React

TanStack Query v5 is the server state library for React that handles caching, background refetching, and stale-while-revalidate out of the box — with 12M+ weekly downloads in 2026, it’s become the default choice for teams building AI-powered applications that need real-time data and LLM streaming. Why TanStack Query v5 Is the Default Choice for AI-Powered React Apps in 2026 TanStack Query v5 (formerly React Query) is a server state management library that handles all the complexity between your React components and your data sources — caching, deduplication, background synchronization, loading states, and error recovery — with minimal configuration. As of June 2026, the library ships at version 5.100.14, has 48K+ GitHub stars (overtaking SWR’s 32K in 2024), and sits at 12.3M weekly npm downloads — a 2.5x lead over SWR’s 4.9M. That adoption reflects a real shift: AI-powered React apps need capabilities beyond simple data fetching. LLM responses stream over seconds, not milliseconds. Dashboards pull from three or more data sources simultaneously. Users open the same AI tool across five browser tabs. TanStack Query v5’s new streamedQuery, broadcastQueryClient, and deep Suspense integration address these patterns directly, which is why teams building AI chatbots, real-time dashboards, and LLM-augmented features in 2026 are reaching for it first. ...

React Testing Library (RTL) remains the default choice for component tests in 2026, but testing components that call AI APIs — streaming chat, autocomplete, content generation — requires async patterns, mock strategies, and setup choices that standard RTL tutorials skip entirely. This guide covers the complete modern stack: Vitest + RTL + MSW + Vercel AI SDK test helpers, with concrete code you can paste into a real project. Why Testing AI-Powered React Components Is Different in 2026 AI-powered React components introduce three testing challenges that have no equivalent in a plain CRUD app: non-deterministic outputs, streaming responses that arrive in chunks over time, and expensive external API calls that you can never make in a test suite. React is used by 44.7% of all developers (Stack Overflow Survey 2025) and holds a 69.74% market share among JavaScript frameworks — which means millions of developers are now wiring AI APIs into React UIs for the first time and discovering that waitFor(() => expect(...)) alone is not enough. A chat component built on useChat from the Vercel AI SDK will fire a POST request, receive a Server-Sent Events (SSE) stream, and progressively update the DOM as tokens arrive. Standard synchronous render tests break immediately. The strategies that work are: deterministic mocks at the network layer via MSW, first-party mock providers from the AI SDK itself (MockLanguageModelV3, simulateReadableStream), and RTL’s async query helpers (findBy*, waitFor) used correctly. Without all three in place, tests either hit live APIs (slow, flaky, costly) or silently pass while the real network behavior goes untested. ...