Reciprocal Rank Fusion for Hybrid Search
Reciprocal Rank Fusion merges two ranked lists without tuning score weights. The RRF formula, why the k constant matters, and how to run it in OpenSearch.
Reciprocal Rank Fusion merges two ranked lists without tuning score weights. The RRF formula, why the k constant matters, and how to run it in OpenSearch.
Vector search misses chunks that lost their document context. Contextual Retrieval prepends a short LLM-written summary to each chunk before you embed it.
Change an OpenSearch mapping without dropping writes or serving stale data. A step-by-step reindex with aliases, the Reindex API, and the failure modes.
Chunking a document for RAG strips each piece of its context. Contextual retrieval adds an LLM-written note to every chunk before you index it.
The embedding model sets the ceiling on RAG retrieval quality. How to choose one by task fit, sequence length, dimensions, and domain, plus the silent bugs.