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databrainhq
dataneuron
Python2024–2024
databrainhq / dataneuron · Archived

dataneuron

Data Neuron is a powerful framework that enables you to build text-to-SQL applications with an easily maintainable semantic layer. Whether you're creating customer-facing chatbots, internal Slack bots for analytics, or other data-driven applications, Data Neuron provides the tools to make your data accessible through natural language

2Distinct people
2Mentions
0Explicit recommenders
45GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Data Neuron is a powerful framework that enables you to build text-to-SQL applications with an easily maintainable semantic layer. Whether you're creating customer-facing chatbots, internal Slack bots for analytics, or other data-driven applications, Data Neuron provides the tools to make your data accessible through natural language

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by hour2 dated mentions

Observed mentions: 2024-07-25 20:29:41 UTC to 2024-07-26 15:16:49 UTC.

012024-07-25 20:00:00 UTC to 2024-07-25 21:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsJul 25, 20:002024-07-25 21:00:00 UTC to 2024-07-25 22:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-25 22:00:00 UTC to 2024-07-25 23:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-25 23:00:00 UTC to 2024-07-26 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 00:00:00 UTC to 2024-07-26 01:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 01:00:00 UTC to 2024-07-26 02:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 02:00:00 UTC to 2024-07-26 03:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 03:00:00 UTC to 2024-07-26 04:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 04:00:00 UTC to 2024-07-26 05:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 05:00:00 UTC to 2024-07-26 06:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJul 26, 05:002024-07-26 06:00:00 UTC to 2024-07-26 07:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 07:00:00 UTC to 2024-07-26 08:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 08:00:00 UTC to 2024-07-26 09:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 09:00:00 UTC to 2024-07-26 10:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 10:00:00 UTC to 2024-07-26 11:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 11:00:00 UTC to 2024-07-26 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 12:00:00 UTC to 2024-07-26 13:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 13:00:00 UTC to 2024-07-26 14:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 14:00:00 UTC to 2024-07-26 15:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-26 15:00:00 UTC to 2024-07-26 16:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsJul 26, 15:00

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jul 25, 20:002024-07-25 20:00:00 UTC2024-07-25 21:00:00 UTC110
Jul 25, 21:002024-07-25 21:00:00 UTC2024-07-25 22:00:00 UTC000
Jul 25, 22:002024-07-25 22:00:00 UTC2024-07-25 23:00:00 UTC000
Jul 25, 23:002024-07-25 23:00:00 UTC2024-07-26 00:00:00 UTC000
Jul 26, 00:002024-07-26 00:00:00 UTC2024-07-26 01:00:00 UTC000
Jul 26, 01:002024-07-26 01:00:00 UTC2024-07-26 02:00:00 UTC000
Jul 26, 02:002024-07-26 02:00:00 UTC2024-07-26 03:00:00 UTC000
Jul 26, 03:002024-07-26 03:00:00 UTC2024-07-26 04:00:00 UTC000
Jul 26, 04:002024-07-26 04:00:00 UTC2024-07-26 05:00:00 UTC000
Jul 26, 05:002024-07-26 05:00:00 UTC2024-07-26 06:00:00 UTC000
Jul 26, 06:002024-07-26 06:00:00 UTC2024-07-26 07:00:00 UTC000
Jul 26, 07:002024-07-26 07:00:00 UTC2024-07-26 08:00:00 UTC000
Jul 26, 08:002024-07-26 08:00:00 UTC2024-07-26 09:00:00 UTC000
Jul 26, 09:002024-07-26 09:00:00 UTC2024-07-26 10:00:00 UTC000
Jul 26, 10:002024-07-26 10:00:00 UTC2024-07-26 11:00:00 UTC000
Jul 26, 11:002024-07-26 11:00:00 UTC2024-07-26 12:00:00 UTC000
Jul 26, 12:002024-07-26 12:00:00 UTC2024-07-26 13:00:00 UTC000
Jul 26, 13:002024-07-26 13:00:00 UTC2024-07-26 14:00:00 UTC000
Jul 26, 14:002024-07-26 14:00:00 UTC2024-07-26 15:00:00 UTC000
Jul 26, 15:002024-07-26 15:00:00 UTC2024-07-26 16:00:00 UTC110

What Hacker News says

2 sources
vysakh0·Jul 25, 2024Submission

Show HN: Data Neuron – a framework to create AI data analyst

Data Neuron is a CLI framework to maintain a semantic/context layer and query DB in natural language. We have been trying to solve the text to sql problem in my company for quite sometime. We have been using a version of semantic layer or the context to get text2sql to some accuracy in our product. The internal framework is UI based and for datawarehouses. I thought I'll create a quick mini version of it (hence the name "neuron", our company is DataBrain) which is a cli tool. Currently supports: SQLite, PostgreSQL, MySQL, MSSQL Works well with Claude 3.5 sonnet which is the default, also has support for OpenAI, LLAMA, Mistral.. The objective is to have a framework or approach so one can create, maintain, improve the semantic layer such that an AI agent can answer questions about one's data. Next set of plans: If one wants to fine tune, tr
Read the rest
ansform the context layer to a compatible dataset. And also to create a flask python API to accept incoming questions and return results as json or stream. And to support synthetic query generation based on existing context and to support some form of eval/testing of the generated queries. I have been wanting it to do this cli for quite sometime. This is just a minimal, quickly put together, early version of it. Any feedback would be appreciated!
1 points · Open discussion

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