Steven EnamakelandGitHub
8757bb9f15
* Enhance documentation and structure across core modules - Added comprehensive module-level documentation for `lib.rs`, `main.rs`, `cli.rs`, `jsonrpc.rs`, `mod.rs`, `config.rs`, and `skills.rs`, detailing their functionalities and responsibilities within the OpenHuman platform. - Improved function-level documentation to clarify arguments, return types, and error handling for key functions such as `run_core_from_args`, `rpc_handler`, and `run_from_cli_args`. - Enhanced comments throughout the code to improve readability and maintainability, ensuring a clearer understanding of the codebase for future development. * Enhance documentation for RuntimeEngine and SkillRegistry - Improved struct and function-level documentation in `qjs_engine.rs` to clarify the lifecycle management of JavaScript-based skills, including skill discovery, startup, and shutdown processes. - Updated comments in `skill_registry.rs` to provide clearer descriptions of the registry's role in managing active skills and their communication channels. - Added detailed explanations for key methods, enhancing understanding of their functionality and usage within the OpenHuman platform. * Enhance documentation across skill modules - Improved module-level and struct-level documentation in `manifest.rs`, `ops.rs`, `socket_manager.rs`, and `types.rs` to clarify the purpose and functionality of various components within the skills system. - Added detailed comments for key structs and functions, including `SkillSetup`, `Skill`, and `SocketManager`, enhancing understanding of their roles in skill management and communication. - Updated descriptions for enums and message types to provide clearer context for their usage in the skill lifecycle and internal messaging. * Enhance documentation across skills modules - Added comprehensive module-level documentation for `registry_ops.rs`, `registry_types.rs`, `schemas.rs`, and `qjs_skill_instance` modules, detailing their functionalities and responsibilities within the OpenHuman skills system. - Improved function-level comments to clarify the purpose and usage of key functions, including `registry_fetch`, `registry_search`, and `skill_install`. - Enhanced descriptions for structs and enums, providing clearer context for their roles in skill management and execution. - Updated comments throughout the code to improve readability and maintainability, ensuring a clearer understanding of the codebase for future development. * Enhance documentation for QuickJS and IndexedDB modules - Improved module-level documentation in `quickjs_libs/mod.rs` to clarify the purpose and functionality of the QuickJS runtime support. - Enhanced comments in `storage.rs` to provide detailed descriptions of the IndexedDB storage layer, including its features and compatibility with the browser's IndexedDB API. - Updated function-level comments to improve clarity on database connection management and object store operations, ensuring better understanding for future development. * Enhance documentation across memory modules - Added comprehensive module-level documentation for `mod.rs`, `ops.rs`, `rpc_models.rs`, `schemas.rs`, and `traits.rs`, detailing their functionalities within the OpenHuman memory system. - Improved function-level comments to clarify the purpose and usage of key functions, enhancing understanding of memory operations, RPC handling, and data structures. - Updated comments throughout the code to improve readability and maintainability, ensuring a clearer understanding of the memory system for future development. * Enhance documentation for memory modules - Updated module-level documentation in `chunker.rs`, `embeddings.rs`, and `relex.rs` to provide clear descriptions of their functionalities within the OpenHuman memory system. - Improved function-level comments to clarify the purpose and usage of key functions, enhancing understanding of markdown chunking, embedding providers, and relation extraction processes. - Added detailed explanations for structs and enums, ensuring better context for their roles in memory operations and data handling. * Enhance documentation across memory modules - Updated module-level documentation in `ingestion_queue.rs`, `ingestion.rs`, `response_cache.rs`, `client.rs`, and `mod.rs` to provide clearer descriptions of their functionalities within the OpenHuman memory system. - Improved function-level comments to clarify the purpose and usage of key functions, enhancing understanding of document ingestion, caching mechanisms, and memory client interactions. - Added detailed explanations for structs and enums, ensuring better context for their roles in memory operations and data handling. * Enhance documentation for memory store modules - Added comprehensive module-level documentation for `factories.rs` and `memory_trait.rs`, detailing their functionalities within the OpenHuman memory system. - Improved function-level comments to clarify the purpose and usage of key functions, enhancing understanding of memory instance creation and management. - Included detailed explanations for the `UnifiedMemory` implementation, ensuring better context for its role as a generic memory backend. * Refactor and enhance documentation across various modules - Removed unnecessary blank lines in `main.rs`, `chunker.rs`, `embeddings.rs`, `ingestion.rs`, `relex.rs`, `rpc_models.rs`, `memory_trait.rs`, `manifest.rs`, `mod.rs`, `ops.rs`, `qjs_engine.rs`, `socket_manager.rs`, and other files to improve code readability. - Improved comments and documentation in several modules to clarify the purpose and functionality of key components, enhancing overall understanding of the codebase. - Ensured consistent formatting and organization of comments throughout the code, contributing to better maintainability and clarity for future development. * fix import * 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 |
Contributors Hall of Fame
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