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Web-based GUI for LizyML

Project description

LizyStudio

A web-based GUI for machine-learning workflows. Configure, train, evaluate, tune and run inference — all from your browser, no code required.

LizyStudio wraps ML backend libraries (starting with LizyML) behind an adapter layer, so the same interface works across different backends.

Features

  • Workspace — iterative loop of data setup, model config, fit, and result review in a single page
  • Jobs — lifecycle management, result browsing, and model export for every training / tuning run
  • Inference — apply trained models to new data and evaluate predictions
  • JSON-Schema-driven forms — backend config schemas are rendered automatically; no hand-written UI per backend
  • Adapter architecture — plug in new ML backends by implementing a single Python protocol

Requirements

  • Python 3.10+

Installation

pip install lizystudio

Quick start

lizystudio              # starts the server on http://localhost:8501
lizystudio --port 9000  # custom port

Open your browser and navigate to the URL shown in the terminal.

Development

# Backend
uv run lizystudio --reload          # dev server with auto-reload
uv run pytest                       # run tests
uv run ruff check .                 # lint
uv run mypy src/lizystudio/         # type check

# Frontend
cd frontend
pnpm install
pnpm dev                            # Vite dev server (port 5173, proxy -> 8501)
pnpm build                          # production build -> src/lizystudio/static/
pnpm check                          # Biome lint + format
pnpm test                           # Vitest

License

MIT

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