--- title: What is RAG? Retrieval-Augmented Generation Explained description: RAG (Retrieval-Augmented Generation) is a technique that addresses key limitations of large language models — outdated knowledge, hallucinations, and lack of... canonical: https://daily.dev/posts/what-is-rag-retrieval-augmented-generation-explained-ekdnyb1la twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What is RAG? Retrieval-Augmented Generation Explained | daily.dev og:description: RAG (Retrieval-Augmented Generation) is a technique that addresses key limitations of large language models — outdated knowledge, hallucinations, and lack of... og:url: https://daily.dev/posts/what-is-rag-retrieval-augmented-generation-explained-ekdnyb1la og:image: https://api.daily.dev/og/posts/EKdnyB1la.png og:image:alt: What is RAG? Retrieval-Augmented Generation Explained og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # What is RAG? Retrieval-Augmented Generation Explained **[Oxylabs](https://daily.dev/sources/oxylabs)** · 5 min read · 2 upvotes · 0 comments ## Summary RAG (Retrieval-Augmented Generation) is a technique that addresses key limitations of large language models — outdated knowledge, hallucinations, and lack of access to proprietary data — by retrieving relevant information before the model generates a response. The core flow: a user query triggers a retrieval layer that searches internal documents or external web sources, assembles the results into context, and passes everything to the LLM as an enriched prompt. The model never searches on its own. This approach enables up-to-date answers, fewer hallucinations, and access to private data without retraining the model. Popular AI tools like ChatGPT web search, Claude PDF uploads, and Perplexity citations all use RAG under the hood. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#ai](https://daily.dev/tags/ai), [#llm](https://daily.dev/tags/llm), [#rag](https://daily.dev/tags/rag), [#vector-search](https://daily.dev/tags/vector-search) [View this post on daily.dev](https://daily.dev/posts/what-is-rag-retrieval-augmented-generation-explained-ekdnyb1la) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"What is RAG? 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