Leveraging Documents and Data to Create a Custom LLM Chatbot | Real Python Podcast #199
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
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