Vector search
Find the nearest indexed chunks for each record's query text.
Find the nearest indexed chunks for each record's query text.
When to use it
Retrieve semantically similar indexed chunks for each query. Select the index, result count, and filters appropriate to the task. A high similarity score is a ranking signal, not a factual validation of a generated answer.
Add and configure
- Add Vector search from the workflow step picker.
- Give the step a recognisable name and connect its required inputs.
- Set the options below. Nested names identify fields within an object or a list item.
- 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 vector_search.
Settings
| Setting | Accepted value | Required | Default | What it controls |
|---|---|---|---|---|
Collection (collection) | string; minimum characters 1; maximum characters 128 | No | "default" | Vector-store collection to search within the tenant. |
Embedding Profile (embedding_profile) | string or null | No | null | Embedding configuration shared by indexing and retrieval. Compatible profiles are needed to compare vectors meaningfully. |
K (k) | integer; minimum 1; maximum 100 | No | 5 | Max matches to return per record. |
Min Score (min_score) | number; minimum -1.0; maximum 1.0 or null | No | null | Cosine-similarity floor; matches below it are dropped. |
Query Field (query_field) | string or null | No | null | Record field holding the query text (dotted paths supported, e.g. question). Mutually exclusive with query_template. |
Query Template (query_template) | string or null | No | null | Per-record query template with ${field} placeholders (e.g. ${title} ${body}). Mutually exclusive with query_field. |
Inputs and outputs
| Direction | Port | Content | Required | Multiple records |
|---|---|---|---|---|
| Inputs | in | records | Yes | Yes |
| Outputs | out | records | Yes | Yes |
Effects, testing, and recovery
Reads an external source.
The declared preview behaviour is to execute this step. Reads, processing, or model usage can therefore be real. Read dry runs before using a preview with live connections.
No duplicate-prevention key is declared for this step. Do not assume that manually repeating the step is free of repeated effects.
Example: Five nearest chunks for each record's question
Step settings:
{
"k": 5,
"query_field": "question"
}
Example: Query rendered from two fields, with a similarity floor
Step settings:
{
"collection": "apps-support-kb",
"k": 3,
"min_score": 0.2,
"query_template": "${title} ${body}"
}
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.