nl2sql

🔥 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.

Curated tutorials and resources for Large Language Models, Text2SQL, Text2DSL、Text2API、Text2Vis and more.

A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL

This is a continuously updated handbook for readers to easily track the latest Text-to-SQL techniques in the literature and provide practical guidance for researchers and practitioners.

[TKDE2025] Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on large language model-based text-to-SQL.

AI-powered desktop SQL client. Cross-platform. Built with Flutter.

Continuously updated paper list on advancements in Data Agents. Companion repo to our paper "A Survey of Data Agents: Emerging Paradigm or Overstated Hype?"

追一科技首届中文NL2SQL挑战赛决赛第3名方案+代码

Agentar-Scale-SQL is a novel framework that leverages scalable computation to significantly improve Text-to-SQL performance.

A relation-aware semantic parsing model from English to SQL

📊 电商数仓智能问数 AI Agent，最适合用于系统学习 LangGraph 的实战项目：基于 LangGraph、FastAPI、Qdrant、Elasticsearch、MySQL 与 React，完整实现元数据知识库、混合检索、自然语言生成 NL2SQL 生成校验、SQL 执行与流式查询展示。前后端完整代码全栈可跑，Docker 环境一键部署，配套 ai-agents-from-zero 免费教程与章节代码分支。适合系统学习大模型应用、数据分析 Agent 和企业级 AI 工程落地。

AI Tool for querying natural language on tabular data.

Asking yours data in a natural language way through pre-modeling (data models and semantic models).

NL2SQL - Ask questions in plain English, get SQL queries and results. Powered by LangGraph.

The Open Data QnA python library enables you to chat with your databases by leveraging LLM Agents on Google Cloud. Open Data QnA enables a conversational approach to interacting with your data by implementing state-of-the-art NL2SQL / Text2SQL methods.

阿里天池首届中文NL2SQL挑战赛top6

The Resources for "Natural Language to Logical Form" ; "自然语言转逻辑形式"研究资料收集。

CogniDB is a Python-powered Natural Language to SQL interface that enables users to query databases like MySQL, PostgreSQL, MongoDB, and AWS RDS using plain English. It parses questions, understands schema, generates safe SQL, and returns results, empowering non-technical users to gain database insights without writing SQL.

Content Enhanced BERT-based Text-to-SQL Generation https://arxiv.org/abs/1910.07179

Agentic text-to-SQL SDK: hand the LLM one execute_sql tool and let it explore the schema, test queries, and self-correct — no RAG, no semantic layer. 20/20 on an 80-table Spider run. Built-in tracing and scenario support.