ai-core/middleware
GitHub提供Chat生命周期中间件钩子,用于分析、日志和追踪。支持onStart、onChunk等事件拦截,通过中间件数组配置执行顺序,替代传统回调。
触发场景
安装
npx skills add TanStack/ai --skill ai-core/middleware -g -y
SKILL.md
Frontmatter
{
"name": "ai-core\/middleware",
"type": "sub-skill",
"library": "tanstack-ai",
"sources": [
"TanStack\/ai:docs\/advanced\/middleware.md",
"TanStack\/ai:docs\/sandbox\/observability.md"
],
"description": "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\/onFinish callbacks on chat() — use middleware.\n",
"library_version": "0.10.0"
}
Middleware
Dependency note: This skill builds on ai-core. Read it first for critical rules.
Setup — Analytics Tracking Middleware
import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
const stream = chat({
adapter: openaiText('gpt-5.2'),
messages,
middleware: [
{
onStart: (ctx) => {
console.log('Chat started:', ctx.model)
},
onFinish: (ctx, info) => {
trackAnalytics({ model: ctx.model, tokens: info.usage?.totalTokens })
},
onError: (ctx, info) => {
reportError(info.error)
},
},
],
})
return toServerSentEventsResponse(stream)
Hooks Reference
Every hook receives a ChatMiddlewareContext as its first argument, which provides
requestId, streamId, phase, iteration, chunkIndex, model, provider,
signal, abort(), defer(), and more.
| Hook | When | Second Argument |
|---|---|---|
onConfig |
Once at startup (init) + once per iteration (beforeModel) + once at structured-output boundary |
ChatMiddlewareConfig (return partial to merge) |
onStructuredOutputConfig |
Once at the structured-output boundary (only when chat({ outputSchema })) |
StructuredOutputMiddlewareConfig (return partial) |
onStart |
Once after initial onConfig |
none |
onIteration |
Start of each agent loop iteration | IterationInfo |
onChunk |
Every streamed chunk | StreamChunk (return void/chunk/chunk[]/null) |
onBeforeToolCall |
Before each tool executes | ToolCallHookContext (return decision or void) |
onAfterToolCall |
After each tool executes | AfterToolCallInfo |
onToolPhaseComplete |
After all tool calls in an iteration | ToolPhaseCompleteInfo |
onUsage |
When RUN_FINISHED includes usage data |
UsageInfo |
onFinish |
Run completed normally | FinishInfo |
onAbort |
Run was aborted | AbortInfo |
onError |
Unhandled error occurred | ErrorInfo |
Terminal hooks (onFinish, onAbort, onError) are mutually exclusive -- exactly
one fires per chat() invocation.
Sampling in
onConfig:temperature,topP, andmaxTokensare not first-class fields onChatMiddlewareConfig. To adjust sampling from middleware, return a partial that mutatesconfig.modelOptionsusing the provider's native key (e.g. OpenAItemperature/max_output_tokens, Anthropicmax_tokens, Ollama nestedoptions.num_predict). Returning a top-leveltemperature/maxTokenshas no effect.
Phase values
ctx.phase is one of:
| Phase | When |
|---|---|
'init' |
Initial setup (before the first onConfig snapshot is built). |
'beforeModel' |
Right before each agent-loop adapter call (onConfig re-fires here). |
'modelStream' |
During model streaming chunks within the agent loop. |
'beforeTools' |
Before tool execution phase. |
'afterTools' |
After tool execution phase. |
'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. |
Structured-output lifecycle rules (when chat({ outputSchema }) is used):
onStructuredOutputConfigfires beforeonConfigat the structured-output boundary.onConfigre-fires at the same boundary withctx.phase === 'structuredOutput', receiving the post-onStructuredOutputConfigview of the config (minusoutputSchema).onChunkandonUsagefire for every chunk and usage event emitted by the structured-output call, withctx.phase === 'structuredOutput'.onIterationdoes not fire for finalization — it is agent-loop-only.onFinishfires once at the end of the wholechat()invocation, after the structured-output finalization completes (not after the agent loop). Terminal-hook exclusivity still holds (one ofonFinish/onAbort/onError).- Terminal
infoand structured-output:info.usage/info.finishReason/info.contentreflect the agent loop's terminal state, NOT the finalization step. Finalization state is intentionally segregated to keep agent-loop semantics clean. For a tools-lesschat({ outputSchema })run,info.usageisundefinedandinfo.finishReasonisnull(no agent-loop iteration producedRUN_FINISHED). To capture finalization tokens, useonUsage— it fires for both agent-loop iterations and the final call. For the structured-output result itself, observe thestructured-output.completeCUSTOM event inonChunk.
onStructuredOutputConfig
A dedicated config hook that fires only at the structured-output boundary
(when chat({ outputSchema }) is invoked). Use it to transform the JSON Schema
sent to the provider (inject $defs, strip vendor-incompatible keywords) or to
apply structured-output-specific config changes that should not affect the
agent-loop adapter calls.
Signature:
onStructuredOutputConfig?: (
ctx: ChatMiddlewareContext,
config: StructuredOutputMiddlewareConfig,
) =>
| void
| null
| Partial<StructuredOutputMiddlewareConfig>
| Promise<void | Partial<StructuredOutputMiddlewareConfig>>
StructuredOutputMiddlewareConfig shape:
interface StructuredOutputMiddlewareConfig extends ChatMiddlewareConfig {
outputSchema: JSONSchema // The JSON Schema being sent to the provider
}
Ordering rule:
onStructuredOutputConfigfires beforeonConfigat the structured-output boundary.onConfigre-fires at the same boundary withctx.phase === 'structuredOutput', receiving the post-onStructuredOutputConfigview of the config (minusoutputSchema).- Use
onConfigfor general-purpose transforms that apply to every adapter call (agent-loop iterations and the final structured-output call). - Use
onStructuredOutputConfigwhen you need to transform the JSON Schema or apply structured-output-specific behavior.
Core Patterns
Pattern 1: Analytics and Logging Middleware
Use onStart, onFinish, onUsage, and onError for comprehensive observability.
Use ctx.defer() for non-blocking async side effects that should not block the stream.
import {
chat,
toServerSentEventsResponse,
type ChatMiddleware,
} from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
const analytics: ChatMiddleware = {
name: 'analytics',
onStart: (ctx) => {
console.log(`[${ctx.requestId}] Chat started — model: ${ctx.model}`)
},
onUsage: (ctx, usage) => {
console.log(`[${ctx.requestId}] Tokens: ${usage.totalTokens}`)
},
onFinish: (ctx, info) => {
ctx.defer(
fetch('/api/analytics', {
method: 'POST',
body: JSON.stringify({
requestId: ctx.requestId,
model: ctx.model,
duration: info.duration,
tokens: info.usage?.totalTokens,
finishReason: info.finishReason,
}),
}),
)
},
onError: (ctx, info) => {
ctx.defer(
fetch('/api/errors', {
method: 'POST',
body: JSON.stringify({
requestId: ctx.requestId,
error: String(info.error),
duration: info.duration,
}),
}),
)
},
}
const stream = chat({
adapter: openaiText('gpt-5.2'),
messages,
middleware: [analytics],
})
return toServerSentEventsResponse(stream)
Pattern 2: Tool Interception Middleware
Use onBeforeToolCall to validate, gate, or transform tool arguments before execution.
Use onAfterToolCall to log results and timing. The first middleware that returns a
non-void decision from onBeforeToolCall short-circuits remaining middleware for that call.
import type { ChatMiddleware } from '@tanstack/ai'
const toolGuard: ChatMiddleware = {
name: 'tool-guard',
onBeforeToolCall: (ctx, hookCtx) => {
// Block dangerous tools
if (hookCtx.toolName === 'deleteDatabase') {
return { type: 'abort', reason: 'Dangerous operation blocked' }
}
// Enforce default arguments
if (hookCtx.toolName === 'search' && !hookCtx.args.limit) {
return {
type: 'transformArgs',
args: { ...hookCtx.args, limit: 10 },
}
}
// Return void to continue normally
},
onAfterToolCall: (ctx, info) => {
if (info.ok) {
console.log(`${info.toolName} completed in ${info.duration}ms`)
} else {
console.error(`${info.toolName} failed:`, info.error)
}
},
}
onBeforeToolCall decision types:
| Decision | Effect |
|---|---|
void / undefined |
Continue normally, next middleware decides |
{ type: 'transformArgs', args } |
Replace tool arguments before execution |
{ type: 'skip', result } |
Skip execution, use provided result (used by toolCacheMiddleware) |
{ type: 'abort', reason? } |
Abort the entire chat run |
Pattern 3: Structured-Output Middleware
When chat({ outputSchema }) is used, the final structured-output adapter call
now flows through the same middleware chain as the agent loop (with
ctx.phase === 'structuredOutput'). Before this change, the final call bypassed
middleware entirely — onChunk, onUsage, onConfig, and terminal hooks did
not see it.
Example A — Observability (tracing every chunk, including finalization):
import type { ChatMiddleware } from '@tanstack/ai'
const tracing: ChatMiddleware = {
name: 'tracing',
onChunk(ctx, chunk) {
span.addEvent('chunk', { phase: ctx.phase, type: chunk.type })
},
}
This middleware now observes every chunk from the final structured-output call,
attributed to ctx.phase === 'structuredOutput'. Before the fix, the final
adapter call bypassed middleware entirely — tracing would only see agent-loop
chunks.
Example B — Schema rewriting (inject shared $defs):
import type { ChatMiddleware } from '@tanstack/ai'
const injectDefs: ChatMiddleware = {
name: 'inject-defs',
onStructuredOutputConfig(_ctx, config) {
return {
outputSchema: { ...config.outputSchema, $defs: { ...sharedDefs } },
}
},
}
onStructuredOutputConfig is the right hook here because it has direct access
to config.outputSchema and runs only on the structured-output boundary —
schema rewrites do not leak into the agent-loop adapter calls.
Pattern 4: Multiple Middleware Composition
Middleware executes in array order (left-to-right). Ordering matters for hooks that pipe or short-circuit:
import { chat, type ChatMiddleware } from '@tanstack/ai'
import { toolCacheMiddleware } from '@tanstack/ai/middlewares'
import { openaiText } from '@tanstack/ai-openai'
const logging: ChatMiddleware = {
name: 'logging',
onStart: (ctx) => console.log(`[${ctx.requestId}] started`),
onChunk: (ctx, chunk) => {
console.log(`[${ctx.requestId}] chunk: ${chunk.type}`)
},
onFinish: (ctx, info) => {
console.log(`[${ctx.requestId}] done in ${info.duration}ms`)
},
}
const configTransform: ChatMiddleware = {
name: 'config-transform',
onConfig: (ctx, config) => {
if (ctx.phase === 'init') {
return {
systemPrompts: [...config.systemPrompts, 'Always respond in JSON.'],
// Sampling options are NOT first-class config fields — mutate them
// through `config.modelOptions` using the provider's native key.
// (e.g. OpenAI `temperature` / `max_output_tokens`.)
modelOptions: { ...config.modelOptions, temperature: 0.2 },
}
}
},
}
const stream = chat({
adapter: openaiText('gpt-5.2'),
messages,
tools: [weatherTool, stockTool],
middleware: [
logging, // Runs first
configTransform, // Transforms config second
toolCacheMiddleware({ ttl: 60_000 }), // Caches tool results third
],
})
Composition rules by hook:
| Hook | Composition | Effect of Order |
|---|---|---|
onConfig |
Piped -- each receives previous output | Earlier middleware transforms first |
onStructuredOutputConfig |
Piped -- each receives previous output | Earlier middleware transforms first |
onStart |
Sequential | All run in order |
onChunk |
Piped -- chunks flow through each | If first drops a chunk, later never see it |
onBeforeToolCall |
First-win -- first non-void decision wins | Earlier middleware has priority |
onAfterToolCall |
Sequential | All run in order |
onUsage |
Sequential | All run in order |
onFinish/onAbort/onError |
Sequential | All run in order |
Built-in: toolCacheMiddleware
Caches tool call results by name + arguments. Import from @tanstack/ai/middlewares:
import { chat } from '@tanstack/ai'
import { toolCacheMiddleware } from '@tanstack/ai/middlewares'
const stream = chat({
adapter,
messages,
tools: [weatherTool],
middleware: [
toolCacheMiddleware({
ttl: 60_000, // Cache entries expire after 60 seconds
maxSize: 50, // Max 50 entries (LRU eviction)
toolNames: ['getWeather'], // Only cache specific tools
}),
],
})
Options: maxSize (default 100), ttl (default Infinity), toolNames (default all),
keyFn (custom cache key), storage (custom backend like Redis). See
docs/advanced/middleware.md for custom storage examples.
Sandbox File-Event Hooks (sandbox group)
Declare a sandbox: ChatSandboxHooks group on defineChatMiddleware to react
to every file created/changed/deleted inside a sandbox provided by
withSandbox (from @tanstack/ai-sandbox). These fire per-run,
server-side, and each handler receives the run's ChatMiddlewareContext as
the first argument:
import { defineChatMiddleware } from '@tanstack/ai'
import { db } from './db'
const auditMiddleware = defineChatMiddleware({
name: 'audit',
sandbox: {
onFile: (ctx, e) => console.log(ctx.runId, e.type, e.path),
onFileCreate: (ctx, e) => db.log({ run: ctx.runId, event: e }),
},
})
| Hook | Fires for |
|---|---|
onFile |
Every create/change/delete |
onFileCreate |
File creates only |
onFileChange |
File changes only |
onFileDelete |
File deletes only |
These are independent of the stream: the engine also emits a sandbox.file
CUSTOM chunk per change regardless of whether any sandbox hooks are
registered, so a client can react to the same edits without middleware. See
ai-core/ag-ui-protocol/SKILL.md for reading that chunk (and the opt-in
sandbox.file.diff chunk) off ChatStream.
before() / after() / diff() — lazy, git-backed content accessors
Each hook receives a SandboxFileHookEvent: the serializable
{ type, path, timestamp } plus three lazy accessors for the file's content:
interface SandboxFileHookEvent {
type: 'create' | 'change' | 'delete'
path: string
timestamp: number
before(): Promise<string> // content at the session baseline ('' if new / non-git)
after(): Promise<string> // current content ('' if deleted)
diff(): Promise<string> // unified patch vs the baseline
}
import { defineChatMiddleware } from '@tanstack/ai'
import { db } from './db'
const auditMiddleware = defineChatMiddleware({
name: 'audit',
sandbox: {
onFileChange: async (ctx, e) => {
const [before, after] = await Promise.all([e.before(), e.after()])
db.log({ run: ctx.runId, path: e.path, before, after })
},
},
})
Lazy — path-only hooks pay nothing. before(), after(), and diff()
are methods, not fields: each only reads the file or shells out to git when
called. A hook that only reads e.path/e.type (like the onFile logger
above) never touches the filesystem or spawns a process.
Git session baseline. The sandbox snapshots git rev-parse HEAD once at
setup as the session baseline (empty string if the workspace isn't a git repo
or has no commits). before() and diff() always diff against that same
fixed baseline for the rest of the run, so onFileChange reports the file's
cumulative change since the run started, not just the delta since the
last poll. after() always reads current on-disk content. None of the three
accessors throw: a deleted file resolves after() to '' (it still has
before()); a new file resolves before() to '' (it still has after());
a non-git workspace resolves both before() and after() to '' and
makes diff() fall back to a synthesized add-patch built from after() —
except for a delete event in a non-git workspace, where there's nothing to
synthesize and diff() resolves to ''. In a git workspace a file git
isn't tracking yet (a file the agent created, and every later edit to it)
diffs empty because git diff ignores untracked files, so diff() falls
back to the same synthesized add-patch whenever the file is absent at the
baseline — a create-or-edit of an untracked file never streams an empty diff.
An empty diff for a tracked file (identical to the baseline) stays empty,
as it should. A git-ignored file is withheld: the file event still fires
(you're notified it changed) but diff() returns '', so a secret like a
.env never has its contents surfaced in the diff feed.
Failures are logged, not silent. Every git/exec/fs failure behind these
accessors (and behind the find-poll watcher) still falls back to ''/an
empty snapshot, but logs first: real anomalies (a failed git diff, an
unreadable file, a lost find poll) under the errors category (on by
default); expected-empty conditions (a new file's before(), a non-git
baseline) under the sandbox debug category.
Hook errors are swallowed per hook. A throwing sandbox hook is caught
and logged under the errors category (on by default) — it cannot break the
run or stop other hooks (or the sandbox.file chunk) from continuing.
Source: docs/sandbox/observability.md
Common Mistakes
a. MEDIUM: Trying to modify StreamChunks in middleware
// WRONG -- mutating the chunk object directly
const broken: ChatMiddleware = {
name: 'broken',
onChunk: (ctx, chunk) => {
chunk.delta = 'modified' // Mutation does nothing; chunk is not modified in-place
},
}
// CORRECT -- return a new chunk to replace the original
const correct: ChatMiddleware = {
name: 'correct',
onChunk: (ctx, chunk) => {
if (chunk.type === 'TEXT_MESSAGE_CONTENT') {
return { ...chunk, delta: chunk.delta.replace(/secret/g, '[REDACTED]') }
}
// Return void to pass through unchanged
},
}
Middleware onChunk hooks are functional transforms. Return a new chunk, an array
of chunks, null (to drop), or void (to pass through). Mutating the input object
has no effect on the stream output.
Source: docs/advanced/middleware.md
b. MEDIUM: Middleware exceptions breaking the stream
// WRONG -- unhandled error kills the entire streaming response
const fragile: ChatMiddleware = {
name: 'fragile-analytics',
onFinish: async (ctx, info) => {
// If this fetch fails, the stream breaks
await fetch('/api/analytics', {
method: 'POST',
body: JSON.stringify({ duration: info.duration }),
})
},
}
// CORRECT -- wrap in try-catch and/or use ctx.defer()
const resilient: ChatMiddleware = {
name: 'resilient-analytics',
onFinish: (ctx, info) => {
// Option 1: defer (non-blocking, errors are isolated)
ctx.defer(
fetch('/api/analytics', {
method: 'POST',
body: JSON.stringify({ duration: info.duration }),
}),
)
},
onChunk: (ctx, chunk) => {
// Option 2: try-catch for synchronous/critical hooks
try {
logChunk(chunk)
} catch (err) {
console.error('Logging failed:', err)
}
// Return void to pass through
},
}
Wrap all middleware hooks in try-catch to prevent analytics or logging failures
from killing the chat stream. For async side effects, prefer ctx.defer() which
runs after the terminal hook and isolates failures.
Source: docs/advanced/middleware.md
Cross-References
- See also: ai-core/chat-experience/SKILL.md -- Middleware hooks into the chat lifecycle
- See also: ai-core/structured-outputs/SKILL.md -- Middleware now wraps the final structured-output call; use
onStructuredOutputConfigfor JSON-Schema transforms - See also: ai-core/ag-ui-protocol/SKILL.md -- Reading the
sandbox.file/sandbox.file.diffCUSTOMchunks the sandbox runtime emits alongside thesesandboxhooks, viaChatStream's typedKnownCustomEventnarrowing
版本历史
-
5fcaf90
当前 2026-07-11 18:44
本次提交主要修复沙箱文件差异检测问题,增强失败可观测性,并更新文档以对齐中间件SKILL中的钩子错误描述,与核心中间件功能无直接变更。
- 5deda27 2026-07-05 10:52


