NeuralLearn 🧠

AI-powered learning, built to turn any topic into a structured course.

NeuralLearn is an AI-powered learning platform that transforms a topic into a complete, structured learning experience. Instead of searching through scattered tutorials and articles, learners can generate a course, work through chapters, watch relevant videos, read supporting resources, test their knowledge, and track their progress in one place.

✨ Features

🤖 AI Course Generation

Enter any topic and NeuralLearn generates a structured course with:

Course title and description
Difficulty level
Estimated learning time
Logically ordered chapters
Chapter descriptions
Relevant YouTube search queries

📚 Structured Learning

Generated courses are organized into individual chapters and lessons, making large topics easier to understand and progress through.

📝 AI-Generated Quizzes

Each chapter can include automatically generated quizzes designed around the lesson content.

Multiple-choice questions
Four answer choices
Correct-answer explanations
Knowledge testing after learning

🧠 Flashcards

NeuralLearn generates flashcards from lesson material to help reinforce important concepts through active recall.

🎥 Learning Resources

Courses can be enriched with external learning material, including:

YouTube tutorials
Educational articles
Additional resources related to the chapter

📈 Progress Tracking

Track learning progress as you move through generated courses and chapters.

🎙️ Voice Input

NeuralLearn supports microphone-based input for a more convenient learning and course-generation experience.

🔐 Authentication

User accounts are protected through Clerk authentication, allowing users to maintain their own courses and learning progress.

☕ Support Development

NeuralLearn includes a one-time donation option through Buy Me a Coffee for users who want to support continued development.

📱 PWA Support

NeuralLearn is designed as a Progressive Web App, allowing the platform to provide an app-like experience across supported devices.

🛠️ Tech Stack

Frontend

Next.js 16
React
TypeScript
Tailwind CSS
Lucide Icons

Backend

Next.js App Router
Next.js API Routes
Server-side authentication
Drizzle ORM

Database

Neon PostgreSQL

Authentication

Clerk

AI

NeuralLearn uses a resilient multi-provider AI architecture:

Groq
Google Gemini

The application uses provider and model fallbacks to improve reliability when a model is unavailable or temporarily rate-limited.

External Learning Resources

YouTube
Educational article sources

Deployment

Vercel

🏗️ Architecture

At a high level, NeuralLearn follows this flow:

User
  │
  ▼
Next.js Application
  │
  ├── Clerk Authentication
  │
  ├── Course Generation
  │       │
  │       ├── Groq
  │       └── Gemini fallback
  │
  ├── Lesson Generation
  │
  ├── Quiz Generation
  │
  ├── Flashcard Generation
  │
  ├── YouTube Resources
  │
  └── Article Resources
          │
          ▼
     Neon PostgreSQL

🚀 Getting Started

Prerequisites

Make sure you have installed:

Node.js 18+
npm
A PostgreSQL-compatible database
Clerk account
Groq API access
Google Gemini API access

Installation

Clone the repository:

git clone https://github.com/XTech-Head/NeauralLearn.git

Enter the project:

cd NeauralLearn

Install dependencies:

npm install

🔐 Environment Variables

Create a .env file in the project root.

Add the environment variables required by your local configuration.

Example:

DATABASE_URL=

NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=
CLERK_SECRET_KEY=

GROQ_API_KEY=
GROQ_MODEL=

GEMINI_API_KEY=
GEMINI_MODEL=

Additional variables may be required depending on the enabled integrations.

Never commit .env, API keys, database credentials, or other secrets to GitHub.

▶️ Development

Start the development server:

npm run dev

Open:

http://localhost:3000

🧪 Production Build

To verify the application builds successfully:

npm run build

Then start the production server:

npm start

📁 Project Structure

NeauralLearn/
│
├── app/
│   ├── ai/
│   │   └── ai.ts
│   │
│   ├── api/
│   │   ├── articles/
│   │   ├── course/
│   │   ├── courses/
│   │   ├── generate-course/
│   │   ├── progress/
│   │   ├── transcribe/
│   │   ├── user/
│   │   └── youtube/
│   │
│   ├── components/
│   ├── course/
│   ├── sign-in/
│   ├── sign-up/
│   ├── globals.css
│   └── page.tsx
│
├── config/
│   └── schema.ts
│
├── lib/
│   └── server-auth.ts
│
├── public/
│   ├── icons/
│   └── screenshots/
│
├── .github/
│   └── dependabot.yml
│
├── manifest.ts
├── next.config.ts
├── package.json
└── README.md

🔄 AI Reliability

AI services can experience temporary rate limits, unavailable models, or provider failures.

NeuralLearn therefore uses a provider abstraction that can:

Attempt the configured Groq model.
Try additional Groq model fallbacks when necessary.
Retry appropriate temporary failures.
Fall back to Gemini when Groq cannot complete the request.
Return an error when no configured provider can fulfill the request.

This helps prevent a temporary model or provider issue from taking down the entire learning workflow.

🔒 Security

NeuralLearn is designed with server-side API access in mind.

Sensitive credentials should remain on the server and must never be exposed to the client.

The project follows several important practices:

API keys stored in environment variables
Database credentials stored in environment variables
Authentication handled through Clerk
Server-side API calls for AI providers
Protected application routes
No secrets committed to the repository
Dependency updates monitored through Dependabot

🗺️ Roadmap

NeuralLearn is actively evolving.

Potential future improvements include:

Improved learning recommendations
More personalized learning paths
Additional AI providers
Better spaced-repetition support
More detailed learning analytics
Expanded PWA capabilities
Custom course editing
Improved accessibility
More external learning-resource integrations

🎯 Why NeuralLearn?

The internet already contains an enormous amount of educational material.

The problem is finding the right material, understanding where to start, and maintaining a structured learning path.

NeuralLearn aims to reduce that friction by turning a simple topic into a guided learning experience.

Enter a topic. Generate a course. Learn. Practice. Track your progress.

👨‍💻 Developer

Built by XTech Devs.

NeuralLearn is part of an ongoing collection of software projects exploring AI-powered productivity, education, and developer tools.

☕ Support

If NeuralLearn has helped you learn something or saved you time, you can support continued development through a one-time coffee donation.

No subscriptions. Just support if you want to.

📄 License

This project is licensed under the MIT License.

See the LICENSE file for more details.

Name		Name	Last commit message	Last commit date
app		app
components/ui		components/ui
config		config
hooks		hooks
lib		lib
public		public
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
components.json		components.json
drizzle.config.ts		drizzle.config.ts
global.d.ts		global.d.ts
manifest.ts		manifest.ts
next.config.ts		next.config.ts
package-lock.json		package-lock.json
package.json		package.json
postcss.config.mjs		postcss.config.mjs
proxy.ts		proxy.ts
tsconfig.json		tsconfig.json

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