Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

LangChain Multi-Query Retriever for RAG - Advanced Technique for Broader Vector Space Search

James Briggs via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore an advanced Retrieval-Augmented Generation (RAG) technique called "Multi-Query" in LangChain through this 19-minute video tutorial. Learn how to broaden search scores by using an LLM to transform a single query into multiple queries, enabling a more comprehensive vector space search and diverse result set. Follow along as the instructor demonstrates the implementation using OpenAI's text-embedding-ada-002, gpt-3.5-turbo, Pinecone vector database, and the LangChain library. Discover the process of creating a LangChain MultiQueryRetriever, adding generation capabilities, utilizing Sequential Chain for RAG, customizing the Multi-Query approach, reducing hallucination, and integrating Multi-Query into a larger RAG pipeline. Gain practical insights into enhancing AI-powered information retrieval and generation systems.

Syllabus

LangChain Multi-Query
What is Multi-Query in RAG?
RAG Index Code
Creating a LangChain MultiQueryRetriever
Adding Generation to Multi-Query
RAG in LangChain using Sequential Chain
Customizing LangChain Multi Query
Reducing Multi Query Hallucination
Multi Query in a Larger RAG Pipeline

Taught by

James Briggs

Reviews

Start your review of LangChain Multi-Query Retriever for RAG - Advanced Technique for Broader Vector Space Search

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.