Elysia: Building an end-to-end agentic RAG app

Elysia is an open-source, agentic RAG framework designed to enhance AI chatbot interactions by not only determining what to communicate but also how to present data effectively. It leverages a decision tree-based architecture to intelligently choose tools and actions, offering both a frontend interface and a Python package for data interaction. Elysia connects to Weaviate clusters for smart searches, dynamically displaying data in various formats such as tables, charts, and product cards, based on the content and context. Its architecture includes a customizable decision tree, dynamic data display, and AI data analysis, providing transparency into its decision-making process. Elysia also features a feedback system for learning from user interactions, a chunk-on-demand document processing method to optimize storage, and a multi-model strategy to tailor model use based on task complexity, further enhancing its adaptability and efficiency. This framework aims to transform AI applications from passive information retrievers to active assistants capable of handling complex queries and providing actionable insights while allowing extensive customization and integration with various data sources and models.