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#retrieval (3)

Cheat sheets (3)

RAG Implementation Checklist

End-to-end checklist and code for building reliable Retrieval-Augmented Generation pipelines — chunking, embedding, vector DBs, retrieval, and evaluation.
rag ai embeddings vector-db llm retrieval semantic-search

LlamaIndex — Data Framework for LLMs

Build RAG pipelines and LLM-powered data applications with LlamaIndex. Covers document loading, indexing, query engines, custom LLMs and embeddings, persistent storage, and agents.
python llamaindex llm rag ai embeddings agents retrieval

ragas — RAG Evaluation Framework

Measure and improve RAG pipeline quality with ragas. Covers faithfulness, answer relevancy, context precision, context recall, dataset format, LLM judges, and CI integration.
python ragas rag evaluation llm ai retrieval metrics