everyharness is an offline-first command-line and terminal user interface for running locally available machine-learning models through pluggable harnesses. It is intended for developers and ML practitioners who need a flexible local model runner.
everyharness sits in PulseGate's CLI tools & terminal category. It focuses on running dropped-in machine-learning models locally without relying on hosted services or a fixed runtime. It is built as an open-source project for developers and ML practitioners. The project is open source (Apache-2.0). It runs on the command line, Linux, macOS, and Windows, and it can be self-hosted.
kavin0x builds and maintains everyharness, and it first shipped in 2026. The project is developed in the open on GitHub with 5 commits in the last 90 days. Among its 6 catalogued features are offline execution, CLI interface, and TUI interface.
Summary written by a language model from the project’s public pages.
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