Close eight open SDK tasks: the pidfile, the log, cards, names and a live curve
Each was a loose end recorded under `### SDK` in the notepad. `serve` takes its own pidfile down on SIGTERM. uvicorn restores the handler it found and re-raises the signal it stopped on, so the default handler ended the process without unwinding and the `finally` never ran — which is what a stop sends, and what left `serve.pid` behind. `serve.log` is cut back past 5 MB by the engine rather than by the screen that started it, so an adopted engine is bounded too. Gated on its own stdout being an appended regular file, which is what makes the cut safe: the kernel then puts the next write at the new end. Cards are counted from `/dev/nvidia[0-9]*`, so `FLOW_GPUS`/`--gpus` of 0 means "work it out" the way `FLOW_CPUS` always has. The engine counts, not the accountant — a remote worker builds one of those from its own inventory, and detecting there would hand it the engine host's cards. The worker counts last: what a batch job says it was granted still wins. `GET /runs/metrics/names` is the distinct over a selection that `--list` and the terminal's metric picker were approximating by reading the newest run that had measured anything, which missed a name only an older run ever wrote. `MetricSink` announces each batch it has written (`run_metric`, carrying the names). Not a per-point event: one covers up to 500 points or two seconds of them, and the rows stay the record. The terminal comparison fills in as the first readings land instead of staying blank until reopened, and the browser refetches the run and any comparison rather than the list behind them. `retry --group` pages the list route by `before` instead of stopping at 500. The terminal dashboard takes the terminal's colours (`ansi-dark`), and the web UI can re-pair from Settings without disconnecting first. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PRQ9bmTvCbqCwXo9mxZzzV
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@@ -28,6 +28,7 @@ from __future__ import annotations
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import argparse
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import asyncio
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import contextlib
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import glob
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import json
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import logging
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import os
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@@ -328,18 +329,22 @@ def _detect_ram_mb() -> int | None:
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def _detect_gpus() -> int:
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"""What this worker was *given*, never what the machine has.
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"""What this worker was *given*, else what the box appears to have.
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Nothing is probed: asking a vendor tool would make the one dependency two,
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and the engine does not probe its own GPUs either. A batch scheduler says
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so in the environment; anywhere else it is ``--gpus``.
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No vendor tool is asked — that would make the one dependency two. A batch
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scheduler says what the job was given in the environment and that always
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wins, since a node with eight cards may have granted this job one. With
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nothing said, NVIDIA's device nodes are counted, which is what the engine
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does for its own machine.
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"""
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for name in ("SLURM_GPUS_ON_NODE", "FLUKSIO_WORKER_GPUS"):
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given = os.environ.get(name, "")
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if given.isdigit():
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return int(given)
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listed = os.environ.get("SLURM_JOB_GPUS", "")
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return len([part for part in listed.split(",") if part.strip()])
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if listed.strip():
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return len([part for part in listed.split(",") if part.strip()])
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return len(glob.glob("/dev/nvidia[0-9]*"))
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def _inventory(args: argparse.Namespace) -> dict[str, Any]:
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