AI & ML

An adaptive AI agent framework that grows with you.

The most popular Deep Learning framework created by Google.

A framework that lets you easily use pre-trained transformer models for NLP, vision, and audio tasks.

Building applications with LLMs through composability.

A general-purpose automatic speech recognition model trained on 680k hours of multilingual and multitask supervised data.

Tensors and Dynamic neural networks in Python with strong GPU acceleration.

Turn any folder of code, SQL schemas, docs, papers, images, or videos into a queryable knowledge graph.

A multi-agents LLM financial trading framework.

A high-throughput and memory-efficient inference and serving engine for LLMs.

A collection of tools and datasets for Chinese NLP.

A library for faster LLM fine-tuning and training with reduced memory usage.

The most popular Python library for Machine Learning with extensive documentation and community support.

A high-level deep learning library with support for JAX, TensorFlow, and PyTorch backends.

An intelligent memory layer for AI agents enabling personalized interactions.

A programming framework for building agentic AI applications.

Ultralytics YOLO for object detection, segmentation, pose estimation, and classification with state-of-the-art accuracy and speed.

A framework for orchestrating role-playing autonomous AI agents for collaborative task solving.

Call 100+ LLMs using OpenAI format.

A family of open-source voice AI models from Microsoft for text-to-speech and long-form speech recognition.

A data framework for your LLM application.

Apache Spark's scalable Machine Learning library for distributed computing.

MindsDB is an open source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning models using standard queries.

Low-level orchestration framework for building stateful, long-running LLM agents.

A framework for programming, not prompting, language models.

A library for high-performance numerical computing with automatic differentiation and JIT compilation.

The most popular Chinese text segmentation library.

A tokenizer-free text-to-speech foundation model for multilingual speech generation and voice cloning.

A library that provides pre-trained diffusion models for generating and editing images, audio, and video.

A library for industrial-strength natural language processing in Python and Cython.

Deep learning framework to train, deploy, and ship AI products Lightning fast.

A high-performance serving framework for large language models and multimodal models.

Ready-to-use OCR with 40+ languages supported.

A scalable, portable, and distributed gradient boosting library.

OpenAI's framework for building and managing AI agents.

A pretrained foundation model from Google Research for time-series forecasting.

Industrial-grade speech recognition toolkit with 170x realtime speed, 50+ languages, speaker diarization, and emotion detection.

A Python agent framework for building generative AI applications with structured schemas.

A fast, distributed, high performance gradient boosting framework.

Topic Modeling for Humans.

Structured text generation for LLMs with JSON schema, regex, and grammar-constrained decoding.

A leading platform for building Python programs to work with human language data.

Approximate Nearest Neighbors in C++/Python optimized for memory usage.

A library for extracting structured data from LLMs, powered by Pydantic.

PyTorch implementations of Stable Baselines (deep) reinforcement learning algorithms.

Open Source Differentiable Computer Vision Library for PyTorch.

The open-source tool for building high-quality datasets and computer vision models.

A fast, scalable, high performance gradient boosting on decision trees library.

A multilingual speech understanding model for speech recognition, language identification, emotion recognition, and audio event detection.

A framework for real time interactive streaming digital human.

A framework that wraps any agent handler with DID-based cryptographic identity, A2A JSON-RPC over HTTP, OAuth2 auth, x402 (USDC) payments, and a built-in operator inbox.

The Stanford NLP Group's official Python library, supporting 60+ languages.

Open Source Fast Scalable Machine Learning Platform.

A scikit for building and analyzing recommender systems.

Run and fine-tune large language models on Apple Silicon with MLX.

A wrapper for Google Tesseract OCR.

Python-friendly security skills for auditing, testing, and safer backend development.

Open Source Computer Vision Library.

An open-source AgentOS for multi-agent orchestration and building agentic AI systems.

A fast Python implementation of collaborative filtering for implicit datasets.

A Python library for probabilistic graphical models and Bayesian networks.

Open-source, local-first memory for any tool-capable LLM agent.

sklearn compatible API with the widest toolset for feature engineering and selection.

A lightweight, hook-first Python framework for channel-native agents that live alongside people.

A collection of lego bricks for scikit-learn pipelines.

Python-focused engineering skills for code review, debugging, and backend workflows.

A framework for building end-to-end production-ready agentic systems, scalable & secure MCP's and autonomous agents.

A deterministic Python orchestrator for CLI coding agents (Claude Code, Codex, Gemini CLI, and 40+ more) with parallel git worktrees and an HMAC-signed audit chain.

Synthetic tabular data generation using GANs, Diffusion Models, and LLMs.

An auditable context control plane that optimizes prompt context, stabilizes cache prefixes, and verifies answers locally with WITNESS.

An agent framework for conversational analysis of SQL, dataframe and multidimensional array data.

A universal LLM API client with a Rust core, calling 142+ providers through a single OpenAI-compatible interface, with a built-in proxy and MCP server.

Django backend agent skills for Django, DRF, Celery, and Django-specific code review.

Nuwa distills the thinking of anyone — let Musk, Naval, Munger, and Feynman work for you.