Replies: 1 comment
-
Hi, yes this is a current limitation and one we are working on. There is an approach described in #20 which is quite close to the idea we are thinking about. We also happily welcome community contributions and PRs on this! |
Beta Was this translation helpful? Give feedback.
0 replies
# for free
to join this conversation on GitHub.
Already have an account?
# to comment
-
The RAPTOR looks interesting but I see a
big limitation
in case one wants to incrementally add information to a vectorstore (quite common in a production scenarios imo). Raptor only works by looking globally at the entire pool of documents, as summaries are iteratively computed on clusters. This produces a sort of"immutable" vectorstore
. In other words, if a user wants to simply add a document to an existing vectorstore, the full Raptor pipeline would have to run again to take into account the new information in existing summaries, which may become quite expensive with many documents (both in terms of cost and latency of the operation). Maybe one could simply replace the most similar summary at each level? I'd love to hear how people will address this.Beta Was this translation helpful? Give feedback.
All reactions