In Day-1, we understood about the overview of a RAG system and what are its components and how it helps the LLM to generate more accurate and contextual responses. Now, lets see about the storage of the data using Vector Databases. Vector Database Lets assume that we have a PDF with us and this would be considered as our private data. Now I want my LLM to have the context about this PDF, So that I could ask any query related to that PDF and get the response. Now, we need to store this PDF data in a format with which the LLM could fetch the data and give us a relevant responses. Here in this case, Vector Database helps us to store the PDF data in a Numerical format which can be used by the LLM to fetch the relevant data. A vector database stores data in the form of vectors (arrays of numbers). A vector database is a specialized database designed to store and search vector embeddings (numerical representations of data).…