This guide walks you through the process of building a powerful RAG pipeline using RAGLite. From configuring your LLM and database to implementing advanced retrieval strategies like semantic chunking and reranking, this guide covers everything you need to optimize and scale your RAG-based applications.

Discover RAGLite, a lightweight toolkit that revolutionizes Retrieval-Augmented Generation (RAG). With features like semantic chunking, adaptive retrieval, and hybrid search, RAGLite overcomes traditional RAG limitations, simplifying workflows and ensuring fast, scalable, and accurate information retrieval for real-world AI applications.

Unsupervised anomaly detection advances quality control in manufacturing by enabling efficient and flexible product defect detection with a minimal labelling effort and the ability to handle changing products and various defect types.