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
通过代码使用此工作流
每个 Comfy 工作流都是一个 JSON 图。下面的内容就是此工作流的完整数据，ComfyUI 运行时也是如此——你可以从该 URL 获取、放入版本控制，或在 ComfyUI 中加载并逐节点运行。
使用 Comfy SDK 从 TypeScript 或 Python 运行。相同代码可用于 Comfy Cloud 或你自托管的 ComfyUI——只需更改基础 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 需要 API 格式的工作流：在 ComfyUI 中打开此工作流，使用 文件 → 导出工作流（API）。
