Ragas provides a robust workflow for building and evaluating RAG pipelines, utilizing open-source libraries such as Ragas, Arize AI's Phoenix, and LlamaIndex. The pipeline involves generating synthetic test data using Ragas, building a simple RAG application with LlamaIndex, launching Phoenix to collect traces and spans, and evaluating the performance of the LLM application using Ragas. Additionally, Phoenix provides visualization tools for analyzing embedded queries and retrieved documents, allowing developers to identify areas of poor performance and gain insights into their application's behavior. By combining Ragas and Phoenix, developers can create a comprehensive evaluation framework for their RAG pipelines, ensuring high-quality responses and efficient model development.