This workflow compares two editing strategies in Nano Banana 2.1—prompt-only global edits versus mask-guided local edits—using a single model node (GeminiNanoBanana2V2) and a consistent pipeline. It loads your image (e.g., the provided silver_frame_profile.png), applies your natural-language edit, and renders a side-by-side before/after via ImageCompare so you can judge impact at a glance. Running once without a mask showcases broad, scene-wide transformations; running with a mask constrains changes to selected regions while preserving the rest.
Methodologically, you keep the same prompt and parameters and only toggle whether a mask is supplied to GeminiNanoBanana2V2. This isolates the effect of masking: global edits offer cohesive stylistic shifts but risk drifting subjects and text, while masked edits improve control and identity retention but may show edge artifacts if the mask is hard. SaveImageAdvanced preserves versioned outputs, and MarkdownNote helps you log prompts, mask intent, and observations across runs for repeatable, defensible comparisons.
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）。
