Mellea

An AI-agent development tool that compiles natural-language skills into structured Python programs. It applies schema, safety, security, and guardian-hook checks during compilation.

MLX is an array framework for machine learning on Apple silicon, developed by Apple machine learning research. It provides Python, C++, C, and Swift APIs modeled on NumPy, plus higher-level packages such as mlx.nn and mlx.optimizers with PyTorch-like interfaces. Its composable transformations support automatic differentiation, automatic vectorization, and computation-graph optimization; computations are lazy, graphs are built dynamically, and operations can run on supported CPUs and GPUs using shared unified memory rather than explicit data transfers. MLX is distributed through PyPI and supports model training and deployment workflows including language-model training and generation, LoRA fine-tuning, image generation, and speech recognition.

Murmell is a cloud platform for running and coordinating AI coding agents (for example Codex, Claude, and Kimi). It provides a shared cloud sandbox for collaborative coding, real-time file-path locking to prevent merge conflicts, and tools to deploy from any terminal.

AirLLM is an open-source Python library for running large language model inference on GPUs with limited memory. It reduces GPU memory use by loading and processing one model layer at a time instead of holding the entire model in GPU memory; for sparse mixture-of-experts models, it streams individual experts as needed. The project is designed to run large models without requiring quantization, distillation, or pruning, and provides a pip-installable package with support for multiple model families, CPU inference, macOS, and optional model compression and quantization features.

MTPLX is an open-source native Mac app and command-line tool for running local language models on Apple Silicon. It uses a model's built-in multi-token prediction (MTP) heads to draft several tokens, verifies the block in one batched forward pass, and commits tokens with exact rejection sampling and residual correction, without requiring a separate draft model or changing the model's sampling distribution. It provides local OpenAI-compatible and Anthropic-compatible APIs, native chat, model management, hardware-specific draft-depth tuning, and tooling for building and verifying MTP models. The server can also expose MLX embedding and reranking models. MTPLX requires an M1-or-newer Mac running macOS 14 or later, and the repository is licensed under Apache-2.0.