Text-to-SQL Agent

About

The Text-to-SQL Agent is an AI-powered tool built with Next.js that allows users to convert natural language queries into SQL commands and directly interact with a database. It utilizes LangChain, LangGraph, and Ollama to generate, execute, and refine SQL queries dynamically. The system can retrieve data from the database, enabling seamless interactions without requiring manual SQL writing.

Features

• Natural Language to SQL Conversion: Converts user queries into SQL statements.
• Direct Database Interaction: Executes generated SQL queries and fetches results.
• Multi-Step Query Processing: Uses LangGraph for structured query generation.
• Supports SQLite: Works with SQLite databases for lightweight and fast execution.
• Extensible and Modular: Easily adaptable for other databases or additional AI capabilities.

Technologies Used

• Next.js: Framework for building the frontend and backend.
• LangChain: For natural language processing and query generation.
• LangGraph: Enables structured decision-making for SQL refinement.
• Ollama: AI-powered model for query understanding.
• SQLite: Lightweight relational database engine.

Installation

Prerequisites

• Node.js (Latest LTS version recommended)
• SQLite installed
• WatsonX API credentials

Setup

1. Clone the repository:

   git clone https://github.com/AlokTheDataGuy/text-to-sql-agent.git
   cd text-to-sql-agent

2. Install dependencies:

   npm install

3. Set up environment variables in a .env.local file:

   WATSONX_AI_ENDPOINT=your_watsonx_endpoint
   WATSONX_AI_APIKEY=your_watsonx_apikey
   WATSONX_AI_PROJECT_ID=your_watsonx_project_id

4. Run the development server:

   npm run dev

Usage

1. Open http://localhost:3000 in your browser.
2. Enter a natural language query (e.g., "Show me all customers who made a purchase last month").
3. The system will generate an SQL query and execute it on the database.
4. Results will be displayed on the interface.

Contributing

1. Fork the repository.
2. Create a new branch: git checkout -b feature-branch-name.
3. Commit your changes: git commit -m "Add new feature".
4. Push to the branch: git push origin feature-branch-name.
5. Open a pull request.

License

This project is licensed under the MIT License.