Measuring RAG Quality With RAGAS and Weights & Biases: Evaluation, Observability, and Cost-Performance Tradeoffs
In Part 1, we covered how Funderburk moves from Jupyter notebooks to a production-ready project structure. Docker, uv, SuperComponents, dual Elasticsearch. Now comes the part that actually tells you if your RAG pipeline is any good: systematic evaluation with RAGAS and continuous monitoring with Weights and Biases.