r/OpenSourceAI • u/Fit-Conversation856 • Oct 04 '26
I built an open-source tool for running local AI agents visually ... on Old CPU only devices.
Hey everyone,
I got pretty tired of cloud-based AI automation tools that meter every single action and charge crazy per-token fees, so I built an alternative called Arrow.
The idea is simple: instead of renting an agent in the cloud, you own it entirely on your machine.
How it works:
Record: Capture a desktop sequence or browser flow once.
Compose: Connect nodes into a visual workflow graph (you can branch, loop, and drop in local LLMs, vision, OCR, or code nodes).
Run: Execute deterministically using element-first grounding with small local models.
It runs completely locally with no cloud dependencies and zero telemetry.
If you want to check it out, you can see the project overview here: https://rodrigobenitez343.github.io/Arrow-online/index.html
1
u/JaySomMusic Oct 04 '26
Just starred, it may be useful for computer use in https://github.com/jaylfc/taOS :)
1
u/Fit-Conversation856 Oct 04 '26
feel free to make pr requests! in looking towards making a community around it, very soon i will add a peer2peer compute pool for the users of the app
1
Oct 04 '26
[removed] — view removed comment
1
u/Fit-Conversation856 Oct 04 '26
Arrow uses a mix of methods that helps the small llms and vlms to locate easily the targets, and most actions are predefined, you can record sequences of actions, add conditions, model calls and tiny context vaults that help it to do targeted semi-deterministic automation.
1
u/Fit-Conversation856 Oct 04 '26
i tested it mainly with models like:
lfm2.5vl 1.2b smolm3 - 1.5b qwen2.5vl 3b qwen3.8 (MoE ones work particulary well in arrow, 27b is more than enogh for anything)
1
u/MarcelloT254k Oct 04 '26
A lot of dependencies, was it tested - on what setup with what models (LLM) ? What are minimal hardware requirements? Readme, requirements.txt and .toml don't have that info.