From 2c08cc47e6bbad657dfecf27afcae1cebc4494e5 Mon Sep 17 00:00:00 2001 From: Paul Gauthier Date: Tue, 10 Sep 2024 13:38:25 -0700 Subject: [PATCH] copy --- aider/website/docs/ctags.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/aider/website/docs/ctags.md b/aider/website/docs/ctags.md index b57f8de33..11bb4f05f 100644 --- a/aider/website/docs/ctags.md +++ b/aider/website/docs/ctags.md @@ -12,6 +12,7 @@ nav_exclude: true ![robot flowchat](/assets/robot-flowchart.png) + ## Updated Aider no longer uses ctags to build a repo map. @@ -228,7 +229,7 @@ Some possible approaches to reducing the amount of map data are: - Distill the global map, to prioritize important symbols and discard "internal" or otherwise less globally relevant identifiers. Possibly enlist `gpt-3.5-turbo` to perform this distillation in a flexible and language agnostic way. - Provide a mechanism for GPT to start with a distilled subset of the global map, and let it ask to see more detail about subtrees or keywords that it feels are relevant to the current coding task. - - Attempt to analyize the natural language coding task given by the user and predict which subset of the repo map is relevant. Possibly by analysis of prior coding chats within the specific repo. Work on certain files or types of features may require certain somewhat predictable context from elsewhere in the repo. Vector and keyword search against the chat history, repo map or codebase may help here. + - Attempt to analyze the natural language coding task given by the user and predict which subset of the repo map is relevant. Possibly by analysis of prior coding chats within the specific repo. Work on certain files or types of features may require certain somewhat predictable context from elsewhere in the repo. Vector and keyword search against the chat history, repo map or codebase may help here. One key goal is to prefer solutions which are language agnostic or which can be easily deployed against most popular code languages.