AI Extensibility Framework

An experimental Open edX plugin for AI-powered educational workflows

The AI Extensibility Framework is a proof-of-concept plugin that explores artificial intelligence integration in Open edX. It provides a modular, extensible architecture for building AI-powered workflows that enhance the learning experience.

• Overview
• Current Status
• Installation
  • Prerequisites
  • Installation
  • Setting Up Development Environment
  • Code Standards
  • Architecture Decisions
• Contributing
• References
• License
• Maintainer

Overview

This plugin demonstrates how AI capabilities can be integrated into Open edX in a modular and extensible way, following the principle of "open for extension, closed for modification." It provides infrastructure for AI workflows while maintaining compliance with educational requirements and Open edX standards.

Key Features (planned for V1):

• Modular workflow-based architecture for AI processing
• Support for multiple LLM providers via LiteLLM (OpenAI, Anthropic, local models)
• Context-aware AI assistance examples integrated into the learning experience
• Observable workflows with event analytics in aspects
• Configuration-driven behavior without code changes

Current Status

Warning

Experimental - This plugin is in active development and should not be used in production environments.

This is an exploratory project developed by edunext as part of FC-111 to investigate AI extensibility patterns for Open edX. The plugin serves as a testing ground for AI integration concepts that may inform future development.

What Works:

• Frontend integration with Learning MFE via plugin slots
• Basic content extraction from course unit
• AI-powered content summarization

Installation

Prerequisites

• Open edX installation (Tutor-based deployment recommended)
• Python 3.11 or higher
• Node.js 18.x or higher (for frontend development)
• API key for supported LLM provider (OpenAI, Anthropic, etc.)

Installation

Install the plugin in your Open edX environment using the provided tutor plugin:

pip install git+https://github.com/openedx/openedx-ai-extensions.git
tutor plugins enable openedx-ai-extensions
tutor images build openedx
tutor images build mfe
tutor local launch

Setting Up Development Environment

TBD when the tutor plugin PR is merged.

Code Standards

• All code, comments, and documentation must be in clear, concise English
• Write descriptive commit messages using conventional commits.
• Follow the CI instructions on code quality.

Architecture Decisions

Significant architectural decisions are documented in ADRs (Architectural Decision Records) located in the docs/decisions/ directory.

Contributing

We welcome contributions! This is an experimental project exploring AI integration patterns for Open edX.

How to Contribute:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/your-feature)
3. Make your changes following the code standards
4. Write or update tests as needed
5. Submit a pull request with a clear description

For questions or discussions, please use the Open edX discussion forum.

References

• Open edX Conference Paris 2025 Presentation
• Open edX Plugin Development
• LiteLLM Documentation
• Architectural Decision Records (ADRs)

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). See the LICENSE file for details.

Maintainer

This repository is covered by the Open edX maintainers program and the current maintainers are listed in the catalog-info.yaml file.

Community Support:

• Open edX Forum: https://discuss.openedx.org
• GitHub Issues

Note: As this is an experimental project, support is provided on a best-effort basis.