PageLM
PageLM is an open-source education platform inspired by NotebookLM that transforms study materials into interactive learning resources such as quizzes, flashcards, notes, and podcasts, leveraging state-of-the-art large language models and text-to-speech systems.
PageLM is notes software teams evaluate for education & research. Use this page to review pricing, integration signals, and the best alternatives before you commit.
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Quick Overview
Best for: Education & Research
What it does
Notes software for decision-makers comparing workflow fit and alternatives.
Best fit
Education & Research
Pricing snapshot
Free
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PageLM
PageLM is a community-driven open-source version of NotebookLM designed to enhance educational experiences by converting study materials into interactive resources. It supports multiple document formats including PDF, DOCX, Markdown, and TXT, enabling students, educators, and researchers to engage with content through quizzes, flashcards, structured notes, and podcasts. The platform integrates advanced large language models (LLMs) and text-to-speech (TTS) technologies to improve learning efficiency and accessibility. It offers a modern interface and supports various AI models and embedding providers, making it a versatile tool for interactive learning.
PageLM is the OSS version of NotebookLM
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Claim this listingKey Features
Contextual Chat
Allows users to ask questions about uploaded documents in formats such as PDF, DOCX, Markdown, and TXT.
SmartNotes
Automatically generates Cornell-style notes from topics or uploaded content to facilitate structured learning.
Flashcards
Extracts non-overlapping flashcards for spaced repetition learning.
Quizzes
Creates interactive quizzes with hints, explanations, and scoring to test knowledge.
AI Podcast
Converts notes and topics into engaging audio content for learning on the go.
Voice Transcribe
Converts lecture recordings and voice notes into organized, searchable study materials instantly.
Homework Planner
Uses AI to plan homework smartly and provides assistance if users get stuck.
ExamLab
Simulates exams, provides feedback, and helps users prepare effectively.
Pricing
PageLM is an open-source project licensed under the CaviraOSS Community License, free to use, share, and modify for personal and educational purposes.
Use Cases
Student Learning Enhancement
Students can transform their study materials into interactive quizzes, flashcards, and podcasts to improve retention and engagement.
Educator Resource Creation
Educators can create structured notes and interactive learning content to support diverse teaching methods.
Research Material Organization
Researchers can organize and query large volumes of documents using contextual chat and smart note generation.
Exam Preparation
Users can simulate exams and receive feedback to better prepare for tests.
Lecture and Voice Note Transcription
Converts audio recordings into searchable and organized study materials for easier review.
Integrations
Google Gemini
Supports Google Gemini AI models for language processing.
OpenAI GPT
Integrates OpenAI GPT models for advanced language understanding.
Anthropic Claude
Supports Anthropic Claude AI models.
xAI Grok
Integration with xAI Grok models.
Ollama (local)
Supports local Ollama AI models.
OpenRouter
Supports OpenRouter for routing AI model requests.
Embedding Providers
Supports OpenAI, Gemini, and Ollama for embedding generation.
Text-to-Speech Engines
Supports Edge TTS, ElevenLabs, and Google TTS for podcast audio generation.
Benefits
Limitations
Frequently Asked Questions
What document formats does PageLM support?
Is PageLM free to use?
Can I contribute to PageLM development?
What AI models does PageLM support?
How do I deploy PageLM?
Getting Started
- 1 Step 1: Ensure prerequisites are installed: Node.js v21.18+, npm or pnpm, ffmpeg (for podcast audio), and optionally Docker.
- 2 Step 2: Clone the repository from GitHub using 'git clone https://github.com/caviraOSS/pagelm.git' and navigate into the directory.
- 3 Step 3: Run the setup script appropriate for your OS (Linux or Windows) or manually install dependencies in backend and frontend folders.
- 4 Step 4: Configure environment variables by copying '.env.example' to '.env' and setting API keys and other settings.
- 5 Step 5: Run backend and frontend servers in separate terminals using 'npm run dev' commands.
- 6 Step 6: Access the platform locally at http://localhost:5173.
Support
Discord
Join the community Discord server for discussions, support, and sharing ideas: https://discord.gg/P7HaRayqTh
GitHub Issues
Report bugs or request features via the GitHub repository issues page.
Documentation
Refer to the README and other documentation files in the GitHub repository for setup and usage instructions.
API
No explicit API documentation mentioned; the platform uses environment-configured LLM providers and TTS engines.
Not available.
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