BM25S provides an efficient implementation of BM25, a classic probabilistic ranking function for keyword-based text retrieval. The library leverages sparse matrices and Numba JIT compilation to achieve high performance for document ranking tasks. It is frequently used as the retrieval backend in Retrieval-Augmented Generation (RAG) pipelines alongside vector search systems.