Category: Rag Architecture
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Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables
Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables Designing a hybrid SQL + vector retrieval system without schema changes, data migration, or performance trade-offs The post Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables appeared first on Towards Data Science. Partha Sarkar Go to original source
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HNSW at Scale: Why Your RAG System Gets Worse as the Vector Database Grows
HNSW at Scale: Why Your RAG System Gets Worse as the Vector Database Grows How approximate vector search silently degrades Recall—and what to do about It The post HNSW at Scale: Why Your RAG System Gets Worse as the Vector Database Grows appeared first on Towards Data Science. Partha Sarkar Go to original source
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Six Lessons Learned Building RAG Systems in Production
Six Lessons Learned Building RAG Systems in Production Best practices for data quality, retrieval design, and evaluation in production RAG systems The post Six Lessons Learned Building RAG Systems in Production appeared first on Towards Data Science. Sabrine Bendimerad Go to original source
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Do You Really Need GraphRAG? A Practitioner’s Guide Beyond the Hype
Do You Really Need GraphRAG? A Practitioner’s Guide Beyond the Hype A perspective on GraphRAG design best practices, challenges and learnings The post Do You Really Need GraphRAG? A Practitioner’s Guide Beyond the Hype appeared first on Towards Data Science. Partha Sarkar Go to original source
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Retrieval Augmented Generation (RAG) — An Introduction
Retrieval Augmented Generation (RAG) — An Introduction The model hallucinated! It was giving me OK answers and then it just started hallucinating. We’ve all heard or experienced it. Natural Language Generation models can sometimes hallucinate, i.e., they start generating text that is not quite accurate for the prompt provided. In layman’s terms, they start making…