Welcome to Episode 6 of Bill's Guide to AI! In this episode, Bill walks us through the process of converting content into vector embeddings, using the Ultimate Go notebook as an example, and preparing it for integration with large language models (LLMs). This episode serves as the foundation for building a responsive chat application that can answer questions intelligently based on its content. Bill explains the “chunking” process, a crucial step where data from the Ultimate Go notebook is divided into context-based chunks. He demonstrates the art of determining chunk sizes to ensure both performance and context relevance, providing an approach that relies on structuring data by key sections of the book. Bill then takes us through the vectorization process using Olamma’s embed-large model to create embeddings for each chunk, saving these as JSON objects. Normally, these embeddings would go directly into a vector database like MongoDB, but Bill temporarily writes them to disk to illustrate each step in detail. With the embeddings prepared, Bill then sets up MongoDB as the vector database and configures it to store and index the chunk embeddings. He highlights the importance of dimension matching in embeddings, noting that the number of dimensions impacts both performance and accuracy. By the end of this episode, you will have a clear roadmap for preparing text-based data for LLM interactions, which will culminate in the next episode’s chat application project. Things you will learn in this video: - Setting up OLAMA: Running a local LLM server and using LangChain Go to interact with models. - Effective Prompt Engineering: Structuring prompts for optimal LLM responses and managing context. - Real-Time Responses: Using the streaming API to enhance user experience with tokenized replies. Comment below or tweet us on twitter & let us know your thoughts, we want to hear from you! ~ If you found this video helpful, hit that like button & subscribe for more content like this. ---- Access our online courses → https://www.ardanlabs.com/education/ Attending a live training → https://www.ardanlabs.com/live-training-events/ Other Links: Website: https://www.ardanlabs.com/ Github: https://github.com/ardanlabs Twitter: https://twitter.com/ardanlabs #A.I #programming #education #tutorials #tips