Mastering LLM Chatbot Testing: Metrics, Methods and Mistakes to Avoid
summary
15 minutes that maps practical failures to the actual pieces to test: routing to multiple micr‑chatbots via a knowledge graph, verifying logged SQL from text-to-SQL flows, measuring RAG quality with vector DB chunk size and cosine similarity, and gating releases with Rouge and BLEU thresholds against an approved‑answers baseline. Covers non‑determinism (temperature tuning), testing tricky entity routing (Apple fruit vs company), guardrail rules for hallucinations, and verifying citations and entitlement checks.
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chapters (5)
- 0:00Introduction to LLM testing
- 1:33Core chatbot components
- 3:54Prompting and data retrieval
- 7:25Performance metrics
- 9:26Guardrails and conclusion
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