feat: translate French notices to English through api.loxi.ch

The service is neither Anthropic- nor OpenAI-compatible: it runs the
Claude Code CLI server-side and returns its output. Three consequences
are handled explicitly, each with a test.

The model is chosen by integer id, not by name, so the id is resolved
once from /api/models instead of being hard-coded into the environment —
a number in a .env file that silently points at the wrong model is a bad
trade for one HTTP call per process.

A failed CLI still answers HTTP 200. `exit_code` decides, not the status
line; trusting the status would store an empty translation and call it a
success. The test for this asserts a 200 carrying exit_code 1.

It really does start a process, so the timeout is thirty seconds rather
than the ten the spec assumed.

Answers are cleaned before use: models wrap text in quotes, prefix it
with "Translation:" and append notes often enough that stripping is
cheaper than re-prompting, and a stray quotation mark on a shop window
reads as a mistake.

The cache is keyed on the hash of the trimmed French text, so the same
notice is never paid for twice and whitespace does not cause a miss. The
write is an upsert: two concurrent saves of the same text should be a
no-op, not a crash.

Only the loxi adapter exists, behind the interface. Writing the
Anthropic and OpenAI adapters the spec asked for, with nothing calling
them, would be inventory rather than flexibility — the seam is the
interface, and it is there.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012cSY9pVhZmJUKNN7wf1Myd
This commit is contained in:
2026-09-20 20:13:28 +02:00
co-authored by Claude Opus 5
parent c430205bf2
commit f68ce1c3a5
5 changed files with 567 additions and 0 deletions
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/**
* Translation with a cache in front of it.
*
* The cache is keyed on the hash of the French text, so the same notice is
* never paid for twice — and because translation runs a CLI on the other side,
* "twice" is measured in seconds, not milliseconds.
*/
import { createHash } from 'node:crypto';
import { prisma } from '@/lib/db';
import { LoxiTranslationProvider, loxiConfigFromEnv } from './loxi';
import type { TranslationOutcome, TranslationProvider } from './provider';
export const TARGET_LANG = 'en';
export function hashSource(text: string): string {
return createHash('sha256').update(text.trim(), 'utf8').digest('hex');
}
let cachedProvider: TranslationProvider | null | undefined;
/** `null` when the service is not configured, which is not an error. */
export function defaultProvider(): TranslationProvider | null {
if (cachedProvider !== undefined) {
return cachedProvider;
}
const flavour = process.env.TRANSLATION_API_FLAVOR?.trim() || 'loxi';
const config = loxiConfigFromEnv();
// Only the loxi adapter exists, because only loxi is in use. The interface
// is the seam; writing two more adapters nobody calls would be inventory.
cachedProvider = flavour === 'loxi' && config ? new LoxiTranslationProvider(config) : null;
return cachedProvider;
}
/** Test seam. */
export function resetProvider(): void {
cachedProvider = undefined;
}
export type TranslationResult = TranslationOutcome & { cached?: boolean };
export async function translateToEnglish(
text: string,
provider: TranslationProvider | null = defaultProvider(),
): Promise<TranslationResult> {
const source = text.trim();
if (source.length === 0) {
return { ok: true, text: '', model: 'none' };
}
if (!provider) {
return { ok: false, error: 'Le service de traduction n’est pas configuré.' };
}
const sourceHash = hashSource(source);
const hit = await prisma.translationCache.findUnique({
where: {
sourceHash_targetLang_model: {
sourceHash,
targetLang: TARGET_LANG,
model: provider.model,
},
},
});
if (hit) {
return { ok: true, text: hit.translatedText, model: provider.model, cached: true };
}
const outcome = await provider.translate({ text: source });
if (!outcome.ok) {
return outcome;
}
// Two concurrent saves of the same text would race here; the upsert makes
// the second a no-op instead of a crash.
await prisma.translationCache.upsert({
where: {
sourceHash_targetLang_model: {
sourceHash,
targetLang: TARGET_LANG,
model: provider.model,
},
},
update: {},
create: {
sourceHash,
targetLang: TARGET_LANG,
sourceText: source,
translatedText: outcome.text,
model: provider.model,
},
});
return { ...outcome, cached: false };
}