Re: [Quantlib-users] Has anyone tested ChatGPT or FinGPT for QuantLib functionality

[sanfranciscofogg <san...@gm...>]

re: – can we use natural language to execute Quantlib code reliability and
consistently. ?
Ben,
   Yes, that is the question.
    Prompt engineering of a non-trivial sort to craft a solution
   Interesting problem worth exploring.
Thanks,
Mark Fogg

On Wed, Oct 25, 2023 at 8:55 PM Ben Watson <ben...@ma...>
wrote:

> I am looking at this as a concept. Taken a bit of a look at FINGPT but
> from what I have seen it is just a training set for finetuning open source
> LLM’s on finance related q&a. Good for sentiment analysis, financial news
> etc.  Mostly done on smaller models. BBG GPT is closed source and from what
> I understand is not setting the world of fire…. They have basically held it
> back to keep researching. BBG are also quite famous for their vapor-were  -
> where they try and kill the incentive for innovation elsewhere.
>
>
> GPT-4 is not bad at coding Quantlib with a bit of guidance – I built a
> pretty good wrapper for FX options in very quick time as well. GPT4 has a
> good broad base financial product understanding and can make inferences
> that get you a long way. But the real benefit of GPT4 is when you
> understand what you are asking and GPT does the grunt work in generating
> code. If you know what the answer should look like, then GPT4 is really
> useful.
>
> But I suspect the question that you are asking – can we use natural
> language to execute Quantlib code reliability and consistently. This part I
> have been doing a lot thinking about and requires chunk of infrastructure
> wrapping around Quantlib. Aside from a high level abstraction above the
> Quantlib layer, you will need a combination things good prompt engineer,
>  RAG (retrieval augmentation generation) and that requires vector databases
> and good documentation,  a finetuned model that understand the instructions
> to create a properly formatted query.
>
>
>
> One of the big  issues is that prompting and RAG is about providing
> context to  the query and the LLM’s that we can run locally have a limited
> context windows. To get a longer window, we need bigger models and now you
> are getting into a hardware issue. Multi-agent framework might be able to
> solve some of these issues. The other big idea that is not really fully
> explored is the idea of meta programming where the output from an LLM
> returns functions that can be executed – this is adding custom vectors to
> the output  that translate to function calls to do certain things. Right
> now GPT4 is the only platform really doing this, but is not great and not
> customisable.
>
> Regards
>
>
>
> Ben
>
>
>
> *From:* sanfranciscofogg <san...@gm...>
> *Sent:* Thursday, October 26, 2023 12:27 AM
> *To:* Qua...@li...
> *Subject:* [Quantlib-users] Has anyone tested ChatGPT or FinGPT for
> QuantLib functionality
>
>
>
> All,
>
>    After going through the FinGPT documentation, it occurred to me that
> QuantLib equivalent output might result from a properly formatted query.
>
>    The code which might be output from such a query, was the specific
> interest.
>
>     Are there any participants of FinGPT who might offer commentary?
>
>
>
> Cordially,
>
> S.F.Fogg
>
>
>
>       *★** San Francisco Fogg **★*
>
> *               Mercury Algorithmics*
>
> *               Fogg Spirits*
>
> *               ecurie Foggio*
>
>
>
>
>