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GitHub Open Source joeynyc/hermes-hudui

Web UI consciousness monitor for Hermes — the AI agent with persistent memory

1,145
Traction Score
129
Forks
Apr 9, 2026
Launch Date
View Origin Link

Product Positioning & Context

AI Executive Synthesis
Advanced AI agent management, skill lifecycle management, enterprise scalability, operational intelligence.
This suggestion proposes integrating 'long-lived skill governance' with the Hermes HUD UI, addressing critical challenges in managing AI agents at scale: skill duplication, staleness, and fragmentation across agents/teams. While `hermes-hudui` provides observability, the proposed `SkillClaw` functionality offers a post-task evolution loop for skill deduplication, merging, and quality improvement. This represents a significant market opportunity to enhance the product's value proposition beyond mere monitoring. For B2B SaaS, offering robust skill lifecycle management is crucial for enterprise adoption, enabling organizations to maintain efficient, high-quality AI operations and prevent technical debt in their agent deployments.
Web UI consciousness monitor for Hermes — the AI agent with persistent memory

Related Ecosystem & Alternatives

Discover adjacent products, open-source repositories, and developer tools sharing similar technical architecture.

Deep-Dive FAQs

What is joeynyc/hermes-hudui?
joeynyc/hermes-hudui is analyzed by our AI as: Advanced AI agent management, skill lifecycle management, enterprise scalability, operational intelligence.. It focuses on This suggestion proposes integrating 'long-lived skill governance' with the Hermes HUD UI, addressing critical challenges in managing AI agents at ...
Where did joeynyc/hermes-hudui originate?
Data for joeynyc/hermes-hudui was aggregated directly from the GitHub Open Source community ecosystem, representing raw developer and early-adopter sentiment.
When was joeynyc/hermes-hudui publicly launched?
The initial public indexing or launch date for joeynyc/hermes-hudui within our tracked developer communities was recorded on April 9, 2026.
How popular is joeynyc/hermes-hudui?
joeynyc/hermes-hudui has achieved measurable traction, logging over 1,145 traction score and facilitating 129 recorded discussions or engagements.
Are there active development issues for joeynyc/hermes-hudui?
Yes, we are currently tracking open architectural debates and bug reports for this project on GitHub. There are currently 4 active high-priority issues logged recently.
Are there open-source alternatives related to joeynyc/hermes-hudui?
Yes, the GitHub ecosystem contains correlated projects. For example, a repository named yizhiyanhua-ai/fireworks-tech-graph shares highly similar architectural descriptions and topics.
How does the creator describe joeynyc/hermes-hudui?
The original author or development team describes the product as follows: "Web UI consciousness monitor for Hermes — the AI agent with persistent memory"

Active Developer Issues (GitHub)

open High and Persistent CPU Usage After Hermes-Hudui Startup
Logged: Apr 18, 2026
open Possible complementary direction for Hermes HUD UI: long-lived skill governance
Logged: Apr 17, 2026
open Enhancement: Include skills from external directories
Logged: Apr 14, 2026
open Enhancement: Add Dockerfile to build a Docker image
Logged: Apr 14, 2026

Community Voice & Feedback

stone100010 • Apr 23, 2026
做就做全套,搞到位,直接上个设置按钮,补充如下功能:
1.主题风格/颜色
2.前端展示哪些栏,顺序编排
3.展示栏对应快捷键
4.每个大模型的tokens定价
5.来个背景壁纸吧
6.数据刷新频率Hz
7.四周跑马灯光环,模拟贪吃蛇,表示Hermes还在工作,停下来就停止贪吃

一时兴起,想起来这些
crazyde21 • Apr 19, 2026
We could implement a simple yet effective interim fix by adding two controls to the top-right corner of the WebUI:
A configurable auto-refresh interval setting (e.g., dropdown with options like 5s/10s/30s/1min)
A toggle switch to enable/disable the auto-refresh feature entirely
Given the high CPU overhead from frequent file reads (especially for the large state.db file), real-time refresh isn’t necessary for monitoring use cases. Even this simple adjustment would significantly reduce the tight loop of file polling/checksumming, and pair well with the immediate fix of removing force_polling=True (or tuning poll_delay_ms for polling-required environments).
This lightweight UI tweak addresses the core pain point (excessive CPU usage) without requiring complex refactoring of the file watcher logic or WebSocket-based state updates—buying time for the more complete fix while delivering tangible performance improvements for end users.
louie0609c • Apr 19, 2026
## Root cause & fix

The CPU spike originates in `backend/file_watcher.py`:

```python
for changes in watch(
*watch_paths, stop_event=self._stop_event, force_polling=True
):
```

`force_polling=True` makes watchfiles compute a checksum of every watched file every ~300 ms. If `state.db` is large (ours is ~103 MB and written to continuously by an active agent), this becomes a tight read-and-hash loop on a large file — 100% CPU indefinitely.

**Immediate fix:** remove `force_polling=True` to fall back to inotify on Linux. CPU drops to 0% instantly.

```python
for changes in watch(
*watch_paths, stop_event=self._stop_event
):
```

---

## Why `force_polling=True` was chosen in the first place

`force_polling` exists for cross-platform compatibility. inotify (Linux) / FSEvents (macOS) do **not** work in:

- NFS or other network-mounted filesystems
- VirtualBox / VMware shared folders
- Some Docker bind mounts (especially on macOS with osxfs/VirtioFS)
- WSL1 (Windows Subsystem for Li...

Discovery Source

GitHub Open Source GitHub Open Source

Aggregated via automated community intelligence tracking.

Tech Stack Dependencies

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Deep Research & Science

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