continue VS aider

Continue (YC S23) | Founding Engineer | ONSITE | Full-time | San Francisco | $130-$170K + 1-2% Equity

At Continue, we are on a mission to make building software feel like making music. We are creating the open-source autopilot for VS Code and JetBrains——the easiest way to code with any LLM (https://github.com/continuedev/continue).

You are likely a good fit if you

- have founded or want to found your own startup one day

- have experience with frontend, backend, ML technologies

- are enthusiastic about AI/LLMs, open source, developer tools

- get excited about supporting users and helping customers

- want to work in-person in SF the majority of the time

More info: https://www.ycombinator.com/companies/continue/jobs/smcxRnM-...

Continue doesn’t support tab completion like Copilot yet.

A pull/merge request is being worked on: https://github.com/continuedev/continue/pull/758

Good job on the project, but it's unfortunately named. A privy also refers to a latrine.

Given that this project was started well after Continue.dev, I think it would be useful to include an FAQ or a comparison table on what exactly makes this project different.

https://github.com/continuedev/continue

In this Continue.dev file https://github.com/continuedev/continue/blob/preview/server/continuedev/libs/llm/llamacpp.py the request to llama.cpp is implemented.

Continue | Founding Engineer | ONSITE | Full-time | San Francisco | $130-$170K + 1-2% Equity

At Continue, we are on a mission to make building software feel like making music. We are creating the open-source autopilot for software development—an IDE extension that brings the power of ChatGPT to VS Code and JetBrains (https://github.com/continuedev/continue).

You are likely a good fit if you

- have founded or want to found your own startup one day

- have experience with frontend, backend, and ML technologies

- are enthusiastic about AI/LLMs, open source, developer tools

- get excited about supporting users and helping customers

- want to work in-person in SF the majority of the time

More info: https://www.ycombinator.com/companies/continue/jobs/smcxRnM-...

Original source: https://github.com/continuedev/continue/tree/main/docs/docs/languages/matlab.md

We are seeing developers deploy open-source LLMs for their teams to use while coding internally, which each developer then uses with Continue

Hi HN!

Since launching Continue two months ago (https://news.ycombinator.com/item?id=36882146), we've received amazing feedback, added features, and greatly improved reliability. But one of the biggest things we heard was the desire for a JetBrains extension. My co-founder Ty and I are super excited to share that we've released an extension for PyCharm, Intellij, WebStorm, and most other JetBrains IDEs - ready for alpha users at https://plugins.jetbrains.com/plugin/22707-continue.

Perhaps the most exciting part is that this effort was kickstarted and in great part developed by a community contributor! If you're curious what it took to make this happen, check out the PR here (https://github.com/continuedev/continue/pull/457). We hope to eventually support every IDE, so we made adding a new extension as easy as implementing a single class. If you're curious why this is possible, you can read more about the Continue Server and the architectural decisions we made here: https://blog.continue.dev/how-we-made-continue-ide-agnostic.

My open source tool aider [0] has long offered a "AI pair programming" workflow. Aider's UX is similar but not identical to Copilot Workspaces.

Aider is more of a collaborative chat, where you work with the LLM interactively asking for a sequence of changes to your git repo. The changes can be non-trivial, modifying a group of files in a coordinated way. So much more than just the original copilot "autocomplete".

Workspaces seems more agentic, a bit like Devin. You need to do a bunch of up-front work to (fully) specify the requirements. Then the agent goes off and (hopefully) builds what you want. You need to fully understand what you want to build up front, and you need the describe it unambiguously to the agent. Also, even with a perfect request, agents often go down wrong paths and waste a lot of time and token costs doing the wrong thing.

That's not how I code personally. My process is more iterative, where I explore the problem and solution spaces as I build.

The other difference between aider and Workspaces is that currently aider is a terminal CLI tool. Although I just released a basic browser UI [1] the other day, making it more approachable for folks who are not fully comfortable on the command line.

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

[1] https://aider.chat/2024/05/02/browser.html

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.