feat: implement background LLM pattern analysis on Insights screen

Adds a prompt builder that serialises 7-day mood/activity data, wires
InsightNotifier to call the on-device LLM directly (no user interaction),
caches results by prompt hash, and renders the analysis as a passive card.
Includes loading, empty (<2 entries), and error states with a force-refresh button.

lib/core/database/daos/mood_dao.dart

@@ -84,6 +84,22 @@ class MoodDao extends DatabaseAccessor<AppDatabase> with _$MoodDaoMixin {
         .getSingleOrNull()) != null;
   }
 
+  // Entries with their linked activities — used by LLM prompt builder
+  Future<List<MoodEntryWithActivities>> getEntriesWithActivitiesInRange(
+      DateTime start, DateTime end) async {
+    final entries = await getEntriesInRange(start, end);
+    return Future.wait(entries.map((e) async {
+      final links = await (select(entryActivities)
+            ..where((t) => t.entryId.equals(e.id)))
+          .get();
+      final actIds = links.map((l) => l.activityId).toList();
+      final acts = actIds.isEmpty
+          ? <Activity>[]
+          : await (select(activities)..where((t) => t.id.isIn(actIds))).get();
+      return MoodEntryWithActivities(entry: e, activities: acts, tags: []);
+    }));
+  }
+
   // Average mood per day — used by calendar heatmap
   Future<Map<DateTime, double>> getDailyAverages(
       DateTime start, DateTime end) async {