Mastering the Art of Prompting LLMs for RAG
Retrieval Augmented Generation (RAG) has become a cornerstone technology for building powerful, context-aware AI applications. By connecting Large Language Models (LLMs) to external knowledge bases, RAG overcomes the limitations of pre-trained models, reducing hallucinations and providing more accurate, grounded answers. But getting the best results from your RAG pipeline isn’t just about retrieval; it’s also […]
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