Eric Allam 08da57dd49 feat(sdk): chat.agent → Sessions migration (phases B + C + min E)
Rewires chat.agent's internal I/O and TriggerChatTransport's send +
subscribe paths onto the Session primitive. Minimum token-scope work
included so the transport's session endpoints actually authenticate.

Phase B — chat.agent internals (ai.ts)

- New ChatInputChunk tagged union (`kind: "message" | "stop"`) —
  replaces the two-stream split (chat-messages + chat-stop) with a
  single Session `.in` channel.
- New chatSessionHandleKey locals slot populated at run start from
  `payload.sessionId ?? payload.chatId`. Every module-level helper
  now resolves to the per-run session handle.
- Module-level `chatStream`, `messagesInput`, `stopInput` become thin
  facades over the session. `chatStream` mirrors
  `RealtimeDefinedStream<UIMessageChunk>` and delegates to
  `handle.out`. `messagesInput` / `stopInput` mirror
  `RealtimeDefinedInputStream<…>` and filter `.in` by kind — the two
  internal `.on()`/`.waitWithIdleTimeout()` callers and the
  `chat.messages` / `chat.createStopSignal` public exposures keep
  their existing shapes.
- Every `streams.writer(CHAT_STREAM_KEY, …)` callsite swaps to
  `chatStream.writer(…)` so all chat output flows through
  `session.out` → `SessionStreamInstance` → direct-to-S2.
- Threaded `sessionId` through `ChatTaskWirePayload` /
  `ChatTaskPayload` / `ChatTaskRunPayload` so advanced users can
  `sessions.open(sessionId)` directly from `run()`.

Phase C — TriggerChatTransport (chat.ts)

- `ChatSessionState` keys durable identity on `sessionId` (friendlyId);
  `runId` becomes an optional hint about whether a run is live.
- `ensureSession(chatId)` lazily upserts the Session via
  `apiClient.createSession({type: "chat.agent", externalId: chatId})`
  on the direct `accessToken` path. Idempotent — two tabs on the
  same chat converge.
- `sendMessages`, `sendPendingMessage`, `stopGeneration`,
  `sendAction` all go through `appendToSessionStream(sessionId, "in",
  serializeInputChunk({kind: …}))` — one endpoint, one tag per
  record.
- SSE subscribe URL moves from `/realtime/v1/streams/{runId}/chat` to
  `/realtime/v1/sessions/{sessionId}/out`. The old run-scoped
  `subscribeToStream` is replaced by `subscribeToSessionStream`.
  Incoming chunks come back as JSON strings on the session channel
  (server wraps records as `{data, id}` on S2), so the subscribe
  loop parses them back into objects to keep the rest of the control
  flow (turn-complete / upgrade-required / skipToTurnComplete)
  unchanged.
- Upgrade-required re-trigger keeps the same Session and swaps only
  the runId + token.
- `getSession` / `setSession` / `setOnSessionChange` / persistence
  shape all grow a `sessionId` field (runId now optional).

Phase E — minimum token scopes

- `chat.createTriggerAction` (server side) now creates the Session
  before triggering so it can (a) thread `sessionId` into the run
  payload and (b) mint a token with both run and session scopes.
  Returns `sessionId` in its result so the transport can skip its
  own `sessions.create` call on the server-side-trigger path.
- `TriggerChatTaskResult` gains optional `sessionId`.
- The two in-run PAT refresh sites (preloadAccessToken,
  turnAccessToken) add `read:sessions:{sessionId}` +
  `write:sessions:{sessionId}` alongside the existing run scopes.

Known follow-ups (deferred to later passes)

- Phase D: `AgentChat` / `ChatStream` in chat-client.ts still uses
  the old `/realtime/v1/streams/{runId}/chat` path. Used by server-
  side task-to-task compositions, not the browser transport.
- Phase F: delete CHAT_STREAM_KEY, CHAT_MESSAGES_STREAM_ID,
  CHAT_STOP_STREAM_ID from chat-constants.ts + ai-chat smoke verify.
2026-05-05 11:06:25 +01:00
2026-05-05 11:06:25 +01:00
2026-05-05 11:06:25 +01:00
2026-05-05 11:06:25 +01:00
2025-06-07 00:57:47 +01:00
2025-08-27 16:52:58 +01:00
2022-12-06 12:28:16 +00:00
2024-08-23 13:10:15 +01:00
2026-05-05 11:06:25 +01:00
2025-03-15 12:20:54 +00:00
2025-12-23 18:37:19 +00:00

Trigger.dev logo

Build and deploy fullymanaged AI agents and workflows

Website | Docs | Issues | Example projects | Feature requests | Public roadmap | Self-hosting

Open Source License npm SDK downloads

Twitter Follow Discord Ask DeepWiki GitHub stars

About Trigger.dev

Trigger.dev is the open-source platform for building AI workflows in TypeScript. Long-running tasks with retries, queues, observability, and elastic scaling.

The platform designed for building AI agents

Build AI agents using all the frameworks, services and LLMs you're used to, deploy them to Trigger.dev and get durable, long-running tasks with retries, queues, observability, and elastic scaling out of the box.

  • Long-running without timeouts: Execute your tasks with absolutely no timeouts, unlike AWS Lambda, Vercel, and other serverless platforms.

  • Durability, retries & queues: Build rock solid agents and AI applications using our durable tasks, retries, queues and idempotency.

  • True runtime freedom: Customize your deployed tasks with system packages run browsers, Python scripts, FFmpeg and more.

  • Human-in-the-loop: Programmatically pause your tasks until a human can approve, reject or give feedback.

  • Realtime apps & streaming: Move your background jobs to the foreground by subscribing to runs or streaming AI responses to your app.

  • Observability & monitoring: Each run has full tracing and logs. Configure error alerts to catch bugs fast.

Key features:

  • JavaScript and TypeScript SDK - Build background tasks using familiar programming models
  • Long-running tasks - Handle resource-heavy tasks without timeouts
  • Durable cron schedules - Create and attach recurring schedules of up to a year
  • Trigger.dev Realtime - Trigger, subscribe to, and get real-time updates for runs, with LLM streaming support
  • Build extensions - Hook directly into the build system and customize the build process. Run Python scripts, FFmpeg, browsers, and more.
  • React hooks - Interact with the Trigger.dev API on your frontend using our React hooks package
  • Batch triggering - Use batchTrigger() to initiate multiple runs of a task with custom payloads and options
  • Structured inputs / outputs - Define precise data schemas for your tasks with runtime payload validation
  • Waits - Add waits to your tasks to pause execution for a specified duration
  • Preview branches - Create isolated environments for testing and development. Integrates with Vercel and git workflows
  • Waitpoints - Add human-in-the-loop judgment at critical decision points without disrupting workflow
  • Concurrency & queues - Set concurrency rules to manage how multiple tasks execute
  • Multiple environments - Support for DEV, PREVIEW, STAGING, and PROD environments
  • No infrastructure to manage - Auto-scaling infrastructure that eliminates timeouts and server management
  • Automatic retries - If your task encounters an uncaught error, we automatically attempt to run it again
  • Checkpointing - Tasks are inherently durable, thanks to our checkpointing feature
  • Versioning - Atomic versioning allows you to deploy new versions without affecting running tasks
  • Machines - Configure the number of vCPUs and GBs of RAM you want the task to use
  • Observability & monitoring - Monitor every aspect of your tasks' performance with comprehensive logging and visualization tools
  • Logging & tracing - Comprehensive logging and tracing for all your tasks
  • Tags - Attach up to ten tags to each run, allowing you to filter via the dashboard, realtime, and the SDK
  • Run metadata - Attach metadata to runs which updates as the run progresses and is available to use in your frontend for live updates
  • Bulk actions - Perform actions on multiple runs simultaneously, including replaying and cancelling
  • Real-time alerts - Choose your preferred notification method for run failures and deployments

Write tasks in your codebase

Create tasks where they belong: in your codebase. Version control, localhost, test and review like you're already used to.

import { task } from "@trigger.dev/sdk";

//1. You need to export each task
export const helloWorld = task({
  //2. Use a unique id for each task
  id: "hello-world",
  //3. The run function is the main function of the task
  run: async (payload: { message: string }) => {
    //4. You can write code that runs for a long time here, there are no timeouts
    console.log(payload.message);
  },
});

Deployment

Use our SDK to write tasks in your codebase. There's no infrastructure to manage, your tasks automatically scale and connect to our cloud. Or you can always self-host.

Environments

We support Development, Staging, Preview, and Production environments, allowing you to test your tasks before deploying them to production.

Full visibility of every job run

View every task in every run so you can tell exactly what happened. We provide a full trace view of every task run so you can see what happened at every step.

Trace view image

Getting started

The quickest way to get started is to create an account and project in our web app, and follow the instructions in the onboarding. Build and deploy your first task in minutes.

Self-hosting

If you prefer to self-host Trigger.dev, you can follow our self-hosting guides:

Support and community

We have a large active community in our official Discord server for support, including a dedicated channel for self-hosting.

Development

To setup and develop locally or contribute to the open source project, follow our development guide.

Meet the Amazing People Behind This Project:

S
Description
Trigger.dev 支持构建和部署完全托管的 AI Agent 与工作流。|GitHub 镜像 16.1k · 🍴 1.4k
https://github.com/triggerdotdev/trigger.dev Readme Apache-2.0 193 MiB
Languages
TypeScript 99.1%
JavaScript 0.4%
Shell 0.2%
CSS 0.1%