Dataherald
Embed NL-to-SQL into your product
Dataherald launched on January 24, 2024 with 126 votes, #406 of 4,438 launches that month and more than 75% of that year's launches.
What it does
Dataherald lets you embed Natural Language to SQL (“NL-to-SQL”) into your product. The NL-to-SQL API, built with an LLM (such as GPT), allows users to conduct no-code data analytics, pull reports, and conduct complex data queries using just natural language.
Does a similar job
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We open sourced our entire text-to-SQL product2024 · github.com · ▲464Long story short: We (Dataherald) just open-sourced our entire codebase, including the core engine, the clients that interact with it and the backend application layer for authentication and RBAC. You can now use the full solution to build text-to-SQL into your product. The Problem: modern LLMs write syntactically correct SQL, but they struggle with real-world relational data. This is because real world data and schema is messy, natural language can often be ambiguous and LLMs are not trained on your specific dataset. Solution: The core NL-to-SQL engine in Dataherald is an LLM based agent…
Dataherald AI – Natural Language to SQL Engine2023 · github.com · ▲215Hi HN community. We are excited to open source Dataherald’s natural-language-to-SQL engine today (https://github.com/Dataherald/dataherald). This engine allows you to set up an API from your structured database that can answer questions in plain English. GPT-4 class LLMs have gotten remarkably good at writing SQL. However, out-of-the-box LLMs and existing frameworks would not work with our own structured data at a necessary quality level. For example, given the question “what was the average rent in Los Angeles in May 2023?” a reasonable human would either assume the…
- NLNatural Language to SQL "Text-to-SQL" API2024 · dataherald.com · ▲62
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;…
Natural-SQL-7B, a strong text-to-SQL model2024 · github.com · ▲362Would love thoughts! Here is the HF page: https://huggingface.co/chatdb/natural-sql-7b
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