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.
GET https://comfy.org/workflows/download/7cecbe192fc2.jsonFetching workflow JSON…
Run it from Python or TypeScript with the Comfy SDK. The same code targets Comfy Cloud or a ComfyUI you host yourself — only the base URL changes.
# Install (beta)
pip install comfy-sdk # Python
npm i @comfyorg/sdk # TypeScript
# Run this workflow (Python)
from comfy_sdk import Comfy
client = Comfy(api_key="comfyui-...")
wf = client.workflows.from_file("workflow_api.json")
job = client.run(wf)
for output in job.get_outputs("<output-node-id>"):
output.to_file(output.name)The SDK takes a workflow in API format: open this workflow in ComfyUI and use File → Export Workflow (API). API access requires a Comfy Cloud plan with an API key. SDK docs · Get an API key
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