Show HN: Modern CI/CD Platform for Kubernetes https://bit.ly/4dgBNxT

Show HN: Modern CI/CD Platform for Kubernetes https://bit.ly/3wHU3Mt September 18, 2024 at 05:47AM

Show HN: I'm making a text editor for desktop (gonna build AI in it soon) https://bit.ly/4ejFUdS

Show HN: I'm making a text editor for desktop (gonna build AI in it soon) https://bit.ly/4ejFUuo September 18, 2024 at 03:55AM

Show HN: Exocortex – Encrypted Note-Taking Desktop App for Networked Thought https://bit.ly/3B8VCdq

Show HN: Exocortex – Encrypted Note-Taking Desktop App for Networked Thought https://bit.ly/3MUihfT September 16, 2024 at 11:51PM

Show HN: Fragaria – From 'R's in Strawberry to Complex Problem-Solving AI https://bit.ly/4e52Ai8

Show HN: Fragaria – From 'R's in Strawberry to Complex Problem-Solving AI I'm excited to share Fragaria, an open-source project that brings advanced AI reasoning capabilities to developers and researchers. Named after the botanical genus of strawberries (a nod to the classic "How many 'r's in strawberry?" problem), Fragaria is designed to tackle both simple queries and complex logical puzzles with increasing efficiency over time. Here are some features! * Multi-Provider Support: Seamlessly switch between OpenAI, Groq, and Together.ai as LLM providers. * Chain of Thought (CoT) Reasoning: Break down complex problems into step-by-step solutions. * Reinforcement Learning: Continuously improve problem-solving strategies through a novel approach combining CoT and RL. * Adaptive Learning: Utilize a SQLite-based scoring system to remember and refine successful strategies. * Easy Integration: RESTful API with OpenAI-compatible endpoints for drop-in replacement in existing projects. What makes Fragaria unique: * More than just another LLM wrapper. Fragaria implements a sophisticated reasoning process that grows more efficient with each solved problem. * The combination of CoT and RL allows Fragaria to develop novel problem-solving approaches that weren't explicitly programmed. * It's designed for researchers to easily experiment with different CoT strategies and RL algorithms. The project includes a sleek Svelte-based demo interface for easy visualization of the reasoning process. I built Fragaria to explore the intersection of language models, reasoning, and reinforcement learning. https://bit.ly/3XrFHhQ September 17, 2024 at 12:28AM

Show HN: React SaaS – Boilerplate with automated setup of dev/prod environments https://bit.ly/3XNERgN

Show HN: React SaaS – Boilerplate with automated setup of dev/prod environments After accidentally nuking the production database of my last side project, I wished I had used dev/prod environments with automated DB backups. When I looked for a SaaS template to start over with integrated dev/prod environments, I couldn’t find one. So I decided to build it myself. To help speed up the setup, I also built Bash and PowerShell scripts to guide users through the process. The current stack is Next.js, Firebase, and Stripe. However, I’m considering writing some Terraform modules for GCP resources to further speed up setup and provide more flexibility for power users. Would love to get your feedback! https://bit.ly/4ehkm1k September 17, 2024 at 12:12AM

Show HN: Sisi – Semantic Image Search CLI tool, locally without third party APIs https://bit.ly/47tl9Ke

Show HN: Sisi – Semantic Image Search CLI tool, locally without third party APIs I wrote this tool to get familiar with CLIP model, I know many people have written similar tools with CLIP before, but I'm new to machine learning and writing a classic tool helps my study. The unusual thing with my version is, it is in pure Node.js, with the power of node-mlx, a Node.js machine learning framework. The repo in the link is mostly about implementing indexing and CLI, the code of the model implementation lives as a Node.js module: https://bit.ly/3XGFSXL . Hope this helps other learners! https://bit.ly/3XJviiE September 16, 2024 at 11:59AM

Show HN: JAQT – JavaScript Queries and Transformations https://bit.ly/4e7u7zA

Show HN: JAQT – JavaScript Queries and Transformations Hi all, I've made a javascript library to simplify searching/sorting/filtering in arrays of objects. Its inspired by both GraphQL and SQL, but implemented using javascript Proxies. Instead of creating a new language, its all just javascript. I've made it as part of an experimental database, which uses javascript as the query engine. The normal javascript map/reduce/sort functions are quite difficult to master for junior developers. JAQT is easier to explain, and can still be used in combination with any existing array functions. Please let me know what you think of the API and its ease of use! https://bit.ly/4d6K0F8 September 16, 2024 at 10:08AM

Show HN: Looksmax AI – Receive Personalized Tips to Enhance Your Appearance https://bit.ly/47vSKn6

Show HN: Looksmax AI – Receive Personalized Tips to Enhance Your Appearance https://bit.ly/3XqLl3x September 16, 2024 at 05:36AM

Show HN: CAD with AI https://bit.ly/3ZxezQS

Show HN: CAD with AI https://bit.ly/3ZrAysD September 16, 2024 at 02:26AM

Show HN: I build Figma plugin for unlimited themes/modes https://bit.ly/4d4dHXb

Show HN: I build Figma plugin for unlimited themes/modes Hi everyone, I’ve created a new Token Swapper plugin for Figma to address limitations I encountered while working on a multi-brand mobile app UI. The Figma’s Pro plan’s 4 Modes (or even the Enterprise plan’s 40 Modes) weren’t sufficient for my needs. I made Token Swapper to quickly switch between themes (based on variables and styles) without relying on Modes. The only requirement is that you organize your themes in top-level folders within both the variables and styles sections. I’d love for you to try it out and share your thoughts. Your feedback is appreciated! https://bit.ly/3TvADrk September 14, 2024 at 08:01PM

Show HN: Wordllama – Things you can do with the token embeddings of an LLM https://bit.ly/3XIfooF

Show HN: Wordllama – Things you can do with the token embeddings of an LLM After working with LLMs for long enough, I found myself wanting a lightweight utility for doing various small tasks to prepare inputs, locate information and create evaluators. This library is two things: a very simple model and utilities that inference it (eg. fuzzy deduplication). The target platform is CPU, and it’s intended to be light, fast and pip installable — a library that lowers the barrier to working with strings semantically . You don’t need to install pytorch to use it, or any deep learning runtimes. How can this be accomplished? The model is simply token embeddings that are average pooled. To create this model, I extracted token embedding (nn.Embedding) vectors from LLMs, concatenated them along the embedding dimension, added a learnable weight parameter, and projected them to a smaller dimension. Using the sentence transformers framework and datasets, I trained the pooled embedding with multiple negatives ranking loss and matryoshka representation learning so they can be truncated. After training, the weights and projections are no longer needed, because there is no contextual calculations. I inference the entire token vocabulary and save the new token embeddings to be loaded to numpy. While the results are not impressive compared to transformer models, they perform well on MTEB benchmarks compared to word embedding models (which they are most similar to), while being much smaller in size (smallest model, 32k vocab, 64-dim is only 4MB). On the utility side, I’ve been adding some tools that I think it’ll be useful for. In addition to general embedding, there’s algorithms for ranking, filtering, clustering, deduplicating and similarity. Some of them have a cython implementation, and I’m continuing to work on benchmarking them and improving them as I have time. In addition to “standard” models that use cosine similarity for some algorithms, there are binarized models that use hamming distance. This is a slightly faster, similarity algorithm, with significantly less memory per embedding (float32 -> 1 bit). Hope you enjoy it, and find it useful. PS I haven’t figured out Windows builds yet, but Linux and Mac are supported. https://bit.ly/3XIfoFb September 15, 2024 at 04:25AM

Show HN: Insta2000 – Re-render Instagram locally, retro, and ad free https://bit.ly/4d1bMTi

Show HN: Insta2000 – Re-render Instagram locally, retro, and ad free I've been avoiding instagram for a few years, as it feels very noisy and addictive. I'm starting to feel out of touch from friends though, so got wondering if I could build a tool to get just my friends updates, without all the other junk. It turns out scraping my own profile and re-rendering a static webpage is quite a successful way to achieve that goal. It has no ads, no discovery injections, no trackers, no infinite scroll, no notifications. It does include stories and posts alongside each other. It does sort things based on recent updates. In the end, it proved better than I expected with a relatively small effort. I made it retro as well just for a fun throwback, and as a protest against the modern web! It leans very heavily on the [instaloader package]( https://bit.ly/47qNhhg I'm quite grateful for the contributors there! Repo is yours to use and build on, and feel free to contribute as well. https://bit.ly/3Txra30 September 15, 2024 at 02:01AM

Show HN: I made a digital circuit drawing and simulation game https://bit.ly/4gsUe5m

Show HN: I made a digital circuit drawing and simulation game Inspired by games like Turing Complete/Virtual Circuit Board/Logic World, I tried to make a mix of aseprite and wiredworld/wired-logic, the idea being the user can build a digital circuit using a "fullstack" pixelart creation workflow. The circuit is just an image. The primitives are (i) connected wires which have undefined, 0 or 1 state during simulation (displayed brighter or darker in function of the state) and (ii) NANDs, which are little pixel triangles. During simulation the user can interact with any wire by clicking on it, toggling its state, which is cool for messing around when learning. The simulation uses a unit-delay event driven algorithm. Then, on top of that there are little wire interfaces on the left side of the image that communicate with an external system. This external system is defined in lua and is simulated together with the main circuit (they alternate until convergence). By default there's a sandbox mode with a clock and a power-on-reset signal. The user can choose other "levels", where the API change and there are some problems to solve, from finding if a number is multiple of 3 to solving hanoi tower to finding if a number is prime. The idea is that if the user want to learn but not sure what to do they can try to solve these puzzles, or they can change the lua scripts to add their own stuff/interface for a custom project. I've also included a small wiki (circuitopedia) with some basic digital concepts to guide those who are new or are a bit rusty. It's not super detailed but I guess it can at the very least present the concepts so the user can dig further on more serious material if they want to. I developed the game in C with raylib, with scripting in lua/luajit. I've put the game on steam (for windows) and released the source code on github under GPLv3. There's also a web demo version on itch.io, even though it's a bit laggy: https://bit.ly/3ZwrAds... . Feedback is appreciated! https://bit.ly/3XI0izF September 14, 2024 at 11:43PM

Show HN: Strip-windows.ps1 – this could get smaller in the right hands https://bit.ly/4e401N8

Show HN: Strip-windows.ps1 – this could get smaller in the right hands https://bit.ly/3TrfKNW September 14, 2024 at 05:25AM

Show HN: Built a Cookie Clicker Clone in Google Sheets https://bit.ly/3B0lIPM

Show HN: Built a Cookie Clicker Clone in Google Sheets https://www.youtube.com/watch?v=r4Z8MdYm1_s September 14, 2024 at 03:23AM

Show HN: Ftail – logger for Rust with multiple drivers (console/daily file/etc.) https://bit.ly/3XIL3qk

Show HN: Ftail – logger for Rust with multiple drivers (console/daily file/etc.) https://bit.ly/4gqRq96 September 13, 2024 at 07:57PM

Show HN: Search San Francisco using natural language https://bit.ly/3TqDMc5

Show HN: Search San Francisco using natural language Hey HN! We're Alex and Szymon from Bluesight ( https://bit.ly/3TQumqH ), where we're developing a foundation model for satellite data. We've created a demo to showcase the current capabilities of state-of-the-art models and identify areas for improvement. Our demo allows you to search for objects in San Francisco using natural language. You can look for things like Tesla cars, dry patches, boats, and more. Key features: - Search using text or by selecting an object from the image as a source ("aim" icon) - Toggle between object search (default) and tile search ("big" toggle, useful when contextual information matters, like tennis courts) - Adjust results with downvotes (useful when results are water images) - Click on tiles to locate them on a map - Control the number of retrieved tiles with a slider We use OpenAI's CLIP model ( https://bit.ly/3ZnyIZL ) to put texts and images into the same embedding space. We do a similarity search within this space using text query or source image. We are using CLIP finetuned on pairs of satellite images and OpenStreetMap ( https://bit.ly/3TsY8Bg ) tags ( https://bit.ly/3ZipzSh ) because vanilla clip performs poorly on satellite data. We pre-segment objects using Meta's Segment Anything Model ( https://bit.ly/3ZqkMy6 ) and pre-compute CLIP embeddings for each object. We'd love to hear your thoughts! What worked well for you? Where did it fail? What features do you wish it had? Any real-world problems you think this could help with? https://bit.ly/3z5wCmM September 12, 2024 at 06:06PM

Show HN: A whiteboard that writes math equations https://bit.ly/3AVDrrl

Show HN: A whiteboard that writes math equations https://bit.ly/3XFXbIp September 9, 2024 at 01:23PM

Show HN: Interested in an automated fact checking service? https://bit.ly/3XhbS3a

Show HN: Interested in an automated fact checking service? Hey everyone, I'm working on an automated fact checking service that works like so: 1. Paste a link to the website, X or facebook comment you want to fact check, 2. Select a quote on the site, 3. We search for relevant results from research databases, reputable news sites and searches on the web, 4. You get a web page with the quote, fact check rating, summary of the findings and sources, 5. Share that fact check back to the source, so people can be aware of the relevant information. This is a work in progress (currently a landing page) and I'd love to know if you are interested in it (it's worth me continuing to work on). Would love to hear your opinions or ideas :) https://bit.ly/3TtnizM September 13, 2024 at 07:46AM

Show HN: Fabrix – Instantly Generate UI Frontend from GraphQL https://bit.ly/4d8ZUP4

Show HN: Fabrix – Instantly Generate UI Frontend from GraphQL https://bit.ly/3XrfoIA September 12, 2024 at 11:10PM