This ComfyUI tutorial workflow shows how to extend an existing video in coherent, story-aware chunks using the GeminiVideoOmniV2 node (Gemini Omni 1.1 Flash). It loads your clip with LoadVideo, extracts the final moments as context via Video Slice, and asks Gemini to continue the scene for up to 10 seconds per run. The model reads the last 10 seconds of visual context so characters, motion, camera framing, and scene layout carry forward naturally instead of restarting from scratch. SaveVideo then exports the extended result as a new clip.
Technically, the pipeline is a loop-friendly chain: LoadVideo → Video Slice (tail window) → GeminiVideoOmniV2 (prompted continuation) → SaveVideo. You can iterate this up to four times to build a 40-second story, or branch at any step by changing the prompt. The GeminiVideoOmniV2 node also supports optional image references, which you can attach mid-story to introduce new characters or props while maintaining continuity with the previous scene. The included MarkdownNote explains the required input asset path and tips for best results.
API
Usa este flujo de trabajo desde código
Cada flujo de trabajo de Comfy es un grafo JSON. El siguiente payload es este flujo de trabajo, exactamente como lo ejecuta ComfyUI: descárgalo desde la URL, guárdalo en control de versiones o cárgalo en ComfyUI y ejecútalo nodo por nodo.
Ejecuta desde TypeScript o Python con el Comfy SDK. El mismo código funciona en Comfy Cloud o en un ComfyUI propio: solo cambia la URL base.
// 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");El SDK utiliza un flujo de trabajo en formato API: abre este flujo de trabajo en ComfyUI y usa Archivo → Exportar flujo de trabajo (API).
El acceso a la API de Comfy Cloud requiere un plan con clave API.
