PageLM

An open source AI powered education platform that transforms study materials into interactive learning experiences, slightly inspired by NotebookLM

Report Bug • Request Feature • Discord server

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Demo

Demo Site: https://pagelm.spotit.dev

demo.mp4

Note: If the video doesn't load above, you can download the demo video directly

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🚀 Features

PageLM converts study material into interactive resources including quizzes, flashcards, structured notes, and podcasts.
The platform provides a modern interface for students, educators, and researchers to enhance learning efficiency using state-of-the-art LLMs and TTS systems.

Learning Tools

• Contextual Chat – Ask questions about uploaded documents (PDF, DOCX, Markdown, TXT)
• SmartNotes – Generate Cornell-style notes automatically from topics or uploaded content
• Flashcards – Extract non-overlapping flashcards for spaced repetition
• Quizzes – Create interactive quizzes with hints, explanations, and scoring
• AI Podcast – Convert notes and topics into engaging audio content for learning on the go
• Voice Transcribe - Convert lecture recordings and voice notes into organized, searchable study materials instantly.
• Homework Planner - Plans your Homework Smartly using AI, Assists if your stuck.
• ExamLab - Simulate any exam, get feedback, and be prepared for the exam
• Debate - Debate with AI to improve your Debate skills.
• Study Companion - A personalised AI Companion that assists you.

Supported AI Models

• Google Gemini • OpenAI GPT • Anthropic Claude • xAI Grok • Ollama (local) • OpenRouter

Embedding Providers

• OpenAI • Gemini • Ollama

Technical Highlights

• WebSocket streaming for real-time chat, notes, and podcast generation
• JSON or vector database support for embeddings and retrieval
• File-based persistent storage for generated content
• Markdown-based outputs for structured answers and notes
• Configurable multi-provider setup for LLMs and TTS engines

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🛠️ Technology Stack

Component	Technology
Backend	Node.js, TypeScript, LangChain, Langraph
Frontend	Vite, React, TailwindCSS
Database	JSON (default), optional vector DB
AI/ML	Multiple LLM providers, embeddings
Audio	Edge TTS, ElevenLabs, Google TTS
Deployment	Docker, Docker Compose
Docs	pdf-lib, mammoth, pdf-parse

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⚡ Getting Started

Prerequisites

• Node.js v21.18+
• npm or pnpm
• ffmpeg (required for podcast audio)
• Docker (optional)

Local Development

# Clone the repository
git clone https://github.com/caviraOSS/pagelm.git
cd pagelm

# Linux:
  chmod 777 ./setup.sh
  ./setup.sh

# Windows:
  Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  ./setup.ps1

# Manual (Both Linux/Windows):
  # Install dependencies
  cd backend
  npm install
  cd ../frontend
  npm install

  # Setup environment
  cd ..
  npm i -g nodemon
  cp .env.example .env
  # Make sure to configure API keys and settings in .env

  # Run these two commands in separate terminals but inside the project directory.
  # Run backend
  cd backend
  npm run dev

  # Run frontend
  cd frontend
  npm run dev

👉 Access at: http://localhost:5173

Docker Deployment

# Development
docker compose up --build

# Production
docker compose -f docker-compose.yml -f docker-compose.prod.yml up -d --build

• Frontend: http://localhost:5173 (dev) / http://localhost:8080 (prod)
• Backend: http://localhost:5000

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⚙️ Configuration

All configuration is handled via environment variables:

• LLM Provider – Choose your model backend
• TTS Engine – Select speech service for podcasts
• Database Backend – JSON or vector DB
• File Upload Limits – Customize size/format limits

See .env.example for all options.

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👥 Community

Join our Discord community to connect, share ideas, and take part in exciting discussions!

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🤝 Contributing

We welcome all contributions.

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

Guidelines:

• Follow code style and conventions
• Add tests where needed
• Update docs for new features
• Ensure all tests pass before PR

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💡 Areas to Contribute

• AI model integrations
• Mobile app support
• Performance improvements
• Accessibility features
• Docs & tutorials

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💖 Support the Project

If you find PageLM useful, please consider supporting:

Ethereum (ERC-20):

0x5a12e3f48b6d761a120bc3cd0977e208c362a74e

Your support helps fund ongoing development and hosting.

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📜 License

Licensed under the CaviraOSS Community License.
Free to use, share, and modify for personal and educational purposes.
Commercial use or resale requires prior written permission from CaviraOSS.

See LICENSE for full terms.

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Built with ❤️ by CaviraOSS and contributors

⭐ Star us on GitHub if this project helps you!