| 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, locks, custom-backend-integration, and debug-logging, plus the skills shipped by companion packages (@tanstack/ai-persistence, @tanstack/ai-code-mode). Use chat() not streamText(), openaiText() not createOpenAI(), toServerSentEventsResponse() not manual SSE, middleware hooks not onEnd callbacks.
|
| type | core |
| library | tanstack-ai |
| library_version | 0.42.0 |
TanStack AI — Core 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 |
| Survive a browser reload (no extra package) | ai-core/client-persistence/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 |
| Coordinate multi-instance work with locks | ai-core/locks/SKILL.md |
| Connect to a non-TanStack-AI backend | ai-core/custom-backend-integration/SKILL.md |
| Turn on/off debug logging, pipe into pino/winston | ai-core/debug-logging/SKILL.md |
| Persist chats server-side (history, runs) | See @tanstack/ai-persistence package skills |
| Set up Code Mode (LLM code execution) | See @tanstack/ai-code-mode package skills |
| Give the model a catalog of SKILL.md skills | See @tanstack/ai-skills package skills |
Companion packages
Some capabilities live in their own package and ship their own skills. Install
the package, then read its skills — do not guess the API from this file.
@tanstack/ai-persistence — durable chat state
Makes a conversation survive a reload, a server restart, a second device, or a
paused tool approval. It ships the store contracts (MessageStore,
RunStore, InterruptStore, MetadataStore), the withPersistence /
withGenerationPersistence middleware, reconstructChat for server-side
hydrate, an in-memory reference backend, and a conformance testkit. Multi-instance
locks are not in this package — LockStore / withLocks ship in
@tanstack/ai/locks; see ai-core/locks. The runs store contract is typed
against run lifecycle types (RunStatus, RunRecord, RunStore,
defineRunStore, InMemoryRunStore), which ship in @tanstack/ai itself;
see ai-core/middleware.
It does not ship a backend for your database — you implement the stores
against Postgres, SQLite, D1, Mongo, or whatever you run, and the package's
skills walk you through it (including Drizzle, Prisma, and Cloudflare recipes).
pnpm add @tanstack/ai-persistence
npx @tanstack/intent@latest install
The skills ship inside the package, so they only exist on disk once it is
installed — the second command re-scans node_modules and wires them into the
agent config. Until then the paths below resolve to nothing.
Entry point: node_modules/@tanstack/ai-persistence/skills/ai-persistence/SKILL.md
| Need to... | Read |
|---|
| Wire server-side chat history, runs, interrupts | ai-persistence/server/SKILL.md |
| Implement the store interfaces for your DB | ai-persistence/stores/SKILL.md |
| Write the adapter for the DB your app runs | ai-persistence/build-*-adapter/SKILL.md |
Browser-side persistence is not in this package — it ships with the
framework packages, so read ai-core/client-persistence instead.
@tanstack/ai-code-mode — LLM code execution
See the ai-code-mode skill in that package.
@tanstack/ai-skills — portable Agent Skills at runtime
Gives the model a library of SKILL.md skills it can load on demand, on any
provider, via the withSkills middleware and a load_skill tool. Skills come
from inlineSkill, skillDirectory, or a build-time bundle. This is the
runtime feature for the model inside your app, not the coding-assistant
skills this file is part of, and not the hosted codeExecutionTool /
shellTool skills (those run in a provider sandbox).
pnpm add @tanstack/ai-skills
npx @tanstack/intent@latest install
Entry point: node_modules/@tanstack/ai-skills/skills/ai-skills/SKILL.md
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
- Surviving reloads / multi-device / durable approvals? →
@tanstack/ai-persistence skills
- Connecting to a custom backend? → ai-core/custom-backend-integration
- Turning on debug logging to trace chunks/tools/middleware? → ai-core/debug-logging
- Debugging mistakes? → Check Common Mistakes in the relevant sub-skill
Critical Rules
- This is NOT the Vercel AI SDK. Use
chat() not streamText(). Use openaiText() not createOpenAI(). Import from @tanstack/ai, not ai.
- Import from framework package on client. Use
@tanstack/ai-react (or solid/vue/svelte/preact), not @tanstack/ai-client.
- Use
toServerSentEventsResponse() to convert streams to HTTP responses. Never implement SSE manually.
- Use middleware for lifecycle events. No
onEnd/onFinish callbacks on chat() — use middleware: [{ onFinish: ... }].
- Ask the user which adapter and model they want. Suggest the latest model. Also ask if they want Code Mode.
- Tools must be passed to both server and client. Server gets the tool in
chat({ tools }); the client passes the .client() implementation through the clientTools() helper into the tools option — useChat({ tools: clientTools(myTool.client(...)) }). There is no clientTools option. See ai-core/tool-calling.
Version
Targets TanStack AI v0.42.0.
