Quick start

git clone https://github.com/tandpfun/wardrobe.git
cd wardrobe
npm install
cp .env.example .env
npm run dev

⚠️ The importer stays disabled until you add OPENAI_API_KEY to .env and place a PNG reference photo of yourself at data/model-reference.png.

Open localhost:5173.

Import with Codex

This repo includes two Codex skills: one imports clothes and generates modeled item photos; the other styles complete outfits and generates a modeled lookbook.

$import-clothes Import the clothes from ~/Pictures/outfits, create modeled photos, and add them to this wardrobe.
$generate-outfits Create modeled outfit ideas from my wardrobe.

Open the cloned repo in Codex and run either prompt. The import skill asks for a local model-reference PNG when needed, reviews every cutout and modeled photo, then writes to data/library.json and data/imported/. The outfit skill asks how many looks to create, then curates, generates, verifies, and saves the complete collection under data/.

For agents

If you are setting up Wardrobe for a user, ask how they want to import their clothes:

• Codex: Ask for a folder or camera-roll location and a model-reference PNG, then extract, model, and import the individual pieces by following the bundled import skill. Afterward, offer to create a requested number of modeled looks with the outfit-generation skill.
• Web UI: Help the user configure their own OPENAI_API_KEY and data/model-reference.png, then let them import through the app.

What it does

• Detects every garment in a photo with the OpenAI Responses API
• Extracts clean product cutouts with the OpenAI Images API
• Generates an optional modeled editorial preview
• Keeps originals, jobs, generated images, and the JSON database local in data/
• Supports drag, drop, paste, editing, review, regeneration, and approval

Configuration

Variable	Default
OPENAI_API_KEY	Required
OPENAI_VISION_MODEL	gpt-5.4-mini
OPENAI_IMAGE_MODEL	gpt-image-2
OPENAI_IMAGE_QUALITY	high
WARDROBE_MODEL_REFERENCE	data/model-reference.png
WARDROBE_DATA_DIR	data

License

MIT