# RX1 v2 — learned action-model stack (scripts/rx1_brain_server_v2.py).
# The robot is driven by the trained model in models/ckpt/act.pt; the world
# model / language / planner remain lightweight stubs (the learned policy does
# the control). v1 configs (rx1_models.yaml) are untouched.

world_model:
  stub: true
  latent_dim: 512
  context_frames: 8

policy:
  ckpt_path: models/ckpt/act.pt   # trained by scripts/train_act.py; absent -> v1 IK fallback
  device: cuda                    # falls back to cpu automatically if no CUDA

language:
  stub: true
  embedding_dim: 512
  enabled: false

diffusion_planner:
  stub: true
  action_dim: 44
  horizon: 30
  ddim_steps: 20
  proprio_dim: 80
  device: cpu

brain:
  # Paced to the control rate so the open-loop trajectory plays smoothly
  # (the learned policy advances ~2 trajectory steps per think; see _STRIDE).
  think_freq: 25
  context_window: 8
  default_task: "stand by"
  action_noise_stub: 0.0