Not an application but a paper and its reference implementation, trained purely on synthetic degradations and loosely licensed enough that a whole shelf of GUI products wraps it. Three ways in, with different costs.

A text-to-image model that draws Chinese hanzi correctly instead of producing gibberish, releases its code and weights, and plugs into an existing generative workflow — while the consumer entry now lives on another platform.

The compact member of the second generation does text to image, single-reference editing and multi-reference composition with the same weights, opens fully for commercial use, and runs on a mid-range gaming card.

A self-hosted image workstation under Apache 2.0 where generation and retouching share one infinite canvas, layers can carry their own prompts, and a node graph waits behind the canvas for anyone who needs a process they can repeat.

Built entirely on SDXL with the sampling parameters tucked behind presets. A GPT-2 prompt engine runs offline to fill in the details, so one short sentence is enough to get four finished pictures.

Same tabs, same parameter column, same model folder. The rewriting went into memory tracking and model support, so a card that struggled before now finishes the same job in half the time.

Every step becomes a box on an endless canvas, wired to the next. Save the graph as a file, drag a generated image back in to recover it, and run isolated environments so one bad node pack does not break the rest.