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
12 KiB
12 KiB