The best Hacker News stories from Show from the past day
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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: A personalised AI tutor with < 1s voice responses
TLDR: We created a personalised Andrej Karpathy tutor that can response to questions about his Youtube videos in sub 1 second responses (voice-to-voice). We do this using a voice enabled RAG agent. See later in the post for demo link, Github Repo and blog write up.<p>A few weeks ago we released the worlds fastest voice bot, achieving 500ms voice-to-voice response times, including a 200ms delay waiting for a user to stop speaking.<p>After reaching the front page of HN, we thought about how we could take this a step further based on feedback we were getting from the community. Many companies were looking for a way to implement function calling and RAG with voice interfaces while retaining a low enough latency. We couldn’t find many resources about how to do this online that:<p>1. Allowed us to achieve sub-second voice-to-voice latency
2. Was more flexible than existing solutions. Vapi, Retell, [Bland.ai](<a href="http://Bland.ai" rel="nofollow">http://Bland.ai</a>) are too opinionated plus since they just orchestrate API’s which incur network latency at every step. See requirement above
3. The unit economics actually work at scale.<p>So we decided to create a implementation of our own.<p>Process:<p>As we mentioned in our previous release, if you want to achieve response times this low you need to make everything as local as possible. So below was our setup<p>- Local STT: Deepgram model
- Local Embedding model: Nomic v1.5
- Local VectorDB: Turso
- Local LLM: Llama 3B
- Local TTS: Deepgram model<p>From our previous example, the only new components where:<p>- Local Embedding model: We chose Nomic Embed text v1.5 model that gave a processing time of roughly ~200ms
- Turso offers local embedded replicas combined with edgeDB’s which meant we were able to achieve 0.01 second read times. Pinecone also gave us good times of 0.043 seconds.<p>The above changes led us to achieve sub 1 second voice-to-voice response times<p>Application:<p>With Andrej Karpathy’s announcement around [Eureka Labs](<a href="https://eurekalabs.ai/" rel="nofollow">https://eurekalabs.ai/</a>), a new AI+Education company we thought we would create our very own personalised Andrej tutor.<p>Listen to anyone of his Youtube lectures, as soon as your start specking, the video will pause and he will reply. Once your question has been answered you can then tell him to continue with the lecture and the video will automatically start playing.<p>Demo: <a href="https://educationbot.cerebrium.ai/">https://educationbot.cerebrium.ai/</a><p>Blog: <a href="https://www.cerebrium.ai/blog/creating-a-realtime-rag-voice-agent">https://www.cerebrium.ai/blog/creating-a-realtime-rag-voice-...</a><p>Github Repo: <a href="https://github.com/CerebriumAI/examples/tree/master/19-voice-rag-agent">https://github.com/CerebriumAI/examples/tree/master/19-voice...</a><p>For demo purposes:<p>- We used OpenAI for GPT-4-mini and embeddings (its cheaper to run on a CPU than GPU’s when running demos at scale. These changes add about ~1 second to the response time
- We used Eleven labs to clone his voice to make replies sound more realistic. This adds about 300ms to the response time.<p>The improvements that can be made which we would like the community to contribute to are:<p>- Embed the video screens as well that when you ask certain questions it can show you the relevant lecture slide for the same chuck that it got context from to answer.
- Insert the timestamps in the vectorDB timestamps so that if a question will be answered later in the lecture he can let you know<p>This unlocks so many use cases in education, employee training, sales etc that it would be great to see what the community builds!
Show HN: Patchwork – Open-source framework to automate development gruntwork
Hi HN! We’re Asankhaya and Rohan and we are building Patchwork.<p>Patchwork tackles development gruntwork—like reviews, docs, linting, and security fixes—through customizable, code-first 'patchflows' using LLMs and modular code management steps, all in Python. Here's a quick overview video: <a href="https://youtu.be/MLyn6B3bFMU" rel="nofollow">https://youtu.be/MLyn6B3bFMU</a><p>From our time building DevSecOps tools, we experienced first-hand the frustrations our users faced as they built complex delivery pipelines. Almost a third of developer time is spent on code management tasks[1], yet backlogs remain.<p>Patchwork lets you combine well-defined prompts with effective workflow orchestration to automate as much as 80% of these gruntwork tasks using LLMs[2]. For instance, the AutoFix patchflow can resolve 82% of issues flagged by semgrep using gpt-4 (or 68% with llama-3.1-8B) without fine-tuning or providing specialized context [3]. Success rates are higher for text-based patchflows like PR Review and Generate Docstring, but lower for more complex tasks like Dependency Upgrades.<p>We are not a coding assistant or a black-box GitHub bot. Our automation workflows run outside your IDE via the CLI or CI scripts without your active involvement.<p>We are also not an ‘AI agent’ framework. In our experience, LLM agents struggle with planning and rarely identify the right execution path. Instead, Patchwork requires explicitly defined workflows that provide greater success and full control.<p>Patchwork is open-source so you can build your own patchflows, integrate your preferred LLM endpoints, and fully self-host, ensuring privacy and compliance for large teams.<p>As devs, we prefer to build our own ‘AI-enabled automation’ given how easy it is to consume LLM APIs. If you do, try patchwork via a simple 'pip install patchwork-cli' or find us on Github[4].<p>Sources:<p>[1] <a href="https://blog.tidelift.com/developers-spend-30-of-their-time-on-code-maintenance-our-latest-survey-results-part-3" rel="nofollow">https://blog.tidelift.com/developers-spend-30-of-their-time-...</a><p>[2] <a href="https://www.patched.codes/blog/patched-rtc-evaluating-llms-for-diverse-software-development-tasks">https://www.patched.codes/blog/patched-rtc-evaluating-llms-f...</a><p>[3] <a href="https://www.patched.codes/blog/how-good-are-llms">https://www.patched.codes/blog/how-good-are-llms</a><p>[4] <a href="https://github.com/patched-codes/patchwork">https://github.com/patched-codes/patchwork</a><p>[Sample PRs] <a href="https://github.com/patched-demo/sample-injection/pulls">https://github.com/patched-demo/sample-injection/pulls</a>
Show HN: Patchwork – Open-source framework to automate development gruntwork
Hi HN! We’re Asankhaya and Rohan and we are building Patchwork.<p>Patchwork tackles development gruntwork—like reviews, docs, linting, and security fixes—through customizable, code-first 'patchflows' using LLMs and modular code management steps, all in Python. Here's a quick overview video: <a href="https://youtu.be/MLyn6B3bFMU" rel="nofollow">https://youtu.be/MLyn6B3bFMU</a><p>From our time building DevSecOps tools, we experienced first-hand the frustrations our users faced as they built complex delivery pipelines. Almost a third of developer time is spent on code management tasks[1], yet backlogs remain.<p>Patchwork lets you combine well-defined prompts with effective workflow orchestration to automate as much as 80% of these gruntwork tasks using LLMs[2]. For instance, the AutoFix patchflow can resolve 82% of issues flagged by semgrep using gpt-4 (or 68% with llama-3.1-8B) without fine-tuning or providing specialized context [3]. Success rates are higher for text-based patchflows like PR Review and Generate Docstring, but lower for more complex tasks like Dependency Upgrades.<p>We are not a coding assistant or a black-box GitHub bot. Our automation workflows run outside your IDE via the CLI or CI scripts without your active involvement.<p>We are also not an ‘AI agent’ framework. In our experience, LLM agents struggle with planning and rarely identify the right execution path. Instead, Patchwork requires explicitly defined workflows that provide greater success and full control.<p>Patchwork is open-source so you can build your own patchflows, integrate your preferred LLM endpoints, and fully self-host, ensuring privacy and compliance for large teams.<p>As devs, we prefer to build our own ‘AI-enabled automation’ given how easy it is to consume LLM APIs. If you do, try patchwork via a simple 'pip install patchwork-cli' or find us on Github[4].<p>Sources:<p>[1] <a href="https://blog.tidelift.com/developers-spend-30-of-their-time-on-code-maintenance-our-latest-survey-results-part-3" rel="nofollow">https://blog.tidelift.com/developers-spend-30-of-their-time-...</a><p>[2] <a href="https://www.patched.codes/blog/patched-rtc-evaluating-llms-for-diverse-software-development-tasks">https://www.patched.codes/blog/patched-rtc-evaluating-llms-f...</a><p>[3] <a href="https://www.patched.codes/blog/how-good-are-llms">https://www.patched.codes/blog/how-good-are-llms</a><p>[4] <a href="https://github.com/patched-codes/patchwork">https://github.com/patched-codes/patchwork</a><p>[Sample PRs] <a href="https://github.com/patched-demo/sample-injection/pulls">https://github.com/patched-demo/sample-injection/pulls</a>
Show HN: Patchwork – Open-source framework to automate development gruntwork
Hi HN! We’re Asankhaya and Rohan and we are building Patchwork.<p>Patchwork tackles development gruntwork—like reviews, docs, linting, and security fixes—through customizable, code-first 'patchflows' using LLMs and modular code management steps, all in Python. Here's a quick overview video: <a href="https://youtu.be/MLyn6B3bFMU" rel="nofollow">https://youtu.be/MLyn6B3bFMU</a><p>From our time building DevSecOps tools, we experienced first-hand the frustrations our users faced as they built complex delivery pipelines. Almost a third of developer time is spent on code management tasks[1], yet backlogs remain.<p>Patchwork lets you combine well-defined prompts with effective workflow orchestration to automate as much as 80% of these gruntwork tasks using LLMs[2]. For instance, the AutoFix patchflow can resolve 82% of issues flagged by semgrep using gpt-4 (or 68% with llama-3.1-8B) without fine-tuning or providing specialized context [3]. Success rates are higher for text-based patchflows like PR Review and Generate Docstring, but lower for more complex tasks like Dependency Upgrades.<p>We are not a coding assistant or a black-box GitHub bot. Our automation workflows run outside your IDE via the CLI or CI scripts without your active involvement.<p>We are also not an ‘AI agent’ framework. In our experience, LLM agents struggle with planning and rarely identify the right execution path. Instead, Patchwork requires explicitly defined workflows that provide greater success and full control.<p>Patchwork is open-source so you can build your own patchflows, integrate your preferred LLM endpoints, and fully self-host, ensuring privacy and compliance for large teams.<p>As devs, we prefer to build our own ‘AI-enabled automation’ given how easy it is to consume LLM APIs. If you do, try patchwork via a simple 'pip install patchwork-cli' or find us on Github[4].<p>Sources:<p>[1] <a href="https://blog.tidelift.com/developers-spend-30-of-their-time-on-code-maintenance-our-latest-survey-results-part-3" rel="nofollow">https://blog.tidelift.com/developers-spend-30-of-their-time-...</a><p>[2] <a href="https://www.patched.codes/blog/patched-rtc-evaluating-llms-for-diverse-software-development-tasks">https://www.patched.codes/blog/patched-rtc-evaluating-llms-f...</a><p>[3] <a href="https://www.patched.codes/blog/how-good-are-llms">https://www.patched.codes/blog/how-good-are-llms</a><p>[4] <a href="https://github.com/patched-codes/patchwork">https://github.com/patched-codes/patchwork</a><p>[Sample PRs] <a href="https://github.com/patched-demo/sample-injection/pulls">https://github.com/patched-demo/sample-injection/pulls</a>
Show HN: Tiny Moon – Swift library to calculate the moon phase
Tiny Moon is a tiny Swift library to calculate the moon phase for any given date, works super fast, and works completely offline.<p>All of this started when I realized that we only have 12, sometimes 13, full moon's in a year. That doesn’t seem like that many.<p>I set out to build a MacOS app to remind me when a full moon occurs, so that I could take a moment and step outside to appreciate it.<p>The MacOS app I ended up creating can be found at <a href="https://apps.apple.com/us/app/tiny-moon/id6502374344" rel="nofollow">https://apps.apple.com/us/app/tiny-moon/id6502374344</a> along with the source code [0], all powered by the Tiny Moon library.<p>I knew that I wanted the app to work offline, so working with a network request was out of the picture. Taking inspiration from SunCalc [1] and Moontool for Windows [2], I decided to create my own library and wrote Tiny Moon as a Swift Package to power my app.<p>The app tries to be as minimal as possible, does what it does very fast, and works completely offline.<p>[0] <a href="https://github.com/mannylopez/TinyMoonApp">https://github.com/mannylopez/TinyMoonApp</a><p>[1] <a href="https://github.com/mourner/suncalc">https://github.com/mourner/suncalc</a><p>[2] <a href="https://www.fourmilab.ch/moontoolw/" rel="nofollow">https://www.fourmilab.ch/moontoolw/</a>
Show HN: Tiny Moon – Swift library to calculate the moon phase
Tiny Moon is a tiny Swift library to calculate the moon phase for any given date, works super fast, and works completely offline.<p>All of this started when I realized that we only have 12, sometimes 13, full moon's in a year. That doesn’t seem like that many.<p>I set out to build a MacOS app to remind me when a full moon occurs, so that I could take a moment and step outside to appreciate it.<p>The MacOS app I ended up creating can be found at <a href="https://apps.apple.com/us/app/tiny-moon/id6502374344" rel="nofollow">https://apps.apple.com/us/app/tiny-moon/id6502374344</a> along with the source code [0], all powered by the Tiny Moon library.<p>I knew that I wanted the app to work offline, so working with a network request was out of the picture. Taking inspiration from SunCalc [1] and Moontool for Windows [2], I decided to create my own library and wrote Tiny Moon as a Swift Package to power my app.<p>The app tries to be as minimal as possible, does what it does very fast, and works completely offline.<p>[0] <a href="https://github.com/mannylopez/TinyMoonApp">https://github.com/mannylopez/TinyMoonApp</a><p>[1] <a href="https://github.com/mourner/suncalc">https://github.com/mourner/suncalc</a><p>[2] <a href="https://www.fourmilab.ch/moontoolw/" rel="nofollow">https://www.fourmilab.ch/moontoolw/</a>
Show HN: Tiny Moon – Swift library to calculate the moon phase
Tiny Moon is a tiny Swift library to calculate the moon phase for any given date, works super fast, and works completely offline.<p>All of this started when I realized that we only have 12, sometimes 13, full moon's in a year. That doesn’t seem like that many.<p>I set out to build a MacOS app to remind me when a full moon occurs, so that I could take a moment and step outside to appreciate it.<p>The MacOS app I ended up creating can be found at <a href="https://apps.apple.com/us/app/tiny-moon/id6502374344" rel="nofollow">https://apps.apple.com/us/app/tiny-moon/id6502374344</a> along with the source code [0], all powered by the Tiny Moon library.<p>I knew that I wanted the app to work offline, so working with a network request was out of the picture. Taking inspiration from SunCalc [1] and Moontool for Windows [2], I decided to create my own library and wrote Tiny Moon as a Swift Package to power my app.<p>The app tries to be as minimal as possible, does what it does very fast, and works completely offline.<p>[0] <a href="https://github.com/mannylopez/TinyMoonApp">https://github.com/mannylopez/TinyMoonApp</a><p>[1] <a href="https://github.com/mourner/suncalc">https://github.com/mourner/suncalc</a><p>[2] <a href="https://www.fourmilab.ch/moontoolw/" rel="nofollow">https://www.fourmilab.ch/moontoolw/</a>
Show HN: Hooper – AI-driven stats and highlights for basketball play
Hey everyone, OP here. Wanted to share a bit more about Hooper — I started building it with a good friend of mine six months ago. We play a lot of pickup together and were arguing about who has a better jump shot and ended up hacking together an app to settle it<p>The way Hooper works is you can record yourself using the app and ideally a tripod (optional). The app will track everyone, whether its a solo practice, a 3v3, or a 5v5. We think there’s a lot of stuff out there for basketball drills but what we really wanted Hooper to be for is actual game play. That means, it can do things like track multiple players, sync two half court recordings, and differentiate 2s vs 3s.<p>Once you finish recording, it’ll process for a bit and then ask you to tag yourself (and optionally other players). Then it spits back out a few things: you can watch the full footage as well as a clipped version that's only the interesting plays; you can see highlights and offensive box stats for every player.<p>When you sign up, you get a Hooper profile that tracks your overall stats across the sessions. You can also do things like build a mixtape from your highlights for insta. You can friend other players on Hooper to see their profile & comment on their games (also add us “grub” and “kangexpress”!)<p>We’ve been in a closed beta for about 3 months now, fixing bugs and getting things to work with a set of early adopters. We are now starting our open beta ! If anyone here wants to try it out, you can just download the app on <a href="https://www.hooper.gg/?utm_campaign=h1" rel="nofollow">https://www.hooper.gg/?utm_campaign=h1</a>. We are early in our journey, and lots of improvements to be made in the next few months, but we would love your feedback and ideas!
Show HN: Hooper – AI-driven stats and highlights for basketball play
Hey everyone, OP here. Wanted to share a bit more about Hooper — I started building it with a good friend of mine six months ago. We play a lot of pickup together and were arguing about who has a better jump shot and ended up hacking together an app to settle it<p>The way Hooper works is you can record yourself using the app and ideally a tripod (optional). The app will track everyone, whether its a solo practice, a 3v3, or a 5v5. We think there’s a lot of stuff out there for basketball drills but what we really wanted Hooper to be for is actual game play. That means, it can do things like track multiple players, sync two half court recordings, and differentiate 2s vs 3s.<p>Once you finish recording, it’ll process for a bit and then ask you to tag yourself (and optionally other players). Then it spits back out a few things: you can watch the full footage as well as a clipped version that's only the interesting plays; you can see highlights and offensive box stats for every player.<p>When you sign up, you get a Hooper profile that tracks your overall stats across the sessions. You can also do things like build a mixtape from your highlights for insta. You can friend other players on Hooper to see their profile & comment on their games (also add us “grub” and “kangexpress”!)<p>We’ve been in a closed beta for about 3 months now, fixing bugs and getting things to work with a set of early adopters. We are now starting our open beta ! If anyone here wants to try it out, you can just download the app on <a href="https://www.hooper.gg/?utm_campaign=h1" rel="nofollow">https://www.hooper.gg/?utm_campaign=h1</a>. We are early in our journey, and lots of improvements to be made in the next few months, but we would love your feedback and ideas!
Show HN: Wat – Deep inspection of Python objects
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: 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: Voluntarily add warning labels to social media websites
A Chrome extension to voluntarily add informative warning labels to social media websites.<p>There is a significant association between social media use and depression. Recently the surgeon general of the United States called on congress to require warning labels. While warning labels are not a sure-fire way to curb use, they can be effective provided that:<p>- The warning must provide new information to users, and
- The user must find the information credible
Show HN: AI over Email
Show HN: Beautiful landing page builder for developers with tailwind and shadcn
Hi, I just build an open source project, convertfast-ui providing landing page blocks you can copy paste to your project. All code blocks are based on shadcn and tailwind.<p>Convertfast-ui also provides a CLI tool, with some quick command to generate landing pages directly into your project, a command example would be:<p>npx convertfast-ui@latest page create <my-page><p>It will generate landing page code in my-page and then you can edit them for customization.<p>Feedback and suggestions are welcome.<p>github repo: <a href="https://github.com/ObservedObserver/convertfast-ui">https://github.com/ObservedObserver/convertfast-ui</a><p>Website and docs: <a href="https://ui.convertfa.st/" rel="nofollow">https://ui.convertfa.st/</a>
Show HN: NoteTech – Create personal automations by writing notes