aider VS llama-cpp-python

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

There is a bit of learning curve to figuring out the most effective ways to collaboratively code with GPT, either through aider or other UXs. My best piece of advice is taken from aider's tips list and applies broadly to coding with LLMs:

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.

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

There's a Python binding for llama.cpp which is actively maintained and has worked well for me: https://github.com/abetlen/llama-cpp-python

I'll share the core bit that took a while to figure out the right format, my main script is a hot mess using embeddings with SentenceTransformer, so I won't share that yet. E.g: last night I did a PR for llama-cpp-python that shows how Phi might be used with JSON only for the author to write almost exactly the same code at pretty much the same time. https://github.com/abetlen/llama-cpp-python/pull/1184

Python Bindings for llama.cpp

If the model could be made to work with llama.cpp, then https://github.com/abetlen/llama-cpp-python might be more compact. llama.cpp only supports a limited list of model types though.

https://github.com/abetlen/llama-cpp-python has a web server mode that replicates openai's API iirc and the readme shows it has docker builds already.

LocalAI https://localai.io/ and LMStudio https://lmstudio.ai/ both have fairly complete OpenAI compatibility layers. llama-cpp-python has a FastAPI server as well: https://github.com/abetlen/llama-cpp-python/blob/main/llama_... (as of this moment it hasn't merged GGUF update yet though)

I went with Python, llama-cpp-python, since my goal is just to get a small project up and running locally.