christianandClaude Opus 5
c9eef0672c
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>
54 lines
2.1 KiB
JavaScript
54 lines
2.1 KiB
JavaScript
/* Measure the hallucination and what actually stops it. Runs the same model,
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dtype and cache the app uses, in a plain node process like mt-service.js. */
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import { pipeline, env } from '@huggingface/transformers';
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import os from 'os';
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import path from 'path';
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env.allowLocalModels = false;
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env.cacheDir = path.join(os.homedir(), 'Library/Application Support/Church Translate Models');
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const t0 = Date.now();
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const pipe = await pipeline('translation', 'Xenova/nllb-200-distilled-600M', { dtype: 'fp32' });
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console.log('loaded in ' + ((Date.now() - t0) / 1000).toFixed(1) + 's\n');
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/* The exact lines from the operator's screenshot, plus stress cases. */
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const CASES = [
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'Donald Trump.',
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'Hello, hello.',
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'His name was John.',
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'Open up to the book, Matthew.',
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'Today we are going to talk about Peter in the Bible.',
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'Turn with me to John chapter 3.',
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'Amen.',
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'Jesus wept.',
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'Paul wrote to the church at Corinth.',
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'How many countries in the world?',
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'And God said, let there be light, and there was light.'
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];
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const CONFIGS = [
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{ name: 'current (no params)', opts: {} },
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{ name: 'cap 2x+8', opts: null, cap: (n) => Math.ceil(n * 2) + 8 },
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{ name: 'cap 2x+8 +nrng3', opts: { no_repeat_ngram_size: 3 }, cap: (n) => Math.ceil(n * 2) + 8 },
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{ name: 'beams2 cap2x+8', opts: { num_beams: 2, no_repeat_ngram_size: 3 }, cap: (n) => Math.ceil(n * 2) + 8 }
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];
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const tok = pipe.tokenizer;
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for (const cfg of CONFIGS) {
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console.log('=== ' + cfg.name + ' ===');
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let total = 0;
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for (const text of CASES) {
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const nIn = tok(text).input_ids.dims.at(-1);
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const opts = Object.assign({ src_lang: 'eng_Latn', tgt_lang: 'spa_Latn' }, cfg.opts || {});
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if (cfg.cap) opts.max_new_tokens = cfg.cap(nIn);
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const s = Date.now();
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const out = await pipe(text, opts);
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const ms = Date.now() - s;
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total += ms;
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const got = (Array.isArray(out) ? out[0] : out).translation_text.trim();
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const flag = (!/[?？]/.test(text) && /[?？]/.test(got)) ? ' <-- INVENTED A QUESTION' : '';
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console.log(' ' + String(ms).padStart(5) + 'ms in' + String(nIn).padStart(3) + ' ' + got + flag);
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}
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console.log(' total ' + total + 'ms\n');
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}
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