Very interesting work. What are your opinions of GraphRAG and the variations?
I'm currently evaluating systems that extend RAG as your PageIndex project does, with an eye on adaptability to new information.
A good portion of my work involves legal issues and case law, and with the US going through a lot of legal transformations with the new administration, I am seeking a system that can ingest new information that imposes new rules on the handling of information, and those new rules need to impose precedence over any similar such rules already in the knowledgebase.
This new information ingestion and logical resolution within the larger knowledgebase needs to be efficient too. The initial GraphRAG is expensive to begin with, and does not appear to have any optimized handling for ingesting of new, conflicting information. The GraphRAG variants that are getting a lot of attention now appear to be addressing the lack of efficiency in the original GraphRAG implementation. Where does PageIndex set within this group of similar offerings?
GitHub repo: https://github.com/VectifyAI/PageIndex/ Open to feedback and suggestions.
Interesting work! How do you construct the relationship between nodes if not all documents fit into context?
Have you compared this solution with tools like Preprocess, Reducto, etc.. ? I'm curious about the performance gain you can achieve with your approach