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AI Course Generator

course-gpt 🤖 combines OpenAI API, YouTube API, and Unsplash API to enable easy course creation. Transform ideas into educational content with AI assistance and rich media integration.

AI Course Generator

With this application, you can easily create and customize AI courses, making it a valuable tool for both educators and AI enthusiasts.

Problem and Solution

The biggest problem while creating this application was AI uncertainity means not able to get desired output.

I used the output parser provided by langchain but still its creating issue.

But still,I only got desired result in 8 out of 10 tries.

Technologies Used

  • Next.js: A popular React framework for building fast and efficient web applications.
  • Prisma: A database toolkit and ORM for Node.js and TypeScript.
  • Docker: Containerization for easy deployment and scalability.
  • Tailwind CSS: A utility-first CSS framework for designing responsive and modern UIs.
  • Stripe AI: For secure payment processing.
  • Digital Ocean: A cloud infrastructure provider for hosting and scaling the application.
  • Nginx: A web server used for reverse proxy and serving the application.
  • Recoil: A state management library for React applications.
  • TypeScript: A statically typed superset of JavaScript for enhanced code quality.
  • Shadcn UI: A UI component library.
  • Next UI: UI components and utilities for Next.js applications.

Features

  • Generate AI courses based on your preferences and inputs.
  • Access a vast library of AI-related content from YouTube and Unsplash.
  • Customize and organize course content as per your requirements.
  • Secure and easy payment processing with Stripe AI.
  • Scalable and deployable on Digital Ocean with Docker and Nginx.

Getting Started

Follow these steps to get the AI Course Generator up and running:

  1. Clone the repository: git clone https://github.com/Abhi1992002/course-gpt.git
  2. Install dependencies: npm install or yarn install
  3. Configure environment variables for API keys and other sensitive information.
  4. Start the application: npm run dev or yarn dev
  5. Open your browser and navigate to http://localhost:3000