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Open-source deep-learning framework for building, training and deploying neural networks on GPUs and CPUs.

The OpenAI Agents SDK is a lightweight yet powerful framework for building multi-agent workflows. It is provider-agnostic, supporting the OpenAI Responses and Chat Completions APIs, as well as 100+ other LLMs via integrations like LiteLLM.

Agent Lightning is an open-source framework developed by Microsoft Research for optimizing and training AI agents using reinforcement learning (RL) and other techniques, supporting integration with any agent framework with minimal code changes.

End-to-end open-source machine-learning platform for building, training and deploying models across desktop, mobile, web and cloud.

KTransformers is a flexible framework for experiencing cutting-edge optimizations in LLM inference and fine-tuning, focusing on CPU-GPU heterogeneous computing. It consists of two core modules: kt-kernel for high-performance inference kernels and kt-sft for fine-tuning. The project supports various hardware and models like DeepSeek series, Kimi-K2, achieving significant resource savings and speedups, such as reducing GPU memory for a 671B model to 70GB and up to 28x acceleration.

Open-source Python library from Hugging Face that supplies thousands of pretrained transformer models and utilities for text, vision, audio and multimodal tasks.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

High-level, multi-backend deep-learning API for building, training and deploying neural-network models.

Lightweight PyTorch wrapper that separates research code from engineering, enabling fast, scalable and reproducible deep-learning workflows.

JAX is a high-performance Python library that brings just-in-time compilation, automatic differentiation and easy parallelism to NumPy-style array programming.

NumPy is the fundamental package for scientific computing in Python. It provides a powerful N-dimensional array object, broadcasting operations, linear algebra, FFT, random number capabilities, and integration with C/C++/Fortran, and serves as a core building block for many AI and scientific libraries.

ONNX (Open Neural Network Exchange) is an open ecosystem that provides an open source format for AI models, including deep learning and traditional ML. It defines an extensible computation graph model, built-in operators, and standard data types, focusing on inferencing capabilities. Widely supported across frameworks and hardware, it enables interoperability and accelerates AI innovation.