FluidUse

typesafe-computer-use is an open-source macOS computer-use tool that drives a Mac toward a plain-English goal. It captures the frontmost window, reads text with OCR, collects labelled controls from the macOS accessibility tree, parses dates, and sends a structured list of possible actions to the TypeSafe decision model instead of sending screenshots to a frontier model for every step. The loop chooses actions such as clicking, scrolling, browser navigation, waiting, or pressing keys; a writing model is called only for free-text entry, proposed URLs, and the final answer, while passwords are never typed. It supports dry runs, confidence and step limits, annotated captures, detailed action and probability logs, and offline replay of saved screenshots. The repository targets macOS 14 or newer with Python 3.12 or newer, requires a TypeSafe API key, and is licensed under the MIT License.

Fast Browser Use is a local-first browser automation engine and agent skill for Claude Code, Codex, Cursor, and Python workflows. It runs Qwen3.5 models locally through MLX or PyTorch on Apple Silicon, CUDA GPUs, or CPUs, without cloud inference. The engine scans the rendered page for visible, interactable controls and converts them into bounded action candidates such as click, select, type, and done. It maps those candidates to single vocabulary tokens, scores them with one forward pass, and dispatches the selected browser action instead of generating CSS selectors, XPath expressions, or Playwright code. Text generation is used specifically for typing into fields, while structural actions use discrete logits scoring. The runtime also includes page-settling waits, visibility and occlusion checks, DOM-freshness checks, read-only protection, immutable execution traces, and external URL, title, and text assertions for outcome verification. The project provides a command-line interface, a Python API, and installable agent-skill integration, using Playwright Chromium for browser execution. It supports offline model operation after local weights are downloaded and is released under the MIT License.

Splash is a local inference engine for Apple silicon developed by Inco AI. It serves selected language models to coding agents and clients compatible with the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs, with streaming, tool calls, JSON Schema output, image input, and inline PDF support. Its runtime uses model-specific fused Metal kernels, weights packed for those kernels, a dedicated DFlash 2 draft model for speculative decoding, and a startup-computed memory plan for context, KV cache, and batching. The served model packages include the target model and its draft model; plain MLX or Transformers checkpoints are not supported. Splash runs locally on macOS, binds to a local HTTP server by default, and can be installed through Homebrew. The project is licensed under Apache-2.0, while model weights retain their own licenses.

ComfyUI is an open-source AI content-creation engine and diffusion-model GUI, API, and backend developed by Comfy-Org. Its visual node-graph interface lets users build and reuse no-code workflows for image, video, audio, 3D, and text generation, editing, and processing, including workflows using diffusion models, VAEs, text encoders, LoRAs, ControlNets, adapters, and upscalers. Workflows can be saved and loaded as JSON, exposed through App Mode, or integrated into applications through local API endpoints. The engine supports asynchronous queueing, partial graph re-execution, VRAM and RAM management, model offloading, quantized models, custom nodes, and fully offline core operation unless optional resources are requested. It can run locally on Windows, Linux, and macOS through desktop, portable, or manual installations, with support for NVIDIA, AMD, Intel, Apple Silicon, and Ascend hardware. Comfy-Org also provides an official paid cloud version.

Qwen Scribe is a private, local transcription and system-wide dictation application for Apple Silicon Macs. It runs Qwen3-ASR through mlx-qwen3-asr on the Mac's Metal GPU, keeping audio and transcripts on the computer without an account, API key, or cloud service. Users can drag audio or video into a local web interface, transcribe with automatic or forced language selection, vocabulary hints, word timestamps, and SRT export, and search or export local transcript history. A menu-bar helper provides push-to-talk dictation in text fields, displaying listening and transcription states in a non-focus-stealing HUD before pasting the result at the cursor. The project requires macOS 14 or newer, Apple Silicon, Python 3.12 or newer, and ffmpeg for non-WAV audio and video. It offers Qwen3-ASR 1.7B and 0.6B model options; model weights are downloaded separately and require roughly 3.4 GB or 1.2 GB of unified memory respectively, in addition to application overhead. It is distributed as a downloadable beta Mac app or can be built from source; the repository describes the project as version 0.2.1-beta.1.