𝐑𝐀𝐆 Uses

Published 2026-01-31 in PySpark

𝐈𝐟 𝐲𝐨𝐮 𝐭𝐡𝐢𝐧𝐤 𝐑𝐀𝐆 𝐢𝐬 𝐣𝐮𝐬𝐭 "𝐫𝐞𝐭𝐫𝐢𝐞𝐯𝐞 𝐬𝐨𝐦𝐞 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐬 𝐚𝐧𝐝 𝐬𝐭𝐮𝐟𝐟 𝐭𝐡𝐞𝐦 𝐢𝐧𝐭𝐨 𝐚 𝐩𝐫𝐨𝐦𝐩𝐭," 𝐲𝐨𝐮'𝐫𝐞 𝐥𝐞𝐚𝐯𝐢𝐧𝐠 𝟗𝟎% 𝐨𝐟 𝐭𝐡𝐞 𝐯𝐚𝐥𝐮𝐞 𝐨𝐧 𝐭𝐡𝐞 𝐭𝐚𝐛𝐥𝐞. RAG is not one thing it is 16+ distinct patterns, each optimized for different problems. 𝐇𝐞𝐫𝐞 𝐢𝐬 𝐭𝐡𝐞 𝐓𝐚𝐱𝐨𝐧𝐨𝐦𝐲 𝐭𝐡𝐚𝐭 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐦𝐚𝐭𝐭𝐞𝐫𝐬: 1. Standard RAG: Basic retrieve + generate. Where everyone begins, rarely where you should stay. 2. Agentic RAG: Agents decide what to retrieve and when. The shift from "retrieve then answer" to "decide what's needed." 3. Graph RAG: Knowledge graphs + relations. When your answer depends on how entities relate, not just what documents say. 4. Modular RAG: Separate retrieval/reasoning modules. Build once, optimize each piece independently at scale. 5. Memory-Augmented RAG: External memory that learns user preferences. Your agent remembers and adapts. 6. Multi-Modal RAG: Text, image, audio retrieval. When your knowledge base isn't just documents. 7. Federated RAG: Data stays distributed. Retrieve without centralizing sensitive data. 8. Streaming RAG: Real-time retrieval. When your context changes faster than your cache invalidates. 9. ODQA RAG: Broad knowledge retrieval. Jack of all domains, master of flexibility. 10. Contextual…

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