This workflow turns a composite reference sheet into a short, identity-consistent video using LTX-2.3 with the IC-LoRA Ingredients add-on. You provide a single image that inventories your characters, props, and/or locations, plus a split prompt where one part lists the "ingredients" from the sheet and the other describes the action. The core LTX-2.3 inference (custom node f9f61b10-b689-4d67-b4fa-0acc1d9b5390) uses the IC-LoRA to anchor visual identity to your sheet while animating the described motion.
Technically, the workflow loads your sheet with LoadImage, normalizes it with GetImageSize and ResizeAndPadImage, and then duplicates it across the timeline via RepeatImageBatch so every frame is conditioned on the same visual references. PrimitiveInt values in the Video Settings group (paired with ComfyMathExpression) control fps and total frames. An EmptyImage node defines the target canvas/resolution for generation, and PreviewImage lets you sanity-check inputs and a sample frame. Finally, SaveVideo encodes the generated frame batch into a video file. A MarkdownNote inside the graph includes quick usage tips and links to the official IC-LoRA documentation for prompt formatting and best practices.
API
從程式碼使用此工作流
每個 Comfy 工作流都是一個 JSON 圖。下方的 payload 就是此工作流，與 ComfyUI 執行時完全相同 — 你可以從此 URL 取得、放入版本控制，或在 ComfyUI 載入並逐節點執行。
使用 Comfy SDK 以 TypeScript 或 Python 執行。相同程式碼可用於 Comfy Cloud 或你自架的 ComfyUI — 只需更改 base URL。
// Install (beta)
npm i @comfyorg/sdk
// Run this workflow (TypeScript)
import { Comfy } from "@comfyorg/sdk";
const client = new Comfy({ apiKey: "comfyui-..." });
const wf = await client.workflows.fromFile("workflow_api.json");
const job = await client.run(wf);
await job.getOutputs("<output-node-id>")[0].toFile("output.png");SDK 需使用 API 格式的工作流：請在 ComfyUI 開啟此工作流，並使用 檔案 → 匯出工作流（API）。
