[Developer] #215 AI frame-suggest vertical slice (mock LlmService)
설계서대로 구현. flutter_gemma 실제 통합은 OQ-1 (모델 URL+SHA) 확정 후.
v1은 LlmService 추상 + ModelLifecycle (다운로드/SHA/purge) + Riverpod
providers + 다이얼로그 + Settings 화면까지. main.dart 가 MockLlmService 를
override 해 모든 경로가 graceful (suggest 결과는 빈 리스트).
추가:
- lib/data/ai/{llm_service,gemma_llm_service,model_lifecycle}.dart
- lib/domain/ai/{frame_candidate,few_shot_builder,parse_response,suggest_frame}.dart
- lib/state/ai_providers.dart (aiSettings + modelAvailability + frameSuggestions)
- lib/ui/screens/settings_screen.dart (opt-in 토글 + 모델 상태 표시)
- lib/ui/widgets/frame_suggestion_dialog.dart (후보 3개 카드 + 다시 시도)
- HabitCreateScreen: "AI 제안" 버튼 (opt-in + ready 일 때만 노출)
- MetaDao.remove(key) 추가 (purge 용)
테스트 31개 신규 추가 (총 62개 통과):
- test/domain/ai/{suggest_frame, few_shot_builder, parse_response}_test.dart
- test/data/ai/model_lifecycle_test.dart (download/SHA/purge/availability)
flutter analyze 0 issue, flutter build apk --debug 통과.
Refs #215
This commit is contained in:
131
app/test/domain/ai/few_shot_builder_test.dart
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131
app/test/domain/ai/few_shot_builder_test.dart
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import 'package:flutter_test/flutter_test.dart';
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import 'package:life_helper/domain/ai/few_shot_builder.dart';
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import 'package:life_helper/domain/ai/frame_candidate.dart';
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import 'package:life_helper/domain/models/frame_pattern.dart';
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import 'package:life_helper/domain/models/habit.dart';
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final _patterns = <FramePatternModel>[
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const FramePatternModel(
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id: 'fp_alcohol',
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domain: 'drink',
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avoidanceKeyword: '술 끊기',
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l0Example: '술 끊기',
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l2Suggestion: '저녁엔 무알콜 음료',
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l3Identity: '나는 맑은 정신의 사람이다',
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),
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const FramePatternModel(
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id: 'fp_smoke',
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domain: 'smoke',
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avoidanceKeyword: '담배 끊기',
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l0Example: '담배 끊기',
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l2Suggestion: '간식 대체',
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l3Identity: '나는 깨끗한 폐를 가진 사람이다',
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),
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const FramePatternModel(
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id: 'fp_general',
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domain: 'general',
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avoidanceKeyword: '안 하기',
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l0Example: '안 하기',
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l2Suggestion: '대체 행동 정의',
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),
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];
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void main() {
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test('matched keyword surfaces relevant pattern first', () {
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final p = buildFewShotPrompt(
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const SuggestFrameInput(
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rawText: '술 끊고 싶어',
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habitType: HabitType.breakHabit,
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),
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_patterns,
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);
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expect(p, contains('## 예시 1'));
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// The alcohol pattern (highest score) should appear before smoke/general.
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final idxAlc = p.indexOf('저녁엔 무알콜 음료');
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final idxSmk = p.indexOf('간식 대체');
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expect(idxAlc, greaterThan(-1));
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expect(idxSmk == -1 || idxAlc < idxSmk, true);
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});
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test('fallback uses first patterns when no keyword matches', () {
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final p = buildFewShotPrompt(
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const SuggestFrameInput(
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rawText: 'xyz unknown words',
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habitType: HabitType.build,
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),
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_patterns,
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);
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expect(p, contains('## 예시 1'));
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// First pattern in list is alcohol.
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expect(p, contains('저녁엔 무알콜 음료'));
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});
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test('empty patterns → prompt has no few-shot section', () {
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final p = buildFewShotPrompt(
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const SuggestFrameInput(
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rawText: '술 끊고 싶어',
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habitType: HabitType.breakHabit,
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),
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const [],
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);
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expect(p.contains('변환 예시'), false);
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expect(p, contains('사용자 입력'));
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expect(p, contains('raw_text:'));
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});
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test('anchor hint appears when provided', () {
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final p = buildFewShotPrompt(
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const SuggestFrameInput(
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rawText: '책 읽고 싶어',
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habitType: HabitType.build,
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anchorHint: '아침 양치 후',
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),
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_patterns,
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);
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expect(p, contains('anchor_hint: "아침 양치 후"'));
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});
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test('habit_type rendered using dbValue', () {
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final pBreak = buildFewShotPrompt(
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const SuggestFrameInput(
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rawText: 'a',
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habitType: HabitType.breakHabit,
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),
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const [],
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);
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expect(pBreak, contains('habit_type: break'));
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final pBuild = buildFewShotPrompt(
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const SuggestFrameInput(rawText: 'a', habitType: HabitType.build),
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const [],
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);
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expect(pBuild, contains('habit_type: build'));
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});
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test('deterministic — same input → same prompt', () {
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final a = buildFewShotPrompt(
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const SuggestFrameInput(
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rawText: '술 끊기',
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habitType: HabitType.breakHabit,
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),
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_patterns,
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);
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final b = buildFewShotPrompt(
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const SuggestFrameInput(
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rawText: '술 끊기',
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habitType: HabitType.breakHabit,
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),
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_patterns,
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);
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expect(a, b);
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});
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test('maxFewShot caps selected examples', () {
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final p = buildFewShotPrompt(
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const SuggestFrameInput(rawText: 'x', habitType: HabitType.build),
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_patterns,
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maxFewShot: 1,
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);
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expect(p, contains('## 예시 1'));
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expect(p.contains('## 예시 2'), false);
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});
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}
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90
app/test/domain/ai/parse_response_test.dart
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90
app/test/domain/ai/parse_response_test.dart
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import 'package:flutter_test/flutter_test.dart';
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import 'package:life_helper/domain/ai/parse_response.dart';
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import 'package:life_helper/domain/models/habit.dart';
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void main() {
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test('parses 3 valid candidates', () {
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final r = parseFrameCandidates({
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'candidates': [
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{'level': 'L2', 'framed_text': '저녁엔 무알콜 마시기', 'confidence': 0.9},
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{'level': 'L3', 'framed_text': '나는 맑은 정신의 사람이다'},
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{'level': 'L2', 'framed_text': '주중엔 운동 우선'},
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],
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});
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expect(r, hasLength(3));
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expect(r[0].level, FrameLevel.l2);
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expect(r[0].confidence, 0.9);
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expect(r[1].level, FrameLevel.l3);
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expect(r[1].confidence, 0.5); // default
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});
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test('candidates missing → FormatException', () {
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expect(
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() => parseFrameCandidates({'foo': 'bar'}),
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throwsA(isA<FormatException>()),
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);
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});
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test('candidates not list → FormatException', () {
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expect(
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() => parseFrameCandidates({'candidates': 'oops'}),
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throwsA(isA<FormatException>()),
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);
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});
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test('empty candidates → empty list (no throw)', () {
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final r = parseFrameCandidates({'candidates': []});
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expect(r, isEmpty);
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});
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test('skips unknown level + length-violating items', () {
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final tooLong = 'a' * 121;
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final r = parseFrameCandidates({
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'candidates': [
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{'level': 'L99', 'framed_text': '?'}, // skipped
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{'level': 'L2', 'framed_text': tooLong}, // skipped
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{'level': 'L3', 'framed_text': ' '}, // skipped (empty after trim)
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{'level': 'L2', 'framed_text': '유효한 후보'},
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],
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});
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expect(r, hasLength(1));
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expect(r.first.framedText, '유효한 후보');
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});
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test('confidence clamps and falls back to 0.5', () {
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final r = parseFrameCandidates({
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'candidates': [
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{'level': 'L2', 'framed_text': 'a', 'confidence': -0.4},
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{'level': 'L2', 'framed_text': 'b', 'confidence': 2.5},
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{'level': 'L2', 'framed_text': 'c', 'confidence': 'not-a-number'},
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],
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});
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expect(r[0].confidence, 0.0);
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expect(r[1].confidence, 1.0);
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expect(r[2].confidence, 0.5);
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});
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test('keeps L0/L1 candidates (filtering is suggestFrame responsibility)', () {
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final r = parseFrameCandidates({
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'candidates': [
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{'level': 'L0', 'framed_text': '술 끊기'},
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{'level': 'L2', 'framed_text': '무알콜'},
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],
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});
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expect(r, hasLength(2));
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expect(r[0].level, FrameLevel.l0);
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});
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test('source_pattern_id preserved when present', () {
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final r = parseFrameCandidates({
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'candidates': [
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{
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'level': 'L2',
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'framed_text': 'foo',
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'source_pattern_id': 'fp_alcohol'
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},
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],
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});
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expect(r.single.sourcePatternId, 'fp_alcohol');
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});
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}
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165
app/test/domain/ai/suggest_frame_test.dart
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165
app/test/domain/ai/suggest_frame_test.dart
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@@ -0,0 +1,165 @@
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import 'package:flutter_test/flutter_test.dart';
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import 'package:life_helper/data/ai/llm_service.dart';
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import 'package:life_helper/domain/ai/frame_candidate.dart';
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import 'package:life_helper/domain/ai/suggest_frame.dart';
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import 'package:life_helper/domain/models/frame_pattern.dart';
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import 'package:life_helper/domain/models/habit.dart';
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final _patterns = <FramePatternModel>[
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const FramePatternModel(
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id: 'fp_alcohol',
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domain: 'drink',
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avoidanceKeyword: '술 끊기',
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l0Example: '술 끊기',
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l2Suggestion: '무알콜',
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l3Identity: '맑은 정신',
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),
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];
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const _input = SuggestFrameInput(
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rawText: '술 끊고 싶어',
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habitType: HabitType.breakHabit,
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);
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void main() {
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test('happy path: returns up to 3 validated candidates', () async {
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final llm = MockLlmService();
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await llm.load();
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llm.enqueueResponse({
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'candidates': [
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{'level': 'L2', 'framed_text': '저녁엔 무알콜 음료', 'confidence': 0.9},
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{'level': 'L3', 'framed_text': '나는 맑은 정신의 사람이다'},
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{'level': 'L2', 'framed_text': '주말엔 운동 우선'},
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],
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});
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final result = await suggestFrame(
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_input,
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, hasLength(3));
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expect(result[0].level, FrameLevel.l2);
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});
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test('L0/L1 candidates discarded by validateFrameLevel', () async {
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final llm = MockLlmService();
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await llm.load();
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llm.enqueueResponse({
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'candidates': [
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{'level': 'L0', 'framed_text': '술 안 마시기'},
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{'level': 'L1', 'framed_text': '음주 중단'},
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{'level': 'L2', 'framed_text': '무알콜 마시기'},
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],
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});
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final result = await suggestFrame(
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_input,
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, hasLength(1));
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expect(result.first.level, FrameLevel.l2);
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});
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test('timeout → empty list (graceful)', () async {
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final llm = MockLlmService();
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await llm.load();
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llm.responseDelay = const Duration(milliseconds: 200);
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llm.enqueueResponse({
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'candidates': [
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{'level': 'L2', 'framed_text': '무알콜'},
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],
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});
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final result = await suggestFrame(
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_input,
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llm: llm,
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framePatterns: _patterns,
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timeout: const Duration(milliseconds: 50),
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);
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expect(result, isEmpty);
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});
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test('StateError (not loaded) → empty list (graceful)', () async {
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final llm = MockLlmService(); // not loaded
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final result = await suggestFrame(
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_input,
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, isEmpty);
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});
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test('malformed JSON → empty list (graceful)', () async {
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final llm = MockLlmService();
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await llm.load();
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llm.enqueueResponse({'foo': 'bar'}); // no candidates key
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final result = await suggestFrame(
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_input,
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, isEmpty);
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});
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test('empty rawText → llm not called', () async {
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final llm = MockLlmService();
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await llm.load();
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final result = await suggestFrame(
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const SuggestFrameInput(
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rawText: ' ',
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habitType: HabitType.breakHabit,
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),
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, isEmpty);
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expect(llm.callCount, 0);
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});
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test('rawText > 200 chars → empty list, llm not called', () async {
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final llm = MockLlmService();
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await llm.load();
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final result = await suggestFrame(
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SuggestFrameInput(
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rawText: 'a' * 201,
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habitType: HabitType.breakHabit,
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),
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, isEmpty);
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expect(llm.callCount, 0);
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});
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test('graceful: arbitrary throw is caught', () async {
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final llm = MockLlmService();
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await llm.load();
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llm.enqueueError(Exception('boom'));
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final result = await suggestFrame(
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_input,
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, isEmpty);
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});
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test('result truncated at 3 even if more valid candidates returned',
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() async {
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final llm = MockLlmService();
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await llm.load();
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llm.enqueueResponse({
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'candidates': [
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{'level': 'L2', 'framed_text': 'a'},
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{'level': 'L2', 'framed_text': 'b'},
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{'level': 'L2', 'framed_text': 'c'},
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{'level': 'L2', 'framed_text': 'd'},
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{'level': 'L2', 'framed_text': 'e'},
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],
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});
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final result = await suggestFrame(
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_input,
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llm: llm,
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framePatterns: _patterns,
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);
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expect(result, hasLength(3));
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});
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}
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Block a user