triggerdotdev--trigger.dev/packages/ai

@trigger.dev/ai

AI SDK integrations for Trigger.dev.

What this package includes

• TriggerChatTransport for wiring AI SDK useChat() to Trigger.dev tasks + Realtime Streams v2
• createTriggerChatTransport(...) factory helper
• ai.tool(...) and ai.currentToolOptions() helpers for tool-calling flows
• helper types such as TriggerChatSendMessagesOptions, TriggerChatReconnectOptions, and TriggerChatHeadersInput

Install

npm add @trigger.dev/ai ai

useChat() transport example

import { useChat } from "@ai-sdk/react";
import { TriggerChatTransport } from "@trigger.dev/ai";
import { aiStream } from "@/app/streams";

export function Chat({ triggerToken }: { triggerToken: string }) {
  const chat = useChat({
    transport: new TriggerChatTransport({
      task: "ai-chat",
      stream: aiStream,
      accessToken: triggerToken,
    }),
  });

  return (
    <button
      onClick={function onClick() {
        chat.sendMessage({ text: "Hello" });
      }}
    >
      Send
    </button>
  );
}

Task payload typing

Use TriggerChatTransportPayload<UIMessage> in your task for the default rich payload:

• chatId
• trigger
• messageId
• messages
• request (headers, body, metadata)

Incoming request.headers can be supplied as a plain object, Headers, or tuple arrays.

Typed request option helper aliases are exported:

• TriggerChatSendMessagesOptions
• TriggerChatReconnectOptions
• TriggerChatHeadersInput
• TriggerChatTransportError / TriggerChatOnError
• normalizeTriggerChatHeaders(...)

import type { TriggerChatTransportPayload } from "@trigger.dev/ai";
import { UIMessage } from "ai";

type Payload = TriggerChatTransportPayload<UIMessage>;

Custom payload mapping

If your task expects a custom payload shape, provide payloadMapper (sync or async):

import { TriggerChatTransport } from "@trigger.dev/ai";
import type { UIMessage } from "ai";

const transport = new TriggerChatTransport<
  UIMessage,
  { prompt: string; tenantId: string | undefined }
>({
  task: "ai-chat-custom",
  accessToken: "pk_...",
  payloadMapper: async function payloadMapper(request) {
    await Promise.resolve();

    const firstPart = request.messages[0]?.parts[0];

    return {
      prompt: firstPart && firstPart.type === "text" ? firstPart.text : "",
      tenantId:
        typeof request.request.body === "object" && request.request.body
          ? (request.request.body as Record<string, string>).tenantId
          : undefined,
    };
  },
});

triggerOptions can also be a function (sync or async), which gives you access to chatId, messages, and request context to compute queueing/idempotency options.

Optional persistent run state

TriggerChatTransport supports custom run stores (including async implementations) to persist reconnect state:

import type { TriggerChatRunState, TriggerChatRunStore } from "@trigger.dev/ai";

class MemoryStore implements TriggerChatRunStore {
  private runs = new Map<string, TriggerChatRunState>();

  async get(chatId: string) {
    return this.runs.get(chatId);
  }

  async set(state: TriggerChatRunState) {
    this.runs.set(state.chatId, state);
  }

  async delete(chatId: string) {
    this.runs.delete(chatId);
  }
}

onTriggeredRun can also be async, which is useful for persisting run IDs before the chat stream is consumed. Callback failures are ignored so chat streaming can continue.

You can optionally provide onError to observe non-fatal transport errors (for example callback failures or reconnect setup issues).

The callback receives:

• phase: "payloadMapper" | "triggerOptions" | "triggerTask" | "onTriggeredRun" | "consumeTrackingStream" | "reconnect"
• chatId
• runId (may be undefined before a run is created)
• error

Reconnect semantics

• reconnectToStream({ chatId }) resumes only while a stream is still active.
• Once a stream completes or errors, its run state is cleaned up and reconnect returns null.
• Provide a custom runStore if you need state shared across processes/instances.

ai.tool(...) example

import { ai } from "@trigger.dev/ai";
import { schemaTask } from "@trigger.dev/sdk";
import { z } from "zod";

const searchTask = schemaTask({
  id: "search",
  schema: z.object({ query: z.string() }),
  run: async function run(payload) {
    return { result: payload.query };
  },
});

const tool = ai.tool(searchTask);

@trigger.dev/sdk/ai remains available for backwards compatibility, but @trigger.dev/ai is the recommended import path.