想在企业级玩转RAG？AWS用Bedrock、Neptune和PageRank搭了一套HippoRAG，让检索更聪明、更精准。
HippoRAG是一种受神经生物学启发的检索增强生成方法，结合图数据库和个性化PageRank算法。文章展示了在AWS上使用Amazon Bedrock提供大语言模型能力，Amazon Neptune作为图数据库，Neptune Analytics运行个性化PageRank计算，以及Amazon Titan Embeddings生成向量表示。该实现面向企业级应用，可提升检索的精度与效率。
HippoRAG: Neurobiologically inspired RAG using Amazon Bedrock, Amazon Neptune, and personalized PageRank
In this post, we demonstrate how to implement HippoRAG using a comprehensive AWS stack. We use Amazon Bedrock for LLM capabilities, Amazon Neptune for graph database functionality, Amazon Neptune Analytics for advanced graph algorithms including Personalized PageRank, and Amazon Titan Embeddings for vector representations. This implementation showcases how to build and deploy HippoRAG within AWS infrastructure for enterprise-scale applications.