A ChatGPT on your own data: how does it work?
summary
Describes how to build a ChatGPT-like chatbot that answers questions using an organization's own documents by ingesting and indexing those files for retrieval-augmented generation with large language models (LLMs). Covers practical details on system design, costs, and usage scenarios such as turning complex software documentation into an interactive assistant to speed up information search.
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chapters (10)
- 0:00Introduction
- 3:48Chatbot demo
- 8:44RAG technical overview
- 16:28From extraction to answer
- 24:48Costs and optimization
- 31:46LLM key parameters
- 33:13Performance evaluation
- 34:36Production tools
- 35:57Experience feedback
- 41:54Q&A
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