by siegblink · Agent Tool · ★ 195
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Interior Designer AI A modern, AI-powered application for transforming interior spaces with cutting-edge design. Upload a photo of your room and get a redesigned space in seconds. Features Modern UI with glassmorphism effects and fluid animations AI-Powered Design transformation using Replicate API Multiple Design Styles including Modern, Vintage, Minimalist, and Professional Various Room Types such as Living Room, Dining Room, Bedroom, Bathroom, and Office Responsive Design that works on both desktop and mobile devices How to use Clone this project's repository In your Terminal app Install Bun (if not already installed) Bun is a fast JavaScript runtime and package manager. Install it using: For more installation options, visit https://bun.sh/docs/installation Install portless globally portless provides a local HTTPS tunnel so the app runs at . On first run, portless will request your password to bind port 443 and install a local CA certificate so browsers trust the HTTPS connection. Install the project dependencies Go
| Stars | 195 |
| Forks | 64 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 70.0060955149799/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-23 |
| Created | 2023-06-19 |
| Platforms | node |
| Est. Tokens | ~2587k |
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interior-designer-ai is Upload a sample room photo and get a design back in seconds.. It is categorized as a Agent Tool with 195 GitHub stars.
interior-designer-ai is primarily written in TypeScript. It covers topics such as ai-tools, next, replicate.
You can find installation instructions and usage details in the interior-designer-ai GitHub repository at github.com/siegblink/interior-designer-ai. The project has 195 stars and 64 forks, indicating an active community.
interior-designer-ai is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to interior-designer-ai on Agent Skills Hub include mcp-gearbox, octocode-mcp, UnrealClaude. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.