Minimemory icon

Minimemory

Embedded vector database for similarity search - no server required

Insert Vector

AI-generated

Summary

Inserts a vector embedding into an in-memory database along with a unique identifier and optional metadata.

Inputs

  • databaseName (required) — Name of the target in-memory database instance.
  • vectorId (required) — Unique identifier to assign to the vector.
  • vector (required) — JSON array of numerical values representing the vector embedding.
  • metadata — Optional JSON object containing key-value metadata to store alongside the vector.

Output shape

a single record

Returns a JSON object with success status, operation name, vector ID, vector dimension count, metadata status, and total vector count in the database.

Examples

Example 1: Insert an embedding generated from a previous step

Set Database Name to 'default', Vector ID to '={{ $json.id }}', Vector to '={{ $json.embedding }}', and Metadata to '={{ { title: $json.title } }}'

Discussion