Remote Compute Ssh

Remote compute over SSH

Use this skill after choosing an ssh: execution context. Wisp owns the job lifecycle locally: run_in_context creates the Run record, stages explicit inputs, starts a detached supervisor on the server, and returns after launch. The Runs panel and SQLite record remain authoritative if the conversation ends or Wisp restarts.

Dispatch workflow

1. Use shell only for a few quick, read-only discovery commands such as

ssh 'nvidia-smi -L', which python3, or module avail.

1. Put the real command in one run_in_context call. Include environment

activation in the command so the Run is reproducible.

1. After the tool returns, report the Run id, context, remote workdir, and

initial status to the user, then end the turn. Do not wait for completion in the conversation.

1. On a later user turn, call get_run once for the latest status and output

tails. Use cancel_run when the user asks to stop it.

Never monitor a Run with Start-Sleep, sleep, ssh ... ps, kill -0, a shell polling loop, nohup, background &, or hand-written PID files. Those duplicate the control plane and can strand the agent turn. A transient SSH error is stored as last_poll_error; do not resubmit, because Wisp retries the same idempotent remote handle.

{
  "context_id": "ssh:gpu-box",
  "title": "Motif enrichment across 2,000 backgrounds",
  "command": "source ~/miniforge3/etc/profile.d/conda.sh && conda activate genomics && python motif_enrichment_analysis.py",
  "timeout_secs": 14400,
  "input_paths": ["scripts/motif_enrichment_analysis.py"]
}

input_paths are project-relative local files. Wisp validates them, copies them into an isolated inputs/ directory, and flattens them to their basenames. The command starts in that directory, so the example above can use the staged script by basename. Keep inputs small enough to transfer interactively. For a large dataset already on the server, reference its absolute remote path in command; do not copy it back to the laptop just to send it out again.

The control directory is ~/.wisp-science/runs/ and the command starts in its inputs/ subdirectory. stdout and stderr are tailed into the Run record. The SSH supervisor requires setsid, GNU-compatible timeout, bash, and /proc; a missing prerequisite fails the Run instead of running without a wall-time limit. Wisp maps the supervisor timeout marker to timed_out.

Results

SSH-direct v1 does not expand remote output globs or automatically download a remote directory. Do not promise that relative output_specs will be harvested. When the command writes a result to a known durable server path, it may register that exact path as a remote Artifact reference:

{
  "output_specs": [
    {
      "glob": "ssh://gpu-box/home/me/project/results/motif_enrichment_all.tsv",
      "kind": "table",
      "residency": "remote"
    }
  ]
}

For a small result that must become local, wait until the Run is terminal, then transfer it as a separate quick operation and register the local file. Large outputs should remain remote references.

Cancellation and recovery

cancel_run({"run_id":"..."}) changes an SSH Run to cancelling. Wisp verifies the persisted token, PGID, and Linux process start time before sending TERM to the remote process group; it records cancelled only after remote confirmation. If the server is temporarily unreachable, the Run stays cancelling and retry continues after reconnection or app restart.

Active statuses are submitted, running, and cancelling. Terminal statuses are succeeded, failed, timed_out, cancelled, and lost. lost means the remote token/control directory/process identity was definitively missing, not merely that one SSH poll failed.

Current boundary

This implementation is SSH-direct and assumes a Linux-like server with sh, bash, nohup, setsid, and /proc. Do not daemonize or create a new session inside the job, because that escapes process-group cancellation.

Scheduler lifecycle is not implemented yet. Do not submit sbatch, qsub, or bsub through this direct runner: the Run would only track the short submit command, not the scheduler job. On a shared login node, ask the user for a dedicated compute host or explain that scheduler-aware submit/poll/cancel is a separate capability still needed.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: xuzhougeng
• Source: xuzhougeng/wisp-science
• License: Apache-2.0
• Homepage: https://wispscience.com/

Install and usage instructions live in the source repository linked above.