Despite being a fairly new offering, vector database vendors have sprung up like wild mushrooms after the rain. As of this writing there are more than 20 vector database vendors, each offering different options and prices.
This publication combines vector database, RAG and LLM for processing and retrieval of a set of publicly accessible publications related to vector database offerings.
This project uses RAG and vector database to embed the selected publications and to provide AI-enabled search functionality of these publications.
The system will enable users to perform searches related to current vector database offerings.
The system allows for loading both, Text (.txt) and PDF (.pdf), documents.