This lab is currently in Beta, content may be updated as we refine the material
LABINTERMEDIATE

RAG Evaluation and Testing

Implement automated RAG evaluation with retrieval quality tests, answer relevance scoring, and regression test suites.

45 minutes
ai-infrastructure/rag
RAG Evaluation and Testing - Platform Engineering Hands-On Lab Icon

Lab Overview

🛠 Lab from the AI Platform Engineering Bootcamp. Used in Week 3. Bootcamp landing page: https://academy.tekanaid.com/bootcamps/ai-platform-engineering-bootcamp Parent course(s):

  • Week 3: RAG Architectures and Vector Databases (slug: rag-architectures-103)

🟡 Beta bootcamp lab. Hands-on instructions, check scripts, and solve scripts are in place. Lab is part of the running Platform Assistant capstone arc that grows across all 8 weeks of the bootcamp.

This hands-on lab teaches you to evaluate and test RAG systems.

You'll learn to:

  • Create evaluation datasets with ground truth
  • Implement retrieval quality metrics (Precision, Recall, MRR)
  • Build automated evaluation pipelines
  • Create regression tests for CI/CD integration

This lab ensures your RAG system maintains quality over time.

What You'll Learn

Create evaluation datasets with ground truth test cases

Implement retrieval quality metrics (Precision, Recall, MRR)

Build automated evaluation pipelines for RAG systems

Create regression tests for CI/CD integration

Prerequisites

rag-api-service

Technologies Covered

ragevaluationtestingmetricsci-cd

Part of a Course

This lab is part of the RAG Architectures and Vector Databases course

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