Weaviate, a vector database, introduced reranking at the second stage in version 1.20. This feature allows users to improve search relevance by adding reranking to the second-stage of their search process. Cohere's rerank endpoint enables users to build search systems that add reranking at the last stage, and fine-tuning boosts the model's performance in unique domains. The blog post demonstrates how to fine-tune Cohere's reranker model using Weaviate's blogs dataset and DSPy's signature and chain-of-thought module. It also explains how to re-index data with a new schema that includes the fine-tuned model ID, and how to query the database with and without reranking.