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Show HN: We open sourced our entire text-to-SQL product

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Re: Show HN: We open sourced our entire text-to-SQL product

#61
post #50
post #41

Earlier quoted context omitted.

i agree that there will be "early adopter" type use cases and others that might take a while (e.g. healthcare with hipaa compliance) it is still the early days. goal is to give the developer tools to do this easier.

Enough of this weasel talk. It's not the early days. Not by a country mile. To quote Cory Doctorow > I don’t see any path from continuous improvements to the (admittedly impressive) ”machine learning” field that leads to a general AI any more than I can see a path from continuous improvements in horse-breeding that leads to an internal combustion engine. You can counter it doesn't necessarily need an AGI here but tha…

> can't crank this engine harder and expect it to power an airplane.

Similarly, but from my far-less notable-self in another discussion today:

> [H]uman exuberance is riding on the (questionable) idea that a really good text-correlation specialist can effectively impersonate a general AI.

> Even worse: Some people assume an exceptional text-specialist model will effectively meta-impersonate a generalist model impersonating a different kind of specialist!

Re: Show HN: We open sourced our entire text-to-SQL product

#62
>Would love to hear from the community on building natural language interfaces to relational data.

I produce a free sql editor that allows users to plugin openai to perform text to sql: https://www.timestored.com/qstudio/help/ai-text2sql so far uptake is slow and the only good benefit is to spit out a few queries as a starting point. The accuracy went up significantly by sending schema and sample data but it sounds like you've done a good job at going beyond that. I wouldn't say my users or I am convinced it's the future but I'll certainly look at your product tomorrow. Good work and congratulations.

Re: Show HN: We open sourced our entire text-to-SQL product

#63

>Would love to hear from the community on building natural language interfaces to relational data. I produce a free sql editor that allows users to plugin openai to perform text to sql: https://www.timestored.com/qstudio/help/ai-text2sql so far uptake is slow and the only good benefit is to spit out a few queries as a starting point. The accuracy went up significantly by sending schema and sample data but it sounds l…

Yes please do. We’d love your feedback and or to hear whether you see material improvement over what you have now

Re: Show HN: We open sourced our entire text-to-SQL product

#64
post #50

Earlier quoted context omitted.

Enough of this weasel talk. It's not the early days. Not by a country mile. To quote Cory Doctorow > I don’t see any path from continuous improvements to the (admittedly impressive) ”machine learning” field that leads to a general AI any more than I can see a path from continuous improvements in horse-breeding that leads to an internal combustion engine. You can counter it doesn't necessarily need an AGI here but tha…

Indeed, AI is not marketed as a BS generator, just as HTTP is not marketed as a spam/ad/fraud/harassment transport protocol. All technologies are dual-use, deal with it!

There's the old adage of "trust, but verify" with LLM's I'm feeling it more like "Acknowledge, but verify, and verify again". It has certainly pointed me in the right direction faster vs google "here's some SEO stuff to sort through" :)

Re: Show HN: We open sourced our entire text-to-SQL product

#66

Earlier quoted context omitted.

Indeed, AI is not marketed as a BS generator, just as HTTP is not marketed as a spam/ad/fraud/harassment transport protocol. All technologies are dual-use, deal with it!

There's the old adage of "trust, but verify" with LLM's I'm feeling it more like "Acknowledge, but verify, and verify again". It has certainly pointed me in the right direction faster vs google "here's some SEO stuff to sort through" :)

I agree with you. The larger point with text to SQL, however, is that it will not work if it is a simple wrap of an LLM (GPT or otherwise). Text to SQL will only work if there is a sufficient understanding of the business context required. To do this is hard, but with tools such as Dataherald a dev's life gets a whole lot easier.

Re: Show HN: We open sourced our entire text-to-SQL product

#67
post #41

Earlier quoted context omitted.

With what level of accuracy? And what guarantee of correctness? Because a report that happens to get the joins wrong once every 1000 reports is going to lead to fun legal problems. You still need someone who understands why you should use which approach to get the data you need without getting completely wrong numbers back that _look_ perfectly fine but reflect fantasy, not reality.

i agree that there will be "early adopter" type use cases and others that might take a while (e.g. healthcare with hipaa compliance) it is still the early days. goal is to give the developer tools to do this easier.

Its not the early days in terms of expecting digital tools to be correct 99% of the time. Early adoption age was back in 2000-2009. Now everyone expects polished tools that does what it expects them to do

Re: Show HN: We open sourced our entire text-to-SQL product

#68
post #59

Earlier quoted context omitted.

What? How does that ensure user 123 only generates LLM queries that constrain on rows where user=123?

As I wrote on the original thread, we recommend using the RDBMS row-level security features. This blog discusses how to do that on Postgres https://www.2ndquadrant.com/en/blog/application-users-vs-row...

Way way too complicated. I thought this tool was suppsed to make my life easier

Re: Show HN: We open sourced our entire text-to-SQL product

#70
post #54

Earlier quoted context omitted.

> I could see it being used in a tool for new devs or those who've focused on a JS stack and need some help with SQL Or they could buy a book like Learning SQL . Or spend a weekend on Youtube.

allow me to clarify.. Dataherald isn't intended for developers because they don't know SQL, it's intended for developers who want to build text to SQL into their products

But who wants text-to-sql in products that they use? You wouldn't be able to trust the results. So what is it useful for? Of course you could learn to check the output. But then you could just learn SQL. I know dozens of not particularly technical people (certainly not software developers) who have learnt enough SQL to be useful over a couple of days.
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