This article introduces a new series focused on improving retrieval-augmented generation (RAG) systems. It highlights the common challenge of RAG systems performing well in demonstrations but failing when used by real users. The series will provide LangChain code examples to address these issues, starting with an introductory part. AI
IMPACT Offers practical guidance and code for developers to enhance the performance of RAG systems in real-world applications.
RANK_REASON The item is an introduction to a series about improving RAG systems, not a release or research milestone itself.
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