How to use LLMs to generate accurate SQL for real-world data
Hey HN, 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). 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…
In plain words
Vanna AI is a Python package that uses large language models to generate SQL queries for real-world databases. Developers can integrate it into existing workflows like Jupyter notebooks or Slackbots to automate SQL creation. The tool is open source and includes a server component for storing metadata, with plans for a fully local version available soon.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN, 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). 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. 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. Cheers!
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