Per-model 'components' (text_encoder / low_noise / vae → cluster node): the
prompt is encoded where the text encoder is, the Wan 2.2 low-noise expert
takes over at the expert boundary with the latents handed over, the VAE
decodes where it lives and returns the finished video. The far side runs
the ordinary generation endpoint with a _handoff block, so loading,
acceleration and LoRAs happen as usual there; the scheduler is sliced to
resume mid-loop (codai/cluster/components.py). Models page block + tests.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FKm7Z56iKjHgNkHc6VhWKz