Show HN: I built an AI trip planner https://ift.tt/djxYgXS

Show HN: I built an AI trip planner https://milotrips.com August 26, 2025 at 02:39AM

Show HN: RAG-Guard: Zero-Trust Document AI https://ift.tt/OShKx1D

Show HN: RAG-Guard: Zero-Trust Document AI Hey HN, I wanted to share something I’ve been working on: *RAG-Guard*, a document AI that’s all about privacy. It’s an experiment in combining Retrieval-Augmented Generation (RAG) with AI-powered question answering, but with a twist — your data stays yours . Here’s the idea: you can upload contracts, research papers, personal notes, or any other documents, and RAG-Guard processes everything locally in your browser. Nothing leaves your device unless you explicitly approve it. ### How It Works - * Zero-Trust by Design*: Every step happens in your browser until you say otherwise. - * Local Document Processing*: Files are parsed entirely on your device. - * Local Embeddings*: We use [all-MiniLM-L6-v2]( https://ift.tt/ybSTdAr... ) via Transformers.js to generate embeddings right in your browser. - * Secure Storage*: Documents and embeddings are stored in your browser’s encrypted IndexedDB. - * Client-Side Search*: Vector similarity search happens locally, so you can find relevant chunks without sending anything to a server. - * Manual Approval*: Before anything is sent to an AI model, you get to review and approve the exact chunks of text. - * AI Calls*: Only the text you approve is sent to the language model (e.g., Ollama). No tracking. No analytics. No “training on your data.” ### Why I Built This I’ve been fascinated by the potential of RAG and AI-powered question answering, but I’ve always been uneasy about the privacy trade-offs. Most tools out there require you to upload sensitive documents to the cloud, where you lose control over what happens to your data. With RAG-Guard, I wanted to see if it was possible to build something useful without compromising privacy. The goal was to create a tool that respects your data and puts you in control. ### Who It’s For If you’re someone who works with sensitive documents — contracts, research, personal notes — and you want the power of AI without the risk of unauthorized access or misuse, this might be for you. ### What’s Next This is still an experiment, and I’d love to hear your thoughts. Is this something you’d use? What features would make it better? You can check it out here: [ https://mrorigo.github.io/rag-guard/ ] Looking forward to your feedback! https://ift.tt/pWt1PTm August 26, 2025 at 03:12AM

Show HN: I built an image-based logical Sudoku Solver https://ift.tt/H4spfNL

Show HN: I built an image-based logical Sudoku Solver https://ift.tt/Fh8SRJi August 26, 2025 at 12:09AM

Show HN: RefForge – A WIP modern, lightweight reading list/reference manager https://ift.tt/IOfBG0A

Show HN: RefForge – A WIP modern, lightweight reading list/reference manager Hi HN! I built RefForge, a lightweight, desktop-first reading list and reference manager (WIP). It's a local-first app built with Next.js + Tauri and stores data in a small SQLite DB. I’m sharing it to get feedback on the UX, feature priorities, and architecture before I invest in more advanced features. This is an experimental project where I am trying to build something from scratch using AI and see how far I can build it without writing a single line of code manually. What does it offer? Manage your reading list and references in a simple, project-based UI Local SQLite storage (no cloud; your data stays on your machine) Add / edit / delete references, tag them, rate priority, group by project Built as a Tauri desktop app with a Next.js/React frontend Why did I build it? Existing reference managers can be heavy or opinionated. I wanted a small, fast, local-first tool focused on reading lists and quick citation exports that I can extend with features I need (PDF attachments, DOI lookup, BibTeX export, lightweight sync). Current features Add / edit / delete references Tagging and project organization Priority and status fields Small, searchable local DB (WIP: full-text search planned) Ready-to-extend codebase (TypeScript + React + Tauri + SQLite) https://ift.tt/YspnOqK August 25, 2025 at 10:09PM

Show HN: A lightweight ML model to predict music emotion - energy, valence, etc. https://ift.tt/vLyhZbR

Show HN: A lightweight ML model to predict music emotion - energy, valence, etc. Spotify has 7 features for each of their music tracks (acousticness, danceability, energy, instrumentalness, liveness, speechiness, valence) which describe the perceptual/emotional content of the song. I wanted to tag my own offline music library with these features so that I could sort my songs into playlists for different occasions (working out, driving, etc.), but unfortunately Spotify doesn't share how they calculate these features. So, I trained my own lightweight neural network to predict these features! https://ift.tt/xtRmKH5 August 25, 2025 at 02:16AM

Show HN: I Built a XSLT Blog Framework https://ift.tt/5cCOSZf

Show HN: I Built a XSLT Blog Framework A few weeks ago a friend sent me grug-brain XSLT (1) which inspired me to redo my personal blog in XSLT. Rather than just build my own blog on it, I wrote it up for others to use and I've published it on GitHub https://ift.tt/v0xqS6L (2) Since others have XSLT on the mind, now seems just as good of a time as any to share it with the world. Evidlo@ did a fine job explaining the "how" xslt works (3) The short version on how to publish using this framework is: 1. Create a new post in HTML wrapped in the XML headers and footers the framework expects. 2. Tag the post so that its unique and the framework can find it on build 3. Add the post to the posts.xml file And that's it. No build system to update menus, no RSS file to update (posts.xml is the rss file). As a reusable framework, there are likely bugs lurking in CSS, but otherwise I'm finding it perfectly usable for my needs. Finally, it'd be a shame if XSLT is removed from the HTML spec (4), I've found it quite eloquent in its simplicity. (1) https://ift.tt/6NO4Vfn (2) https://ift.tt/v0xqS6L (3) https://ift.tt/CxremK6 (4) https://ift.tt/evxj3Ly (Aside - First time caller long time listener to hn, thanks!) https://ift.tt/qH3f6AF August 24, 2025 at 11:08PM

Show HN: Configurable Open Source Audio Spectrum Analyzer https://ift.tt/0aqOkyC

Show HN: Configurable Open Source Audio Spectrum Analyzer Hi, I’ve developed an open-source app for practicing basic skills in digital signal processing and computer graphics using OpenGL. It’s written mainly in C++ for data processing and visualization, with Python used for data input and configuration. This makes it easier to run experiments or adjust settings without recompiling the code, lowering the entry barrier for users unfamiliar with C++. By default, the app captures audio from a microphone in real-time and displays its spectrum on the screen. It’s highly customizable — you can change the number of bars, colors, and the overall color theme. The app runs on both Raspberry Pi and standard Ubuntu desktops. In my Raspberry Pi setup, I use a HiFiBerry DAC+ DSP to analyze music in real-time. The signal comes via optical input (TOSLINK) from a CD player, but you can also connect a microphone for live audio visualization. I’ve written instructions and a tutorial to help you get started — feel free to check it out and give it a try! Demo video (Ubuntu): https://www.youtube.com/watch?v=Sjx05eXpgq4 Demo video (raspberry pi with hifiberry dac+dsp): https://www.youtube.com/watch?v=QA2DYmdZ_Gw Simplified spec: https://sylwekkominek.github.io/SpectrumAnalyzer/ Hope someone finds it useful or fun to play with! https://ift.tt/tKuAPUH August 25, 2025 at 01:25AM