Introducing the hybrid index to enable keyword-aware semantic search

What this post added

Introduced the hybrid vector index, a novel approach to combine dense (semantic) and sparse (keyword) vector representations within a single index. This enables keyword-aware semantic search by allowing users to upload and query with both dense vectors from language models and sparse vectors derived from term frequencies. The API now supports a hybrid endpoint for upserting and querying, accepting both vector types and an 'alpha' parameter to control the weighting between keyword and semantic relevance. This simplifies hybrid search implementation by eliminating the need for separate keyword and vector search systems and a reranking system.