RAG Evaluation Using DeepEval & Confident AI — Full Tutorial

In this video - I show you how to perform RAG evaluation using DeepEval, the open-source LLM evaluation framework, together with the Confident AI platform. We cover how to integrate DeepEval into a retrieval-augmented generation (RAG) app, set up test cases, pick the right metrics (answer relevancy, faithfulness, contextual precision/recall), run evaluations, and interpret the results. What you’ll learn: 1. Understanding RAG evaluation and why it matters for RAG pipelines 2. Installing and setting up DeepEval in your project 3. Choosing appropriate RAG metrics and thresholds using DeepEval 4. Confident AI 5. Using Confident AI to manage evaluation data, run experiments, track metrics and dashboards 6. Integrating evaluation into your development/CI workflow for RAG apps Resources & links: • Project Git : https://github.com/yashprogrammer/DeepEval.git • RAG Project used : https://github.com/yashprogrammer/document_portal.git • DeepEval GitHub: https://github.com/confident-ai/deepeval.git • Confident AI Evaluation Platform: https://www.confident-ai.com/ Drop a 👍 if you found this useful, and subscribe for more tutorials on AI engineering, prompt-engineering, RAG pipelines and evaluation best-practices. Leave your questions/comments below! #RAGEvaluation #DeepEval #ConfidentAI #LLMEvaluation #RetrievalAugmentedGeneration #AIEngineering