How I Made a $6758 RAG AI Chatbot Read 100,000 Pages using FREE Vector Database!

About this Video

• Video Title: How I Made a $6758 RAG AI Chatbot Read 100,000 Pages using FREE Vector Database!
• Channel: The Metaverse Guy
• Speakers: The Metaverse Guy
• Duration: 00:05:51

Introduction

This video demonstrates how to build a RAG (Retrieval Augmented Generation) AI chatbot capable of processing over 100,000 pages of data from 500 PDF files, all while utilizing a free vector database. The speaker emphasizes the importance of accuracy and avoiding hallucinations in this corporate-level tool, which is used for legal information retrieval. The video focuses on using Quadrant (qd.te) as a free alternative to paid services like Pinecone.

Key Takeaways

• A RAG AI chatbot was built to process over 100,000 pages from 500 PDF files.
• Accuracy and the avoidance of hallucinations are crucial for the chatbot's intended use.
• Quadrant (qd.te) is presented as a free vector database alternative to Pinecone.
• A Python script is provided on GitHub to facilitate uploading files to Quadrant.
• The video shows how to use Quadrant's free tier to handle a large number of files.