# Rollout Artifacts Design

**Goal:** Add a one-off evaluation path that can record rollout video, export per-step timing breakdowns, and save executed end-effector trajectories for a selected checkpoint while preserving default eval behavior when artifact capture is disabled.

**Approach:** Extend `roboimi/demos/vla_scripts/eval_vla.py` with optional evaluation-time artifact capture that stays backward compatible when disabled. Reuse existing environment observation and camera streams, record one camera stream to MP4, collect per-step timing around observation read / preprocessing / model inference / env step / total loop, and save per-step raw predicted EE actions plus executed EE poses after stepping.

**Artifact contract:**
- `video.mp4`: optional MP4 encoded from a selected camera stream (`r_vis`, `top`, `front`, etc.), written only when recording is enabled.
- `trajectory.npz`: canonical trajectory export containing at minimum `step`, `reward`, `raw_action`, `executed_left_link7_pos`, `executed_left_link7_quat`, `executed_right_link7_pos`, `executed_right_link7_quat`, and optional duplicated tool-body poses if captured.
- `timing.json`: JSON-serializable per-episode timing summary with millisecond units for `obs_read_ms`, `preprocess_ms`, `inference_ms`, `env_step_ms`, `loop_total_ms`, plus aggregate mean/std/min/max and counts. Raw per-step timing arrays should also be persisted in the NPZ for later analysis.

**Checkpoint selection:** Prefer an explicitly requested checkpoint path. If the caller asks for “latest” or omits a path in the execution helper, select the newest fully written checkpoint file by mtime/name and fail clearly if none exists.

**Stop-training / execution safety:** Before rollout, stop any active training process using the target run, wait for process exit, then verify the chosen checkpoint exists and is readable. If the most recent checkpoint is missing or mid-write, fall back to the previous completed checkpoint or `vla_model_best.pt` with the decision logged.

**Backward compatibility:** With all new eval flags left at default values, `_run_eval` return shape must remain compatible with existing callers, training-time rollout validation should continue to work without passing new options, and no artifact files should be written.