RAG systems depend on high-quality retrieval to surface relevant information. Analyzing how document rankings evolve through multiple re-ranking steps is complex. This article explores ways to collect ranking data and visualize rank changes to optimize retriever effectiveness.

Managing and monitoring the complex behavior of Large Language Models (LLMs) becomes increasingly crucial. LLMOps and LLM Observability provide essential tools for understanding and controlling these models, ensuring their safe and effective deployment. This article delves into the critical aspects of LLM Observability in the realm of generative AI.