apra-fleet
Run a fleet of AI agents across your machines
What it does
An open-source MCP server that turns machines you already own into a fleet of AI agents. Mix Claude, Antigravity, Codex, Copilot, and local models via OpenCode; route work by cost tier; run durable, multi-hour, observable workflows. It builds its self autonomously.
What Kubernetes did for containers, apra-fleet does for AI agents: scheduling, credentials, isolation, and observability for an agentic workforce -- on hardware you already own, mixing every LLM provider at once. "Register a local member called doer. Register another called reviewer. Pair them." fleet manifest -- 4 members registered apra-fleet workflow fleet-sprint \ --issue my-project-epic --members doer \ --branch fleet-sprint/first-run --base main Three real moments, not a mockup: the registration wording, the manifest, and the launch command are all quoted from the project README. Real devices you already own -- registered, credentialed, health-checked members. Local or over SSH, on…from apra-labs.github.io
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, August 2026
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Life & fun · 10d ago · louisabraham.github.io
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com