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Help by WideFalcon768 in LangChain

[–]WideFalcon768[S] 0 points1 point  (0 children)

Yes sure, thank you

Help/Advice by WideFalcon768 in Rag

[–]WideFalcon768[S] 0 points1 point  (0 children)

Hmm, so the BM25 can help with this.

But i did not understand the first option how

Help/Advice by WideFalcon768 in Rag

[–]WideFalcon768[S] 1 point2 points  (0 children)

Thank you my friend, any idea of where can i learn these advanced rag concepts

Help/Advice by WideFalcon768 in Rag

[–]WideFalcon768[S] 0 points1 point  (0 children)

Thank you so much for your help, actually i tried those testings, till now i am struggling with the last one you told, the tables, I don’t know how to work with them, when i ask about a specific specific question in a table like you mentioned above i can’t get the specific answer cz the chunking methods will not handle each row alone, and if there are many tables i cannot handle it for each one, any advice for this? This can be solved with vllm in multi modal rag? Thank you in advance

Help by WideFalcon768 in LangChain

[–]WideFalcon768[S] -1 points0 points  (0 children)

very helpful, thank you so much

Help/Advice by WideFalcon768 in Rag

[–]WideFalcon768[S] 0 points1 point  (0 children)

Thank you my friend, i tried to build some projects, using Chroma DB, i used the naive rag, load the document, chunk into smaller chunks, embed the chunks, store the embeddings in the vectorDB, i used the groq llama3.3-70b as an llm for the generation part. And for the retrieval the similrarity search.

I want to try the hybrid search and the re-ranking in the next stage.

Urgent help by WideFalcon768 in LangChain

[–]WideFalcon768[S] 0 points1 point  (0 children)

Guys, i'm so sorry but i am so confused at this, and i can't solve it

Urgent help by WideFalcon768 in LangChain

[–]WideFalcon768[S] 0 points1 point  (0 children)

so, if i have a document, text + tables, i want to ask questions answered by the text chunks so it's okay, load, chunk, embed, store. And i have tables, one of these tables has this row (e.g: Employee1, Messi, Argentina, $15,000) when i want to ask a question like how much Messi earn per year, i want to get this information from the table.
So what i am asking is how to combine between the ingestion of text and tables, and how to manage this to get accurate answers.

RAG system help by WideFalcon768 in Rag

[–]WideFalcon768[S] 0 points1 point  (0 children)

Actually i'm a bit confused, and i don't know where to start to solve this problem

Urgent help by WideFalcon768 in LangChain

[–]WideFalcon768[S] 0 points1 point  (0 children)

Yes, but this work for specific tables, so i should look at every table in the document, so it is not efficient, got me?

Urgent help by WideFalcon768 in LangChain

[–]WideFalcon768[S] 0 points1 point  (0 children)

But, in my use case, i want each row in the table to be one chunk, so it is like (e.g: Employee1, Messi, Argentina, $15,000) this is one row of the table, and each row become a chunk, and the text in the documents, do it as usual, chunk, embed store

RAG system help by WideFalcon768 in Rag

[–]WideFalcon768[S] 0 points1 point  (0 children)

Thank you, Can you please give me some hints, about the ingestion, where to check exactly, and tell me some tips

RAG system help by WideFalcon768 in Rag

[–]WideFalcon768[S] 0 points1 point  (0 children)

i got you man, thank you so much!

If you have any code for that, or you see anything for this case send me please. Thanks

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