Building a production-ready RAG pipeline

Large Language Models (LLMs) often hallucinate when lacking current context or specific knowledge. Retrieval-Augmented Generation (RAG) fixes this by providing LLMs with external, relevant data, enabling them to generate accurate responses; the author built Keystone to apply RAG to GitHub repository activity.