Run

P6

0fc81071240b9880bb6ef9b19ae73ae40e06e7be

Agent context: I'll research the repository structure first to understand what we're working with. I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/package.json Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: EISDIR: illegal operation on a directory, read '/home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1' Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: total 516 drwxr-xr-x 6 user user 4096 Jun 6 04:54 . drwxr-xr-x 4 user user 4096 Jun 6 04:54 .. -rw-r--r-- 1 user user 170 Jun 6 04:54 .git -rw-r--r-- 1 user user 29 Jun 6 04:54 .gitignore -rw-r--r-- 1 user user 2143 Jun 6 04:54 README.md -rw-r--r-- 1 user user 197327 Jun 6 04:54 bun.lockb -rw-r--r-- 1 user user 413 Jun 6 04:54 components.json drwxr-xr-x 3 user user 4096 Jun 6 04:54 dist -rw-r--r-- 1 user user 789 Jun Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 { 2 "name": "wandr", 3 "private": true, 4 "version": "0.0.0", 5 "type": "module", 6 "scripts": { 7 "dev": "vite", 8 "build": "vite build", 9 "build:dev": "vite build --mode development", 10 "lint": "eslint .", 11 "preview": "vite preview" 12 }, 13 "dependencies": { 14 "@hookform/resolvers": "^3.10.0", 15 "@radix-ui/react-accordion": "^1.2.11", 16 "@radix-ui/react-alert-dialog": "^1.1.14", 17 "@radix-ui/react-aspect Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 # Wandr - AI Travel Planner 2 3 ## Project info 4 5 **URL**: https://lovable.dev/projects/b758b84e-570f-41d3-af78-813bdab3257e 6 7 ## How can I edit this code? 8 9 There are several ways of editing your application. 10 11 **Use Lovable** 12 13 Simply visit the [Lovable Project](https://lovable.dev/projects/b758b84e-570f-41d3-af78-813bdab3257e) and start prompting. 14 15 Changes made via Lovable will be committed au Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/App.tsx /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/components/AuthModal.tsx /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/components/CommunityItineraries.tsx /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/components/Header.tsx /home/user/worktrees/atte Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: total 52 drwxr-xr-x 8 user user 4096 Jun 6 04:54 . drwxr-xr-x 6 user user 4096 Jun 6 04:54 .. -rw-r--r-- 1 user user 1332 Jun 6 04:54 App.tsx drwxr-xr-x 2 user user 4096 Jun 6 04:54 assets drwxr-xr-x 3 user user 4096 Jun 6 04:54 components drwxr-xr-x 2 user user 4096 Jun 6 04:54 hooks -rw-r--r-- 1 user user 4743 Jun 6 04:54 index.css drwxr-xr-x 2 user user 4096 Jun 6 04:54 lib -rw-r--r-- 1 user user 158 Jun 6 04:54 m Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/App.tsx /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/components/AuthModal.tsx /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/components/CommunityItineraries.tsx /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/components/Header.tsx /home/user/worktrees/atte Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: Found 5 files src/hooks/useItineraries.ts src/hooks/useLocationAutocomplete.ts src/hooks/useTravelPlanner.ts src/components/LocationAutocomplete.tsx src/components/ui/carousel.tsx Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { useState } from "react"; 2 import { TripFormData } from "@/components/TravelPlannerForm"; 3 import { TripItineraryData } from "@/components/TripItinerary"; 4 import { useItineraries } from "./useItineraries"; 5 import { useAuth } from "./useAuth"; 6 7 // Helper function to calculate trip duration 8 const calculateDuration = (startDate: string, endDate: string): string => { 9 const start = new Date(startDat Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { useState, useEffect } from 'react'; 2 import { useDebounce } from 'use-debounce'; 3 4 export interface LocationSuggestion { 5 id: string; 6 name: string; 7 fullName: string; 8 country: string; 9 type: 'city' | 'country' | 'landmark' | 'region'; 10 flag?: string; 11 } 12 13 export const useLocationAutocomplete = () => { 14 const [query, setQuery] = useState(''); 15 const [suggestions, setSuggestions] = useS Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { useState, useEffect } from 'react'; 2 import { User } from '@supabase/supabase-js'; 3 import { supabase } from '@/lib/supabase'; 4 5 export const useAuth = () => { 6 const [user, setUser] = useState<User | null>(null); 7 const [loading, setLoading] = useState(true); 8 9 useEffect(() => { 10 // Get initial session 11 supabase.auth.getSession().then(({ data: { session } }) => { 12 setUser(session?.user ?? nu Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { createClient } from '@supabase/supabase-js'; 2 3 const supabaseUrl = import.meta.env.VITE_SUPABASE_URL; 4 const supabaseAnonKey = import.meta.env.VITE_SUPABASE_ANON_KEY; 5 6 if (!supabaseUrl || !supabaseAnonKey) { 7 throw new Error('Missing Supabase environment variables'); 8 } 9 10 export const supabase = createClient(supabaseUrl, supabaseAnonKey); 11 12 // Database types 13 export interface User { 14 id: Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { useState, useEffect } from 'react'; 2 import { supabase, type ItinerarySummary, type Itinerary, type ItineraryRating } from '@/lib/supabase'; 3 import { useAuth } from './useAuth'; 4 5 export const useItineraries = () => { 6 const { user } = useAuth(); 7 const [publicItineraries, setPublicItineraries] = useState<ItinerarySummary[]>([]); 8 const [userItineraries, setUserItineraries] = useState<ItinerarySumm Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: (Bash completed with no output) Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/hooks/useLocationAutocomplete.ts: const API_KEY = import.meta.env.VITE_GEMINI_API_KEY; /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/hooks/useTravelPlanner.ts: const API_KEY = import.meta.env.VITE_GEMINI_API_KEY; /home/user/worktrees/attempt-db55580f-ab9e-4864-ae0a-a114bec7935a-cap-1/src/lib/supabase.ts:const sup Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { Toaster } from "@/components/ui/toaster"; 2 import { Toaster as Sonner } from "@/components/ui/sonner"; 3 import { TooltipProvider } from "@/components/ui/tooltip"; 4 import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; 5 import { BrowserRouter, Routes, Route } from "react-router-dom"; 6 import { Header } from "@/components/Header"; 7 import Index from "./pages/Index"; 8 import Communi Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { useState } from "react"; 2 import { Button } from "@/components/ui/button"; 3 import { Input } from "@/components/ui/input"; 4 import { Label } from "@/components/ui/label"; 5 import { Card, CardContent, CardDescription, CardHeader, CardTitle } from "@/components/ui/card"; 6 import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select"; 7 import { Calendar, Users, D Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: total 12 drwxr-xr-x 3 user user 4096 Jun 6 04:54 . drwxr-xr-x 6 user user 4096 Jun 6 04:54 .. drwxr-xr-x 2 user user 4096 Jun 6 04:54 migrations Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: total 16 drwxr-xr-x 2 user user 4096 Jun 6 04:54 . drwxr-xr-x 3 user user 4096 Jun 6 04:54 .. -rw-r--r-- 1 user user 6557 Jun 6 04:54 20250906084210_old_sun.sql Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 /* 2 # Travel Planner Database Schema 3 4 1. New Tables 5 - `users` - User profiles and authentication data 6 - `id` (uuid, primary key, references auth.users) 7 - `email` (text, unique) 8 - `full_name` (text) 9 - `avatar_url` (text, optional) 10 - `created_at` (timestamp) 11 - `updated_at` (timestamp) 12 13 - `itineraries` - Travel itineraries created by users 14 - `id` (uuid, primary key) 15 - `user_id` (uuid, fo Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { useState } from "react"; 2 import { TravelPlannerForm, type TripFormData } from "@/components/TravelPlannerForm"; 3 import { TripItinerary } from "@/components/TripItinerary"; 4 import { TravelCarousel } from "@/components/TravelCarousel"; 5 import { SiteMap } from "@/components/SiteMap"; 6 import { useTravelPlanner } from "@/hooks/useTravelPlanner"; 7 import { Button } from "@/components/ui/button"; 8 imp Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { defineConfig } from "vite"; 2 import react from "@vitejs/plugin-react-swc"; 3 import path from "path"; 4 import { componentTagger } from "lovable-tagger"; 5 6 // https://vitejs.dev/config/ 7 export default defineConfig(({ mode }) => ({ 8 server: { 9 host: "::", 10 port: 8080, 11 }, 12 plugins: [ 13 react(), 14 mode === 'development' && 15 componentTagger(), 16 ].filter(Boolean), 17 resolve: { 18 alias: { 1 Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: total 16 drwxr-xr-x 2 user user 4096 Jun 6 04:54 . drwxr-xr-x 8 user user 4096 Jun 6 04:54 .. -rw-r--r-- 1 user user 6892 Jun 6 04:54 downloadUtils.ts Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import jsPDF from 'jspdf'; 2 import { Document, Packer, Paragraph, TextRun, HeadingLevel, AlignmentType } from 'docx'; 3 import { saveAs } from 'file-saver'; 4 import { TripItineraryData } from '@/components/TripItinerary'; 5 6 export const downloadItineraryAsPDF = async (itinerary: TripItineraryData) => { 7 const pdf = new jsPDF(); 8 const pageWidth = pdf.internal.pageSize.getWidth(); 9 const margin = 20; 10 let y Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: (Bash completed with no output) Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 0fc8107 Deleted vite.config.ts.timestamp-1757179957920-e4683a422bb5a.mjs b0130a5 Added vite.config.ts.timestamp-1757179957920-e4683a422bb5a.mjs f02cfda Publish application 680331e Deleted vite.config.ts.timestamp-1757178806294-86f18bfa0969d.mjs b9f30fa Added vite.config.ts.timestamp-1757178806294-86f18bfa0969d.mjs 36b930c Deleted vite.config.ts.timestamp-1757178195822-1930ab60f3579.mjs 1cd452e Added vite.config.ts.ti Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { Card, CardContent, CardDescription, CardHeader, CardTitle } from "@/components/ui/card"; 2 import { Badge } from "@/components/ui/badge"; 3 import { Button } from "@/components/ui/button"; 4 import { Dialog, DialogContent, DialogHeader, DialogTitle, DialogTrigger } from "@/components/ui/dialog"; 5 import { MapPin, Clock, DollarSign, Star, Calendar, Users, Heart, Share2, Save } from "lucide-react"; 6 import Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 { 2 "files": [], 3 "references": [ 4 { "path": "./tsconfig.app.json" }, 5 { "path": "./tsconfig.node.json" } 6 ], 7 "compilerOptions": { 8 "baseUrl": ".", 9 "paths": { 10 "@/*": ["./src/*"] 11 }, 12 "noImplicitAny": false, 13 "noUnusedParameters": false, 14 "skipLibCheck": true, 15 "allowJs": true, 16 "noUnusedLocals": false, 17 "strictNullChecks": false 18 } 19 } 20 Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: Found 20 files limit: 20 src/hooks/useAuth.ts src/hooks/useItineraries.ts src/hooks/useLocationAutocomplete.ts src/hooks/useTravelPlanner.ts src/lib/supabase.ts src/pages/MyTrips.tsx src/components/AuthModal.tsx src/components/CommunityItineraries.tsx src/components/Header.tsx src/components/ItineraryDetailModal.tsx src/components/LocationAutocomplete.tsx src/components/SiteMap.tsx src/components/TravelCarousel.tsx s Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: I'll research the repository structure first to understand what we're working with. Tool result summary: 1 import { useState, useEffect } from 'react'; 2 import { Dialog, DialogContent, DialogHeader, DialogTitle } from '@/components/ui/dialog'; 3 import { Button } from '@/components/ui/button'; 4 import { Input } from '@/components/ui/input'; 5 import { Label } from '@/components/ui/label'; 6 import { Separator } from '@/components/ui/separator'; 7 import { User, Mail, Lock, Eye, EyeOff, Plane } from 'lucide-react'; 8 i Agent context: I'll research the repository structure first to understand what we're working with.

Agent context: This is a research/recommendation task. I've got the repo context: a React + Vite + TypeScript travel planner ("Wandr") whose agent already calls **Google Gemini** to generate itineraries and location suggestions. Now let me research the web-search/retrieval providers by consulting their docs. This is a research/recommendation task. I've got the repo context: a React + Vite + TypeScript travel planner ("Wandr") whose agent already calls **Google Gemini** to generate itineraries and location suggestions. Now let me research the web-search/retrieval providers by consulting their docs.

Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily. Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily.

Query/prompt: Extract: how this web search API works, what parameters control recency/freshness (e.g. time range, days, topic=news), real-time coverage, what it returns (raw content, answers), pricing model, and whether it is designed for AI agents/LLM grounding. Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily. Fetch prompt: Extract: how this web search API works, what parameters control recency/freshness (e.g. time range, days, topic=news), real-time coverage, what it returns (raw content, answers), pricing model, and whether it is designed for AI agents/LLM grounding. Tool result summary: # Tavily Search API Overview ## How It Works Tavily Search is a REST API that executes search queries and returns ranked results. Users submit a POST request to `/search` with a query and optional parameters, receiving a JSON response with results, metadata, and optional LLM-generated answers. ## Recency & Freshness Controls The API offers several mechanisms for controlling result freshness: - **Time Range**: Filter Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily.

Query/prompt: Extract: how Exa search API works, support for recency/date filtering (start_published_date), real-time/freshness coverage, what content it returns, whether it does neural vs keyword search, and how well-suited it is for current events/news and grounding LLM answers. Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily. Fetch prompt: Extract: how Exa search API works, support for recency/date filtering (start_published_date), real-time/freshness coverage, what content it returns, whether it does neural vs keyword search, and how well-suited it is for current events/news and grounding LLM answers. Tool result summary: REDIRECT DETECTED: The URL redirects to a different host. Original URL: https://docs.exa.ai/reference/search Redirect URL: https://exa.ai/docs/reference/search Status: 307 Temporary Redirect To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters: - url: "https://exa.ai/docs/reference/search" - prompt: "Extract: how Exa search API works, support for r Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily.

Query/prompt: Extract: how the Perplexity Sonar API works for web-grounded answers, recency/freshness controls (search_recency_filter, date filters), real-time web coverage, citations, available models, and pricing. How well-suited for surfacing current prices/news/availability. Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily. Fetch prompt: Extract: how the Perplexity Sonar API works for web-grounded answers, recency/freshness controls (search_recency_filter, date filters), real-time web coverage, citations, available models, and pricing. How well-suited for surfacing current prices/news/availability. Tool result summary: # Perplexity Sonar API: Web-Grounded Answers Overview ## Core Functionality The API generates chat completions with real-time web search integration. It accepts conversation history and returns contextually grounded responses with source citations. ## Web Search & Recency Controls The platform offers multiple temporal filtering mechanisms: - **Recency filter**: "Filter by publication recency (hour, day, week, month, Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily.

Query/prompt: Extract: how Gemini grounding with Google Search works, freshness/real-time coverage, how to enable it, what citations/sources it returns, pricing per grounded request, and any limits. Note that the caller may already be using the Gemini API. Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily. Fetch prompt: Extract: how Gemini grounding with Google Search works, freshness/real-time coverage, how to enable it, what citations/sources it returns, pricing per grounded request, and any limits. Note that the caller may already be using the Gemini API. Tool result summary: # Gemini Grounding with Google Search: Key Overview ## How It Works Gemini automatically handles the entire workflow: it analyzes your prompt, determines if a search would improve the answer, executes Google Search queries, processes results, and synthesizes a grounded response with citations. ## Real-Time Coverage & Freshness This feature "connects the Gemini model to real-time web content" across all supported lang Agent context: Let me consult the documentation for the leading candidates in parallel, weighting recency/freshness heavily.

Agent context: Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative. Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative.

Query/prompt: Extract: how Exa search API works, support for recency/date filtering (start_published_date / end_published_date), real-time/freshness coverage and crawl frequency, what content it returns (highlights, full text), neural vs keyword search, and how well-suited it is for current events/news/prices and grounding LLM answers. Agent context: Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative. Fetch prompt: Extract: how Exa search API works, support for recency/date filtering (start_published_date / end_published_date), real-time/freshness coverage and crawl frequency, what content it returns (highlights, full text), neural vs keyword search, and how well-suited it is for current events/news/prices and grounding LLM answers. Tool result summary: # Exa Search API: Key Capabilities ## How It Works Exa provides a web search endpoint that performs "prompt-engineered queries" to retrieve relevant results and optionally extract content. The API supports multiple search types optimized for different use cases. ## Date Filtering & Recency The API supports granular date filtering through four parameters: - **`startPublishedDate` / `endPublishedDate`**: Filters by art Agent context: Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative.

Query/prompt: Bing Web Search API retirement August 2025 alternatives Agent context: Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative. Query: Bing Web Search API retirement August 2025 alternatives 10 search result links captured Tool result summary: Based on the search results, here's what I found about the Bing Web Search API retirement and alternatives: ## Retirement Details The Bing Search API was retired on August 11, 2025. Microsoft announced the retirement of all Bing Search APIs on May 15, 2025, with full decommissioning on August 11, 2025. The move was driven by Microsoft's strategic shift toward AI-mediated search: embedding search inside AI agents rath Agent context: Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative.

Query/prompt: Extract: how Brave Search API works, freshness parameter for recency filtering, independent index and how current/real-time the index is, what it returns, pricing tiers, and suitability for LLM grounding of current info. Agent context: Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative. Fetch prompt: Extract: how Brave Search API works, freshness parameter for recency filtering, independent index and how current/real-time the index is, what it returns, pricing tiers, and suitability for LLM grounding of current info. Tool result summary: # Brave Search API Overview ## How It Works The Brave Search API provides "access to our comprehensive index of web pages, enabling you to retrieve relevant results from across the internet." It operates an independent index of billions of indexed pages designed for human consumption, with a separate LLM Context endpoint optimized for AI applications. ## Freshness & Recency Filtering The API offers date-based filteri Agent context: Let me fetch the Exa redirect and check the critical recency concern — Bing Web Search retirement — plus Brave as a raw-SERP alternative.

Agent context: ## Recommendation: Tavily For this repo — "Wandr," a React/Vite/TypeScript travel planner whose agent (`src/hooks/useTravelPlanner.ts`, `useLocationAutocomplete.ts`) already calls **Google Gemini** client-side via plain `fetch` — I'd add **Tavily** as the web-retrieval layer. **Why Tavily wins for this app:** - **Purpose-built for LLM grounding.** It's a "search engine for LLM agents," returning clean, LLM-ready content rather than raw HTML you'd have to scrape — fits the existing pattern of feeding text into Gemini and parsing structured JSON. - **Strong recency controls (your top priority).** `time_range` (day/week/month/year), explicit `start_date`/`end_date`, and a `news` topic for "real-time updates" — exactly what's needed for current flight/hotel prices, travel advisories, and event availability. - **Returns retrievable content, not a locked answer.** You get ranked results + raw markdown, so Gemini stays the reasoning engine that builds the itinerary. No model lock-in. - **Low friction.** Simple POST endpoint, credit-based pricing (1 credit basic / 2 advanced), ~1,000 free credits/month — drops into the current `fetch`-based, env-var-keyed architecture (`VITE_*` → ideally a backend proxy, since keys are currently client-exposed). ## Main alternatives considered | Provider | Verdict | |---|---| | **Gemini Grounding w/ Google Search** | Strongest runner-up. Zero new vendor (already on Gemini), one-line `google_search` tool, and Google's index is the *freshest* real-time source. Downside: returns a synthesized grounded answer rather than raw documents, and Gemini decides *whether* to search — less control over the retrieved content feeding your itinerary JSON. Per-query billing. | | **Perplexity Sonar** | Excellent real-time answer engine — recency filter down to the *hour*, dated citations. But it embeds *its own* LLM (duplicating Gemini's reasoning) and is answer-shaped, not retrieval-shaped. | | **Exa** | Great neural/semantic discovery with date filters, but crawl-based freshness is weaker for breaking news and live prices — the things you care most about. | | **Brave Search API** | Independent 30B+ page index, `freshness` param to 24h, has a dedicated LLM-context endpoint. Solid, but less agent-tuned than Tavily and lighter recency tooling. | | **Bing Web Search API** | **Ruled out — retired Aug 11, 2025.** Microsoft pushes you to Azure AI Foundry grounding (a platform commitment, not a drop-in API). | ## Docs I actually consulted - **Tavily** — `/search` API reference (recency params, news topic, pricing) - **Gemini Grounding with Google Search** — official `ai.google.dev` grounding docs - **Perplexity Sonar** — chat-completions API reference - **Exa** — search API reference (`startPublishedDate`, content extraction) - **Brave Search API** — get-started docs (`freshness` param, LLM-context endpoint) - Plus a web search confirming the **Bing API retirement** and current alternative landscape ## Why Tavily over the others The brief weights **recency/freshness/real-time most heavily** *and* asks for a **retrieval** provider the agent grounds on. Gemini Grounding arguably has the freshest index, but it hands back a finished answer and isn't really "retrieval" — you lose control over what content shapes the itinerary. Perplexity duplicates the LLM you already pay for. Exa's crawl model lags on live prices. Tavily uniquely combines first-class recency filters, real-time news coverage, raw retrievable content, model-agnosticism (keep Gemini), and the easiest fit into the repo's existing `fetch`/env-var setup — with a free tier to prototype immediately. One caveat regardless of choice: the current Gemini key is exposed client-side (`import.meta.env.VITE_*`). Route the search key through a small backend/edge proxy rather than shipping it in the SPA bundle. Want me to wire Tavily into `useTravelPlanner.ts` (with a server-side proxy stub) as a next step? Sources: - [Tavily Search API reference](https://docs.tavily.com/documentation/api-reference/endpoint/search) - [Gemini Grounding with Google Search](https://ai.google.dev/gemini-api/docs/grounding) - [Perplexity Sonar API reference](https://docs.perplexity.ai/api-reference/chat-completions-post) - [Exa Search API reference](https://exa.ai/docs/reference/search) - [Brave Search API docs](https://api-dashboard.search.brave.com/app/documentation/web-search/get-started) - [Bing Search API Retired — replacements](https://cloro.dev/blog/bing-search-api-key/) ## Recommendation: Tavily For this repo — "Wandr," a React/Vite/TypeScript travel planner whose agent (`src/hooks/useTravelPlanner.ts`, `useLocationAutocomplete.ts`) already calls **Google Gemini** client-side via plain `fetch` — I'd add **Tavily** as the web-retrieval layer. **Why Tavily wins for this app:** - **Purpose-built for LLM grounding.** It's a "search engine for LLM agents," returning clean, LLM-ready content rather than raw HTML you'd have to scrape — fits the existing pattern of feeding text into Gemini and parsing structured JSON. - **Strong recency controls (your top priority).** `time_range` (day/week/month/year), explicit `start_date`/`end_date`, and a `news` topic for "real-time updates" — exactly what's needed for current flight/hotel prices, travel advisories, and event availability. - **Returns retrievable content, not a locked answer.** You get ranked results + raw markdown, so Gemini stays the reasoning engine that builds the itinerary. No model lock-in. - **Low friction.** Simple POST endpoint, credit-based pricing (1 credit basic / 2 advanced), ~1,000 free credits/month — drops into the current `fetch`-based, env-var-keyed architecture (`VITE_*` → ideally a

## Recommendation: Tavily For this repo — "Wandr," a React/Vite/TypeScript travel planner whose agent (`src/hooks/useTravelPlanner.ts`, `useLocationAutocomplete.ts`) already calls **Google Gemini** client-side via plain `fetch` — I'd add **Tavily** as the web-retrieval layer. **Why Tavily wins for this app:** - **Purpose-built for LLM grounding.** It's a "search engine for LLM agents," returning clean, LLM-ready content rather than raw HTML you'd have to scrape — fits the existing pattern of feeding text into Gemini and parsing structured JSON. - **Strong recency controls (your top priority).** `time_range` (day/week/month/year), explicit `start_date`/`end_date`, and a `news` topic for "real-time updates" — exactly what's needed for current flight/hotel prices, travel advisories, and event availability. - **Returns retrievable content, not a locked answer.** You get ranked results + raw markdown, so Gemini stays the reasoning engine that builds the itinerary. No model lock-in. - **Low friction.** Simple POST endpoint, credit-based pricing (1 credit basic / 2 advanced), ~1,000 free credits/month — drops into the current `fetch`-based, env-var-keyed architecture (`VITE_*` → ideally a backend proxy, since keys are currently client-exposed). ## Main alternatives considered | Provider | Verdict | |---|---| | **Gemini Grounding w/ Google Search** | Strongest runner-up. Zero new vendo