This ComfyUI workflow applies TheBurgstall’s Googlyeyes LoRA for LTX-Video 2.3 to any input clip, turning ordinary footage into a playful googly‑eyes edit. It ingests your video with VHS_LoadVideo, trims the timeline using skip_first_frames and frame_count, and then routes the frames through the LTX 2.3 inference group (node id: 2e37ecc9-770a-4ac2-972c-e953901f49d3), where the Googlyeyes LoRA is loaded over the LTX‑Video 2.3 base model. Finally, VHS_VideoCombine reassembles the processed frames back into a video at the original frame rate.
Technically, the pipeline is video‑to‑video: frames decoded by VHS_LoadVideo are processed in sequence by the LTX 2.3 node that applies the LoRA to emphasize and transform eye regions while preserving overall scene structure. Because it runs through a video‑aware model pipeline, the effect tends to remain consistent across adjacent frames. The simple set of controls—especially skip_first_frames and frame_count—makes it practical to target only the part of the timeline you want, saving VRAM and time on longer clips.
API
Use this workflow from code
Every Comfy workflow is a JSON graph. The payload below is this workflow, exactly as ComfyUI runs it — fetch it from the URL, keep it in version control, or load it in ComfyUI and run it node by node.
Run it from TypeScript or Python with the Comfy SDK. The same code targets Comfy Cloud or a ComfyUI you host yourself — only the base URL changes.
// 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");The SDK takes a workflow in API format: open this workflow in ComfyUI and use File → Export Workflow (API).
Comfy Cloud API access requires a plan with an API key.
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