Evaluating RAG Applications with RAGAs

A framework with metrics and LLM-generated data to evaluate the performance of your Retrieval-Augmented Generation pipeline

By now, we know that building a proof of concept for a Retrieval-Augmented Generation (RAG) application is easy, but making it production-ready is very difficult. Getting the RAG pipeline's performance to a satisfying state is especially difficult because of the different components in a RAG pipeline:

• Retriever component: retrieves additional context from an external database for the LLM …

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