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/providers/insight_provider.dart

@@ -3,71 +3,87 @@ import 'package:crypto/crypto.dart';
 import 'package:drift/drift.dart';
 import 'package:flutter_riverpod/flutter_riverpod.dart';
 import '../database/app_database.dart';
+import '../llm/prompt_builder.dart';
 import 'database_provider.dart';
+import 'llm_provider.dart';
 
 // ── Insight type enum ─────────────────────────────────────────────────────────
 
 enum InsightType { weekly, monthly, query }
 
-// ── Cached insight lookup ─────────────────────────────────────────────────────
-
-final cachedInsightProvider =
-    FutureProvider.autoDispose.family<LlmInsight?, String>((ref, promptHash) {
-  return ref.watch(insightDaoProvider).getCached(promptHash);
-});
-
-// ── Insight notifier — triggers generation and caches results ─────────────────
+// ── Insight notifier — fetches data, builds prompt, calls LLM, caches result ──
 
 class InsightNotifier extends Notifier<AsyncValue<String?>> {
   @override
   AsyncValue<String?> build() => const AsyncData(null);
 
-  String _hashPrompt(String prompt) =>
-      sha256.convert(utf8.encode(prompt)).toString();
-
   Future<void> generateInsight({
-    required String prompt,
-    required InsightType type,
-    DateTime? rangeStart,
-    DateTime? rangeEnd,
+    InsightType type = InsightType.weekly,
+    bool forceRefresh = false,
   }) async {
     state = const AsyncLoading();
 
-    final hash = _hashPrompt(prompt);
-    final dao = ref.read(insightDaoProvider);
+    try {
+      // Ensure model is initialised before generating
+      await ref.read(llmReadyProvider.future);
+      if (!ref.mounted) return;
 
-    final cached = await dao.getCached(hash);
-    if (!ref.mounted) return;
-    if (cached != null) {
-      state = AsyncData(cached.responseText);
-      return;
+      final now = DateTime.now();
+      final end = DateTime(now.year, now.month, now.day, 23, 59, 59);
+      final start = end.subtract(const Duration(days: 6));
+
+      final dao = ref.read(moodDaoProvider);
+      final entries = await dao.getEntriesWithActivitiesInRange(start, end);
+      if (!ref.mounted) return;
+
+      if (entries.length < 2) {
+        state = const AsyncData(null);
+        return;
+      }
+
+      final prompt = PromptBuilder.buildWeeklyPrompt(entries);
+      final hash = _hashPrompt(prompt);
+
+      if (!forceRefresh) {
+        final cached = await ref.read(insightDaoProvider).getCached(hash);
+        if (!ref.mounted) return;
+        if (cached != null) {
+          state = AsyncData(cached.responseText);
+          return;
+        }
+      }
+
+      final llm = ref.read(llmServiceProvider);
+      final buffer = StringBuffer();
+      await for (final token in llm.generateStream(prompt)) {
+        if (!ref.mounted) return;
+        buffer.write(token);
+        state = AsyncData(buffer.toString());
+      }
+
+      if (!ref.mounted) return;
+      final result = buffer.toString().trim();
+      await ref.read(insightDaoProvider).upsertInsight(
+            LlmInsightsCompanion.insert(
+              type: type.name,
+              promptHash: hash,
+              responseText: result,
+              rangeStart: Value(start),
+              rangeEnd: Value(end),
+            ),
+          );
+      if (!ref.mounted) return;
+      state = AsyncData(result);
+    } catch (e, st) {
+      if (!ref.mounted) return;
+      state = AsyncError(e, st);
     }
-
-    // Generation happens in LlmNotifier (see llm_provider.dart)
-    state = const AsyncData(null);
-  }
-
-  Future<void> saveInsight({
-    required String promptHash,
-    required String responseText,
-    required InsightType type,
-    DateTime? rangeStart,
-    DateTime? rangeEnd,
-  }) async {
-    await ref.read(insightDaoProvider).upsertInsight(
-          LlmInsightsCompanion.insert(
-            type: type.name,
-            promptHash: promptHash,
-            responseText: responseText,
-            rangeStart: Value(rangeStart),
-            rangeEnd: Value(rangeEnd),
-          ),
-        );
-    if (!ref.mounted) return;
-    state = AsyncData(responseText);
   }
 
   void clear() => state = const AsyncData(null);
+
+  static String _hashPrompt(String prompt) =>
+      sha256.convert(utf8.encode(prompt)).toString();
 }
 
 final insightNotifierProvider =