The best Hacker News stories from Show from the past day
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Show HN: A Stable Diffusion desktop frontend with inpainting, img2img and more
I was frustrated with laggy notebook stable diffusion demos. Plus they usually didn't have all the features I wanted (for example some of them only had inpainting and some only had img2img, so if I wanted both I had to repeatedly copy images between notebooks). So I made this desktop frontend which has much smoother performance than notebook alternatives and integrates image generation, inpainting and img2img into the same workflow. See a video demo here: <a href="https://user-images.githubusercontent.com/6392321/191858568-0550f52d-e89c-4b37-aa07-23df605b4807.mp4" rel="nofollow">https://user-images.githubusercontent.com/6392321/191858568-...</a><p>Features include:<p>* Can run locally or connect to a google colab server<p>* Ability to erase<p>* Ability to paint custom colors into the image. It is useful both for img2img (you can sketch a rough prototype and reimagine it into something nice) and inpainting (for example, you can paint a pixel red and it forces Stable Diffusion to put something red in there)<p>* Infinite undo/redo<p>* You can import your other images into a scratch pad and paste them into main image after erasing/cropping/scaling it<p>* Increase image size (by padding with transparent empty margins) for outpainting
Show HN: Venice – open-source Plaid to Postgres in minutes without code
Hi HN!<p>Tony & Ali here, we are super excited to introduce Venice - an open source financial data integrations platform. Our MVP is getting financial data from Plaid into your postgres database in under 5 mins.<p>We met while building our own respective fintechs. We noticed how much developer time went into setting up and maintaining the infrastructure rather than actually building the fintech itself. In Tony’s last project Alka for instance, the engineering team spent 30%+ of time building and maintaining the data connectivity and pipeline rather than the core work of accounting.<p>What we wish existed is a Segment / Airtable for fintech, letting you get financial data from wherever they are produced to anywhere they are useful. We think the most basic version is a Plaid to Postgres database connector with a self-service portal where your customers can add / remove / repair and manage their financial connections. This takes less than 5 mins to set up without writing a single line of code. In fact, we went so far as asking non technical people to get set up and they were able to do it just as fast using Vercel, Supabase and Plaid.<p>Today, our product is perfect if you’re just starting out or using it as a hobby, but eventually we hope any sized fintech could use what we’ve built as the project matures and community grows.<p>We wrote it using full stack TypeScript, and paid special attention to composability and extensibility. There is a core connect & sync library with its own cli, a HTTP API (thank you to the amazing folks at trpc + zod), a set of headless React components, theme-able data-connected UI library leveraging tailwindcss, and finally a next.js application that puts it all together. Each layer is built on the one before, so you can start with no code at all while drop down to any layer of abstraction as your need grow. What we are shipping today is a complete, instantly deployable next.js application which you can use either as a standalone portal via redirect, or embed into your application via iframe. The default setup uses Vercel as we expect you to bring your own database and authentication that powers the rest of your application.<p>The repo is licensed under MIT & ELv2, so you are completely free to use it for your own projects and companies while we retain the right to being the only one to release a cloud hosted version in the future.<p>Check us out at <a href="https://github.com/useVenice/venice" rel="nofollow">https://github.com/useVenice/venice</a>. We have a ton of ideas in mind and would love your feedback. Hit us up at hello@useVenice.com or on slack at <a href="http://link.usevenice.com/slack" rel="nofollow">http://link.usevenice.com/slack</a>
Show HN: Jot: Rapid note management for the terminal, inspired by Obsidian
Show HN: Jot: Rapid note management for the terminal, inspired by Obsidian
Show HN: Jot: Rapid note management for the terminal, inspired by Obsidian
Show HN: Jot: Rapid note management for the terminal, inspired by Obsidian
Show HN: Vim Tutorial as RPG
Show HN: Vim Tutorial as RPG
Show HN: Morgan – PyPI Mirror for Restricted/Offline Environments
Mirroring PyPI packages for environments/networks that do not have access to the Internet is hard. It's actually hard even in environments that do have access to the Internet. Most solutions out there either:<p>1. Depend on pip to download and cache package distributions. This means those downloads will probably only work in a similar environment (same Python interpreter, same libc), because of the nature of binary package distributions and the fact that packages have optional dependencies for different environments.<p>2. Depend on other PyPI packages, meaning installing the mirror in a restricted environment in itself is too difficult.<p>3. Cannot resolve dependencies of dependencies, meaning mirroring PyPI partially is extremely difficult, and PyPI is huge.<p>Morgan works differently. It creates a mirror based on a configuration file that defines target environments (using Python's standard Environment Markers specification from PEP 345) and a list of package requirement strings (e.g. "requests>=2.24.0"). It downloads all files relevant to the target environments from PyPI (both source and binary distributions), and recursively resolves and downloads their dependencies, again based on the target environments. It then extracts a single-file server to the mirror directory that works with Python 3.7+, has no outside dependencies, and implements the standard Simple API. This directory can be copied to the restricted network, through whatever security policies are in place, and deployed easily with a simple `python server.py` command.<p>I should note that Morgan can find dependencies from various metadata sources inside package distributions, including standard METADATA/PKG-INFO/pyproject.toml files, and non-standard files such as setuptools' requires.txt.<p>There's more information in the Git repository. If this is interesting to you, I'll be happy to receive your feedback.<p>Thanks!
Show HN: Morgan – PyPI Mirror for Restricted/Offline Environments
Mirroring PyPI packages for environments/networks that do not have access to the Internet is hard. It's actually hard even in environments that do have access to the Internet. Most solutions out there either:<p>1. Depend on pip to download and cache package distributions. This means those downloads will probably only work in a similar environment (same Python interpreter, same libc), because of the nature of binary package distributions and the fact that packages have optional dependencies for different environments.<p>2. Depend on other PyPI packages, meaning installing the mirror in a restricted environment in itself is too difficult.<p>3. Cannot resolve dependencies of dependencies, meaning mirroring PyPI partially is extremely difficult, and PyPI is huge.<p>Morgan works differently. It creates a mirror based on a configuration file that defines target environments (using Python's standard Environment Markers specification from PEP 345) and a list of package requirement strings (e.g. "requests>=2.24.0"). It downloads all files relevant to the target environments from PyPI (both source and binary distributions), and recursively resolves and downloads their dependencies, again based on the target environments. It then extracts a single-file server to the mirror directory that works with Python 3.7+, has no outside dependencies, and implements the standard Simple API. This directory can be copied to the restricted network, through whatever security policies are in place, and deployed easily with a simple `python server.py` command.<p>I should note that Morgan can find dependencies from various metadata sources inside package distributions, including standard METADATA/PKG-INFO/pyproject.toml files, and non-standard files such as setuptools' requires.txt.<p>There's more information in the Git repository. If this is interesting to you, I'll be happy to receive your feedback.<p>Thanks!
Show HN: Morgan – PyPI Mirror for Restricted/Offline Environments
Mirroring PyPI packages for environments/networks that do not have access to the Internet is hard. It's actually hard even in environments that do have access to the Internet. Most solutions out there either:<p>1. Depend on pip to download and cache package distributions. This means those downloads will probably only work in a similar environment (same Python interpreter, same libc), because of the nature of binary package distributions and the fact that packages have optional dependencies for different environments.<p>2. Depend on other PyPI packages, meaning installing the mirror in a restricted environment in itself is too difficult.<p>3. Cannot resolve dependencies of dependencies, meaning mirroring PyPI partially is extremely difficult, and PyPI is huge.<p>Morgan works differently. It creates a mirror based on a configuration file that defines target environments (using Python's standard Environment Markers specification from PEP 345) and a list of package requirement strings (e.g. "requests>=2.24.0"). It downloads all files relevant to the target environments from PyPI (both source and binary distributions), and recursively resolves and downloads their dependencies, again based on the target environments. It then extracts a single-file server to the mirror directory that works with Python 3.7+, has no outside dependencies, and implements the standard Simple API. This directory can be copied to the restricted network, through whatever security policies are in place, and deployed easily with a simple `python server.py` command.<p>I should note that Morgan can find dependencies from various metadata sources inside package distributions, including standard METADATA/PKG-INFO/pyproject.toml files, and non-standard files such as setuptools' requires.txt.<p>There's more information in the Git repository. If this is interesting to you, I'll be happy to receive your feedback.<p>Thanks!
Show HN: TwitterToNitter. A bookmarklet that makes reading on Twitter easier
Show HN: TwitterToNitter. A bookmarklet that makes reading on Twitter easier
Show HN: TwitterToNitter. A bookmarklet that makes reading on Twitter easier
Show HN: MathB.in – Mathematics pastebin written in Common Lisp
Show HN: MathB.in – Mathematics pastebin written in Common Lisp
Show HN: MathB.in – Mathematics pastebin written in Common Lisp
Show HN: MathB.in – Mathematics pastebin written in Common Lisp
Show HN: Ezno, a type checker for JavaScript and optimiser for React
Show HN: Ezno, a type checker for JavaScript and optimiser for React