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Comment by cvzakharchenko | Hacker News Reader

Oh, I’m yet to find a good alternative to Cursor’s RAG-powered side chat. It helps me work with huge codebases so much. Tried Continue, but it’s very unstable, and doesn’t work as well. Would prefer a command line solution, vscode plugin is the next choice, having a separate editor is not ideal, but I’m glad there’s some competition.

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Aider is AI pair programming in your terminal.

Aider lets you pair program with LLMs, to edit code in your local git repository. Start a new project or work with an existing git repo. Aider works best with GPT-4o & Claude 3.5 Sonnet and can connect to almost any LLM.

https://aider.chat/

See LLM Leaderboards as well: https://aider.chat/docs/leaderboards/

Thanks! I use Aider with Claude 3.5 Sonnet on smaller projects sometimes, and it's really fun and helpful when it can put a whole repo map into the LLM's context.

> Would prefer a command line solution

I haven't tried this myself so I apologize if it ends up being bad, but I've seen Aider [0] get linked a few times from people who wanted a CLI solution for AI code completion.

[0]: https://aider.chat/

Aider is really cool for small projects, but it builds a repo map instead of using RAG. That works on small codebases, but totally fails to be useful on large ones.

How large?

In use, treesitter-derived approach seems far effective than rag.

>5k source files. They don't fit into the context. I know I can limit what is sent, and I can attach files in the Aider chat myself. But this is not perfect for making an LLM answer questions about a codebase when I don't know much context beforehand. With Cursor, I can just do "@codebase How is a %feature% implemented?", and it's very quick and often helpful with a couple of follow-ups.

Not sure if this is what you'd like, but I remember this repo from some time ago https://github.com/Storia-AI/sage

Storia-AI/sage: Chat with any codebase with 2 commands

Thanks for the suggestion! It needs some work to set up, and it looks like it only works on Github repos. Also, to work with non-local LLMs, you can only use Pinecone for vector storage. I might have misunderstood something, but I will check it out again later.

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