Open Source Feature Flagging and A/B Testing Platform

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

This repo is for experimentation and exploring new ideas that may or may not make it into the main corefx repo.

A feature flags service written in .NET

Shadow is a discrete-event network simulator that directly executes real application code, enabling you to simulate distributed systems with thousands of network-connected processes in realistic and scalable private network experiments using your laptop, desktop, or server running Linux.

Train to 94% on CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110 seconds (or less!)

GO Feature Flag is a simple, complete and lightweight self-hosted feature flag solution 100% Open Source. 🎛️

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Feature flags, experiments, and remote config management with GitOps

Open-source Python library for statistical analysis of randomised control trials (A/B tests)

Deep-Learning Model Exploration and Development for NLP

PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more

JustTweak is a feature flagging framework for iOS apps.

🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.

LLMOps with Prompt Flow is a "LLMOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.

Official Omnitool repository

🧪 Source-controlled split testing stack for building, launching and analysing A/B tests.

A hardware kit to experiment with inflatable and vacuum based soft robotics.

moai is a PyTorch-based AI Model Development Kit (MDK) created to improve data-driven model workflows, design and reproducibility.

Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.