Reranking in RAG with Qdrant Vector Database In Retrieval-Augmented Generation (RAG) systems, irrelevant or missing information can throw off your model’s ability to produce accurate, meaningful outputs. One of the best ways to ensure you’re feeding your language model the most relevant, context-rich documents is through reranking. It’s a game-changer. In this guide, we’ll dive into using reranking to boost the relevance of search results in Qdrant. We’ll start with an easy use case...
