Show HN: Open-Sourcing My LLM Drag and Drop Website Builder Hey HN - OP here. I wrote some about this project in the following link, and there's a video demo as well: https://ift.tt/Zv1PARS... This has been one of my favorite things I've ever worked on - the way the LLM collaborates with the user to accelerate tedious and hard work, the way you can directly edit the code instead of dealing with a panel of visual editing toggles - I think it has a lot of potential but I don't have time to pursue it anymore so open-sourcing it. The idea for this came out of conversations with a few people who were struggling with frontend development. For technical people, strictly using an LLM to write code can be tedious. To combat this, LLM usage is limited to getting started quickly, improving design, and wiring up frontend state. On the other hand, writing frontend code feels less efficient than just moving things around on a screen. Hence the drag and drop interface that makes it fast to build. Finally, I despise the visual editing toggles on Figma / Bubble / Squarespace / etc. The amount of hunt and peck to simply adjust a font a bit and change some colors or add a shadow is a huge time suck. So I built a way to directly edit the underlying React code when styling - just add or remove tailwind classes. IMO the craziest thing is that all of the code is just stored on the frontend in a config language of sorts. It is inflated at runtime and can be updated without any hot reload. There is no "underlying React code" for the app you're building here - in order to edit the code, I convert the config into React code, then convert back to a config, which triggers updates in the dom. Anyways, I think there's a lot of clever stuff in here, but then again I wrote it. Happy to answer any questions and hope this is interesting/helpful to someone else out there. https://ift.tt/tOx7hLo February 14, 2025 at 11:38PM
Show HN: Dockershrink – AI Assistant to reduce the size of Docker images For the past few months, I've been hacking around a project I call Dockershrink. It automates a simple task: Take a Dockerfile and optimize its code with the goal of reducing the size of the final Docker image. People don't realize that we can apply some very basic techniques to reduce, for eg, a 2GB image down to just ~100MB: - Multistage builds with light-weight base image for final stage - Remove unused dependencies - Optimizations specific to the tech stack And I feel like I've already done this optimization for my personal projects and backend apps at my job(s) a couple of times. The project currently uses GPT-4o (open source so you can run it locally) and only works for Nodejs projects. There are a couple of reasons why I think dockershrink can be better than using just Vanilla LLM or Github Copilot/Cursor: - Image optimization can benefit from a lot of custom prompting, especially when you have insights about specific tech stacks. Describing techniques deeply in the prompt gave better results than simply asking the LLM to "optimize code for bloat reduction". - A RAG approach will be truly beneficial. I plan on giving dockershrink access to up-to-date documentations of Docker, Bash and all programming languages out there. Additionally, it can be given a few suitable chunks of code to enhance the context. - Analysing custom base images: most orgs have their customized base images. Adding context about these can further help Dockershrink make better decisions. Try it out - "brew install dockershrink" Happy to hear your thoughts! https://ift.tt/fZ1o8ME February 14, 2025 at 04:15AM
Show HN: SQL Noir – Learn SQL by solving crimes I built SQL Noir, an interactive detective game that challenges you to solve mysteries using real SQL queries. It’s fully open source, designed to give you a practical and immersive way to learn SQL while engaging with a narrative-driven mystery. https://www.sqlnoir.com February 14, 2025 at 03:19AM
Show HN: Dev SSO IdP, a mock single sign-on provider as a development aide Hi HN! This project grew out of my want for the development of my web UIs to not get hung up on integration with OpenID Connect single sign-on. SSO was only available in our stage and prod environments. Getting this integration laid down and tested fast, without having to jury-rig something in stage, would've been huge. And so I decided to build a solution myself. Hence, Dev SSO IdP. The vision for it is to mock all the features of an OIDC SSO server that would be pertinent to the development of web apps. To try it out: 1) Create a file called `.production.env` and paste in it the following 2 lines to start with: DEVSSOIDP_PERCENT_ENCODED_REDIRECT_URIS=http%3A%2F%2Flocalhost%3A5173 DEVSSOIDP_CLIENT_IDS=my_cool_app 2a) (with Node) Clone the repo with `git clone https://ift.tt/Dxi10Qr `, then overwrite the project's `.production.env` with yours, then in the project's folder run `npm install`, then `npm start` 2b) (with Docker) Run `docker run -p 3000:3000 --rm --env-file .production.env bmcase/devssoidp:1.0.0` You can then see it at (and have your app redirect to) http://localhost:3000/authorize?response_type=code&client_id... You can add or change environment variables in `.production.env` in the likely case that its defaults don't apply to you. The GitHub readme goes into more detail on all of this. They say "be flexible in what you accept and strict in what you output". But Dev SSO IdP is intentionally strict in what it accepts so that I could catch issues faster. It raises an alarm in dev so you don't later get one in prod. This version I am comfortable designating v1.0.0. It has all the features needed for the OIDC code flow. I'd appreciate any advice, and in particular am interested in: * Would this actually be useful in your projects? Is there anything else it would need? * Do you use the OIDC implicit flow? I've never had reason to, and I understand it's regarded as a bad practice. But I worry I may be in a bubble and so I want to know if there's in fact a lot of folks out there who use the implicit flow. Aside, I'm open to work, and would be interested in bringing my full stack skills to your team (or the team of someone you want to do a favor for), in the Austin TX area or remotely. I'm happy to hear from you by email (ben@benswords.com) or LinkedIn ( https://ift.tt/CFtjpOg ). https://ift.tt/yR1tNjk February 14, 2025 at 01:53AM
Show HN: Sort lines semantically using llm-sort This is a small plugin I made for Simon Willison's llm utility. You can do things like: cat names.txt | llm sort -q "Which one of these names is best for a pet seagull?" cat books.txt | llm sort -q "Which book is more related to basic vs. advanced CS topics?" I see a lot of potential marrying LLMs with classic UNIX interfaces. https://ift.tt/qBKiYfD February 11, 2025 at 08:55AM
Show HN: Community Detection on Bluesky We ran the Leuven community detection algorithm on popular users on Bluesky (where the graph has edges determined by Jaccard similarity of a users' followers). We identified 118 communities and based on the names and descriptions of the top 10-20 users had LLMs generate title and descriptions for them. There are communities like "Feline enthusiasts", "Web Professionals", a bunch of NSFW ones and quite many communities are many different flavors of progressive/liberal activists. https://ift.tt/qThzLNX February 12, 2025 at 02:09AM
Show HN: Colada for Claude I actually enjoy Claude.ai's interface and artifacts implementation. I didn't want to lift and shift over to another LLM tool. So, to get past the daily limits, I decided to build a simple Chrome extension which continues conversations using your own Anthropic API key (or using our managed key). In short: - Get past Claude.ai conversation limits - Bring your own Anthropic API key - Optionally use our managed unlimited API key - Preserve conversation context - Bring project knowledge context into your extended convos - Reference web search results anytime by asking "Search the web" Let me know what you think. Open to any and all feedback. https://usecolada.com February 11, 2025 at 10:38PM
Show HN: WhisperCat – An Audio Recorder and Transcription Tool Hi HN, I wanted to share my first open-source project with you all: WhisperCat . WhisperCat is a small desktop application for recording audio and transcribing it using OpenAI's Whisper API. I built this because I needed something simple and reliable for my own transcription workflows, and now I'm hoping it might be useful to others as well. It's still pretty early stage, but it works well for basic audio recording and transcription tasks. What It Does: Lets you record audio with your preferred microphone. Transcribes audio files automatically via Whisper (OpenAI's transcription API). Supports global hotkeys for recording (e.g., CTRL + R or a custom sequence like triple ALT). Runs in the background (system tray) when minimized. Has a basic microphone testing feature to help you pick the right device. Shows desktop notifications for events (e.g., when recording starts or errors happen). Platforms: WhisperCat is available for Windows and Linux , and there’s also an experimental macOS build you can try if you’re feeling adventurous: Experimental macOS Build You can download the latest release here: https://ift.tt/3c1ka2E Feedback is welcome! https://ift.tt/RCcf6pr February 11, 2025 at 01:11AM
Show HN: Arelo – A simple, flexible file watcher for auto-restarting commands arelo is a lightweight, language-agnostic file watcher that automatically runs a command when files change. It requires no configuration files; everything is controlled via simple command-line options. Easy to use: arelo -p '**/*.go' -- go run . Flexible file watching: Supports fsnotify (real-time), polling (for environments like WSL2), and fine-grained control with extended globbing (** and {js,ts,json}). Cross-platform and lightweight: Runs on Windows, macOS, and Linux without extra dependencies. Installation: - go install github.com/makiuchi-d/arelo@latest - Or download a prebuilt binary from GitHub Releases: https://ift.tt/1asD0UM https://ift.tt/awq5iZ3 February 10, 2025 at 09:49PM
Show HN: Curatrs – Scheduled Programming for Podcasts Like many of us, I got tired of scrolling endlessly through podcast apps trying to find the right show for my commute. So I built Curatrs (curatrs.com) - it brings radio-style scheduled programming to podcast discovery. Instead of endless scrolling, you get podcasts programmed for specific times and durations. Currently in early MVP, built with Vite/Supabase, focused on making discovery more intentional and time-based. Would appreciate any feedback, especially from regular podcast listeners https://ift.tt/Ppm0DVL February 10, 2025 at 01:23AM
Show HN: Neovim Plugin for iOS and macOS Development Over two years ago, I began exploring whether it was possible to shift my iOS development to Neovim. It took me over six months to resolve all issues and figure out how to connect everything, creating an environment with all the features required for development. After that, I decided to develop my own plugin to enable others to do the same. Since then, I have been developing apps for iOS and macOS using Neovim, for both my professional work and personal projects with no issues. This change has significantly boosted my productivity, and I no longer have to deal with Xcode's flaws. I can accomplish 95% of my work without needing to open Xcode. Before that, it seemed impossible to develop for Apple platforms outside of Xcode. I'm proud that I was stubborn enough to make it work after all those failures along the way. Neovim is an amazing project <3. https://github.com/wojciech-kulik/xcodebuild.nvim February 9, 2025 at 06:16PM
Show HN: Hyloblog – minimal, Git-based SSG for writing (not theming) Hi HN, We're working on Xr0 [0] and have been building a static-site generator that meets our tastes and needs. The basic emphasis is on simplicity and content rather than customisability and feature-richness. We are imitating Jekyll and Hugo (and other SSGs) in their basic generation paradigm and LaTeX in its separating form from content, but attempting to combine these into a unified, minimal philosophy where you can open a repo and start writing without needing a CLI tool to generate your folder for you. The project is broken into two applications: an SSG you can run locally (or in a GH Action etc.) and a platform for easy hosting that bundles in some basic audience interaction features. Both are available on GitHub: [1] and [2]. We've been working on this somewhat sporadically for the past couple of months, and it is very much a WIP, particularly in the themes it offers, but we're keen to hear thoughts on this. [0]: https://xr0.dev [1]: https://ift.tt/618wZAl [2]: https://ift.tt/FNxkqhI https://hyloblog.com/ February 9, 2025 at 02:53AM
Show HN: Chez Scheme txtar port from Go This is a loose port of https://ift.tt/aQuUEe0 , which concatenates files together and allows for a top-level comment. The txtar format is specifically designed to be easy for humans to read and write by hand. It's perfect for test data. The library itself tries to follow scheme standards by depending on only SRFIs. I hope it's a helpful showcase of a scheme library! I'm also new to writing scheme, and if any experienced scheme devs are out there with feedback, that would be much appreciated. https://ift.tt/yDNlHTB February 8, 2025 at 11:54PM
Show HN: Open-source Hacker News apps We at Emerge Tools (YC W21) recently released open source Hacker News apps for both iOS and Android. The apps use the latest SwiftUI and Compose frameworks and are entirely native. Our goal is to help dogfood our products, but more importantly our team just enjoys reading HN every day and wanted an app to hack on and call our own. :) We are still missing some features but should otherwise be pretty solid. And open to any contributions. iOS: https://ift.tt/TmC1QvY... Android: https://ift.tt/Xt34dDG... https://ift.tt/q8WeDMa February 8, 2025 at 02:11AM
Show HN: A configuration management system for minimal *Nix environments I built this thing to scratch my itch for a simpler alternative to Ansible and similar for basic jobs like setting up a dev env, building containers, and provisioning small fleets of servers. Grateful for feedback on the approach! A couple of friends and I have found it useful for day-to-day automation tasks and I'm wondering if there's enough utility in its ability to target minimal environments like Alpine containers or IoT devices to warrant fleshing out a proper 1.0 release. https://ift.tt/CI6uEtQ February 7, 2025 at 11:16PM
Show HN: Heap Explorer I wrote a little LD_PRELOAD library that makes it easy to inspect and interact with a running program's glibc heap. It's fun to pause processes, free a bunch of their allocations, then resume them. Most of the time, the processes continue as though nothing happened, but sometimes they do interesting things :) https://ift.tt/06CVZmT February 6, 2025 at 10:24AM
Show HN: Kindly RSS, a self-hostable RSS app designed for e-ink devices In the last few weeks I've been working on a RSS application designed to be used in e-ink devices such as Kindle, through the device's web browser. It's a self-hostable app optimized for running on low-end hardware (such as Raspberry Pi, I actually run it on a 3b model). The project is in its early stages of development. It is usable, but you may (and probably will :P) encounter bugs from time to time. I did it for myself (I like to read at night before going to sleep but I don't like to use my phone at that time). I thought people could find it useful so I worked on it a little bit more to publish it. At the moment it can only be run by downloading and compiling the source code or using the docker image (in the repo and the landing page there is a curl that executes the script to run the container, manual instructions can be found in the repo's README). Repo: https://ift.tt/DLun96a Dockerhub: https://ift.tt/RrZkF3N Thank you for reading! I'd love to hear your thoughts and suggestions. https://kindlyrss.app/ February 6, 2025 at 02:16AM
Show HN: CoPlay – Enabling In-Room Xbox Gaming for Children's Hospitals Hey everybody, My name is Brady. I'm the creator of CoPlay. Think of it as an MDM/fleet management for xbox accounts and devices. Pediatric hospitals want to allow their patients to play and connect with friends, family and other patients but they have lacked the tools to facilitate and manage this in the past. A friend and I found this problem while volunteering at our local children's hospital. We are now in 6 pediatric hospitals across the US. Yup, it's a niche. But it's a cool niche. I'm sharing this to get feedback, answer questions, contribute to this amazing community and most importantly, HOPEFULLY FIND SOMEONE THAT CAN GET US CONNECTED TO SOME OF THE HIGHER UPS AT MICROSOFT/XBOX. If you have any connections at all please reach out. We believe there is an opportunity for a beautiful partnership there. Sorry for shouting ;) https://ift.tt/2HGADes February 5, 2025 at 02:08AM
Show HN: Haystack Code Reviewer – Perform code reviews on a canvas Hi HN! We’re building Haystack Code Reviewer, a tool that lays out code diffs for a GitHub pull request on an interactive canvas. Instead of scrolling through diffs line-by-line, you can view all changes in a more connected, visual format – similar to viewing a call graph. We hope this will make it easier and less cognitively taxing to understand how different changes across files work together. For a quick overview, check out our short demo video: https://www.youtube.com/watch?v=QeOz70x0WPE . If you would like to give it a spin, head over to https://ift.tt/RTGSDjI , click the “Review pull request button” in the top toolbar, and load any pull request via URL or pick a pull request from a dropdown. We built Haystack Code Reviewer because we found pull requests difficult to review in a pure textual format — especially when hopping between multiple files or trying to break down complex changes. Oftentimes, pull request authors would have to specifically structure their commits so that code reviews would be easier to tackle, which is a time-consuming and error-prone process. Our goal is to make any pull request easy to understand at a glance, and reduce the effort needed from both reviewers and authors to craft a good code review. Haystack Code Reviewer works on private repositories! We have authentication to ensure that someone cannot open the server for your pull request without having access to that pull request on GitHub. For additional security, we plan to build self-hosting soon. Please contact us if you’re interested in this. Alternatively, a completely local option would be to download desktop Haystack and then navigate to your pull request from there. This is great for trying out the feature without exposing any data on the cloud! In the near future, we plan to: 1. Introduce step-by-step navigation to guide reviewers through each part of the changeset 2. Allow for self-hosting We’d love to hear your thoughts, suggestions, and any feedback on our approach or potential features! https://ift.tt/tSGg4f7 February 4, 2025 at 10:32PM
Show HN: CLI tool that makes your app self-hostable in one command I've been exploring the self-hosting world for some time now, and I wanted to simplify things with one command and avoid having to jump through hoops to make my application self-hostable. I thought many of these could be automated, so I'm automating everything related to self-hosting, one after the other. Please check the roadmap for what I have in mind. I'm open to anyone who wants to contribute and give feedback. https://kagehq.com/ February 4, 2025 at 11:34PM
Show HN: Mandarin Word Segmenter with Translation I've built mandoBot, a web app that segments and translates Mandarin Chinese text. This is a Django API (using Django-Ninja and PostgreSQL) and a NextJS front-end (with Typescript and Chakra). For a sample of what this app does, head to https://ift.tt/wdZ0Ex6 . This is my presentation of the first chapter of a classic story from the Republican era of Chinese fiction, Diary of a Madman by Lu Xun. Other chapters are located in the "Reading Room" section of the app. This app exists because reading Mandarin is very hard for learners (like me), since Mandarin text does not separate words using spaces in the same way Western languages do. But extensive reading is the most effective way to learn vocabulary and grammar. Thus, learning Mandarin by reading requires first memorizing hundreds or thousands of words, before you can even know where one word ends and the next word begins. I'm solving this problem by allowing users to input Mandarin text, which is then computationally segmented and machine translated by my server, which also adds dictionary definitions for each word and character. The hard part is the segmentation: it turns out that "Chinese Word Segmentation"[0] is the central problem in Chinese Natural Language Processing; no current solutions reach 100% accuracy, whether they're from Stanford[1], Academia Sinica[2], or Tsing Hua University[3]. This includes every LLM currently available. I could talk about this for hours, but the bottom line is that this app is a way to develop my full-stack skills; the backend should be fast, accurate, secure, well-tested, and well-documented, and the front-end should be pretty, secure, well-tested, responsive, and accessible. I am the sole developer, and I'm open to any comments and suggestions: roberto.loja+hn@gmail.com Thanks HN! [0] https://ift.tt/60OTK8Q [1] https://ift.tt/WJSpGEL [2] https://ift.tt/cjzCVm4 [3] https://ift.tt/2crU8ge https://ift.tt/4CXU1kP February 4, 2025 at 11:26PM
Show HN: I Built a Platform to Buy and Sell GitHub Repositories Hey HN, I built a platform that allows developers to buy and sell GitHub repositories using private forking. The idea is to help indie developers, open-source maintainers, and teams monetize their work while ensuring buyers get fully functional projects with minimal hassle. Many developers create great projects but lack the time or resources to maintain them. Instead of letting them fade away, why not sell them to someone who wants to continue the work? Here is how it works: - Sellers list theis GitHub repos in the platform - Buyers purchase repos - Buyers automatically added as collaborators and can fork the repo Check it out here: https://gittrader.com https://ift.tt/yEQcLnz February 3, 2025 at 06:07AM
Show HN: Chrome extension to run DeepSeek, LLMs and Whisper locally in browser Hi all, I open sourced my toy project that runs Generative AI models LOCALLY in the side panel of a Chrome extension. The Chrome extension uses Transformers.js to run models in browser under the hood. I've integrated and tested these models so far. \1. LLM: Llama 3, Phi 3.5, Qwen 2.5, SmolLM2 \2. Reasoning: DeepSeek R1 \3. Multimodal LLM: Janus \4. Speech-to-Text: Whisper On an M1 MacBook, DeepSeek R1 1.5B runs at ~30 tokens/sec If you're interested in, you can download the extension from chrome web store or clone my github repository. \1. chrome web store: https://ift.tt/TYnW9vw... \2. github: https://ift.tt/rCbGxUg \3. demo: https://www.youtube.com/watch?v=MSCDdFG5Lls It's my first react project. Feedback is always welcome! https://ift.tt/rCbGxUg February 2, 2025 at 11:19PM
Show HN: Groundhog AI Spring API For anyone building weather-related AI apps, I am releasing an exciting iteration on last year’s model. My Groundhog API is trained on 130 years of data and makes use of 82 separate data sources. Similar to DeepSeek, it is completely open source and free to use. The primary use case is to make inferences about whether spring will come early or not, using a Mixture of Exports (MoE) approach, but surely others can be found if you are creative. Other use cases: - All predicting groundhogs - Where they all live - Whether they are “real” groundhogs or imposters Excited to see what people do with it! https://ift.tt/xtD0YE9 February 2, 2025 at 10:59PM
Show HN: ESP32 RC Cars This is a projected I started that blends both the fun of playing a split screen multiplayer driving game and controlling real rc cars. The cars can also be controlled via bluetooth gamepads and is meant to be easily hackable. https://ift.tt/cfNoauW February 2, 2025 at 12:21AM
Show HN: I hacked LLMs to work like scikit-learn Working with LLMs in existing pipelines can often be bloated, complex, and slow. That's why I created FlashLearn , a streamlined library that mirrors the user experience of scikit-learn. It follows a pipeline-like structure allowing you to "fit" (learn) skills from sample data or instructions, and "predict" (apply) these skills to new data, returning structured results. High-Level Concept Flow: Your Data --> Load Skill / Learn Skill --> Create Tasks --> Run Tasks --> Structured Results --> Downstream Steps Installation: pip install flashlearn Learning a New "Skill" from Sample Data Just like a fit/predict pattern in scikit-learn, you can quickly "learn" a custom skill from minimal (or no!) data. Here's an example where we create a skill to evaluate the likelihood of purchasing a product based on user comments: from flashlearn.skills.learn_skill import LearnSkill from flashlearn.client import OpenAI # Instantiate your pipeline "estimator" or "transformer", similar to a scikit-learn model learner = LearnSkill(model_name="gpt-4o-mini", client=OpenAI()) data = [ {"comment_text": "I love this product, it's everything I wanted!"}, {"comment_text": "Not impressed... wouldn't consider buying this."}, # ... ] # Provide instructions and sample data for the new skill skill = learner.learn_skill( data, task=( "Evaluate how likely the user is to buy my product based on the sentiment in their comment, " "return an integer 1-100 on key 'likely_to_buy', " "and a short explanation on key 'reason'." ), ) # Save skill to use in pipelines skill.save("evaluate_buy_comments_skill.json") Input Is a List of Dictionaries Simply wrap each record into a dictionary, much like feature dictionaries in typical ML workflows: user_inputs = [ {"comment_text": "I love this product, it's everything I wanted!"}, {"comment_text": "Not impressed... wouldn't consider buying this."}, # ... ] Run in 3 Lines of Code - Concurrency Built-in up to 1000 calls/min # Suppose we previously saved a learned skill to "evaluate_buy_comments_skill.json". skill = GeneralSkill.load_skill("evaluate_buy_comments_skill.json") tasks = skill.create_tasks(user_inputs) results = skill.run_tasks_in_parallel(tasks) print(results) Get Structured Results Here's an example of structured outputs mapped to indexes of your original list: { "0": { "likely_to_buy": 90, "reason": "Comment shows strong enthusiasm and positive sentiment." }, "1": { "likely_to_buy": 25, "reason": "Expressed disappointment and reluctance to purchase." } } Pass on to the Next Steps You can use each record’s output for downstream tasks such as storing results in a database or filtering high-likelihood leads: # Suppose 'flash_results' is the dictionary with structured LLM outputs for idx, result in flash_results.items(): desired_score = result["likely_to_buy"] reason_text = result["reason"] # Now do something with the score and reason, e.g., store in DB or pass to next step print(f"Comment #{idx} => Score: {desired_score}, Reason: {reason_text}") https://ift.tt/KnsYruq February 1, 2025 at 10:09PM
Show HN: I re-designed interface for HN Any suggestions are appreciated, stack utilizes Gluestack UI ,Expo, React Native, and Cloudflare Pages. There is a known bug via touch scroll ability on Android, external keyboard's spacebar or mouse works correctly though, currently. If you know about a solution, let me know. Please note, this is just a prototype, it still has a lot of features to be included. I'd like to learn more about how people use HN and how Hacked could help, where other HN clients failed. https://ift.tt/c6RvFrG February 1, 2025 at 10:41PM
Show HN: Simple to build MCP servers that easily connect with custom LLM calls Hi! After learning about MCP, I'm really excited about the future of provider-agnostic, re-usable tooling. Unfortunately I've found that while it's easy to implement an MCP server for use with tools that support it (such as Claude Desktop), it's not as easy to implement your own support (such as integrating an MCP server into your own LLM application). We implemented a thin MCP wrapper that easily integrates with Mirascope calls so that you can hook up an MCP server and client super easily to any supported LLM provider. Excited to see what people build with this! https://ift.tt/c5qC27Y February 1, 2025 at 06:20AM
Show HN: Ros2_utils_tool, a powerful GUI toolset for ROS2-based utilities Hi Hackernews, over the past few weeks, I've been tirelessly working on a GUI toolset for all sorts of ROS2-based utilites to simplify my tasks with ROS at work. Now I want to present to you the ros2_utils_tool. This tool can do many ROS2-based utilites, for example editing a ROS bag file to remove, rename or crop topics, extracting a video or image sequence out of a ROS bag, creating dummy bag files or just publishing a video as a ROS topic. While being developed to be as simple and lightweight as possible, the toolset supports many advanced options, for example different video and image formats, custom fps values, switching colorspaces and more. I've also heavily optimized the tool to support multithreading or in some cases even hardware-acceleration to run as fast as possible. The tool offers full graphical user interface support for all features, while I've also added additional command line interface support for most of them. As of now, the ros2_utils_tool supports ROS2 humble and jazzy. The application is still in an alpha phase, which means I want to add many more features in the future, for example GUI-based ROS bag merging or republishing of topics under different names, or some more advanced options such as selecting messages for video or image generation. The ros2_utils_tool requires an installed ROS2 distribution, as well as Qt6 or Qt5 for the user interface, the cv_bridge for transforming images to ROS and vice versa, and finally catch2_ROS for unit testing. You can install all dependencies (except for the ROS2 distribution itself) with the following command: sudo apt install libopencv-dev ros-humble-cv-bridge qt6-base-dev ros-humble-catch-ros2 For ROS2 Jazzy: sudo apt install libopencv-dev ros-jazzy-cv-bridge qt6-base-dev ros-jazzy-catch- Install the UI with the following steps: cd path/to/your/workspace/src git clone https://ift.tt/yq65k7R cd path/to/your/workspace/ colcon build Then run it with the following commands: source install/setup.bash ros2 run ros2_utils_tool tool_ui The ros2_utils_tool uses the EUPLv1.2 as license. More information, for example regarding the command line interface tools are shown under [0]. [0] https://ift.tt/NhnglxR https://ift.tt/NhnglxR January 31, 2025 at 09:13PM
Show HN: Audiocube – A 3D DAW for Spatial Audio I’ve recently released my solo project Audiocube I wanted to make a 3D DAW, where spatial audio, physics, and virtual acoustics are all directly integrated into the engine. This makes it easy to create music in 3D, and experiment with new techniques which aren’t possible in traditional DAWs and plugins. I’d love to get any feedback on this software (Mac/Windows) to make it better. You can download it for free through the website. Thanks, Noah https://ift.tt/JTRzLKb January 30, 2025 at 06:42PM
Show HN: ENT Stack – Full-Stack TypeScript Starter Hey HN, I wanted a simple and batteries-included way to start my full-stack TypeScript projects so I built ENT Stack - a monorepo with Express, Next.js and tRPC. It covers the basics - code sharing (between backend and frontend), auth, DB, validation, state management, i18n, logging, mailing, testing, CI/CD and infra. Its focus is to be minimal, flexible, and scalable. It uses proven libraries (Drizzle, Playwright, TanStack Query, Tailwind, Zod, Zustand ...) with custom authentication, authorization and i18n solutions that are easy to modify or replace. The project also contains an NPM package, so new projects can be created with one command: - pnpm create ent-stack@latest https://ift.tt/sdrNO1v January 30, 2025 at 10:39PM
Show HN: Vogent – Better Building Blocks for Voice AI Hi HN! Excited to share some stuff we’ve been building. We spent the last year building voice agents to automate individual call tasks for companies with large call centers. The STT-LLM-TTS-VAD cycle is mostly solved at this point, but the last-mile problem for making these agents performant was frustrating. We ended up building a lot of band-aids, and we decided to put them together into their own end-to-end product. Vogent is a platform for building and serving Voice AI agents, with a focus on providing higher-level building blocks that make it easy to get a voice agent working quickly. You can check out the docs at https://docs.vogent.ai It supports the typical design process of a voice agent (choosing/prompting a model, selecting a voice, and hosting on a phone number or accessing via API), but it has additional pieces that make voice agents performant quickly, like (among other things): - A drag-and-drop agent builder Under the hood, this involves feeding the model only context relevant to the goals of the current node (e.g., asking a particular question and probing conversationally for the answer), while giving it the ability to call a function with the outcome once the goal is achieved to transition to the appropriate next node. This makes it easy to build voice agents that need the structure of a multi-step talk track with the flexibility of accomplishing each task conversationally. - Voices that are trained to spell Off-the-shelf voices (e.g. Eleven, Cartesia) sound much more artificial when they spell. It might sound like an edge case, but this killed almost every engagement we had. We ended up recruiting Upworkers with different accents, having them spell a few thousand phrases, and training our own voices by modifying open-source architectures. Choose “Carlos” for a spelling-optimized voice right now; we’re adding a lot more soon. - An IVR detection model This detector uses the audio stream to predict whether a line came from an IVR or a human, and switches between different LLMs based on the result (so you can have independent IVR navigation and conversational models). - Model versioning and counterfactuals Vogent enables model versioning and testing against past dials within the product. Any feedback would be appreciated. Please also feel free to join our Discord: https://ift.tt/6ufNhKc https://www.vogent.ai/ January 29, 2025 at 10:09PM
Show HN: Mcp-Agent – Build effective agents with Model Context Protocol Hey HN, I spent my xmas break building an agent framework called mcp-agent [1]( https://ift.tt/cs9ThJO ) for Model Context Protocol [2]. It makes it easy to build AI apps with MCP servers, and implements every pattern from the popular Building Effective Agents blog [3] as well as OpenAI’s Swarm [4]. I’m sharing it early to get community feedback on where to take it from here, and to ask for contributions. For those who aren’t familiar with MCP, I think of it as a standardized interface to let AI communicate with software via tool calls, resources and prompts. mcp-agent provides a higher level interface to build apps with MCP. It handles the connection management of MCP servers so you don’t have to. It also implements the Building Effective Agents patterns: - Augmented LLM (an LLM with access to one or more MCP servers) - Router, Orchestrator-Worker, Evaluator-Optimizer, and more - Swarm The key design principles are composability and reusability – every pattern is an AugmentedLLM itself, so you can chain them into more complex workflows. Some background: I worked on LSP [5] and language servers at Microsoft, and saw firsthand how standards and protocols can revolutionize developer workflows. Before LSP every IDE had its own esoteric ways of providing language services. LSP changed all that, and arguably made every language server better, since they can focus on improving a single implementation for all clients. I think AI development is in a similar pre-LSP space right now. There are tons of frameworks [6], every model provider has its own way of handling messages, tool calls, streaming, etc. I really think we need a protocol to standardize these patterns. Pretty soon every service is going to expose an MCP interface, and mcp-agent is about letting developers orchestrate these services into applications (i.e. build “MCP apps”). This can cover any use of an AI model that needs to interact with the world around it: - RAG pipelines and Q&A chatbots - Process automation via AI workflows/async tasks - Multi-agent orchestration, with human in the loop The repo contains examples [7] to build RAG agents, streamlit apps and more. There’s a lot left to build, like streaming support, server auth and tighter integration with MCP clients. But I wanted to share early in the hopes that you can guide me: - If you find this useful, please let me know. If it’s useful to you, I will dedicate all my time to improving it. - I really welcome contributions. If you want to collaborate, please reach out on github to help take this forward. I want to help standardize AI development, so developers a few years from now can look back with horror at the pre-MCP days. [1] - https://ift.tt/cs9ThJO [2] - https://ift.tt/jsSD7tx [3] - https://ift.tt/E9jT163 [4] - https://ift.tt/gYM9O85 [5] - https://ift.tt/CgxjIen [6] - https://xkcd.com/927/ (I understand the irony) [7] - https://ift.tt/IKfH97k https://ift.tt/cs9ThJO January 29, 2025 at 09:56PM
Show HN: I built a SaaS thanks to my wife I’m Michał, and I’d like to share with you the journey I went through with my wife and how, thanks to her, we built our first SaaS, PDFBolt ( https://pdfbolt.com ). I’ve been a developer for over 10 years. In 2020, I decided to build a side project to learn all aspects of app development—deployment, authentication, payments, frontend, landing pages, etc. While looking for project ideas, I came across the Indie Hackers community, where I found a simple HTML-to-PDF API project. The creator mentioned a lot of interest in it and that it was generating revenue. I thought I’d build something similar myself and learn a lot in the process. But it wasn’t easy at all. After working from 9 to 5, it’s hard to spend another few hours in front of the computer in the evening. What about other responsibilities? Groceries, cooking, cleaning, hobbies, spending time with my wife? Still, I tried, very slowly. I had breaks lasting several months, and at one point, due to mental health issues, I practically stopped working on the project altogether. My wife worked as a physiotherapist but, due to difficulties in her job, decided to switch to IT with my help, starting as a manual tester. She did it very quickly (maybe six months) and immediately found a job. In mid-2024, she started asking about my old project and insisted that we finish it. Thanks to her enthusiasm, we managed to do it very quickly. I focused on the backend, and she, in addition to testing, handled the entire frontend and landing page. Around the same time, we also adopted a dog from a shelter, which added a lot of positive energy to our lives and helped us stay motivated. In early January 2025, we officially launched the project. It’s been a long journey, and we don’t have any customers yet—we don’t even know if we will, as we have no idea about marketing :) But we’ve learned a lot and are already happy with the journey itself. As for the technical aspects, the app uses: Backend: Kotlin, Spring Boot, Postgres, Redis Frontend: React, Next.js, Docusaurus Auth: Firebase Hosting: Render (the app is Dockerized) Cloudflare R2 for file storage PDFs are generated using Chromium via Playwright. If you have any questions about the tech stack or anything else, feel free to ask! I’ll be happy to answer. Any feedback or criticism will be greatly appreciated. Thank you! :) https://pdfbolt.com/ January 30, 2025 at 12:54AM
Show HN: Share your path to resolve issues with Savvy's Chrome Extension Track and Share links used to resolve issues from your browser history with Savvy's Chrome extension Try it out from the Chrome Web Store: https://ift.tt/Dp4vVPx... Use Cases: - Share your debug path or highlight links crucial to solving a bug. - Attach a log of your actions to any issue or postmortem. Privacy Savvy's Chrome extension does not store any of your browsing history. It reads your browsing history to surface relevant links (all done client side). Selected links can be copied to your clipboard or sent to Savvy's CLI. You can choose to store workflows generated from Savvy's CLI on Savvy or export data locally on your machine. Drop a comment if you have any questions or suggestions. https://ift.tt/KTCoLjY January 28, 2025 at 10:51PM
Show HN: Ollama server discovery tool (finds public LLM instances) I built a network discovery tool in Rust that helps identify public Ollama LLM servers. It scans IP ranges to find Ollama instances and catalogs their available models. Important note: This is intended for educational purposes and authorized security testing only. https://ift.tt/qLyaUNV January 28, 2025 at 02:40AM
Show HN: A new native app for 20 year old OS X A few of us here are probably familiar with the original Xbox modding scene and the iconic xbins FTP server. Recently, I came across an amazing tool called Pandora by Team Resurgent [0], which got me thinking about how incredible something like this would have been 20 years ago. Just to clarify, I had no involvement in creating Pandora—I’m just inspired by their work. For those who aren’t familiar, getting access to xbins involves a rather dated process. You need to connect to a channel on an EFnet IRC server, message a bot for temporary credentials, then plug those credentials into your FTP client to access xbins. Pandora (and my app) simplifies this entire workflow into a single click. Inspired by Pandora, I decided to build my own take on what this dream tool might have looked like back in the day. I wrote a native Mac app on original hardware—an Intel iMac (20-inch, 2007)—running a 20-year-old operating system, Mac OS X 10.4 Tiger. This was my first foray into native Mac app development, though I’ve done some iOS development in the past. The result is Uppercut [1], and the source is available on GitHub [2]. For the development process, I used Claude to help with a lot of the coding, especially since I was constrained to Xcode 2.5 and the pre-“Objective-C 2.0” features available at the time. I had to be very specific in prompting Claude to avoid newer features that didn’t exist back then. Since the majority of Objective-C code out there comes from the era of iOS development (which relied heavily on Objective-C 2.0 until the arrival of Swift), this was a unique and challenging exercise in retro development. [0] - https://ift.tt/6jb2YqQ [1] - https://ift.tt/N6nEO35 [2] - https://ift.tt/PLpYaJs https://ift.tt/N6nEO35 January 24, 2025 at 06:16AM
Show HN: Actionate – GitHub Actions for JetBrains IDEs I’m excited to share Actionate, a passion project my team and I have been building to reimagine GitHub Actions within JetBrains IDEs. We’ve spent over a decade working in innovation labs at major tech companies, but our true passion lies in crafting tools that we genuinely want to use every day. With Actionate, we’re not just integrating CI/CD into JetBrains; we’re leveraging the powerful building blocks provided by JetBrains and GitHub Actions to create new, transformative functionality. Our MVP (Minimum Viable Product) focuses on the most essential features we find critical for a smoother workflow, but the goal is to push beyond typical CI/CD boundaries and empower developers in ways that haven’t been possible before. If this vision resonates with you, we’d love for you to check out Actionate and let us know what you think—good or bad. We thrive on community input, and your feedback will shape our roadmap as we continue expanding on what’s possible inside the IDE. Thanks for reading, and I hope Actionate helps you take your GitHub Actions workflow to the next level! https://ift.tt/ICk7vrM January 26, 2025 at 01:53AM
Show HN: Freelens OSS Kubernetes IDE Hello everyone, disappointed that Open Lens has become closed source, I and other enthusiasts are trying to continue its open source project with Freelens. We hope this will help others who like us used Open Lens as a graphical IDE to work with Kubernetes, continuing to give the community the opportunity to develop it by directly contributing to its realization as an open source project. What do you think? Any feedback or contribution is welcome! Thanks! https://ift.tt/YkubeTh January 26, 2025 at 12:50AM
Show HN: Magenta.nvim – AI coding plugin for Neovim focused on tool use I've been developing this on and off for a few weeks. There are a few videos on the README page showing demos of the plugin. I just shipped an update today, which adds: - inline editing with forced tool use - better pinned context management - prompt caching for anthropic - port to node (from bun) Check it out! https://ift.tt/Jg4Y6vi January 21, 2025 at 08:37AM
Show HN: Snap Scope – Visualize Lens Focal Length Distribution from EXIF Data Hey HN, I built this tool because I wanted to understand which focal lengths I actually use when taking photos. It's a web app that analyzes EXIF data to visualize focal length distribution patterns. While it's admittedly niche (focused specifically on photography), I think it could be useful for photographers trying to understand their lens usage patterns or making decisions about lens purchases. Features: Client-side EXIF data processing (no server uploads/tracking) / Handles thousands of photos at once / Clean visualization with shareable summaries This tool supports most RAW formats, but you might occasionally encounter files where EXIF extraction fails. In such cases, converting to more common formats like JPEG usually resolves the issue. Try it out: https://ift.tt/D0TEPYc Source: https://ift.tt/3v6j4LV https://ift.tt/D0TEPYc January 24, 2025 at 07:48PM
Show HN: Helicone (YC W23) – OSS LLM Observability and Development Platform Hey HN, we're Justin and Cole, the founders of Helicone ( https://helicone.ai ). Helicone is an open-source platform that helps teams build better LLM applications through a complete development lifecycle of logging, evaluation, experimentation, and release. You can try our free demo by signing up ( https://ift.tt/hJHnzId ) or self-deploy with our new fully open-source helm chart ( https://ift.tt/rWDKy13 ). When we first launched 22 months ago, we focused on providing visibility into LLM applications. With just a single line of code, teams could trace requests and responses, track token usage, and debug production issues. That simple integration has since processed over 2.1B requests and 2.6T tokens, working with teams ranging from startups to Fortune 500 companies. However, as we scaled and our customers matured, it became clear that logging alone wasn’t enough to manage production-grade applications. Teams like Cursor and V0 have shown what peak AI application performance looks like and it's our goal to help teams achieve that quality. From speaking with users, we realized our platform was missing the necessary tools to create an iterative improvement loop - prompt management, evaluations, and experimentation. Helicone V1: Log → Review → Release (Hope it works) From talking with our users, we noticed a pattern: while many successfully launch their MVP quickly, the teams that achieve peak performance take a systematic approach to improvement. They identify inconsistent behaviors through evaluation, experiment methodically with prompts, and measure the impact of each change. This observation shaped our new workflow: Helicone V2: Log → Evaluate → Experiment → Review → Release It begins with comprehensive logging, capturing the entire context of an LLM application. Not just prompts and responses, but variables, chain steps, embeddings, tool calls, and vector DB interactions ( https://ift.tt/CGz9hVs ). Yet even with detailed traces, probabilistic systems are notoriously hard to debug at scale. So, we released evaluators (either via LLM-as-judge or custom Python evaluators leveraging the CodeSandbox SDK - https://ift.tt/pgYh2yS ). From there, our users were able to more easily monitor performance and investigate what went wrong. Did the embedding search return poor results? Did a tool call fail? Did the prompt mishandle an edge case? But teams would still edit prompts in a playground, run a few test cases, and deploy based on intuition. This lacked the systematic testing we’re used to in traditional software development. That’s why we built experiments (similar to Anthropic's workbench but model-agnostic) ( https://ift.tt/O03AhX8 ). For instance, when a prompt generates occasional rude support responses, you can test prompt variations against historical conversations. Each variant runs through your production evaluators, measuring real improvement before deployment. Once deployed, the cycle begins again. We recognize that Helicone can’t solve all of the problems you might face when building an LLM application, but we hope that we can help you bring a better product to your customers through our new workflow. If you're curious how our infrastructure handled our growth: Our initial architecture struggled - synchronous log processing overwhelmed our database and query times went from milliseconds to minutes. We've completely rebuilt our infrastructure with two key changes: 1) using Kafka to decouple log ingestion from processing, and 2) splitting storage by access pattern across S3, Kafka, and ClickHouse. This was a long journey but resulted in zero data loss and fast query times even at billions of records. You can read about that here: https://ift.tt/lq0wzCo... We'd love your feedback and questions - join us in this HN thread or on Discord ( https://ift.tt/7McyUL3 ). If you're interested in contributing to what we build next, check out our GitHub. https://ift.tt/ROBqTeM January 23, 2025 at 11:28PM
Show HN: Mixlist built a web app that uses k-means clustering on artist genres (one or multiple) to automatically organize Spotify liked songs into playlists. clean UI. you might have to click refresh playlists couple of times to get what you want. comments are appreciated. thanks! https://ift.tt/X3AaOMq January 23, 2025 at 11:11PM
Show HN: Turn Figma into working apps without coding (Designer –> Production) Hey HN! Last summer I was struggling to get my Figma designs shipped - stuck waiting for dev bandwidth and trying to hand off every iteration. Got really frustrated and decided to do something about it. Today we're launching a native integration between Builder.io and Lovable that lets designers directly convert Figma designs into production-ready apps. No code, no BS, just a working app you can iterate on. How it works: - Design in Figma (supports Auto-Layout) - Export through Builder.io's plugin (2 modes: quick or pixel-perfect) - Opens in Lovable where you can add functionality via prompts - Connect Supabase for backend/auth/db if needed - One click deploy to cloudflare We've been testing this with early users and seeing designers ship entire apps solo in hours instead of weeks. One designer built and deployed a complete employee directory app from their Figma design in an afternoon. Try it out: https://ift.tt/Tq3ziaN... Docs: https://ift.tt/PtAWn6O Would love feedback from fellow designers and builders. Especially interested in hearing from others who've dealt with design-dev handoff pains, and what parts of your workflow can this help with? Built by builder.io and Lovable.dev teams. We're around to answer questions! https://ift.tt/PtAWn6O January 22, 2025 at 10:44PM
Show HN: RAG Web UI – Possibly the Most Beginner-Friendly RAG Knowledge Base RAG Web UI is designed to be the most straightforward way to build your own knowledge-based Q&A system. While other RAG (Retrieval-Augmented Generation) projects might be complex, we focus on making it super easy to understand and use. Why It's The Most Beginner-Friendly: Simple Document Management - Just upload your documents (PDF, DOCX, Markdown, Text) - System handles all the complex processing automatically - No need to worry about document chunking or vectorization - Documents update automatically in the background Easy-to-Use Chat Interface - Ask questions in plain language - Get accurate answers from your documents - See exactly which parts of your documents the answers come from - Natural back-and-forth conversations just like chatting Professional Architecture Made Simple - Clean, modern web interface - Rock-solid backend design - Built for reliability with distributed storage - High-performance search using ChromaDB/Qdrant - Easy to switch databases without touching code Get Started in Minutes: 1. Clone the repo 2. Follow our beginner-friendly setup guide 3. Upload your documents 4. Start chatting with your knowledge base Whether you're building a company knowledge base or a personal Q&A system, you don't need to be a RAG expert - we handle the complexity for you. Looking forward to your feedback on how we can make it even more beginner-friendly! https://ift.tt/sCfgXB5 January 22, 2025 at 09:35PM
Show HN: Stratoshark, a sibling application to Wireshark Hi all, I'm excited to announce Stratoshark, a sibling application to Wireshark that lets you capture and analyze process activity (system calls) and log messages in the same way that Wireshark lets you capture and analyze network packets. If you would like to try it out you can download installers for Windows and macOS and source code for all platforms at https://stratoshark.org. AMA: I'm the goofball whose name is at the top of the "About" box in both applications, and I'll be happy to answer any questions you might have. https://ift.tt/tWSegEJ January 22, 2025 at 08:55PM
Show HN: Hold yourself accountable for gym visits with a $10 stake I don't go to the gym as much as I should or want to. To give myself some financial motivation I made this website. First you set a goal for how many days you'll hit the gym. To prove you're at the gym, you will verify each visit by pressing a button on your phone (with location sharing on). You stake $10 as motivation and if you hit your target, you get the money back. If you fail, your $10 goes to the "Save The Children" charity with a donation receipt emailed to you. Obviously you could visit the gym and then just go home without working out - but getting to the gym is half the battle! It's simple to use with a Google sign-in and hopefully it will encourage some people to workout (or give to charity)! https://ift.tt/HovweB2 January 21, 2025 at 10:14PM
Show HN: Crawlspace – A centralized web crawling platform built on Cloudflare Crawlspace is a centralized web crawling platform that benefits crawler developers AND website owners. Developers can affordably crawl tens of millions of pages per month, scrape with LLMs, and save data in attached storage. Website owners are shielded by a platform-wide TTL cache that absorbs redundant bot traffic. AI bots are running rampant on the open web. Many recent HN stories[1][2][3][4] describe how web crawlers have run amok and hammer websites with DDoS-like traffic. They often do this with blatant disregard of website owners' wishes (e.g. ignoring robots.txt, 429s, Retry-After headers, etc) because they face no repercussions for deploying poorly-behaved crawlers (and are not incentivized to improve them). The knee-jerk reaction to fix this problem is to give more tools to website owners. Maintaining denylists of IP addresses and user agents, implementing honeypots and tarpits, etc are tactics that website owners use to combat the problem. However, this ends up resulting in and endless arms race between web crawlers and website owners, as they each try to employ new mechanisms of one-upping each other. Crawlspace takes a different approach _by providing a convenient and affordable platform to web crawler developers_. By funneling web crawling traffic through a centralized platform, we can control neat things like making crawlers well-behaved by default, implementing proper caching, and more — all the tedium that that developers don't want to (and therefore, don't) do themselves. Music streaming services like Spotify used convenience and affordability to curb music piracy; we're following the same playbook to curb rampant bot traffic on the internet. In about 50 lines of code, you can deploy a performant and polite web crawler on Cloudflare's network. Every crawler gets its own queue, SQLite database, vector database, and S3-compatible bucket, which allows you to query your crawl as it's crawling with either SQL statements or a RAG chat interface. We've stitched together 10+ Cloudflare products including Queues, Durable Objects, Browser Rendering, Workers AI, D1, R2, and Vectorize. Please let us know what you think! Happy to answer any questions. [1] https://ift.tt/ltYARBg [2] https://ift.tt/YQrXSts [3] https://ift.tt/QOuo5Pd [4] https://ift.tt/PJErKvR https://crawlspace.dev January 21, 2025 at 10:11PM
Show HN: Searchlight – Open-source Postgres client for macOS Hi HN, Over the past year, I’ve been building a native MacOS Postgres client for my personal use. While there are plenty of existing clients, I built this because: - No open-source Postgres client matched the smooth UX of tools like Sequel Pro/SequelAce (for MySQL). - I missed the satisfaction of long-term product ownership and iteration—recent work has me jumping between projects. - I’ve been using Postgres more lately and wanted to get hands-on to deepen my knowledge. I also wanted a playground to experiment with client features that would help me on day-to-day. Some I have implemented already: - Hover over a foreign key column to see the linked record in a popover. - Autocomplete lookup for foreign key records when inserting/editing rows. - High-level stats pop-up when hovering over a column. - Contextual “sugar” features (e.g., UUID fields include a button to generate a UUID while editing). - On update/insert failures, it tries to highlight the issue on the problematic column, vs some generic error alert. It’s still very bare-bones and I still use it alongside other tools for features I haven’t implemented (management features for tables/schemas/user), but I’m already using as my main client for 90% of what I work on. I’m sharing here to get early feedback. Mostly trying to determine if more people find value in this project if I keep developing it. ps.: I’m using my personal Apple developer account so I can’t notarize the app with Apple. If you try to install from the GitHub releases page MacOS will warn that it can’t verify the developer identity, so you will need to approve the install on Settings > Privacy, or build from source. https://ift.tt/E6rJHYO January 20, 2025 at 09:50PM
Show HN: TikTok Video Downloader We just built a small tool to download all your tiktok videos by just providing your tiktok username. You can try it out in https://ift.tt/8syq5wX Even though it's reinstated, with all the ban and no-ban conversation it's better to download all your videos and back it up. This is primarily aimed at creators who have a large number of videos. Please feel free to drop any feedback! https://ift.tt/aPufgm6 January 20, 2025 at 12:05AM
Show HN: We built an Anime Recommendation and streaming Website Me and my friend built an unique content based Recommendation System, where user can just select Anime or write synopsis and our system will find the most similar anime available. We used Qdrant Vector Database for the Recommendations. Other Features includes, Streaming, Custom watchlist creation and sharing of watchlists. We update our Database regularly and plan to introduce new features in future. https://aniversehd.com/ January 19, 2025 at 11:27PM
Show HN: Discorch – Offline tool to browse and delete your Discord messages Built this to help users manage their Discord message history. Upload your data package to browse messages and generate deletion requests that comply with Discord's requirements, all offline and locally. Discord's bulk deletion process is complex and poorly documented. With their recent push toward monetization and ads, users need better tools to control their data. Discorch makes this accessible by guiding you through the process step by step, with a simple and intuitive interface. Includes a Go CLI for attachment downloads. Search functionality needs improvement and there are some known bugs, but it works well for most use cases. Issues and PRs welcome at https://ift.tt/ykvCT2l . I'll keep an eye on the comments for feedback and bug reports! https://discorch.org January 18, 2025 at 04:30AM
Show HN: Compile C to Not Gates Hi! I've been working on the flipjump project, a programming language with 1 opcode: flip (invert) a bit, then jump (unconditionally). So a bit-flip followed by more bit-flips. It's effectively a bunch of NOT gates. This language, as poor as it sounds, is RICH. Today I completed my compiler from C to FlipJump. It takes C files, and compiles them into flipjump. I finished testing it all today, and it works! My key interest in this project is to stretch what we know of computing and to prove that anything can be done even with minimal power. I appreciate you reading my announcement, and be happy to answer questions. More links: - The flipjump language: https://ift.tt/CwtbFGh https://ift.tt/vaGs3HZ - c2fj python package https://ift.tt/q3Pjrma https://ift.tt/siXjVxa January 18, 2025 at 01:06AM
Show HN: News Minimalist – News ranked by significance Hey HN! I'm the author of News Minimalist — a news aggregator where all news is ranked by significance on a scale from 0 to 10. The project was born out of personal pain — I wanted a way to read only significant news, like major humanity milestones, or historical political events, filtering out all the celebrity gossip and smartphone releases. But I couldn't find a way to do that — everywhere I looked, the news was ranked by popularity, coverage, or relevance, not significance. I first tried to solve the problem in the beginning of 2023 with GPT-3 (the top model at that time) by asking it to estimate the significance of some news stories. The results were painfully bad — for some reason, the model preferred tragic, personal stories, completely missing the essence of what makes the news significant. No amount of prompt engineering could fix that. But it all changed in March 2023 when GPT-4 came out. The scores it gave made much more sense. After a month of work, the first version was ready. News Minimalist had its first successful Hacker News post ( https://ift.tt/MVeb7gc ), and I realized that a lot of people had the same problem I had. I've been working on improving the project ever since. As probably most tech founders, I spent too much time on technical improvements, completely ignoring marketing. But I think that work paid off, and I'm finally satisfied with the scores it gives. The results are posted on the site: https://ift.tt/SrqUaw5 Let me know what you think! Vadim https://ift.tt/SrqUaw5 January 16, 2025 at 02:05AM
Show HN: I Put Snake in my Resume [pdf] I'm sure you've seen the post about putting Tetris in a PDF ( https://ift.tt/YyO9KEk ) and putting DOOM in a PDF ( https://ift.tt/ZIcpf1h ). Someone suggested using this technique in a resume to potentially demonstrate your engineering skills, and being chronically unemployed, I had the chance to try that out. The vision is that some recruiter out there will take a break from work, enjoy a game of snake, before inevitably pressing reject. Take a look if you like. Like the others, it requires chromium based browsers. https://ift.tt/Tt0ir3m January 16, 2025 at 03:25AM
Show HN: QwQ-32B APIs – o1 like reasoning at 1% the cost Ubicloud is an open source alternative to AWS. Today, we launched our inference APIs, built with open source AI models. QwQ-32B-Preview is one of those models; and it can provide o1-like reasoning at 1% the cost. QwQ is licensed under Apache 2.0 [1] and Ubicloud under AGPL v3. We deploy open models on a cloud stack that can run anywhere. This allows us to offer great price / performance. From an accuracy standpoint, QwQ does well in math and coding domains. For example, in the MMLU-Pro Computer Science LLM Benchmark, the accuracy rankings are as follows. Claude-3.5 Sonnet (82.5), QwQ-32B-Preview (79.1), and GPT 4o 2024-11-20 (73.1). [2] You can start evaluating QwQ (and Llama 3B / 70B) by logging into the Ubicloud console: https://ift.tt/SM5wKvp We also provide an AI chat box for convenience. We price the API endpoints at $0.60 per M tokens, or 100x lower than o1’s output token price. Also, when using open models, your first million tokens each month are free. This way, you can start evaluating these models today. ## OpenAI o1 or QwQ-32B In math and coding benchmarks, QwQ-32B ties with o1 and outperforms Claude 3.5 Sonnet. In our qualitative tests, we found o1 to perform better. For example, we asked both models to “add a pair of parentheses to the incorrect equation: 1 + 2 * 3 + 4 * 5 + 6 * 7 + 8 * 9 = 479, to make the equation true.” [3] QwQ’s answer shows iterative reasoning steps, where the model enumerates over answers using light heuristics. o1’s answer to the same question feels like an iterative deepen-and-test (though not purely depth-first). When we asked the models harder questions, it felt that o1 could understand the question better and employ more complex strategies. [3][4] Finally, we found that o1’s advantage in reasoning compounded with other ones. For example, we asked both models to write example Python programs. Looking at the answers, it became clear that o1 was trained on a larger data set and that it was aware of Python libraries that QwQ-32B didn’t know about. Further, QwQ-32B at times flip flopped between English and Chinese, making it harder for us to understand the model. [3] Now, if we think that o1 has these advantages, why the heck are we doing a Show HN on QwQ-32B (and other open weight models)? Two reasons. First, QwQ is still comparable to o1 and Ubicloud offers it for 100x less. You can employ a dozen QwQ-32Bs, prompt them with different search strategies, use VMs to verify their results, and still come in under what o1 costs. In the short term, combining these classic AI search strategies with AI models feels much more efficient than trying to “teach” an uber AI model. Second, we think open source fosters collaboration and trust -- and that is its superpower that compounds over time. We foresee a future where open source AI not only delivers top-quality results, but also surpasses proprietary models in some areas. If you believe in that future and are looking for someone to partner with on the infrastructure side, please hit us up at info@ubicloud.com! [1] https://ift.tt/0NunErG [2] https://ift.tt/OjfcV5R... [3] https://ift.tt/K36l0OW [4] https://ift.tt/cRFNIXA January 15, 2025 at 08:59PM
Show HN: A complete e-commerce website builder to build ecom stores in minutes StoreLauncher is a professional Shopify store builder primarily designed for newbies who struggle to create a professional-looking Shopify store. All you have to do is follow a few simple steps to have your store built in literally minutes. There are 8 niches to choose from, each filled with numerous products in our database. The product pages are highly descriptive and unique, as we use AI API to generate product information. Each product gets a dedicated product page template. A logo is also generated using one of 100 premium fonts and published on the store. StoreLauncher creates a professional, clean homepage filled with collections and featured products, as well as image-with-text sections. All essential pages are also created and published to your store. The header and footer navigation are automatically generated and assigned to the appropriate pages and products. Try it for yourself, it's completely free! https://ift.tt/NWF8sYe January 14, 2025 at 03:11AM
Show HN: wonderful.dev – social platform for programmers Hey HN, I'm Alan Founder of wonderful.dev ( https://wonderful.dev/ ) We're building a community for programmers, with a goal to make it easier to network with other devs and connect with companies you’re interested in. The inspiration for wonderful.dev came from my own experiences job searching in the tech industry. I wanted to create a platform where the focus was on mutual interest and meaningful connections instead of resumes, job applications, and coding challenges. Here's how wonderful.dev works: 1. Profile creation: You link accounts like GitHub and WakaTime, and we pull in key metrics to create your profile. 2. Matching: Instead of applying to job postings, you explore companies and star the ones you like. If they star you back, you can chat with them. 3. Community timeline: Like Bluesky for devs, you share updates, interact with other devs, and build your network. When posting to the timeline, we support a subset of Markdown, detect and tag posts with corresponding programming languages for easier discovery, and support integrations with dev tools when posting. Hover over a username to see the programming languages they use, detected from the integrations they connected. Finally, you control your timeline by filtering instead of an algorithm pushing content onto you. More features: https://ift.tt/DPstLF5 Video intro: https://youtu.be/4RLp4Nbmd_o I'd love to hear your thoughts, feedback, or ideas for what could make wonderful.dev even better. https://wonderful.dev January 6, 2025 at 04:12PM
Show HN: Next gen AI workout planner and logger Hey HN! Excited to share my new App. I built hitt.ai to solve the common gym challenges we all face: planning effective workouts, tracking progress, and knowing when to adjust our routines. What makes hitt.ai different? It's built with AI-first capabilities at its core. Think of it as having a personal trainer in your pocket who creates workout plans, reviews your performance, and discusses anything fitness-related – just like a human trainer would. The best part? It's 50x cheaper than a human personal trainer and available 24/7 (because let's face it, AIs don't need protein shakes or rest days ). Key features: - AI-powered workout planning that adapts to your goals and progress - Smart logging system that remembers your exercises and patterns - Personalized recommendations based on your performance - Detailed progress tracking and analytics - Chat with your AI trainer about any fitness topic, anytime The app is now live Download from App Store - https://ift.tt/lgiCTD5... For Android Join this google group - https://ift.tt/8QaN0BG And then download the app by joining app testers - https://ift.tt/MV3vtkS I'd love to hear your thoughts and feedback! I'm actively developing new features and your input would help shape the app's future. https://hitt.ai January 10, 2025 at 09:18PM
Show HN: Freeact – A Lightweight Library for Code-Action Based Agents Hello! We just released freeact ( https://ift.tt/2DyrSFM ), a lightweight agent library that empowers language models to act as autonomous agents through executable code actions. By enabling agents to express their actions directly in code rather than through constrained formats like JSON, freeact provides a flexible and powerful approach to solving complex, open-ended problems that require dynamic solution paths. * Supports dynamic installation and utilization of Python packages at runtime * Agents learn from feedback and store successful code actions as reusable skills in long-term memory * Skills can be interactively developed and refined in collaboration with freeact agents * Agents compose skills and any other Python modules to build increasingly sophisticated capabilities * Code actions are executed in ipybox ( https://ift.tt/90g8kpF ), a secure Docker + IPython sandbox that runs locally or remotely GitHub repo: https://ift.tt/2DyrSFM Evaluation: https://ift.tt/HQKAXde See it in action: https://ift.tt/TZ0elwb... We'd love to hear your feedback! https://ift.tt/2DyrSFM January 10, 2025 at 10:14PM
Show HN: Never let friends forget who is the winner Hi HN, I made a simple little app to keep track of game rankings with friends. It uses the Elo system (like in chess) to adjust scores after each game. Works for board games, chess, padel, tennis, or anything that’s competitive. It’s free — give it a try https://www.shmelo.io/ January 10, 2025 at 06:17AM
Show HN: Ultra-portable Gantt chart tool for very regulated environments I work for government agency with a lot of security considerations. We can't install anything and using public webapps is out of the question. Going through clearance or procurement to buy or install something is a pain. I needed a project management tool, and what we had on offer was too clunky and old. I built SimpleGantt to be ultra lightweight and portable. It's one HTML, one Javascript and one CSS file. Each project is saved into a single .yaml file. If you have a SharePoint environment you can "host" it by uploading the repo to SharePoint after renaming simplegantt.html to simplegantt.aspx. That allows anyone with access to open the tool by simply having the URL. Try it at: https://ift.tt/WTwGm3C This is a couple of days of tinkering, and mostly exists to keep me from going crazy while managing projects with lots of deadlines and dependencies, so don't expect much. But another person in the same position, finding this might lead to calmer days. https://ift.tt/67vhne4 January 9, 2025 at 10:41PM
Show HN: TabPFN v2 – A SOTA foundation model for small tabular data I am excited to announce the release of TabPFN v2, a tabular foundation model that delivers state-of-the-art predictions on small datasets in just 2.8 seconds for classification and 4.8 seconds for regression compared to strong baselines tuned for 4 hours. Published in Nature, this model outperforms traditional methods on datasets with up to 10,000 samples and 500 features. The model is available under an open license: a derivative of the Apache 2 license with a single modification, adding an enhanced attribution requirement inspired by the Llama 3 license: https://ift.tt/WKkpgcA . You can also try it via API: https://ift.tt/b7aE3D4 TabPFN v2 is trained on 130 million synthetic tabular prediction datasets to perform in-context learning and output a predictive distribution for the test data points. Each dataset acts as one meta-datapoint to train the TabPFN weights with SGD. As a foundation model, TabPFN allows for fine-tuning, density estimation and data generation. Compared to TabPFN v1, v2 now natively supports categorical features and missing values. TabPFN v2 performs just as well on datasets with or without these. It also handles outliers and uninformative features naturally, problems that often throw off standard neural nets. TabPFN v2 performs as well with half the data as the next best baseline (CatBoost) with all the data. We also compared TabPFN to the SOTA AutoML system AutoGluon 1.0. Standard TabPFN already outperforms AutoGluon on classification and ties on regression, but ensembling multiple TabPFNs in TabPFN v2 (PHE) is even better. There are some limitations: TabPFN v2 is very fast to train and does not require hyperparameter tuning, but inference is slow. The model is also only designed for datasets up to 10k data points and 500 features. While it may perform well on larger datasets, it hasn't been our focus. We're actively working on removing these limitations and intend to release new versions of TabPFN that can handle larger datasets, have faster inference and perform in additional predictive settings such as time-series and recommender systems. We would love for you to try out TabPFN v2 and give us your feedback! https://ift.tt/dymgRUo January 9, 2025 at 10:08PM
Show HN: Cardstock- Free TCG Proxy Manager for Magic, Yugioh, & Pokemon Trading cards are awesome, but paying $30 for some cardboard isn’t. I’ve upscaled 60,000 cards from the entire catalog of Yugioh, Magic, Pokemon, & a newer game, https://elestrals.com . I've made it easy to build a decklist, download it, and then print at home. Modern inkjet printers got really good when nobody was looking. While it’s clear they’re not real cards, the upscaling makes them look great for casual play (these are not tournament legal). It’s totally free, give it a try! Supplies: https://ift.tt/ZtN52GU Printer Settings: https://ift.tt/khXcue3 Instructions: https://ift.tt/zJtW3d6 Overview: I built Cardstock because I had some scripts to do this lying around, and wanted to explore the new Rails 8 magic. Kamal 2 (kamal-deploy.org/) is a game changer, SQLite in production is fine, and the database backed solid family of gems work like a charm. Compute: I am renting a box on https://hetzner.com located in VA for $15/mo. This box has 8 gigs of ram and 2 vCPU's. This is such a deal compared to compute prices on https://render.com . Kamal 2: This thing is amazing. Kamal gives me everything I could want (easy console access, easy shell access, a way to manage secrets, a way to see my logs, and letsencrypt support for DNS), all without a PaaS tax. The best part is the accessories feature: https://ift.tt/LwOoHIp . I am running my main app with two accessories: Meilisearch( https://meilisearch.com ) and OpenObserve ( https://openobserve.ai ). Instead of paying Algolia to host search infrastructure and sentry to host monitoring infrastructure, I’m hosting my own OSS without any fanfare. Upscaling: To upscale the trading cards (a mandatory part of this build, scans are never high enough DPI). I am using this ( https://ift.tt/hMQ0BRx ) model. For upscaling every card, I've used under a hundred bucks of compute. This model was picked on a whim, but worked well enough that I didn’t compare other models. SQLite: I used SQLite combined with Litestream (litestream.io) for my database. While I considered Postgres, I hesitated due to uncertainties around handling backups on self-hosted infrastructure. This was my first time using SQLite in production, and it was functional but with some minor annoyances. Here’s what I encountered: 1. No Default UUID Primary Key Type I had to set primary keys as strings and assign IDs manually from the application record. It’s an annoying workaround but manageable. 2. No Native Array Columns Because SQLite doesn’t support array columns, I had to use its native JSON column type, which just felt icky. If I were working with something like embeddings, this would be especially annoying, because you couldn’t enforce all the records to have the same number of dimensions. 3. Cryptic Errors At one point, a migration failed silently, leaving a cryptic error in schema.rb. The issue was resolved by rolling back the migration and redoing it, but it was once again, annoying. 4. Litestream Defaults Litestream deletes snapshots after 24 hours by default, which is far too short. When I tried to recover some data, I found it had already been deleted. Adjusting these defaults fixed the problem. Solid Queue/Cache/Cable: The solid family of gems are all backed by the database and were a pleasure to work with. Goal was to prevent needing to reach for redis, so you have one less thing to worry about. You end up with a little more latency, which is a totally reasonable tradeoff. Conclusions: We are moving into a post platform as a service world. Instead of buying a bespoke render.com or heroku, you just buy commodity compute and use Kamal to manage. It's like, pretty much all there, excited to see how this space matures. https://ift.tt/8krjed3 January 8, 2025 at 08:41PM
Show HN: HipScript – Run CUDA in the Browser with WebAssembly and WebGPU CUDA is NVIDIA's language for GPU programming, allowing you to mix write CPU and GPU code in C++ in one file. By chaining a few projects that compile CUDA to OpenCL, then Vulkan, then WebGPU, you can experiment with this GPGPU language on any hardware. https://ift.tt/gXUYo7B January 7, 2025 at 09:14PM
Show HN: Tinyhnsw – The Littlest Vector Database In an effort to understand it, I put together a simple, pure python implementation of HNSW, an approximate nearest neighbor library. Learned a lot, and I think for anyone interested in vector search it's an exercise that's absolutely worth doing. The code is optimized (imo) for readability, and working (albeit, quite slowly) on putting together a tutorial that walks through the motivation and implementation of HNSW. There's also working code examples for using the library for text and image search with sentence transformers and CLIP! https://ift.tt/Ijwsqix January 7, 2025 at 11:14PM
Show HN: I created a tool that helps developers generate fake data for databases Hi, everyone! Lately, I've been working on quite a few applications that require a database, and as a result, I need some data to test everything. It has always taken me a lot of time to ask ChatGPT to generate fake data for me, so I decided to create a tool for developers called FakeData. FakeData allows developers to generate fake data easily with a simple UI/UX and customizable fields. This data can be used in their applications to test various functionalities. P.S. The app is not yet finished, and I would love to hear your honest feedback on it. Please be brutally honest about what you like and what you don’t! https://ift.tt/4v6QHka January 7, 2025 at 03:47AM
Show HN: A 100-Line LLM Framework I've seen a lot of comments about how complex frameworks like LangChain can be. Over the holidays, I wanted to see how minimal an LLM framework could get if we stripped away everything non-essential. The result is an LLM framework in just 100 lines of code. These 100 lines capture what I see as the core abstraction of most LLM frameworks: a nested directed graph that breaks down tasks into multiple LLM steps, with branching and recursion to enable agent-like decision-making. From there, you can layer on more advanced features like agents, RAG, task decomposition, and more. I’ve intentionally avoided bundling vendor-specific wrappers (e.g., for OpenAI) into the framework. That kind of lock-in can be brittle and is easy to recreate on the fly—just feed the vendor’s API docs into your favorite LLM to generate a new wrapper. With miniLLMFlow, you only get the fundamentals. It also works nicely with coding assistants like ChatGPT, Claude, and Cursor.ai. Because the code is so minimal, you can quickly share the entire "source code and documentation with an AI assistant, and it can help you build new workflows on the spot. I’m adding more examples (including multi-agent setups) and would love feedback! If there's a feature or use case you’d like to see, please let me know. GitHub: https://ift.tt/48KJLtO https://ift.tt/48KJLtO January 6, 2025 at 09:20PM
Show HN: Skeet – A local-friendly command-line copilot that works with any LLM I've been using GitHub Copilot CLI, and while it's great, I found myself wanting something that could work with any LLM (including running local models through Ollama), so I built Skeet. The key features that make it different: - Works with any LLM provider through LiteLLM (OpenAI, Anthropic, local models, etc.) - Automatically retries and adapts commands when they fail - Can generate and execute Python scripts with dependencies (powered by uv) without virtual environment hassles You can try simple tasks like: ``` skeet show me system information skeet what is using port 8000 skeet --python "what's the current time on the ISS?" ``` Demo: https://ift.tt/qf75QRh Code: https://ift.tt/Rtj1gpQ I built it for myself, and I've been really happy with the results. It's interesting to see how different models fare against one another with everyday tasks. If running a local model, I've had decent luck with ollama_chat/phi3:medium but I'm curious to know what others use. Cheers! https://ift.tt/Rtj1gpQ January 6, 2025 at 10:53PM
Show HN: I made a simple tool to track Google Rankings I was frustrated with how complex and expensive most rank tracking tools are. I wanted something that was both powerful and beautifully simple. That's Rank! helps you: • Track rankings for up to 15 domains and 300 keywords • Get daily rank updates automatically • View historical ranking data and trends • Access advanced reporting features • Monitor competitor rankings (coming soon) • Get ranking change alerts (coming soon) It's completely free while in beta! Please try it out :-) https://ift.tt/607Yigo January 6, 2025 at 01:00AM
Show HN: Discuo – Anonymous discussions with infinite branching and 24h lifespan I built Discuo, a unique discussion platform that combines: - Infinite thread branching: conversations evolve naturally in multiple directions - 24h post lifespan: all content auto-deletes after 24 hours - No account needed: just start posting or commenting instantly - Complete anonymity: no tracking, no personal data collection - Minimalist design: distraction-free, focused on pure discussion Originally created for developers to share progress and discuss code, it evolved into a platform covering various topics while maintaining its minimalist essence. https://discuo.com January 1, 2025 at 10:23PM
Show HN: Does your food have gluten? Hey folks! About a couple of months or so ago, I finally figured out I’m gluten intolerant after months of chasing random symptoms and getting nowhere. After a wild goose chase (started this via Djokovic's Serve To Win book) finally found out I was highly gluten sensitive/intolerant. I had to rethink everything I ate. Grocery shopping turned into ingredient detective work, and eating out became a gamble. I quickly realized I needed something to make this easier and built GlutenAI. It’s a super simple tool to check if something’s gluten-free. Type in a food or product or even a common recipe name, and it’ll let you know if you’re good to go or should steer clear. Would love to get y'all's feedback on this and let me know what else you would like to see here : https://ift.tt/VGydjwm https://ift.tt/VGydjwm January 6, 2025 at 12:58AM
Show HN: Lightweight Llama3 Inference Engine – CUDA C Hey, recently I took inspiration from llama.cpp, ollama, and many other similar tools that enable inference of LLMs locally, and I just finished building a Llama inference engine for the 8B model in CUDA C. I recently wanted to explore my newly founded interest in CUDA programming and my passion for machine learning. This project only makes use of the native CUDA runtime api and cuda_fp16. The inference takes place in fp16, so it requires around 17-18GB of VRAM (~16GB for model params and some more for intermediary caches). It doesn’t use cuBLAS or any similar libraries since I wanted to be exposed to the least amount of abstraction. Hence, it isn’t as optimized as a cuBLAS implementation or other inference engines like the ones that inspired the project. ## *A brief overview of the implementation* I used CUDA C. It reads a .safetensor file of the model that you can pull from HuggingFace. The actual kernels are fairly straightforward for normalizations, skip connections, RoPE, and activation functions (SiLU). For GEMM, I got as far as implementing tiled matrix multiplication with vectorized retrieval for each thread. The GEMM kernel is also written in such a way that the second matrix is not required to be pre-transposed while still achieving coalesced memory access to HBM. Feel free to have a look at the project repo and try it out if you’re interested. If you like what you see, feel free to star the repo too! I highly appreciate any feedback, good or constructive. https://ift.tt/VJ91tXI January 5, 2025 at 03:37AM
Show HN: A remake of my 2004 PDA video game My background project for the last two years has been re-implementing my 2004 C++ shoot'em up game in TypeScript + WebGL, and it's finally done (just in time for the 20th anniversary!) Play the game online: https://ift.tt/CUwExs4 Technical article about the remake: https://ift.tt/CxmJYuP I have tested Firefox, Chrome and Edge on desktop and mobile (no access to a device capable of running Safari). It's amazing how much difference 20 years makes: the hardware is so much more powerful, the web as a deployment platform is so much easier than side-loading onto a PDA through a serial cable or sharing .exe files through e-mail, and my experience as a professional developer makes almost everything so much easier... but at the same, it didn't feel that the language, editor or debugger (TypeScript on Visual Studio Code) were significantly better than good old Visual C++ 6. Repository with the code of the remake: https://ift.tt/Km38pDs (sadly, I cannot provide the video and audio assets themselves under any open license). https://ift.tt/CxmJYuP December 31, 2024 at 04:25PM
Show HN: NeatShift – A Modern Windows File Organizer with Symbolic Link Support Hi HN, I've been developing NeatShift, a Windows application designed to help users organize their files and folders seamlessly using symbolic links. The aim is to declutter storage without disrupting file accessibility. Key Features: Smart Moving: Relocate files while NeatShift creates symbolic links to maintain system functionality. Safety Measures: Options for quick backups with NeatSaves and system restore points to ensure data integrity. Integrated File Explorer: Modern interface with drag-and-drop support, customizable views, and both light and dark themes. Link Management: Easily view and manage all symbolic links in one place. I initiated this project to address the challenges of managing large files on limited SSD storage, ensuring that moving files doesn't break application dependencies. NeatShift is open-source (GPL-3.0 license), and I'm actively seeking feedback and contributors to enhance its functionality. Explore the project here: GitHub Repo https://ift.tt/IKORPoc Looking forward to your thoughts and suggestions! https://ift.tt/IKORPoc January 3, 2025 at 12:56AM
Show HN: I built a recipe app weeks after starting to code GoRecipeHub is live I started learning to code just a few weeks ago, and today I’m thrilled to share my 4th app, GoRecipeHub. It’s a cooking companion that lets users discover, save, and share recipes effortlessly. I’d love your feedback: What features would you add to make it even better? Check it out here: https://gorecipehub.com https://gorecipehub.com January 2, 2025 at 04:41PM
Show HN: I built a green noise player to help you relax, focus, and stay calm Sometimes, I struggle to block distractions and create a calming environment while working. Most tools I’ve tried were either cluttered, didn’t provide the right kind of sound, or required payment. So, I decided to build my own simple green noise player. For context, green noise features balanced, mid-range frequencies that mimic soothing natural sounds—ideal for relaxation, focus, or creating a peaceful backdrop while working. It’s also great for taking a mindful break during a busy day. Right now, it’s a free, lightweight, browser-based solution. Playback pauses on mobile when the screen locks, but I’m exploring ways to improve it. Maybe a dedicated mobile version in the future? Would love to hear your thoughts and feedback! https://ift.tt/N3qT0ru January 2, 2025 at 03:49AM
Show HN: GitHub-style screen time visualizer on iOS I wanted a longer-running view of my screen time data - in particular my usage on a given day vs. my goal usage. Github absolutely nails year-long visualization with their contributions heatmap, so borrowed some inspiration and created a similar screen time visualizer on iOS. Here's what it looks like: https://ift.tt/ZgXkF1r This is a free feature of the Clearspace app. Here's a link to our original HN launch with Clearspace: https://ift.tt/mWSbqk6 https://ift.tt/k5oR7S0 January 2, 2025 at 01:24AM
Show HN: Cave Adventure 1976 PICO-8 port Made this during COVID. I was into PICO-8 at the time and saw someone ported DOOM to it. I'm more of a text adventure guy, so I decided to port ADVENT. Basically I wrote a FORTRAN-to-Lua transpiler. The hardest part was figuring out what version of FORTRAN the source code was written in, finding a manual, cramming it into the limited cartridge space, but most of all, wrapping my mind around the data file format. Always admired Will Crowther for making this. Very fun project. I recorded myself during the whole process but I never posted a video. Future work maybe. https://ift.tt/C0pbGXL December 31, 2024 at 09:14PM
Show HN: GitHub repository through a Podcast Understanding any GitHub repository is tough, especially a big one - this project aims to make it a tad bit easier by giving the listener a primer + some details on the specific repository. For some people (like me) - audio/visual medium is more easily understandable. So, I hope this project is helpful to some of them. This project was inspired by https://gitdiagram.com - so check it out as well, and maybe use them together for better understanding. Future plans: 1. To add more voices and let users choose most natural one (decide between OpenAI/Microsoft Speech) 2. Custom instructions to the SSML creator. Self hosting: 1. For speech - You can use Microsoft Speech (they do have free credits I think) 2. For SSML text - You can also use Gemini flash 2.0 exp - with 15 free credits (I am using OpenAI GPT 4o) https://ift.tt/eXdfVRu December 31, 2024 at 11:50AM
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