CADAM: Open-Source Text-to-CAD with Parametric Sliders and WebAssembly Rendering
Adam (YC W25) released CADAM, an open-source text-to-CAD web app that generates parametric 3D models from natural language or image references. It outputs OpenSCAD code with automatically extracted parameters that surface as interactive sliders for instant dimension tweaking. You can try it live at adam.new/cadam.
Key Features
- Two generation modes: Parametric mode writes/edits OpenSCAD via a
build_parametric_modeltool; mesh mode generates textured 3D meshes. - Deterministic slider updates: Adjusting a slider does a regex-based update on the SCAD source — no LLM call needed for simple parameter changes.
- Model-agnostic backend: Uses Vercel AI SDK to support Anthropic (Claude), Google (Gemini), Gemini 3.1 Pro (top performer in evals), and OpenAI/others via OpenRouter. Adaptive thinking auto-enables on newer models.
- Browser-based rendering: Compiles OpenSCAD to WebAssembly in a Web Worker, UI never blocks. Renders with Three.js via React Three Fiber.
- Library support: Includes BOSL, BOSL2, and MCAD. Built-in Geist font for text in models.
- Export formats: .STL, .SCAD, .OBJ, .GLB/GLTF, .FBX, .DXF.
Under the Hood
Built with React (TanStack Start) and Supabase for auth, database, and file storage. The repo includes benchmarks for complex assemblies — V8 engine, radial engine, turbofan jet engine — all generated from single prompts with multiple parametric controls.
Future Plans
- Add build123d and CadQuery for constraint-driven modeling beyond CSG primitives.
- Better spatial context: UI for face/edge selection and viewport image integration for LLMs.
Clone the repo from github.com/Adam-CAD/CADAM and run locally. Contributions welcome.
📖 Read the full source: HN AI Agents
👀 See Also
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