Steven EnamakelandGitHub 73f8d1287a refactor: remove hardware-related components and streamline service management (#502)
* feat(config): introduce pre-login user directory structure

- Added support for a pre-login user directory to encapsulate configuration, memory, and state before any user logs in. This ensures that all initial data is scoped under a dedicated user directory (`users/local`), preventing direct writes to the root `.openhuman` path.
- Implemented the `pre_login_user_dir` function to return the appropriate path for the pre-login user.
- Updated configuration loading logic to defer disk state creation until the first successful login, enhancing user data management and isolation.
- Added tests to verify the correct behavior of the pre-login directory structure.

* refactor: remove hardware-related components and streamline service management

- Deleted hardware configuration and related tools from the codebase, including `HardwareConfig`, `HardwareTransport`, and associated memory management tools.
- Introduced a new `service.ts` module for managing service and daemon commands, consolidating service-related functionalities.
- Updated import paths across the application to reflect the removal of hardware references and the addition of the new service management module.
- Refactored the `build_system_prompt` function to remove hardware access instructions, focusing on action instructions instead.
- Cleaned up the Cargo.toml and Cargo.lock files by removing unused dependencies related to hardware management.

* chore: apply formatting and tauri lockfile sync

* refactor(tests): extract config file writing logic into a reusable function

- Introduced a `write_config_file` function to encapsulate the logic for creating directories and writing configuration files, improving code reuse and readability.
- Updated test cases to utilize the new function for writing configuration files, ensuring consistency and reducing duplication.
- Added handling for pre-login user directory structure to ensure configuration is correctly written to the appropriate paths.
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OpenHuman

The age of super intelligence is here. OpenHuman is your Personal AI super intelligence. Private, Simple and extremely powerful.

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Early Beta Platforms: desktop only Latest Release

The Tet

"The Tet. What a brilliant machine" — Morgan Freeman as he reminisces about alien superintelligence in the movie Oblivion

Early Beta — Under active development. Expect rough edges.

To install or get started, either download from the website over at tinyhumans.ai/openhuman or run

# For MacOS/Linux
curl -fsSL https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.sh | bash

# For Windows
irm https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.ps1 | iex

What is OpenHuman?

OpenHuman is an open-source agentic assistant that is designed to integrate with you in your daily life. Here's what makes OpenHuman special:

  • Simple, UI-first — A clean desktop experience and short onboarding paths so you can go from install to a working agent in a few clicks, without a config-first setup. You don't need a terminal to run OpenHuman.

  • One subscription, many providers — You only need one account to get access to many agentic APIs (AI Models, Search, Webhooks/Tunnels and other 3rd party APIs etc..), simplifying the experience to get a powerful agent going.

  • Rich Skills — Plug into Gmail, Slack, Notion, and the rest of your stack via rich, feature-backed skills. Connections are typically one click through setup wizards instead of wiring APIs by hand. Workflow data is kept on device, encrypted locally, and treated as yours: encryption and sensitive context stay on your machine. Webhooks give instant feedback into the agent when external systems or skills emit events, so the loop stays tight without constant polling.

  • Local knowledge base — Built from your data and your activity. How you work across tools, sessions, and connected services—so the agent gets rich, workflow-aware context, not a one-off chat transcript. Everything is stored on your machine and compounding over time without becoming a cloud dossier. Channels, skills and ongoing conversations feed the same loop so day-to-day context does not reset every session.

  • Local AI model — The Rust core exposes local AI paths (and the desktop bundle can ship local/bundled runners where applicable) for the workloads above—vision snippets, speech helpers, summarization, tooling—so sensitive steps can stay off the cloud when you choose.

  • Deep desktop integrations — OpenHuman is a native desktop assistant, not a web-only chat: memory-aware keyboard autocomplete, voice (STT listening and TTS replies), screen intelligence that understands what is on screen and feeds your local context, plus windowing and OS-level permissions—so the agent meets you on the machine, not trapped in a browser tab.

Architecture: docs/ARCHITECTURE.md. Contributor orientation: CONTRIBUTING.md.

OpenHuman vs other agents

High-level comparison (products evolve—verify against each vendor). OpenHuman is built to minimize vendor sprawl, keep workflow knowledge on-device, and ship deep desktop features—not only chat.

Claude Code/Cowork OpenClaw Hermes Agent OpenHuman
Open-source: Is the codebase open to review? 🚫 Proprietary client MIT License MIT License GNU License
Simple: Is it simple to get started? Simple Desktop App + CLI ⚠️ Terminal first and often complex ⚠️ Terminal first and often complex Simple, Clean UI/UX. Get started within minutes
Cost: How expensive is to run? ⚠️ Subscription + add-on tool/API costs ⚠️ Tied to models & hosting you choose ⚠️ Tied to models & hosting you choose Cost optimized with the option to run many things locally for free
Memory & Knowledge Base (KB): Does the agent know you and your world? Built-in memory; mostly chat/session scoped ⚠️ Has a local memory but often needs plugins for richer behavior Self-learning / task loops (typical) 🚀 Local KB + Self-learning from your activity & data (GMail, Notion etc... via skills) & prompts
API spagetti: How complex is it to hook mulitple features together? 🚫 Claude bill + often extra keys for MCP/tools 🚫 BYOK / multi-vendor common 🚫 Multiple providers common One account get access to many bundled platform APIs
Extensibility: Can you add rich features into it? MCP (different model than sandboxed skills) Plugin Architecture (SKILL.md) Plugin Architecture (SKILL.md) 🚀 Rich Skills with ability to have realtime updates, local DB & more
Desktop integrations: Can it integrate into your desktop completely? ⚠️ Desktop app & access to folders ⚠️ Often lighter native surface ⚠️ Often lighter native surface STT, TTS, screen intelligence, memory-aware autocomplete and a whole lot more

Contributors Hall of Fame

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