helixml / helix

Learn using Shoulder.dev

Shoulder.dev transforms codebases into tailored learning experiences. Below are organized categories of the codebase to help you start with your initial focus.

Introduction to HelixML

Significance and basic information about HelixML, a private GenAI platform that allows users to deploy open AI models in their own data center or VPC, retaining complete data security and control.

Installation and Setup

Step-by-step guide on how to install and set up HelixML, including cloning the repository, creating an .env file, and starting the services using Docker.

Docker and Containerization

Understanding how HelixML uses Docker for containerization, including creating and managing containers, and attaching GPU runners.

Environment Variables and Configuration

Understanding the role of environment variables in HelixML, including creating and editing the .env file, and updating Keycloak realm settings.

API and Command Reference

Detailed guide on the available APIs and commands in HelixML, including the helix command and its options.

Authentication and Authorization

Security protocols used in HelixML, including authentication and authorization mechanisms, and how they are implemented using Keycloak.

Database Schema and Management

Detailed schema layout of the HelixML database, including the different components and how they interact with each other.

Testing Strategies and Methodologies

Overview of the testing frameworks and methodologies used in HelixML, including unit testing, integration testing, and end-to-end testing.

CI/CD and Deployment

Continuous integration and deployment processes used in HelixML, including automated testing, building, and deployment of the application.

Development Environments and Stages

Management of various development stages in HelixML, including local development, testing, and production environments.

Monitoring and Logging

Setup and maintenance of monitoring and logging mechanisms in HelixML, including logging levels, log formats, and log storage.

Performance Optimization

Techniques used in HelixML to enhance performance, including caching, parallel processing, and optimization of database queries.

Security and Data Validation

Security strategies used in HelixML to protect user data, including data validation, input sanitization, and encryption.

UI Design and Frontend Development

Principles of usability and accessibility used in the HelixML frontend, including component design, layout, and styling.