Show HN: Chat with Your Wearables Data https://ift.tt/q09hRk8

Show HN: Chat with Your Wearables Data https://ift.tt/ZCtPB8e August 22, 2025 at 01:52AM

Show HN: Playing Piano with Prime Numbers https://ift.tt/Z2NBC53

Show HN: Playing Piano with Prime Numbers I decided to turn prime numbers into a mini piano and see what kind of music they could make. Inspired by: https://ift.tt/aJrVRSW Github: https://ift.tt/z5ijbJ6 https://ift.tt/ku3K6Ow August 18, 2025 at 08:44PM

Show HN: Tool shows UK properties matching group commute/time preferences https://ift.tt/E6KJSb0

Show HN: Tool shows UK properties matching group commute/time preferences I came up with this idea when I was looking to move to London with a friend. I quickly learned how frustrating it is to trial-and-error housing options for days on end, just to be denied after days of searching due to some grotesque counteroffer. To add to this, finding properties that meet the budgets, commuting preferences and work locations of everyone in a group is a Sisyphean task - it often ends in failure, with somebody exceeding their original budget or somebody dropping out. To solve this I built a tool ( https://closemove.com/ ) that: - lets you enter between 1-6 people’s workplaces, budgets, and maximum commute times - filters public rental listings and only shows the ones that satisfy everyone’s constraints - shows results in either a list or map view No sign-up/validation required at present. Currently UK only, but please let me know if you'd want me to expand this to your city/country. This currently works best in London (with walking, cycling, driving and public transport links connected), and works decently in the rest of the UK (walking, cycling, driving only). This started as a side project and it still needs improvement. I’d appreciate any feedback! https://closemove.com August 21, 2025 at 12:29AM

Show HN: PlutoPrint – Generate Beautiful PDFs and PNGs from HTML with Python https://ift.tt/8nBt5IR

Show HN: PlutoPrint – Generate Beautiful PDFs and PNGs from HTML with Python Hi everyone, I built PlutoPrint because I needed a simple way to generate beautiful PDFs and images directly from HTML with Python. Most of the tools I tried felt heavy, tricky to set up, or produced results that didn’t look great, so I wanted something lightweight, modern, and fast. PlutoPrint is built on top of PlutoBook’s rendering engine, which is designed for paged media, and then wrapped with a Python API that makes it easy to turn HTML or XML into crisp PDFs and PNGs. I’ve used it for things like invoices, reports, tickets, and even snapshots, and it can also integrate with Matplotlib to render charts directly into documents. I’d be glad to hear what you think. If you’ve ever had to wrestle with generating PDFs or images from HTML, I hope this feels like a smoother option. Feedback, ideas, or even just impressions are all very welcome, and I’d love to learn how PlutoPrint could be more useful for you. https://ift.tt/vuI0B4Y August 21, 2025 at 02:07AM

Show HN: Bizcardz.ai – Custom metal business cards https://ift.tt/qboz80s

Show HN: Bizcardz.ai – Custom metal business cards Bizcardz.ai is a website where you design business cards which are converted to KiCad PCB schematics which can be manufactured (using metals) by companies such as Elecrow and PCBWay The site is free. Elecrow charges about $1 per pcb in quantities of 50 and $0.80 in quantities of 100. https://ift.tt/tJwHAoU August 20, 2025 at 11:24PM

Show HN: Nestable.dev – local whiteboard app with nestable canvases, deep links https://ift.tt/SomF0Gk

Show HN: Nestable.dev – local whiteboard app with nestable canvases, deep links https://ift.tt/lOcaFtZ August 20, 2025 at 11:20PM

Show HN: Lemonade: Run LLMs Locally with GPU and NPU Acceleration https://ift.tt/KHtz9q4

Show HN: Lemonade: Run LLMs Locally with GPU and NPU Acceleration Lemonade is an open-source SDK and local LLM server focused on making it easy to run and experiment with large language models (LLMs) on your own PC, with special acceleration paths for NPUs (Ryzen™ AI) and GPUs (Strix Halo and Radeon™). Why? There are three qualities needed in a local LLM serving stack, and none of the market leaders (Ollama, LM Studio, or using llama.cpp by itself) deliver all three: 1. Use the best backend for the user’s hardware, even if it means integrating multiple inference engines (llama.cpp, ONNXRuntime, etc.) or custom builds (e.g., llama.cpp with ROCm betas). 2. Zero friction for both users and developers from onboarding to apps integration to high performance. 3. Commitment to open source principles and collaborating in the community. Lemonade Overview: Simple LLM serving: Lemonade is a drop-in local server that presents an OpenAI-compatible API, so any app or tool that talks to OpenAI’s endpoints will “just work” with Lemonade’s local models. Performance focus: Powered by llama.cpp (Vulkan and ROCm for GPUs) and ONNXRuntime (Ryzen AI for NPUs and iGPUs), Lemonade squeezes the best out of your PC, no extra code or hacks needed. Cross-platform: One-click installer for Windows (with GUI), pip/source install for Linux. Bring your own models: Supports GGUFs and ONNX. Use Gemma, Llama, Qwen, Phi and others out-of-the-box. Easily manage, pull, and swap models. Complete SDK: Python API for LLM generation, and CLI for benchmarking/testing. Open source: Apache 2.0 (core server and SDK), no feature gating, no enterprise “gotchas.” All server/API logic and performance code is fully open; some software the NPU depends on is proprietary, but we strive for as much openness as possible (see our GitHub for details). Active collabs with GGML, Hugging Face, and ROCm/TheRock. Get started: Windows? Download the latest GUI installer from https://ift.tt/XJmyiLf Linux? Install with pip or from source ( https://ift.tt/XJmyiLf ) Docs: https://ift.tt/hB6ZKyQ Discord for banter/support/feedback: https://ift.tt/zw4ZcMh How do you use it? Click on lemonade-server from the start menu Open http://localhost:8000 in your browser for a web ui with chat, settings, and model management. Point any OpenAI-compatible app (chatbots, coding assistants, GUIs, etc.) at http://localhost:8000/api/v1 Use the CLI to run/load/manage models, monitor usage, and tweak settings such as temperature, top-p and top-k. Integrate via the Python API for direct access in your own apps or research. Who is it for? Developers: Integrate LLMs into your apps with standardized APIs and zero device-specific code, using popular tools and frameworks. LLM Enthusiasts, plug-and-play with: Morphik AI (contextual RAG/PDF Q&A) Open WebUI (modern local chat interfaces) Continue.dev (VS Code AI coding copilot) …and many more integrations in progress! Privacy-focused users: No cloud calls, run everything locally, including advanced multi-modal models if your hardware supports it. Why does this matter? Every month, new on-device models (e.g., Qwen3 MOEs and Gemma 3) are getting closer to the capabilities of cloud LLMs. We predict a lot of LLM use will move local for cost reasons alone. Keeping your data and AI workflows on your own hardware is finally practical, fast, and private, no vendor lock-in, no ongoing API fees, and no sending your sensitive info to remote servers. Lemonade lowers friction for running these next-gen models, whether you want to experiment, build, or deploy at the edge. Would love your feedback! Are you running LLMs on AMD hardware? What’s missing, what’s broken, what would you like to see next? Any pain points from Ollama, LM Studio, or others you wish we solved? Share your stories, questions, or rant at us. Links: Download & Docs: https://ift.tt/XJmyiLf GitHub: https://ift.tt/cG6Pfuk Discord: https://ift.tt/zw4ZcMh Thanks HN! https://ift.tt/cG6Pfuk August 20, 2025 at 01:05AM