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Show HN: SnapQL – Desktop app to query Postgres with AI

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Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#31
post #26

Earlier quoted context omitted.

What I meant was that it isn't a web app and I don't store your connection strings or query results. I'll make this more clear

You might not but openai does.

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.

Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#33
post #26

Earlier quoted context omitted.

What I meant was that it isn't a web app and I don't store your connection strings or query results. I'll make this more clear

You might not but openai does.

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.

Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#34
post #26

Earlier quoted context omitted.

You might not but openai does.

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.

But it knows what you're querying, which depending on what you're doing may also give away a good bit about whats in the DB.

Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#35
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)

Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#36
This is nice -- we're heavy users of postgresql and haven't found the right tool here yet.

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?

Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#37

This is nice -- we're heavy users of postgresql and haven't found the right tool here yet. 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?

Thank you for the feedback. Please feel free to raise some issues on the repo and we can jam this out there

Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#39

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 an…

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!

Re: Show HN: SnapQL – Desktop app to query Postgres with AI

#40

This is nice -- we're heavy users of postgresql and haven't found the right tool here yet. 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?

just opened a PR for local llm support https://github.com/NickTikhonov/snap-ql/pull/11
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