Steven EnamakelandGitHub
e925e8a319
* refactor: clean up imports and improve code structure in skills_cli and registry_ops - Removed unused imports in `skills_cli.rs` and `registry_ops.rs` to enhance code clarity. - Streamlined import statements for better organization and readability. - Minor adjustments in `engine.rs` to maintain consistency in import usage. * fix: update UI text and styles for MemoryWorkspace and SkillSetupWizard components - Changed the title in MemoryWorkspace to "Memory (EverMind)" for clarity. - Updated text colors in SkillSetupWizard for better visibility and consistency. - Enhanced button styles and loading indicators for improved user experience. * feat: implement reset functionality for OpenHuman data and enhance app data clearing process - Added a new utility function `resetOpenHumanDataAndRestartCore` to reset local OpenHuman data and restart the core process. - Updated `clearAllAppData` in `SettingsHome` to utilize the new reset function, improving the app's data clearing process. - Enhanced error handling during the data reset and session clearing operations to ensure robustness. - Introduced tests for the new reset functionality to validate its behavior and integration. * refactor: remove screen recording permission from AccessibilityPanel - Eliminated the screen recording permission check and associated UI elements from the AccessibilityPanel component. - Updated tests to ensure the screen recording option is no longer present in the rendered output, improving clarity and focus on relevant permissions. * chore: update package.json files to integrate Husky for Git hooks - Added Husky as a dev dependency in both package.json files to manage Git hooks. - Included "prepare" and "postinstall" scripts in the main package.json to ensure Husky is set up correctly. - Cleaned up the app's package.json by removing the "prepare" script, as it is now handled in the main package.json. - Enhanced logging in tauriCommands.ts for better debugging during the reset process. * fix: update variable name for clarity in ops.rs test assertions - Changed the variable name from `data` to `value` in the test assertions to enhance clarity and better reflect its purpose. - Ensured that the assertions remain functional and maintain the integrity of the test logic. * feat: enhance skill selection logic in skills_debug_e2e.rs - Introduced a new function `select_skill_id` to improve skill selection based on environment variables and preferred skills. - Updated the skill ID retrieval process to prioritize user-defined skills while maintaining a fallback to the default skill. - Enhanced documentation to clarify the usage of environment variables for skill testing. * format
OpenHuman
The age of super intelligence is here. OpenHuman is your Personal AI super intelligence. Private, Simple and extremely powerful.
Discord • Reddit • X/Twitter • Docs
"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:
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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.
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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.
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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.
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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.
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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.
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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 |
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