Ask
Talk to your shell in natural language. 100% local AI.
What it does
'ask' turns natural language into shell commands using AI that runs 100% locally via Ollama. No API keys, no cloud, no data leaves your machine. 🔍 Project-aware - detects Go, Node, Python, Rust and tailors commands accordingly; ⚠️ Safety warnings - flags dangerous commands like rm -rf before execution; 💡 Explain mode - prefix any command with ? to understand what it does; 📡 Works offline - once set up, no internet required Open source, built with Go, one-line install.
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I was constantly googling CLI commands so I built this small CLI tool with GPT3. You can ask for shell commands right from the CLI. You'd need to use your own API KEY for this but it's pretty simple, instructions are in the README Not perfect but not bad either.
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Hi HN, I just released a very simple AI Shell / CLI tool that lets you convert natural language directly into executable shell commands. Built with python to simplify terminal workflows and help you quickly run commands without memorizing syntax. It has two main usage modes: One-shot mode: Quickly execute commands using natural language. Example: ai "find all PNG files larger than 5MB" The AI responds with the appropriate command and asks if you want to execute it. Interactive chat mode: Start a terminal chat session with the AI (ai -i) to iteratively build commands or scripts. Some…
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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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AI · 18d ago · company-app.joinastute.com
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…
AI · 27d ago · cactuscompute.com
