Show HN: Temp.now – A free temporary disposable email generator https://bit.ly/4eIn2oI

Show HN: Temp.now – A free temporary disposable email generator Yesterday I registered the domain temp.now. Today, I deployed a temporary email tool using open-source code, which is convenient for registering products and services. As long as you save the login credentials, you can keep the generated addresses indefinitely. Enjoy! EN URL: https://bit.ly/4eO7Bvy https://bit.ly/3YbIOw0 October 2, 2024 at 09:25PM

Show HN: Quilt – Powerful RAG UI for Document QA https://bit.ly/3ZMSHkU

Show HN: Quilt – Powerful RAG UI for Document QA Hey HN! We've just launched Quilt, a robust RAG (Retrieval-Augmented Generation) UI that revolutionizes how you interact with your documents. Key features: - Multi-user setup with private/public document collections - Advanced hybrid RAG pipeline combining full-text & vector search - Smart citations with in-browser PDF preview and highlights - Fully customizable settings and prompts through the UI Making an account is free, no need to even use a strong password: this is only to ensure your documents are separate from the rest. We're keen to hear your thoughts and feedback. What features would you like to see next? https://bit.ly/4gMrepw October 2, 2024 at 04:54AM

Show HN: Speech-to-speech playground for OpenAI's new Realtime API https://bit.ly/3BsLRXC

Show HN: Speech-to-speech playground for OpenAI's new Realtime API Hi there - Ben from LiveKit here! If you’re curious about OpenAI’s brand-new Realtime API and speech-to-speech model, check out this hosted playground and play with the model yourself. If you’d like to learn more about how this came together, read on. If you’re like me, you’ve probably been wondering what novel things a model like this can do in an API setting with unfettered access to the system prompt and other parameters. I’ve been fortunate to have had early access through my work at LiveKit, where we’ve built open-source developer tooling that makes deploying this model in a production app as simple as possible. I thought it would also be fun to build a “playground” environment, partially to dogfood our own tooling but largely because I just wanted to play with the model. This playground is freely available to anyone to try, and comes loaded up with a bunch of fun demos of the model’s unique capabilities that I’ve put together. What blew my mind is how much mileage you can get out of the system prompt alone in this API. Here are some use-cases that are at least halfway to a complete MVP: - "Customer Support": An complete phone support agent for the playground - "Spanish Tutor": A bilingual language-learning demo - "Meditation Coach": It can actually pause and resume speech all on its own as it guides you through a meditation routine Also some fun (and a bit irreverent…) demos of its style and non-verbal capabilities: - "Smoker’s Rasp": It can cough and speak like it’s been smoking three packs a day for 30 years (my favorite, lol) - "Unconfident Assistant": Umms, buts, and more - surprisingly lifelike - "Opera Singer": The best singing demo I’ve been able to compose (but still not quite what they showed off back in May…) The playground doesn’t store anything anywhere besides your browser but you can share anything fun you put together with a link that encodes your config into URL params. For now - anyone can use this playground to access the model and give it a spin (session limit 5min). In the coming days when more people have access to the underlying API, I’ll update it to require you bring your own OpenAI API Key. Lastly - if you’re even more curious how this was built or want to tweak or adapt it for yourself, the whole project and every dependency is open-source (link in footer!). https://bit.ly/3XQ25S5 October 2, 2024 at 02:59AM

Show HN: DnsTrace - Monitor DNS Queries by host processes using BPF https://bit.ly/3zHhPic

Show HN: DnsTrace - Monitor DNS Queries by host processes using BPF https://bit.ly/3N8fWOF October 2, 2024 at 01:08AM

Show HN: TextSnap – Open-Source Tool for Accurate Text Formatting Using AI https://bit.ly/4eKVxuV

Show HN: TextSnap – Open-Source Tool for Accurate Text Formatting Using AI After months of trial and error to format our texts quickly and accurately, we have arrived at this version of Text Snap. We've open-sourced it and launched TextSnap. All the code is open, including the prompts for each of the formats… each prompt is very well crafted, as this is the result of months of trial and error. Feel free to clone it or self-host it, or use it for commercial purposes. Check out the repository ( https://bit.ly/4eOZqiz ) Looking forwards for your feedback. https://bit.ly/4gQJH4q October 2, 2024 at 12:30AM

Show HN:Using Cloudflare, query DNS results from 120 countries and 330 cities https://bit.ly/3XUrvOG

Show HN:Using Cloudflare, query DNS results from 120 countries and 330 cities https://bit.ly/3MqnRXa October 1, 2024 at 03:07AM

Show HN: Presidential polling with instant electoral results https://bit.ly/4emeuEz

Show HN: Presidential polling with instant electoral results Hi HN! This is an experiment with low-friction, "fearless", Internet-based polling. There is no authentication, only a captcha and restriction to US IP addresses. Congressional district is detected automatically. Selections can be changed at any time until the poll closes, kind of like a presidential caucus. Just tap to select. Tap again to change. I built this after pondering about how polling (or even voting) could be improved through technology. Yes, digital voting is a tough space with trust issues. Maybe there are practical, partial solutions. This is my third post. Earlier submissions didn't perform well, probably because politics is a sensitive subject. However, this project is not political. It is about tech and process. I believe it's an appropriate submission for HN and it ought to be interesting no matter your political leaning. Hopefully with this better framing there can be better discussion. Another way of looking at it: if the poll results bother you, think about how improving polling/voting generally might help your cause. Here are some topics to guide constructive discussion: * Internet-based polling. Can we make this a routine thing? Would it be worthwhile? Abuse prevention? * Internet-based voting. About time or never gonna happen? * Augmenting the voting experience. We don't have ranked choice voting, but maybe it could be simulated in advance of an election. Maybe an organization could act as a delivery agent for mail-in votes. * The tech stack. This project uses a combination of boring (Django+Postgres) and shiny (Fastly edge pub/sub, captcha, etc). The database ought to be able to handle a few million participants. To get to a few hundred million I'd probably add more PG nodes and shard. Curious what others think about the database options for accurate+fast counting. * Have fun with it! This isn't a real election. If you want to VPN to an empty state to claim a bunch of electoral votes, go for it. I hope with enough participants the results would be mostly representative, though. The poll will run every Monday afternoon/evening until Election Day. It's designed to withstand a good bit of traffic so feel free to share it. Earlier posts: https://bit.ly/3TOhb9z https://bit.ly/3TQ6zqx https://bit.ly/4enX0Hz September 30, 2024 at 09:26PM

Show HN: Offline macOS app to convert Markdown documents https://bit.ly/47Pd4Qn

Show HN: Offline macOS app to convert Markdown documents Hi HN, I've just launched DocFlex, an offline macOS app that converts Markdown documents into over 30 formats like PDF, HTML, EPUB, LaTeX, and more. Why I built it: As someone who frequently works with Markdown, I found it cumbersome to convert documents into different formats, especially when dealing with multiple files. Online converters weren't ideal due to privacy concerns and the need for an internet connection. So, I created DocFlex to make the process seamless and entirely offline. Key Features: 100% Offline: All conversions happen locally on your machine. Your documents are never sent to any servers. Batch Conversion: Convert multiple Markdown documents at once. 30+ Formats Supported: Export to PDF, HTML, EPUB, LaTeX, JSON, and many more. Native macOS App: Lightweight and focused solely on conversion without any unnecessary bloat (only installs basicTeX and pandoc). Download: You can download it here: https://bit.ly/4dou9BH I'd love to get your feedback and answer any questions you might have! https://bit.ly/4dou9BH September 30, 2024 at 11:51PM

Show HN: Rocky AI – Chat with any webpage in Chrome using AI https://bit.ly/4gI2EWK

Show HN: Rocky AI – Chat with any webpage in Chrome using AI A simple chrome extension that lets you chat with any webpage using AI. I was tired of copy pasting into Chat GPT from webpages all them time so built this. Popular Use Cases: 1. Summarize Articles – Get concise overviews of content from sources like HackerNews, Reddit, and more. 2. Quick Information Lookup – Effortlessly locate key details on pages such as developer documentation, car forums, and beyond. 3. Personalized LinkedIn Outreach – Craft customized outreach messages for your LinkedIn connections with ease. 4. Review Analysis – Analyze feedback and reviews from platforms like Airbnb, Amazon, and others for quick insights. https://bit.ly/3XSAAHM September 30, 2024 at 04:17AM

Show HN: Fin.flights 2.0 – AI-powered flight search https://bit.ly/4dmb4Ag

Show HN: Fin.flights 2.0 – AI-powered flight search fin.flights is an AI-powered flight search tool that uses natural language processing to find the best flights based on user queries. just released version 2.0 with significant improvements: - No login required: Start searching immediately without creating an account - Advanced AI: Utilizing latest LLMs for more accurate flight results - Natural language interface: Type queries as you would ask a friend - Global coverage: Searches flights worldwide with multi-language support - Free to use: Only upgrade if you find it valuable How it works: 1. Enter a natural language query (e.g., "cheapest business class flights from NYC to Tokyo in the next 3 months with max 1 stopover") 2. Our AI interprets the query and searches across multiple airlines and booking platforms 3. Results are displayed instantly, sortable by price, duration, or best value I built this because existing flight search engines often require too many inputs and don't offer the flexibility of natural language queries. Myy goal is to make flight search as simple as asking a knowledgeable friend. I'd love to get feedback from the HN community on the user experience, AI accuracy, and any features you'd like to see added. https://bit.ly/4dwVNfY September 29, 2024 at 11:02PM

Show HN: FlowG – A KISS low-code log processing software https://bit.ly/4duvE1g

Show HN: FlowG – A KISS low-code log processing software https://bit.ly/4dsXaMP September 29, 2024 at 04:22AM

Show HN: htmgo - build simple and scalable systems with golang + htmx https://bit.ly/4dvH9Wi

Show HN: htmgo - build simple and scalable systems with golang + htmx Hey all, I just wanted to share a project I've been working on for the past month. After years of heavy frameworks, I really like the idea of using htmx, but it’s a little too low level for me and needs a thin layer above it to facilitate things like components, better syntax with complex JS inside of an attribute, etc To try and solve this problem with a very minimal stack (golang + htmx) that I've been really enjoying, I'm building this project to cater to my needs and was thinking it would be useful for other developers. https://bit.ly/401p7s7 September 28, 2024 at 10:34PM

Show HN: Iceoryx2 – Fast IPC Library for Rust, C++, and C https://bit.ly/47GMY21

Show HN: Iceoryx2 – Fast IPC Library for Rust, C++, and C Hello everyone, Today we released iceoryx2 v0.4! iceoryx2 is a service-based inter-process communication (IPC) library designed to make communication between processes as fast as possible - like Unix domain sockets or message queues, but orders of magnitude faster and easier to use. It also comes with advanced features such as circular buffers, history, event notifications, publish-subscribe messaging, and a decentralized architecture with no need for a broker. For example, if you're working in robotics and need to process frames from a camera across multiple processes, iceoryx2 makes it simple to set that up. Need to retain only the latest three camera images? No problem - circular buffers prevent your memory from overflowing, even if a process is lagging. The history feature ensures you get the last three images immediately after connecting to the camera service, as long as they’re still available. Another great use case is for GUI applications, such as window managers or editors. If you want to support plugins in multiple languages, iceoryx2 allows you to connect processes - perhaps to remotely control your editor or window manager. Best of all, thanks to zero-copy communication, you can transfer gigabytes of data with incredibly low latency. Speaking of latency, on some systems, we've achieved latency below 100ns when sending data between processes - and we haven't even begun serious performance optimizations yet. So, there’s still room for improvement! If you’re in high-frequency trading or any other use case where ultra-low latency matters, iceoryx2 might be just what you need. If you’re curious to learn more about the new features and what’s coming next, check out the full iceoryx2 v0.4 release announcement. Elfenpiff Links: * GitHub: https://bit.ly/4dGdWbv * iceoryx2 v0.4 release announcement: https://bit.ly/47L0nG6 * crates.io: https://bit.ly/3Y1IwHJ * docs.rs: https://bit.ly/47I4ymf https://bit.ly/47L0nG6 September 28, 2024 at 05:40PM

Show HN: Open-source Docker image to run Chrome browsers in your cloud https://bit.ly/3N3NeOR

Show HN: Open-source Docker image to run Chrome browsers in your cloud If you’ve ever worked with web scraping or automation using Puppeteer or Playwright, you know that running Chrome can be tricky. While headless mode (Chrome with no display) often works, some page elements only render in headed mode, forcing you to run Chrome with a display. This usually means bloating your Dockerfile with complex dependencies like xvfb. Updating your server or Lambda container to handle this can increase costs and lead to dependency hell. The Solution: I’ve built a streamlined solution—a Docker image that runs Chrome with all its necessary dependencies and exposes a FastAPI interface. This decouples the browser logic from your main codebase, letting you focus on scraping or automation without worrying about the underlying setup. The container exposes a WebSocket endpoint at ws://localhost:8000/ws, allowing you to connect Playwright or Puppeteer over Chrome DevTools Protocol (CDP). For example: browser = await pw.chromium.connect_over_cdp('ws://localhost:8000/ws') Each connection to the WebSocket spins up a new Chrome session in headed mode, and you can run multiple sessions concurrently. Unlike other solutions, Finic is fully open-source (Apache 2.0 licensed). You can try it by pulling the official Docker image or cloning the repo at Finic on GitHub ( https://bit.ly/3XKPBw6 ) and running `docker-compose up --build`. This approach simplifies handling Chrome for scraping, saves on cloud costs, and keeps your setup clean. Give it a try! https://bit.ly/3ZCDzq8 September 27, 2024 at 04:06PM

Show HN: DecisionBox – Continuous Accuracy Improvement for LLM Apps https://bit.ly/4eqTZGQ

Show HN: DecisionBox – Continuous Accuracy Improvement for LLM Apps Just released DecisionBox, an open-source SDK that helps developers make high-accuracy decisions in LLM apps, which continuously improve with more data. DecisionBox tackles the challenge of maintaining decision accuracy beyond the limitations of prompt engineering. It streamlines the data science process with an easy-to-use API and enables ongoing accuracy metrics and model improvements. Get started: https://bit.ly/3TMNghZ We’re excited to hear feedback and answer any questions! AMA. https://bit.ly/3TMNghZ September 27, 2024 at 07:57PM

Show HN: A tool that turns everyday computers into your own AI cloud https://bit.ly/3ZDxbit

Show HN: A tool that turns everyday computers into your own AI cloud I have a favour to ask. I’ve been working for a while on Kalavai, a project to make distributed AI easy. There are brilliant tools out there to help AI hobbyists and devs on the software layer (shout out to vLLM and llamacpp amongst many others!) but it’s a jungle out there when it comes to procuring and managing the necessary hardware resources and orchestrating them. This has always led me to compromise on the size of the models I end up using (quantized versions, smaller models) to save cost or to play within the limits of my rig. Today I am happy to share the first public version of our Kalavai client (totally free, forever), a CLI that helps you build an AI cluster from your everyday devices. Our first use case is distributed LLM deployment, and we hope to expand this with the help of the community. Now, the favour! I’d love for people interested in AI at scale (bigger than a single machine) to give it a go and provide honest feedback. Do you share our motivation? If you tried Kalavai, did you find it useful? What would you like it to do for you? What are your painpoints when it comes to using large LLMs? https://bit.ly/3zoGHve September 27, 2024 at 07:12PM

Show HN: Scandium: No-Code Test Automation Tool for Software Testing https://bit.ly/4dq1FaR

Show HN: Scandium: No-Code Test Automation Tool for Software Testing https://bit.ly/4gJAFWz September 24, 2024 at 12:01PM

Show HN NGINIX Manager https://bit.ly/3Buh3Wd

Show HN NGINIX Manager A simple NGINX manager https://bit.ly/4dlJPpy September 26, 2024 at 09:09PM

Show HN: Structured, GitHub App for Automated DBT PR Reviews https://bit.ly/3Y2l1xh

Show HN: Structured, GitHub App for Automated DBT PR Reviews Scaling data teams today means dealing with the complexity of the modern data stack. While DBT has become a core tool for transforming raw data into structured, analytics-ready tables, most teams are using it in ways that lead to chaos: duplicated models, inconsistent metrics, and inefficient SQL that directly impacts cloud spend. The real issue isn’t with DBT itself—it’s in how it’s applied across teams. Here’s the typical setup: Finance defines a revenue model, Marketing calculates customer lifetime value, and Product defines churn. All in DBT, but all with slightly different logic, leading to metric fragmentation. This results in data drift, conflicting reports, and a ton of unnecessary engineering time spent reconciling definitions. Worse, engineers end up re-inventing the wheel by duplicating logic that already exists in other models. The inefficiencies don’t stop there: suboptimal SQL patterns (e.g., full-table scans, poor joins) creep into production and drive up cloud costs. We designed our GitHub App to automate the grunt work of DBT model management, focusing on three key areas: preventing redundant logic, maintaining the semantic layer, and optimizing SQL performance. --- (1) Stop Redundant Models: A lot of teams waste time rebuilding models that already exist. Engineers aren’t aware of what’s been built, so they duplicate work. Our app automatically reviews pull requests, flags redundant models, and suggests reusing existing logic. This keeps your key metrics like revenue or churn consistent across teams and prevents conflicting reports. (2) Maintain the Semantic Layer: DBT’s value is in creating a semantic layer—a consistent definition of business metrics. But as teams scale, maintaining this layer gets tricky. People unknowingly break it with small changes, leading to inconsistencies. Our app checks every new model for deviations from the semantic layer, flagging inconsistencies before they go live. This prevents those all-too-common situations where two departments are debating whose revenue number is right. By ensuring everyone’s using the same definitions, you avoid trust issues with the data. (3) SQL Performance = Real Costs: Bad SQL isn’t just a performance problem—it’s a cost problem. Inefficient joins, full-table scans, and poorly written SQL in your DBT models can blow up your cloud bill. Our app reviews SQL in pull requests, flags inefficiencies, and suggests optimizations. Example: An engineer submits a model that joins two large tables without filtering. Our app flags the full-table scan and suggests using indexed columns and adding WHERE filters. This reduces query cost and improves performance before the code hits production. --- Data engineers are already stretched thin with the demands of modern data pipelines. By automating model consistency checks, semantic layer enforcement, and SQL performance reviews, our GitHub App frees up your team to focus on higher-impact work rather than wasting cycles on repetitive tasks or fighting fires caused by bad data logic. The app is live—give it a try, and let us know how it’s improving your workflow. Also, keep an eye out for our upcoming DBT code generation features—we’re automating more of the heavy lifting soon. https://bit.ly/4eC3fYc September 26, 2024 at 10:28PM

Show HN: Oku – A Web browser with an emphasis on local-first data storage https://bit.ly/4gHOt4a

Show HN: Oku – A Web browser with an emphasis on local-first data storage Hello HN, My name is Emil. I'm a recent unemployed graduate, and I've been spending a lot of my time working on a passion project from my teenage years. When I was younger, I wanted a place on the Web that I could call my own—not a social media page, but a proper site. I was interested in the IndieWeb community for a while, but I grew to believe a P2P alternative to the Web made more sense than having people host federated services. My browser isn't production-ready, but I'm satisfied with the progress so far and would appreciate thoughts & feedback. Thank you! https://bit.ly/3MZQ7QP September 26, 2024 at 02:33AM