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Building & Evaluating a RAG Chatbot

This example shows how you can use PromptLayer to evaluate Retrieval Augmented Generation (RAG) systems. As a cornerstone of the LLM revolution, RAG systems enhance our ability to extract precise information from vast datasets, significantly improving question-answering capabilities.

We will create a RAG system designed for financial data analysis using a dataset from the New York Stock Exchange. The tutorial video elaborates on the step-by-step process of constructing a pipeline that encompasses prompt creation, data retrieval, and the evaluation of the system’s efficacy in answering finance-related queries.

Most importantly, you can use PromptLayer to build end-to-end evaluation tests for RAG systems.