joungmin
6ab4c0da7d
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
61 lines
1.6 KiB
Dart
61 lines
1.6 KiB
Dart
import '../models/habit.dart';
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import 'frame_candidate.dart';
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/// Parses function-calling JSON into FrameCandidate list. Throws
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/// [FormatException] on missing/invalid top-level shape; silently skips
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/// individual malformed items.
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List<FrameCandidate> parseFrameCandidates(Map<String, dynamic> json) {
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final raw = json['candidates'];
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if (raw == null) {
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throw const FormatException('candidates missing');
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}
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if (raw is! List) {
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throw const FormatException('candidates not array');
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}
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final result = <FrameCandidate>[];
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for (final item in raw) {
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if (item is! Map) continue;
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final map = item.map((k, v) => MapEntry(k.toString(), v));
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final levelStr = map['level'];
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if (levelStr is! String) continue;
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final level = _parseLevel(levelStr);
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if (level == null) continue;
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final framedText = map['framed_text'];
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if (framedText is! String) continue;
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final trimmed = framedText.trim();
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if (trimmed.isEmpty || trimmed.length > 120) continue;
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double confidence = 0.5;
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final c = map['confidence'];
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if (c is num) {
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confidence = c.toDouble().clamp(0.0, 1.0);
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}
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final src = map['source_pattern_id'];
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result.add(FrameCandidate(
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level: level,
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framedText: trimmed,
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confidence: confidence,
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sourcePatternId: src is String ? src : null,
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));
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}
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return result;
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}
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FrameLevel? _parseLevel(String s) {
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switch (s.toUpperCase()) {
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case 'L0':
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return FrameLevel.l0;
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case 'L1':
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return FrameLevel.l1;
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case 'L2':
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return FrameLevel.l2;
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case 'L3':
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return FrameLevel.l3;
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}
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return null;
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}
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