RAGSkeleton
RAGSkeleton is a modular, foundational framework designed to streamline the creation of Retrieval-Augmented Generation (RAG) systems. By combining retrieval mechanisms with language model generation, RAGSkeleton enables developers and researchers to build adaptable, context-aware solutions across diverse domains. This framework offers a flexible structure to retrieve relevant information from document databases, generate precise responses to user queries, and easily incorporate domain-specific models and retrieval methods. RAGSkeleton serves as an intuitive foundation for applications in natural language understanding, question-answering, and document-centric AI tasks.
Key Features
Modular Structure: Allows for easy customization and integration with various models.
Domain Flexibility: Supports diverse applications, from scientific literature to customer support.
Compatibility: Works with both local and cloud-hosted language models.
Scalability: Built to support scalable document processing and information retrieval.