Claude Code has /init and /compact that do this. It doesn’t recreate the context as-is, but creates a context that is presumed to be functionally equivalent. I find that’s not the case and that building up from very little stored context and a lot of specialised dialogue works better.
So it's not STT -> LLM -> TTS? If I scream Chewbacca noises as input, will the model recognize it as nonsense, or will it interpret it with some lousy STT as some random words?
It's not, but it probably won't recognize it as nonsense. According to the paper,
> we construct a dataset named InstructS2S-200K by rewriting existing text instruction data and performing speech synthesis
It has only been trained on questions spoken by TTS, it has never seen (heard) nonsense. Most likely it'll just hallucinate that you asked some question and it'll generate some answer instead of asking if you're good. There's just not many audio datasets with real voices, there's no audio version of StackOverflow to be scraped
I used to have fun with that. Set Google Translate to Chinese (Or some other language I don't speak, though tonal languages seemed to work better), make some vague noises into it, and get out coherent but crazy phrases in English.
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.
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.
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.
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.
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.
>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.
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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