477cb43d4a
3 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
| 477cb43d4a |
feat: escalate magazine OCR to a connected vision engine on garbled/scanned pages
A page needing OCR (or whose already-extracted text -- native or
tesseract alike -- scores as mostly garbage via ocr_quality_score) is
now escalated to a connected vision OCR engine before falling back to
tesseract. Falls back automatically on any failure (unreachable engine,
timeout, unparseable output); never fatal to ingestion.
Verified live against ocr-baidu-unlimited-ocr on a real 28-page scanned
c't magazine excerpt (Epson ES-580W, no scanner OCR): every garbled
article title tesseract produced ("K | soll Arbeit abnehmen", ". |",
"@)X", "Owns mee") was replaced by the real headline ("1. Irrtum: KI
ist ein allgemeiner Jobkiller", etc.), and furniture detection jumped
from 44 to 151 blocks because the engine labels running headers/
footers/page numbers directly instead of needing fuzzy post-hoc
matching. 26 of 28 pages used the vision path; the remaining 2 fell
back to tesseract automatically.
Also fixes two real defects found investigating the same real-world
data, both regression-tested against the actual garbled strings
observed:
- Exact-match repeated-line detection (running header/footer) silently
failed once tesseract OCR'd the same line differently each time --
cluster_running_furniture fuzzy-matches near-edge blocks instead.
- ocr_page() built one Block per OCR text-LINE rather than per
paragraph, so a single anomalous line (a chart number, scan noise, a
wrapped headline continuation) could independently trigger title
classification -- now grouped by paragraph like the native PyMuPDF
path, using the paragraph's median line height rather than its total
bbox height for font size.
A vision-engine label (footer/title/page_number/caption) is trusted
outright and skips classify_blocks' font-size heuristics entirely,
since the engine gives no reliable font metric; an ambiguous "text"
region gets a synthesized estimate from its paragraph area and length
(estimate_font_size_from_area) and still goes through normal
classification.
Off unless vision_ocr_url/vision_ocr_model are configured
(vision_ocr_enabled setting, default on if reachable); per-request
override via the ingest endpoint body. Default engine URL uses
host.docker.internal, confirmed live -- the OCR container runs on its
own Docker network, not dgx_net, so a container-name default would not
resolve from the app container.
28 new tests (136 total in the module). ocr_quality_score is
deliberately coarse and documented as such: it catches text that is
mostly symbol noise, not a plausible single-word misread inside an
otherwise normal sentence (confirmed live: a misread "KI" -> "K |"
still scored 0.81) -- that class of error needs a dictionary or
language-model check, out of scope here.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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| 71a398b82f |
feat: add magazine reader frontend (P1)
Studio -> Magazines: library, contents tree grouped by section with
confidence/pages/listening-time/audio status, the Stage D review
screen (tick/untick layout blocks, correct title/author, approve or
reject), a reflowed article view with click-to-seek sentence
highlighting, a linked original-page view showing the source bounding
box, and a podcast panel (2-3 host pickers, script generation,
turn-by-turn playback).
Wired into the existing lazy-module system (module-manifest.json,
loader.js, nav.js) rather than a separate app. Reuses /api/tts-preview
for both narration and podcast turns -- no new audio pipeline.
Fixes found building this:
- The pane toggle used role="tab" without the full ARIA tabs pattern
(aria-selected, roving tabindex, arrow-key nav) -- fails WCAG 2.2 AA
and hid the buttons from role-based tooling. Replaced with a button
group + aria-pressed, matching the plain-click interaction it
actually has.
- Print layout cues ("(continued on page 8)") were being sent to TTS
verbatim -- narration would have spoken the parenthetical aloud.
Stripped from the narration copy only; layout.json keeps the
original for the review screen.
- has_podcast now comes from the articles listing so opening an
article without a generated script skips a doomed GET instead of a
routine 404 on every open.
Verified against the real API contract with Playwright (library,
review pre-selection, approval, sentence highlighting + PDF-page
linking, podcast approval gate, zero console errors across the flow)
and manually end-to-end against a real ingested fixture, screenshots
included. Full suite: 94 Python tests, 33/34 desktop Playwright tests
(one unrelated pre-existing flaky DOM-count assertion).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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| 736aeaaeac |
feat: add magazine projects with layout-aware article extraction
Magazines break the audiobook pipeline's assumptions: several unrelated articles share a page, columns run in parallel, adverts and sidebars interrupt body copy, and a feature routinely jumps twenty pages to its tail. Narrating page-by-page walks out of an article mid-sentence and into an advert, so the canonical object is the article, not the page. core/magazine.py reconstructs articles from a flat PDF: PyMuPDF extracts blocks with bboxes and font metrics, tesseract supplies a TSV fallback so scanned pages join the same column grouping, blocks are classified and ordered column-major, and articles are anchored by the parsed table of contents with "continued on page N" tails linked back. routes/magazine.py adds 13 endpoints. Ingestion is a restart-safe background job. Nothing is narrated until a human approves the boundaries; podcast generation refuses unapproved articles. Podcast mode renders an approved article as a 2-3 host discussion using the configured LLM and voices the user picks, alongside narration rather than instead of it. Verified end-to-end over HTTP on a synthetic 8-page issue: the feature came back as pages [3, 8] with its jump tail absorbed and the advert page excluded, and an image-only rendering recovered all 47 blocks via OCR. 44 new tests; full suite 90 passing. The Studio UI is not built — this is reachable only via the API. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> |
