An npm‑published Node library that adds LLM‑driven assistants to Kubernetes/DevOps workflows. It provides a CLI and a managed platform (MCP) for natural‑language cluster queries, deployment recommendations, automated remediation, policy‑driven prompt libraries, and semantic doc search, all packaged for easy installation on a Kubernetes cluster.

A Julia package that enables programming and executing computations on AMD GPUs using the ROCm platform.

A set of utilities for deploying and managing Dask workers on CUDA-enabled systems to facilitate GPU-accelerated computing.

An AI-native console for ClickHouse that enables natural language query generation, intelligent visualization, and cluster diagnostics.

A JAX-based library for second-order optimization of neural networks using the K-FAC optimizer and scalable curvature approximations.

A Python implementation of Local Outlier Probabilities (LoOP) that provides interpretable outlier scores as probabilities between 0 and 1.

A local-first long-term memory layer for AI agents that stores durable facts and manages context through isolated project boundaries called wings.

An autonomous security agent that performs automated penetration testing, LLM red-teaming, and provides a cryptographic identity standard for AI agents via the Agent Trust Protocol.

Oryx is a probabilistic programming and deep learning library built on JAX that integrates with JAX's function transformations.

An evaluation framework that measures how coding agents evolve executable policies through iterative experimentation and feedback in interactive environments.

A ComfyUI custom node for precise resolution and aspect ratio control, featuring a visual 2D canvas and model-specific optimizations for AI image generation.

A Python package for ontology engineering that integrates deep learning models with formal knowledge representation to support tasks like ontology matching and subsumption prediction.

A set of performance optimizations for Qwen3.5-122B-A10B on NVIDIA DGX Spark, increasing inference speed from 28.3 to 52 tokens per second using hybrid quantization and speculative decoding.

A library that extends the safetensors format to provide a unified storage and management system for various LLM compression and quantization schemes.

A set of Python tools for experimenting with and studying recommender systems, providing support for training, running, and evaluating recommendation algorithms.

A multi-agent security console for macOS that runs isolated AI agent instances in separate macOS user accounts to ensure data privacy and system security.

A unified interface for various automatic differentiation backends in Julia, providing a consistent syntax for computing gradients, Jacobians, and Hessians.

An open-source Spark library that integrates Amazon SageMaker into Spark ML pipelines for scalable model training and inference on DataFrames.

An MCP server that enables AI models to interact with Elasticsearch and OpenSearch, providing tools for searching documents, managing indices, and monitoring cluster health.

A Dart FFI binding for llama.cpp that enables running LLMs, vision, and audio models locally within Flutter apps on iOS and Android.

A high-frequency trading framework in Java and Python that enables L2 tick-data backtesting and live market execution using a unified codebase.

A code-first educational collection of handwritten Python implementations for various tabular anomaly detection methods, including PCA reconstruction, RobustPCC, and PU learning.

An open-source, low-code platform providing seamless access to pre-trained AI/ML models for infectious and neglected disease research and drug discovery.

A comprehensive suite of APIs and tools to integrate safety, privacy, explainability, and fairness into Generative AI and traditional ML models to ensure trustworthiness.

A collection of example projects and templates demonstrating how to implement AI features like LLMs, computer vision, and simulation in Unity using the Sentis package.

A high-performance inference engine for GPUs and AI accelerators that enables efficient model deployment and academic validation.

TFTS is a TensorFlow-based library that provides a unified interface for implementing state-of-the-art deep learning models for time series prediction, classification, and anomaly detection.

A Triton-based subset of PyTorch's nn module that provides a readable and hackable collection of neural network layers for developing custom deep learning operations.

A lightweight, self-hosted semantic cache for GenAI workloads that reduces LLM costs and latency by serving cached responses for similar prompts.

continuous-eval is a Python library for modular, data‑driven evaluation of LLM‑powered pipelines. It provides a catalog of retrieval, generation, code, and agent metrics, lets you attach those metrics to individual pipeline modules, runs them on a dataset, and can enforce regression tests. Custom LLM‑as‑a‑judge metrics are also supported.

A contribution package for Stable-Baselines3 containing experimental reinforcement learning algorithms and niche tools for researchers and developers.

A high-performance C++-based batched environment pool for reinforcement learning that significantly accelerates experience collection across various simulators.

A modular TensorFlow framework designed for building and scaling neural networks, particularly sequence-to-sequence models and giant language models.

A unified, high-performance training engine for multimodal models that integrates distributed training, kernel fusion, and advanced optimizers to enable scalable pretraining and fine-tuning.

A Python frontend and library for ComfyUI that allows users to define and run image generation workflows as Python scripts instead of visual node graphs.

A CLI tool for packaging and deploying AI/ML models to production, automating containerization, GPU configuration, and dependency management.

An AI-driven navigation hub that uses autonomous agents to discover, evaluate, and organize high-quality open-source AI projects from GitHub into an auto-updating directory.

A time series forecasting library that provides a uniform interface for ML and deep learning models, simplifying model selection, validation, and pipeline creation.

An MCP server that connects AI assistants to the Gemini/Antigravity CLI, enabling large-scale codebase analysis and sandboxed code execution.

An MCP server that enables structured, spec-driven development for AI agents by enforcing a sequential workflow of requirements, design, and tasks with a real-time monitoring dashboard.

A graphical toolbox for training, evaluating, and deploying state-of-the-art AI models with support for various hardware accelerators.

A PyTorch library for Relational Table Learning (RTL) that standardizes and combines GNNs, LLMs, and TNNs to analyze data across linked tables.

An open-source platform that provides a unified API and toolkit for using state-of-the-art generative AI models to accelerate hypothesis generation in scientific discovery.

A framework for writing differentiable logic programs in Python, enabling the creation of expressive relational learning models that extend beyond standard Graph Neural Networks.

A high-quality C++ header-only library providing a wide range of non-linear numerical optimizers, including gradient-based and gradient-free methods.

A version control system and Claude Agent SDK plugin that allows developers to commit, diff, and merge agent configurations and traces to prevent performance regressions.

An agentic system optimization framework that uses coding agents to automate parameter tuning by reasoning over the semantic meaning of parameters and trial history.

NVIDIA Merlin is an open-source library suite that accelerates the end-to-end creation of large-scale recommender systems using GPU acceleration for feature engineering, training, and inference.