Your closet already knows what you own; Wardrowbe is the part that remembers it for you and decides what goes together tomorrow morning. Photograph garments one at a time or several in a single shot, and a vision model tags each piece with its type, color, pattern, fabric, style, and formality, with a confidence score you can correct. From that catalog the app builds complete outfits out of clothes you already have, weighing your local weather, the occasion, notes you attached to individual pieces, and the aesthetic you described. A daily suggestion can arrive on a schedule through ntfy, Mattermost, or email, so the outfit is waiting before you are. Accept, reject, and rate what you wear, and the history calendar keeps every past recommendation while the feedback sharpens the next ones. Pairings work the other way around too: pick one item and get outfits built around it, each with a plain-language explanation of why the combination works. Analytics show what you actually wear, what never leaves the rail, and how your colors distribute, and the wardrobe view flags pieces that need washing. Households manage several members' wardrobes with personalized suggestions for each person. Everything runs against any OpenAI-compatible endpoint, so Ollama with a local multimodal model keeps the whole pipeline offline and free. The interface speaks eight languages and follows your browser by default. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Your closet, cataloged like an inventory system instead of a pile you rummage through every morning. Photograph each garment once and record its name, category, brand, size, colors, washing details, and acquisition date, then filter the whole wardrobe by custom categories you define yourself, with type-ahead suggestions keeping entries consistent. Uploads get automatic background removal and WebP optimization, so every item sits on a clean backdrop that makes outfits easy to judge side by side. The outfit builder combines garments into saved looks, and the scheduling calendar lays those looks across the week while showing what you have already worn, so repeats and neglected favorites become obvious. A weather forecast rides along on each calendar day, and tapping a day opens the detail you need before dressing for an important date. Wardrobes can be shared through invite links with view-only or can-edit permissions, which suits couples, families, and stylists managing client closets. The interface installs to a phone home screen as a PWA and keeps working offline, with the UI available in seven languages. Run it wide open for personal use or switch on JWT accounts for a multi-user household, all from one container with SQLite on local disk. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.