Boosting RAG Performance: The Secret Isn't Always the LLM!

This article dives into optimizing Retrieval-Augmented Generation (RAG) systems, revealing that the key to improved accuracy often lies in enhancing the retrieval and ranking stages, rather than solely focusing on the performance of the underlying Large Language Model (LLM). It offers valuable insights into common pitfalls and practical solutions for boosting RAG effectiveness.

• •RAG accuracy can be hampered by poor retrieval and ranking, not just the LLM.
• •Improving tool activation conditions based on similarity thresholds is crucial.
• •Keyword extraction and date considerations are key for effective search.