Module knn

A k-nearest neighbor (kNN) search finds the k nearest vectors to a query vector, as measured by a similarity metric.

Common use cases for kNN include:

• Relevance ranking based on natural language processing (NLP) algorithms
• Product recommendations and recommendation engines
• Similarity search for images or videos

https://www.elastic.co/guide/en/elasticsearch/reference/current/knn-search.html#approximate-knn

Structs

Knn

Performs a k-nearest neighbor (kNN) search and returns the matching documents.

TextEmbedding

The natural language processing task to perform.

Enums

QueryVectorBuilder

A configuration object indicating how to build a query_vector before executing the request.