davidyz/vectorcode

github

ai

335

7

5

17

CREATED

2025-01-11

UPDATED

yesterday

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VectorCode

VectorCode is a code repository indexing tool. It helps you build better prompt for your coding LLMs by indexing and providing information about the code repository you're working on. This repository also contains the corresponding neovim plugin because that's what I used to write this tool.

[!NOTE] This project is in beta quality and only implements very basic retrieval and embedding functionalities. There are plenty of rooms for improvements and any help is welcomed.

[!NOTE] Chromadb, the vector database backend behind this project, supports multiple embedding engines. I developed this tool using SentenceTransformer, but if you encounter any issues with a different embedding function, please open an issue (or even better, a pull request :D).

• Why VectorCode?
• Documentation
• TODOs
• Credit

Why VectorCode?

LLMs usually have very limited understanding about close-source projects, projects that are not well-known, and cutting edge developments that have not made it into releases. Their capabilities on these projects are quite limited. With VectorCode, you can easily (and programmatically) inject task-relevant context from the project into the prompt. This significantly improves the quality of the model output and reduce hallucination.

Documentation

[!NOTE] The documentation on the main branch reflects the code on the latest commit (apologies if I forget to update the docs, but this will be what I aim for). To check for the documentation for the version you're using, you can check out the corresponding tags.

• For the setup and usage of the command-line tool, see the CLI documentation;
• For neovim users, after you've gone through the CLI documentation, please refer to the neovim plugin documentation for further instructions.
• Additional resources:
  • the wiki for extra tricks and tips that will help you get the most out of VectorCode;
  • the discussions where you can ask general questions and share your cool usages about VectorCode.

If you're trying to contribute to this project, take a look at the contribution guide, which contains information about some basic guidelines that you should follow and tips that you may find helpful.

TODOs

• query by file path excluded paths;
• chunking support;
  • add metadata for files;
  • chunk-size configuration;
  • smarter chunking (semantics/syntax based), implemented with py-tree-sitter and tree-sitter-language-pack;
  • configurable document selection from query results.
• NeoVim Lua API with cache to skip the retrieval when a project has not been indexed Returns empty array instead;
• job pool for async caching;
• persistent-client;
• [-] proper remote Chromadb support (with authentication, etc.);
• respect .gitignore;
• implement some sort of project-root anchors (such as .git or a custom .vectorcode.json) that enhances automatic project-root detection. Implemented project-level .vectorcode/ and .git as root anchor
• ability to view and delete files in a collection (atm you can only drop and vectorise again);
• joint search (kinda, using codecompanion.nvim/MCP).

Credit

• Thank @milanglacier (and minuet-ai.nvim) for the support when this project was still in early stage;
• Thank @olimorris for the help (personally and from codecompanion.nvim) when this project made initial attempts at tool-calling;
• Thank @ravitemer for the help to interface VectorCode with MCP.