HippoRAG: Neurobiologically inspired RAG using Amazon Bedrock, Amazon Neptune, and personalized PageRank
Quick Answer
HippoRAG leverages Amazon Bedrock for LLMs, Amazon Neptune for graph databases, and Personalized PageRank for advanced analytics, enabling enterprise-scale applications.
Quick Take
HippoRAG leverages Amazon Bedrock for LLMs, Amazon Neptune for graph databases, and Personalized PageRank for advanced analytics, enabling enterprise-scale applications. This AWS stack showcases a robust implementation for deploying neurobiologically inspired models.
Key Points
- Utilizes Amazon Bedrock for large language model capabilities.
- Employs Amazon Neptune for efficient graph database management.
- Integrates Personalized PageRank for advanced graph analytics.
- Supports enterprise-scale applications with robust AWS infrastructure.
- Showcases deployment of neurobiologically inspired models.
Article Excerpt
From source RSS / original summaryIn 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.
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