Zay-M3/NaturalSQL
Este es un proyecto para experimentar sobre el conceto de RAG y como se implementa esta tactica de contexto en los modelos grandes de IA (LLM)
This tool helps data analysts, business intelligence specialists, or anyone needing to query data to quickly get the right SQL table information for their questions. You provide a natural language question and your database schema, and it identifies the most relevant tables and columns, making it easier to construct accurate SQL queries. It's designed for anyone who interacts with databases and wants to leverage large language models to assist with query writing.
Use this if you need to find specific database tables and columns relevant to a natural language question, speeding up the process of writing SQL queries, especially when working with large or unfamiliar databases.
Not ideal if you prefer to hand-craft all your SQL queries from scratch or are looking for a complete end-to-end SQL generation tool that writes the entire query for you without your intervention.
Stars
16
Forks
4
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 26, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/Zay-M3/NaturalSQL"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
mindsdb/mindsdb
Query Engine for AI Analytics: Build self-reasoning agents across all your live data
dataease/SQLBot
🔥 基于大模型和 RAG 的智能问数系统，对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.
vanna-ai/vanna
🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using Agentic Retrieval 🔄.
weAIDB/CrackSQL
LLM-based Dialect Translation System
Canner/WrenAI
⚡️ GenBI (Generative BI) queries any database in natural language, generates accurate SQL...