Steven EnamakelandGitHub
ae9ac30db6
* feat: add proactive agents for onboarding experience - Introduced two new proactive agents: "Morning Briefing" and "Welcome Message". - The Morning Briefing agent provides a daily summary of the user's calendar, tasks, and relevant context, scheduled to run automatically at 7 AM. - The Welcome Message agent delivers a personalized greeting after onboarding, utilizing user information for a tailored experience. - Updated the cron job system to seed these agents upon onboarding completion, enhancing user engagement from the start. - Added comprehensive tests to ensure the correct functionality of the new agents and their integration into the system. * feat: implement proactive message handling for user engagement - Added a new `ProactiveMessageSubscriber` to route proactive messages (e.g., morning briefings, welcome messages) to the user's active channel, enhancing user engagement. - Introduced `ProactiveMessageRequested` event in the event bus to facilitate proactive message delivery. - Updated the configuration schema to include a preferred channel for proactive messages, allowing for tailored user experiences. - Seeded default proactive agent cron jobs to ensure timely delivery of messages post-onboarding. - Enhanced the startup process to register the proactive message subscriber, ensuring proactive messages are consistently routed. - Comprehensive tests added to validate the functionality of proactive message handling and delivery mechanisms. * feat: enhance welcome agent functionality and onboarding process - Updated the welcome agent's description to clarify its role as the first point of contact for new users, focusing on guiding them through remaining onboarding steps. - Increased the maximum iterations for the agent from 4 to 6 to allow for more complex interactions. - Introduced a new `complete_onboarding` tool to check the user's setup status and mark onboarding as complete, improving the onboarding experience. - Enhanced the prompt structure to provide clearer guidance on the agent's workflow, including steps for checking setup status, greeting users, and completing onboarding. - Updated the tools list to include `complete_onboarding`, ensuring the welcome agent can effectively manage user onboarding. - Comprehensive documentation added to clarify the agent's functionality and improve user engagement. * feat: enhance welcome agent functionality and onboarding process - Updated the welcome agent's description to clarify its role as the first point of contact for new users, focusing on guiding them through setup and onboarding. - Increased the maximum iterations for the agent from 4 to 6 to allow for more comprehensive interactions. - Introduced a new `complete_onboarding` tool to check the user's setup status and mark onboarding as complete, improving the onboarding experience. - Enhanced the prompt structure to provide clearer guidance on the agent's workflow, including steps for checking setup status, greeting users, and completing onboarding. - Updated the tools list to include the new `complete_onboarding` tool, ensuring it is available for the welcome agent's operations. - Improved documentation for the welcome agent's prompt, emphasizing tone guidelines and what not to do during user interactions. * style: apply rustfmt to onboarding flow changes * refactor: streamline proactive message subscriber registration and enhance onboarding agent tests - Replaced the direct registration of the proactive message subscriber with a new `register_web_only_proactive_subscriber` function, ensuring it is only registered once during domain startup. - Updated the welcome agent test to reflect the addition of the `complete_onboarding` tool, verifying its presence and adjusting the expected number of tools. - Enhanced the onboarding process by improving logging for proactive agent seeding transitions, providing clearer insights during onboarding state changes. - Refactored the cron job system to support agent definitions, allowing for more flexible job scheduling and execution based on defined agent parameters. - Improved documentation and comments across the affected modules to clarify the purpose and functionality of changes made. * refactor: improve proactive subscriber registration and logging - Streamlined the registration process for the web-only proactive message subscriber, enhancing clarity and maintainability. - Consolidated logging statements in the onboarding completion function for improved readability and consistency. - These changes aim to enhance the overall structure and logging clarity within the proactive messaging and onboarding processes.
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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