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Atlas: Competency Based Learning Management System

Welcome to the AtlasML documentation!

What is AtlasML?

AtlasML is a FastAPI-based microservice that provides AI-powered competency management features for the Artemis learning platform. It uses machine learning and vector embeddings to suggest competencies, cluster exercises, and analyze learning relationships—all backed by a centralized Weaviate vector database shared across multiple microservices.

Main Features

  • Competency Suggestions - AI-powered competency recommendations for exercises based on semantic similarity
  • Exercise Clustering - Automatic grouping of exercises by semantic similarity for course organization
  • Vector Embeddings - Azure OpenAI integration for generating multi-modal embeddings
  • Centralized Vector Database - Shared Weaviate instance for cross-microservice semantic search
  • REST API - FastAPI-based endpoints for integration with Artemis
  • Type Safety - Pydantic models for robust data validation and API contracts

Who Should Read This Documentation?

🛠️ Administrators (DevOps/Deployment)

If you need to deploy, configure, or maintain AtlasML in production, start here:

Quick Start Checklist:

Key Sections:

👨‍💻 Contributors (Developers)

If you want to contribute code, fix bugs, or understand AtlasML's internals, start here:

Quick Start Checklist:

Key Sections: