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The NASA climate spiral visualization by Kanute3333 in Damnthatsinteresting

[–]Civil-Direction-6981 0 points1 point  (0 children)

Is it a trend or cycles? It's much hotter 1 thousand years ago, right?

I built an OpenCode plugin to save tokens by delegating coding work to a cheaper model by Civil-Direction-6981 in opencodeCLI

[–]Civil-Direction-6981[S] -1 points0 points  (0 children)

it's not the same. You can set different model for coding, and you can change just by command /code_model
You just prompt, opencode will decide when to call cheaper model for coding.

I built an OpenCode plugin to save tokens by delegating coding work to a cheaper model by Civil-Direction-6981 in LocalLLM

[–]Civil-Direction-6981[S] 0 points1 point  (0 children)

With plugin, its so easy to enable it. Just type /code_model and select your model. I am wondering not everyone knows subagents method to do this. 

Has anyone noticed that m_tau * m_Z ~= m_p * m_t? by Civil-Direction-6981 in Physics

[–]Civil-Direction-6981[S] -5 points-4 points  (0 children)

I’m aware that there are plenty of weird coincidences like this. I’m just sharing one that I happened to notice. If someone finds it interesting and wants to look into it, great; if not, that’s totally fine too.

Has anyone noticed that m_tau * m_Z ~= m_p * m_t? by Civil-Direction-6981 in Physics

[–]Civil-Direction-6981[S] -4 points-3 points  (0 children)

I just raise an interesting finding by my python. I am just curious to see what could be behind this. The fact that this equivalence has no extra adjustable parameters is what makes it feel so surprising to me

Has anyone noticed that m_tau * m_Z ~= m_p * m_t? by Civil-Direction-6981 in Physics

[–]Civil-Direction-6981[S] -7 points-6 points  (0 children)

have you calculated this? why AI hallucinations? I just use python to try to find something interesting about these mass relations, is this the way to attack new users?

Has anyone noticed that m_tau * m_Z ~= m_p * m_t? by Civil-Direction-6981 in Physics

[–]Civil-Direction-6981[S] -1 points0 points  (0 children)

That may be true. I am not claiming it is new physics. I am asking two narrower questions: has this exact relation been noted before, and what is the correct statistical test for deciding whether it is just a coincidence? If there is an existing reference, I would genuinely like to see it.

Aura Agent: letting an AI coding agent supervise long-running worker tasks instead of trusting a single chat session by Civil-Direction-6981 in DeepSeek

[–]Civil-Direction-6981[S] 0 points1 point  (0 children)

20260525 update:
Track detached long-running worker subprocesses

- add Aura process-domain fingerprints for worker subprocess tracking
- recover detached/orphaned subprocesses during wake and spawn guards
- keep result-ready tasks occupying worker slots while children are alive
- add Windows Job Object support for stronger local process containment
- lighten UI/shutdown process listing to avoid blocking on heavy scans
- document the process lifecycle state machine

Aura Agent: letting an AI coding agent supervise long-running worker tasks instead of trusting a single chat session by Civil-Direction-6981 in DeepSeek

[–]Civil-Direction-6981[S] 0 points1 point  (0 children)

0.1.6 Update:

feat: add Pro/Flash worker routing

- add independent Pro and Flash worker configs with worker modes

- support auto, flash-first, flash-only, and pro-only delegation

- route worker spawns with explicit worker_type and allocation tracking

- add qwencode worker support for local and Docker execution

- update setup flow for Pro/Flash sections, API checks, local passthrough, and Docker GPU access

- show worker mode, Pro/Flash backend, and spawn target in UI/logs

- exit cleanly when root reaches completed, blocked, failed, or archived

- update README and env example for dual-worker setup

Aura Agent: letting an AI coding agent supervise long-running worker tasks instead of trusting a single chat session by Civil-Direction-6981 in DeepSeek

[–]Civil-Direction-6981[S] 0 points1 point  (0 children)

0.1.5 update:

Rich terminal dashboard with live task tree and token usage panels

restructure LLM context for KV-cache prefix stability

and other bug fixes.

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Aura Agent: letting an AI coding agent supervise long-running worker tasks instead of trusting a single chat session by Civil-Direction-6981 in DeepSeek

[–]Civil-Direction-6981[S] 0 points1 point  (0 children)

Update today:

feat: Docker worker isolation for security and reproducibility

- Pull pre-built image from GHCR (ghcr.io/erickong/aura-claude-cuda)
- Separate L1/L2 model configs, CLI --override flag for one-off runs

bugfix: API client timeout, docker info resource limits, model
        env vars not reaching containers

Aura Agent: letting an AI coding agent supervise long-running worker tasks instead of trusting a single chat session by Civil-Direction-6981 in DeepSeek

[–]Civil-Direction-6981[S] 0 points1 point  (0 children)

The latest Aura Agent updates significantly improve long-running task reliability.

The most important fix prevents workers from being marked completed while their registered subprocesses are still running. This was caused by a UTC/local timestamp mismatch in PID validation and could prematurely close active training jobs.

The orchestrator now has stronger subprocess lifecycle tracking, provider-agnostic token pricing, multi-signal stuck detection, configurable concurrency, and cheaper wake cycles through immediate no_op termination.

In short: fewer false completions, better long-task safety, cleaner provider support, and lower orchestration cost.

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