Anyesh/wardrowbe

Put your wardrobe in rows. Self-hosted AI-powered wardrobe management app.

What it solves

Wardrowbe is a self-hosted wardrobe management system that helps users organize their clothing and decide what to wear. It eliminates the manual effort of tagging clothes and the daily struggle of choosing outfits by using AI to analyze images and suggest clothing combinations based on external factors like weather and occasion.

How it works

Users upload photos of their clothing items, which are then processed by a vision-capable AI model (such as Gemma 3 or GPT-4o) to automatically extract details like color, pattern, and style. The system stores these items in a digital wardrobe and uses a text-based AI model to generate personalized outfit recommendations. These suggestions are integrated with real-time weather data via Open-Meteo and can be sent to users as daily notifications via email or ntfy.sh.

Who it’s for

It is designed for individuals who want a digital inventory of their clothes, people who struggle with outfit planning, and self-hosting enthusiasts who prefer to keep their personal data on their own hardware.

Highlights

  • AI-Powered Tagging: Automatically extracts clothing details from photos using vision models.
  • AI Outfit Suggestions: Recommends outfits based on weather, occasion, and user preferences.
  • Self-Hosted & Private: Runs locally via Docker, ensuring data stays on the user's hardware.
  • Flexible AI Backend: Compatible with OpenAI, Ollama, LocalAI, or any OpenAI-compatible API.
  • Comprehensive Tracking: Includes wear history, ratings, wash tracking, and color distribution analytics.
  • Multi-User Support: Allows management of wardrobes for multiple household members.
  • Coded in Modern Stack: Built with Next.js, FastAPI, PostgreSQL, and Redis.

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