Improved auto translation support #2

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LeoVasanko merged 10 commits from llm-trans into main 2026-09-21 14:22:00 +00:00
3 changed files with 78 additions and 13 deletions
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@@ -37,6 +37,8 @@ Pagerite is a CMS. See `docs` for the full design and implementation details. Ke
- `assets/` — base CSS, Pygments styles, fonts.
- `scripts/devserver.py` — dev server with auto reload (the user mostly uses this; avoid running the server yourself, ask the user to test).
- `scripts/translator.py` — Seed-X translator service client for the `/_translate/{key}` socket (reference client, runs in its own uv env via PEP 723); stays connected full time, unloads the model after 60 s idle and reloads on the next job.
- `scripts/llm_translator.py` — instruct-LLM translator service client (docs/llm-translation.md): speaks the `markdown`/`article` job modes against an OpenAI Chat Completions endpoint or ollama's native `/api/chat` (its `/v1` ignores `think: false`); all LLM specifics (prompts, sampling, generation caps) live here, not in pagerite.
- `scripts/import_translation.py` — import a human-made whole-article translation file into the fragment store (same `align_article` validation as article-mode results; run with the server stopped).
Server run by CLI entry point `uv run pagerite` (no auto reloads, build needed). Dev mode is `scripts/devserver.py` (auto reloads, no build needed).
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@@ -1,5 +1,14 @@
# Whole-article and scoped LLM translation
**Status: implemented** (protocol modes and validation in
`pagerite/translate.py`, reference client `scripts/llm_translator.py`,
human-translation import `scripts/import_translation.py`; wire-level docs
in docs/localization.md). One deviation from the text below: ollama's
OpenAI-compatible `/v1/chat/completions` silently ignores `think: false`
(verified on 0.34.2), so the client's `api` config selects ollama's native
`/api/chat` for ollama backends; the OpenAI shape serves llama.cpp and
hosted APIs.
Design for augmenting the fragment-based machine translation
(docs/localization.md) with general-purpose instruct LLMs that understand
Markdown natively — as opposed to pure text-to-text models like Seed-X.
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@@ -337,15 +337,18 @@ transaction `user`.
Frames are JSON-encoded tagged msgspec structs (`pagerite/translate.py`;
`bytes` fields ride as base64):
- `{"type": "hello", "langs": [...]}` — client greeting announcing its
**capabilities**: the language codes its model can produce (normalized
to base subtags; `en`/empty dropped).
- `{"type": "job", "lang", "key", "texts", "path", "kind", "contexts"}`
server push: ONE fragment to translate (an article title or a chunk), as
a list of **prose segments** (see Segmentation below). `contexts` is
parallel to `texts` ("" = none): the surround to translate the segment
in — for clients that translate better with context (see below).
Contexts are not part of the result.
- `{"type": "hello", "langs": [...], "model", "modes"}` — client greeting
announcing its **capabilities**: the language codes its model can produce
(normalized to base subtags; `en`/empty dropped). `model` is a free-form
model string (logging only); `modes` lists the job granularities the
client accepts (default `["segments"]`, see Job modes below).
- `{"type": "job", "lang", "key", "texts", "path", "kind", "mode",
"contexts"}` — server push: ONE fragment to translate (an article title
or a chunk). In the default `segments` mode `texts` is a list of **prose
segments** (see Segmentation below) and `contexts` is parallel to `texts`
("" = none): the surround to translate the segment in — for clients that
translate better with context (see below). Contexts are not part of the
result. See Job modes for the other modes.
- `{"type": "result", "lang", "key", "texts"}` — client reply: the
segments translated, same order and count, matching its job by (lang, key).
@@ -387,6 +390,55 @@ Results are stored into `trans` in one transaction and set
pages gain a language from one fragment). Unknown keys are stored anyway
and re-storing overwrites — results are idempotent.
#### Job modes: segments, markdown, article
Instruct LLMs understand Markdown natively, so for them the segmentation
round trip below is unnecessary scaffolding (docs/llm-translation.md for
the design and the model trial evidence). `Hello.modes` announces which
job granularities a connection accepts; routing is per connection and per
mode, so a mixed fleet (a Seed-X instance, a local qwen, an API-backed
client) shares the work by capability. The validation skip-list is
mode-scoped — `(lang, key, mode)` — so a fragment one model rejects stays
offerable to clients of another approach.
- **`segments`** (default when a client omits `modes`) — the protocol as
described so far: `Job.texts` carries prose segments, `Result.texts`
returns them, the server splices by offset.
- **`markdown`** — one fragment as full Markdown: `Job.texts` carries a
single element, the chunk (a title crosses as plain text, with the
article's opening as its context as today). `Job.contexts` carries the
previous and next block of the **served hybrid** in the target language
(machine translation with user patches applied, "" where none), so human
corrections propagate into fresh translations as terminology/tone
reference; contexts are never part of the result. The result must
re-chunk to exactly one block with the source's anchor constructs (link
and image destinations, `{...}` placeholders) intact (`clean_block`),
then stores to `Data.trans` as usual.
- **`article`** — a whole page at once, offered only to article-capable
connections and only while a page is *mostly* pending (a new article or
a full refresh; steady-state edit follow-up stays scoped jobs). The
job's key is the page's first chunk; `Job.texts` carries the full
original Markdown. The result is decomposed per chunk
(`align_article`): non-translatable blocks (code fences, container
fences, raw HTML — everything `needs_translation` rejects) must appear
verbatim and in order and anchor the alignment; regions between anchors
pair positionally, a region whose block count changed stores nothing
(its chunks stay pending and fall back to scoped jobs), and a paired
block whose destinations/placeholders did not survive likewise.
`scripts/llm_translator.py` is the reference markdown+article client
(instruct LLMs via an OpenAI Chat Completions endpoint or ollama's native
API); `scripts/translator.py` (Seed-X) is untouched and announces
`["segments"]` implicitly.
**Importing human-made full translations:** `align_article` doubles as an
import path — `scripts/import_translation.py PATH LANG FILE.md` (run with
the server stopped) decomposes a pasted whole-article translation (e.g.
from ChatGPT) into proper `Data.trans` fragments with the same validation,
so later source edits invalidate and re-translate per chunk rather than
letting the translation editor's one monolithic patch go stale hunk by
hunk.
#### Segmentation
Fragments cross the wire as **prose segments** (`pagerite/segments.py`): the
@@ -423,10 +475,12 @@ of the block it splices into, closing fence included — segments are
inline prose, so `pure_prose` alone cannot see this) — each returned
segment must parse as
pure prose with no block-starting line or blank line, or the whole result
is dropped and logged, and the (lang, key)
pair is skipped for the rest of the server run (generation is
near-deterministic, so an immediate retry would re-fail; the fragment stays
pending and gets another chance on restart or `DELETE /_api/translations`).
is dropped and logged, and the (lang, key, mode)
combination is skipped for the rest of the server run (generation is
near-deterministic per model, so an immediate retry in the same mode would
re-fail; the fragment stays
pending and gets another chance on restart, in another mode, or on
`DELETE /_api/translations`).
`Data.trans` therefore only ever holds clean translated Markdown.
Link- and formatting-carrying blocks are the one place a segment is not