RepoGraph

Absolutely! Code has vastly more useful structure than prose. Aider exploits all this structure, using a "repository map" [0]. It use tree-sitter to build a call graph of the code base. Then runs a graph optimization on it with respect to the current state of the AI coding chat. This finds the most relevant parts of the code base, which aider shares with the LLM as context. Your first link to RepoGraph is an adaptation of the actual aider repo map implementation. In their source code [1], they have some acknowledgements to aider and grep-ast (which is part of aider). [0] https://aider.chat/docs/repomap.html [1] https://github.com/ozyyshr/RepoGraph/blob/79861642515f0d6b17...

For 2 years I built RAG apps for clients. They are not Code-Assistants but everytime I see code assistants solely relying on embeddings to find the right pieces as context, it feels wrong to me: Code is very well structured. Based on a starting point (current cursor, current file, or results of an embedding search result) you would probably fair better to traverse the code tree up and down building a tree or using Abstract Syntax Trees (ASTs) as described in this blog post [4]. It's like a tree search in order to get relevant code pieces for a certain task, and it imitates what human coders do. It would integrate well into an agent loop to search relevant code. Aren't there any open source code assistants and plugins that do this? All I see are embedding searches for the big projects such as cursor, cline or continue. All I ever found wer