RAGLite

RAGLite is a powerful Python toolkit designed for Retrieval-Augmented Generation (RAG) applications, providing robust support for both PostgreSQL and SQLite databases. It streamlines the development of RAG pipelines, offering features such as adaptive retrieval, hybrid search with reranking, and optimal query adaptation. It excels at processing and converting diverse file types into Markdown, enabling semantic chunking, and multi-vector embedding for enhanced information retrieval. RAGLite's ability to integrate with llama.cpp models, along with the option to leverage a customizable ChatGPT-like frontend, makes it an attractive option for developers seeking flexible and high-performance RAG solutions.

This toolkit is targeted towards AI developers and researchers looking to build sophisticated RAG systems, and provides the flexibility for both manual and automated pipeline control, alongside advanced capabilities like query adaptation and evaluation with Ragas. Furthermore, its server component facilitates seamless integration with tools like Claude, and supports deployments to web, Slack and Teams, making it a versatile solution for a range of use cases and platforms. RAGLite empowers developers to achieve superior output quality by incorporating features such as reranking and optimized chunk retrieval.