Streamlining Retrieval-Augmented Generation Model Evaluation with Amazon API Gateway and Ragas

Retrieval-augmented generation (RAG) is a robust AI architecture that combines the strengths of retrieval-based and generative models to produce more accurate and context-aware outputs. RAG allows models to retrieve relevant information from external sources, enhancing the response generation process, especially in scenarios where knowledge or context is required outside the model’s training data. This technique is essential in legal, medical, and technical industries, where up-to-date and factual responses are critical.

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