moa

Optimizing inference proxy for LLMs

A machine learning package for streaming data in Python. The other ancestor of River.

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

Running Mixture of Agents on CPU: LFM2.5 Brain (1.2B) + Falcon-R Reasoner (600M) + Tool Caller (90M). CPU-only, 16GB RAM. Lightweight AI Legion.

Mixture-of-Ollamas

My Java codes for the MOA framework. It includes the implementations of FHDDM, FHDDMS, and MDDMs.

Elucidate and visualise a compound's mechanism of action by combining structure-based target prediction with gene expression-based causal reasoning, plus pathway enrichment to put results into biological context. GUI-based (minimal coding experience required).

An external pipeline filter for Open WebUI that refactors aggregate requests with collective wisdom to output structured expert analysis reports.

UMM-Discovery is a fully unsupervised deep learning method to cluster cellular images with similar phenotypes together, solely based on the intensity values.

iGNGSVM, OI-SVM, GNG and ENN developed in MOA/WEKA.

This Streamlit application showcases the Mixture of Agents (MOA) architecture proposed by Together AI, powered by Groq LLMs. It allows users to interact with a configurable multi-agent system for enhanced AI-driven conversations.

A simplified agentic workflow process based on the Mixture of Agents (MoA) system for Large Language Models (LLMs)

A streaming Digital Twin of a steel hot rolling mill demonstrating Online Machine Learning (OML) with Apache Kafka, Apache Flink and MOA to handle real-time concept drift.

Official repo for DK904 - IOT Stream Data Mining

Adaptive Decision Forest(ADF) is an incremental machine learning framework called to produce a decision forest to classify new records. ADF is capable to classify new records even if they are associated with previously unseen classes. ADF also is capable of identifying and handling concept drift; it, however, does not forget previously gained kn…

Repository for the StreamingRandomPatches algorithm implemented in MOA 2019.04

MODIS Mosaic of Antarctica

Cloudflare Workers AI 上的 Mixture-of-Agents 服务——多模型组合逼近前沿模型能力

Mixture-of-Agents (MoA) plugin for OpenCode. It fans out a single prompt to multiple models (subagents) in parallel. The primary agent then evaluates and synthesizes the outputs into a unified, high-quality response. Child worker sessions persist and are navigable via the TUI.