The best Hacker News stories from Show from the past week
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Show HN: Free e-book about WebGPU Programming
I am excited to announce the launch of my e-book on Graphics/WebGPU programming! This project has consumed much of my spare time, during which I developed various tools to facilitate the publishing process, including a code playground and a static site generator that can reference sample codes.<p>However, I'm feeling burnt out and ready to call it finished, even though it may not feel completely done. Avoiding another abandoned side project has been my primary motivation in reaching this point.
Show HN: Hanon Pro – piano technique and exercises for the digital age
Show HN: Ell – A command-line interface for LLMs written in Bash
Hi HN!<p>I've created a CLI tool called "ell" that allows you to interact with LLMs directly from your terminal. Designed with the Unix philosophy in mind, ell is simple, modular, and extensible. You can easily pipe input and output to integrate with other tools. Its templates and hook-based plugins enable you to customize and extend its functionality to suit any needs. Check out the README for usage instructions and examples.<p>I developed this tool because existing solutions often felt too heavy, with many dependencies, or they weren't friendly to piping and customization. I, on the contrary, wrote in almost pure Bash with least dependencies. Additionally, I found a lack of tools that could read past terminal output as context. Imagine encountering an issue in your terminal and being able to directly ask an LLM for help with a simple command—this is now possible with ell (see the demo video).<p>Known limitations:<p>- To maintain simplicity and efficiency, jq is used for JSON parsing.<p>- Cannot avoid curl to sending HTTPS requests. If only there were SSL / TLS support in `/dev/tcp/`!<p>- Perl is used to handle terminal escape sequences because regex in Bash does not support looking around.<p>- Markdown syntax highlighting is not perfect due to the need for streaming output. It relies on a simple state machine instead of a full parser, which may produce falsy results.<p>- Other known issues are listed in Github Issues. Please help add more!<p>I welcome any criticism and suggestions, whether it's about the idea or code!
Show HN: Turn any website into a knowledge base for LLMs
I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications.<p>It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically.<p>I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
Show HN: Turn any website into a knowledge base for LLMs
I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications.<p>It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically.<p>I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
Show HN: Create diagrams of complex data flows in software systems
Hello HN,<p>It has been a while since I contributed to the web, so I decided to get back in shape and publish "something".<p>This app is a POC of "what if diagrams were more dynamic".
I'm a software engineer by trade, and with conventional tools, I often times struggle to explain flows of data in complex software systems.<p>I got inspired by video games like The Incredible Machine and Factorio, as in some ways, software systems tend to become Rube Goldberg-esque machines ;)
As a side quest, I also wanted to craft diagrams faster than text-based tools (ex: mermaid), as I am always forgetting their syntax.<p>If you try the app, you will certainly struggle with its UI, especially when crafting flows, as I used all my brain juice on the core idea.
I have cool features in my head for a v1 but today I really wanted to simply show what I got.<p>You can access the app directly at <a href="https://gg-charts.com" rel="nofollow">https://gg-charts.com</a> and there are some examples in the Github README to get you started.<p>Happy to answer questions and humbly receive your honest feedback on this crazy idea!
Show HN: Create diagrams of complex data flows in software systems
Hello HN,<p>It has been a while since I contributed to the web, so I decided to get back in shape and publish "something".<p>This app is a POC of "what if diagrams were more dynamic".
I'm a software engineer by trade, and with conventional tools, I often times struggle to explain flows of data in complex software systems.<p>I got inspired by video games like The Incredible Machine and Factorio, as in some ways, software systems tend to become Rube Goldberg-esque machines ;)
As a side quest, I also wanted to craft diagrams faster than text-based tools (ex: mermaid), as I am always forgetting their syntax.<p>If you try the app, you will certainly struggle with its UI, especially when crafting flows, as I used all my brain juice on the core idea.
I have cool features in my head for a v1 but today I really wanted to simply show what I got.<p>You can access the app directly at <a href="https://gg-charts.com" rel="nofollow">https://gg-charts.com</a> and there are some examples in the Github README to get you started.<p>Happy to answer questions and humbly receive your honest feedback on this crazy idea!
Show HN: I made a tool to receive alerts when answers change
Hi HN,<p>I've created a tool called Alertfor that scours the open web to find the most relevant and up-to-date answers for complex questions. You can set up alerts to receive continuous updates whenever there are changes or new information becomes available for a given question.<p>I used an agent framework (Autogen + Sibyl) to collect and answer questions, and I schedule a Celery job to run the same query continuously every six hours.<p>I would love to hear your feedback, suggestions, or anything else you’d like to say.<p>Note: I'm submitting this for a second time; I'm not sure if this is against HN policy.
Show HN: A football/soccer pass visualizer made with Three.js
I've been working on a football pass visualiser for the past week.<p>It uses open data from StatsBomb to analyse and visualise passing patterns, allowing users to explore and filter the data by pass distance, team and players.
Show HN: I built an open-source tool to make on-call suck less
Hey HN,<p>I am building an open source platform to make on-call better and less stressful for engineers. We are building a tool that can silence alerts and help with debugging and root cause analysis. We also want to automate tedious parts of being on-call (running runbooks manually, answering questions on Slack, dealing with Pagerduty).
Here is a quick video of how it works: <a href="https://youtu.be/m_K9Dq1kZDw" rel="nofollow">https://youtu.be/m_K9Dq1kZDw</a><p>I hated being on-call for a couple of reasons:<p>* Alert volume: The number of alerts kept increasing over time. It was hard to maintain existing alerts. This would lead to a lot of noisy and unactionable alerts. I have lost count of the number of times I got woken up by alert that auto-resolved 5 minutes later.<p>* Debugging: Debugging an alert or a customer support ticket would need me to gain context on a service that I might not have worked on before. These companies used many observability tools that would make debugging challenging. There are always a time pressure to resolve issues quickly.<p>There were some more tangential issues that used to take up a lot of on-call time<p>* Support: Answering questions from other teams. A lot of times these questions were repetitive and have been answered before.<p>* Dealing with PagerDuty: These tools are hard to use. e.g. It was hard to schedule an override in PD or do holiday schedules.<p>I am building an on-call tool that is Slack-native since that has become the de-facto tool for on-call engineers.<p>We heard from a lot of engineers that maintaining good alert hygiene is a challenge.<p>To start off, Opslane integrates with Datadog and can classify alerts as actionable or noisy.<p>We analyze your alert history across various signals:<p>1. Alert frequency<p>2. How quickly the alerts have resolved in the past<p>3. Alert priority<p>4. Alert response history<p>Our classification is conservative and it can be tuned as teams get more confidence in the predictions. We want to make sure that you aren't accidentally missing a critical alert.<p>Additionally, we generate a weekly report based on all your alerts to give you a picture of your overall alert hygiene.<p>What’s next?<p>1. Building more integrations (Prometheus, Splunk, Sentry, PagerDuty) to continue making on-call quality of life better<p>2. Help make debugging and root cause analysis easier.<p>3. Runbook automation<p>We’re still pretty early in development and we want to make on-call quality of life better. Any feedback would be much appreciated!
Show HN: I built an open-source tool to make on-call suck less
Hey HN,<p>I am building an open source platform to make on-call better and less stressful for engineers. We are building a tool that can silence alerts and help with debugging and root cause analysis. We also want to automate tedious parts of being on-call (running runbooks manually, answering questions on Slack, dealing with Pagerduty).
Here is a quick video of how it works: <a href="https://youtu.be/m_K9Dq1kZDw" rel="nofollow">https://youtu.be/m_K9Dq1kZDw</a><p>I hated being on-call for a couple of reasons:<p>* Alert volume: The number of alerts kept increasing over time. It was hard to maintain existing alerts. This would lead to a lot of noisy and unactionable alerts. I have lost count of the number of times I got woken up by alert that auto-resolved 5 minutes later.<p>* Debugging: Debugging an alert or a customer support ticket would need me to gain context on a service that I might not have worked on before. These companies used many observability tools that would make debugging challenging. There are always a time pressure to resolve issues quickly.<p>There were some more tangential issues that used to take up a lot of on-call time<p>* Support: Answering questions from other teams. A lot of times these questions were repetitive and have been answered before.<p>* Dealing with PagerDuty: These tools are hard to use. e.g. It was hard to schedule an override in PD or do holiday schedules.<p>I am building an on-call tool that is Slack-native since that has become the de-facto tool for on-call engineers.<p>We heard from a lot of engineers that maintaining good alert hygiene is a challenge.<p>To start off, Opslane integrates with Datadog and can classify alerts as actionable or noisy.<p>We analyze your alert history across various signals:<p>1. Alert frequency<p>2. How quickly the alerts have resolved in the past<p>3. Alert priority<p>4. Alert response history<p>Our classification is conservative and it can be tuned as teams get more confidence in the predictions. We want to make sure that you aren't accidentally missing a critical alert.<p>Additionally, we generate a weekly report based on all your alerts to give you a picture of your overall alert hygiene.<p>What’s next?<p>1. Building more integrations (Prometheus, Splunk, Sentry, PagerDuty) to continue making on-call quality of life better<p>2. Help make debugging and root cause analysis easier.<p>3. Runbook automation<p>We’re still pretty early in development and we want to make on-call quality of life better. Any feedback would be much appreciated!
Show HN: I built an open-source tool to make on-call suck less
Hey HN,<p>I am building an open source platform to make on-call better and less stressful for engineers. We are building a tool that can silence alerts and help with debugging and root cause analysis. We also want to automate tedious parts of being on-call (running runbooks manually, answering questions on Slack, dealing with Pagerduty).
Here is a quick video of how it works: <a href="https://youtu.be/m_K9Dq1kZDw" rel="nofollow">https://youtu.be/m_K9Dq1kZDw</a><p>I hated being on-call for a couple of reasons:<p>* Alert volume: The number of alerts kept increasing over time. It was hard to maintain existing alerts. This would lead to a lot of noisy and unactionable alerts. I have lost count of the number of times I got woken up by alert that auto-resolved 5 minutes later.<p>* Debugging: Debugging an alert or a customer support ticket would need me to gain context on a service that I might not have worked on before. These companies used many observability tools that would make debugging challenging. There are always a time pressure to resolve issues quickly.<p>There were some more tangential issues that used to take up a lot of on-call time<p>* Support: Answering questions from other teams. A lot of times these questions were repetitive and have been answered before.<p>* Dealing with PagerDuty: These tools are hard to use. e.g. It was hard to schedule an override in PD or do holiday schedules.<p>I am building an on-call tool that is Slack-native since that has become the de-facto tool for on-call engineers.<p>We heard from a lot of engineers that maintaining good alert hygiene is a challenge.<p>To start off, Opslane integrates with Datadog and can classify alerts as actionable or noisy.<p>We analyze your alert history across various signals:<p>1. Alert frequency<p>2. How quickly the alerts have resolved in the past<p>3. Alert priority<p>4. Alert response history<p>Our classification is conservative and it can be tuned as teams get more confidence in the predictions. We want to make sure that you aren't accidentally missing a critical alert.<p>Additionally, we generate a weekly report based on all your alerts to give you a picture of your overall alert hygiene.<p>What’s next?<p>1. Building more integrations (Prometheus, Splunk, Sentry, PagerDuty) to continue making on-call quality of life better<p>2. Help make debugging and root cause analysis easier.<p>3. Runbook automation<p>We’re still pretty early in development and we want to make on-call quality of life better. Any feedback would be much appreciated!
Show HN: Semantic Grep – A Word2Vec-powered search tool
Much improved new version. Search for words similar to the query. For example, "death" will find "death", "dying", "dead", "killing"... Incredibly useful for exploring large text datasets where exact matches are too restrictive.
Show HN: Semantic Grep – A Word2Vec-powered search tool
Much improved new version. Search for words similar to the query. For example, "death" will find "death", "dying", "dead", "killing"... Incredibly useful for exploring large text datasets where exact matches are too restrictive.
Show HN: Semantic Grep – A Word2Vec-powered search tool
Much improved new version. Search for words similar to the query. For example, "death" will find "death", "dying", "dead", "killing"... Incredibly useful for exploring large text datasets where exact matches are too restrictive.
Show HN: Wat – Deep inspection of Python objects
Show HN: Wat – Deep inspection of Python objects
Show HN: Haystack – an IDE for exploring and editing code on an infinite canvas
Hi HN, we’re building Haystack Editor (<a href="https://haystackeditor.com/" rel="nofollow">https://haystackeditor.com/</a>), a canvas-based IDE that automates the boring stuff (plumbing, refactoring, and finding code) so that you can focus on the exciting parts of software development! You can see a quick overview of Haystack at <a href="https://www.youtube.com/watch?v=c2uZnR5D_cc" rel="nofollow">https://www.youtube.com/watch?v=c2uZnR5D_cc</a>!<p>(It's currently only on Mac OS but we're working on Linux and Windows. Edit: just added a Linux download!)<p>Haystack was born out of our frustrations with working in large and mature codebases, specifically with navigating and editing functional flows (e.g. the code flow for adding an item to the Amazon shopping cart).<p>Oftentimes dealing with such flows would involve navigating a maze of files and functions, and making any edits would involve a lengthy process of doing corresponding downstream/upstream plumbing.<p>Haystack attempts to address this in the following ways:<p><pre><code> 1. It allows you to explore your codebase as a directed graph of functions, classes, etc on the canvas. We feel like this better fits how your mind understands your codebase and helps you find and alter functional flows more intuitively. We especially want to utilize this for pull request reviews!
2. It has a navigational copilot that makes edits across files or functions much easier. After you make some changes, Haystack will try to predict your next action and create functions/methods or refactor upstream/downstream code for you. Haystack will surface these speculative edits on the canvas in a way that you can easily dismiss or incorporate them, allowing you to make large changes with a few clicks or keystrokes.
3. Haystack will utilize natural language search so you don’t have to play “Where’s Waldo” to find a functional flow in your codebase. This is coming soon!
</code></pre>
We’re still pretty early in development and we really want to perfect the experience of navigating and editing code on a canvas. Any feedback would be much appreciated!<p>PSA: Since Haystack is a VS Code fork, you should be able to move your extensions and keyboard shortcuts. Please let us know if you have any issues with this!
Show HN: Haystack – an IDE for exploring and editing code on an infinite canvas
Hi HN, we’re building Haystack Editor (<a href="https://haystackeditor.com/" rel="nofollow">https://haystackeditor.com/</a>), a canvas-based IDE that automates the boring stuff (plumbing, refactoring, and finding code) so that you can focus on the exciting parts of software development! You can see a quick overview of Haystack at <a href="https://www.youtube.com/watch?v=c2uZnR5D_cc" rel="nofollow">https://www.youtube.com/watch?v=c2uZnR5D_cc</a>!<p>(It's currently only on Mac OS but we're working on Linux and Windows. Edit: just added a Linux download!)<p>Haystack was born out of our frustrations with working in large and mature codebases, specifically with navigating and editing functional flows (e.g. the code flow for adding an item to the Amazon shopping cart).<p>Oftentimes dealing with such flows would involve navigating a maze of files and functions, and making any edits would involve a lengthy process of doing corresponding downstream/upstream plumbing.<p>Haystack attempts to address this in the following ways:<p><pre><code> 1. It allows you to explore your codebase as a directed graph of functions, classes, etc on the canvas. We feel like this better fits how your mind understands your codebase and helps you find and alter functional flows more intuitively. We especially want to utilize this for pull request reviews!
2. It has a navigational copilot that makes edits across files or functions much easier. After you make some changes, Haystack will try to predict your next action and create functions/methods or refactor upstream/downstream code for you. Haystack will surface these speculative edits on the canvas in a way that you can easily dismiss or incorporate them, allowing you to make large changes with a few clicks or keystrokes.
3. Haystack will utilize natural language search so you don’t have to play “Where’s Waldo” to find a functional flow in your codebase. This is coming soon!
</code></pre>
We’re still pretty early in development and we really want to perfect the experience of navigating and editing code on a canvas. Any feedback would be much appreciated!<p>PSA: Since Haystack is a VS Code fork, you should be able to move your extensions and keyboard shortcuts. Please let us know if you have any issues with this!
Show HN: We made glhf.chat – run almost any open-source LLM, including 405B
Try it out! <a href="https://glhf.chat/" rel="nofollow">https://glhf.chat/</a><p>Hey HN!<p>We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant.<p>Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and it’ll work (as long as vLLM supports the base model architecture, we’ll run anything up to ~640GB of VRAM, give or take a little for some overhead buffer).<p>Large models will take a few minutes to boot, but if a bunch of people are trying to use the same model, it might already be loaded and not need boot time at all. The Llama-3-70b finetunes are especially nice, since they’re basically souped-up versions of the 8b finetunes a lot of people like to run locally but don’t have the VRAM for. We’re expecting the Llama-3.1 finetunes to be pretty great too once they start getting released.<p>There are some caveats for now — for example, while we support the Deepseek V2 architecture, we actually can only run their smaller “Lite” models due to some underlying NVLink limitations (though we’re working on it). But for the most part if vLLM supports it, we should too!<p>We figured Llama-3.1-405B Launch Day was a good day to launch ourselves too — let us know in the comments if there’s anything you want us to support, or if you run into any issues. I know it’s not “local” Llama, but, well, that’s a lot of GPUs…