A Python wrapper for ByteDance's Seedance AI video generator, enabling high-fidelity text-to-video and image-to-video generation with a focus on realistic human faces and character consistency.

An AI-powered penetration testing automation framework that orchestrates security tools and multi-agent AI to perform adaptive security assessments and evidence-backed reporting.

An end-to-end AI platform that simplifies the orchestration of unstructured data, AI pipelines, and model deployment to build RAG and AI-first applications.

A minimalist framework for training video world models based on diffusion-forcing, used for future video prediction, 3D reconstruction, and robotic planning.

An open-source machine learning platform that unifies training, fine-tuning, inference, and evaluation into a single interface for individuals and research labs.

A private, local-first AI companion and art generation platform that combines a customizable chat partner with a layered creative canvas.

A one-click portable installer for AI-Toolkit by Ostris that simplifies the setup of image and video diffusion model training on Windows NVIDIA GPUs.

A high-performance, scalable LLM library written in JAX and Python for pre-training and post-training large models on Google Cloud TPUs and GPUs.

A media analytics framework based on GStreamer and OpenVINO that enables hardware-accelerated video and audio intelligence pipelines on Intel CPU, GPU, and NPU.

A native Swift inference server for Apple Silicon that serves MLX models via an OpenAI-compatible API, featuring SSD expert streaming and KV cache compression.

A scikit-learn compatible Python library for time series machine learning, providing state-of-the-art algorithms for classification, forecasting, and clustering.

A columnar file format by Meta designed for large, wide datasets, optimizing storage and access for machine learning training tables and feature engineering.

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.

An open-source library providing a comprehensive set of algorithms and metrics to improve the interpretability and explainability of machine learning models and datasets across various data modalities.

PyKEEN is a Python package for training and evaluating knowledge graph embedding models, providing a comprehensive library of built-in datasets and models.

A Python library for audio data augmentation that provides a wide variety of transforms to make audio deep learning models more robust for real-world use.

DataChain is a Python library that turns files in S3/GCS/Azure (or local) into versioned, typed datasets stored in a lightweight SQLite DB. It provides fast, sub‑second filtering, joins, aggregations and vector similarity over millions of records without moving the raw files. Pipelines are written as ordinary Python functions; the engine handles parallel execution, checkpointing and incremental updates. Optional features include an auto‑generated markdown Knowledge Base for humans/LLMs and a skill that makes the data layer visible to Claude, Cursor, Codex, Copilot or Pi. A hosted “Studio” service adds shared dataset registry, distributed compute and UI for large media. Install with `pip install datachain` and (optionally) `datachain skill install --target claude`.

A production-grade TypeScript SDK that provides a unified, local interface for calling over 300 LLMs across multiple providers.

Agently is a Python framework for building reliable AI services. It provides structured request/response contracts, instant streaming of partial results, observable actions (tool calls), versioned skills, and a signal‑driven workflow engine (TriggerFlow). The library abstracts model providers, supports model pools, and includes built‑in actions for Python, shell, web browsing, SQLite, etc. Designed for production‑grade assistants, internal copilots, and AI‑backed APIs that need debuggability, restart‑safe workflows, and strict output validation.

DemoGPT is an open-source framework that automatically generates LangChain code and Streamlit apps from user instructions and provides a library of tools for building AI agents with RAG capabilities.

A Python framework for producing structured outputs and building agentic AI workflows using tasks, specialized agents, and type-safe results.

A local-first Agent OS that lets you run official AI agent CLIs on your own machine and control them remotely via a browser or messaging apps.

GoalBuddy is an npm‑based CLI that creates a file‑backed “board” inside your repo to orchestrate long‑running coding tasks with LLM agents like Codex and Claude Code. It lets you define a goal, break it into safe, verifiable slices, dispatch those slices to a chosen harness, capture a YAML receipt, and verify the work against an oracle (tests, demos, etc.). Boards persist across tools, enabling seamless hand‑off between agents, audit trails, and parallel sub‑goals, all with a tiny runtime footprint.

A pure Python library for estimating the orientation of mobile systems using various attitude and heading reference system (AHRS) algorithms.

A Python library for machine learning on graphs that uses sparse matrices for memory-efficient network analysis.

A collection of Unity samples for Meta Quest 3/3S that enables mixed reality experiences to detect objects, track QR codes, and use multimodal AI to understand the surroundings.

OASIS is a Python CLI tool that uses locally hosted LLMs (via Ollama or any OpenAI‑compatible server) to scan source code for security vulnerabilities. It runs a fast scan model, then deep‑analysis models, validates findings deterministically, caches results, and outputs canonical JSON plus HTML/PDF/Markdown reports. A password‑protected web dashboard lets users explore findings and ask the assistant for re‑investigations. It supports multi‑model runs, suppression registries, diffing against baselines, and CI exit‑code gating.

A Julia package for performing efficient nearest neighbor searches using KD-Trees, Ball-Trees, and support for periodic boundary conditions.

A workflow that uses the Mistral AI OCR API to convert PDFs into structured Markdown documents with linked images, specifically formatted for Obsidian.

A collection of 21 specialized workflows for Claude that apply top-tier strategy-consulting frameworks to tasks like market mapping, risk governance, and executive communication.

An emergent world simulation engine that uses LLMs to drive autonomous characters to create unscripted, evolving civilizations and social dynamics.

An automated machine learning framework that allows users to create ML models via ready-to-use presets or by building custom pipelines for tabular, text, image, and time series data.

An integrated platform for building and hosting dynamic websites and web applications featuring a high-performance runtime and Native AI for automated site creation and maintenance.

A Rust‑based, step‑by‑step course that guides you to implement an in‑memory vector database, covering Arrow tables, DataFusion integration, and several ANN indexes (IVFFlat, NSW, HNSW, IVF‑PQ), with SQL support and benchmark tools.

A universal content reader that fetches, transcribes, and digests content from various platforms like YouTube, X, and WeChat into a structured format.

An extension of openai-whisper that provides accurate word-level timestamps and confidence scores for multilingual automatic speech recognition.

A desktop plugin for Hermes Agent that turns agent profiles into a roster of named bots with individual personalities, group chat capabilities, and automated routines.

A gradient-free optimization platform for minimizing functions, particularly useful for hyperparameter tuning in machine learning.

A lightweight wrapper that converts Model Context Protocol (MCP) tools into LangChain/​LangGraph tools, supporting multiple transports (stdio, HTTP, streamable‑HTTP) and multi‑server setups.

oneDNN (oneAPI Deep Neural Network Library) is an open‑source, cross‑platform performance library that supplies highly optimized CPU and GPU kernels for deep‑learning operators. It implements the oneAPI specification, supports Intel, AMD, Arm, and experimental Power/IBM z/RISC‑V hardware, and is used by major frameworks such as PyTorch, TensorFlow, ONNX Runtime, and llama.cpp.

A Gaussian processes framework in Python that provides tools for implementing and optimizing probabilistic models for regression and classification.

TensorFlow Quantum is a Python library that integrates Cirq quantum circuits with TensorFlow/Keras, providing high‑performance hybrid quantum‑classical machine‑learning models, automatic differentiation, and scalable simulation via qsim.

A collective communications library that provides primitives like allreduce and broadcast for efficient multi-machine machine learning training.

A JavaScript SDK that enables running production-ready LLMs and multimodal AI models directly in the browser using WebGPU acceleration for privacy and zero server costs.

A high-performance library for approximate nearest neighbor searches in high-dimensional vector spaces, supporting graph and tree-based indexing for datasets up to billions of objects.

A World Action Model for robot control that uses visual dynamics during training but action-only decoding during inference to achieve real-time, low-latency deployment.

A PyTorch implementation of the Transfusion architecture that unifies next-token prediction for text and flow matching for continuous modalities like images in a single model.