Add chat preference extraction on shared ingest
This commit is contained in:
Rijad Zuzo
@@ -7,6 +7,39 @@ Updated: 2026-02-22
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- After every sensible code/documentation change set, create a git commit as
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the last step so the next agent session can pick up from clean checkpoints.
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## Latest Milestone (2026-02-22): MVP Chat Preference Extractor + Ingest Enrichment
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Implemented the first local semantic-enrichment pass so shared chat messages can
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start building inferred person preferences automatically.
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- `lib/features/local/chat_preference_extractor.dart` (new)
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- added a pure Dart, local-first rule-based extractor
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- extracts evidence-backed preference candidates from message text:
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- `prefer X over Y` (creates like/dislike pair)
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- `favorite ... is ...`
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- `I love/like/enjoy ...`
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- `I hate/dislike/don’t like ...`
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- `allergic to ...`
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- adds category heuristics (e.g. drink/food/hobby/environment/health)
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- returns confidence-scored candidates with evidence snippets
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- `lib/features/local/local_repository.dart`
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- integrated extractor into resolved shared-message ingest flow
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- when a chat share is imported and linked to a profile:
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- store raw shared message + capture moment (existing behavior)
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- extract preference candidates from message text
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- upsert local inferred preference signals with evidence + source metadata
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- Tests
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- `test/features/local/chat_preference_extractor_test.dart` (new)
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- extractor unit coverage for positive/negative/comparative/allergy patterns
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- `test/features/local/local_repository_test.dart`
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- added ingest test proving shared chat import creates inferred signals
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- Validation
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- `flutter analyze` -> pass
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- `flutter test` -> pass
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## Latest Milestone (2026-02-22): Local Preference Signal Scaffolding (Inferred/Confirmed)
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Added a local-first data model and repository APIs for chat-derived preference
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@@ -0,0 +1,311 @@
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import 'package:flutter/foundation.dart';
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import 'package:relationship_saver/features/local/local_models.dart';
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/// A lightweight, local-first rule-based extractor for chat-derived preferences.
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///
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/// This is intentionally conservative and evidence-backed:
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/// - returns inferred candidates with confidence
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/// - deduplicates by key + polarity
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/// - is easy to replace or augment with backend NLP later
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class ChatPreferenceExtractor {
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const ChatPreferenceExtractor();
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static const int _maxCandidates = 8;
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/// Extracts preference candidates from a shared chat message.
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List<ExtractedPreferenceSignalCandidate> extract(String messageText) {
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final String text = messageText.trim();
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if (text.isEmpty) {
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return const <ExtractedPreferenceSignalCandidate>[];
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}
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final List<ExtractedPreferenceSignalCandidate> out =
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<ExtractedPreferenceSignalCandidate>[];
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void addCandidate(ExtractedPreferenceSignalCandidate candidate) {
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final bool exists = out.any(
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(ExtractedPreferenceSignalCandidate item) =>
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item.key == candidate.key && item.polarity == candidate.polarity,
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);
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if (!exists && out.length < _maxCandidates) {
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out.add(candidate);
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}
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}
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for (final RegExpMatch match in _preferOverPattern.allMatches(text)) {
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final String? preferred = _cleanPhrase(match.namedGroup('preferred'));
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final String? over = _cleanPhrase(match.namedGroup('over'));
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if (preferred == null || over == null) {
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continue;
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}
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final String category = _inferCategory(preferred, fallback: 'general');
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addCandidate(
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_candidate(
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phrase: preferred,
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category: category,
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polarity: PreferenceSignalPolarity.like,
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confidence: 0.86,
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evidenceSnippet: _extractEvidenceSnippet(text, match),
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),
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);
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addCandidate(
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_candidate(
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phrase: over,
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category: _inferCategory(over, fallback: category),
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polarity: PreferenceSignalPolarity.dislike,
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confidence: 0.72,
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evidenceSnippet: _extractEvidenceSnippet(text, match),
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),
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);
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}
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for (final RegExpMatch match in _favoritePattern.allMatches(text)) {
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final String? categoryRaw = _cleanPhrase(match.namedGroup('category'));
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final String? thing = _cleanPhrase(match.namedGroup('thing'));
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if (thing == null) {
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continue;
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}
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final String category = _normalizeCategory(
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categoryRaw ?? _inferCategory(thing, fallback: 'general'),
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);
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addCandidate(
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_candidate(
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phrase: thing,
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category: category,
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polarity: PreferenceSignalPolarity.like,
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confidence: 0.9,
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evidenceSnippet: _extractEvidenceSnippet(text, match),
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),
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);
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}
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for (final RegExpMatch match in _positivePattern.allMatches(text)) {
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final String? phrase = _cleanPhrase(match.namedGroup('thing'));
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if (phrase == null) {
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continue;
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}
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addCandidate(
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_candidate(
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phrase: phrase,
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category: _inferCategory(phrase, fallback: 'general'),
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polarity: PreferenceSignalPolarity.like,
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confidence: 0.74,
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evidenceSnippet: _extractEvidenceSnippet(text, match),
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),
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);
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}
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for (final RegExpMatch match in _negativePattern.allMatches(text)) {
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final String? phrase = _cleanPhrase(match.namedGroup('thing'));
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if (phrase == null) {
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continue;
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}
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addCandidate(
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_candidate(
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phrase: phrase,
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category: _inferCategory(phrase, fallback: 'general'),
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polarity: PreferenceSignalPolarity.dislike,
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confidence: 0.8,
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evidenceSnippet: _extractEvidenceSnippet(text, match),
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),
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);
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}
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for (final RegExpMatch match in _allergyPattern.allMatches(text)) {
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final String? phrase = _cleanPhrase(match.namedGroup('thing'));
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if (phrase == null) {
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continue;
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}
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addCandidate(
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_candidate(
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phrase: phrase,
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category: 'health',
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polarity: PreferenceSignalPolarity.dislike,
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confidence: 0.95,
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evidenceSnippet: _extractEvidenceSnippet(text, match),
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),
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);
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}
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return out;
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}
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ExtractedPreferenceSignalCandidate _candidate({
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required String phrase,
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required String category,
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required PreferenceSignalPolarity polarity,
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required double confidence,
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required String evidenceSnippet,
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}) {
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final String normalizedCategory = _normalizeCategory(category);
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final String normalizedValue = _normalizeValue(phrase);
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return ExtractedPreferenceSignalCandidate(
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key: '$normalizedCategory:$normalizedValue',
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label: _displayLabel(phrase),
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category: normalizedCategory,
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polarity: polarity,
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confidence: confidence,
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evidenceSnippet: evidenceSnippet,
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);
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}
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String _inferCategory(String phrase, {required String fallback}) {
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final String normalized = phrase.toLowerCase();
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if (_containsAny(normalized, <String>[
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'coffee',
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'tea',
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'matcha',
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'espresso',
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'latte',
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'wine',
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'beer',
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'juice',
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])) {
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return 'drink';
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}
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if (_containsAny(normalized, <String>[
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'sushi',
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'ramen',
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'pizza',
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'pasta',
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'burger',
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'brunch',
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'chocolate',
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'dessert',
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'spicy food',
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])) {
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return 'food';
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}
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if (_containsAny(normalized, <String>[
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'book',
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'books',
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'bookstore',
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'reading',
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'novels',
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'poetry',
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])) {
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return 'hobby';
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}
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if (_containsAny(normalized, <String>[
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'music',
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'jazz',
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'vinyl',
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'concerts',
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])) {
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return 'music';
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}
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if (_containsAny(normalized, <String>['morning', 'evening', 'night'])) {
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return 'schedule';
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}
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if (_containsAny(normalized, <String>['crowds', 'clubs', 'noise'])) {
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return 'environment';
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}
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return fallback;
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}
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bool _containsAny(String value, List<String> probes) {
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for (final String probe in probes) {
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if (value.contains(probe)) {
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return true;
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}
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}
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return false;
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}
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String _normalizeCategory(String value) {
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final String normalized = value
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.trim()
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.toLowerCase()
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.replaceAll(RegExp(r'[^a-z0-9]+'), '_')
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.replaceAll(RegExp(r'_+'), '_')
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.replaceAll(RegExp(r'^_|_$'), '');
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return normalized.isEmpty ? 'general' : normalized;
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}
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String _normalizeValue(String value) {
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return value
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.trim()
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.toLowerCase()
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.replaceAll(RegExp(r'[^a-z0-9]+'), ' ')
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.replaceAll(RegExp(r'\s+'), ' ')
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.trim();
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}
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String _displayLabel(String value) {
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final String clean = value.trim();
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if (clean.isEmpty) {
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return value;
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}
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return clean[0].toUpperCase() + clean.substring(1);
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}
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String? _cleanPhrase(String? raw) {
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if (raw == null) {
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return null;
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}
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final String cleaned = raw
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.trim()
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.replaceAll(RegExp(r'^[\s,:;.-]+'), '')
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.replaceAll(RegExp(r'[\s,:;.!?]+$'), '')
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.replaceAll(RegExp(r'\s+'), ' ');
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if (cleaned.isEmpty) {
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return null;
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}
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if (cleaned.length > 42) {
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return cleaned.substring(0, 42).trim();
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}
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return cleaned;
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}
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String _extractEvidenceSnippet(String text, RegExpMatch match) {
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final int start = match.start < 0 ? 0 : match.start;
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final int end = match.end > text.length ? text.length : match.end;
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final int prefix = (start - 16).clamp(0, text.length).toInt();
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final int suffix = (end + 16).clamp(0, text.length).toInt();
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return text.substring(prefix, suffix).trim();
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}
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static final RegExp _preferOverPattern = RegExp(
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r'\b(?:i\s+)?prefer\s+(?<preferred>[^,.!?]{1,40}?)\s+over\s+(?<over>[^,.!?]{1,40}?)(?=\s+(?:and|but)\b|[,.!?]|$)',
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caseSensitive: false,
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);
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static final RegExp _favoritePattern = RegExp(
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r'\b(?:my\s+)?favorite(?:\s+(?<category>food|drink|color|music|movie|book))?\s+is\s+(?<thing>[^,.!?]{1,40})\b',
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caseSensitive: false,
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);
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static final RegExp _positivePattern = RegExp(
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r'\b(?:i\s+)?(?:really\s+)?(?:love|like|enjoy)\s+(?<thing>[^,.!?]{1,40})\b',
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caseSensitive: false,
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);
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static final RegExp _negativePattern = RegExp(
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r"\b(?:i\s+)?(?:(?:really\s+)?(?:hate|dislike)|don't\s+like|do\s+not\s+like|can't\s+stand|cannot\s+stand)\s+(?<thing>[^,.!?]{1,40})\b",
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caseSensitive: false,
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);
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static final RegExp _allergyPattern = RegExp(
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r'\b(?:i\s+am\s+)?allergic\s+to\s+(?<thing>[^,.!?]{1,40})\b',
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caseSensitive: false,
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);
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}
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@immutable
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class ExtractedPreferenceSignalCandidate {
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const ExtractedPreferenceSignalCandidate({
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required this.key,
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required this.label,
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required this.category,
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required this.polarity,
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required this.confidence,
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required this.evidenceSnippet,
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});
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final String key;
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final String label;
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final String category;
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final PreferenceSignalPolarity polarity;
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final double confidence;
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final String evidenceSnippet;
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}
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@@ -2,6 +2,7 @@ import 'dart:convert';
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import 'package:flutter_riverpod/flutter_riverpod.dart';
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import 'package:relationship_saver/core/config/app_config.dart';
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import 'package:relationship_saver/features/local/chat_preference_extractor.dart';
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import 'package:relationship_saver/features/local/local_models.dart';
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import 'package:relationship_saver/features/local/storage/local_data_store.dart';
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import 'package:relationship_saver/features/local/storage/local_data_store_hive.dart';
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@@ -81,6 +82,8 @@ class LocalRepository extends AsyncNotifier<LocalDataState> {
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static const int _syncSchemaVersion = 1;
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static const Uuid _uuid = Uuid();
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static const ChatPreferenceExtractor _chatPreferenceExtractor =
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ChatPreferenceExtractor();
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@override
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Future<LocalDataState> build() async {
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@@ -1856,8 +1859,7 @@ class LocalRepository extends AsyncNotifier<LocalDataState> {
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moment,
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...current.moments,
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];
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final List<SharedMessageEntry> nextMessages = <SharedMessageEntry>[
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SharedMessageEntry(
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final SharedMessageEntry sharedEntry = SharedMessageEntry(
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id: 'sm-${_uuid.v4()}',
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sourceApp: sourceApp,
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profileId: resolvedPerson.id,
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@@ -1868,7 +1870,9 @@ class LocalRepository extends AsyncNotifier<LocalDataState> {
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sourceDisplayName: sourceDisplayName,
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sourceUserId: sourceUserId,
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sourceThreadId: sourceThreadId,
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),
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);
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final List<SharedMessageEntry> nextMessages = <SharedMessageEntry>[
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sharedEntry,
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...current.sharedMessages,
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];
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final List<SharedInboxEntry> nextInbox = consumedInboxEntryId == null
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@@ -1906,6 +1910,24 @@ class LocalRepository extends AsyncNotifier<LocalDataState> {
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];
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await _enqueueChanges(outbound);
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final List<ExtractedPreferenceSignalCandidate> extractedSignals =
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_chatPreferenceExtractor.extract(summary);
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for (final ExtractedPreferenceSignalCandidate candidate
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in extractedSignals) {
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await upsertInferredPreferenceSignalObservation(
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personId: resolvedPerson.id,
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key: candidate.key,
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label: candidate.label,
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category: candidate.category,
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polarity: candidate.polarity,
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confidence: candidate.confidence,
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sourceApp: sourceApp,
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evidenceMessageId: sharedEntry.id,
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evidenceSnippet: candidate.evidenceSnippet,
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observedAt: sharedAt,
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);
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}
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return SharedMessageIngestResult.imported(
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profileId: resolvedPerson.id,
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profileName: resolvedPerson.name,
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@@ -0,0 +1,65 @@
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import 'package:flutter_test/flutter_test.dart';
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import 'package:relationship_saver/features/local/chat_preference_extractor.dart';
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import 'package:relationship_saver/features/local/local_models.dart';
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void main() {
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const ChatPreferenceExtractor extractor = ChatPreferenceExtractor();
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test('extracts prefer-over like/dislike signals', () {
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final List<ExtractedPreferenceSignalCandidate> result = extractor.extract(
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'I prefer tea over coffee, especially at night.',
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);
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expect(
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result.any(
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(ExtractedPreferenceSignalCandidate item) =>
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item.key == 'drink:tea' &&
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item.polarity == PreferenceSignalPolarity.like,
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),
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isTrue,
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);
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expect(
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result.any(
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(ExtractedPreferenceSignalCandidate item) =>
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item.key == 'drink:coffee' &&
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item.polarity == PreferenceSignalPolarity.dislike,
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),
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isTrue,
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);
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});
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test('extracts positive and negative statements with categories', () {
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final List<ExtractedPreferenceSignalCandidate> result = extractor.extract(
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"I love bookstores and I don't like loud clubs.",
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);
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expect(
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result.any(
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(ExtractedPreferenceSignalCandidate item) =>
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item.category == 'hobby' &&
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item.polarity == PreferenceSignalPolarity.like,
|
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),
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isTrue,
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);
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expect(
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result.any(
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(ExtractedPreferenceSignalCandidate item) =>
|
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item.category == 'environment' &&
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item.polarity == PreferenceSignalPolarity.dislike,
|
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),
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isTrue,
|
||||
);
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});
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test('extracts allergy as high-confidence dislike signal', () {
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final List<ExtractedPreferenceSignalCandidate> result = extractor.extract(
|
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'I am allergic to peanuts, please remember that.',
|
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);
|
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|
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final ExtractedPreferenceSignalCandidate signal = result.firstWhere(
|
||||
(ExtractedPreferenceSignalCandidate item) => item.key == 'health:peanuts',
|
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);
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expect(signal.polarity, PreferenceSignalPolarity.dislike);
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expect(signal.confidence, greaterThan(0.9));
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});
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}
|
||||
@@ -226,6 +226,57 @@ void main() {
|
||||
},
|
||||
);
|
||||
|
||||
test(
|
||||
'ingestSharedMessage extracts chat-derived preference signals',
|
||||
() async {
|
||||
final ProviderContainer container = _createContainer();
|
||||
addTearDown(container.dispose);
|
||||
|
||||
await container.read(localRepositoryProvider.future);
|
||||
|
||||
final SharedMessageIngestResult result = await container
|
||||
.read(localRepositoryProvider.notifier)
|
||||
.ingestSharedMessage(
|
||||
const SharedMessageIngestInput(
|
||||
sourceApp: 'whatsapp',
|
||||
sourceDisplayName: 'Nora Diaz',
|
||||
sourceUserId: 'wa:nora_001',
|
||||
messageText:
|
||||
"I prefer tea over coffee and I don't like loud clubs.",
|
||||
),
|
||||
);
|
||||
|
||||
final LocalDataState after = await container.read(
|
||||
localRepositoryProvider.future,
|
||||
);
|
||||
final List<PersonPreferenceSignal> signals = after.preferenceSignals
|
||||
.where(
|
||||
(PersonPreferenceSignal signal) =>
|
||||
signal.personId == result.profileId,
|
||||
)
|
||||
.toList(growable: false);
|
||||
|
||||
expect(signals, isNotEmpty);
|
||||
expect(
|
||||
signals.any(
|
||||
(PersonPreferenceSignal signal) =>
|
||||
signal.key == 'drink:tea' &&
|
||||
signal.polarity == PreferenceSignalPolarity.like &&
|
||||
signal.status == PreferenceSignalStatus.inferred,
|
||||
),
|
||||
isTrue,
|
||||
);
|
||||
expect(
|
||||
signals.any(
|
||||
(PersonPreferenceSignal signal) =>
|
||||
signal.key == 'drink:coffee' &&
|
||||
signal.polarity == PreferenceSignalPolarity.dislike,
|
||||
),
|
||||
isTrue,
|
||||
);
|
||||
},
|
||||
);
|
||||
|
||||
test(
|
||||
'queues near-match conflict and then uses fingerprint mapping for follow-up shares',
|
||||
() async {
|
||||
|
||||
Reference in New Issue
Block a user