AI Solution

Enterprise Knowledge Q&A with RAG and OCI Generative AI

Introduction

It’s not enough to have answers—they have to be accessible and easy to retrieve by users. Large organizations with many moving parts face a particular challenge keeping up with Q&A systems over time. That’s where OCI Generative AI and retrieval-augmented generation (RAG) can step in to help create friendlier systems with more frequent updates based on new web pages.

In this demo, we’ll create a RAG model using OCI Generative AI, LlamaIndex, Qdrant vector database, and SentenceTransformerEmbeddings. This 21-line code will allow you to scrape web pages and use LlamaIndex for indexing, OCI Generative AI for question generation, and Qdrant for vector indexing.

Demo

Demo: Enterprise Knowledge Q&A with RAG and OCI Generative AI (1:28)

Prerequisites and setup

  1. Oracle Cloud account—sign-up page
  2. Getting started with OCI Generative AI—documentation
  3. LlamaIndex—documentation
  4. LangChain—documentation
  5. Qdrant vector similarity search engine—documentation
  6. SentenceTransformers—documentation

注:为免疑义,本网页所用以下术语专指以下含义:

  1. Oracle专指Oracle境外公司而非甲骨文中国。
  2. 相关Cloud或云术语均指代Oracle境外公司提供的云技术或其解决方案。