Large Language Model Knowledge Base Q&A Guide

This guide outlines the process for developing a knowledge base Q&A model utilizing large language models (LLMs) within Databricks Professional Services. It begins by explaining the necessity of specialized language models tailored to specific business needs, particularly in natural language processing applications. The guide details the steps involved in building a prototype model, including data cleaning, vector database creation, and model fine-tuning. It emphasizes the importance of collaboration with domain experts for effective model evaluation and provides a clear strategy for implementing a knowledge base Q&A system. Additionally, the guide identifies prerequisites for successful implementation, such as data accessibility and the involvement of subject matter experts. It also discusses potential challenges, including data set construction and model evaluation, while noting that certain aspects, like integration with non-Databricks products, are out of scope. The document aims to enhance developer productivity and reduce time to market while ensuring data security.