Custom columns

Tests evaluate a whole column. When your output is structured — for example, a transcription object with a summary inside it — a test on the output column measures the whole serialized object, not the key you care about. A custom column gives one key a name. It is an RFC 9535 JSONPath expression that points into the output or an input column. Once it exists, you use its name wherever a column name goes: in tests, in filters, and in the records table. For example, a character length test on a custom column measures transcription.summary alone. A custom column belongs to the project. You define it once, and every inference pipeline in the project and every development commit use the same definition, so tests in both monitoring and development mode can target it.

Prerequisites

Data in the project whose output, or one of whose input columns, holds a JSON object or array — or JSON stored as a string. That data can come from an inference pipeline or from a development commit. Path suggestions and the preview both read recent rows.
The Update projects permission to create, edit, and delete custom columns. See Roles and permissions. Without it, the list is read-only.

Create a custom column

Custom columns live under the project’s Settings → Custom columns, one list for the whole project. The Add custom columns entry in the records table’s options menu, on a pipeline or a commit, opens the same page. The New custom column form asks for:

Name — what tests and filters refer to. Use letters, numbers, spaces, underscores, and hyphens, starting with a letter or underscore. Names are unique per project, and a name can’t start with openlayer_ or match a column that already exists in the project’s data.
Source column — the column the path is evaluated against: the output (openlayer_output, the default) or an input column from any of the project’s pipelines or development datasets. In development, openlayer_output is the column your openlayer.json sets as outputColumnName.
Path — a JSONPath relative to the source column, starting with $. Paths seen in recent data are offered as suggestions. Paths inside stringified JSON are not suggested, so type those by hand and check them with the preview.

Example

Suppose each row’s output looks like this:

{
  "transcription": [
    {
      "language": "en-GB",
      "summary": "The caller asked to move their appointment."
    },
    {
      "language": "fr-FR",
      "summary": "L'appelant a demandé à déplacer son rendez-vous."
    }
  ]
}

With Source column set to openlayer_output:

Path	Value on this row
`$.transcription[0].summary`	`The caller asked to move their appointment.`
`$.transcription[?@.language == 'fr-FR'].summary`	`L'appelant a demandé à déplacer son rendez-vous.`
`$.transcription[?@.language == 'en-GB'].summary`	`The caller asked to move their appointment.`

Save the last one as summary_en_gb, and a test on summary_en_gb measures the English summary on every row, whichever position it appears in.

Path syntax

Paths follow RFC 9535 and are at most 512 characters long. The parts you are most likely to need:

Syntax	Selects
`$.a.b`	Key `b` inside key `a`
`$['x-request-id']`	A key that contains hyphens, spaces, or other punctuation
`$.items[0]`, `$.items[-1]`	The first or last array element
`$.items[*].name`	`name` in every element of `items`
`$.items[?@.score > 0.5]`	Elements of `items` that pass a filter expression
`$..summary`	Every `summary` key, at any depth

The path is relative to the source column, so it never repeats the column’s name.

Check the match rate before saving

Select Check path in the form’s Preview section to resolve the path against recent rows from up to five of the project’s data sources: the newest development commit and the pipelines that most recently received data. The preview reports one total, Matched X of Y recent rows, names any source where the path matches no row, and shows a few distinct sample values. That way you catch a path that matches only some row shapes, only some pipelines, or the wrong key.

The preview never blocks saving. A path that matches none of the recent rows is still saved, because a pipeline may not carry the field yet. Tests on the column are skipped wherever the path matches nothing, so read the preview’s warning before you save.

On rows where the path matches nothing, the custom column is empty (null).

When a path matches several values

A path with a wildcard, a filter, or .. can match several values on one row, but a column holds one value per row. The column’s reduction picks it:

Reduction	Value the row holds
`first`	The first match. This is the default.
`last`	The last match.
`longest`	The match with the most characters.
`shortest`	The match with the fewest characters.
`join`	All matches, concatenated with newlines.

Non-string matches are compared and joined as their JSON text. The form saves new columns with first; a column with any other reduction shows it as a tag in the list’s Options column.

Stringified JSON

Some payloads hold JSON as a string, such as {"transcript": "{\"summary\": \"...\"}"}. With Parse stringified JSON on (the default), the path still resolves through those strings:

The path runs against the raw value first. If it matches, that value is used, so a field whose JSON text you want to measure as text stays text.
Only on a miss does Openlayer parse string values that hold a JSON object or array and retry, up to five levels deep. Strings such as "42" or "true" stay strings.

When a path resolves only this way, the preview says Resolves by parsing stringified JSON, and the column shows an unwraps JSON tag in the list.

Use a custom column

Tests — pick the custom column in a test’s column picker. In a tests.json, in development or monitoring mode, use its name as the column value in insightParameters:
tests.json
"insightParameters": [{ "name": "column_name", "value": "summary_en_gb" }]
When the path matches none of the rows a test evaluates, the test is skipped rather than failed, with a message that names the custom column and its path. A data source that doesn’t carry the field yet doesn’t break the test.
Filters — you can filter tests and records on a custom column whose path is a chain of plain keys (such as $.transcription.summary) and that has Parse stringified JSON turned off. Filtering on any other custom column returns an error instead of empty results, and its filter offers no value suggestions.
Records — custom columns appear in the records table and in the record detail, for every pipeline and development commit. A custom column can start out hidden in the table, for example when you saved a column layout before it existed. Enable it in the table’s column options.

Edit a custom column

You can change a custom column’s source column, path, and Parse stringified JSON setting. The name can’t change, because tests refer to the column by name. The edit form lists the tests that use the column. An edit applies to every pipeline and every development test in the project from their next evaluation. Existing test results don’t change.

Delete a custom column

You can’t delete a custom column while any test uses it, archived tests included. The list’s Used by column shows which tests those are. Change those tests to stop using the column, or delete them, and then delete the column. Deleting an inference pipeline doesn’t delete the project’s custom columns.

Limits

Exports do not include custom columns.
Values keep the type they have in your data. A number stored as a string stays a string.

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Other resources

Prerequisites

Create a custom column

Example

Path syntax

Check the match rate before saving

When a path matches several values

Stringified JSON

Use a custom column

Edit a custom column

Delete a custom column

Limits

​Prerequisites

​Create a custom column

​Example

​Path syntax

​Check the match rate before saving

​When a path matches several values

​Stringified JSON

​Use a custom column

​Edit a custom column

​Delete a custom column

​Limits

Prerequisites

Create a custom column

Example

Path syntax

Check the match rate before saving

When a path matches several values

Stringified JSON

Use a custom column

Edit a custom column

Delete a custom column

Limits