Building RAG Applications with Milvus, Qwen, and vLLM

The text discusses the integration of three technologies: Milvus, a vector database; vLLM, an open-source library optimized for large language models; and Qwen, a family of state-of-the-art open-source models that combine multilingual fluency, advanced reasoning capabilities, and high efficiency. These technologies are combined to build a robust Retrieval-Augmented Generation (RAG) system capable of addressing complex queries in real-time. The integration enables the deployment of large language models with enhanced efficiency, scalability, and cost-effectiveness, making them accessible for various industries such as healthcare, education, software development, and scientific research.