Set up a compute environment

Set up a compute environment

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.

Plan the environment

Define before installing:

• Python or R version;
• ordered conda/pip/R package phases with important pins;
• required CUDA capability and minimum VRAM;
• cache variables and durable weight locations;
• import checks, CLI checks, and one seeded representative workload;
• the exact activation command later Runs must include.

Use references/envs_reference.md for package-order and cache examples, but replace container-specific paths with paths valid on the selected context.

Direct SSH workflow

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",