How do you customize a LLM chatbot to address a collection of documents and data? What tools and techniques can you use to build embeddings into a vector database? This week on the show, Calvin Hendryx-Parker is back to discuss developing an AI-powered, Large Language Model-driven chat interface. 👉 Links from the show: https://realpython.com/podcasts/rpp/199/ Calvin is the co-founder and CTO of Six Feet Up, a Python and AI consultancy. He shares a recent project for a family-owned seed company that wanted to build a tool for customers to access years of farm research. These documents were stored as brochure-style PDFs and spanned 50 years. We discuss several of the tools used to augment a LLM. Calvin covers working with LangChain and vectorizing data with ChromaDB. We talk about the obstacles and limitations of capturing documentation. Calvin also shares a smaller project that you can try out yourself. It takes the information from a conference website and creates a chatbot using Django and Python prompt-toolkit. This episode is sponsored by Mailtrap. Topics: - 00:00:00 -- Introduction - 00:02:21 -- Background on the project - 00:03:51 -- Complexity of adding documents - 00:09:01 -- Retrieval-augmented generation and providing links - 00:13:46 -- Updating information and larger conversation context - 00:18:08 -- Sponsor: Mailtrap - 00:18:43 -- Working with context - 00:21:02 -- Temperature adjustment - 00:22:07 -- Rally Conference Chatbot Project - 00:26:20 -- Vectorization using ChromaDB - 00:32:49 -- Employing Python prompt-toolkit - 00:35:07 -- Learning libraries on the fly - 00:37:38 -- Video Course Spotlight - 00:39:00 -- Problems with tables in documents - 00:42:30 -- Everything looks like a chat box - 00:44:26 -- Finding the right fit for a client and customer - 00:49:05 -- What are questions you ask a new client now? - 00:51:54 -- Canada Air anecdote - 00:56:20 -- How do you stay up to date on these topics? - 01:01:03 -- What are you excited about in the world of Python? - 01:03:22 -- What do you want to learn next? - 01:04:58 -- How can people follow your work online? - 01:05:31 -- IndyPy - 01:07:13 -- Thanks and goodbye 👉 Links from the show: https://realpython.com/podcasts/rpp/199/