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Core TanStack AI library - Open source AI SDK

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--- name: ai-core description: > Entry point for TanStack AI skills. Routes to chat-experience, tool-calling, media-generation, structured-outputs, adapter-configuration, ag-ui-protocol, middleware, and custom-backend-integration. Use chat() not streamText(), openaiText() not createOpenAI(), toServerSentEventsResponse() not manual SSE, middleware hooks not onEnd callbacks. type: core library: tanstack-ai library_version: '0.10.0' --- # TanStack AICore Concepts TanStack AI is a type-safe, provider-agnostic AI SDK. Server-side functions live in `@tanstack/ai` and provider adapter packages. Client-side hooks live in framework packages (`@tanstack/ai-react`, `@tanstack/ai-solid`, etc.). Always import from the framework package on the client — never from `@tanstack/ai-client` directly (unless vanilla JS). ## Sub-Skills | Need to... | Read | | ------------------------------------------------- | ------------------------------------------- | | Build a chat UI with streaming | ai-core/chat-experience/SKILL.md | | Add tool calling (server, client, or both) | ai-core/tool-calling/SKILL.md | | Generate images, video, speech, or transcriptions | ai-core/media-generation/SKILL.md | | Get typed JSON responses from the LLM | ai-core/structured-outputs/SKILL.md | | Choose and configure a provider adapter | ai-core/adapter-configuration/SKILL.md | | Implement AG-UI streaming protocol server-side | ai-core/ag-ui-protocol/SKILL.md | | Add analytics, logging, or lifecycle hooks | ai-core/middleware/SKILL.md | | Connect to a non-TanStack-AI backend | ai-core/custom-backend-integration/SKILL.md | | Set up Code Mode (LLM code execution) | See `@tanstack/ai-code-mode` package skills | ## Quick Decision Tree - Setting up a chatbot? ai-core/chat-experience - Adding function calling? ai-core/tool-calling - Generating media (images, audio, video)? ai-core/media-generation - Need structured JSON output? ai-core/structured-outputs - Choosing/configuring a provider? → ai-core/adapter-configuration - Building a server-only AG-UI backend? ai-core/ag-ui-protocol - Adding analytics or post-stream events? ai-core/middleware - Connecting to a custom backend? ai-core/custom-backend-integration - Debugging mistakes? Check Common Mistakes in the relevant sub-skill ## Critical Rules 1. **This is NOT the Vercel AI SDK.** Use `chat()` not `streamText()`. Use `openaiText()` not `createOpenAI()`. Import from `@tanstack/ai`, not `ai`. 2. **Import from framework package on client.** Use `@tanstack/ai-react` (or solid/vue/svelte/preact), not `@tanstack/ai-client`. 3. **Use `toServerSentEventsResponse()`** to convert streams to HTTP responses. Never implement SSE manually. 4. **Use middleware for lifecycle events.** No `onEnd`/`onFinish` callbacks on `chat()` — use `middleware: [{ onFinish: ... }]`. 5. **Ask the user which adapter and model** they want. Suggest the latest model. Also ask if they want Code Mode. 6. **Tools must be passed to both server and client.** Server gets the tool in `chat({ tools })`, client gets the definition in `useChat({ clientTools })`. ## Version Targets TanStack AI v0.10.0.