Build 120.
Swapping the speech model did nothing about the queue that caused the swap. The
first of those chunks went straight to a model that had just loaded, took the
full 30 s worker timeout, and tripped the absolute rule — so the ladder fell
again. MEASURED on a campus Mac: large-v3-turbo to small to base in 34 seconds,
landing on a model measurably SLOWER than the one it started from, which is the
opposite of what stepping down is for.
Two changes. A successful step-down now discards the queued chunks: they are
already past the caption-only cutoff, so they cannot be translated in time and
are worth nothing to the room, and it says how many it dropped. And no further
step-down is allowed for twenty seconds, so the new model is judged on sentences
it was actually given rather than on the wreckage of the old one.
Twenty seconds covers a cold first inference while still letting a genuinely
hopeless model fall through the ladder within a sentence or two. Checked against
the real cascade from the log, including that a hung model long after a swap is
still caught.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Build 118. Build 117 got the first half right and the second half wrong.
117 compared the time taken against the audio the chunk held, which was correct,
and then required a queue five deep as proof the machine was losing. Watching a
campus M4 Pro go red disproved that: the queue sat at 2-3 while the lag held at
15 s and the verdict was already red. A machine can be persistently late without
ever stacking work up — it finishes each sentence just slightly too slowly, for
ever, and the backlog never gets deep enough to notice.
The second test is now how far behind the speaker the sentence actually landed,
which is what the operator is complaining about in the first place.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Build 117.
A campus M4 Pro sat in the red with nobody listening and no language being
translated — so transcription alone. Measured over SSH: sentences 4.2-4.7 s
against roughly 4-5 s of audio, queue 46 deep, lag 152 s and still climbing.
The mechanism built to catch exactly this could not fire. It triggers past 8 s,
on the reasoning that 8 s means slower than people talk. That held when a chunk
could be 8 s long; chunks are capped at HARD_CUT_MAX, 5.5 s. A 4.4 s sentence is
already losing and never comes near 8 s, so the ladder never stepped down and
the backlog grew without bound.
It now compares against the audio the chunk actually held. Two details are
measured rather than chosen: the margin is 0.85, because the Mini's 4.4 s
against 4.5 s was NOMINALLY faster than real time while still losing — the work
outside that timer (segmenting, the preview model sharing the GPU, the
scheduler) loses on its own. And it requires a backlog of five, so one slow
sentence on a healthy machine touches nothing. Checked against eight cases
including the Mini's real numbers and a healthy M2 Max.
The old absolute rule stays for a model that is genuinely hung.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Build 115. Downloading and then telling the operator to quit, mount and drag
was the friction the updater was supposed to remove.
An app cannot replace itself while running, so the swap is done by a small
script that outlives the process: it waits for us to exit, moves the old bundle
aside, copies the new one in, clears the quarantine flag and relaunches.
Moved aside, not deleted. If the copy fails half way — a full disk, a truncated
download, the volume going away — the old app goes straight back and is
reopened. The failure this is written against is a campus Mac with no working
app and a service in an hour, which is far worse than not updating. Tested in a
sandbox across all three paths: a clean swap, a copy that fails mid-way (old app
restored, no leftovers), and a disk image with no app in it (aborts before
touching the installed one).
It refuses while translation is live: quitting stops every listener's captions
and no update is worth that. Stop translating first.
No sudo — /Applications is admin-writable and the bundle belongs to the
operator. If that is ever untrue the copy fails and the rollback runs.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Settings gains an Updates block: it asks the church Gitea for the newest
release, compares the tag against the running build, and if there is a newer
one shows what changed and offers to download the installer.
Deliberately not electron-updater. That wants a static feed published beside
the artifacts, and this build is ad-hoc signed with no Team ID, so a silent
in-place swap would meet Gatekeeper on a machine nobody is sitting at. And
nothing here happens on its own: a background check that announces itself three
minutes into a sermon is a hazard, so the operator presses the button, and
presses a second one to download. The file lands in Downloads and is revealed;
installing is a drag across when the room is empty.
Tags are v<version>-<build>, compared numerically field by field so 3.9.0 does
not read as newer than 3.23.2 and build 113 beats build 112.
Two things only real testing found. Gitea answers with whatever address it was
reached on, so the release API returned asset URLs on 10.3.8.90 while the forge
is configured by hostname — the same-host guard refused a perfectly good
installer. The URL is now rebuilt on the configured origin, which keeps the
property that matters (this only ever fetches from the server the operator
configured) and survives a forge that knows itself by more than one name. And a
private repository answers 404 rather than 401, so 'no releases published yet'
told the operator the opposite of the truth; without a token that case now names
the remedy instead.
The token is this machine's credential: it stays out of PORTABLE_APP, so it does
not ride along in an exported settings file.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Live sermon translation into 100+ languages, running entirely on one Mac per
campus: audio in, voice detection, Whisper on the GPU, NLLB-200 in its own
process, and a built-in web server the congregation reads from on their
phones. No audio leaves the building.
This is the source only. What used to sit beside it — 14 GB of speech and
translation models, 8 GB of voice bundles, 6 GB of natural voices, the Electron
caches, and the app data holding the operator PIN and every service transcript
— is machine state and downloaded assets, and stays in the NAS backup where it
belongs. The vendored node, cloudflared and Windows ffmpeg binaries are out too
(533 MB, re-fetched for packaging); the browser-side runtime beside them is
kept, so a checkout still serves the congregation page.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
christianandClaude Opus 5