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Harbor is an agent-environment framework from the Laude Institute: agent orchestration and grading are unified in a single Trial.run() call, and a task is fully described by four files (instruction.md, Dockerfile, test.sh, task.toml), so mixed task suites — SWE-bench, Terminal-Bench, custom tasks — train through one endpoint. Miles integrates Harbor as an agent-function integration: the agent function hands each session’s OpenAI-compatible URL to a Harbor server, which runs the per-task container, installs and runs the agent against that URL, and grades the result; the grade becomes the sample’s reward through a custom reward hook.

Try it

The maintained recipe lives in examples/swe-agent, with synchronous and fully-async launchers. Follow the recipe README for the architecture, Harbor server setup, task format, and launch scripts.