Database Architect Agent

An advanced, AI-powered system that generates comprehensive database schemas from natural language descriptions. Designed with a professional enterprise aesthetic, this agent delivers production-ready SQL and Mermaid entity-relationship diagrams instantly.

🚀 Features

• 🤖 Intelligent Schema Generation: Powered by OpenAI's GPT-4 Turbo (or advanced mock logic), acting as a Senior Database Architect.
• 🎨 Enterprise UI: A clean, modern interface featuring a specific "Blue/Slate" professional theme.
• 🔄 Dual-Dialect Support: Generate optimized SQL for PostgreSQL, MySQL, SQLite, and SQL Server.
• 📊 Interactive Visualization: Automatically compiles generic schemas into Mermaid.js ER diagrams for instant clarity.
• ⚡ Real-time Compilation: See the generated SQL code side-by-side with the visual diagram.
• 🔒 Secure & Exportable: Download your schema as a .sql file or copy it directly to your clipboard.

🏗 Architecture

The application is built on a robust modern stack:

• Frontend: React + TypeScript + Vite + Tailwind CSS (v4) + Zustand + Mermaid.js
• Backend: Python FastAPI + Pydantic + OpenAI SDK + Python-Dotenv

Workflow

1. User Input: You describe your data requirements (e.g., "A multi-vendor e-commerce platform").
2. AI Orchestration: The backend constructs a "Senior Architect" system prompt and queries the LLM.
3. Structured IR: The AI returns a strict JSON Intermediate Representation (IR) of the schema.
4. Compilation: The frontend compiles this IR into both SQL DDL statements and Mermaid diagram syntax.
5. Visualization: The UI renders the diagram and SQL editor for user review.

🛠 Prerequisites

• Node.js 18+
• Python 3.10+
• OpenAI API Key (optional, defaults to advanced mock generator if missing)

🏁 Getting Started

1. Backend Setup

cd backend

# Install dependencies
pip install -r requirements.txt

# Configure Environment
# Create a .env file and add your API key:
# OPENAI_API_KEY=sk-proj-...
# (If skipped, the system uses a Mock Generator for demo purposes)

# Run the server
python main.py

The API runs at http://localhost:8000

2. Frontend Setup

cd frontend

# Install dependencies
npm install

# Run the development server
npm run dev

The application runs at http://localhost:5173

💡 Usage

1. Open http://localhost:5173.
2. In the prompt box, enter a description like:

   "Design a database for a blog with users, posts, comments, and tags."

3. Select your target SQL Dialect (e.g., PostgreSQL).
4. Click Generate.
5. Review the SQL Code and Schema Diagram in the results pane.
6. Click Download SQL File to save your schema.

📄 License

MIT License