[03-Developer] #311 LLM warm-up + concurrent guard + quickCheck

ChatScreen 마운트 시 백그라운드 native init 으로 첫 send 시점에 native
load 지연을 안 보이게 한다. 12개 AC + UX-Reviewer 의 6개 권고 모두 코드
반영.

핵심 변경:
- `chat_warmup_provider.dart` — `ChatWarmupController` (Idle/Loading/Ready
  /Unavailable/Failed sealed state). fast path (`llm.isLoaded` → Ready),
  FileSystemException ↔ runtime kind 분기, _disposed race guard.
- `model_lifecycle.dart` — `quickCheck()`: 2.4GB SHA-256 hashing 없이
  meta_kv + 파일 존재만 보고 ready 추정 (R4 UX 권고).
- `gemma_llm_service.dart` + `llm_service.dart` — `_loadingFuture` 동시
  호출 가드. 두 caller 가 동시에 load() 해도 native init 은 1 회만.
- `chat_screen.dart` — initState postFrameCallback 에서 warmup.start().
  warmup 상태에 따라 hintText / spinner / 실패 banner 분기.

AC coverage (12개):
- AC1~AC8: ChatWarmupController unit (chat_warmup_test.dart 8 tests).
- AC9~AC12: UX-Reviewer 의 4개 권고 (입력 enabled / send auto-activate /
  fast path no-flicker / 명령형 메시지 금지) — controller 레벨에서 검증.

테스트: 167 passed (1 pre-existing skip). `flutter analyze` clean.

Refs #311

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

app/test/data/ai/model_lifecycle_test.dart

@@ -172,6 +172,66 @@ void main() {
     expect(await lc.checkAvailability(), ModelAvailability.downloading);
   });
 
+  test('quickCheck ready when meta_kv complete + file exists (no SHA)', () async {
+    const file = 'gemma_quick.bin';
+    final lc = ModelLifecycle(
+      meta: meta,
+      // 일부러 expectedSha 와 다르게 — quickCheck 는 SHA 비교 X.
+      config: ModelConfig(
+        url: Uri.parse(url),
+        expectedSha256: 'unused_by_quickcheck',
+        filename: file,
+      ),
+      storage: storage,
+    );
+    await meta.put(AiMetaKeys.optIn, 'true');
+    final path = '${tmp.path}/$file';
+    File(path).writeAsStringSync('payload');
+    await meta.put(AiMetaKeys.modelPath, path);
+    await meta.put(AiMetaKeys.modelSha, 'whatever');
+
+    expect(await lc.quickCheck(), ModelAvailability.ready);
+  });
+
+  test('quickCheck missing when modelPath not set', () async {
+    final lc = ModelLifecycle(
+      meta: meta,
+      config: ModelConfig(url: Uri.parse(url), expectedSha256: 'x'),
+      storage: storage,
+    );
+    await meta.put(AiMetaKeys.optIn, 'true');
+    expect(await lc.quickCheck(), ModelAvailability.missing);
+  });
+
+  test('quickCheck missing when file deleted from disk', () async {
+    const file = 'gemma_gone.bin';
+    final lc = ModelLifecycle(
+      meta: meta,
+      config: ModelConfig(
+        url: Uri.parse(url),
+        expectedSha256: 'x',
+        filename: file,
+      ),
+      storage: storage,
+    );
+    await meta.put(AiMetaKeys.optIn, 'true');
+    await meta.put(AiMetaKeys.modelPath, '${tmp.path}/$file');
+    await meta.put(AiMetaKeys.modelSha, 'sha');
+    // 파일 자체는 만들지 않음.
+    expect(await lc.quickCheck(), ModelAvailability.missing);
+  });
+
+  test('quickCheck downloading when state in progress', () async {
+    final lc = ModelLifecycle(
+      meta: meta,
+      config: ModelConfig(url: Uri.parse(url), expectedSha256: 'x'),
+      storage: storage,
+    );
+    await meta.put(AiMetaKeys.optIn, 'true');
+    await meta.put(AiMetaKeys.downloadState, 'downloading');
+    expect(await lc.quickCheck(), ModelAvailability.downloading);
+  });
+
   test('checkAvailability returns corrupt when file SHA mismatches', () async {
     const file = 'gemma_corrupt.bin';
     final lc = ModelLifecycle(