kleon

AI-Powered Data Query Interface using Rust

Features

• SQL Query Explanation: Input an SQL query and receive a detailed explanation of its purpose and functionality.
• SQL Query Generation: Provide a prompt to generate SQL queries for various use cases, such as SELECT, INSERT, UPDATE, DELETE, JOIN, and aggregation operations.

Technologies Used

• Frontend: Next.js
• Backend: Rust (for query generation and explanation)
• API Communication: Axios for making HTTP requests
• Database: MySQL

Getting Started

Prerequisites

• Node.js (v16.0 or later)
• Rust (for backend development)
• MySQL database

Installation

1. Clone the Repository

   git clone https://github.com/yourusername/sql-query-tool.git
   cd sql-query-tool

2. Set Up the Frontend

Navigate to the frontend directory and install dependencies:

cd frontend
npm install

3. Set Up the Backend

Navigate to the backend directory and install dependencies:

cd backend
cargo build

4. Configure Environment Variables
5. Create a .env file in both frontend and backend directories and set up your environment variables. Example .env file for frontend:

.env

NEXT_PUBLIC_API_URL=http://localhost:8080

6. Example .env file for backend:

.env

DATABASE_URL=mysql://user:password@localhost:3306/yourdatabase

7. Run the Project Start the backend server:

cd backend
cargo run

8. Start the frontend server:

cd frontend
npm run dev

The frontend should now be available at http://localhost:3000, and it will communicate with the backend at http://localhost:8080.

Usage

1. Explaining SQL Queries
2. Navigate to the Explain Query section.
3. Enter your SQL query into the text area.
4. Click Explain Query to receive a detailed explanation.
5. Generating SQL Queries
6. Navigate to the Generate Query section.
7. Provide a prompt describing the SQL query you need.
8. Click Generate Query to receive the generated SQL query.
9. API Endpoints
10. POST /api/explain_sql

Request Body: { "prompt": "your SQL query", "dialect": "mysql" }
Response: { "message": "Explanation of the query" }

2. POST /api/generate_sql

Request Body: { "prompt": "your query prompt", "dialect": "mysql" }
Response: { "query": "Generated SQL query" }

10. Contributing
Feel free to contribute to this project by submitting pull requests or opening issues. Contributions are welcome to improve the functionality or add new features.