organizes links into roughly a dozen categories: official specifications, browser support details, articles, tutorials, books, libraries, debuggers/profilers, gists, demos, videos, presentations, community channels, and bug-reporting trackers. It includes enablement instructions for Chrome, Firefox, Safari, and iOS/iPadOS, and points to both the W3C WebGPU/WGSL specifications and the MDN API reference. The repository is maintained as a community resource: it is CC0-licensed, has contribution guidelines and a code of conduct, and receives regular commits. Its value is informational rather than executable—there are no build scripts, package manifests, tests, entry points, or runtime dependencies. It is best used as a discovery reference for engineers evaluating WebGPU libraries, WGSL tooling, rendering engines, or GPU compute examples. The list also internally flags stale debugger projects, demonstrating careful curation. Because this repo contains no source code, there are no reusable software components, libraries, or data assets to extract. Its quality should be evaluated as documentation and curation, not as software engineering.