|
|
|
|
|
by pbmonster
1031 days ago
|
|
Depending on how serious you are about this (and how well you can slap together a few different python packages), it is very doable today. Get one of the better llama versions fine-tuned on code (e.g. WizardCoder), take your entire code base and create embeddings from it, put those into a vector database. Now, every time you ask your LLM a question about your code base, you first turn that prompt into an embedding and perform a search on your vector database. The results of that search are appended as context to the actual prompt before passing it to the LLM itself. There's tons of packages that help with all of that, Langchain and Faiss are probably the most popular right now. |
|
thanks for the helpful keywords though, it helps point me in the right direction.