/natural-language-postgres

Primary LanguageTypeScript

Natural Language PostgreSQL

Deploy with Vercel

This project is a Next.js application that allows users to query a PostgreSQL database using natural language and visualize the results. It's powered by the AI SDK by Vercel and uses OpenAI's GPT-4o model to translate natural language queries into SQL.

Features

  • Natural Language to SQL: Users can input queries in plain English, which are then converted to SQL using AI.
  • Data Visualization: Results are displayed in both table and chart formats, with the chart type automatically selected based on the data.
  • Query Explanation: Users can view the full SQL query and get an AI-generated explanation of each part of the query.

Technology Stack

  • Next.js for the frontend and API routes
  • AI SDK by Vercel for AI integration
  • OpenAI's GPT-4o for natural language processing
  • PostgreSQL for data storage
  • Vercel Postgres for database hosting
  • Framer Motion for animations
  • ShadowUI for UI components
  • Tailwind CSS for styling
  • Recharts for data visualization

How It Works

  1. The user enters a natural language query about unicorn companies.
  2. The application uses GPT-4 to generate an appropriate SQL query.
  3. The SQL query is executed against the PostgreSQL database.
  4. Results are displayed in a table format.
  5. An AI-generated chart configuration is created based on the data.
  6. The results are visualized using the generated chart configuration.
  7. Users can toggle between table and chart views.
  8. Users can request an explanation of the SQL query, which is also generated by AI.

Data

The database contains information about unicorn companies, including:

  • Company name
  • Valuation
  • Date joined (unicorn status)
  • Country
  • City
  • Industry
  • Select investors

This data is based on CB Insights' list of unicorn companies.

Getting Started

To get the project up and running, follow these steps:

  1. Install dependencies:

    npm install

  2. Copy the example environment file:

    cp .env.example .env

  3. Add your OpenAI API key and PostgreSQL connection string to the .env file:

    OPENAI_API_KEY=your_api_key_here
POSTGRES_URL="..."
POSTGRES_PRISMA_URL="..."
POSTGRES_URL_NO_SSL="..."
POSTGRES_URL_NON_POOLING="..."
POSTGRES_USER="..."
POSTGRES_HOST="..."
POSTGRES_PASSWORD="..."
POSTGRES_DATABASE="..."

  4. Download the dataset:

  1. Seed the database:
npm run seed
  1. Start the development server: 
    npm run dev

Your project should now be running on http://localhost:3000.

Deployment

The project is set up for easy deployment on Vercel. Use the "Deploy with Vercel" button in the repository to create your own instance of the application.

Deploy with Vercel

Learn More

To learn more about the technologies used in this project, check out the following resources: