🚀 𝗠𝗮𝘀𝘁𝗲𝗿 𝗥𝗔𝗚 𝘄𝗶𝘁𝗵 𝗔𝘇𝘂𝗿𝗲 – 𝗳𝗿𝗼𝗺 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝘀 𝘁𝗼…

This is a dev post classified by AGK Intelligence as Databases (a tutorial), kept by the Dev Radar because it carries real work, not commentary.

🚀 𝗠𝗮𝘀𝘁𝗲𝗿 𝗥𝗔𝗚 𝘄𝗶𝘁𝗵 𝗔𝘇𝘂𝗿𝗲 – 𝗳𝗿𝗼𝗺 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝘀 𝘁𝗼 𝗮𝗻𝘀𝘄𝗲𝗿𝘀 Retrieval-Augmented Generation (RAG) isn’t magic. It’s a well-designed pipeline — and Azure gives you all the building blocks. 𝗧𝗵𝗶𝘀 𝘃𝗶𝘀𝘂𝗮𝗹 𝗯𝗿𝗲𝗮𝗸𝘀 𝗥𝗔𝗚 𝗶𝗻𝘁𝗼 𝟰 𝗰𝗹𝗲𝗮𝗿 𝘀𝘁𝗮𝗴𝗲𝘀 👇 🔹 Indexing • Parse documents (PDFs, docs, etc.) • Chunk text for better recall • Generate embeddings using Azure embedding models • Store them in a vector database 🔹 Retrieval (R) • User query → encoded into embeddings • Semantic search over the vector store • Fetch the most relevant chunks 🔹 Augmentation (A) • Combine retrieved chunks • Build context-aware prompts • G

Posted by Aiswarya Venkitesh (3.1k followers) 20 min ago · 0 likes · 20 views · view the original post on X. Kept by the Dev Radar as Databases.

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