Meet RAGxplorer: An interactive AI Tool to Support the Building of Retrieval Augmented Generation (RAG) Applications by Visualizing Document Chunks and the Queries in the Embedding Space
Main Ideas:
- Understanding the comprehension and organization of information is crucial in advanced language models like Retriever-Answer Generator (RAG).
- Visualizing the relationships between different document parts and chunks of information can be challenging.
- Existing tools sometimes fail to provide a clear picture of how information relates to each other.
- RAGxplorer is an interactive AI tool designed to support the building of RAG applications.
- RAGxplorer visualizes document chunks and queries in the embedding space, helping to understand their relationships.
Author’s Take:
RAGxplorer is a new interactive AI tool designed to overcome the challenge of visualizing the relationships between document parts and information in advanced language models like RAG. By providing a clear picture of how document chunks and queries relate to each other in the embedding space, RAGxplorer can greatly support the building of RAG applications. This tool has the potential to enhance comprehension and organization in language models, ultimately benefiting various AI applications.