The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.

ADEPT: Agentic Discovery and Exploration Platform for Tools — A three-tier secure framework for multi-agent scientific workflows with 28+ MCP tools, 10 client interfaces, and declarative multi-LLM …

Search infrastructure for AI

Complete AI Governance Platform from Obot AI

Real-time behaviour synthesis with MuJoCo, using Predictive Control

Official Python SDK for the Agent2Agent (A2A) Protocol

The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

Deep Reinforcement Learning Hands-On, 3E_Published by Packt

A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

ROS-LLM is a framework designed for embodied intelligence applications in ROS. It allows natural language interactions and leverages Large Language Models (LLMs) for decision-making and robot contr…

A programming framework for agentic AI

Web UI for AutoGen (A Framework Multi-Agent LLM Applications)

A deep learning package for many-body potential energy representation and molecular dynamics

Doing simple retrieval from LLM models at various context lengths to measure accuracy

Code for the ProteinMPNN paper

AutoDock Vina

AlphaFold Meets Flow Matching for Generating Protein Ensembles

TorchCFM: a Conditional Flow Matching library

Official repository of the xLSTM.

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of …

Copilot for Jupyter notebooks.

The official repository for the AiiDA code

dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

An Introduction to Statistical Learning with Applications in PYTHON

Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS