Deployed 2026-09-30 1211 PT by pointing SCRIBERR_IMAGE at the patched tag (.env backed up as .env.bak-20260930-pre-slicer1; rollback is the unpatched scriberr:local-blackwell). PrepareEnvironment rewrote the env's parakeet_transcribe_buffered.py from the embed (sha256 matches the patched source). One live run on GPU 1 beside intern-decision peaked at 5,496 MiB. Memory records the open Parakeet mid-chunk dropout finding and the held upstream PR.
Carry patches/0001 on our Scriberr build (upstream a353078): adjacent
buffered chunks overlap by 4 s inside --chunk-len and hand over at a word
both chunks transcribed alike, instead of cutting at fixed marks with no
overlap. Pause-aware cutting is included as an opt-in (--pause-search);
it measured neutral once the stitch was right. The Go<->Python CLI and
JSON seam is unchanged.
Bench (4 recordings, 118 min, 3 cut placements each, against a no-cut
whole-file reference; metrics only, private audio stays on fv-ml1):
cuts with an error within +-3 s fall from 52% (93/179) to 22% (41/184)
against a 19% background; floor +-0.08. Positive control: upstream's
cutter +0.33 over background. A-vs-A byte-identical in-process and
across CLI processes. Peak GPU memory unchanged at 5,496 MiB (n=3).
Also found: Parakeet skips runs of >=10 words mid-chunk with any
slicer, upstream's included; not addressed here.
scripts/scriberr-rebuild clones a pinned upstream sha into a new
/opt/docker/src dir, git-apply-checks the patches, builds a distinct
tag, and checks embed, unit tests, the JSON seam (scriberr-seam-check.py)
and the memory budget on idle GPU 3. Deploy stays manual. The upstream
PR is prepared under patches/upstream-pr/ and not opened.
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