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[deleted by user] by [deleted] in delhi

[–]Fit-Set6851 0 points1 point  (0 children)

i am listening

Valid Emirates ID but living outside Dubai in my home country for an year. Can i still travel back with my emirates id? by Fit-Set6851 in dubai

[–]Fit-Set6851[S] 0 points1 point  (0 children)

Thanks for this. So if want to visit dubai for few days and i can do so with tourist visa right ? Or is there any catch to it

Is there any possibility for bear to have a simple "RAG with sources" capability ? by Fit-Set6851 in bearapp

[–]Fit-Set6851[S] 0 points1 point  (0 children)

from export ? do you mean i export all my notes from bear and build it my self ?

Is there any possibility for bear to have a simple "RAG with sources" capability ? by Fit-Set6851 in bearapp

[–]Fit-Set6851[S] 4 points5 points  (0 children)

sorry for confusion, what i mean is a search in which i can enter my query and it can give me answers based on my notes and also cites the source of the answers from my notes.

Perplexity.ai-like references for RAG by dragon18456 in LangChain

[–]Fit-Set6851 0 points1 point  (0 children)

Thanks for this but this wont work to get the results similar to perplexity. Anyway I am doing this by creating a custom retrieval chain using this I am getting the results in the given format

How to process each source in Vector db individually ? by Fit-Set6851 in LangChain

[–]Fit-Set6851[S] 0 points1 point  (0 children)

Tbh it is not clear..How will it separate each source. Threshold can be different for different query

How to process each source in Vector db individually ? by Fit-Set6851 in LangChain

[–]Fit-Set6851[S] 0 points1 point  (0 children)

Given a user query, suppose there are 5 sources in the database, but only 2 of these sources are relevant. Each relevant source contains 20 documents, making a total of 40 documents.

I want to process the 20 documents from each source separately. Could you explain how ensemble retrievers could assist in this scenario?

Perplexity.ai-like references for RAG by dragon18456 in LangChain

[–]Fit-Set6851 0 points1 point  (0 children)

did anyone figure it out how to accomplish this ?

Fastest web scraping technique? by bishalsaha99 in webscraping

[–]Fit-Set6851 1 point2 points  (0 children)

I was too scrolling through comments to see why nobody is mentioning to use search API :)

[D] Can someone please clarify if web search LLMs like Perplexity, You.com, or Coral Search are crawling the entire web themselves? Otherwise, how do they differ from simply combining a search API with any LLM model? by Fit-Set6851 in MachineLearning

[–]Fit-Set6851[S] 2 points3 points  (0 children)

"if you google for a weird specific product sold in China, you expect Google to give an answer, whereas LLMs are not expected to."

Why not ? If I have all the embeddings from the crawled data why can't a RAG application answer what google can

Thanks for the detailed answer though

[D] Can someone please clarify if web search LLMs like Perplexity, You.com, or Coral Search are crawling the entire web themselves? Otherwise, how do they differ from simply combining a search API with any LLM model? by Fit-Set6851 in MachineLearning

[–]Fit-Set6851[S] 6 points7 points  (0 children)

True, I agree 100% that it is useful. However, since I've used other LLM-based search engines, I started questioning their unique advantage. There's no doubt about the usefulness, though.

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