Yup, you nailed it! That's the idea :) it just saves time from worrying about building a machine learning model, because we all have access to a big one in the form of a large language model (Google/OpenAI are paying the electricity cost).
So this can help save time by removing the overhead and creating a "deterministic" classifier in the form a python program that is likely more concise, maintainable, and interpretable than machine learning models trained for this task. On Mon, Mar 11, 2024 at 7:03 AM Chary Chary <[email protected]> wrote: > Hi, > > I briefly scanned through the article. > > So in the essence you give LLM a bunch some CSV example and then ask LLM > to write a python code, which would categorize similar, based on the > keywords. > > So, this is a kind of alternative to teaching ML model based on the > previous transactions to be able to categorize new ones. > > Did it get the main idea correctly? > > On Monday, March 11, 2024 at 12:36:00 AM UTC+1 [email protected] wrote: > >> Made a quick prompt over the weekend: >> https://gist.github.com/jaanli/1f735ce0ddec4aa4d1fccb4535f3843f >> >> Results are that my partner (someone non-technical, design background, >> but familiar with prompt engineering) can use the prompts—the last thing I >> would want is an inscrutable system that I manually built to import >> transactions from our dozen institutions across multiple countries & >> currencies, that they can't re-use or extend. >> >> Visual Studio Code and the Beancount extension are already a stretch for >> them so having something that works with a single prompt at a time and copy >> and pasting was my goal. >> >> Hope this helps someone else! Surprised that these tools are not easier >> to use (and thank you for beancount, this wouldn't be possible otherwise :) >> >> Would be fun to extend this with DSPy ( >> https://github.com/stanfordnlp/dspy/blob/main/intro.ipynb) which could >> likely help squeeze several different converters into a few signatures >> (compressed prompts), and things like chain-of-thought prompting (iterative >> runs of large language models) would further reduce the >> extract-transform-load overhead that has kept me from trying beancount all >> these years. >> >> Very best, >> Jaan >> > -- > You received this message because you are subscribed to a topic in the > Google Groups "Beancount" group. > To unsubscribe from this topic, visit > https://groups.google.com/d/topic/beancount/aoZ7-H1tCX4/unsubscribe. > To unsubscribe from this group and all its topics, send an email to > [email protected]. > To view this discussion on the web visit > https://groups.google.com/d/msgid/beancount/eefe5ba4-c0cd-46cd-9fb8-8922b399c221n%40googlegroups.com > <https://groups.google.com/d/msgid/beancount/eefe5ba4-c0cd-46cd-9fb8-8922b399c221n%40googlegroups.com?utm_medium=email&utm_source=footer> > . > -- You received this message because you are subscribed to the Google Groups "Beancount" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/beancount/CAKLvh_QPbA7gioL1bG%2BunerEGZisMSN_7MvAuwPG%2BjV_kz17bQ%40mail.gmail.com.
