scoreText (more normalized occurrences rank higher; earlier first match breaks
ties) and rankHits (score every source, drop non-matches, attach a display
snippet of the original text, sort best-first with an explicit input-order
tiebreak since Dart's sort isn't stable). The search_indexer's pure ranking
core, making search_text + search_snippet load-bearing.
flutter analyze lib/editor clean; 223/223 tests (+9).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
normalizeForIndex (lowercase + collapse whitespace runs incl. hard PDF/OCR
newlines + trim) and matchesNormalized so a query matches across the line breaks
in raw extracted text. Deliberately NO word-tokenization: Chinese has no
inter-word spaces, so substring match over normalized text is correct for both
Latin and CJK (段/word segmentation belongs in the DB FTS tokenizer). Verified
on CJK inputs (你好/笔记应用).
flutter analyze lib/editor clean; 181/181 tests (+9).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
For library-wide full-text search (the user's #1 named differentiator):
snippetFor() finds the first case-insensitive match of a query in a source
string (PDF text page / typed box / OCR'd handwriting) and returns a windowed
excerpt centered on it, preserving the match offset + length and
truncatedStart/End flags so the results list can render "…ctx **match** ctx…"
and jump to the hit. The full match is always included; near-edge matches don't
over-truncate. Returns null for empty/absent query.
The FTS index + ranking live in the DB (search_indexer, later); this is the
pure, storage-free excerpt math, fully unit-tested.
flutter analyze lib/editor clean; 164/164 tests (+8).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
