Yes, UltraRAG is an open-source project. It is publicly available on GitHub, providing its code, demonstration videos, and an installable package for developers and researchers. The project is a collaborative effort jointly proposed by institutions such as Tsinghua University (THUNLP), Northeastern University (NEUIR), OpenBMB, and AI9stars. Its open-source nature facilitates community contributions, allowing for shared development and a collaborative ecosystem for advanced RAG research.
UltraRAG is specifically designed to be researcher-friendly, reproducible, and extensible, making it suitable for academic AI community needs. It enables the design of complex RAG workflows with minimal coding, primarily through YAML configuration, supporting features like sequential, looped, or conditional pipelines. The framework also integrates with various backend systems such as Infinity, Sentence-Transformers, OpenAI, vLLM, and Hugging Face, allowing model switching without extensive code rewrites. Its open availability underscores its goal of accelerating RAG system development and fostering innovation within the field.
The framework also integrates with open-source tools like Milvus, a vector database. This integration allows UltraRAG to leverage Milvus for efficient storage, indexing, and similarity search of embeddings, which is crucial for the retrieval layer in RAG systems. By combining UltraRAG’s low-code orchestration capabilities with a robust vector database like Milvus, developers can construct flexible and efficient RAG pipelines. The public repository also provides detailed instructions for installation, including source code installation and Docker deployment options, further emphasizing its commitment to open development.