CodeRocket Deploy
AI generates GitHub Actions workflows in 60 seconds
What it does
A GitHub App that uses AI to generate production-ready GitHub Actions workflows. Install it, select a repo, and get a custom CI/CD workflow in 60 seconds. Analyzes your codebase to detect language, framework, and deploy target, then generates an optimized workflow and opens a PR for review. Supports 8 languages, 20+ frameworks (Next.js, Django, Rails, Spring Boot...), and 10+ deploy targets (Vercel, Railway, AWS, Docker). Free tier available.
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https://the-pocket.github.io/Tutorial-Codebase-Knowledge/
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Hey HN! I'm Jacob, one of the founders of Depot (https://depot.dev), a build service for Docker images, and I'm excited to show what we’ve been working on for the past few months: run GitHub Actions jobs in AWS, orchestrated by Depot! Here's a video demo: https://www.youtube.com/watch?v=VX5Z-k1mGc8, and here’s our blog post: https://depot.dev/blog/depot-github-actions-runners. While GitHub Actions is one of the most prevalent CI providers, Actions is slow, for a few reasons: GitHub uses underpowered CPUs, network throughput for cache and the…
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My friends and I were complaining about having to decipher incomprehensible code one day and decided to pass the code through GPT to see if it could write easily understandable comments to help us out. It turns out that GPT can but it was still a hassle to generate comments for large files. So we decided to develop a basic web application that automatically integrates with your Github repository, generate comments, create a pull request and send you an email when it is all done. There is definitely a lot more that can be done but we wanted to gain feedback on whether this is a problem that…
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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…
AI · 27d ago · cactuscompute.com
