FlexRAG is a flexible and high-performance framework for Retrieval-Augmented Generation (RAG) tasks. It supports multimodal data, seamless configuration management, and out-of-the-box performance, making it suitable for research and prototyping. Written in Python, it combines lightweight design with high performance, significantly improving the speed of RAG workflows and reducing latency. Key advantages include support for multiple data types, unified configuration management, and ease of integration and extension.