Add a CPU-only, English-first OCR engine (the `ocrs` crate on the `rten`
runtime) as an alternative to the local-LLM "vision" backend, which ran
too slowly on the target Raspberry Pi 5.
- `ANALYSIS_BACKEND` (default `ocr`) selects the engine; `vision` keeps the
existing LLM path. Deploy-time, env-only — not admin-tunable.
- `analysis::ocr` adds an `OcrEngine` trait (testable seam), the `OcrsEngine`
impl (models loaded once, inference on the blocking pool), and an
`OcrAnalyzeDispatcher` that plugs into the existing `AnalyzeDispatcher`
seam and reuses `persist_analysis`, so OCR text lands in `page_ocr_text`
and the `search_doc` tsvector exactly as the vision path produces them.
- The backend image bakes the two `.rten` models into /models, where
`OCRS_DETECTION_MODEL` / `OCRS_RECOGNITION_MODEL` default.
Because `/v1/me/page-search` ranks on `search_doc`, OCR text search works
the moment pages are processed. Auto-tagging, scene description and NSFW
flags remain the vision backend's job (deferred).
Bumps to 0.90.0 (minor) in both manifests.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Broadcasts analysis progress so the dashboard updates live:
- analysis::events: AnalysisEvents broadcaster + AnalysisEvent
(Enqueued / Started / Completed / Failed), carrying the
manga/chapter/page breadcrumb.
- The worker daemon resolves each page's breadcrumb (repo::page::locate)
and publishes Started before dispatch and Completed/Failed after.
- The admin reenqueue publishes Enqueued (scoped by manga/chapter).
- GET /v1/admin/analysis/status/stream — SSE (RequireAdmin) forwarding
each event as a named `analysis` frame; broadcast lag emits a `lagged`
frame. AppState carries the always-present events bus.
Tests: worker publishes started+completed (with breadcrumb) and failed;
SSE route is admin-gated (403 non-admin) and returns text/event-stream.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The OpenAI-compatible vision client and the bounded prompt/output handling
for the analysis worker (no DB, fully unit-tested):
- analysis::prompt: terse system prompt carrying the JSON schema, the OCR
kind / content-warning vocabularies, and the output-size caps.
- analysis::vision: VisionClient (downscale via the new `image` dep →
base64 data-URL → chat/completions with an image_url part), plus pure
parse_chat_completion (fence/prose-tolerant) and sanitize (drop empty
OCR, truncate, clamp tags to 10 via the shared page-tag normalizer,
filter unknown warnings).
- config::AnalysisConfig extended with endpoint/model/api_key/timeouts/
max_tokens/max_image_dim/max_image_bytes + from_env.
- Deps: add `image` (jpeg/png/webp), reqwest `json` feature. Expose
api::page_tags::normalize_tag as pub(crate) for reuse.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
