Train a Character LoRA (local, Flux.1-dev)

Overview

The trainer runs ostris ai-toolkit's run.py inside a headless GPU Docker container, driven through the three train_* MCP tools. You (the LLM) are the UI. Each takes an action: train_prepare_dataset owns the datasets, train_start owns the jobs, and train_doctor owns the trainer itself. You generate the dataset, launch the job, watch progress, and the finished LoRA lands in ComfyUI models/loras/ and the LoRA catalog without further steps.

• Base model: FLUX.1-dev (the best proven character consistency; needs ~24GB VRAM with quantization, RTX 4090 class).
• Phase-1 scope: character LoRAs only. Style/slider/edit and other bases come later.

The flow (tool sequence)