Report what this Forge instance offers: routes, counts, and which metadata sources are available. Call this first in a session.

Describe the currently loaded checkpoint: architecture preset, whether it behaves as a turbo/distilled model, the sampling parameters that actually worked before, the expected prompt dialect, and whether its VAE and text encoder modules exist. Call before writing a prompt for an unfamiliar model.

How the loaded checkpoint expects to be prompted, with its quality tags.

Returns the dialect (pony / illustrious / animagine / anima / sd15 / sdxl_base / natural), the quality prefix and negative baseline it needs, and where that conclusion came from. Quality tags are not decoration: an Illustrious prompt without them degrades, and a Flux prompt with them degrades too.

When the dialect comes back unknown — xl covers Pony, Illustrious and stock SDXL, which share tensors and preset — ask the operator, then call again with confirm set to their answer. It is cached by file hash and never asked again.

Search available LoRAs by name, title, tags, trigger words or description.

Only call this when the request actually calls for one (a named style, character, or concept) — most generations need no LoRA at all. kind can be "content" or "accelerator"; accelerators change the sampling regime rather than the image, so adopting one means adjusting steps and CFG together.

Full detail for one LoRA, including description, tags, past usage and a ready-to-paste prompt fragment with its trigger words.

List or load checkpoints. action: "list" | "load" | "refresh".

Loading swaps the model for the whole instance, including any human using the web UI at the same time, and takes several seconds — only do it when the operator asked for that model. When the target belongs to a different architecture, its preset, VAE and text encoder are switched with it, since Forge would otherwise load it against whatever modules are selected now. The architecture is inferred from two signals and only acted on when they agree; pass preset to state it outright.

Check the VAE and text encoders loaded for an architecture against what it actually needs, and list installed files that could fill any gap.

Defaults to the active preset. Worth calling after switching architecture or when output looks wrong for no obvious reason: Forge records the last selection made under a preset, so loading a checkpoint while another preset was active can leave the wrong modules attached. Where the reference does not state a VAE, it says so instead of guessing — a wrong VAE degrades output without raising an error.

Find, and optionally fetch, a VAE or text encoder the architecture needs.

Called with no arguments it lists what the active preset is missing and where each file comes from, downloading nothing. Downloading requires both a label naming one entry and confirm=True, and the operator has to agree first: these are multi-gigabyte files written into their models folder, often across a network share.

Links come from the Forge Classic wiki's Download Models page. Where several builds exist — bf16, fp8_scaled, gguf — they are all offered, because which to take depends on the operator's hardware, not on a default worth hiding.

Generate an image from an already-written prompt.

The prompt is sent verbatim: include any <lora:name:weight> yourself. With use_profile_defaults on, missing sampling parameters are filled from what the loaded model actually used before, so leave them unset unless you mean to override. That includes shift (Forge's distilled_cfg_scale) and the dimensions: leaving them at 0 takes the architecture's own values instead of a generic default. Returns file paths when the output folder is readable.

Pass init_image (a local file path) to run img2img instead, where denoising_strength controls how far the result may drift from it: around 0.3 keeps the composition, 0.75 reinterprets it freely. Edit-style and video models expect values close to 1.0.

Check or stop the current generation. action: "status" | "interrupt" | "skip".