The only advantage I can think of is how introducing an LLM is basically a way to hopefully/maybe (with low accuracy) go one step further than low-code? Like, you can type "in thought/in English" as if it was a robust instruction prompt with sophisticated understanding that was able to boil down to the equivalent of basically a few lines of code/shell script to fill in a PDF.
ChatPDF – Chat with Any PDF
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Re: ChatPDF – Chat with Any PDF
#72But if I asked if the claimant name was in the PDF it answered yes.
I am assuming the PDF to Text is not working great here, which I supposed is the whole point.
Re: ChatPDF – Chat with Any PDF
#73I'm glad it was reposted so I get another chance at developing a habit of using it.
Re: ChatPDF – Chat with Any PDF
#74IMO folks are better off deploying their own version where they can adjust a few knobs (e.g. split chunk size) to get better results, given that PDF Q&A is such a commodity application. Wrote a https://github.com/angad/dharamshala/blob/main/docs.py return_source_documents is particularly helpful to get a sense of what is being sent in the prompt.
Re: ChatPDF – Chat with Any PDF
#75Re: ChatPDF – Chat with Any PDF
#76This was pretty bad for me, I tried asking the name of a person references in the PDF and it couldn't find it. I asked who is the claimant in this PDF and it said the claimant was empty. But if I asked if the claimant name was in the PDF it answered yes. I am assuming the PDF to Text is not working great here, which I supposed is the whole point.
I have it working with 600 page documents.