The best Hacker News stories from Show from the past day
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Show HN: Run a GitHub Actions step in a gVisor sandbox
Show HN: Run a GitHub Actions step in a gVisor sandbox
Show HN: Run a GitHub Actions step in a gVisor sandbox
Show HN: Meals You Love – AI-powered meal planning and grocery shopping
Meals You Love is a meal planning app that creates weekly meal plans tailored to your tastes and dietary preferences. It integrates with Kroger and Instacart's APIs so you can add your meal plan groceries directly to your cart. You can also import your own recipes to include alongside AI suggestions.<p>I originally built this to help my wife with meal planning and grocery shopping. We were always struggling to decide what to make and inevitably forgot ingredients. Most meal planners felt too rigid or generic, and few handled the grocery side well (or at all). We've also used meal kits like Home Chef in the past but they end up being quite expensive and produce a comical amount of packaging waste, plus you still wind up needing to purchase groceries anyway. In all honesty, I also wanted an excuse to try building something "real" using AI and to see if it could be used in an actually useful manner.<p>Would love feedback from anyone interested in food, meal planning, or product design!<p>Tech stack:<p>- Cloud Run<p>- Firestore<p>- Vertex AI / Gemini<p><a href="https://mealsyoulove.com" rel="nofollow">https://mealsyoulove.com</a>
Show HN: Meals You Love – AI-powered meal planning and grocery shopping
Meals You Love is a meal planning app that creates weekly meal plans tailored to your tastes and dietary preferences. It integrates with Kroger and Instacart's APIs so you can add your meal plan groceries directly to your cart. You can also import your own recipes to include alongside AI suggestions.<p>I originally built this to help my wife with meal planning and grocery shopping. We were always struggling to decide what to make and inevitably forgot ingredients. Most meal planners felt too rigid or generic, and few handled the grocery side well (or at all). We've also used meal kits like Home Chef in the past but they end up being quite expensive and produce a comical amount of packaging waste, plus you still wind up needing to purchase groceries anyway. In all honesty, I also wanted an excuse to try building something "real" using AI and to see if it could be used in an actually useful manner.<p>Would love feedback from anyone interested in food, meal planning, or product design!<p>Tech stack:<p>- Cloud Run<p>- Firestore<p>- Vertex AI / Gemini<p><a href="https://mealsyoulove.com" rel="nofollow">https://mealsyoulove.com</a>
Show HN: I made a heatmap diff viewer for code reviews
0github.com is a pull request viewer that color-codes every diff line/token by how much human attention it probably needs. Unlike PR-review bots, we try to flag not just by "is it a bug?" but by "is it worth a second look?" (examples: hard-coded secret, weird crypto mode, gnarly logic, ugly code).<p>To try it, replace github.com with 0github.com in any pull-request URL. Under the hood, we split the PR into individual files, and for each file, we ask an LLM to annotate each line with a data structure that we parse into a colored heatmap.<p>Examples:<p><a href="https://0github.com/manaflow-ai/cmux/pull/666" rel="nofollow">https://0github.com/manaflow-ai/cmux/pull/666</a><p><a href="https://0github.com/stack-auth/stack-auth/pull/988" rel="nofollow">https://0github.com/stack-auth/stack-auth/pull/988</a><p><a href="https://0github.com/tinygrad/tinygrad/pull/12995" rel="nofollow">https://0github.com/tinygrad/tinygrad/pull/12995</a><p><a href="https://0github.com/simonw/datasette/pull/2548" rel="nofollow">https://0github.com/simonw/datasette/pull/2548</a><p>Notice how all the example links have a 0 prepended before github.com. This navigates you to our custom diff viewer where we handle the same URL path parameters as github.com. Darker yellows indicate that an area might require more investigation. Hover on the highlights to see the LLM's explanation. There's also a slider on the top left to adjust the "should review" threshold.<p>Repo (MIT license): <a href="https://github.com/manaflow-ai/cmux" rel="nofollow">https://github.com/manaflow-ai/cmux</a>
Show HN: I made a heatmap diff viewer for code reviews
0github.com is a pull request viewer that color-codes every diff line/token by how much human attention it probably needs. Unlike PR-review bots, we try to flag not just by "is it a bug?" but by "is it worth a second look?" (examples: hard-coded secret, weird crypto mode, gnarly logic, ugly code).<p>To try it, replace github.com with 0github.com in any pull-request URL. Under the hood, we split the PR into individual files, and for each file, we ask an LLM to annotate each line with a data structure that we parse into a colored heatmap.<p>Examples:<p><a href="https://0github.com/manaflow-ai/cmux/pull/666" rel="nofollow">https://0github.com/manaflow-ai/cmux/pull/666</a><p><a href="https://0github.com/stack-auth/stack-auth/pull/988" rel="nofollow">https://0github.com/stack-auth/stack-auth/pull/988</a><p><a href="https://0github.com/tinygrad/tinygrad/pull/12995" rel="nofollow">https://0github.com/tinygrad/tinygrad/pull/12995</a><p><a href="https://0github.com/simonw/datasette/pull/2548" rel="nofollow">https://0github.com/simonw/datasette/pull/2548</a><p>Notice how all the example links have a 0 prepended before github.com. This navigates you to our custom diff viewer where we handle the same URL path parameters as github.com. Darker yellows indicate that an area might require more investigation. Hover on the highlights to see the LLM's explanation. There's also a slider on the top left to adjust the "should review" threshold.<p>Repo (MIT license): <a href="https://github.com/manaflow-ai/cmux" rel="nofollow">https://github.com/manaflow-ai/cmux</a>
Show HN: I made a heatmap diff viewer for code reviews
0github.com is a pull request viewer that color-codes every diff line/token by how much human attention it probably needs. Unlike PR-review bots, we try to flag not just by "is it a bug?" but by "is it worth a second look?" (examples: hard-coded secret, weird crypto mode, gnarly logic, ugly code).<p>To try it, replace github.com with 0github.com in any pull-request URL. Under the hood, we split the PR into individual files, and for each file, we ask an LLM to annotate each line with a data structure that we parse into a colored heatmap.<p>Examples:<p><a href="https://0github.com/manaflow-ai/cmux/pull/666" rel="nofollow">https://0github.com/manaflow-ai/cmux/pull/666</a><p><a href="https://0github.com/stack-auth/stack-auth/pull/988" rel="nofollow">https://0github.com/stack-auth/stack-auth/pull/988</a><p><a href="https://0github.com/tinygrad/tinygrad/pull/12995" rel="nofollow">https://0github.com/tinygrad/tinygrad/pull/12995</a><p><a href="https://0github.com/simonw/datasette/pull/2548" rel="nofollow">https://0github.com/simonw/datasette/pull/2548</a><p>Notice how all the example links have a 0 prepended before github.com. This navigates you to our custom diff viewer where we handle the same URL path parameters as github.com. Darker yellows indicate that an area might require more investigation. Hover on the highlights to see the LLM's explanation. There's also a slider on the top left to adjust the "should review" threshold.<p>Repo (MIT license): <a href="https://github.com/manaflow-ai/cmux" rel="nofollow">https://github.com/manaflow-ai/cmux</a>
Show HN: In a single HTML file, an app to encourage my children to invest
Show HN: In a single HTML file, an app to encourage my children to invest
Show HN: In a single HTML file, an app to encourage my children to invest
Show HN: In a single HTML file, an app to encourage my children to invest
Show HN: In a single HTML file, an app to encourage my children to invest
Show HN: HUD-like live annotation and sketching app for macOS
Hey all!<p>I'm happy to announce we've finally released our 2nd macOS app, Draw Over It, a tiny desktop app that enables drawing, highlighting, or annotating directly on top of anything on your Mac.<p>I've always wanted something like this for instant and unobtrusive sketching and annotation for pair programming and demos. I always found the standard web-based diagram and drawing tools a bit too cumbersome. So we built a simple overlay that could appear over any window or app with one shortcut.<p>It doesn't collect any user data and doesn't require any system permissions - it's sandboxed. It all stays on your device. You can export your annotations to a PNG with one click - or just take a screenshot if you need the background too.<p>It offers a slim but functional toolkit for every day tasks:<p>- Global hotkeys, hit a shortcut and start drawing over any app<p>- Multiple tools, pens, shapes, highlighters<p>- Per-screen canvases, each monitor gets its own space<p>- Focus mode, temporarily blur the background to emphasize what matters<p>- Low footprint, no subscriptions, no sign-ups, no data collected<p>- Localization, the app is translated to 14 languages<p>These two reasons make it different from other canvas apps, it's simple, lean and keeps your data on-device only.<p>It’s a one-time purchase ($2.99) on the Mac App Store.<p>I’d love feedback and suggestions for improvements!
Show HN: HUD-like live annotation and sketching app for macOS
Hey all!<p>I'm happy to announce we've finally released our 2nd macOS app, Draw Over It, a tiny desktop app that enables drawing, highlighting, or annotating directly on top of anything on your Mac.<p>I've always wanted something like this for instant and unobtrusive sketching and annotation for pair programming and demos. I always found the standard web-based diagram and drawing tools a bit too cumbersome. So we built a simple overlay that could appear over any window or app with one shortcut.<p>It doesn't collect any user data and doesn't require any system permissions - it's sandboxed. It all stays on your device. You can export your annotations to a PNG with one click - or just take a screenshot if you need the background too.<p>It offers a slim but functional toolkit for every day tasks:<p>- Global hotkeys, hit a shortcut and start drawing over any app<p>- Multiple tools, pens, shapes, highlighters<p>- Per-screen canvases, each monitor gets its own space<p>- Focus mode, temporarily blur the background to emphasize what matters<p>- Low footprint, no subscriptions, no sign-ups, no data collected<p>- Localization, the app is translated to 14 languages<p>These two reasons make it different from other canvas apps, it's simple, lean and keeps your data on-device only.<p>It’s a one-time purchase ($2.99) on the Mac App Store.<p>I’d love feedback and suggestions for improvements!
Show HN: Research Hacker News, ArXiv & Google with Hierarchical Bayesian Models
Hi Hacker News! I’m a Bayesian statistician that has been working on applying hierarchical mixture models (originally developed for genomics) to structure text data, and in the process, used these models to build (what started as a personal) tool for conducting literature reviews and deep research.<p>My literature review process starts with a broad search to find a few key papers/groups, and from there expands along their citation networks. I needed to conduct a few rounds of literature reviews during the course of my research and decided to build a tool to facilitate this process. The tool started as an experimental wrapper over low-level statistical software in C, quickly became a testing/iteration ground for our api, and is now my personal go-to for lit reviews.<p>The tool organizes corpuses of text content, visualizes the high level themes, and enables me to pull up relevant excerpts. Unlike LLMs, this model transparently organizes the data and can train from scratch quickly on small datasets to learn custom hierarchical taxonomies. My favorite part of the tool is the citation network integration: any research paper it pulls up has a button “Citation Network Deep Dive” that pulls every paper that cites or is cited by the original paper, and organizes it for further exploration.<p>I initially built this tool for academic research, but ended up extending it to support Hacker News to mine technical conversation, the top 200 Google results, and earnings transcripts. We have a gallery of ready to explore results on the homepage. If you are kicking off a custom deep dive, it takes about 1-5 minutes for academic search, 3-7 minutes for Hacker News, and 5-10 minutes for Google.
To demonstrate the process, I put together a video walkthrough of a short literature review I conducted on AI hallucinations: <a href="https://www.youtube.com/watch?v=OUmDPAcK6Ns" rel="nofollow">https://www.youtube.com/watch?v=OUmDPAcK6Ns</a><p>I host this tool on my company’s website, free for personal use. I’d love to know if the HN community finds it useful (or to hear what breaks)!
Show HN: Research Hacker News, ArXiv & Google with Hierarchical Bayesian Models
Hi Hacker News! I’m a Bayesian statistician that has been working on applying hierarchical mixture models (originally developed for genomics) to structure text data, and in the process, used these models to build (what started as a personal) tool for conducting literature reviews and deep research.<p>My literature review process starts with a broad search to find a few key papers/groups, and from there expands along their citation networks. I needed to conduct a few rounds of literature reviews during the course of my research and decided to build a tool to facilitate this process. The tool started as an experimental wrapper over low-level statistical software in C, quickly became a testing/iteration ground for our api, and is now my personal go-to for lit reviews.<p>The tool organizes corpuses of text content, visualizes the high level themes, and enables me to pull up relevant excerpts. Unlike LLMs, this model transparently organizes the data and can train from scratch quickly on small datasets to learn custom hierarchical taxonomies. My favorite part of the tool is the citation network integration: any research paper it pulls up has a button “Citation Network Deep Dive” that pulls every paper that cites or is cited by the original paper, and organizes it for further exploration.<p>I initially built this tool for academic research, but ended up extending it to support Hacker News to mine technical conversation, the top 200 Google results, and earnings transcripts. We have a gallery of ready to explore results on the homepage. If you are kicking off a custom deep dive, it takes about 1-5 minutes for academic search, 3-7 minutes for Hacker News, and 5-10 minutes for Google.
To demonstrate the process, I put together a video walkthrough of a short literature review I conducted on AI hallucinations: <a href="https://www.youtube.com/watch?v=OUmDPAcK6Ns" rel="nofollow">https://www.youtube.com/watch?v=OUmDPAcK6Ns</a><p>I host this tool on my company’s website, free for personal use. I’d love to know if the HN community finds it useful (or to hear what breaks)!
Show HN: Learn German with Games
I just started learning German, and it has been a frustrating experience, to say the least. There are so many seemingly arbitrary rules that make pattern recognition very difficult. Therefore, I have been looking for ways to make memorization a bit easier and fun. So, I came up with a bunch of games to make learning German a bit more engaging. Hope you find it useful as well!
Show HN: Learn German with Games
I just started learning German, and it has been a frustrating experience, to say the least. There are so many seemingly arbitrary rules that make pattern recognition very difficult. Therefore, I have been looking for ways to make memorization a bit easier and fun. So, I came up with a bunch of games to make learning German a bit more engaging. Hope you find it useful as well!
Show HN: Learn German with Games
I just started learning German, and it has been a frustrating experience, to say the least. There are so many seemingly arbitrary rules that make pattern recognition very difficult. Therefore, I have been looking for ways to make memorization a bit easier and fun. So, I came up with a bunch of games to make learning German a bit more engaging. Hope you find it useful as well!