--- title: "Actions" sidebarTitle: "Actions" description: "Custom commands sent from the frontend that mutate chat state without consuming a turn — undo, rollback, edit, regenerate." --- ## Overview Custom actions let the frontend send structured commands (undo, rollback, edit, regenerate) that modify the conversation state. **Actions are not turns**: they fire `hydrateMessages` (if set) and `onAction` only. No turn lifecycle hooks (`onTurnStart` / `prepareMessages` / `onBeforeTurnComplete` / `onTurnComplete`), no `run()`, no turn-counter increment. The trace span is named `chat action`. Actions wake the agent from suspension the same way a new message does, run their handler against the latest accumulator state, and emit a `trigger:turn-complete` chunk so the frontend's `useChat` knows the action has been applied. ## Defining an action handler Define an `actionSchema` for validation and an `onAction` handler that uses [`chat.history`](/ai-chat/backend#chat-history) to modify state: ```ts import { z } from "zod"; export const myChat = chat.agent({ id: "my-chat", actionSchema: z.discriminatedUnion("type", [ z.object({ type: z.literal("undo") }), z.object({ type: z.literal("rollback"), targetMessageId: z.string() }), z.object({ type: z.literal("edit"), messageId: z.string(), text: z.string() }), ]), onAction: async ({ action }) => { switch (action.type) { case "undo": chat.history.slice(0, -2); // Remove last user + assistant exchange break; case "rollback": chat.history.rollbackTo(action.targetMessageId); break; case "edit": chat.history.replace(action.messageId, { id: action.messageId, role: "user", parts: [{ type: "text", text: action.text }], }); break; } // returning void → side-effect-only, no model call }, run: async ({ messages, signal }) => { return streamText({ model: anthropic("claude-sonnet-4-5"), messages, abortSignal: signal }); }, }); ``` **Lifecycle flow:** Wake → parse action against `actionSchema` → `hydrateMessages` (if set) → **`onAction`** → apply `chat.history` mutations → emit `trigger:turn-complete` → wait for next message. ## Returning a model response from an action `onAction` can return a `StreamTextResult`, `string`, or `UIMessage` to produce a response. The returned stream is auto-piped to the frontend just like a normal turn, but the rest of the turn machinery (`onTurnStart`, `onTurnComplete`, etc.) still does not fire. ```ts onAction: async ({ action, messages }) => { if (action.type === "regenerate") { chat.history.slice(0, -1); // drop the last assistant return streamText({ model: anthropic("claude-sonnet-4-5"), messages, stopWhen: stepCountIs(15), }); } // other actions return void → side-effect only } ``` This is useful for actions that both mutate state and want a fresh model response (regenerate-from-here, retry-with-different-style). Persistence is your responsibility inside `onAction` itself; you have access to the streamed response object. ## Gating actions on HITL state If you have a [human-in-the-loop](/ai-chat/patterns/human-in-the-loop) tool waiting on `addToolOutput`, you usually want to refuse competing actions like `regenerate` until the answer arrives. [`chat.history.getPendingToolCalls()`](/ai-chat/backend#chat-history) gives you exactly that signal: ```ts onAction: async ({ action, messages, signal }) => { if (action.type === "regenerate") { if (chat.history.getPendingToolCalls().length > 0) return; // gated chat.history.slice(0, -1); return streamText({ model: anthropic("claude-sonnet-4-5"), messages, abortSignal: signal }); } }, ``` ## Sending actions from the frontend ```ts // Browser — TriggerChatTransport const stream = await transport.sendAction(chatId, { type: "undo" }); // Server — AgentChat const stream = await agentChat.sendAction({ type: "rollback", targetMessageId: "msg-3" }); ``` The action payload is validated against `actionSchema` on the backend; invalid actions throw and surface as a stream error. The `action` parameter in `onAction` is fully typed from the schema. For silent state changes that should never appear as a turn (e.g. injecting background context), use [`chat.inject()`](/ai-chat/background-injection) instead. Actions are explicit user-driven mutations; injections are agent-side context updates. ## See also - [`chat.history`](/ai-chat/backend#chat-history) — the imperative API actions use to mutate state - [Sending actions from the frontend](/ai-chat/frontend#sending-actions) — `transport.sendAction` ergonomics - [`hydrateMessages`](/ai-chat/lifecycle-hooks#hydratemessages) — fires before `onAction` when set - [Branching conversations](/ai-chat/patterns/branching-conversations) — pairs action handlers with backend-controlled history - [Human-in-the-loop](/ai-chat/patterns/human-in-the-loop) — gating fresh actions while a tool is waiting