What is RAG and How it Works - step by step visualisation

Published: 01 January 1970
on channel: TDevelopers

140

Retrieval Augmented Generation (RAG), with the help of RAG you can overcome the limitations of llms and chat with your own documents such as pdf, markdown files.

Timestamps -
0:00 Introduction of RAG
2:38 RAG vs LLMs
3:37 Understanding the architecture of RAG
4:41 Overview of Streamlit, Langchain and Huggingface
6:16 Streamlit python app ui overview
7:46 Step1 - Extracting text from pdf
9:56 Step2 - Creating text chunks
12:24 Step 3&4 - Creating embeddings and storing in vector database
17:50 Understanding similarity search and context
21:15 Final steps - Augmenting the LLM with context and query
24:20 Getting response from chatbot
27:47 Outro

To know more about langchain and document loaders -
https://python.langchain.com/docs/mod...

Steamlit
https://streamlit.io/

Huggingface
https://huggingface.co/

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