LayoutMind AI Platform

(Formerly LayoutMind X)

LayoutMind is a proprietary, AI-powered interior layout generation studio. It leverages Natural Language Processing, a deterministic collision-aware spatial engine, and WebGL to instantly transform text descriptions into fully interactive 3D rooms.

🚀 Key Features

• Cinematic Interface: A split-panel glassmorphic workspace powered by Framer Motion, GSAP, and smooth scrolling (Lenis).
• 🧠 Artificial Intelligence & Soft Computing:
  • Natural Language Processing (NLP): Utilizes spaCy and advanced heuristics to extract precise constraints (dimensions, budgets, items) and semantic styling from natural user prompts.
  • Fuzzy Inference System (Neuro-Fuzzy AI): Uses scikit-fuzzy to map ambiguous, qualitative style concepts ("cozy", "minimal") into strict numerical variables like layout density, openness gradients, and budget sensitivities.
  • Evolutionary Genetic Algorithms: Powered by DEAP, the AI engine simulates natural evolution. It rapidly mates, mutates, and evaluates hundreds of layout coordinates in real-time acting as a virtual interior designer, optimizing for a strict fitness score based on collision avoidance, clearance, and style alignment.
• Deterministic Spatial Anchor (Collision AI): Operates alongside the GA to ensure mathematically perfect bounding-box constraints, preventing any 3D models from overlapping or breaching walls.
• Real-time 3D Rendering: High-fidelity shadows and materials using React-Three-Fiber and Drei.

🛠 Tech Stack

• Frontend: React 19, Vite, TypeScript, TailwindCSS v4, Zustand, Framer Motion, GSAP, Three.js (@react-three/fiber).
• AI & Spatial Engine: Python, FastAPI, DEAP (Genetic Algorithm), scikit-fuzzy, SpaCy.
• Architecture Base: Node.js Express proxy (Legacy support).

💻 Local Development

1) Run the Engine (Python)

cd softcomputing-service
pip install -r requirements.txt
uvicorn main_fixed:app --reload --port 8000

Health check: http://127.0.0.1:8000/health

2) Run the Frontend (Vite)

cd frontend
npm install
npm run dev

Open http://localhost:5173.

Note: The frontend is configured to communicate directly with the local Python engine in development. Production deployments can connect to hosted engine URLs using the VITE_API_URL environment variable.

©️ License

Copyright © 2026 AHMED SINAAN. All Rights Reserved. Unauthorized copying, modification, or distribution is strictly prohibited.