Case Study, Developing a Q&A System Using Vector DB and LLM
September 17, 2023
Methods to overcome the limitations of Large Language Models (LLMs) by utilizing Vector Databases (VectorDBs) are gaining attention. To provide accurate answers on specialized information such as law firm case precedents or company communication records—domain data that is not included in the training data—we can use a Vector Database that can convert, store, and search all kinds of data into vector embeddings, serving as a long-term memory storage for LLMs. To illustrate this, we examine a concrete case of how a vector database can complement an LLM through processes like data preprocessing, vectorization, storage, and search, using a Q&A system based on Wikipedia.