Seems like a cool concept. I personally know people in finance whose whole job is to write SQL queries all day. Would be nice to have something like this.
The demo video in the README legit tried to give me a seizure tho…
Interesting lead. What else would they be looking for in a tool like this? My bad re the video, I'll make sure not to toggle dark mode in the next one.
Would love to contribute. I have made a fork, will try and raise a PR if contributions are welcome.
Question, how are you testing this? Like doing it on dummy data is a bit too easy. These models, even 4o, falter when it comes to something really specific to a domain (like I work with supply chain data and other column names specific to the work that I do, that only makes sense to me and my team, but wouldn't make any sense to an LLM unless it somehow knows what those columns are)
I'm using my own production databases at the moment. But it might be quite nice to be able to generate complex databases with dummy data in order to test the prompts at the higher levels of complexity!
And thank you for offering to contribute. I'll be very active on GitHub!
Looks useful! And the system prompt didn't require too much finessing. I wonder how it would work with some later models than gpt-4o as in my own dabbling around gpt-4o wasn't quite there yet and the latest models are getting really good.
Appreciate the input! I'd love to be able to support more models. That's one of the issues in the repo right now. And I'd be more than happy to welcome contributions to add this and other features
Not really - I had some previous experience with electron and wanted to finish the core feature set in a few hours, so just went with what I already know.
It is a web app, though. You just aren't running the server, OpenAI is. And you're packaging the front end in electron instead of chrome to make it feel as if it all runs locally, even though it doesn't.
Side note: I don't see a license anywhere, so technically it isn't open source.
That makes no sense. OpenAI doesn't know the secret database connection string or any query results. Perhaps you should have read the code before making baseless claims.
API gateways could accept public keys instead of generating bearer tokens. Then the private key could reside in an HSM, and apps like this could give HSMs requests to sign. IMO even though this could be done in an afternoon, everyone - Apple and Google, the CDN / WAF provider, the service provider - is too addicted to the telemetry.
You can set up an MCP and use it in your existing AI app, but is afaiu the first open source standalone app that gives you a familiar interface to other SQL workspace tools. I built it to be a familiar but much more powerful experience for both technical and nontechnical people.
> I wish you luck in refining your differentiation.
Can't agree more with you. It's about distribution (which Snowflake/Databricks/... have) or differentiation.
Still, chatting with your data is already working and useful for lots.
The first doesn't have good UX and the second isn't open source. SnapQL is both :) But I'll find new ways to differentiate for sure, it's part of the fun of building.
The demo video in the README legit tried to give me a seizure tho…
Question, how are you testing this? Like doing it on dummy data is a bit too easy. These models, even 4o, falter when it comes to something really specific to a domain (like I work with supply chain data and other column names specific to the work that I do, that only makes sense to me and my team, but wouldn't make any sense to an LLM unless it somehow knows what those columns are)
And thank you for offering to contribute. I'll be very active on GitHub!
For analytical purposes, this text-to-SQL is the future; it's already huge with Snowflake (https://www.snowflake.com/en/engineering-blog/cortex-analyst...).
I could see this being incredible if it had a set of performance related queries or ran explain analyze and offered some interpreted results.
Can this be run fully locally with a local llm?
Pardon my technical ignorance, but what exactly is OpenAI's API being used for in this?
https://github.com/NickTikhonov/snap-ql/blob/main/src/main/l...
[0]: https://github.com/NickTikhonov/snap-ql/blob/409e937fa330deb...
[1]: https://github.com/vercel/ai
Side note: I don't see a license anywhere, so technically it isn't open source.
I wish you luck in refining your differentiation.
> I wish you luck in refining your differentiation. Can't agree more with you. It's about distribution (which Snowflake/Databricks/... have) or differentiation.
Still, chatting with your data is already working and useful for lots.