Abstract implementation of a similarity searcher.
Searcher()Finds the k closes neighbors of each instance of embeddings.
Adds documents to the index.
Gets datapoint IDs that match the given metadata filter.
Performs semantic search using auto-generated embeddings.
Performs keyword/full-text search on data fields.
Note: Text search does not support filters. Use semantic_search or vector_search if you need filtering.
Performs hybrid search combining semantic and text search with RRF.
Hybrid search runs both semantic search (with auto-generated embeddings) and text search (keyword matching) in parallel, then combines results using Reciprocal Rank Fusion (RRF) algorithm for optimal ranking.