Build experiences that use General RAG

Workflow with the main stages to build an end-to-end experience that calls the General RAG model

Introduction

General RAG capability enables the implementation of RAG (Retrieval Augmented Generation) techniques to surpass the capabilities of LLMs in the development of generic questions use cases (based on FAQs).

Steps in the process

a. Prerequisites: Install and enable

Enable ATRIA components in Aura installer
Publish aura-gateway-api in Kernel

GES team / Kernel DevOps Team

Is aura-gateway-api published in Kernel? If not:
Publish the aura-gateway-api API in Kernel as a prerequisite to call this API

Get a Kernel token

GES team

Check if your Kernel token has already expired. If so:
Get a valid Kernel two-legged token

b. Build experience

Configure, build and test your experience with Generative/RAG