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Metadata lets you attach up to 256KB of structured data to a run and update it while the task runs. Subscribers (via React hooks or backend) get those updates in real time, making metadata the simplest way to build progress bars, status indicators, and live dashboards. You can access metadata from inside the run function, via the API, Realtime, and in the dashboard. Common uses: progress percentage, current step, user context, intermediate results.

Usage

Add metadata to a run when triggering by passing it as an object to the trigger function:
You can get the current metadata at any time by calling metadata.get() or metadata.current() (only inside a run):
Any of these methods can be called anywhere “inside” the run function, or a function called from the run function:
If you call any of the metadata methods outside of the run function, they will have no effect:
This means it’s safe to call these methods anywhere in your code, and they will only have an effect when called inside the run function.
Calling metadata.current() or metadata.get() outside of the run function will always return undefined.
These methods also work inside any task lifecycle hook, either attached to the specific task or the global hooks defined in your trigger.config.ts file.

Updates API

One of the more powerful features of metadata is the ability to update it as the run progresses. This is useful for tracking the progress of a run, storing intermediate results, or storing any other information that changes over time. (Combining metadata with Realtime can give you a live view of the progress of your runs.) All metadata update methods (accept for flush and stream) are synchronous and will not block the run function. We periodically flush metadata to the database in the background, so you can safely update the metadata inside a run as often as you need to, without worrying about impacting the run’s performance.

set

Set the value of a key in the metadata object:

del

Delete a key from the metadata object:

replace

Replace the entire metadata object with a new object:

append

Append a value to an array in the metadata object:

remove

Remove a value from an array in the metadata object:

increment

Increment a numeric value in the metadata object:

decrement

Decrement a numeric value in the metadata object:

stream

As of SDK version 4.1.0, metadata.stream() has been replaced by Realtime Streams v2. We recommend using the new streams.pipe() API for better reliability, unlimited stream length, and improved developer experience. The examples below are provided for backward compatibility.
Capture a stream of values and make the stream available when using Realtime. See our Realtime Streams v2 documentation for the recommended approach.
metadata.stream accepts any AsyncIterable or ReadableStream object. The stream will be captured and made available in the Realtime API. So for example, you could pass the body of a fetch response to metadata.stream to capture the response body and make it available in Realtime:
Or the results of a streaming call to the OpenAI SDK:

flush

Flush the metadata to the database. The SDK will automatically flush the metadata periodically, so you don’t need to call this method unless you need to ensure that the metadata is persisted immediately.

Fluent API

All of the update methods can be chained together in a fluent API:

Parent & root updates

Tasks that have been triggered by a parent task (a.k.a. a “child task”) can update the metadata of the parent task. This is useful for propagating progress information up the task hierarchy. You can also update the metadata of the root task (root = the initial task that was triggered externally, like from your backend). To update the parent task’s metadata, use the metadata.parent accessor:
All of the update methods are available on metadata.parent and metadata.root:
You can also chain the update methods together:

Example

An example of where you might use parent and root updates is in a task that triggers multiple child tasks in parallel. You could use the parent metadata to track the progress of the child tasks and update the parent task’s progress as each child task completes:
Combined with Realtime, you could use this to show a live progress bar of the CSV processing in your frontend, like this:

More metadata task examples

Using metadata updates in conjunction with our Realtime React hooks can be a powerful way to build real-time UIs. Here are some example tasks demonstrating how to use metadata in your tasks to track progress, status, and more:

Progress tracking

Track progress with percentage and current step:

Status updates with logs

Append log entries while maintaining status:

User context and notifications

Store user information and notification preferences:

Metadata propagation

Metadata is NOT propagated to child tasks. If you want to pass metadata to a child task, you must do so explicitly:

Type-safe metadata

The metadata APIs are currently loosely typed, accepting any object that is JSON-serializable:
If you pass in an object like a Date, it will be serialized to a string when stored in the metadata. That also means that when you retrieve it using metadata.get() or metadata.current(), you will get a string back. You will need to deserialize it back to a Date object if you need to use it as a Date.
We recommend wrapping the metadata API in a Zod schema (or your validator library of choice) to provide type safety:

Inspecting metadata

Dashboard

You can view the metadata for a run in the Trigger.dev dashboard. The metadata will be displayed in the run details view: View run metadata dashboard

API

You can use the runs.retrieve() SDK function to get the metadata for a run:
See the API reference for more information.

Size limit

The maximum size of the metadata object is 256KB. If you exceed this limit, the SDK will throw an error. If you are self-hosting Trigger.dev, you can increase this limit by setting the TASK_RUN_METADATA_MAXIMUM_SIZE environment variable. For example, to increase the limit to 16KB, you would set TASK_RUN_METADATA_MAXIMUM_SIZE=16384.