feat(ai): implement agent-redesign plan with enhanced AI travel features

Phase 1 - Configuration Infrastructure (WS1):
- Add instance-level AI env vars (VOYAGE_AI_PROVIDER, VOYAGE_AI_MODEL, VOYAGE_AI_API_KEY)
- Implement fallback chain: user key → instance key → error
- Add UserAISettings model for per-user provider/model preferences
- Enhance provider catalog with instance_configured and user_configured flags
- Optimize provider catalog to avoid N+1 queries

Phase 1 - User Preference Learning (WS2):
- Add Travel Preferences tab to Settings page
- Improve preference formatting in system prompt with emoji headers
- Add multi-user preference aggregation for shared collections

Phase 2 - Day-Level Suggestions Modal (WS3):
- Create ItinerarySuggestionModal with 3-step flow (category → filters → results)
- Add AI suggestions button to itinerary Add dropdown
- Support restaurant, activity, event, and lodging categories
- Backend endpoint POST /api/chat/suggestions/day/ with context-aware prompts

Phase 3 - Collection-Level Chat Improvements (WS4):
- Inject collection context (destination, dates) into chat system prompt
- Add quick action buttons for common queries
- Add 'Add to itinerary' button on search_places results
- Update chat UI with travel-themed branding and improved tool result cards

Phase 3 - Web Search Capability (WS5):
- Add web_search agent tool using DuckDuckGo
- Support location_context parameter for biased results
- Handle rate limiting gracefully

Phase 4 - Extensibility Architecture (WS6):
- Implement decorator-based @agent_tool registry
- Convert existing tools to use decorators
- Add GET /api/chat/capabilities/ endpoint for tool discovery
- Refactor execute_tool() to use registry pattern

frontend/src/routes/settings/+page.server.ts

@@ -1,7 +1,7 @@
 import { fail, redirect, type Actions } from '@sveltejs/kit';
 import type { PageServerLoad } from '../$types';
 const PUBLIC_SERVER_URL = process.env['PUBLIC_SERVER_URL'];
-import type { ImmichIntegration, User } from '$lib/types';
+import type { ImmichIntegration, User, UserRecommendationPreferenceProfile } from '$lib/types';
 import { fetchCSRFToken } from '$lib/index.server';
 const endpoint = PUBLIC_SERVER_URL || 'http://localhost:8000';
 
@@ -95,11 +95,25 @@ export const load: PageServerLoad = async (event) => {
 
 	let apiKeys: UserAPIKey[] = [];
 	let apiKeysConfigError: string | null = null;
-	let apiKeysFetch = await fetch(`${endpoint}/api/integrations/api-keys/`, {
-		headers: {
-			Cookie: `sessionid=${sessionId}`
-		}
-	});
+	let [apiKeysFetch, recommendationPreferencesFetch] = await Promise.all([
+		fetch(`${endpoint}/api/integrations/api-keys/`, {
+			headers: {
+				Cookie: `sessionid=${sessionId}`
+			}
+		}),
+		fetch(`${endpoint}/api/integrations/recommendation-preferences/`, {
+			headers: {
+				Cookie: `sessionid=${sessionId}`
+			}
+		})
+	]);
+
+	let recommendationProfile: UserRecommendationPreferenceProfile | null = null;
+	if (recommendationPreferencesFetch.ok) {
+		const recommendationProfiles =
+			(await recommendationPreferencesFetch.json()) as UserRecommendationPreferenceProfile[];
+		recommendationProfile = recommendationProfiles[0] ?? null;
+	}
 
 	if (apiKeysFetch.ok) {
 		apiKeys = (await apiKeysFetch.json()) as UserAPIKey[];
@@ -131,6 +145,7 @@ export const load: PageServerLoad = async (event) => {
 			stravaUserEnabled,
 			apiKeys,
 			apiKeysConfigError,
+			recommendationProfile,
 			wandererEnabled,
 			wandererExpired
 		}