Accelerate the development and research of complex Retrieval-Augmented Generation (RAG) systems with a low-code, modular framework.
UltraRAG 2.0 addresses the high engineering costs associated with reproducing and iterating on complex RAG systems, which often involve adaptive knowledge organization, multi-turn reasoning, and dynamic retrieval. It provides a RAG framework built on the Model Context Protocol (MCP) architecture, enabling researchers to declare intricate logic such as sequential, loop, and conditional branching through simple YAML files. This design significantly lowers the technical barrier and learning curve for building and experimenting with sophisticated RAG pipelines, allowing researchers to focus on algorithmic innovation and experimental design rather than extensive engineering implementation.