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💻 Codebase context

AIKoder indexes your codebase so that it can later automatically pull in the most relevant context from throughout your workspace. This is done via a combination of embeddings-based retrieval and keyword search. By default, all embeddings are calculated locally with all-MiniLM-L6-v2 and stored locally in ~/.aikoder/index.

Currently, the codebase retrieval feature is available as the "codebase" and "folder" context providers. You can use them by typing @codebase or @folder in the input box, and then asking a question. The contents of the input box will be compared with the embeddings from the rest of the codebase (or folder) to determine relevant files.

Here are some common use cases where it can be useful:

  • Asking high-level questions about your codebase
    • "How do I add a new endpoint to the server?"
    • "Do we use VS Code's CodeLens feature anywhere?"
    • "Is there any code written already to convert HTML to markdown?"
  • Generate code using existing samples as reference
    • "Generate a new React component with a date picker, using the same patterns as existing components"
    • "Write a draft of a CLI application for this project using Python's argparse"
    • "Implement the foo method in the bar class, following the patterns seen in other subclasses of baz.
  • Use @folder to ask questions about a specific folder, increasing the likelihood of relevant results
    • "What is the main purpose of this folder?"
    • "How do we use VS Code's CodeLens API?"
    • Or any of the above examples, but with @folder instead of @codebase

Here are use cases where it is not useful:

  • When you need the LLM to see literally every file in your codebase
    • "Find everywhere where the foo function is called"
    • "Review our codebase and find any spelling mistakes"
  • Refactoring
    • "Add a new parameter to the bar function and update usages"

Ignore files during indexing

AIKoder respects .gitignore files in order to determine which files should not be indexed.

If you want to see exactly what files AIKoder has indexed, the metadata is stored in ~/.aikoder/index/index.sqlite. You can use a tool like DB Browser for SQLite to view the tag_catalog table within this file.

If you need to force a refresh of the index, reload the VS Code window with cmd/ctrl + shift + p + "Reload Window", or press the indexing button on the bottom left of the chat panel.