Reranking

A reranker scores an existing candidate set against one query. Unlike vector search, it does not require you to generate or store embeddings.

let result = try await rerank(
  model: CohereRerankingModel("rerank-v4-fast"),
  query: "warm places in january",
  documents: candidates,
  topN: 5
)

for item in result.rankedDocuments {
  print(item.relevanceScore, item.document)
}

Each result includes document, relevanceScore, and index, which points back to the document's position in the original array. An empty document list returns an empty result.

The built-in reranker is CohereRerankingModel; it reads COHERE_API_KEY. See the Cohere provider page for its chat, embedding, and reranking model types.

For vector generation and local similarity scoring, see embeddings.