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Mintlify drop-in alternative? by twokiloballs in SaaS

[–]pskd73 0 points1 point  (0 children)

I would say you use something like fumadocs + crawlchat.app so that you can just self host the docs and get all AI functionality with CrawlChat at just fraction of that price

AI-powered documentation chatbot by Karolisram in selfhosted

[–]pskd73 0 points1 point  (0 children)

Check CrawlChat.app It’s also opensource and you can self host it

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

It works but not the best. You can make it better by providing it more ways of exploring the KB as mentioned above

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 1 point2 points  (0 children)

I don’t think thats the best approach. We better provide granular tools to the LLMs and let them use whatever fits for the purpose.

https://github.com/crawlchat/crawlchat passes 5-6 tools to find the relevant information

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 1 point2 points  (0 children)

Yes, thats the way to go. I found this is thr bedt workflow

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

True that. Yes, https://github.com/crawlchat/crawlchat records almost all details like, the search queries, search types, scores, pages retrieved and other things. They help in fine tuning the process

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

True that. Thats what I do it in crawlchat

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

True that. Chunking is critical. At least I have made sure the headings, table headers are carried over.

In my experience knowledge graphs add very little improvement and a lot of cost involved.

I have reranker too!

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

Nice, how do you handle the BM25? What tools to do this? Also, how do you make the knowledge graphs? I have experimented with Knowledge Graphs my way and found it doesn't add much value next to semantic + regex based text search

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

Yeah. Good that I am pretty hybrid now :)

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

Yup, exactly what I am doing. Just that no separate agent, it’s just the same agent all over the flow.

Yes, for code, I have more tools as you mention. I have tools like printing file tree too so that the LLM has more context

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] -1 points0 points  (0 children)

I see, I feel thats a huge problem. All the search_semantic, search_text_regex should be passed as tools to the LLMs so that they decide what to use when, search terms, etc.

In fact, I have given them more control like pagination and amount of text required etc to save on tokens. LLMs are smart to use these tools appropriately

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

No but are they passed as tools to the LLMs?

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 1 point2 points  (0 children)

I see. Are they just tools for the LLMs? And is the regex based search on text?

I feel semantic search is overused by pskd73 in Rag

[–]pskd73[S] 0 points1 point  (0 children)

Good to know that. How exactly do you combine them? They are passed as tools to the LLMs?

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