[HN Gopher] Show HN: Natural Language to SQL "Text-to-SQL" API
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Show HN: Natural Language to SQL "Text-to-SQL" API
Hi HN- Today, we are releasing the hosted API for our natural
language to SQL engine, which allows you to: (1) Explain Your
Data: Feed in dictionaries, dbt, schemas, Confluence docs - we'll
understand the business context to your data. (2) Train Your AI:
Fine-tune an LLM (including GPT-4) specifically for your data,
increasing accuracy and lowering latency (3) Trust the Answer: See
confidence scores with each AI-generated query, stay in control.
(4) Conduct complex SQL queries Problem background - Developers
struggle to build NL-to-SQL into products because LLMs do not work
out-of-the-box; they lack metadata and business definitions.
Existing NL-to-SQL tools struggle with context, complexity, and
adapting to your data. For example, given the question "what was
the average rent in Los Angeles in May 2023?" a reasonable human
would either assume the question is about Los Angeles, CA or would
confirm the state with the question asker in a follow up. However,
an LLM translates this to: select price from
rent_prices where city="Los Angeles" AND month="05" AND year="2023"
Dataherald integrates with major data warehouses, including
PostgreSQL, Databricks, Snowflake, BigQuery, and DuckDB. You can
try it now free - no fees, no credit card, no sales pitches, just
get the API key and get going. Let us know if it works for you,
even your complex queries.
(https://console.dataherald.ai/playground) While the open source
version works just fine (https://github.com/Dataherald/dataherald),
the hosted API might be a better fit for those looking for: (1)
someone else to take care of infrastructure setup, (2) access to an
Admin UI console where you can configure and monitor performance,
and (3) ability to invite team members to a project. We're looking
for feedback, particularly from anyone who can compare this
performance to other NL-to-SQL products. Share your thoughts and
join the conversation For more background on the release:
https://www.dataherald.com/news/introducing-dhai
Author : saigal
Score : 25 points
Date : 2024-02-14 19:03 UTC (3 hours ago)
(HTM) web link (www.dataherald.com)
(TXT) w3m dump (www.dataherald.com)
| nick_rocks wrote:
| What do you mean by complex SQL? How complex?
| aazo11 wrote:
| For large databases, LLMs do not perform well if you pass the
| entire schema (either run into context window issues or confuse
| the LLM with too much info). There is a schema linking step
| that identifies the relevant schema and only passes that. The
| schema linking is also done in the fine-tuning process.
| deely3 wrote:
| Good, but.. What do you mean by complex SQL? How complex?
| aazo11 wrote:
| The largest we have successfully deployed is on the OSQuery
| schema https://osquery.io/ which is 277 tables and lots of
| business context (malwares, vulnerabilities, Windows
| registry keys, etc).
| edmundsauto wrote:
| I've been playing w/ this product self-hosted for a few weeks.
| It can join across multiple tables, windowing functions. I
| haven't tried self-joins yet, nor I have put much effort into
| tuning w/ Golden SQL or other documentation.
|
| I would put this at the skill level of a junior data engineer.
| It's pretty impressive.
| cstanley wrote:
| If you don't want to integrate an API, and want an interface for
| everyone to use that _just works_ with charting check out
| patterns.app
| daenney wrote:
| The submitted link results in a login wall. It would probably be
| worth updating the submission to the introducing-dhai page that's
| mentioned all the way at the end here, as getting greeted by a
| login prompt that way isn't going to entice people to explore or
| learn about the product.
| saigal wrote:
| i'll try to change it out the link
| dang wrote:
| We've switched from https://console.dataherald.ai/playground by
| OP's request.
| saigal wrote:
| The API introduction announcement is here:
| https://www.dataherald.com/news/introducing-dhai
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(page generated 2024-02-14 23:00 UTC)