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

[TKDE'25] 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. Official repo for A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?

基于python和llm大模型开发的数据处理和任务调度系统。 支持数据源管理，数据模型管理，数据集成，数据查询API接口，低代码自定义数据处理任务模版，单任务及dag任务工作流调度等功能。集成了llm模块实现rag知识库问答，链接各数据源数据进行数据对话问答，交互式数据分析功能。

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

A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG

RSL-SQL: Robust Schema Linking in Text-to-SQL Generation

🔥[VLDB'24] Official repository for the paper “The Dawn of Natural Language to SQL: Are We Fully Ready?”

GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training

This repo accelerates development of RAG applications with rich data sources including SQL Warehouses and documents analysed with Azure Document Intelligence

Convert natural language query to appropriate SQL, make ERPs cool again.

Fine-Tuning Dataset Auto-Generation for Graph Query Languages.

🌶️ R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)

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

Text2SQL Engine with advanced RAG

The easiest and most comprehensive framework for building enterprise-grade NL2SQL solutions at scale.

The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question IntentionClassification Benchmark for Text-to-SQL"

EvalBench is a flexible framework designed to measure the quality of generative AI (GenAI) workflows around database specific tasks.

Table2answer: Read the database and answer without SQL https://arxiv.org/abs/1902.04260

轻量化自然语言数据库查询工具，支持多轮对话完善查询目标，精确输出SQL查询语句、执行查询、数据分析并返回自然语言结果。A lightweight system enbales multiple rounds of chat to transfer natural language into SQL query, execute query, perform data analysis and return analysis results.

Using Database Rule for Weak Supervised Text-to-SQL Generation https://arxiv.org/abs/1907.00620