EduTelligence is a comprehensive suite of AI-powered microservices designed to enhance Learning Management Systems (LMS) with intelligent features for education. The suite seamlessly integrates with Artemis to provide automated assessment, exercise creation, competency modeling, and intelligent tutoring capabilities.

EduTelligence maintains compatibility with different versions of Artemis. The following table shows the compatibility matrix:

Note: Always ensure you're using compatible versions for optimal integration and functionality.

Pyris - An intermediary system that connects Artemis with various Large Language Models (LLMs) to power Iris, a virtual AI tutor.

Key Features:

• Exercise Support: Provides intelligent feedback on programming exercises
• Course Content Support: Uses RAG (Retrieval-Augmented Generation) for detailed course content explanations
• Competency Generation: Automates the creation of course competencies

Technology Stack: Python 3.12, Poetry, FastAPI, Weaviate (Vector DB)

AI-driven programming exercise creation assistance that illuminates the process of creating engaging, effective programming exercises.

Key Features:

• Problem Statement Refinement: AI-powered improvement of exercise descriptions
• Code Stub Generation: Automatic generation of starter code templates
• Context-Aware Suggestions: Intelligent recommendations for exercise improvement
• CI Integration: Seamless integration with build agents for validation

Technology Stack: Python 3.13, Poetry, gRPC, Docker

A sophisticated system designed to provide (semi-)automated assessments for various types of academic exercises.

Key Features:

• Multi-Exercise Support: Text exercises, programming exercises, and planned UML/math support
• LMS Integration: Efficient evaluation for large courses
• Advanced Assessment: AI-powered grading and feedback generation

Technology Stack: Python, Docker Compose, PostgreSQL

Documentation: ls1intum.github.io/Athena/

A microservice that incorporates competency models into Learning Management Systems using machine learning and generative AI.

Key Features:

• AI-Powered Competency Models: Automatic generation of sophisticated competency frameworks
• Relationship Mapping: Automated relationships between competencies
• Learning Activity Recommendations: AI-driven suggestions for linking competencies to activities
• Seamless LMS Integration: Works with Artemis and adaptable to other LMSs

Technology Stack: Python, Machine Learning, GenAI/LLMs

A comprehensive LLM Engineering Platform that provides centralized management and monitoring for AI services.

Key Features:

• Usage Logging: Comprehensive tracking of LLM usage
• Billing Management: Cost tracking and billing for AI services
• Central Resource Management: Unified management of AI resources
• Policy-Based Model Selection: Intelligent model routing based on policies
• Scheduling & Monitoring: Advanced scheduling and real-time monitoring

Technology Stack: Python 3.13, Poetry, FastAPI, Docker

Documentation and features coming soon

Technology Stack: Python, Poetry

• Python 3.12+ (3.13 recommended for newer services)
• Poetry for dependency management
• Docker & Docker Compose for containerization
• Git for version control

1. Clone the repository:

   git clone https://github.com/ls1intum/edutelligence.git
   cd edutelligence

2. Choose your service(s): Navigate to the specific service directory you want to set up and follow its individual README instructions.

Each service has its own development setup instructions in its respective README file. Generally, the process involves:

1. Installing Poetry dependencies
2. Setting up configuration files
3. Running the service locally or via Docker

We welcome contributions to improve EduTelligence! Please follow these guidelines:

1. Fork the repository and create a feature branch
2. Follow the coding standards defined in each service's documentation
3. Write tests for new functionality
4. Update documentation as needed
5. Submit a pull request with a clear description of changes

• All services use pre-commit hooks for code quality
• Linting with flake8/pylint
• Formatting with black
• Type checking where applicable

This project is licensed under the MIT License - see the LICENSE file for details.

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: Individual service READMEs and documentation