---
prelude: >
    We're introducing a new ranker to Haystack - DiversityRanker. This
    ranker aims to maximize the overall diversity of the given documents.
    It leverages sentence-transformer models to calculate semantic embeddings
    for each document. It orders documents so that the next one, on average,
    is least similar to the already selected documents. Such ranking results in a
    list where each subsequent document contributes the most to the overall
    diversity of the selected document set.
features:
  - |
    The DiversityRanker can be used like other rankers in Haystack and
    it can be particularly helpful in cases where you have highly relevant
    yet similar sets of documents. By ensuring a diversity of documents,
    this new ranker facilitates a more comprehensive utilization of the
    documents and, particularly in RAG pipelines, potentially contributes
    to more accurate and rich model responses.
