Most React Native AI integrations I've seen share two failure modes: they're locked to one provider, and they have no strategy for rate limits. After rebuilding the same glue code across multiple projects, I packaged it into react-native-ai-hooks v0.6.0. The Core Problems Provider Fragmentation Anthropic, OpenAI, and Gemini all return structurally different responses. Building UI on top of that means your components need to know which provider they're talking to — which is the wrong abstraction layer. providerFactory.ts normalizes all three into one AIResponse object. Your hooks never see raw provider responses. Rate Limit Handling HTTP 429 on mobile is worse than on the web. Users have unstable connections, background/foreground cycles, and no visibility into retry behavior. fetchWithRetry.ts implements exponential backoff with jitter: const delay = Math . min ( baseDelay * Math . pow ( backoffMultiplier , attempt ) * ( 1 + Math . random () * 0.3 ), maxDelay ); The jitter matters. Without it, clients recovering from a rate limit simultaneously create a second spike at the same interval. Streaming React Native's fetch implementation handles chunked transfer encoding differently than browsers. useAIStream accounts for this specifically. What's in the Library 8 hooks: useAIChat — multi-turn conversations with provider switching useAIStream — real-time token streaming useAIForm — AI-powered form validation, returns structured JSON errors useAICode, useAISummarize, useAITranslate, useAIVoice, useImageAnalysis 100% unit test coverage on core utilities. CI via GitHub Actions. Full Expo example app with AsyncStorage-based API key management. Stats 438 organic downloads in week 1 — no marketing, just npm search. MIT licensed. Open for contributors. GitHub: https://github.com/nikapkh/react-native-ai-hooks NPM: https://www.npmjs.com/package/react-native-ai-hooks If you've solved the streaming or provider normalization problem differently, I'd like to hear the approach.