prosolis
336cae93e0
Every `中文 · English` string moves out of ~29 components into web/src/i18n: one Pack type, a verbatim zh pack, and two ways to read it — usePack() for components, pack() for the modules that build a line when something happens rather than when something renders. Anything with a value in it is a function on the pack rather than a template at the call site, English pluralisation included: word order isn't universal, and a pack author has to be able to move the number. The roster constants (tones, rewrite styles, export formats, companions) keep only value + emoji, so a label can't drift from its key. On the server, internal/llm/lang.go replaces "Simplified Chinese" in the three prompts that actually name her language. pt-PT is spelled "European Portuguese (pt-PT, never Brazilian Portuguese)" in the prompt itself, and each Lang carries her word for "why" so the tutor prompt still recognises the question when she asks it her way. pair_lang reaches the model through the row-scoped query each handler already ran — the one that proves she owns the document — rather than a second lookup that could disagree with it. Also records Phase 18's deploy: migration 0011 rehearsed against a copy of the live VPS database, then applied for real.
53 lines
2.3 KiB
Go
53 lines
2.3 KiB
Go
package llm
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import "strings"
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// The pair language, as the prompts need to talk about it.
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//
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// Three of Petal's prompts name the writer's first language rather than merely
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// being written in English: the collocation coach asks for a gloss in it, Ask
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// Petal offers to answer in it, and the explanation translator renders into it.
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// Before Phase 19 all three said "Simplified Chinese" outright, which made the
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// zh pair the only one that could ever work.
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//
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// A Lang is not a translation of the prompt — the instructions stay in English,
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// which is what the model follows best. It is the name the model should use for
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// her language, plus the one word it should watch for when she writes in it.
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type Lang struct {
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// Code matches users.pair_lang.
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Code string
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// Name is how the prompt refers to the language, spelled the way a model
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// recognises it. Regional precision matters here: "European Portuguese" is
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// not "Portuguese" to a model that has read far more pt-BR than pt-PT.
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Name string
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// Why asks the same thing she would ask in her own language. It goes into
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// the Ask Petal prompt as an example, so a model that answers only to
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// English "why" still recognises the question when she types it her way.
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Why string
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}
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// langs holds every pair Petal can currently be a partner in. A language with a
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// frontend langpack but no entry here still works — it falls back to zh's
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// behaviour of the prompts, which is wrong but not broken — so keep the two in
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// step when a pair ships.
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var langs = map[string]Lang{
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"zh": {Code: "zh", Name: "Simplified Chinese (Mandarin)", Why: "为什么"},
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"pt-PT": {Code: "pt-PT", Name: "European Portuguese (pt-PT, never Brazilian Portuguese)", Why: "porquê"},
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"fr": {Code: "fr", Name: "French", Why: "pourquoi"},
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"es": {Code: "es", Name: "Spanish", Why: "por qué"},
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}
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// DefaultLang is the pair assumed when none is known — the column's default, and
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// the only pair that existed before Phase 19.
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var DefaultLang = langs["zh"]
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// LangFor resolves a users.pair_lang value. An empty or unrecognised code falls
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// back to the default rather than erroring: a prompt is not the place to
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// discover a configuration problem, and the writing still has to be checked.
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func LangFor(code string) Lang {
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if l, ok := langs[strings.TrimSpace(code)]; ok {
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return l
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}
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return DefaultLang
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}
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