RAG App on AWS icon

RAG App on AWS

Deploys a complete AWS backend infrastructure for retrieval-augmented generation applications, integrating with Gemini Pro and a Streamlit UI.

About

This tool provides a Terraform-based solution for deploying a complete AWS backend service, ideal for building Retrieval-Augmented Generation (RAG) applications. By integrating Google's free-tier Gemini Pro and Embedding models, it allows for AI-powered document querying. Key components include a Streamlit UI for interaction and a Remote Streamable HTTP-based Web Search MCP Server. It offers a streamlined approach to setting up the necessary infrastructure for document processing, semantic search, and AI-driven question answering.

Key Features

  • Infrastructure as Code (IaC) with Terraform for consistent deployments
  • Integrates with Google's Gemini Pro and Embedding models
  • Includes a Streamlit UI with token-based authentication
  • Leverages AWS Lambda for serverless compute
  • Utilizes PostgreSQL RDS with pgvector for vector storage
  • 19 GitHub stars

Use Cases

  • Deploying scalable RAG infrastructure on AWS
  • Creating a secure and authenticated document processing pipeline
  • Building AI-powered document querying applications