A.U.R.A
Architectural Understanding & Rendering Agent
Upload any floor plan image. Describe your use case in plain English. Walk through a fully configured 3D scene in seconds.
A.U.R.A turns a static 2D floor plan into an explorable, furnished 3D space. Gemini Vision reads the plan's rooms, walls, and doors; a three-stage agent pipeline places furniture and fixtures for the use case you describe (a family home, an office, a clinic); and the result opens in an in-browser 3D viewer you can walk through, edit, and share.
Live demo: https://aura-bay-nu.vercel.app/
Features
- Floor plan to 3D — upload a PNG/JPG/WebP plan and get a normalized 3D scene with walls, doors, and rooms.
- Use-case-aware furnishing — describe how the space will be used and the placement agent furnishes it accordingly.
- Walk and orbit modes — explore in first person or orbit the model, with a top-down minimap.
- Scene editor — select, move, add, and delete objects in the sidebar inspector, then save a shareable copy.
- Bring your own Gemini key — visitors can paste their own Gemini API key on the landing page; it is stored in the browser and sent with uploads instead of the server key.
- Resilient pipeline — Backboard → direct Gemini → rule-based fallbacks, plus SHA-256 caching of repeat uploads.
Tech Stack
| Layer | Technology |
|---|
| Frontend Framework | Next.js 14 (App Router) |
| 3D Rendering | Three.js + React Three Fiber + Drei |
| Animation | Framer Motion |
| AI Vision + Language | Gemini 2.5 Flash API |
| Agent Orchestration | Backboard (3 sequential agents) |
| Database | PostgreSQL (Vultr Managed) |
| File Storage | Vultr Object Storage (S3-compatible) |
| UI Primitives | Radix UI, Lucide React |
| Language | TypeScript throughout |
Getting Started
# 1. Install dependencies
npm install
# 2. Copy the environment template
cp .env.example .env.local
# Fill in all required variables (see Environment section below)
# 3. Run the database migrations
psql "$DATABASE_URL" < migrations/002_floorplan_ai_schema.sql
psql "$DATABASE_URL" < migrations/003_add_image_hash.sql
# 4. (Optional) Create Backboard assistants
npm run setup-backboard
# 5. Validate the setup
npm run check
# 6. Start the dev server
npm run dev
App runs on http://localhost:3000.
Environment
The root .env.example is the only active environment template. (The internal package name is still floorplan-ai.)
Required variables:
APP_BASE_URL — Public base URL (e.g. http://localhost:3000)GEMINI_API_KEY — Google Gemini API keyDATABASE_URL — Vultr PostgreSQL connection string (sslmode=require)VULTR_STORAGE_ENDPOINT — Vultr Object Storage S3-compatible endpointVULTR_STORAGE_BUCKET — Storage bucket nameVULTR_STORAGE_ACCESS_KEY — S3 access keyVULTR_STORAGE_SECRET_KEY — S3 secret keyBACKBOARD_API_KEY — Backboard platform API key
Optional variables:
BACKBOARD_AGENT1_ASSISTANT_ID — Pre-created Backboard assistant for Agent 1BACKBOARD_AGENT2_ASSISTANT_ID — Pre-created Backboard assistant for Agent 2BACKBOARD_AGENT3_ASSISTANT_ID — Pre-created Backboard assistant for Agent 3BACKBOARD_LLM_PROVIDER — LLM provider for Backboard (default: google)BACKBOARD_MODEL_NAME — Model name (default: gemini-2.5-flash)GEMINI_MODEL — Override Gemini model (default: gemini-2.5-flash)
This is the beginning of the README. Read the rest at the original. Read the full README ↗
