Home/Model Training/MOE

MOE

YelpArchive/MOE

A global, black box optimization engine for real world metric optimization

GitHub

GraphCanon updated Oct 2, 2026 · GitHub synced Oct 2, 2026

36views this month

1.3k stars138 forksLast push Mar 24, 2023 C++ Other

Decision brief

MOE optimizes real-world metrics via automated black-box processes. It is written in C++.

Good fit when

When you require an optimization engine that operates as a global, isolated system through Docker containers.
For tasks demanding high performance and precision due to its foundation in C++.

Avoid when

If your team lacks the knowledge or experience to configure and run Docker environments.
Not suitable for projects where real-time interaction with optimization processes is needed, as MOE focuses on batch processing scenarios.

Observed Jul 17, 2026 · Source: enrich:decision_facts

MOE alternatives Trust report

Verify the decision

Maintenance and security

Full trust report

Maintenance: Archived (1287d since push); As of Oct 2, 2026
Provenance: Not a fork · Organization account; As of Oct 2, 2026
Security (OSV): 15 low (15 low); As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

git clone https://github.com/YelpArchive/MOE

Similar tools

Same-category neighbours. No typed graph edges are catalogued for this tool yet.

deepeval

LLM Evaluation Framework.

18k★

optuna

A hyperparameter optimization framework

15k★

nni

An open source AutoML toolkit for automating machine learning lifecycle

14k★

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

The repository contains a tool that optimizes real-world metrics through automated black-box optimization processes.

Capability facts

Deploy: Self-host
Source: dockerfile:Dockerfile · Oct 2, 2026
Docker: Dockerfile present
Source: dockerfile:Dockerfile · Oct 2, 2026
Languages: c++
Source: github.language · Oct 2, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Oct 2, 2026)

[9]: http://yelp.github.io/MOE/moe.optimal_learning.python.python_version.html

Source link

README

Install in docker: This is the recommended way to run the MOE REST server. All dependencies and building is done automatically and in an isolated container. [Docker (http://docs.docker.io/)][6] is a container based virtualization framework. Unlike traditional virtualization Docke...

For agents

This page has a .md twin and JSON over the API.

/tools/yelparchive-moe.md GET /api/graphcanon/tools/yelparchive-moe GET /api/graphcanon/graph?tool=yelparchive-moe

MOE