Evaluation of QA systems built on LlamaIndex
summary
Builds a QA pipeline on LlamaIndex that chunks documents into nodes and wires them to LLMs; index creation and a query loop run in four lines of code. Questions are auto‑generated with GPT‑3 (default five questions per chunk) and answers are checked with a GPT‑4‑based evaluator that compares response text, response source, and query+source alignment (response vs source evaluation). Demonstrates a production use (Albus HR/recruitment bot) and shows how to surface only supporting source documents to reduce hallucination.
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chapters (8)
- 0:00LlamaIndex and QA systems intro
- 2:34Core components of LlamaIndex
- 6:31QA system in 4 lines of code
- 10:23Evaluating QA responses
- 14:44Demo of evaluation
- 20:21Validating answers and reasoning
- 24:43Token limits and chunking
- 30:38How nodes work in indexing
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