Steven EnamakelandGitHub
3db06e8e92
* Enhance debug-agent-prompts script and prompt rendering logic - Updated the `debug-agent-prompts.sh` script to always run `cargo build`, ensuring the latest binary is used and preventing stale binaries from affecting agent behavior. - Modified the output directory handling to wipe and recreate it at the start of each run, ensuring a clean snapshot of the current agent set. - Enhanced the `render_subagent_system_prompt` function to unconditionally inject `PROFILE.md`, ensuring it is included even when identity information is omitted, thus improving personalization for agents like `welcome`. - Added tests to verify the correct injection of `PROFILE.md` under various conditions, ensuring robust functionality and preventing regressions in prompt rendering. * Enhance debug-agent-prompts script to utilize the currently-logged-in user's workspace - Updated the `debug-agent-prompts.sh` script to point to the real user's workspace, ensuring onboarding-generated files like `PROFILE.md` are included in the dump. - Improved workspace resolution logic to prioritize the active user's workspace, falling back to default paths as necessary. - Added error handling for cases where the workspace is not found, providing clear guidance for users to complete onboarding or specify a different workspace. - Enhanced output to include the presence state of `PROFILE.md`, improving visibility into the onboarding process. * Add profile inclusion for user-facing agents to enhance personalization - Updated agent TOML configurations for orchestrator, trigger reactor, trigger triage, and welcome agents to include user profile data by setting `omit_profile = false`. This allows agents to personalize interactions based on user context derived from `PROFILE.md`. - Refactored the `AgentDefinition` struct to include a new `omit_profile` field, ensuring that agents can opt-in to utilize user profile information. - Enhanced prompt rendering logic to conditionally inject `PROFILE.md` based on the `omit_profile` flag, improving the relevance and personalization of agent responses. - Updated tests to verify the correct behavior of profile inclusion across various agents, ensuring robust functionality and preventing regressions. * Implement `omit_profile` flag in `AgentBuilder` and `Agent` for profile management - Added a new `omit_profile` field to the `AgentBuilder` struct, allowing agents to specify whether to include user profile data in their responses. - Updated the `Agent` struct to mirror the `omit_profile` flag, ensuring that the profile inclusion logic is consistent across agent instances. - Enhanced the `omit_profile` method in `AgentBuilder` to facilitate the configuration of this flag during agent construction. - Adjusted the default behavior to omit profiles for legacy agents while allowing opt-in for specific agents that require user context. - Updated documentation to clarify the purpose and usage of the `omit_profile` flag in agent definitions. * Implement profile management enhancements in Agent and prompt rendering - Introduced an `omit_profile` flag in the `AgentBuilder` and `Agent` to control the inclusion of user profile data in responses, defaulting to true for legacy paths. - Updated the `Agent` struct to utilize the `omit_profile` flag, ensuring consistent profile inclusion logic across agent instances. - Enhanced prompt rendering logic to conditionally include or exclude `PROFILE.md` based on the `omit_profile` setting, improving personalization for user-facing agents. - Added tests to verify the correct behavior of profile inclusion and omission across various scenarios, ensuring robust functionality and preventing regressions. * feat(prompt): per-agent MEMORY.md injection with 2000-char cap Add `omit_memory_md` to `AgentDefinition` (mirror of `omit_profile`) and inject `MEMORY.md` alongside `PROFILE.md` in both the main and sub-agent render paths. Both user-specific files are capped at `USER_FILE_MAX_CHARS = 2_000` (~1000 tokens each) via a new `inject_workspace_file_capped` helper so growing on-disk files can't balloon the system prompt. Opt-in on the same four user-facing agents (welcome, orchestrator, trigger_triage, trigger_reactor). Narrow specialists leave it at the `true` default. KV-cache contract is documented on the flag, the injection sites, and the capped helper: rendered bytes are frozen per session, and mid-session writes only surface on the next session. Pinned with a new `rendered_subagent_system_prompt_is_byte_stable_across_repeat_calls` test plus coverage for injection / opt-out / 2000-char cap. * refactor(tests): clean up test formatting and improve readability - Removed unnecessary line breaks and adjusted indentation in test files for better consistency and clarity. - Reformatted the `RewardsCouponSection` test to enhance readability and maintain a uniform style across test cases. - Ensured that all test cases align with the updated formatting standards, improving overall maintainability. * feat(debug-agent-prompts): enhance output directory validation and canonicalization - Improved the `debug-agent-prompts.sh` script to validate and canonicalize the output directory (`OUT_DIR`) before performing any file operations. - Added checks to reject relative paths and ensure the output directory is an absolute path, preventing potential catastrophic deletions. - Implemented a `canonicalize` function that uses `realpath` or `readlink` to resolve paths, with a fallback to Python for compatibility on barebones systems. - Enhanced error handling to provide clear feedback when the output directory cannot be validated or canonicalized. - Ensured that the script operates on the canonicalized path for all subsequent commands, maintaining consistency and safety. * style(turn): single-line rustfmt for redacted log branch
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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