In my previous posts, I have walked you through putting together a very basic RAG pipeline in Python, as well as chunking large text documents. We’ve also looked into how documents are transformed into embeddings, allowing us to quickly search for similar documents within a vector database, along with how reranking is used to identify … Continue reading How to Evaluate Retrieval Quality in RAG Pipelines: Precision@k, Recall@k, and F1@k