feat: AI persistence and resumable interrupts

.changeset/persistence-layer.md

@@ -0,0 +1,75 @@
+---
+'@tanstack/ai': minor
+'@tanstack/ai-client': minor
+'@tanstack/ai-angular': minor
+'@tanstack/ai-preact': minor
+'@tanstack/ai-react': minor
+'@tanstack/ai-solid': minor
+'@tanstack/ai-svelte': minor
+'@tanstack/ai-vue': minor
+'@tanstack/ai-persistence': minor
+'@tanstack/ai-persistence-sql': minor
+'@tanstack/ai-persistence-sqlite': minor
+'@tanstack/ai-persistence-postgres': minor
+'@tanstack/ai-persistence-cloudflare': minor
+'@tanstack/ai-persistence-drizzle': minor
+'@tanstack/ai-persistence-prisma': minor
+'@tanstack/ai-sandbox': minor
+---
+
+Persistence + resumable runs as composable `chat()` middleware.
+
+`withPersistence(...)` makes any run durable: it loads/saves thread message
+history (server-authoritative), creates/updates run records, persists every
+AG-UI `StreamChunk` to an append-only public event log, and persists usage. It
+is fully **optional** - a `chat()` with no persistence middleware is unchanged.
+The primary API is `AIPersistence` / `defineAIPersistence`; `ChatPersistence` /
+`defineChatPersistence` remain deprecated compatibility aliases.
+
+**Resume.** Each persisted chunk carries an in-band, opaque `cursor` (a
+monotonic per-run sequence). A client that disconnects mid-run reconnects with
+`{ threadId, runId, cursor }`; `chat({ cursor })` replays the persisted public
+event tail after that cursor. The public chat hooks expose resume state and a
+manual `resume()` helper, with automatic resume behavior enabled unless
+`autoResume` is opted out.
+
+**Interrupts.** Actionable waits are represented by
+`RUN_FINISHED.outcome.type === 'interrupt'` and resumed with AG-UI
+`RunAgentInput.resume[]`. Pending user-actionable interrupts block normal new
+input on the same thread by default. Approval custom events are legacy
+compatibility/projection only.
+
+**Event model.** Public stream events are separate from internal CAS/checkpoint
+events. `PublicEventStore` replays the AG-UI `StreamChunk` stream itself;
+`InternalEventStore` stores package-owned checkpoints that must not leak into
+public replay. Optional feature validation fails loudly when a requested feature
+is missing its required stores.
+
+**Backends (shared SQL core + thin adapters).** One SQL implementation behind a
+minimal `SqlDriver` (`@tanstack/ai-persistence-sql`), with dialect support for
+SQLite, Postgres, and MySQL and backends for SQLite (`-sqlite`,
+node:sqlite/better-sqlite3), Postgres (`-postgres`, pg), Cloudflare D1
+(`-cloudflare`, with R2-backed `BlobStore`, D1-indexed R2 artifacts, and
+concrete Durable Object locks), and bring-your-own Drizzle (`-drizzle`) and
+Prisma (`-prisma`). The shared SQL core emits MySQL-safe DDL and conflict
+handling (binary key columns, `LONGTEXT` persisted payloads, and no-op
+`ON DUPLICATE KEY UPDATE` idempotent inserts). Raw drivers auto-migrate the
+small base schema (`runs`, `public_events`, `internal_events`, `messages`,
+`interrupts`, `metadata`, `_tanstack_ai_migrations`); ORMs own their schema.
+The Drizzle and Prisma packages now include `tanstack-ai-persistence-drizzle`
+and `tanstack-ai-persistence-prisma` CLIs that generate migration SQL files for
+manual `migrate: false` workflows.
+Cloudflare artifact metadata is lazily indexed in D1 while artifact bytes and
+generic blobs live in R2, with optional artifact/blob cleanup APIs for deletion
+and garbage collection.
+`memoryPersistence()` ships in core for tests/examples.
+
+**Sandboxes, MCP, and workflows.** `@tanstack/ai-sandbox` now consumes
+configured persistence capabilities directly. Place `withPersistence(...)`
+before `withSandbox(...)` and sandbox resume records are stored in persistence
+metadata while sandbox ensure-locking uses the shared persistence lock
+capability when present. `defineSandbox({ persistence: { workspace } })` can
+checkpoint managed sandbox workspace files to persistence metadata/artifacts
+and restore them before `hooks.onReady`. MCP persistence is app-owned metadata
+plus raw stream replay only. Workflow extensions are deferred to optional
+packages and should reuse these primitives without adding base schema cost.

docs/architecture/approval-flow-processing.md

@@ -41,6 +41,12 @@ execution until the user explicitly approves or denies the action. This
 creates a human-in-the-loop checkpoint for sensitive operations (sending
 emails, making purchases, deleting data).
 
+The primary durable wait signal is now the AG-UI terminal event
+`RUN_FINISHED.outcome.type === 'interrupt'`. The legacy
+`CUSTOM { name: "approval-requested" }` event is kept as a compatibility
+projection for older clients and UI state updates, but new persistence and
+resume logic should treat actionable waits as interrupts.
+
 The flow spans three layers:
 
 ```mermaid
@@ -55,9 +61,9 @@ flowchart TD
 
 | Layer | Responsibility |
 |-------|----------------|
-| **Server (TextEngine)** | `chat()` detects `needsApproval` → emits CUSTOM `approval-requested` instead of executing the tool |
-| **StreamProcessor** | Receives CUSTOM chunk → `updateToolCallApproval()` → fires `onApprovalRequest` callback |
-| **ChatClient** | Exposes `addToolApprovalResponse()` → updates message state → triggers `checkForContinuation()` → sends new stream |
+| **Server (TextEngine)** | `chat()` detects `needsApproval` -> emits a `RUN_FINISHED` interrupt outcome and may project legacy `approval-requested` events |
+| **StreamProcessor** | Receives interrupt outcome / compatibility custom event -> `updateToolCallApproval()` -> fires `onApprovalRequest` callback |
+| **ChatClient** | Exposes `addToolApprovalResponse()` -> updates message state -> sends AG-UI `RunAgentInput.resume[]` entries through the next request |
 
 Framework hooks (`useChat` in React, Solid, Vue, Svelte) delegate to
 `ChatClient`, which owns all concurrency and continuation logic.
@@ -70,15 +76,23 @@ Framework hooks (`useChat` in React, Solid, Vue, Svelte) delegate to
 
 - Runs the agent loop: calls the LLM adapter, accumulates tool calls, executes
   tools, and re-invokes the adapter with results.
-- When a tool has `needsApproval: true`, the engine emits a
-  `CUSTOM { name: "approval-requested" }` event instead of executing the tool.
-- The stream ends with `RUN_FINISHED { finishReason: "tool_calls" }` so the
-  client knows tools are pending.
+- When a tool has `needsApproval: true`, the engine emits a terminal
+  `RUN_FINISHED` event with `outcome.type === 'interrupt'` instead of executing
+  the tool.
+- Compatibility `CUSTOM { name: "approval-requested" }` events may still be
+  emitted or projected so older approval UI can render the same tool-call state.
+- Persistence stores pending interrupts and validates the later
+  `RunAgentInput.resume[]` response before accepting normal new input on the
+  same thread.
 
 ### StreamProcessor (`packages/ai/src/activities/chat/stream/processor.ts`)
 
 - Single source of truth for `UIMessage[]` state.
-- On `approval-requested` custom event:
+- On `RUN_FINISHED.outcome.type === 'interrupt'`:
+  1. Persists/surfaces each interrupt as a pending user-actionable wait.
+  2. Calls `updateToolCallApproval()` for approval-shaped interrupts so legacy
+     approval UI renders as before.
+- On legacy `approval-requested` custom event:
   1. Calls `updateToolCallApproval()` to set the tool-call part's state to
      `approval-requested` and attach approval metadata.
   2. Fires `onApprovalRequest` so the ChatClient can emit devtools events.
@@ -192,24 +206,31 @@ Step-by-step flow for a single tool requiring approval:
 TOOL_CALL_START   { toolCallId: "tc-1", toolName: "send_email" }
 TOOL_CALL_ARGS    { toolCallId: "tc-1", delta: '{"to":"..."}' }
 TOOL_CALL_END     { toolCallId: "tc-1" }
-CUSTOM            { name: "approval-requested", value: {
-                      toolCallId: "tc-1",
-                      toolName: "send_email",
-                      input: { to: "..." },
-                      approval: { id: "appr-1", needsApproval: true }
+RUN_FINISHED      { outcome: {
+                      type: "interrupt",
+                      interrupts: [{
+                        id: "appr-1",
+                        reason: "approval_required",
+                        metadata: {
+                          kind: "approval",
+                          toolCallId: "tc-1",
+                          toolName: "send_email",
+                          input: { to: "..." }
+                        }
+                      }]
                   }}
-RUN_FINISHED      { finishReason: "tool_calls" }
 ```
 
-### 2. StreamProcessor processes the CUSTOM chunk
+### 2. StreamProcessor processes the interrupt outcome
 
 ```
-handleCustomEvent():
+handleRunFinished():
   1. updateToolCallApproval(messages, messageId, "tc-1", "appr-1")
      → Sets part.state = "approval-requested"
      → Sets part.approval = { id: "appr-1", needsApproval: true }
-  2. emitMessagesChange()
-  3. fires onApprovalRequest({ toolCallId, toolName, input, approvalId })
+  2. records the pending interrupt on the client
+  3. emitMessagesChange()
+  4. fires onApprovalRequest({ toolCallId, toolName, input, approvalId })
 ```
 
 ### 3. Stream ends, ChatClient processes
@@ -233,7 +254,9 @@ addToolApprovalResponse({ id: "appr-1", approved: true }):
      → updateToolCallApprovalResponse():
        part.approval.approved = true
        part.state = "approval-responded"
-  2. isLoading is false → call checkForContinuation() directly
+  2. queue a resume entry:
+     { interruptId: "appr-1", status: "resolved", payload: { approved: true } }
+  3. isLoading is false → call checkForContinuation() directly
 ```
 
 ### 5. Continuation
@@ -244,8 +267,9 @@ checkForContinuation():
   2. shouldAutoSend() → areAllToolsComplete():
      part.state === "approval-responded" → true
   3. continuationPending = true
-  4. streamResponse() → new stream to server with approval in messages
-  5. Server sees approval, executes tool, returns result + LLM response
+  4. streamResponse() → new stream to server with `resume[]`
+  5. Persistence validates `resume[]`, resolves the pending interrupt, then the
+     server executes or cancels the tool and returns result + LLM response
   6. continuationPending = false
 ```
 
@@ -388,11 +412,52 @@ Timeline (with fix):
 
 ### Approval-related AG-UI events
 
-These are `CUSTOM` events emitted by the TextEngine, not by adapters directly.
+The primary wait event is `RUN_FINISHED` with an interrupt outcome:
+
+```typescript ignore
+{
+  type: 'RUN_FINISHED',
+  outcome: {
+    type: 'interrupt',
+    interrupts: [
+      {
+        id: string,
+        reason: 'approval_required',
+        metadata: {
+          kind: 'approval',
+          toolCallId: string,
+          toolName: string,
+          input: unknown
+        }
+      }
+    ]
+  }
+}
+```
+
+Resume uses AG-UI `RunAgentInput.resume[]` on the next request:
+
+```typescript ignore
+{
+  resume: [
+    {
+      interruptId: 'appr-1',
+      status: 'resolved',
+      payload: { approved: true }
+    }
+  ]
+}
+```
+
+Pending user-actionable interrupts block normal input on the same thread by
+default. A stale cursor replay may read the public event tail, but a new
+non-resume input must resolve the pending interrupts first.
 
 #### `approval-requested`
 
-Emitted when a tool with `needsApproval: true` has its arguments finalized.
+Legacy compatibility/projection event emitted when a tool with
+`needsApproval: true` has its arguments finalized. Use this to keep older UI
+rendering paths working; do not use it as the primary durable wait signal.
 
 ```typescript ignore
 {
@@ -422,13 +487,15 @@ TOOL_CALL_START     → creates tool-call part (state: awaiting-input)
 TOOL_CALL_ARGS*     → accumulates arguments (state: input-streaming)
 TOOL_CALL_END       → finalizes arguments (state: input-complete)
 CUSTOM              → approval-requested (state: approval-requested)
-RUN_FINISHED        → finishReason: "tool_calls"
+RUN_FINISHED        → outcome.type: "interrupt"
 ```
 
 After the stream ends and the user responds, the ChatClient:
 1. Updates the tool-call part (state: `approval-responded`)
-2. Sends a new stream request with the full conversation (including approval)
-3. The server sees the approval and either executes or cancels the tool
+2. Sends a new stream request with `RunAgentInput.resume[]` entries resolving
+   the pending interrupt
+3. Persistence validates the resume entries, resolves the interrupt, and the
+   server executes or cancels the tool based on the resume payload
 
 ---
 

docs/chat/connection-adapters.md

@@ -73,7 +73,7 @@ import { useChat, fetchServerSentEvents } from "@tanstack/ai-react";
 
 const { messages } = useChat({
   connection: fetchServerSentEvents("/api/chat", {
-    body: { provider: "openai", model: "gpt-5.1" },
+    body: { provider: "openai", model: "gpt-5.5" },
   }),
 });
 ```
@@ -178,7 +178,7 @@ import { chatServerFn } from "./server/chat.server";
 
 // `chatServerFn` is an in-process server-side function that synchronously
 // returns an AsyncIterable<StreamChunk> — e.g. the result of
-// `chat({ adapter, model, messages })` on the server.
+// `chat({ adapter: openaiText("gpt-5.5"), messages })` on the server.
 const { messages } = useChat({
   connection: stream((messages, data) => chatServerFn({ messages, ...data })),
 });
@@ -197,13 +197,28 @@ When you call into your server with an **async** function — the universal case
 import { createServerFn } from "@tanstack/react-start";
 import { chat, toServerSentEventsResponse } from "@tanstack/ai";
 import { openaiText } from "@tanstack/ai-openai";
-import type { UIMessage } from "@tanstack/ai";
+import type { RunAgentResumeItem, UIMessage } from "@tanstack/ai";
+
+type ChatFnInput = {
+  messages: Array<UIMessage>;
+  threadId?: string;
+  runId?: string;
+  cursor?: string;
+  resume?: Array<RunAgentResumeItem>;
+};
 
 export const chatFn = createServerFn({ method: "POST" })
-  .inputValidator((data: { messages: Array<UIMessage> }) => data)
+  .inputValidator((data: ChatFnInput) => data)
   .handler(({ data }) =>
     toServerSentEventsResponse(
-      chat({ adapter: openaiText("gpt-5.1"), messages: data.messages }),
+      chat({
+        adapter: openaiText("gpt-5.5"),
+        messages: data.messages,
+        threadId: data.threadId,
+        runId: data.runId,
+        cursor: data.cursor,
+        resume: data.resume,
+      }),
     ),
   );
 ```
@@ -213,11 +228,14 @@ import { useChat } from "@tanstack/ai-react";
 import { chatFn } from "./server/chat.server";
 
 const { messages, sendMessage } = useChat({
-  fetcher: ({ messages }, { signal }) => chatFn({ data: { messages }, signal }),
+  fetcher: (input, { signal }) => chatFn({ data: input, signal }),
 });
 ```
 
-The fetcher receives `{ messages, data, threadId, runId }` plus an `AbortSignal` (triggered by `stop()` or when a send is superseded). Return a `Response` — whose SSE body the chat client parses for you — **or** an `AsyncIterable<StreamChunk>`, which is yielded directly. If your server function returns the stream itself (instead of wrapping it in a `Response`), the fetcher handles that too. Sync and `Promise`-wrapped returns are both accepted.
+The fetcher receives `{ messages, data, threadId, runId, cursor, resume }` plus an `AbortSignal` (triggered by `stop()` or when a send is superseded). Forward `cursor` when replaying persisted public events, and forward `resume` when responding to pending AG-UI interrupts. Return a `Response` — whose SSE body the chat client parses for you — **or** an `AsyncIterable<StreamChunk>`, which is yielded directly. If your server function returns the stream itself (instead of wrapping it in a `Response`), the fetcher handles that too. Sync and `Promise`-wrapped returns are both accepted.
+
+For the server persistence path that produces those replay cursors, see
+[Resumable Chat](../persistence/resumable-chat).
 
 > **Tip:** The choice between `fetcher` and [`stream()`](#server-functions-and-direct-async-iterables) is about **async vs sync**, not `Response`-vs-iterable — both can yield an `AsyncIterable<StreamChunk>`. `stream()`'s factory must return that iterable **synchronously**, so a server-function call (which returns a `Promise`) won't typecheck there — that's the gap `fetcher` fills ([issue #509](https://github.com/TanStack/ai/issues/509)). Use `stream()` when you can hand back an async iterable synchronously (in-process `chat()`, an RPC client, tests); use `fetcher` for anything you have to `await`. Both normalize to the same request-scoped adapter, so `stop()`/abort, error handling, and tool calls behave identically.
 
@@ -315,6 +333,8 @@ function websocketConnection(url: string): SubscribeConnectionAdapter {
         JSON.stringify({
           threadId: runContext?.threadId,
           runId: runContext?.runId,
+          cursor: runContext?.cursor,
+          resume: runContext?.resume,
           messages,
           data,
         }),
@@ -382,6 +402,8 @@ const myAdapter: ConnectConnectionAdapter = {
       body: JSON.stringify({
         threadId: runContext?.threadId,
         runId: runContext?.runId,
+        cursor: runContext?.cursor,
+        resume: runContext?.resume,
         messages,
         ...data,
       }),
@@ -415,20 +437,26 @@ const myAdapter: ConnectConnectionAdapter = {
 const { messages } = useChat({ connection: myAdapter });
 ```
 
-`runContext` carries `threadId`, `runId`, `clientTools`, and `forwardedProps`. Include them in your request payload so the server can build an AG-UI-compliant response. If your `connect` stream completes without emitting `RUN_FINISHED`, the runtime synthesizes one for you; if it throws, a `RUN_ERROR` is synthesized.
+`runContext` carries `threadId`, `runId`, `cursor`, `resume`, `clientTools`, and `forwardedProps`. Include them in your request payload so the server can build an AG-UI-compliant response, replay from `{ threadId, runId, cursor }`, and validate `RunAgentInput.resume[]` for pending interrupts. If your `connect` stream completes without emitting `RUN_FINISHED`, the runtime synthesizes one for you; if it throws, a `RUN_ERROR` is synthesized.
+
+If the request-scoped adapter talks to a persisted `chat()` endpoint, those
+fields are the durable replay identity described in
+[Resumable Chat](../persistence/resumable-chat).
 
 ## The Adapter Interface
 
 A `ConnectionAdapter` is a union — provide **either** `connect`, **or** both `subscribe` and `send`. Never both modes.
 
 ```typescript
 import type { UIMessage } from "@tanstack/ai-client";
-import type { ModelMessage, StreamChunk } from "@tanstack/ai";
+import type { ModelMessage, RunAgentResumeItem, StreamChunk } from "@tanstack/ai";
 
 export interface RunAgentInputContext {
   threadId: string;
   runId: string;
   parentRunId?: string;
+  cursor?: string;
+  resume?: Array<RunAgentResumeItem>;
   clientTools?: Array<{ name: string; description: string; parameters: unknown }>;
   forwardedProps?: Record<string, unknown>;
 }