Metadata-Version: 2.4
Name: exowindows
Version: 0.1.0
Summary: Fast, distributed ML scaling on Windows. Connect computers over Ethernet, Wi-Fi, USB-C, or Thunderbolt.
License: Apache-2.0
Requires-Python: >=3.11
Requires-Dist: click>=8.1.0
Requires-Dist: httpx>=0.27.0
Requires-Dist: psutil>=6.0.0
Requires-Dist: rich>=13.0.0
Requires-Dist: wmi>=1.5.1; sys_platform == 'win32'
Provides-Extra: torch
Requires-Dist: torch>=2.0.0; extra == 'torch'
Description-Content-Type: text/markdown

# exowindows

Fast, distributed ML scaling on Windows. Seamlessly connect machines via Ethernet, USB-C, or Thunderbolt, and run distributed PyTorch training/inference and Ollama LLMs with automatic hardware detection, heterogeneous partitioning, and speedup alerts.

## Installation

```bash
pip install exowindows
```

## Features

- **Distributed Compute & RAM speed filtering**: Automatically runs across local and remote GPUs, CPU, and RAM, with a 3200MHz RAM speed constraint to filter out slow devices.
- **Ollama CLI Integration**: Run `exowindows ollama run llama3.1` to scan for connected worker machines, see performance suggestions, and run distributed inference.
- **PyTorch Hook**: Integrates with PyTorch training to auto-detect optimal cluster nodes and show speedup recommendations.
- **Easy Worker Join**: Run `exowindows-node join` to connect workers.
