Vector Search
Configure dense vector fields for semantic and similarity search using SearchProjectionConfig, with support for cosine, dot product, and L2 norm similarity metrics.
Vector search enables semantic and similarity search by storing embedding vectors alongside traditional text fields. NeoArc Studio configures vector search at the property level via SearchProjectionConfig, allowing each field to define its dimensionality, algorithm profile, and similarity metric.
Configuration Fields
To enable vector search on a property, set searchFieldType to dense_vector and provide the required vector parameters.
Similarity Metrics
The similarityMetric field determines how the search engine calculates distance between vectors.
Engine Support
Configuration Steps
Example Configuration
The following JSON shows a vector search configuration on a property's search projection.
{
"included": true,
"searchFieldType": "dense_vector",
"dimensions": 1536,
"vectorSearchProfile": "my-hnsw-profile",
"similarityMetric": "cosine",
"stored": true,
"indexEnabled": true
}Validation Rules
NeoArc Studio enforces two validation rules specific to vector search fields.