Re:LlamaCloud and LlamaParse
by analyte123 on Tuesday February 20, 2024 @07:34PM
(#39448815)
Making something appear as if it might be an open source library, but is actually just a wrapper to a paid hosted service is endemic in the Python world in general and the LLM space in particular.
Out of interest - Why are you looking to move from Kendra? I havent heard much good about it but keen to understand what your issues with it are.
It’s too expensive for the features it provides. The person who estimated the cost got it wrong and were paying 3x. But I can’t just rip it out due to it powering a very important piece of software.
Re:LlamaCloud and LlamaParse
by mahmoudimus on Wednesday February 21, 2024 @12:51AM
(#39450593)
If you're serious about this, I'm working on a new startup about this that is 100% working on using different techniques to help with this. I'd love to talk to you about what your needs are as it would help me have more data points as I take this to market. My email is in my profile if you shoot a message.
Sorry, but I’m in the process of building my own and can’t provide any info due to regulations. Best of luck.
Feel free to try - https://github.com/nlmatics/llmsherpa. It is fully open source - both client and server and it not ML augmented, so very fast and cheap to run.
Thank you for sharing.
Re:LlamaCloud and LlamaParse
by johnthescott on Thursday February 22, 2024 @03:14AM
(#39464522)
we have had great success with apache pdfbox.
1. The comparison with the open source pdf libraries is rather strange. They are self contained libraries. Not ML augmented services. Does this mean you plan to open source the underlying technology and offer it under the same licenses as pypdf or pymupdf?
2. How does this compare to AWS Kendra? I have one of the bigger deployments out there and am looking for alternatives.
3. How fast is the pdf extraction? In terms of microseconds given we pay for execution time.