goggles-quickstart VS aider

I see a lot of recommendations for kagi, but no mention of brave search - specifically the (beta) feature called “goggles”. Afaiu it’s a blend of kagi’s “lenses” and the site ranking in search results.

https://search.brave.com/help/goggles There is a list (search) of public goggles: https://search.brave.com/goggles

The goggles itself are just text files with basic syntax and can be hosted on e.g. github gist. (though you have to publish it to brave)

https://github.com/brave/goggles-quickstart/blob/main/goggle...

Tbh, I can’t really compare brave search to kagi, since I never used kagi (though I’m using Orion - webkit based browser from the same dev and love it). Afaik, brave search is using its own index, thus making the results somehow limited and inferior to kagis. Just wanted to throw some (free) alternative here that works for me. :)

* Note that Brave search, despite privacy oriented, is still ad funded and there was few controversies about brave’s (browser) privacy in the past. (if that’s relevant for you)

You are technically in control of it even if it is in Brave's servers, so, you can create, modify it and delete it. https://github.com/brave/goggles-quickstart

I'm putting together a list of UL resources to ultimately become indexed and searchable (through Goggles). This index will be public and something that will hopefully be community maintained, but I'll just be getting it started for now.

If you have some time, would you like to try to create such a Goggle? There are some instructions and examples as to how to do that here: https://github.com/brave/goggles-quickstart

If you talk about search results, well, Brave Search has goggles, you only need a github account and you can create your own list, so you can only get what you want.

"Goggles are simple, self-contained text files which can be hosted in Github or Gitlab. These files contain instructions allowing you to tell Brave Search how you'd like your results to be ranked. You can target specific URL patterns (and, soon, website titles and other aspects of Web pages) and indicate how their ranking should be altered (e.g. boosted, downranked, or completely discarded from the results)." - https://github.com/brave/goggles-quickstart

Great to see a company protecting and empowering its users. I just tried it out myself. Very easy to implement (e.g., "Amazon-Excluded Search"). Thanks for sharing!

Try Brave goggles: https://github.com/brave/goggles-quickstart

If you haven't heard of [Brave Goggles](https://github.com/brave/goggles-quickstart) I highly recommend checking it out. Just being able to create the search index is a massive task, so being able to apply rules server-side to their "expanded recall set" will give you what most people building search engines want, which is to control the algorithm. We weren't able to do that until now since applying rules client-side doesn't work well on a small search result set.

Related: I created a tool to create Goggles using subreddits as a signal source for domains: [Narwhalizer](https://github.com/forcesunseen/narwhalizer)

To learn more about Goggles, visit the repository, where you can find the syntax specification, examples, FAQs, and more.

And most important of all, anyone can create, apply and share their own rules (https://github.com/brave/goggles-quickstart). This means you can effectively implement your own web result ranking. For example you can give priority to websites you consider more trustworthy and remove the ones that have low-quality clickbait.

Aider was developed by Paul Gaither and focuses on giving developers a pair programming experience directly from developers' terminals. This command-line tool edits code in real-time based on a user prompt in the command terminal. As of writing, it only supports OpenAI’s API but can write, edit, and refine code across multiple languages including Python, JavaScript, and HTML. Developers can use Aider for code generation, debugging, and understanding complex projects.

I built a similar thing in python using Playwright and Pandoc [0]. It's used by aider's `/web ` command that lets you paste a markdown version of any webpage into your AI coding chat. This helps if you want to include docs for an obscure or non-public package/api/etc with the LLM while coding.

I really value dependencies which are easy for all users to install, cross-platform. Playwright is nice because it has a simple way to install its dependencies on most platforms. And the `pypandoc` module provides a seamless install of pandoc across platforms.

The result turns most web pages into nice markdown without requiring users to solve some painful platform specific chromium dependency nightmare.

[0] https://github.com/paul-gauthier/aider/blob/main/aider/scrap...

Thanks for trying aider, and sorry to hear you had trouble getting the hang of it. It might be worth looking through some of the tips on the aider GitHub page [0].

In particular, this is one of the most important tips: Large changes are best performed as a sequence of thoughtful bite sized steps, where you plan out the approach and overall design. Walk GPT through changes like you might with a junior dev. Ask for a refactor to prepare, then ask for the actual change. Spend the time to ask for code quality/structure improvements.

Not sure if this was a factor in your attempts? I'd be happy to help you if you'd like to open an GitHub issue [1] our jump into our discord [2].

[0] https://github.com/paul-gauthier/aider#tips

[1] https://github.com/paul-gauthier/aider/issues/new/choose

[2] https://discord.gg/Tv2uQnR88V

Have you tried something like Agentic’s Glide? (They announced it this week here on HN)

They use gpt, but they might be able to configure it so it uses Claude

Another tool to check out could be aider https://github.com/paul-gauthier/aider

Are you aware of the work on https://github.com/paul-gauthier/aider? What's your take on generating code diffs directly instead of code editing instructions?

He should add AI to his site!

Not really - the site is great as-is and there's nothing wrong with this approach. It looks like it works really well for Mr. 61.

But I'd imagine it'd be pretty helpful to write tools to help with maintaining the site which do leverage LLM models. Do a combination of search + AI to rewrite + reviewing the individual edits (e.g. through selective git adds).

I'm imagining a tool like https://github.com/paul-gauthier/aider (which I haven't tried yet, but it looks useful for this kind of effort).

I recently used [0] Playwright for Python and [1] pypandoc to build a scraper that fetches a webpage and turns the content into sane markdown so that it can be passed into an AI coding chat [2].

They are both very gentle dependencies to add to a project. Both packages contain built in or scriptable methods to install their underlying platform-specific binary dependencies. This means you don't need to ask end users to use some complex, platform-specific package manager to install playwright and pandoc.

Playwright let's you scrape pages that rely on js. Pandoc is great at turning HTML into sensible markdown. Below is an excerpt of the openai pricing docs [3] that have been scraped to markdown [4] in this manner.

[0] https://playwright.dev/python/docs/intro

[1] https://github.com/JessicaTegner/pypandoc

[2] https://github.com/paul-gauthier/aider

[3] https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turb...

[4] https://gist.githubusercontent.com/paul-gauthier/95a1434a28d...

  ## GPT-4 and GPT-4 Turbo

Thanks for trying aider, and sorry to hear you had trouble getting the hang of it. It might be worth looking through some of the tips on the aider github page:

https://github.com/paul-gauthier/aider#tips

In particular, this is one of the most important tips: Large changes are best performed as a sequence of thoughtful bite sized steps, where you plan out the approach and overall design. Walk GPT through changes like you might with a junior dev. Ask for a refactor to prepare, then ask for the actual change. Spend the time to ask for code quality/structure improvements.

Not sure if this was a factor in your attempts? But it's best not to ask for a big sweeping change all at once. It's hard to unambiguously and completely specify what you want, and it's also harder for GPT to succeed at bigger changes in one bite.

How does Voxos help avoid copying & pasting code into your IDE? I had a look around the code base and don't see any indication that it allows GPT to directly edit your source files. But maybe I am missing it?

I'm asking because this is a major focus of my open source AI coding project aider [0]. I always like to see how other projects approach the challenge of letting GPT edit existing code. Most recently aider adopted unified diffs as the GPT 4 Turbo code editing format [1].

[0] https://github.com/paul-gauthier/aider

[1] https://aider.chat/docs/unified-diffs.html