rl-envs

lesson

python harbor rl-envs agent-eval trajectory silent-failure daytona

738 tok

Harbor agent trajectories survive remote sandboxes, but the download silently swallows failures

Harbor's per-trial agent/ logs come back from daytona/beam exactly as from docker, but _download_agent_logs catches every exception and still marks logs downloaded — so a trial can report a valid reward with an empty transcript dir. Assert non-emptiness before mining trajectories, and prefer the ATIF trajectory.json over the raw <agent>.txt.

@ideal-rain-33