SLERP Interpolate (LRW)

Most of this pack is about not doing naive interpolation. This node is the deliberate exception: SLERP Interpolate is the boring, reliable baseline - spherical linear interpolation between two latents, no metric required, no Jacobians, no drama. It exists so you have something honest to compare the fancy geodesic stuff against.

What it does

You give it two latents and a count, and it produces a stack of n_points frames interpolating along a sphere: direction slerps, magnitude eases between the endpoints. It's the same math people have used for latent walks since before Wan was a thing, and it works. The output latent_path is one stacked latent with n_points * B items, same layout as LRW_GeodesicInterpolate produces.

Inputs are exactly three: latent_from, latent_to, and n_points (default 10). Notably absent: a metric input. That's the whole tell - SLERP doesn't know or care about the curvature of latent space. It's a straight-ish shot, and sometimes that's exactly what you want: it's fast, it never crashes on an unstable metric, and for near-identical latents it's effectively indistinguishable from fancier methods.

Why the pack includes it at all

The author built this as the control arm for his experiments. When you're testing whether geodesic interpolation or parallel transport actually improves your transitions, you need a fixed reference point, and SLERP is it. Render the SLERP path and the geodesic path from the same two endpoints, and you've got a clean A/B. That's a genuinely useful pattern and I'd bet most people who try it find the differences are smaller than the marketing implies on small image models - which is a useful discovery in itself, because then you haven't wasted an hour on a Jacobian.

It also doubles as a plain latent-morph tool if you just want a smooth batch of intermediate latents and don't care about the geometry lecture. Feed the output to a LatentBatch → KSampler → VAEDecode chain, or slice a single frame out with LRW_LatentBlend - that node expects exactly this stacked layout.

The context

This is part of lajjadred's comfyui-lrw-nodes, the ComfyUI front-end for his latent-riemannian-world package. Announced on r/comfyui in June 2026 with a WAN2.2 First-Last Frame demo, the pack's real headline is the WAN branch; the image-model geodesic tools (of which this is the baseline) are the research side. Early builds had an import/registration bug that showed nodes as broken - if you installed early, git pull and a full restart, and keep only one copy in custom_nodes.

Install

Search comfyui-lrw-nodes in ComfyUI Manager, or:

cd ComfyUI/custom_nodes
git clone https://github.com/lajjadred/comfyui-lrw-nodes
cd comfyui-lrw-nodes
pip install -r requirements.txt

Restart ComfyUI. Real deps: latent-riemannian-world >= 0.3.0, torch >= 2.4, Python 3.12+. License is BSL-1.1. And one tip: because SLERP doesn't touch your metric, it's also the cheapest way to sanity-check that two latents are even worth interpolating - if the SLERP result is garbage, a geodesic isn't going to rescue it.