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kevinveenbirkenbachandClaude Opus 5
2d886ad19b
The gateway had two engine kinds and neither reaches the catalogue. LibreTranslate covers roughly 48 languages. The chat engine is backed by the single entry in AI_LOCAL_MODELS, llama3.2:1b, which officially speaks eight, while web-svc-translate/vars/main.yml declares every language in meta/languages.yml as a chat target. The gateway therefore asserted 183-language capability for a model that invents the rest: Belarusian came back as Polish in 86 of 87 new entries, Abkhaz had no Cyrillic in any of 83, Amharic 10 of 236 in Ethiopic, and Avaric, Assamese and Bashkir returned the source verbatim. NLLB-200 is built for translation rather than generation. A third engine kind serves it beside the two libretranslate instances, since it is seq2seq and does not belong as an ollama alias. The honest ceiling is 136 of 184, not 184. flores.py maps 136 ISO codes and names the 48 the model has no code for, and the test asserts mapped plus unserved equals exactly the keys of meta/languages.yml so neither side can drift. Belarusian, Amharic, Assamese and Bashkir are covered; Abkhaz and Avaric are not, so two of the worst catalogues still have no local engine. The script half of each mapping is derived rather than typed: the test re-derives every endonym's script from unicodedata and asserts it matches the suffix of the FLORES code, ja and zh excepted because Han cannot distinguish Jpan from Hans from Hant. The subtag half cannot be derived, because where ISO 639-1 names a macrolanguage NLLB ships one variety (ar->arb_Arab, fa->pes_Arab, ms->zsm_Latn and ten more), so it is stated once in one table. Counting languages surfaced a real bug: meta/languages.yml has 184 entries, not 183. 'no' is quoted because YAML reads bare no as false. Inert until deployed. The engine entry is multiplied by zero while TRANSLATE_NLLB_ENABLED is false, so TRANSLATE_ENGINES is unchanged; the two new vars are evaluated unconditionally and every key they read exists in the new role. No variant round was added, so CI does not exercise this engine yet, and a first deploy needs an inventory regeneration for the new service key, volume and subnet. Assumed facebook/nllb-200-distilled-600M, about 3 GB resident, which fits the envelope svc-ai-s1 already occupies. 1.3B buys roughly +2 chrF++ concentrated in low-resource languages for twice the memory; the README tables the sizes so that choice is visible. Owed before this is offered beyond private use: the weights are CC BY-NC 4.0, and the role does not yet say so or credit the NLLB team. Tracked with the per-role licence index. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>