Show HN: Rivet – open-source AI Agent dev env with real-world applications https://bit.ly/3RaoGXJ

Show HN: Rivet – open-source AI Agent dev env with real-world applications We just launched Rivet, the open-source visual AI programming environment! We built Rivet, because we were building complex AI Agent applications at Ironclad. It unlocked our abilities here, and we're excited to make available to the entire community. Backstory: A few months ago, inspired by things like LangChain and LlamaIndex, we started building an AI agent that could work with legal contracts. Unfortunately, we couldn't just use retrieval augmented generation (RAG), because a lot of contracts are basically identical (many chunks with near-identical embeddings), except for a few key details. So, we turned to things like ReAct and AutoGPT for inspiration. At first, things went great. We were adding agent capabilities, doing chain-of-thought prompting. But then we hit a wall. The agent became too complex. We had debugger breakpoints on almost every line of code, but we still had no idea where the agent was breaking. Every change we made destabilized something else. After two weeks of fumbling, I decided to end the project. But one of my teammates, Andy, didn't give up. The following week, he showed me v0 of Rivet. He'd used it to refactor and improve our existing agent. I was skeptical... it just seemed like a visual programming environment, and I was not a fan. But I gave it a shot, and suddenly found myself able to add new skills to the agent, debug brittle areas with ease, and update prompts with confidence. Rivet is a game-changer. And more than that, it makes building with LLMs super fun. What exactly makes it different? First, the debugger is incredible. You have to experience it to believe it. You can update a graph, and then immediately run it, and see where it succeeded or failed. Even better: you can attach Rivet as a remote debugger, and watch your agent graphs execute in your app. Second, visual programming is actually a game-changer for prompting LLMs. I don't know why exactly, but it's way easier to understand and organize your work when you have an extra dimension to work with. Finally, Rivet is built to be embedded into a larger application (TypeScript for now, but we've also found a way to run it in Python). Beyond importing Rivet as a dependency, you can also define "external functions" dynamically at run-time. It feels pretty sketchy to give a LLM a key and unfettered access to an API. With Rivet, you can give it access to a specific set of defined functions, potentially pre-scoped to the access level you want. ...Sorry that was long. If you read this whole thing, thank you! We're really excited to hear what you think! We just launched our first Rivet-based application at Ironclad, and we've been working with companies like Sourcegraph, Attentive, AssemblyAI, Bento, and Willow to make Rivet useful for others. https://bit.ly/462leml September 8, 2023 at 02:29PM

Show HN: Rocketify – your one-stop shop for growth hacking tools https://bit.ly/45zol5n

Show HN: Rocketify – your one-stop shop for growth hacking tools https://bit.ly/3Lfwy6D September 8, 2023 at 07:43AM

Show HN: Yggdrasil 1.0 – Native executables for Shen https://bit.ly/3P3RHSm

Show HN: Yggdrasil 1.0 – Native executables for Shen Yggdrasil allows for the generation of type secure stand-alone native language programs from Shen source programs. We are pleased to announce the release of Yggdrasil 1.0 which has a plug-in configured for Common Lisp. Yggdrasil requires Shen 34.6 which is now available from https://bit.ly/3rdISNP . Questions to https://bit.ly/3Pv1kLi . More details on Yggdrasil can be found at https://bit.ly/3PtbCf0 . September 7, 2023 at 07:29AM

Show HN: Study hack using AI powered article-to-podcast tool https://bit.ly/3PwqTeM

Show HN: Study hack using AI powered article-to-podcast tool https://bit.ly/3ZaJqAF September 8, 2023 at 04:10AM

Show HN: Nero Burning ROM X Muse – The Burning Art of CD https://bit.ly/3Ewg1Ye

Show HN: Nero Burning ROM X Muse – The Burning Art of CD Hi HN, Have you heard of Nero Burning ROM? It was named after 'the Great Fire of Rome' as a pun. We are thrilled to announce that we're back with an AI-powered new product called 'Nero Muse' – a CD/Album cover generator. It's the great fire of virtuality now. :) https://bit.ly/489sKOf September 8, 2023 at 02:56AM

Show HN: HackYourNews – AI summaries of the top HN stories https://bit.ly/3PvyYkc

Show HN: HackYourNews – AI summaries of the top HN stories Hey there HN! I wanted to share a pet project of mine. I built HackYourNews [1] to scratch a personal itch: Knowing which stories to focus on while browsing aimlessly (though there is a certain joy in that, as well!) HackYourNews uses OpenAI's gpt-3.5-turbo to summarize the destination article as well as the comments section. Summarization of the article is always cached, while summaries of the comments are regenerated if the comments count is >10% (or >10 comments) different. While I styled the homepage to welcome HNers, my preferred view is the Mobile view, accessed from the navbar. This no-frills view honors OS-level dark mode and is easy to skim on any device. Tried to keep the site minimal. The only JS is Cloudflare's privacy-preserving analytics [2], just to gauge interest. This is the first time I'm releasing something to the wild. Hope you find this useful! The frontend is pure HTML+CSS. The backend is Python with the excellent Microsoft Guidance [3] library to interface to OpenAI's API. [1] https://bit.ly/3PbUaKs [2] https://bit.ly/3Pcz8eZ [3] https://bit.ly/3PtVXMf https://bit.ly/3PbUaKs September 8, 2023 at 12:30AM

Show HN: SeoBot – An Autopilot for Programmatic SEO https://bit.ly/3PE7h8Z

Show HN: SeoBot – An Autopilot for Programmatic SEO https://bit.ly/44K28Ar September 7, 2023 at 10:57AM

Show HN: AI Chatbot for WordPress https://bit.ly/3Pbho3k

Show HN: AI Chatbot for WordPress https://bit.ly/3Pbhp7o September 7, 2023 at 01:28PM

Show HN: Security Compliance in Context (I am starting a side project) https://bit.ly/460kHRN

Show HN: Security Compliance in Context (I am starting a side project) https://bit.ly/44CxXet September 7, 2023 at 01:07PM

Show HN: All visitors pointers on a webpage (How-to) https://bit.ly/44KrHkC

Show HN: All visitors pointers on a webpage (How-to) https://bit.ly/44NITpn September 7, 2023 at 12:26PM

Show HN: Curated custom search engine portal https://bit.ly/44L1S45

Show HN: Curated custom search engine portal Hey friends, a little background - A friend of mine who’s also a newsletter writer once told me that when he’s interested in certain topic he would like to know the opinion of some of his favorite writers on the same topic. He would use Google to search something like discomfort site:sive.rs, and then expand his search across various authors he admires. It turns out that Google’s programmable search engine does exactly that. By simply adding a few websites (much like subscribing to newsletters or RSS feeds), we can craft a search engine tailored for our specific needs. I think that's a great idea - more signal and less noise. So I built a portal to facilitate sharing personal curations https://bit.ly/3L9umgL . Thanks for reading, lemme know what you think :D https://bit.ly/3L9umgL September 7, 2023 at 06:49AM

Show HN: Formstr: An open source and decentralized alternative to Google Forms https://bit.ly/3Rfgupd

Show HN: Formstr: An open source and decentralized alternative to Google Forms https://bit.ly/3sFqhux September 7, 2023 at 04:24AM

Show HN: uDSV.js – A faster CSV parser https://bit.ly/3PsrLAf

Show HN: uDSV.js – A faster CSV parser Hey folks! I know CSV parsers (especially in JS) aren't terribly exciting and someone writes a "better" one every week. I'm in the middle of my parental leave, and this was a project that came out of me looking for the fastest/smallest CSV parser. It all started so innocently, and then turned into a benchmark-validation-athon; the library itself took ~2 weeks to write, but the performance comparisons took another ~4 weeks (on and off). The benchmarks were a huge effort, but I think they are the most thorough to date, both in breadth and in depth, so hopefully you find them useful: https://bit.ly/3rcacfk Let me know if you have specific concerns / questions / improvements :) cheers! Leon https://bit.ly/48gnXKW September 4, 2023 at 05:04PM

Show HN: A better way to read blogs https://bit.ly/3RawBEH

Show HN: A better way to read blogs https://bit.ly/3R4gFUm September 6, 2023 at 12:12PM

Show HN: Automated Pull Request Reviews https://bit.ly/45FcAdM

Show HN: Automated Pull Request Reviews https://bit.ly/3sDeTPH September 6, 2023 at 06:42AM

Show HN: I built an extension that never lets you overpay for a book again https://bit.ly/45YZ849

Show HN: I built an extension that never lets you overpay for a book again https://bit.ly/461jxFA September 6, 2023 at 02:40AM

Show HN: ColorMood https://bit.ly/3P6Wwu7

Show HN: ColorMood Does your mood affect which color you like - a tool that attempts to find your favourite color right now https://bit.ly/3P6WwKD September 6, 2023 at 05:48AM

Show HN: Trellis – open-source Python framework to build DAG-based LLM workflows https://bit.ly/44Hheq8

Show HN: Trellis – open-source Python framework to build DAG-based LLM workflows Hey HN! Trellis is an open-source framework for programmatically orchestrating LLM workflows as Directed Acyclic Graphs (DAGs) in Python. My friend and I started working on this a few weeks ago after we tried building applications using mainstream LLM frameworks, and faced all the common complaints (too abstracted, hard to customize, bad docs/support). After talking to a few other people building with LLMs, we also noticed that these frameworks were not inherently built to support DAG-based LLM workflows. We designed Trellis to be as minimal and flat as possible, so developers can have lower level control over their DAGs. Trellis is composed of only three abstractions: Node, DAG, and LLM. Node: the atomic unit of Trellis. Nodes are chained together to form a DAG. Node is an abstract class with only one method required to implement. DAG: a directed acyclic graph of Nodes. It is the primary abstraction for orchestrating LLM workflows. When you add edges between Nodes, you can specify a transformation function to reuse Nodes and connect any two Nodes. Trellis verifies the data flowing between Nodes in a DAG to ensure the flow of data is validated. LLM: a wrapper around a large language model with simple catches for common OpenAI errors. Currently, the only provider that Trellis supports is OpenAI. Check out our docs if this sounds interesting: https://bit.ly/3EsVio1... We'd love it if you tried hacking with it and give us any feedback you have! :) https://bit.ly/3sHq4XJ September 6, 2023 at 03:04AM

Show HN: Fully client-side GPT2 prediction visualizer https://bit.ly/45TSJHe

Show HN: Fully client-side GPT2 prediction visualizer https://bit.ly/45HJM4g September 5, 2023 at 11:42PM

Show HN: Simple passwordless authentication for your website https://bit.ly/45APSU3

Show HN: Simple passwordless authentication for your website Solo founder here - built a passwordless authentication service after getting frustrated with the very high pricing and lack of customizability, easy passwordless authentication on existing solutions. Check it out here and let me know what you think! https://bit.ly/45FSkbS September 5, 2023 at 08:47AM