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Show HN: Chatblade – A CLI Swiss Army Knife for ChatGPT
integrate chatGPT into your scripts or terminal work. Supports piping text, saving prompts, estimating costs, and some basic json/yaml extraction.<p>I've added some elaborate examples on the readme of how to use it with pictures, that may provide a better overview.
Show HN: Chatblade – A CLI Swiss Army Knife for ChatGPT
integrate chatGPT into your scripts or terminal work. Supports piping text, saving prompts, estimating costs, and some basic json/yaml extraction.<p>I've added some elaborate examples on the readme of how to use it with pictures, that may provide a better overview.
Show HN: Llamero – A GUI app to easily download, install and infer LLaMA models
Show HN: i2forge – A Platform for Verified Reasoning
Hi! We're Amisi and Claude, builders of the i2 language and the i2forge platform. i2 is an (early draft of a) language designed to make formal verification easy for mathematicians.<p>We are launching the language as an open source project today (<a href="https://i2lang.org" rel="nofollow">https://i2lang.org</a>) together with a closed alpha for i2forge.<p>However, we have a publicly accessible demo page which anyone can use, and we would love your feedback.<p>Thanks.
Show HN: Easy-to-use licensing library for .NET apps
This free, open-source .NET library allows you to license your non-free applications through activation keys. Follow the quick start instructions and try it out in 5 minutes!<p>Available on:<p>NuGet
<a href="https://www.nuget.org/packages/SNBS.Licensing.ActivationKeys/" rel="nofollow">https://www.nuget.org/packages/SNBS.Licensing.ActivationKeys...</a><p>Website (full docs, downloads)
<a href="https://snbslibs.github.io/Licensing.ActivationKeys" rel="nofollow">https://snbslibs.github.io/Licensing.ActivationKeys</a><p>GitHub (downloads, full docs, release notes etc.)
<a href="https://github.com/SNBSLibs/Licensing.ActivationKeys">https://github.com/SNBSLibs/Licensing.ActivationKeys</a>
Show HN: Easy-to-use licensing library for .NET apps
This free, open-source .NET library allows you to license your non-free applications through activation keys. Follow the quick start instructions and try it out in 5 minutes!<p>Available on:<p>NuGet
<a href="https://www.nuget.org/packages/SNBS.Licensing.ActivationKeys/" rel="nofollow">https://www.nuget.org/packages/SNBS.Licensing.ActivationKeys...</a><p>Website (full docs, downloads)
<a href="https://snbslibs.github.io/Licensing.ActivationKeys" rel="nofollow">https://snbslibs.github.io/Licensing.ActivationKeys</a><p>GitHub (downloads, full docs, release notes etc.)
<a href="https://github.com/SNBSLibs/Licensing.ActivationKeys">https://github.com/SNBSLibs/Licensing.ActivationKeys</a>
Show HN: AI copywriter that cannot be caught by AI content detectors
Show HN: GPT4 – Full Playthrough of Pokemon Yellow
Show HN: Glish, the extension to inject foreign language vocab into websites
Available for Firefox and Chrome:<p><a href="https://addons.mozilla.org/en-US/firefox/addon/glish/" rel="nofollow">https://addons.mozilla.org/en-US/firefox/addon/glish/</a><p><a href="https://chrome.google.com/webstore/detail/glish/jfheijenmheiialipkmahkhcdmfefclb/" rel="nofollow">https://chrome.google.com/webstore/detail/glish/jfheijenmhei...</a>
Show HN: Glish, the extension to inject foreign language vocab into websites
Available for Firefox and Chrome:<p><a href="https://addons.mozilla.org/en-US/firefox/addon/glish/" rel="nofollow">https://addons.mozilla.org/en-US/firefox/addon/glish/</a><p><a href="https://chrome.google.com/webstore/detail/glish/jfheijenmheiialipkmahkhcdmfefclb/" rel="nofollow">https://chrome.google.com/webstore/detail/glish/jfheijenmhei...</a>
Show HN: HN Profiles – Searchable Database of People “Who Want to Be Hired”
Show HN: 'Hello, World ' in x86 assembly, but make it gibberish
Show HN: 'Hello, World ' in x86 assembly, but make it gibberish
Show HN: 'Hello, World ' in x86 assembly, but make it gibberish
Show HN: 'Hello, World ' in x86 assembly, but make it gibberish
Show HN: GPT Repo Loader – load entire code repos into GPT prompts
I was getting tired of copy/pasting reams of code into GPT-4 to give it context before I asked it to help me, so I started this small tool. In a nutshell, gpt-repository-loader will spit out file paths and file contents in a prompt-friendly format. You can also use .gptignore to ignore files/folders that are irrelevant to your prompt.<p>gpt-repository-loader as-is works pretty well in helping me achieve better responses. Eventually, I thought it would be cute to load itself into GPT-4 and have GPT-4 improve it. I was honestly surprised by PR#17. GPT-4 was able to write a valid an example repo and an expected output and throw in a small curveball by adjusting .gptignore. I did tell GPT the output file format in two places: 1.) in the preamble when I prompted it to make a PR for issue #16 and 2.) as a string in gpt_repository_loader.py, both of which are indirect ways to infer how to build a functional test. However, I don't think I explained to GPT in English anywhere on how .gptignore works at all!<p>I wonder how far GPT-4 can take this repo. Here is the process I'm following for developing:<p>- Open an issue describing the improvement to make<p>- Construct a prompt - start with using gpt_repository_loader.py on this repo to generate the repository context, then append the text of the opened issue after the --END-- line.<p>- Try not to edit any code GPT-4 generates. If there is something wrong, continue to prompt GPT to fix whatever it is.<p>- Create a feature branch on the issue and create a pull request based on GPT's response.<p>- Have a maintainer review, approve, and merge.<p>I am going to try to automate the steps above as much as possible. Really curious how tight the feedback loop will eventually get before something breaks!
Show HN: GPT Repo Loader – load entire code repos into GPT prompts
I was getting tired of copy/pasting reams of code into GPT-4 to give it context before I asked it to help me, so I started this small tool. In a nutshell, gpt-repository-loader will spit out file paths and file contents in a prompt-friendly format. You can also use .gptignore to ignore files/folders that are irrelevant to your prompt.<p>gpt-repository-loader as-is works pretty well in helping me achieve better responses. Eventually, I thought it would be cute to load itself into GPT-4 and have GPT-4 improve it. I was honestly surprised by PR#17. GPT-4 was able to write a valid an example repo and an expected output and throw in a small curveball by adjusting .gptignore. I did tell GPT the output file format in two places: 1.) in the preamble when I prompted it to make a PR for issue #16 and 2.) as a string in gpt_repository_loader.py, both of which are indirect ways to infer how to build a functional test. However, I don't think I explained to GPT in English anywhere on how .gptignore works at all!<p>I wonder how far GPT-4 can take this repo. Here is the process I'm following for developing:<p>- Open an issue describing the improvement to make<p>- Construct a prompt - start with using gpt_repository_loader.py on this repo to generate the repository context, then append the text of the opened issue after the --END-- line.<p>- Try not to edit any code GPT-4 generates. If there is something wrong, continue to prompt GPT to fix whatever it is.<p>- Create a feature branch on the issue and create a pull request based on GPT's response.<p>- Have a maintainer review, approve, and merge.<p>I am going to try to automate the steps above as much as possible. Really curious how tight the feedback loop will eventually get before something breaks!
Show HN: GPT Repo Loader – load entire code repos into GPT prompts
I was getting tired of copy/pasting reams of code into GPT-4 to give it context before I asked it to help me, so I started this small tool. In a nutshell, gpt-repository-loader will spit out file paths and file contents in a prompt-friendly format. You can also use .gptignore to ignore files/folders that are irrelevant to your prompt.<p>gpt-repository-loader as-is works pretty well in helping me achieve better responses. Eventually, I thought it would be cute to load itself into GPT-4 and have GPT-4 improve it. I was honestly surprised by PR#17. GPT-4 was able to write a valid an example repo and an expected output and throw in a small curveball by adjusting .gptignore. I did tell GPT the output file format in two places: 1.) in the preamble when I prompted it to make a PR for issue #16 and 2.) as a string in gpt_repository_loader.py, both of which are indirect ways to infer how to build a functional test. However, I don't think I explained to GPT in English anywhere on how .gptignore works at all!<p>I wonder how far GPT-4 can take this repo. Here is the process I'm following for developing:<p>- Open an issue describing the improvement to make<p>- Construct a prompt - start with using gpt_repository_loader.py on this repo to generate the repository context, then append the text of the opened issue after the --END-- line.<p>- Try not to edit any code GPT-4 generates. If there is something wrong, continue to prompt GPT to fix whatever it is.<p>- Create a feature branch on the issue and create a pull request based on GPT's response.<p>- Have a maintainer review, approve, and merge.<p>I am going to try to automate the steps above as much as possible. Really curious how tight the feedback loop will eventually get before something breaks!
Show HN: GPT Repo Loader – load entire code repos into GPT prompts
I was getting tired of copy/pasting reams of code into GPT-4 to give it context before I asked it to help me, so I started this small tool. In a nutshell, gpt-repository-loader will spit out file paths and file contents in a prompt-friendly format. You can also use .gptignore to ignore files/folders that are irrelevant to your prompt.<p>gpt-repository-loader as-is works pretty well in helping me achieve better responses. Eventually, I thought it would be cute to load itself into GPT-4 and have GPT-4 improve it. I was honestly surprised by PR#17. GPT-4 was able to write a valid an example repo and an expected output and throw in a small curveball by adjusting .gptignore. I did tell GPT the output file format in two places: 1.) in the preamble when I prompted it to make a PR for issue #16 and 2.) as a string in gpt_repository_loader.py, both of which are indirect ways to infer how to build a functional test. However, I don't think I explained to GPT in English anywhere on how .gptignore works at all!<p>I wonder how far GPT-4 can take this repo. Here is the process I'm following for developing:<p>- Open an issue describing the improvement to make<p>- Construct a prompt - start with using gpt_repository_loader.py on this repo to generate the repository context, then append the text of the opened issue after the --END-- line.<p>- Try not to edit any code GPT-4 generates. If there is something wrong, continue to prompt GPT to fix whatever it is.<p>- Create a feature branch on the issue and create a pull request based on GPT's response.<p>- Have a maintainer review, approve, and merge.<p>I am going to try to automate the steps above as much as possible. Really curious how tight the feedback loop will eventually get before something breaks!
Show HN: Scriptable.run, make your product extendable by anyone.