[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-tanstack-ai-coremiddleware":3,"mdc--4ja2xc-key":53,"related-repo-tanstack-ai-coremiddleware":11603,"related-org-tanstack-ai-coremiddleware":11704},{"slug":4,"name":5,"fn":6,"description":7,"org":8,"tags":12,"stars":24,"repoUrl":25,"updatedAt":26,"license":27,"forks":28,"topics":29,"repo":48,"sourceUrl":51,"mdContent":52},"ai-coremiddleware","ai-core\u002Fmiddleware","configure chat lifecycle middleware","Chat lifecycle middleware hooks: onConfig, onStart, onChunk, onBeforeToolCall, onAfterToolCall, onUsage, onFinish, onAbort, onError. Use for analytics, event firing, tool caching (toolCacheMiddleware), logging, and tracing. Middleware array in chat() config, left-to-right execution order. NOT onEnd\u002FonFinish callbacks on chat() — use middleware.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},"tanstack","TanStack","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Ftanstack.png",[13,17,20,23],{"name":14,"slug":15,"type":16},"Observability","observability","tag",{"name":18,"slug":19,"type":16},"AI SDK","ai-sdk",{"name":21,"slug":22,"type":16},"Middleware","middleware",{"name":10,"slug":9,"type":16},2884,"https:\u002F\u002Fgithub.com\u002FTanStack\u002Fai","2026-07-30T05:26:09.402989",null,269,[30,31,19,32,33,34,35,36,37,38,39,40,41,42,43,9,44,45,46,47],"ai","ai-agents","anthropic","chatbot","function-calling","gemini","generative-ai","llm","multimodal","openai","react","solidjs","streaming","svelte","tool-calling","typescript","typescript-sdk","vue",{"repoUrl":25,"stars":24,"forks":28,"topics":49,"description":50},[30,31,19,32,33,34,35,36,37,38,39,40,41,42,43,9,44,45,46,47],"🤖 Type-safe, provider-agnostic TypeScript AI SDK for streaming chat, tool calling, agents, and multimodal apps across OpenAI, Anthropic, Gemini, React, Vue, Svelte, and Solid.","https:\u002F\u002Fgithub.com\u002FTanStack\u002Fai\u002Ftree\u002FHEAD\u002Fpackages\u002Fai\u002Fskills\u002Fai-core\u002Fmiddleware","---\nname: ai-core\u002Fmiddleware\ndescription: >\n Chat lifecycle middleware hooks: onConfig, onStart, onChunk,\n onBeforeToolCall, onAfterToolCall, onUsage, onFinish, onAbort, onError.\n Use for analytics, event firing, tool caching (toolCacheMiddleware),\n logging, and tracing. Middleware array in chat() config, left-to-right\n execution order. NOT onEnd\u002FonFinish callbacks on chat() — use middleware.\ntype: sub-skill\nlibrary: tanstack-ai\nlibrary_version: '0.10.0'\nsources:\n - 'TanStack\u002Fai:docs\u002Fadvanced\u002Fmiddleware.md'\n - 'TanStack\u002Fai:docs\u002Fsandbox\u002Fobservability.md'\n - 'TanStack\u002Fai:docs\u002Fpersistence\u002Foverview.md'\n---\n\n# Middleware\n\n> **Dependency note:** This skill builds on ai-core. Read it first for critical rules.\n\n## Setup — Analytics Tracking Middleware\n\n```typescript\nimport { chat, toServerSentEventsResponse } from '@tanstack\u002Fai'\nimport { openaiText } from '@tanstack\u002Fai-openai'\n\nconst stream = chat({\n adapter: openaiText('gpt-5.2'),\n messages,\n middleware: [\n {\n onStart: (ctx) => {\n console.log('Chat started:', ctx.model)\n },\n onFinish: (ctx, info) => {\n trackAnalytics({ model: ctx.model, tokens: info.usage?.totalTokens })\n },\n onError: (ctx, info) => {\n reportError(info.error)\n },\n },\n ],\n})\n\nreturn toServerSentEventsResponse(stream)\n```\n\n## Hooks Reference\n\nEvery hook receives a `ChatMiddlewareContext` as its first argument, which provides\n`requestId`, `streamId`, `phase`, `iteration`, `chunkIndex`, `model`, `provider`,\n`signal`, `abort()`, `defer()`, and more.\n\n| Hook | When | Second Argument |\n| -------------------------- | -------------------------------------------------------------------------------------------------- | --------------------------------------------------- |\n| `onConfig` | Once at startup (`init`) + once per iteration (`beforeModel`) + once at structured-output boundary | `ChatMiddlewareConfig` (return partial to merge) |\n| `onStructuredOutputConfig` | Once at the structured-output boundary (only when `chat({ outputSchema })`) | `StructuredOutputMiddlewareConfig` (return partial) |\n| `onStart` | Once after initial `onConfig` | none |\n| `onIteration` | Start of each agent loop iteration | `IterationInfo` |\n| `onShouldContinue` | Whether to start another agent-loop iteration (AND with strategy; `false` stops) | `AgentLoopState` |\n| `onChunk` | Every streamed chunk | `StreamChunk` (return void\u002Fchunk\u002Fchunk[]\u002Fnull) |\n| `onBeforeToolCall` | Before each tool executes | `ToolCallHookContext` (return decision or void) |\n| `onAfterToolCall` | After each tool executes | `AfterToolCallInfo` |\n| `onToolPhaseComplete` | After all tool calls in an iteration | `ToolPhaseCompleteInfo` |\n| `onUsage` | When `RUN_FINISHED` includes usage data | `UsageInfo` |\n| `onFinish` | Run completed normally | `FinishInfo` |\n| `onAbort` | Run was aborted | `AbortInfo` |\n| `onError` | Unhandled error occurred | `ErrorInfo` |\n\nTerminal hooks (`onFinish`, `onAbort`, `onError`) are **mutually exclusive** -- exactly\none fires per `chat()` invocation.\n\n> **Sampling in `onConfig`:** `temperature`, `topP`, and `maxTokens` are **not**\n> first-class fields on `ChatMiddlewareConfig`. To adjust sampling from\n> middleware, return a partial that mutates `config.modelOptions` using the\n> provider's native key (e.g. OpenAI `temperature` \u002F `max_output_tokens`,\n> Anthropic `max_tokens`, Ollama nested `options.num_predict`). Returning a\n> top-level `temperature`\u002F`maxTokens` has no effect.\n\n### Phase values\n\n`ctx.phase` is one of:\n\n| Phase | When |\n| -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `'init'` | Initial setup (before the first `onConfig` snapshot is built). |\n| `'beforeModel'` | Right before each agent-loop adapter call (`onConfig` re-fires here). |\n| `'modelStream'` | During model streaming chunks within the agent loop. |\n| `'beforeTools'` | Before tool execution phase. |\n| `'afterTools'` | After tool execution phase. |\n| `'structuredOutput'` | During the final structured-output adapter call (set for all chunks from `adapter.structuredOutputStream` or the synthesized fallback). Triggered only when `chat({ outputSchema })` is invoked; one phase transition per `chat()` invocation. |\n\n**Structured-output lifecycle rules** (when `chat({ outputSchema })` is used):\n\n- `onStructuredOutputConfig` fires **before** `onConfig` at the structured-output boundary.\n- `onConfig` re-fires at the same boundary with `ctx.phase === 'structuredOutput'`, receiving the post-`onStructuredOutputConfig` view of the config (minus `outputSchema`).\n- `onChunk` and `onUsage` fire for every chunk and usage event emitted by the structured-output call, with `ctx.phase === 'structuredOutput'`.\n- `onIteration` does **not** fire for finalization — it is agent-loop-only.\n- `onFinish` fires once at the end of the whole `chat()` invocation, **after** the structured-output finalization completes (not after the agent loop). Terminal-hook exclusivity still holds (one of `onFinish` \u002F `onAbort` \u002F `onError`).\n- **Terminal `info` and structured-output:** `info.usage` \u002F `info.finishReason` \u002F `info.content` reflect the **agent loop's** terminal state, NOT the finalization step. Finalization state is intentionally segregated to keep agent-loop semantics clean. For a tools-less `chat({ outputSchema })` run, `info.usage` is `undefined` and `info.finishReason` is `null` (no agent-loop iteration produced `RUN_FINISHED`). To capture finalization tokens, use `onUsage` — it fires for both agent-loop iterations and the final call. For the structured-output result itself, observe the `structured-output.complete` CUSTOM event in `onChunk`.\n\n## onStructuredOutputConfig\n\nA dedicated config hook that fires **only** at the structured-output boundary\n(when `chat({ outputSchema })` is invoked). Use it to transform the JSON Schema\nsent to the provider (inject `$defs`, strip vendor-incompatible keywords) or to\napply structured-output-specific config changes that should not affect the\nagent-loop adapter calls.\n\n**Signature:**\n\n```ts\nonStructuredOutputConfig?: (\n ctx: ChatMiddlewareContext,\n config: StructuredOutputMiddlewareConfig,\n) =>\n | void\n | null\n | Partial\u003CStructuredOutputMiddlewareConfig>\n | Promise\u003Cvoid | Partial\u003CStructuredOutputMiddlewareConfig>>\n```\n\n**`StructuredOutputMiddlewareConfig` shape:**\n\n```ts\ninterface StructuredOutputMiddlewareConfig extends ChatMiddlewareConfig {\n outputSchema: JSONSchema \u002F\u002F The JSON Schema being sent to the provider\n}\n```\n\n**Ordering rule:**\n\n- `onStructuredOutputConfig` fires **before** `onConfig` at the structured-output boundary.\n- `onConfig` re-fires at the same boundary with `ctx.phase === 'structuredOutput'`, receiving the post-`onStructuredOutputConfig` view of the config (minus `outputSchema`).\n- Use `onConfig` for general-purpose transforms that apply to every adapter call (agent-loop iterations and the final structured-output call).\n- Use `onStructuredOutputConfig` when you need to transform the JSON Schema or apply structured-output-specific behavior.\n\n## Core Patterns\n\n### Pattern 1: Analytics and Logging Middleware\n\nUse `onStart`, `onFinish`, `onUsage`, and `onError` for comprehensive observability.\nUse `ctx.defer()` for non-blocking async side effects that should not block the stream.\n\n```typescript\nimport {\n chat,\n toServerSentEventsResponse,\n type ChatMiddleware,\n} from '@tanstack\u002Fai'\nimport { openaiText } from '@tanstack\u002Fai-openai'\n\nconst analytics: ChatMiddleware = {\n name: 'analytics',\n onStart: (ctx) => {\n console.log(`[${ctx.requestId}] Chat started — model: ${ctx.model}`)\n },\n onUsage: (ctx, usage) => {\n console.log(`[${ctx.requestId}] Tokens: ${usage.totalTokens}`)\n },\n onFinish: (ctx, info) => {\n ctx.defer(\n fetch('\u002Fapi\u002Fanalytics', {\n method: 'POST',\n body: JSON.stringify({\n requestId: ctx.requestId,\n model: ctx.model,\n duration: info.duration,\n tokens: info.usage?.totalTokens,\n finishReason: info.finishReason,\n }),\n }),\n )\n },\n onError: (ctx, info) => {\n ctx.defer(\n fetch('\u002Fapi\u002Ferrors', {\n method: 'POST',\n body: JSON.stringify({\n requestId: ctx.requestId,\n error: String(info.error),\n duration: info.duration,\n }),\n }),\n )\n },\n}\n\nconst stream = chat({\n adapter: openaiText('gpt-5.2'),\n messages,\n middleware: [analytics],\n})\n\nreturn toServerSentEventsResponse(stream)\n```\n\n### Pattern 2: Tool Interception Middleware\n\nUse `onBeforeToolCall` to validate, gate, or transform tool arguments before execution.\nUse `onAfterToolCall` to log results and timing. The first middleware that returns a\nnon-void decision from `onBeforeToolCall` short-circuits remaining middleware for that call.\n\n```typescript\nimport type { ChatMiddleware } from '@tanstack\u002Fai'\n\nconst toolGuard: ChatMiddleware = {\n name: 'tool-guard',\n onBeforeToolCall: (ctx, hookCtx) => {\n \u002F\u002F Block dangerous tools\n if (hookCtx.toolName === 'deleteDatabase') {\n return { type: 'abort', reason: 'Dangerous operation blocked' }\n }\n\n \u002F\u002F Enforce default arguments\n if (hookCtx.toolName === 'search' && !hookCtx.args.limit) {\n return {\n type: 'transformArgs',\n args: { ...hookCtx.args, limit: 10 },\n }\n }\n\n \u002F\u002F Return void to continue normally\n },\n onAfterToolCall: (ctx, info) => {\n if (info.ok) {\n console.log(`${info.toolName} completed in ${info.duration}ms`)\n } else {\n console.error(`${info.toolName} failed:`, info.error)\n }\n },\n}\n```\n\n**`onBeforeToolCall` decision types:**\n\n| Decision | Effect |\n| --------------------------------- | ------------------------------------------------------------------- |\n| `void` \u002F `undefined` | Continue normally, next middleware decides |\n| `{ type: 'transformArgs', args }` | Replace tool arguments before execution |\n| `{ type: 'skip', result }` | Skip execution, use provided result (used by `toolCacheMiddleware`) |\n| `{ type: 'abort', reason? }` | Abort the entire chat run |\n\n### Pattern 3: Structured-Output Middleware\n\nWhen `chat({ outputSchema })` is used, the final structured-output adapter call\nnow flows through the same middleware chain as the agent loop (with\n`ctx.phase === 'structuredOutput'`). Before this change, the final call bypassed\nmiddleware entirely — `onChunk`, `onUsage`, `onConfig`, and terminal hooks did\nnot see it.\n\n**Example A — Observability (tracing every chunk, including finalization):**\n\n```typescript\nimport type { ChatMiddleware } from '@tanstack\u002Fai'\n\nconst tracing: ChatMiddleware = {\n name: 'tracing',\n onChunk(ctx, chunk) {\n span.addEvent('chunk', { phase: ctx.phase, type: chunk.type })\n },\n}\n```\n\nThis middleware now observes every chunk from the final structured-output call,\nattributed to `ctx.phase === 'structuredOutput'`. Before the fix, the final\nadapter call bypassed middleware entirely — `tracing` would only see agent-loop\nchunks.\n\n**Example B — Schema rewriting (inject shared `$defs`):**\n\n```typescript\nimport type { ChatMiddleware } from '@tanstack\u002Fai'\n\nconst injectDefs: ChatMiddleware = {\n name: 'inject-defs',\n onStructuredOutputConfig(_ctx, config) {\n return {\n outputSchema: { ...config.outputSchema, $defs: { ...sharedDefs } },\n }\n },\n}\n```\n\n`onStructuredOutputConfig` is the right hook here because it has direct access\nto `config.outputSchema` and runs only on the structured-output boundary —\nschema rewrites do not leak into the agent-loop adapter calls.\n\n### Pattern 4: Multiple Middleware Composition\n\nMiddleware executes in array order (left-to-right). Ordering matters for hooks that\npipe or short-circuit:\n\n```typescript\nimport { chat, type ChatMiddleware } from '@tanstack\u002Fai'\nimport { toolCacheMiddleware } from '@tanstack\u002Fai\u002Fmiddlewares'\nimport { openaiText } from '@tanstack\u002Fai-openai'\n\nconst logging: ChatMiddleware = {\n name: 'logging',\n onStart: (ctx) => console.log(`[${ctx.requestId}] started`),\n onChunk: (ctx, chunk) => {\n console.log(`[${ctx.requestId}] chunk: ${chunk.type}`)\n },\n onFinish: (ctx, info) => {\n console.log(`[${ctx.requestId}] done in ${info.duration}ms`)\n },\n}\n\nconst configTransform: ChatMiddleware = {\n name: 'config-transform',\n onConfig: (ctx, config) => {\n if (ctx.phase === 'init') {\n return {\n systemPrompts: [...config.systemPrompts, 'Always respond in JSON.'],\n \u002F\u002F Sampling options are NOT first-class config fields — mutate them\n \u002F\u002F through `config.modelOptions` using the provider's native key.\n \u002F\u002F (e.g. OpenAI `temperature` \u002F `max_output_tokens`.)\n modelOptions: { ...config.modelOptions, temperature: 0.2 },\n }\n }\n },\n}\n\nconst stream = chat({\n adapter: openaiText('gpt-5.2'),\n messages,\n tools: [weatherTool, stockTool],\n middleware: [\n logging, \u002F\u002F Runs first\n configTransform, \u002F\u002F Transforms config second\n toolCacheMiddleware({ ttl: 60_000 }), \u002F\u002F Caches tool results third\n ],\n})\n```\n\n**Composition rules by hook:**\n\n| Hook | Composition | Effect of Order |\n| -------------------------- | --------------------------------------------- | ------------------------------------------ |\n| `onConfig` | **Piped** -- each receives previous output | Earlier middleware transforms first |\n| `onStructuredOutputConfig` | **Piped** -- each receives previous output | Earlier middleware transforms first |\n| `onStart` | Sequential | All run in order |\n| `onChunk` | **Piped** -- chunks flow through each | If first drops a chunk, later never see it |\n| `onBeforeToolCall` | **First-win** -- first non-void decision wins | Earlier middleware has priority |\n| `onAfterToolCall` | Sequential | All run in order |\n| `onUsage` | Sequential | All run in order |\n| `onFinish\u002FonAbort\u002FonError` | Sequential | All run in order |\n\n## Pattern: tool-call budget (app-owned)\n\nNot a built-in. Cap fan-out with `onBeforeToolCall` skip + `onShouldContinue`.\nSee `docs\u002Fchat\u002Fagentic-cycle.md` (\"Tool-call budgets\").\n\n```typescript\nimport { chat, maxIterations, type ChatMiddleware } from '@tanstack\u002Fai'\n\nfunction toolCallBudget(opts: {\n max?: number\n maxPerTurn?: number\n}): ChatMiddleware {\n let perTurn = 0\n return {\n onIteration: () => {\n perTurn = 0\n },\n onToolPhaseComplete: () => {\n perTurn = 0\n },\n onBeforeToolCall: () => {\n if (opts.maxPerTurn == null) return undefined\n if (++perTurn > opts.maxPerTurn) {\n return {\n type: 'skip',\n result: {\n error: `Skipped: exceeded maxToolCallsPerTurn (${opts.maxPerTurn})`,\n },\n }\n }\n return undefined\n },\n onShouldContinue: (_ctx, state) =>\n opts.max != null && state.toolCallCount >= opts.max ? false : undefined,\n }\n}\n\nchat({\n adapter,\n messages,\n tools: [weatherTool],\n agentLoopStrategy: maxIterations(20),\n middleware: [toolCallBudget({ maxPerTurn: 10, max: 20 })],\n})\n```\n\n## Built-in: toolCacheMiddleware\n\nCaches tool call results by name + arguments. Import from `@tanstack\u002Fai\u002Fmiddlewares`:\n\n```typescript\nimport { chat } from '@tanstack\u002Fai'\nimport { toolCacheMiddleware } from '@tanstack\u002Fai\u002Fmiddlewares'\n\nconst stream = chat({\n adapter,\n messages,\n tools: [weatherTool],\n middleware: [\n toolCacheMiddleware({\n ttl: 60_000, \u002F\u002F Cache entries expire after 60 seconds\n maxSize: 50, \u002F\u002F Max 50 entries (LRU eviction)\n toolNames: ['getWeather'], \u002F\u002F Only cache specific tools\n }),\n ],\n})\n```\n\nOptions: `maxSize` (default 100), `ttl` (default Infinity), `toolNames` (default all),\n`keyFn` (custom cache key), `storage` (custom backend like Redis). See\n`docs\u002Fadvanced\u002Fmiddleware.md` for custom storage examples.\n\n## Server State Persistence: withPersistence\n\n`withPersistence(persistence)` (from `@tanstack\u002Fai-persistence`) is a\n`ChatMiddleware` that persists **state** for `chat()` — thread messages, run\nrecords (status\u002Ftiming\u002Fusage\u002Ferrors), and interrupt state — to a backend store.\nAdd it to the `middleware` array like any other middleware. It never mutates the\nchunk stream; replaying a dropped\u002Freloaded _stream_ is a separate transport-layer\nconcern (see ai-core\u002Fchat-experience\u002FSKILL.md resumability, not this middleware).\n\n```typescript\nimport {\n chat,\n chatParamsFromRequest,\n toServerSentEventsResponse,\n} from '@tanstack\u002Fai'\nimport { openaiText } from '@tanstack\u002Fai-openai'\nimport { withPersistence, memoryPersistence } from '@tanstack\u002Fai-persistence'\n\n\u002F\u002F memoryPersistence() is the in-process reference backend (dev\u002Ftests). For a\n\u002F\u002F durable one, implement the store contracts against your database — see the\n\u002F\u002F @tanstack\u002Fai-persistence skills.\nconst persistence = memoryPersistence()\n\nexport async function POST(request: Request) {\n const params = await chatParamsFromRequest(request)\n\n const stream = chat({\n adapter: openaiText('gpt-5.5'),\n messages: params.messages,\n threadId: params.threadId,\n runId: params.runId,\n ...(params.resume ? { resume: params.resume } : {}),\n middleware: [withPersistence(persistence)],\n })\n\n return toServerSentEventsResponse(stream)\n}\n```\n\n### Authoritative-history contract\n\nThe middleware treats each request's `messages` as the source of truth for the\nthread:\n\n- **Non-empty `messages`** → on a successful finish (and at an interrupt\n boundary) the middleware **overwrites** the entire stored thread with that\n array. Post the **complete** transcript, never just the newest message(s) — a\n delta would replace and destroy the stored history.\n- **Empty `messages`** → the middleware **loads** the stored thread and runs the\n turn from the server's copy. This is how you continue a conversation without\n resending history from the client.\n\n### Backends\n\n`@tanstack\u002Fai-persistence` ships **contracts, not a database backend**. It\nprovides the four store interfaces (`messages`, `runs`, `interrupts`,\n`metadata`), the middleware that drives them, `memoryPersistence()` for\ndev\u002Ftests, and a conformance testkit. For anything durable you implement the\nstores against your own database and pass the result to `withPersistence`.\n\nAnnotate your factory with a named shape (`ChatPersistence` \u002F\n`ChatTranscriptPersistence`) — bare `AIPersistence` is the all-optional bag and\n`withPersistence` rejects it.\n\nLocks are separate from state and are **not** a `stores` key: wire a\n`LockStore` with `withLocks(lockStore)`.\n\n**Full guidance lives in the package's own skills** — start at\n`node_modules\u002F@tanstack\u002Fai-persistence\u002Fskills\u002Fai-persistence\u002FSKILL.md`,\nwhich routes to the server, client, stores, locks, and adapter-recipe\n(Drizzle \u002F Prisma \u002F Cloudflare) sub-skills.\n\n### Resume reconstruction is the middleware's job (server-authoritative path)\n\nWhen a thread has pending interrupts, the middleware **records** them and\n**gates** new input: a request that carries pending interrupts must include a\n`resume` batch that references them, or `onConfig` throws. On a valid resume\nbatch the middleware also **builds `ChatResumeToolState`** (approvals \u002F\nclient-tool results) and **clears `config.resume`** so the chat engine skips\nits ephemeral reconstruction — that path needs client message history the\npersistence flow deliberately omits when the server owns the transcript.\nResumes accepted in `onConfig` are committed (marked resolved\u002Fcancelled) only\nonce the run reaches a successful boundary, so a provider failure between\naccepting a resume and finishing leaves the interrupt pending and a retry with\nthe same resume succeeds.\n\n> A companion `withGenerationPersistence(persistence)` tracks run records for\n> non-chat generation activities (image, audio, TTS, video, transcription).\n\nSource: docs\u002Fpersistence\u002Foverview.md\n\n## Sandbox File-Event Hooks (`sandbox` group)\n\nDeclare a `sandbox: ChatSandboxHooks` group on `defineChatMiddleware` to react\nto every file created\u002Fchanged\u002Fdeleted inside a sandbox provided by\n`withSandbox` (from `@tanstack\u002Fai-sandbox`). These fire **per-run**,\nserver-side, and each handler receives the run's `ChatMiddlewareContext` as\nthe first argument:\n\n```typescript\nimport { defineChatMiddleware } from '@tanstack\u002Fai'\nimport { db } from '.\u002Fdb'\n\nconst auditMiddleware = defineChatMiddleware({\n name: 'audit',\n sandbox: {\n onFile: (ctx, e) => console.log(ctx.runId, e.type, e.path),\n onFileCreate: (ctx, e) => db.log({ run: ctx.runId, event: e }),\n },\n})\n```\n\n| Hook | Fires for |\n| -------------- | -------------------------- |\n| `onFile` | Every create\u002Fchange\u002Fdelete |\n| `onFileCreate` | File creates only |\n| `onFileChange` | File changes only |\n| `onFileDelete` | File deletes only |\n\nThese are independent of the stream: the engine also emits a `sandbox.file`\n`CUSTOM` chunk per change regardless of whether any `sandbox` hooks are\nregistered, so a client can react to the same edits without middleware. See\n`ai-core\u002Fag-ui-protocol\u002FSKILL.md` for reading that chunk (and the opt-in\n`sandbox.file.diff` chunk) off `ChatStream`.\n\n### `before()` \u002F `after()` \u002F `diff()` — lazy, git-backed content accessors\n\nEach hook receives a `SandboxFileHookEvent`: the serializable\n`{ type, path, timestamp }` plus three lazy accessors for the file's content:\n\n```ts\ninterface SandboxFileHookEvent {\n type: 'create' | 'change' | 'delete'\n path: string\n timestamp: number\n before(): Promise\u003Cstring> \u002F\u002F content at the session baseline ('' if new \u002F non-git)\n after(): Promise\u003Cstring> \u002F\u002F current content ('' if deleted)\n diff(): Promise\u003Cstring> \u002F\u002F unified patch vs the baseline\n}\n```\n\n```typescript\nimport { defineChatMiddleware } from '@tanstack\u002Fai'\nimport { db } from '.\u002Fdb'\n\nconst auditMiddleware = defineChatMiddleware({\n name: 'audit',\n sandbox: {\n onFileChange: async (ctx, e) => {\n const [before, after] = await Promise.all([e.before(), e.after()])\n db.log({ run: ctx.runId, path: e.path, before, after })\n },\n },\n})\n```\n\n**Lazy — path-only hooks pay nothing.** `before()`, `after()`, and `diff()`\nare methods, not fields: each only reads the file or shells out to `git` when\ncalled. A hook that only reads `e.path`\u002F`e.type` (like the `onFile` logger\nabove) never touches the filesystem or spawns a process.\n\n**Git session baseline.** The sandbox snapshots `git rev-parse HEAD` once at\nsetup as the session baseline (empty string if the workspace isn't a git repo\nor has no commits). `before()` and `diff()` always diff against that same\nfixed baseline for the rest of the run, so `onFileChange` reports the file's\n**cumulative** change since the run started, not just the delta since the\nlast poll. `after()` always reads current on-disk content. None of the three\naccessors throw: a deleted file resolves `after()` to `''` (it still has\n`before()`); a new file resolves `before()` to `''` (it still has `after()`);\na non-git workspace resolves **both** `before()` and `after()` to `''` and\nmakes `diff()` fall back to a synthesized add-patch built from `after()` —\nexcept for a `delete` event in a non-git workspace, where there's nothing to\nsynthesize and `diff()` resolves to `''`. In a git workspace a file git\n**isn't tracking yet** (a file the agent created, and every later edit to it)\ndiffs empty because `git diff` ignores untracked files, so `diff()` falls\nback to the same synthesized add-patch whenever the file is absent at the\nbaseline — a create-or-edit of an untracked file never streams an empty diff.\nAn empty diff for a **tracked** file (identical to the baseline) stays empty,\nas it should. 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For backends serving AG-UI events without client packages.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11657,11660,11661],{"name":11658,"slug":11659,"type":16},"API Development","api-development",{"name":11647,"slug":37,"type":16},{"name":10,"slug":9,"type":16},"2026-07-16T06:04:10.093367",{"slug":11664,"name":11665,"fn":11666,"description":11667,"org":11668,"tags":11669,"stars":24,"repoUrl":25,"updatedAt":11676},"ai-corechat-experience","ai-core\u002Fchat-experience","implement chat experiences with TanStack AI","End-to-end chat implementation: server endpoint with chat() and toServerSentEventsResponse(), client-side useChat hook with fetchServerSentEvents(), message rendering with UIMessage parts, multimodal content, thinking\u002Freasoning display. Covers streaming states, connection adapters, and message format conversions. NOT Vercel AI SDK — uses chat() not streamText().\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11670,11671,11674,11675],{"name":11658,"slug":11659,"type":16},{"name":11672,"slug":11673,"type":16},"Frontend","frontend",{"name":11647,"slug":37,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:26:11.505241",{"slug":11678,"name":11679,"fn":11680,"description":11681,"org":11682,"tags":11683,"stars":24,"repoUrl":25,"updatedAt":11689},"ai-coreclient-persistence","ai-core\u002Fclient-persistence","implement browser chat persistence for TanStack AI","Browser chat persistence on useChat \u002F ChatClient: localStoragePersistence, sessionStoragePersistence, indexedDBPersistence. Client-authoritative (adapter, full transcript) vs server-authoritative (persistence: true, no client cache). Reload restore, pending interrupts, mid-stream rejoin with delivery durability. Use for SPA reload durability — NOT server history alone. No extra package: the adapters ship in the framework packages.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11684,11685,11686,11688],{"name":11632,"slug":30,"type":16},{"name":11672,"slug":11673,"type":16},{"name":11687,"slug":8215,"type":16},"Persistence",{"name":10,"slug":9,"type":16},"2026-07-30T05:53:35.503176",{"slug":11691,"name":11692,"fn":11693,"description":11694,"org":11695,"tags":11696,"stars":24,"repoUrl":25,"updatedAt":11703},"ai-corecustom-backend-integration","ai-core\u002Fcustom-backend-integration","integrate custom backends with TanStack AI","Connect useChat to a non-TanStack-AI backend through custom connection adapters. ConnectConnectionAdapter (single async iterable) vs SubscribeConnectionAdapter (separate subscribe\u002Fsend). Customize fetchServerSentEvents() and fetchHttpStream() with auth headers, custom URLs, and request options. Import from framework package, not @tanstack\u002Fai-client.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11697,11698,11699,11702],{"name":11632,"slug":30,"type":16},{"name":11658,"slug":11659,"type":16},{"name":11700,"slug":11701,"type":16},"Backend","backend",{"name":10,"slug":9,"type":16},"2026-07-17T06:06:39.855351",{"items":11705,"total":11845},[11706,11720,11732,11744,11759,11771,11781,11791,11804,11814,11825,11835],{"slug":11707,"name":11707,"fn":11708,"description":11709,"org":11710,"tags":11711,"stars":11717,"repoUrl":11718,"updatedAt":11719},"aggregation","perform data aggregation in TanStack Table","Aggregate TanStack Table columns independently of grouping, including grand totals, caller-selected row totals, multiple keyed aggregations, custom context-based definitions, grouped merges, manual values, and worker constraints.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11712,11715,11716],{"name":11713,"slug":11714,"type":16},"Data Analysis","data-analysis",{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},28175,"https:\u002F\u002Fgithub.com\u002FTanStack\u002Ftable","2026-07-30T05:25:59.429787",{"slug":11721,"name":11721,"fn":11722,"description":11723,"org":11724,"tags":11725,"stars":11717,"repoUrl":11718,"updatedAt":11731},"api-not-found","diagnose TanStack Table API errors","Diagnose missing TanStack Table v9 exports, options, state slices, and instance methods. Load before inventing an API when code sees a type error, undefined feature method, absent object key, adapter mismatch, or v8-shaped example.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11726,11729,11730],{"name":11727,"slug":11728,"type":16},"Debugging","debugging",{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:26:05.418735",{"slug":11733,"name":11733,"fn":11734,"description":11735,"org":11736,"tags":11737,"stars":11717,"repoUrl":11718,"updatedAt":11743},"cell-selection","select rectangular cell ranges in tables","Select rectangular cell ranges with cellSelectionFeature: two-corner range state keyed by row and column id, mousedown\u002Fmouseenter handlers, selection edges, render-order resolution under pinning, and autoResetCellSelection. Load when ranges widen unexpectedly after sorting or column reordering, when a drag re-renders the whole table, or when building copy-to-clipboard from a selection.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11738,11739,11740],{"name":11713,"slug":11714,"type":16},{"name":10,"slug":9,"type":16},{"name":11741,"slug":11742,"type":16},"UI Components","ui-components","2026-07-30T05:25:38.403427",{"slug":11745,"name":11745,"fn":11746,"description":11747,"org":11748,"tags":11749,"stars":11717,"repoUrl":11718,"updatedAt":11758},"client-vs-server","manage TanStack Table data pipelines","Choose client or server ownership for filtering, grouping, sorting, expanding, and pagination in TanStack Table v9. Load for manual* flags, mixed pipelines, server counts, or deciding which dataset each row-model stage receives.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11750,11753,11754,11757],{"name":11751,"slug":11752,"type":16},"Data Pipeline","data-pipeline",{"name":11672,"slug":11673,"type":16},{"name":11755,"slug":11756,"type":16},"Performance","performance",{"name":10,"slug":9,"type":16},"2026-07-30T05:25:45.400104",{"slug":11760,"name":11760,"fn":11761,"description":11762,"org":11763,"tags":11764,"stars":11717,"repoUrl":11718,"updatedAt":11770},"column-faceting","build faceted filter UIs","Build faceted filter UIs with columnFacetingFeature, facetedRowModel, facetedUniqueValues, and facetedMinMaxValues. Load for facet counts, numeric ranges, own-filter exclusion, or server-page facet completeness.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11765,11768,11769],{"name":11766,"slug":11767,"type":16},"Data Visualization","data-visualization",{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:25:41.397257",{"slug":11772,"name":11772,"fn":11773,"description":11774,"org":11775,"tags":11776,"stars":11717,"repoUrl":11718,"updatedAt":11780},"column-filtering","implement column filtering in TanStack Table","Filter columns with columnFilteringFeature, filteredRowModel, filterFns, filterMeta, nested-row direction, and manualFiltering. Load for accessor compatibility, controlled filter updaters, fuzzy metadata, or client\u002Fserver ownership.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11777,11778,11779],{"name":11713,"slug":11714,"type":16},{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:25:53.391632",{"slug":11782,"name":11782,"fn":11783,"description":11784,"org":11785,"tags":11786,"stars":11717,"repoUrl":11718,"updatedAt":11790},"column-ordering","manage TanStack Table column ordering","Control TanStack Table v9 leaf columnOrder with stable IDs while accounting for pinning regions, visibility, and groupedColumnMode precedence. Load for drag-and-drop columns or rendered order that differs from state.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11787,11788,11789],{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},{"name":11741,"slug":11742,"type":16},"2026-07-30T05:26:03.37801",{"slug":11792,"name":11792,"fn":11793,"description":11794,"org":11795,"tags":11796,"stars":11717,"repoUrl":11718,"updatedAt":11803},"column-pinning","configure column pinning in TanStack Table","Pin columns into logical start, center, and end regions with columnPinningFeature and renderer-owned sticky CSS. Load for RTL offsets, z-index, backgrounds, overflow, widths, gaps, or overlaps.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11797,11800,11801,11802],{"name":11798,"slug":11799,"type":16},"CSS","css",{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},{"name":11741,"slug":11742,"type":16},"2026-07-30T05:25:55.377366",{"slug":11805,"name":11805,"fn":11806,"description":11807,"org":11808,"tags":11809,"stars":11717,"repoUrl":11718,"updatedAt":11813},"column-resizing","implement column resizing in TanStack Table","Wire columnResizingFeature, header.getResizeHandler, resize mode and direction, pointer or touch events, and performant CSS-variable updates. Load when resize state changes but widths do not, or large tables resize slowly.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11810,11811,11812],{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},{"name":11741,"slug":11742,"type":16},"2026-07-30T05:25:51.400011",{"slug":11815,"name":11815,"fn":11816,"description":11817,"org":11818,"tags":11819,"stars":11717,"repoUrl":11718,"updatedAt":11824},"column-sizing","configure column sizing in TanStack Table","Use columnSizingFeature numeric size, minSize, maxSize, getSize, getStart, getAfter, and total-size APIs in table, grid, or flex CSS. Load for auto or percentage misconceptions and sizing\u002Fpinning layout mismatch.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11820,11821,11822,11823],{"name":11798,"slug":11799,"type":16},{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},{"name":11741,"slug":11742,"type":16},"2026-07-30T05:25:48.703799",{"slug":11826,"name":11826,"fn":11827,"description":11828,"org":11829,"tags":11830,"stars":11717,"repoUrl":11718,"updatedAt":11834},"column-visibility","manage column visibility in TanStack Table","Hide columns with columnVisibilityFeature while rendering visibility-aware header, column, and cell collections. Load when hidden columns remain in the DOM, false-versus-absent state is confused, or enableHiding is misunderstood.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11831,11832,11833],{"name":11672,"slug":11673,"type":16},{"name":10,"slug":9,"type":16},{"name":11741,"slug":11742,"type":16},"2026-07-30T05:25:47.367943",{"slug":11836,"name":11836,"fn":11837,"description":11838,"org":11839,"tags":11840,"stars":11717,"repoUrl":11718,"updatedAt":11844},"core","build data grids with TanStack Table","Use TanStack Table v9 as a headless data-grid state and row-processing engine. Load for first-table architecture, stable data and columns, row numbering with getDisplayIndex, semantic rendering, framework adapter choice, or deciding what Table owns versus the renderer.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[11841,11842,11843],{"name":11713,"slug":11714,"type":16},{"name":11672,"slug":11673,"type":16},{"name":11741,"slug":11742,"type":16},"2026-07-30T05:25:52.366295",125]