Hey HN,<p>We are Zain and Ashish, founders of Vanna AI. We recently embarked on an experiment to see if large language models (specifically LLMs) could help in generating SQL queries for real-world datasets. We initially started this project as a web app but realized that it was most useful and had broadest applicability as a Python package since you can then incorporate it into an existing workflow (Jupyter notebook, Slackbot, etc).<p>We've had some good success with customer datasets but we've generally heard a lot of skepticism so we decided to write a paper about the methodology we're using and how various LLMs compare.<p>Let us know if you have any questions or requests. The underlying Python package is open source. There is a server component to store and retrieve metadata but by next week there will be a fully open-source and locally runnable version.<p>Cheers!
This looks awesome, great work team! A few questions :)<p>How complex were the 'static examples' that were used? Can you share the examples of the three that were used in the tests?<p>Were the "contextually relevant sql" ran in addition to or isolated from the "static examples"?