[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

app/test/domain/ai/suggest_frame_test.dart

@@ -0,0 +1,165 @@
+import 'package:flutter_test/flutter_test.dart';
+import 'package:life_helper/data/ai/llm_service.dart';
+import 'package:life_helper/domain/ai/frame_candidate.dart';
+import 'package:life_helper/domain/ai/suggest_frame.dart';
+import 'package:life_helper/domain/models/frame_pattern.dart';
+import 'package:life_helper/domain/models/habit.dart';
+
+final _patterns = <FramePatternModel>[
+  const FramePatternModel(
+    id: 'fp_alcohol',
+    domain: 'drink',
+    avoidanceKeyword: '술 끊기',
+    l0Example: '술 끊기',
+    l2Suggestion: '무알콜',
+    l3Identity: '맑은 정신',
+  ),
+];
+
+const _input = SuggestFrameInput(
+  rawText: '술 끊고 싶어',
+  habitType: HabitType.breakHabit,
+);
+
+void main() {
+  test('happy path: returns up to 3 validated candidates', () async {
+    final llm = MockLlmService();
+    await llm.load();
+    llm.enqueueResponse({
+      'candidates': [
+        {'level': 'L2', 'framed_text': '저녁엔 무알콜 음료', 'confidence': 0.9},
+        {'level': 'L3', 'framed_text': '나는 맑은 정신의 사람이다'},
+        {'level': 'L2', 'framed_text': '주말엔 운동 우선'},
+      ],
+    });
+    final result = await suggestFrame(
+      _input,
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, hasLength(3));
+    expect(result[0].level, FrameLevel.l2);
+  });
+
+  test('L0/L1 candidates discarded by validateFrameLevel', () async {
+    final llm = MockLlmService();
+    await llm.load();
+    llm.enqueueResponse({
+      'candidates': [
+        {'level': 'L0', 'framed_text': '술 안 마시기'},
+        {'level': 'L1', 'framed_text': '음주 중단'},
+        {'level': 'L2', 'framed_text': '무알콜 마시기'},
+      ],
+    });
+    final result = await suggestFrame(
+      _input,
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, hasLength(1));
+    expect(result.first.level, FrameLevel.l2);
+  });
+
+  test('timeout → empty list (graceful)', () async {
+    final llm = MockLlmService();
+    await llm.load();
+    llm.responseDelay = const Duration(milliseconds: 200);
+    llm.enqueueResponse({
+      'candidates': [
+        {'level': 'L2', 'framed_text': '무알콜'},
+      ],
+    });
+    final result = await suggestFrame(
+      _input,
+      llm: llm,
+      framePatterns: _patterns,
+      timeout: const Duration(milliseconds: 50),
+    );
+    expect(result, isEmpty);
+  });
+
+  test('StateError (not loaded) → empty list (graceful)', () async {
+    final llm = MockLlmService(); // not loaded
+    final result = await suggestFrame(
+      _input,
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, isEmpty);
+  });
+
+  test('malformed JSON → empty list (graceful)', () async {
+    final llm = MockLlmService();
+    await llm.load();
+    llm.enqueueResponse({'foo': 'bar'}); // no candidates key
+    final result = await suggestFrame(
+      _input,
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, isEmpty);
+  });
+
+  test('empty rawText → llm not called', () async {
+    final llm = MockLlmService();
+    await llm.load();
+    final result = await suggestFrame(
+      const SuggestFrameInput(
+        rawText: '   ',
+        habitType: HabitType.breakHabit,
+      ),
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, isEmpty);
+    expect(llm.callCount, 0);
+  });
+
+  test('rawText > 200 chars → empty list, llm not called', () async {
+    final llm = MockLlmService();
+    await llm.load();
+    final result = await suggestFrame(
+      SuggestFrameInput(
+        rawText: 'a' * 201,
+        habitType: HabitType.breakHabit,
+      ),
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, isEmpty);
+    expect(llm.callCount, 0);
+  });
+
+  test('graceful: arbitrary throw is caught', () async {
+    final llm = MockLlmService();
+    await llm.load();
+    llm.enqueueError(Exception('boom'));
+    final result = await suggestFrame(
+      _input,
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, isEmpty);
+  });
+
+  test('result truncated at 3 even if more valid candidates returned',
+      () async {
+    final llm = MockLlmService();
+    await llm.load();
+    llm.enqueueResponse({
+      'candidates': [
+        {'level': 'L2', 'framed_text': 'a'},
+        {'level': 'L2', 'framed_text': 'b'},
+        {'level': 'L2', 'framed_text': 'c'},
+        {'level': 'L2', 'framed_text': 'd'},
+        {'level': 'L2', 'framed_text': 'e'},
+      ],
+    });
+    final result = await suggestFrame(
+      _input,
+      llm: llm,
+      framePatterns: _patterns,
+    );
+    expect(result, hasLength(3));
+  });
+}