Enhancing AI with Retrieval-Augmented Generation (RAG)!
RAG combines powerful language models with data retrieval for smarter, context-rich responses. Here’s how it works:
1️⃣ User Query: A prompt is submitted.
2️⃣ Data Retrieval: System searches internal/company data.
3️⃣ Processing & Vectorization: Content is split, chunked, tokenized, and converted to vectors.
4️⃣ Find Relevant Info: A vector database (like Milvus) locates the best match.
5️⃣ Answer Generation: The AI model combines user input with retrieved data to generate a well-informed response.
RAG delivers accuracy by using existing knowledge to augment AI responses!
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