This workflow demonstrates how to drive MiniMax H3 video generation with multiple image anchors placed anywhere along the timeline. The core MiniMaxH3ReferenceToVideo node takes a long-form prompt (via PrimitiveStringMultiline) and up to four reference frames, each with its own timestamp and strength (PrimitiveInt and PrimitiveFloat), to steer motion, framing, and subject continuity at specific moments. ResolutionSelector and ComfyMathExpression set clean, multiple-of-32 dimensions, while RandomNoise provides a seed for reproducibility.

Under the hood, H3 returns video and native stereo audio as model latents. VAEDecode converts the video latents to RGB frames, and VAEDecodeAudio decodes the audio stream. CreateVideo assembles frames at the chosen FPS and muxes the decoded audio; SaveVideo then writes the final file to disk. ComfySwitchNode lets you quickly enable/disable individual reference anchors or the audio path. The workflow is grouped for clarity (User Inputs, Conditioning, Extra Image Guidance Conditioning, Video Settings, Decoding and create video), so you can focus on anchoring key frames to force narrative beats, continue an existing clip, or produce tightly timed social content with synchronized audio.

Advanced nodes like UNETLoader, CLIPLoader, VAELoader, BasicScheduler, SamplerCustomAdvanced, and BasicGuider are included for compatibility and potential extension, but the default H3 path works out of the box. If you want to customize dimensions beyond the presets, remove the ResolutionSelector and drive width/height directly (PrimitiveInt), keeping both divisible by 32 for stable decoding.

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。

e99bd5fc385c.json
正在取得工作流 JSON…

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)。

Comfy Cloud API 存取需有 API 金鑰的方案。

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