AI PromptCraft Analyzer

A Next.js application for teachers to input, evaluate, refine, and execute AI prompts.

Features

• Prompt Input and Evaluation: Analyze prompts for effectiveness
• Prompt Execution: Test prompts with AI responses
• Prompt Management: Save and organize your prompts
• Learning Resources: Educational content on prompt engineering
• User Authentication: Secure login with Google via Supabase

Tech Stack

• Frontend: Next.js 14 with App Router, React, and Tailwind CSS
• Backend: Next.js API routes
• Database: PostgreSQL with Prisma ORM
• Authentication: Supabase

Getting Started

1. Clone the repository
2. Install dependencies:

   npm install

3. Set up environment variables in .env:

   DATABASE_URL="postgresql://user:password@localhost:5432/mydatabase"
   NEXT_PUBLIC_SUPABASE_URL="your-supabase-url"
   NEXT_PUBLIC_SUPABASE_ANON_KEY="your-supabase-anon-key"
   

4. Generate Prisma client:

   npm run prisma:generate

5. Create database schema:

   npm run prisma:push

6. Run the development server:

   npm run dev

7. Open http://localhost:3000 in your browser

Project Structure

• app/: Page components and API routes
• components/: Reusable UI components
• lib/: Utility functions and configurations
• prisma/: Database schema and configurations
• public/: Static assets

Key Features Implementation

Prompt Evaluation

The prompt evaluation feature analyzes user prompts based on several criteria:

• Tone/Persona
• Task Clarity
• Format & Output Specification
• Context & Background

The application then provides a detailed analysis with suggestions for improvement.

Prompt Execution

The prompt execution feature sends the user's prompt to an AI model and displays the response, allowing users to:

• Test their prompts with real AI models
• Compare different versions of prompts
• Save successful prompts for future use

My Prompts Management

Users can:

• Save prompts with versions
• Organize prompts by categories
• Mark favorites for quick access
• Track prompt performance and history

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Next.js team for the amazing framework
• Supabase for authentication and database solutions
• The developers of all the libraries used in this project