An AI-driven CLI that tests Android and iOS apps using natural language specifications, utilizing multimodal models to interact with the UI and generate test reports.

A warehouse-native event collection layer that unifies tracking across multiple destinations like GA4 and BigQuery using a config-as-code approach.

An MCP server that integrates DeepSeek's V4.1 Flash API into MCP-compatible clients, enabling text and visual chat and file management.

A fast, scalable machine learning system focused on online learning and reinforcement learning that uses the hashing trick to maintain a bounded memory footprint.

A comprehensive machine learning toolkit for Rust, similar to scikit-learn, providing classical ML algorithms and preprocessing tools.

A scalable evolutionary computation library built on PyTorch that solves non-differentiable optimization problems using GPU acceleration and Ray distribution.

A Go implementation of the Model Context Protocol (MCP) SDK that enables seamless communication between external systems and AI applications.

A generic bash tool for AI agents that enables them to execute shell commands and manage files within a sandbox environment.

A Python LSP client library that provides a unified API to query static analysis results from multiple language servers to support AI-driven code generation and agents.

A pure Python library for simulating various poker variants, evaluating hands, and conducting statistical analysis, designed for AI development and tool creation.

A Go-based LLM load-balancing gateway that provides a unified REST API, weighted scheduling, and detailed observability for multiple AI providers.

A high-performance serverless GPU task orchestration system that manages AI workloads across multiple compute providers with smart autoscaling.

A C++ framework for high-capacity, low-latency trading that provides specialized tools for tracking option combos, calculating real-time Greeks, and executing trades across multiple brokers.

A collection of high-performance, custom-written GPU kernels for H100 and GB300 that optimize matrix multiplication and sum reduction operations.

OpenPAI is a full-stack AI platform that enables organizations to share computing resources like GPUs and FPGAs and manage AI assets to simplify the training pipeline.

A distributed SQL database that combines the scalability of NoSQL with the power of standard SQL for real-time analysis of massive datasets.

A .NET library that enables developers to run C# code in parallel on the GPU by dynamically generating HLSL shaders via DX12 and D2D1.

A C++ library providing unified wrappers for SIMD intrinsics to accelerate numerical computations across different CPU architectures.

A Python library for wavelet transforms that enables time-frequency analysis of signals and data across multiple dimensions.

A collection of opinionated configurations, sandboxing rules, and hooks for Claude Code to enable secure, high-throughput autonomous AI coding.

An open-source adversary emulation framework for red-teaming AI agents and MCP servers, providing automated vulnerability scanning based on OWASP standards.

An open-source framework for globally distributed training of large models that reduces communication overhead using distributed weight averaging.

A framework for configuring and running large-scale machine learning experiments on top of Jax, optimized for Cloud TPU and GPU infrastructure.

A PyTorch-based Python library designed for deep learning research in hydrology, allowing users to train neural networks via configuration files.

A library providing a programming model for writing performance-critical machine learning kernels that are portable across different GPU and CPU architectures.

A plugin ecosystem and marketplace for Dify, enabling developers to extend AI applications with custom models, tools, and agent reasoning strategies.

A machine learning runtime written in Rust that enables running ONNX models trained in PyTorch and other Python frameworks in Rust and WebAssembly environments.

A general-purpose framework for reinforcement fine-tuning of LLMs that decouples exploration, training, and data buffering to support diverse RL algorithms and agentic workflows.

A high-performance, time-indexed object storage system for robotics and industrial IoT that allows querying binary data by time range and labels.

A fast, portable C++ library for deep reinforcement learning and continuous control, optimized for everything from microcontrollers to GPUs.

A modern multimodal recommendation toolbox that provides a unified framework and source code for a wide variety of research-based recommendation models.

A PyTorch implementation of 1-bit Transformers that replaces standard linear layers with binarized projections to drastically reduce LLM memory and compute requirements.

A machine learning library for unsupervised time series anomaly detection that provides verified ML pipelines to identify rare patterns in signals.

A Python toolkit that provides a unified, OpenAI-compatible interface for 40+ free and paid AI models, including text, image, and voice generation.

codedb is a Zig‑based code‑intelligence engine that builds a local index of a repository (symbols, callers, dependencies, trigram search, etc.) and serves that information to AI coding assistants via the Model Context Protocol (JSON‑RPC over stdio). It provides MCP tools such as `codedb_context`, `codedb_explain`, and `codedb_callpath` for fast, sub‑millisecond queries, while remaining a read‑only “compass” for agents. Installable as native binaries or via an npm wrapper, it works on macOS, Linux and Windows, supports hybrid local/remote semantic retrieval, and can run as an HTTP server for debugging.

An Emacs integration for Aider, bringing AI pair programming and automated code editing to the Emacs editor.

A security scanning tool for Model Context Protocol (MCP) servers and tools that uses YARA, LLMs, and Cisco AI Defense to detect malicious behavior and vulnerabilities.

A Python SDK for Oxylabs AI Studio, providing AI-powered web scraping, crawling, and browsing agents to extract structured data using natural language prompts.

A library of CUDA-accelerated fundamental algorithms and primitives for machine learning and data mining, designed as building blocks for high-performance AI applications.

A modern C++ library for high-performance GPU inference of CNN models using NVIDIA TensorRT, featuring a safe engine cache and zero-copy Python bindings.

A Python package for computations, statistics, and machine learning on manifolds, enabling the analysis of non-Euclidean data like rotations and shapes.

A package for generating synthetic tabular and time-series data using generative models like GANs and Gaussian Mixtures to ensure privacy and augment datasets.

A PyTorch library for training machine learning models with differential privacy, allowing users to protect sensitive training data while tracking privacy loss.

A Python toolbox for machine learning on partially-observed time series, providing unified APIs for imputation, forecasting, and anomaly detection on data with missing values.

An extensible open-source library for Python and R that provides metrics and algorithms to detect and mitigate algorithmic bias in machine learning models.

A fast, flexible C++ machine learning library providing a core tensor interface and neural network tools for high-performance AI research across speech, vision, and text.

A high-performance serving system for machine learning models designed to manage model lifetimes and provide versioned inference via gRPC and HTTP in production environments.

A collection of official Amazon SageMaker example notebooks and the SageMaker-Core SDK for building, training, deploying, and operationalize machine learning models on AWS.