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Embed records

Chunk text records per document and embed each chunk through Knowledge.

Chunk text records per document and embed each chunk through Knowledge.

When to use it

Create searchable representations of document text in chunks. Choose a compatible embedding model and destination. A new model or chunking strategy can require reindexing; semantic similarity does not verify that a retrieved passage answers a question correctly.

Add and configure

  1. Add Embed records from the workflow step picker.
  2. Give the step a recognisable name and connect its required inputs.
  3. Set the options below. Nested names identify fields within an object or a list item.
  4. Validate the recipe, inspect the test result, then run it on the intended data.

The step identifier used in the editor’s code view is embed.

Settings

SettingAccepted valueRequiredDefaultWhat it controls
Batch Size (batch_size)integer; minimum 1; maximum 500No128Maximum chunk texts submitted together for embedding; at most 500 per batch.
Embedding Profile (embedding_profile)string or nullNonullEmbedding configuration shared by indexing and retrieval. Compatible profiles are needed to compare vectors meaningfully.
Generation Model (generation_model)string or nullNonullModel choice used when generating content associated with this embedding task.
Group By Field (group_by_field)stringNo"object_key"Record field that scopes chunk identity (one document per group). Records missing it group under 'ungrouped'.
Include Breadcrumbs (include_breadcrumbs)booleanNotruePrefix each chunk with its heading path ('A > B').
Max Tokens (max_tokens)integer; minimum 64; maximum 2000No480Token budget per chunk.
Min Chunk Tokens (min_chunk_tokens)integer; minimum 0No120Trailing chunks under this merge into their predecessor (same heading).
Model (model)string or nullNonullOptional embedding model selection. It must match the embedding configuration available to your organisation. Leave unset to use that default.
Order By Field (order_by_field)stringNo"index"Record field that orders segments within a group.
Overlap Tokens (overlap_tokens)integer; minimum 0; maximum 512No64Tokens shared between consecutive parts of a split chunk.
Record Type (record_type)stringNo"embedded_chunk"record_type stamped on every emitted record.
Text Field (text_field)stringNo"text"Record field holding the text to chunk and embed.

Inputs and outputs

DirectionPortContentRequiredMultiple records
InputsinrecordsYesYes
Outputsoutembedded_chunkYesYes

Outputs record fields

SettingAccepted valueRequiredDefaultWhat it controls
dimensions (dimensions)integer or nullNoNot specified—
embedding (embedding)list of numberYesNot specified—
meta (meta)objectNoNot specified—
model (model)string or nullNoNot specifiedProvider-qualified model identifier for the operation.
ref (ref)string; minimum characters 1YesNot specified—
text (text)stringNoNot specified—

Effects, testing, and recovery

Calls a model and can consume model budget.

The declared preview behaviour is to execute this step. Reads, processing, or model usage can therefore be real. Read dry runs before using a preview with live connections.

No duplicate-prevention key is declared for this step. Do not assume that manually repeating the step is free of repeated effects.

Example: Embed digest segments grouped by file (defaults)

Step settings:

{
  "group_by_field": "object_key",
  "text_field": "text"
}

Example: Smaller chunks with a wider overlap

Step settings:

{
  "max_tokens": 256,
  "min_chunk_tokens": 64,
  "overlap_tokens": 48
}

Check the result

Inspect the selected run’s status, counts, errors, and output records. An empty collection can be a valid result, and a completed step can contain per-record failures where the step defines that behaviour. Check the next step’s expected record shape before publishing or delivering the result.