Elastic RAG Demo
Contents
- Summary
- Architecture
- Features
- Prerequisites
- Installation
- Usage
Summary
This is a demo of usage of Elastic as a vector store for Retrieval Augmented Generation (RAG) for this scenario:
- Pure LangChain Expression Language (LCEL) chain with no safeguards on user or LLM interactions
- Content from the Elastic online documentation of Elastic Vector Search is used for the RAG content.
Architecture
Features
- Elastic Search for the vector store
- Python Bot server (Chainlit)
- LangChain implementation of RAG with Elastic
Prerequisites
- OpenAI API key
- docker compose
Installation
git clone https://github.com/joeywhelan/es-rag.git && cd es-rag
- Edit the .env_template file with your OpenAI key, Elastic Cloud ID, and Elastic Cloud API Key and rename the file to .env
Usage
Start Up
Shut Down
