chat_waitlist_signup VS easy-chat

To get started using GitHub Copilot Chat in VSCode, ensure that you have access to the extension by checking your email for access privileges. You get access privileges through your organization or by being taken off the waitlist for the private beta for individuals. You also need to ensure that you have an active GitHub Copilot subscription.

Using a tool like GitHub Copilot Chat, a developer could highlight a block of code and ask questions like the ones listed above. It's a great opportunity to interactively learn more about accessibility, the experience different users have on a website, and how best to ensure the pages they build are usable by everyone. The information will be contextual to their specific situation, making it more relevant and impactful to the developer.

To complete the second half of this tutorial, you will need access to Copilot Chat. Additionally, you need an active subscription to GitHub Copilot to access Copilot Chat. Learn more here.

https://github.com/github-copilot/chat_waitlist_signup/join

I can't remember what the other platform options are, but for VSCode you need to use a preview version, which has meant I haven't had much time to test it yet as I'm full on with the stable release.

Copilot Chat will probably be something you’ll like. Have you used it? There is a waitlist.

https://github.com/github-copilot/chat_waitlist_signup/join

You can ask GPT for new features, improvements, and bug fixes and aider will directly apply the changes to your source files. Each change is automatically committed to git with a sensible commit message. These frequent, automatic commits provide a comforting safety net. You can confidently collaborate with aider, because it's easy to use git to undo missteps or manage a long series of changes.

You can find out more about aider on GitHub: https://github.com/paul-gauthier/aider

I was initially using GPT to generate code snippets with the OpenAI web chat UI and generic ChatGPT command line tools like `aichat`. But that involved a somewhat klunky workflow where I had to cut and paste code into ChatGPT and then back into my source files.

I streamlined my process while developing a children's chat interface called EasyChat (https://github.com/paul-gauthier/easy-chat). I adopted a "whole file in, whole file out" workflow. I would send GPT-3.5 the entire source code of my project along with a change request and had it reply with the modified version of all the code. This approach was way less tedious than cutting and pasting code between the chat and my source files. I had some simple command line tooling to feed source files to GPT, overwrite them with GPT's modified version and display diffs. This workflow was also quite reliable: GPT-3.5 could consistently produce the code changes I requested without getting lost or confused. But it was slow waiting for GPT to retype all the code, and I quickly hit context window limits asking GPT to read and rewrite every line of the entire codebase.

Access to the GPT-4 API really unlocked a lot of possibilities for improving my tooling. GPT-4 is much better than GPT-3.5 at following directions and replying in a stable, parsable format. Aider still sends GPT-4 entire source files, but asks for replies in a concise `diff` like format. Aider automatically applies these diffs to the source files and git commits them with a GPT generated commit message. Aider lets you easily manage which of your source files are "in the chat session" to control how much code you send to GPT-4 with each request. The ability to reply with diffs makes it much less likely to overflow GPT-4's larger context window.

The resulting workflow is quite effective. You can bounce back and forth between the aider chat and your editor to collaborate on code changes. Aider's code changes aren't always perfect, but wow they are great for blasting through boilerplate or quickly integrating unfamiliar libraries or packages into your code. And if you don't like a code edit, you can quickly discard it by typing `/undo` into the chat.

I now use aider as a force multiplier for a lot of my coding. I even use aider to improve the tool itself.

Let me know if you try aider and find it helpful.

I had chat gpt 3.5 build a small web app for me too. I have since been building some tooling for this sort of GPT-assisted programming.

https://github.com/paul-gauthier/easy-chat

GPT is significantly better at modifying code when following this "all code in, all code out" pattern. This pattern has downsides: you can quickly exhaust the context window, it's slow waiting for GPT to re-type your code (most of which it hasn't modified) and of course you're running up token costs. But the ability of GPT to understand and execute high level changes to the code is far superior with this approach.

I have tried quite a large number of alternative workflows. Outside the "all code in/out" pattern, GPT gets confused, makes mistakes, implements the requested change in different ways in different sections of the code, or just plain fails.

If you're asking for self contained modifications to a single function, that's all the code that needs to go in/out. On the other side of the spectrum, I had GPT build an entire small webapp using this pattern by repeatedly feeding it all the html/css/js along with a series of feature requests. Many feature requests required coordinated changes across html/css/js.

https://github.com/paul-gauthier/easy-chat#created-by-chatgp...

Another HN user has also released a command line tool along these lines called gish:

https://github.com/drorm/gish

Gish looks really nice. I'm going to give it a try.

It seems like you've been using similar workflows to what I've been trying for coding with gpt?

https://github.com/paul-gauthier/easy-chat#created-by-chatgp...