A-Guide-to-Retrieval-Augmented-LLM
This guide provides a thorough exploration of Retrieval Augmented Large Language Models (LLMs), focusing on alleviating common issues such as hallucinations and outdated information. It examines how integrating LLMs with external retrieval techniques can enhance accuracy and address challenges related to data freshness. It also details core concepts, implementation strategies, and potential applications. By enhancing LLMs' abilities with long-tail knowledge and private data, and improving their source-traceability, this guide provides useful insights for developing efficient retrieval-augmented AI systems. It highlights key components such as data management, indexing, and retrieval processes.
