dataherald
ada
| dataherald | ada | |
|---|---|---|
| 4 | 5 | |
| 1,163 | 28 | |
| 7.7% | - | |
| 9.3 | 8.7 | |
| 2 days ago | 8 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dataherald
-
Show HN: Natural Language to SQL "Text-to-SQL" API by Dataherald
Hi HN- Today, we are releasing the hosted API for Dataherald's natural language to SQL engine.
The Dataherald hosted API 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
All this with a few simple API calls.
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:
- Show HN: Dataherald AI – Natural Language to SQL Engine
ada
- ADA: Accelerate Data Analysis with AI
-
Ask HN: What apps have you created for your own use?
I built Ada - https://github.com/BenderV/ada - a BI tool to leverage AI for data analysis.
-
Show HN: Dataherald AI – Natural Language to SQL Engine
I switched to chat version, named [Ada](https://github.com/BenderV/ada), and IMHO, it's better. The AI explore the database, it's connection, the data format & co. Plus, it help with ambiguity and feels more "natural".
What are some alternatives?
sqlcoder - SoTA LLM for converting natural language questions to SQL queries
spider - scripts and baselines for Spider: Yale complex and cross-domain semantic parsing and text-to-SQL challenge
LLMStack - No-code platform to build LLM Agents, workflows and applications with your data
DB-GPT-Hub - A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL
sql-examples - Curated list of SQL to help you find useful script easily 🚀
gitbi - Lightweight BI app based on git repo
beekeeper-studio - Modern and easy to use SQL client for MySQL, Postgres, SQLite, SQL Server, and more. Linux, MacOS, and Windows.
tableQA - AI Tool for querying natural language on tabular data.