feat: add local-first private AI digest workflow
Migrate app code into canonical feature slices, add phone-only AI digest scheduling and review, wire local notification/background task support, and cover the flow with tests.
This commit is contained in:
Rijad Zuzo
@@ -0,0 +1,285 @@
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import 'dart:convert';
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import 'dart:math' as math;
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import 'package:relationship_saver/app/state/local_data_state.dart';
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import 'package:relationship_saver/features/people/domain/person_models.dart';
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class AnonymizedLlmDigestContext {
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const AnonymizedLlmDigestContext({
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required this.payload,
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required this.tokenToPersonId,
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});
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final Map<String, dynamic> payload;
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final Map<String, String> tokenToPersonId;
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String toPromptJson() {
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return const JsonEncoder.withIndent(' ').convert(payload);
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}
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}
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class AnonymizedLlmContextBuilder {
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const AnonymizedLlmContextBuilder({
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this.maxPeople = 20,
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this.maxSignalsPerPerson = 8,
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DateTime Function()? now,
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}) : _now = now ?? DateTime.now;
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final int maxPeople;
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final int maxSignalsPerPerson;
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final DateTime Function() _now;
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AnonymizedLlmDigestContext build(LocalDataState state) {
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final DateTime now = _now();
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final List<PersonProfile> selectedPeople =
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state.people
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.where(
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(PersonProfile person) => _isDigestRelevant(state, person, now),
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)
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.toList(growable: false)
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..sort(
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(PersonProfile a, PersonProfile b) => _urgencyScore(
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state,
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b,
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now,
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).compareTo(_urgencyScore(state, a, now)),
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);
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final List<Map<String, dynamic>> peoplePayload = <Map<String, dynamic>>[];
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final Map<String, String> tokenToPersonId = <String, String>{};
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for (int i = 0; i < math.min(selectedPeople.length, maxPeople); i += 1) {
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final PersonProfile person = selectedPeople[i];
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final String token = 'person_${(i + 1).toString().padLeft(3, '0')}';
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tokenToPersonId[token] = person.id;
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peoplePayload.add(_personPayload(state, person, token, now));
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}
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return AnonymizedLlmDigestContext(
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tokenToPersonId: tokenToPersonId,
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payload: <String, dynamic>{
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'schema': 'relationship_saver_private_digest_v1',
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'task':
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'Create a balanced private weekly digest with gift ideas, event ideas, reminders, and check-ins.',
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'rules': <String>[
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'Use only personToken values from the input.',
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'Do not infer or ask for names.',
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'Return JSON only.',
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'Prefer practical suggestions that can be reviewed before saving.',
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],
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'limits': <String, dynamic>{
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'maxItems': 10,
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'allowedKinds': <String>[
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'giftIdea',
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'eventIdea',
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'checkIn',
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'reminder',
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],
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},
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'people': peoplePayload,
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},
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);
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}
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bool _isDigestRelevant(
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LocalDataState state,
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PersonProfile person,
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DateTime now,
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) {
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if (_daysUntil(person.nextMoment, now).abs() <= 60) {
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return true;
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}
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final DateTime? last = person.lastInteractedAt;
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if (last == null || now.difference(last).inDays >= 14) {
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return true;
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}
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return state.importantDates.any(
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(PersonImportantDate value) =>
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value.personId == person.id &&
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!value.isSensitive &&
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_daysUntil(value.date, now).abs() <= 60,
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) ||
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state.preferenceSignals.any(
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(PersonPreferenceSignal signal) =>
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signal.personId == person.id &&
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signal.status != PreferenceSignalStatus.dismissed,
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);
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}
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int _urgencyScore(LocalDataState state, PersonProfile person, DateTime now) {
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final int nextMomentDays = _daysUntil(person.nextMoment, now).abs();
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int score = math.max(0, 80 - nextMomentDays);
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final DateTime? last = person.lastInteractedAt;
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if (last == null) {
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score += 30;
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} else {
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score += math.min(40, now.difference(last).inDays);
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}
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score +=
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state.importantDates
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.where(
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(PersonImportantDate value) =>
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value.personId == person.id &&
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!value.isSensitive &&
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_daysUntil(value.date, now).abs() <= 60,
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)
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.length *
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10;
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return score;
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}
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Map<String, dynamic> _personPayload(
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LocalDataState state,
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PersonProfile person,
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String token,
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DateTime now,
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) {
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final List<PersonPreferenceSignal> signals = state.preferenceSignals
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.where(
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(PersonPreferenceSignal signal) =>
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signal.personId == person.id &&
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signal.status != PreferenceSignalStatus.dismissed,
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)
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.take(maxSignalsPerPerson)
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.toList(growable: false);
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final List<PersonImportantDate> dates = state.importantDates
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.where(
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(PersonImportantDate value) =>
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value.personId == person.id && !value.isSensitive,
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)
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.take(maxSignalsPerPerson)
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.toList(growable: false);
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return <String, dynamic>{
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'personToken': token,
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'relationshipCategory': _relationshipCategory(person.relationship),
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'affinityBand': _affinityBand(person.affinityScore),
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'upcoming': <String>[
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_relativeWindow('next planned moment', person.nextMoment, now),
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...dates.map(
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(PersonImportantDate value) => _relativeWindow(
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_safeCategory(value.classification),
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value.date,
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now,
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),
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),
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],
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'recency': _recency(person.lastInteractedAt, now),
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'interests': _safeList(<String>[
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...person.tags,
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...signals
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.where(
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(PersonPreferenceSignal signal) =>
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signal.polarity == PreferenceSignalPolarity.like,
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)
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.map((PersonPreferenceSignal signal) => signal.label),
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]).take(maxSignalsPerPerson).toList(growable: false),
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'constraints': _safeList(
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signals
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.where(
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(PersonPreferenceSignal signal) =>
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signal.polarity == PreferenceSignalPolarity.dislike,
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)
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.map((PersonPreferenceSignal signal) => 'avoid ${signal.label}')
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.toList(growable: false),
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).take(maxSignalsPerPerson).toList(growable: false),
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};
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}
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String _relationshipCategory(String value) {
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final String normalized = value.toLowerCase();
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if (_containsAny(normalized, <String>[
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'partner',
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'spouse',
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'wife',
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'husband',
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])) {
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return 'partner';
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}
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if (_containsAny(normalized, <String>[
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'family',
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'sister',
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'brother',
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'mother',
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'father',
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'parent',
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'cousin',
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'aunt',
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'uncle',
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])) {
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return 'family';
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}
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if (normalized.contains('friend')) {
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return 'friend';
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}
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if (_containsAny(normalized, <String>['work', 'colleague', 'coworker'])) {
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return 'colleague';
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}
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return 'relationship';
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}
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String _affinityBand(int score) {
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if (score >= 85) {
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return 'very close';
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}
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if (score >= 65) {
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return 'close';
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}
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return 'light';
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}
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String _relativeWindow(String label, DateTime date, DateTime now) {
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final int days = _daysUntil(date, now);
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final String when = days == 0
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? 'today'
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: days > 0
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? 'in about $days days'
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: 'about ${days.abs()} days ago';
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return '${_safeCategory(label)} $when';
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}
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String _recency(DateTime? lastInteractedAt, DateTime now) {
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if (lastInteractedAt == null) {
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return 'no recent interaction recorded';
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}
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final int days = now.difference(lastInteractedAt).inDays;
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if (days <= 1) {
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return 'contacted recently';
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}
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return 'last contact about $days days ago';
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}
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List<String> _safeList(Iterable<String> values) {
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final List<String> out = <String>[];
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final Set<String> seen = <String>{};
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for (final String raw in values) {
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final String value = _safeCategory(raw);
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if (value.isEmpty) {
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continue;
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}
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if (seen.add(value.toLowerCase())) {
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out.add(value);
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}
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}
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return out;
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}
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String _safeCategory(String value) {
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return value
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.trim()
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.replaceAll(RegExp(r'https?://\S+'), '')
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.replaceAll(RegExp(r'[^a-zA-Z0-9 +&/-]+'), '')
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.replaceAll(RegExp(r'\s+'), ' ')
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.trim()
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.toLowerCase();
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}
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int _daysUntil(DateTime date, DateTime now) {
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return date.difference(DateTime(now.year, now.month, now.day)).inDays;
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}
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bool _containsAny(String value, List<String> probes) {
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return probes.any(value.contains);
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}
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}
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