ONCard

Fully offline AI-powered studying, flashcards, MCQs, and intelligent learning tools.

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Important Notice!

Development has now shifted toward ONCard Pro.
The term Pro does not indicate a paid version; instead, it represents a more refined and modern evolution of the current ONCard project.

ONCard Pro will primarily focus on cloud-based functionality and services. User data, interactions, and security preferences are carefully handled and managed through ONCard Cloud to improve reliability, synchronization, and overall user experience.

ONCard will continue using local AI for in-app processing wherever possible and will ship with its own built-in AI models for a faster, more integrated experience. Cloud services will mainly be used for data synchronization and powering the ONCard Marketplace. This approach allows reliable account migration, better cross-device experiences, and helps build a stronger community-driven ecosystem.

Upcoming Feature:
An experimental BETA release of the ONCard Marketplace will be introduced under this repository as part of the ONCard Cloud ecosystem.

Please Note:
By using ONCard Marketplace, you acknowledge and agree that marketplace-related data may be utilized by ONCard Cloud to help improve ONCard’s in-house AI models for enhanced speed, reliability, and platform performance till ONCard-Pro. ㅤ ㅤ

Table of Contents

• About ONCard
• Features
• Installation
• How to Use ONCard
• Recommended Requirements
• Citation

About ONCard

ONCard (Open-source Neural-Accelerated Cards) is a fully offline study app with a virtual teacher and an adaptive learning algorithm that improves context and teaching quality over time.

Features

These are the core features that make ONCard powerful for daily studying:

• Fully Offline AI Workflow ONCard runs locally with Ollama, so your study sessions continue without cloud dependency.

• One-Input Card Generation Enter a single prompt from your notes or slides and ONCard auto-generates:

  • title
  • hints
  • answer
  • difficulty
  • suggested subject location/path

• Virtual Teacher with Real-Time Grading Submit your answer and get instant evaluation and study feedback.

• Follow-Up Teaching Chat Ask follow-up questions directly after grading to get concept explanations while context is still fresh.

• Subject-Path Organization Cards are structured by topic paths (for example, computer science → languages → Python) so large subjects stay organized.

• Adaptive Learning Behavior ONCard improves how it helps you as you keep studying, creating a more personalized learning flow over time.

• Fast Study Loop Create, review, answer, grade, and clarify in one app without switching tools.

• Focused UI for Study Sessions The Create and Cards workflow is designed to keep attention on learning instead of setup.

Installation

Note: Currently the app is not code signed.

If Windows Defender shows a warning during installation, you may need to allow the app manually. ("More info" -> "Run anyways")

Windows

1. Download and install Ollama.
2. Go to this repository’s Releases page.
3. Download the latest .exe from the release assets.

Linux

Use the Linux-specific version here: ONCard-Linux.

How to Use ONCard

1. Open ONCard and go to the Create tab.
2. Enter a question from your notes or slides.
3. ONCard generates the rest automatically: title, hints, answer, difficulty, and suggested subject path.
4. Go to the Cards tab and press Start (or click any card) to begin studying.
5. Submit your answer or reveal a hint if needed.
6. Press Grade to receive real-time feedback from the virtual teacher.
7. Ask follow-up questions in chat for further explanation.

Recommended Requirements

For a smooth experience:

• Intel i5-8100
• 16 GB DDR4 RAM
• NVIDIA RTX 2060 Super

Citation

If you use this project or parts of its code, please cite:

@software{mightyxdash_oncard_2026,
  author       = {{MightyXdash}},
  title        = {{ONCard}: Open-source Neural-Accelerated Cards},
  year         = {2026},
  version      = {1.5.9},
  date         = {2026-05-13},
  publisher    = {GitHub},
  url          = {https://github.com/MightyXdash/ONCard},
  license      = {Apache-2.0},
  note         = {Fully offline AI-powered study platform featuring local neural workflows, adaptive learning systems, semantic search, virtual teacher feedback, flashcard and MCQ generation, and Ollama-powered AI integration.}
}

Thanks for using ONCard 🤗 Love to the open-source community 🥰