Show HN: I Drew Stickers for Programmers https://ift.tt/78HbEWp

Show HN: I Drew Stickers for Programmers same free for Telegram: https://ift.tt/xmWh58O https://ift.tt/mBNcGZl January 28, 2025 at 01:47AM

Show HN: Ollama server discovery tool (finds public LLM instances) https://ift.tt/Q9Kmq30

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/gYA7Psk January 28, 2025 at 02:40AM

Show HN: LLMule – Run and Share Local LLMs in a P2P Network https://ift.tt/IKV7iBf

Show HN: LLMule – Run and Share Local LLMs in a P2P Network https://llmule.xyz January 28, 2025 at 12:44AM

Show HN: AnswerHN https://ift.tt/JAsen17

Show HN: AnswerHN I had an itch to build a weekend project, and I've noticed that a lot of Ask HNs often go unanswered, so I built AnswerHN as a simple way to see recently asked, but as yet unanswered, questions on Hacker News. https://ift.tt/RWCZVSx January 28, 2025 at 12:27AM

Show HN: A new native app for 20 year old OS X https://ift.tt/M9ecKND

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/LofV0PY [1] - https://ift.tt/wxksVvf [2] - https://ift.tt/Bl2N90b https://ift.tt/wxksVvf January 24, 2025 at 06:16AM

Show HN: SimpleSearch – Yep, just a list of the search bars you need https://ift.tt/OrVEhKD

Show HN: SimpleSearch – Yep, just a list of the search bars you need I made this site for myself, SimpleSearch.info, as new default browser page. I’m not sure if it actually _saves_ time or clicks (though, for me, it saves at least one click per search), but I find the search experience more pleasant. On desktop, it’s nice to just have these search bars as the first thing that pops up in a new window or tab vs clicking bookmarks in the toolbar or elsewhere then searching. Similarly, on mobile, I like just clicking on one icon for all my searches. The vast majority of my web browsing begins with a search or LLM query. I’m curious if this is helpful to anyone else and if there are any additional features I might add to make it more useful. Thanks! https://ift.tt/QqZrvnj January 27, 2025 at 12:35AM

Show HN: Actionate – GitHub Actions for JetBrains IDEs https://ift.tt/L26Ch50

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/W2G4RqA January 26, 2025 at 01:53AM

Show HN: I made an extension that turns Google Sheets into Google Slides https://ift.tt/aQ7EnSk

Show HN: I made an extension that turns Google Sheets into Google Slides https://ift.tt/5zStXwd January 23, 2025 at 07:14PM

Show HN: Freelens OSS Kubernetes IDE https://ift.tt/BcT59ZR

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/CzfZInr January 26, 2025 at 12:50AM

Show HN: Pokemon BattleSim – Make your friends into Pokemon https://ift.tt/fAn2CSI

Show HN: Pokemon BattleSim – Make your friends into Pokemon https://ift.tt/9GafqEX January 24, 2025 at 09:31PM

Show HN: Magenta.nvim – AI coding plugin for Neovim focused on tool use https://ift.tt/THGaqXY

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/U8rB2lG January 21, 2025 at 08:37AM

Show HN: Snap Scope – Visualize Lens Focal Length Distribution from EXIF Data https://ift.tt/ANdjCeP

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/qz90hpR Source: https://ift.tt/6GFizAV https://ift.tt/qz90hpR January 24, 2025 at 07:48PM

Show HN: I'm Building an Alternative to Figma https://ift.tt/tws9ofq

Show HN: I'm Building an Alternative to Figma I'm building Octo because I needed a tool that combined Figma’s collaboration with Illustrator and Photoshop’s tooling. As a developer, I wanted something that supports both the technical and creative sides of UI/UX design. Octo is cross-platform and built to simplify workflows for people who code and design. https://octo.coffee January 24, 2025 at 01:44AM

Show HN: Helicone (YC W23) – OSS LLM Observability and Development Platform https://ift.tt/pcrabLe

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/fzKQB5e ) or self-deploy with our new fully open-source helm chart ( https://ift.tt/Md8CLIZ ). 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/PhvzOxi ). 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/cXz0PaZ ). 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/jNXbJm7 ). 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/uWbCDdK... We'd love your feedback and questions - join us in this HN thread or on Discord ( https://ift.tt/32GvrRY ). If you're interested in contributing to what we build next, check out our GitHub. https://ift.tt/geAotJ6 January 23, 2025 at 11:28PM

Show HN: Open-source AI video editor https://ift.tt/GZDWbSA

Show HN: Open-source AI video editor Hey HN community! I'm one of the lead devs of this project at fal.ai and we created an open source lightweight video editor powered by the latest media AI models. The main goal was to tackle some challenges when dealing with complex media handling and encoding on the browser. It all started as an internal experiment but as we tackled some of the issues it was clear there could be some value sharing it with the open source community. Some of the key points and tech stack details: - It uses IndexedDb, so all data is local (i.e. no auth, no cloud db) - Multiple AI models for video, image, music and voice-over. APIs are provided by fal.ai - Built with the typical React+Next.js, Shadcn front-end - Used remotion.dev for the realtime video preview (this is such a great project, without it the codebase would be twice as large) - File uploads so you can bring your own media by uploadthing.gg - ffmpeg for encoding the final video and also some ui tricks, like the audio waveform We deployed a version of it and for now it's free to use. We do plan to add some rate limiting and a bring your own API Key next, but it's open source and I'm curious about what the community will build on top of it, or derive from it. Customize your own video app and if you do, please share. If you have any questions, hit me up! https://ift.tt/nAxdipW January 24, 2025 at 12:04AM

Show HN: I Made an Open-Source Laptop from Scratch https://ift.tt/ZvQOMSU

Show HN: I Made an Open-Source Laptop from Scratch Hello! I'm Byran. I spent the past ~6 months engineering a laptop from scratch. It's fully open-source on GH at: https://ift.tt/HA8TQJ7 https://ift.tt/6PxzYlE January 23, 2025 at 02:11AM

Show HN: Responding to SMS Spam with Ollama https://ift.tt/wngWzKk

Show HN: Responding to SMS Spam with Ollama I've been working on a side project to generate responses to spam with various funny LLM personas, such as a millenial gym bro and a 19th century British gentleman. By request, I've made a write-up on my website which has some humorous screenshots and made the code available on Github for others to try out [0]. A brief outline of the system: - Android app listens for incoming SMS events and forwards them over MQTT to a server running Ollama which generates responses - Conversations are whitelisted and manually assigned a persona. The LLM has access to the last N messages of the conversation for additional context. [0]: https://ift.tt/JVdzcAv I'm aware that replying can encourage/allow the sender to send more spam. Hopefully reporting the numbers after the conversation is a reasonable compromise. https://ift.tt/igrbj4M January 23, 2025 at 12:53AM

Show HN: RAG Web UI – Possibly the Most Beginner-Friendly RAG Knowledge Base https://ift.tt/7UxAwnd

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/yptH5N3 January 22, 2025 at 09:35PM

Show HN: CloudCoil – Production-ready Python client for cloud-native ecosystem https://ift.tt/tWZkQRy

Show HN: CloudCoil – Production-ready Python client for cloud-native ecosystem Show HN: CloudCoil – Production-ready Python client for the cloud-native ecosystem I built CloudCoil ( https://ift.tt/g0pYqlj ) to make cloud-native development in Python feel first-class, starting with a modern async Kubernetes client. Frustrated with existing tools that felt like awkward ports from Go/Java, I focused on creating an API that Python developers would actually enjoy using. Installation is as simple as: uv add cloudcoil[kubernetes] # Using uv (recommended) pip install cloudcoil[kubernetes] # Using pip Key features: - Elegant, truly Pythonic API that follows Python idioms - Async-first with native async/await (but sync works too!) - Full type safety with MyPy + Pydantic - Zero-config pytest fixtures for K8s integration testing Quick taste of the API: # It's this simple to work with resources service = k8s.core.v1.Service.get("kubernetes") # Async iteration feels natural async for pod in await k8s.core.v1.Pod.async_list(): print(f"Found pod: {pod.metadata.name}") # Create resources with pure Python syntax deployment = k8s.apps.v1.Deployment( metadata=dict(name="web"), spec=dict(replicas=3) ).create() The ecosystem is growing! We already have first-class integrations for: - cert-manager (cloudcoil.models.cert_manager) - FluxCD (cloudcoil.models.fluxcd) - Kyverno (cloudcoil.models.kyverno) Missing your favorite operator? I've made it super easy to add new integrations using our cookiecutter template and codegen tools. I'd especially love feedback on: 1. The API design - does it feel natural to Python devs? 2. Testing features - what else would make k8s testing easier? 3. Which operators/CRDs you'd most like to see integrated next Check out https://ift.tt/g0pYqlj or try it out with PyPI: cloudcoil https://ift.tt/g0pYqlj January 22, 2025 at 03:26AM

Show HN: Pytest-evals – Simple LLM apps evaluation using pytest https://ift.tt/0WsQuIz

Show HN: Pytest-evals – Simple LLM apps evaluation using pytest https://ift.tt/safyUEw January 21, 2025 at 11:33PM