  This paper demonstrates RAGE, an interactive tool for explaining Large
Language Models (LLMs) augmented with retrieval capabilities; i.e., able to
query external sources and pull relevant information into their input context.
Our explanations are counterfactual in the sense that they identify parts of
the input context that, when removed, change the answer to the question posed
to the LLM. RAGE includes pruning methods to navigate the vast space of
possible explanations, allowing users to view the provenance of the produced
answers.
