Text to SQL
Explore the best open-source Text to SQL tools. Compare top-rated repositories by star count and activity to find the best fit for your project.
Text to SQL
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- chat2db/chat2db
chat2db/Chat2DB
25,762View on GitHubChat2DB is an AI-powered SQL client and multi-database management GUI. It serves as a centralized graphical interface for administering diverse relational and non-relational database engines, integrating large language models to transform natural language prompts into executable SQL statements and application code. The tool utilizes schema-aware prompt engineering to inject database metadata into AI requests, ensuring generated queries match the actual schema. It also functions as an AI data reporting tool, using artificial intelligence to create dashboards and visual reports directly from da
Chat2DB is an AI-powered SQL client that uses LLMs to translate natural language into executable SQL statements with schema-aware prompting, making it a strong fit for generating SQL from natural language queries, though it lacks explicit fine-tuning and accuracy evaluation features.
JavaDatabase Dialect AdaptersSchema-Aware Prompting - tencentmusic/supersonic
tencentmusic/supersonic
4,913View on GitHubSupersonic is an LLM-based data analysis platform and semantic layer engine that translates natural language questions into executable SQL queries. It functions as a business intelligence dashboard and text-to-SQL interface, allowing users to retrieve business metrics and insights through a conversational interface. The system decouples business definitions from physical database schemas by using a governed logical layer to define unified metrics and dimensions. This semantic modeling allows the platform to map human language patterns to curated models and translate abstract semantic statemen
Supersonic is an LLM-based platform that directly translates natural language questions into SQL queries, with semantic schema mapping, multi-database support, and built-in accuracy evaluation tools, making it a comprehensive text-to-SQL generator for your needs.
JavaBI Semantic LayersLLM-Based SQL GenerationConversational Data Analysis Tools - canner/wrenai
Canner/WrenAI
14,437View on GitHubWrenAI is a platform designed to enable natural language interaction with relational and analytical databases. By combining a text-to-SQL engine with semantic data modeling, it allows users to explore structured data through plain language questions, removing the requirement for manual code generation. The system functions by grounding natural language requests in a predefined business logic layer rather than raw database schemas. This semantic approach, supported by context-aware prompt engineering, ensures that generated queries remain consistent and accurate across an organization. The pla
WrenAI is a full text-to-SQL platform that uses LLMs, semantic data modeling, and supports multiple database dialects (PostgreSQL, BigQuery, DuckDB) via a web interface, making it a strong fit for translating natural language queries into SQL.
TypeScriptText-to-SQL TranslatorsNatural Language Query GeneratorsSemantic Data Models - vanna-ai/vanna
vanna-ai/vanna
22,707View on GitHubVanna is a Python framework designed to build conversational interfaces that translate natural language into executable database queries. It functions as an enterprise-grade toolkit that connects language models to relational databases, allowing users to retrieve information through conversational prompts rather than manual code. The system maintains context across interactions by utilizing vector databases to store historical query patterns and schema metadata. The framework distinguishes itself through a focus on security and schema-aware generation. It incorporates granular access control,
Vanna is a Python framework that directly translates natural language into SQL queries using LLMs and schema-aware generation, making it a solid fit for the intent despite missing explicit mention of model fine-tuning or accuracy evaluation tools.
PythonText-to-SQL TranslatorsEnterprise AI Integration ToolsNatural Language Data Exploration - csunny/db-gpt
csunny/DB-GPT
19,006View on GitHubDB-GPT is an AI-driven database management system that uses agentic reasoning to execute data tasks. It converts natural language prompts into executable database queries and combines structured database records with unstructured knowledge bases to provide grounded analysis. The system orchestrates multi-step reasoning chains that integrate database queries, custom scripts, and external tool calls. It allows for the packaging of domain knowledge into reusable analysis skills and executes generated code within sandboxed environments for system safety. The platform covers data orchestration ac
DB-GPT is an AI-driven platform that converts natural language into executable database queries, placing it squarely in the NL-to-SQL category, but it does not explicitly offer model fine-tuning or accuracy evaluation tools.
PythonText-to-SQL TranslatorsCode Execution SandboxesDatabase Agents - timescale/pgai
timescale/pgai
5,802View on GitHubpgai is a PostgreSQL AI toolkit and framework designed to integrate large language models and vector embeddings directly into a database. It serves as a bridge for executing machine learning model requests and performing text-to-SQL translations within standard database queries. The project provides an automated vector embedding pipeline that handles the loading, parsing, and chunking of text from tables and unstructured documents. This system utilizes a background worker to synchronize embeddings automatically as source data changes and includes specialized tools for building retrieval-augme
pgai is a PostgreSQL AI toolkit that directly translates natural language to SQL using LLMs and schema awareness, fitting the core requirement, though it is focused on PostgreSQL and does not emphasize multiple dialect support or dedicated evaluation tools.
PLpgSQLAI Model IntegrationsAI Model IntegrationsDatabase AI Toolkits - dataease/sqlbot
dataease/SQLBot
6,297View on GitHub🔥 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.
SqlBot is a conversational analytics system that uses LLMs and RAG to generate SQL from natural language queries, directly matching the core need of translating questions into SQL, though it may not include built-in fine-tuning or accuracy evaluation features.
JavaScriptConversational Data ExplorationConversation State MachinesLLM-Based SQL Generation - eosphoros-ai/db-gpt
eosphoros-ai/DB-GPT
18,999View on GitHubDB-GPT is an agentic data analysis platform and business intelligence AI that functions as a large language model data assistant. It provides a text-to-SQL interface and a sandboxed code execution environment to translate natural language into executable database queries and Python scripts. The platform utilizes iterative agentic reasoning to plan and execute multi-step data analysis workflows through tool calls. It features a modular skill-based extension system that allows domain knowledge and analysis workflows to be packaged into reusable functional components. The system integrates data
DB-GPT is an AI-powered data analysis platform with a built-in text-to-SQL interface that uses LLMs to translate natural language into database queries and offers database schema awareness, a web/API interface, and agentic reasoning for complex workflows, though it does not explicitly include model fine-tuning or accuracy evaluation tools.
PythonData Analysis AgentsText-to-SQL TranslatorsAgentic Planning - sqlchat/sqlchat
sqlchat/sqlchat
5,731View on GitHubSQL Chat is a Docker-deployed chat interface that translates natural language questions into SQL queries and executes them against connected databases. It uses a large language model to generate SQL from plain English instructions, supporting both querying and record modification through INSERT, UPDATE, and DELETE statements within the chat conversation flow. The application connects to MySQL, PostgreSQL, MSSQL, TiDB Cloud, and OceanBase databases through a unified driver abstraction layer, allowing users to interact with multiple database types from a single chat interface. Users provide the
SQL Chat is a chat interface that uses LLMs to translate natural language into SQL queries against multiple database types (MySQL, PostgreSQL, MSSQL, etc.) and runs via Docker, so it directly fits the category—though it lacks built-in fine-tuning and accuracy evaluation tools, which keeps it from being a flagship example.
TypeScriptDocker Container DeploymentsLLM-Based SQL GenerationChat-Based Interfaces - whoiskatrin/sql-translator
whoiskatrin/sql-translator
4,312View on GitHubThis project is a developer utility that functions as an artificial intelligence-powered assistant for database query management. It provides an interactive interface for translating between natural language and structured database code, simplifying the processes of writing, debugging, and maintaining complex queries. The tool distinguishes itself by incorporating schema-aware context injection, which allows it to align generated queries with specific table definitions and relationship metadata. By maintaining stateful conversation history and utilizing large language model prompting, it enab
SQL Translator is an open-source AI-powered tool that converts natural language to SQL, directly matching the core search requirement, though it may not cover advanced features like schema awareness or multi-dialect support.
TypeScriptSchema-Aware Prompting
