Would it be possible to do something like A* pathfinding thru the vector database to find better results? #3911
Labels
area:context-providers
Relates to context providers
kind:enhancement
Indicates a new feature request, imrovement, or extension
"needs-triage"
Validations
Problem
With some documentation sites, the
@Docs
triggers sometimes goes somewhere random or just sticks with the index page or something of sort instead of loading a relevant page. For example, https://docs.scipy.org/doc/scipy/#scipy-documentation instead of the page about actual command mentioned in the prompt.ps: Since Docs functionality have degraded significantly after .250 pre-release for me, getting pretty much unusable, for now I'm stuck at that version and haven't double-checked it in more recent versions to know if the RAG can aim better after .250
Solution
I'm not 100% sure how the internals work to able to tell if this would make sense; but in case it does, here's the idea: look for pages that are linked from the first impulse response of the RAG and evaluate if their content have better relevance score, recursively, using something like a variation of the A* pathfinding algorithm; and maybe have a setting for how many dead-end branches (where it reaches a point where there are no improvements in the score) to try until giving up and going with the closest it found so far (since, based on my superficial level understanding of how vector databases work, I imagine it will rarely be a perfect score even if a human would consider it exact).
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