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rag/overviewRAG
Python12 challenges8 skillsupdated 8 days ago
Founded
2020
Creator
Patrick Lewis et al.
// what we offer
Hands-on RAG exercises that mirror real engineering work — from core fundamentals to the patterns interviewers actually probe. Every challenge is graded automatically and mapped to a skill below.
// what is it
Retrieval-Augmented Generation puts a search step in front of the model: chunk the source material, embed it, retrieve what matches the question, and pass that to the model as context. Most of the difficulty is in retrieval quality rather than generation - chunk sizes, embedding choice, reranking, and knowing when the retrieved context does not actually answer the question.
// environment
// skills covered
chunking strategiesembeddingsvector searchrerankinghybrid searchcontext windowscitation and groundingretrieval evaluation
// companies using it
Doordash
Grab// deep-dive topics