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Church Translate, as it runs at the campuses

Browse Source 
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>
This commit is contained in:
christian
2026-09-23 15:41:21 -04:00
co-authored by Claude Opus 5
commit c9eef0672c
118 changed files with 36031 additions and 0 deletions
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app/selftest.js
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/*
* Proves the model half of the engine works without needing any audio hardware:
* a known WAV goes in, a transcript and translations come out. When something
* is wrong on a Sunday, this separates "the AI is broken" from "the audio
* routing is wrong" in about a minute.
*/
const out = document.getElementById('out');
const lines = [];
function say(msg, cls) {
lines.push(msg);
out.innerHTML = lines.map((l) => l.startsWith('FAIL') ? '<span class="bad">' + l + '</span>'
: l.startsWith('PASS') ? '<span class="ok">' + l + '</span>' : l).join('\n');
console.log('[selftest] ' + msg);
}
function makeWorker(label, task, model, dtype, fallback) {
return new Promise((resolve, reject) => {
const w = new Worker(new URL('./model-worker.js', import.meta.url), { type: 'module' });
w.onerror = (e) => reject(new Error(e.message || 'worker error'));
w.onmessage = (e) => {
const m = e.data;
if (m.type === 'gpu') { say(' gpu: ' + (m.features.includes('shader-f16') ? 'shader-f16 present' : 'no shader-f16')); return; }
if (m.type === 'ready') { resolve(w); return; }
if (m.type === 'loadError') {
if (fallback && /f16|fp16/i.test(m.message)) {
say(' ' + label + ': no fp16, retrying with integer weights');
w.terminate();
makeWorker(label, task, model, fallback, null).then(resolve, reject);
return;
}
reject(new Error(m.message));
}
};
w.postMessage({ type: 'load', label, task, model, dtype });
});
}
let seq = 0;
const pending = new Map();
function run(worker, input, options, transfer) {
return new Promise((resolve, reject) => {
const id = ++seq;
pending.set(id, { resolve, reject });
const prev = worker.onmessage;
worker.onmessage = (e) => {
const m = e.data;
if (m.type === 'result' || m.type === 'error') {
const p = pending.get(m.id);
if (p) { pending.delete(m.id); m.type === 'result' ? p.resolve(m.out) : p.reject(new Error(m.message)); }
return;
}
if (prev) prev(e);
};
worker.postMessage({ type: 'run', id, input, options }, transfer || []);
});
}
const ARGS = new URLSearchParams(location.search);
(async () => {
let failures = 0;
try {
const cfg = await window.engineHost.getConfig();
/* ?mt=q4f16 overrides the configured weights, and ?skipAsr=1 skips the
speech model — loading it costs ~50s and it is not what we are testing
when we are iterating on translation. */
const mtDtype = ARGS.get('mt') || cfg.mtDtype || 'fp16';
const skipAsr = ARGS.get('skipAsr') === '1';
say('translation weights under test: ' + mtDtype + (skipAsr ? ' (speech model skipped)' : ''));
say('loading audio…');
const buf = await (await fetch('./selftest.wav')).arrayBuffer();
const ctx = new OfflineAudioContext(1, 1, 16000);
const decoded = await ctx.decodeAudioData(buf);
const audio = decoded.getChannelData(0);
say(' ' + decoded.duration.toFixed(1) + 's at ' + decoded.sampleRate + ' Hz');
let text = 'Good morning, church. Turn with me to Habakkuk, chapter one. ' +
'How long, O Lord, must I call for help, and you will not listen?';
if (!skipAsr) {
say('loading speech model…');
const t0 = performance.now();
const asr = await makeWorker('speech', 'automatic-speech-recognition', cfg.asrModel,
{ encoder_model: 'fp16', decoder_model_merged: 'q4' },
{ encoder_model: 'q4', decoder_model_merged: 'q4' });
say(' ready in ' + ((performance.now() - t0) / 1000).toFixed(1) + 's');
say('transcribing…');
const t1 = performance.now();
const res = await run(asr, audio.slice(), { language: 'en', task: 'transcribe', return_timestamps: false });
const elapsed = (performance.now() - t1) / 1000;
text = (Array.isArray(res) ? res.map((r) => r.text).join(' ') : res.text).trim();
say(' "' + text + '"');
say(' ' + elapsed.toFixed(1) + 's for ' + decoded.duration.toFixed(1) + 's of audio ('
+ (decoded.duration / elapsed).toFixed(1) + '× real time)');
const lower = text.toLowerCase();
if (lower.includes('habakkuk')) say('PASS heard "Habakkuk"');
else { say('FAIL did not hear "Habakkuk" — got: ' + text); failures++; }
if (lower.includes('how long')) say('PASS heard "how long"');
else { say('FAIL did not hear "how long"'); failures++; }
if (decoded.duration / elapsed > 1) say('PASS faster than real time');
else { say('FAIL slower than real time — will fall behind a preacher'); failures++; }
}
say('loading translation model…');
const t2 = performance.now();
window.engineHost.onMtProgress(() => {});
await window.engineHost.mtEnsure();
say(' ready in ' + ((performance.now() - t2) / 1000).toFixed(1) + 's');
/* Catch the failure mode that quantized NLLB produces: fluent-looking
output made of tokens from a dozen unrelated languages. Checking the
script is cheap and catches it every time — an empty-or-identical check
does not. */
const SCRIPT = {
spa_Latn: { want: /[a-z\u00c0-\u024f]/i, banned: /[\u4e00-\u9fff\u0600-\u06ff\uac00-\ud7af\u0400-\u04ff\u0900-\u097f]/ },
hat_Latn: { want: /[a-z\u00c0-\u024f]/i, banned: /[\u4e00-\u9fff\u0600-\u06ff\uac00-\ud7af\u0400-\u04ff\u0900-\u097f]/ },
zho_Hans: { want: /[\u4e00-\u9fff]/, banned: /[\uac00-\ud7af\u0600-\u06ff]/ },
kor_Hang: { want: /[\uac00-\ud7af]/, banned: /[\u0600-\u06ff]/ },
arb_Arab: { want: /[\u0600-\u06ff]/, banned: /[\u4e00-\u9fff\uac00-\ud7af]/ }
};
function scriptOk(text, lang) {
const rule = SCRIPT[lang];
if (!rule) return true;
if (!rule.want.test(text)) return false;
if (rule.banned.test(text)) return false;
return true;
}
const targets = ['spa_Latn', 'zho_Hans', 'kor_Hang', 'hat_Latn', 'arb_Arab'];
say('translating into ' + targets.length + ' languages…');
const t3 = performance.now();
for (const tgt of targets) {
const one = performance.now();
const got = (await window.engineHost.mtTranslate({ text, src: 'eng_Latn', tgt })).trim();
const name = window.Languages.get(tgt).name;
say(' ' + name.padEnd(20) + ((performance.now() - one) / 1000).toFixed(2) + 's ' + got.slice(0, 120));
if (!got || got === text) { say('FAIL ' + name + ' came back empty or untranslated'); failures++; }
else if (!scriptOk(got, tgt)) { say('FAIL ' + name + ' is not in the right script — quantized-model gibberish'); failures++; }
else say('PASS ' + name + ' is real ' + name);
}
const total = (performance.now() - t3) / 1000;
say(' ' + total.toFixed(1) + 's for all ' + targets.length);
if (total < 5) say('PASS all languages inside 5s');
else { say('FAIL ' + total.toFixed(1) + 's is too slow for live use'); failures++; }
} catch (e) {
say('FAIL ' + (e && e.message || e));
failures++;
}
say(failures ? ('SELFTEST: ' + failures + ' FAILED') : 'SELFTEST: all passed');
})();