This ComfyUI template demonstrates a high‑fidelity image editing pipeline that preserves the original subject, pose, lighting, and composition while making targeted changes. It’s built around a simple, reliable graph: LoadImage feeds a reference image into OpenAIGPTImageNodeV2 for natural‑language edits, and SaveImageAdvanced handles consistent output naming and metadata. The included sample asset (hairstyle_makeup_base_gpt_image25.png) lets you test the flow immediately.
Technically, OpenAIGPTImageNodeV2 calls an OpenAI GPT image model in image‑edit mode, using the source pixels as strong conditioning so that only requested elements (e.g., outfit, hairstyle, facial features, or camera angle) change. You guide the edit by writing a precise prompt that also states what must stay the same (for example: “Keep the same pose, lighting, background, and composition; only change the hairstyle to a short bob”). This makes the workflow excellent for sequential frames and subject‑consistent variations. SaveImageAdvanced then writes the results with versioned filenames so iterations are easy to track.
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）。
