HomePlan

An open-source, self-hostable alternative to Maket.ai — describe a home in plain language and get a real, computed floor plan with room-by-room dimensions.

3-bedroom, 2-bath, ~1400 sqft, open-plan kitchen/living

→ a footprint, a room program (entry / great room / bedrooms / bathrooms / hallway), real rectangle coordinates for every room, walls, and doors — rendered as SVG. See examples/*.svg for real generated output (not mockups).

Why

Maket.ai does the same basic job (text → floor plan) but is closed-source, credit-metered (reviewers report burning a month's credits on one plan), and has well-documented spatial reasoning problems (a front door opening into the primary bedroom, in one reviewer's words). HomePlan is MIT-licensed, has no credit meter, and makes every layout decision explicit and inspectable in code — see lib/layout/ for the actual rules (e.g. ensuite bathrooms are always paired with their bedroom and never routed through the hallway; a half bath only ever lands in the public zone, never next to a bedroom).

How it works

No GAN, no diffusion model, no LLM call on the generation path — a deterministic rectangular-subdivision ("slicing floor plan") algorithm:

1. lib/parseDescription.ts — regex-based extraction of bedroom/bathroom count, target square footage, open-plan/garage/office flags from the free-text description.
2. lib/layout/program.ts — turns that into a room program: which rooms exist, their ideal/minimum area, and bedroom↔bathroom pairing (ensuite vs. shared).
3. lib/layout/generate.ts — the actual layout engine: computes a footprint from the target square footage, splits it into a public zone (entry/living/kitchen/dining/office, sliced side-by-side across the front) and a private zone (bedrooms/bathrooms, in one or two rows around a central hallway), then derives walls and doors from the real geometry of the placed rooms — never a hand-drawn template.
4. lib/layout/geometry.ts — the one reusable primitive everything is built on: constrained proportional 1D allocation (split a length across items by ideal share, respecting minimums), plus shared-edge detection between two rectangles (used for both wall and door placement).
5. lib/renderSvg.ts / components/FloorPlanSvg.tsx — render the computed rooms/walls/ doors as SVG (string version for scripts/exports, React version for the web UI).

Every number in the output is computed from the input — nothing is a canned image or a lookup table keyed by bedroom count.

Fast-follow (not in this MVP)

• LLM-assisted parsing for descriptions that don't match the regex patterns (today: deterministic regex only, by design — free, instant, nothing to hallucinate).
• Photorealistic 3D rendering (Maket's headline feature). Skipped for v1 — SVG floor plans are an honestly-scoped first version; a Three.js extrusion pass from the same room rectangles is a natural next step and doesn't require touching the layout engine.
• L-shaped / non-rectangular lots, multi-story coordination, chat-based editing of an existing plan, PDF export.
• Real building-code minimums per jurisdiction (current minimums are reasonable defaults, not code citations).

Getting started

npm install
npm run dev       # http://localhost:3000

Verify the generation engine directly (prints real room coordinates for 3 example briefs):

npm run verify

Render example SVGs to examples/:

npm run render-examples

API

POST /api/generate with { "description": "..." } returns { input, plan } — input is the parsed brief, plan is the full computed layout (footprint, rooms[], walls[], doors[], warnings[]). warnings is populated honestly when a brief is too tight for its square footage (e.g. 3 bedrooms in 450 sqft) instead of silently shrinking rooms below realistic minimums.

License

MIT.