$ show google/model-viewer
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.
The LLM identified 4 files worth highlighting for reuse:
A small, self-contained critically damped interpolation utility used for smooth camera movement, AR placement, and UI transitions. It works on both scalars and vectors, has no internal coupling to the model-viewer package, and can be lifted directly into any animation or interaction project.
A generic reference-counting cache eviction policy with retain/release semantics and LRU-style eviction callbacks. It powers the GLTF loader cache and texture environment caching, but is isolated and reusable for any expensive resource cache where lifetime is managed by multiple consumers.
An activity-based progress aggregation utility that tracks multiple concurrent async operations and emits normalized progress updates. It is generic enough to be reused in loaders, upload queues, or any parallel workflow where aggregate progress must be reported to a UI.
Core image-comparison logic for the visual fidelity harness, computing RMS color distance and producing comparison/delta imagery for renderer regression testing. This pattern is directly reusable by any screenshot-based visual testing pipeline that needs quantitative pixel-level difference reporting.