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KAG – Knowledge Graph RAG Framework

(github.com)
230 points taikon | 1 comments | 30 Dec 24 02:55 UTC | HN request time: 0.196s | source
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dcreater ◴[30 Dec 24 06:01 UTC] No.42546890[source]▶
Yet another RAG/knowledge graph implementation.

At this point, the onus is on the developer to prove it's value through AB comparisons versus traditional RAG. No person/team has the bandwidth to try out this (n + 1) solution.

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ertdfgcvb ◴[30 Dec 24 06:19 UTC] No.42546979[source]▶
I enjoy the explosion of tools. Only time will tell which ones stand the test of time. But this is my day job so I never get tired of new tools but I can see how non-industry folks can find it overwhelming
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trees101 ◴[30 Dec 24 06:33 UTC] No.42547052[source]▶
Can you expand on that? Where do big enterprise orgs products fit in, eg Microsoft, Google? What are the leading providers as you see them? As an outsider it is bewildering. First I hear that llama_index is good, then I hear that its overcomplicating slop. What sources or resources are reliable on this? How can we develop anything that will still stand in 12 months time?
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1. dcreater ◴[30 Dec 24 18:09 UTC] No.42551860[source]▶
haha I had heard that langchain was overcomplicated, self contradictory slop and that llama index was better. I dont doubt its bad as well.

Both are cut from the same cloth of typical inexperienced devs who made something cool in a new space and posted on GitHub but then immediately morphed into a companies trying to trap users etc. without going through an organic lifecycle of growing, improving, refactoring with the community.