agent-infini
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Set up and validate a reproducible Python or R environment on a Wisp execution context. Use for a selected local, WSL, or direct SSH context when installing scientific packages, configuring caches, recording interpreter activation, or producing an environment smoke test. Do not
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Set up and validate a reproducible Python or R environment on a Wisp execution context. Use for a selected local, WSL, or direct SSH context when installing scientific packages, configuring caches, recording interpreter activation, or producing an environment smoke test. Do not
name: compute-env-setup description: Set up and validate a reproducible Python or R environment on a Wisp execution context. Use for a selected local, WSL, or direct SSH context when installing scientific packages, configuring caches, recording interpreter activation, or producing an environment smoke test. Do not use for scheduler clusters or managed cloud providers that Wisp cannot track yet. license: Apache-2.0
Treat the selected and probed `ExecutionContext` as authoritative. Wisp currently supports `local`, `wsl:<distro>`, and direct `ssh:<alias>` contexts; it does not expose an authenticated provider SDK inside Python.
Define before installing:
Use `references/envs_reference.md` for package-order and cache examples, but replace container-specific paths with paths valid on the selected context.
1. Require a selected `ssh:<alias>` context with a recent Probe result. Respect recorded GPU, privilege, interpreter, conda/mamba, module, and scheduler capabilities. 2. If a scheduler is detected, stop. Do not install or run long work on a shared login node; Wisp needs a scheduler-aware Run backend first. 3. Use at most a few bounded read-only `shell` commands to confirm free space, existing environments, and cache paths. 4. Write an idempotent project script such as `runs/setup-<environment>.sh`. It must use user-writable paths, fail fast, activate the environment explicitly, run all smoke checks, and write a small JSON manifest only after validation succeeds. 5. Submit the setup script through one persisted Run:
{
"context_id": "ssh:gpu-box",
"title": "Set up singlecell environment",
"command": "bash setup-singlecell.sh /home/me/envs/singlecell /home/me/wisp-env-manifests/singlecell.json",
"timeout_secs": 14400,
"input_paths": ["runs/setup-singlecell.sh"],
"output_specs": [
{
"glob": "ssh://gpu-box/home/me/wisp-env-manifests/singlecell.json",
"kind": "environment-manifest",
"residency": "remote"
}
]
}6. Replace all example paths with probed absolute paths. Call `monitor_run` when waiting is useful (again after `wait_interrupted`; do not resubmit). Use one `get_run` snapshot later or `cancel_run` when requested. 7. Record the validated activation command, versions, cache paths, GPU witness, date, and known limitations in a normal project file such as `environments/<context>/<name>.md`. This file is documentation, not a hidden resolver.
actionable version mismatch.
replace pinned torch, CUDA, JAX, NumPy, or compiled extensions.
the user authorizes it. Prefer conda packages, modules, or user paths.
model's real loader, verify non-empty content and completion markers, then run a representative inference witness.
representative workload pass.
Local and WSL Runs are currently capped at 300 seconds and do not support `input_paths`. Use `local-env-setup` for normal interactive setup. Use `run_in_context` only for a bounded command that finishes within that limit and writes outputs to host-visible project paths.
Wisp has no scheduler, Modal, RunPod, cloud Batch, container-service, or managed endpoint execution context today. Do not invent a provider id or hide those lifecycles inside an SSH submission command. Explain the boundary or use a dedicated direct SSH host until a backend implementing submit, poll, cancel, recovery, secrets, and artifact harvest exists.
The open-source, local-first AI research workbench. WISP — Workspace for Intelligent Scientific Practice Search the literature, run Python and R, query ~80 scientific databases, and keep the trail — figures, runs, decisions, and drafts — in one project.
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