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docs: add links for wiki and discussion to README. (#89)
* docs: add links for wiki and discussion to README. * add logging to CONTRIBUTING.md * replace demo with codecompanion chat.
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README.md

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[![Test and Coverage](https://github.com/Davidyz/VectorCode/actions/workflows/test_and_cov.yml/badge.svg)](https://github.com/Davidyz/VectorCode/actions/workflows/test_and_cov.yml)
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[![pypi](https://img.shields.io/pypi/v/vectorcode.svg)](https://pypi.org/project/vectorcode/)
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VectorCode is a code repository indexing tool. It helps you write better prompt
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VectorCode is a code repository indexing tool. It helps you build better prompt
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for your coding LLMs by indexing and providing information about the code
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repository you're working on. This repository also contains the corresponding
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neovim plugin because that's what I used to write this tool.
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## Why VectorCode?
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LLMs usually have very limited understanding about close-source projects, projects
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that are not well-known, and cutting edge developments that have not made it into
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releases. Their capabilities on these projects are quite limited. Take my little
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toy sudoku-solving project as an example: When I wrote the first few lines and
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want the LLM to fill in the list of solvers that I implemented in
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`solver_candidates`, without project context, the completions are simply random
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guesses that *might* be part of another sudoku project:
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![](./images/sudoku_no_rag.png)
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But with RAG context provided by VectorCode, my completion LLM was able to
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provide completions that I actually implemented:
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![](./images/sudoku_with_rag.png)
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This makes the completion results far more usable.
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[A similar strategy](https://docs.continue.dev/customize/deep-dives/codebase)
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is implemented in [continue](https://www.continue.dev/), a popular AI completion
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and chat plugin available on VSCode and JetBrain products.
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releases. Their capabilities on these projects are quite limited. With
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VectorCode, you can easily (and programmatically) inject task-relevant context
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from the project into the prompt. This significantly improves the quality of the
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model output and reduce hallucination.
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![](./images/codecompanion_chat.png)
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## Documentation
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- For the setup and usage of the command-line tool, see [the CLI documentation](./docs/cli.md);
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- For neovim users, after you've gone through the CLI documentation, please refer to
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[the neovim plugin documentation](./docs/neovim.md) for further instructions.
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- Additional resources:
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- the [wiki](https://github.com/Davidyz/VectorCode/wiki) for extra tricks and
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tips that will help you get the most out of VectorCode;
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- the [discussions](https://github.com/Davidyz/VectorCode/discussions) where
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you can ask general questions and share your cool usages about VectorCode.
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If you're trying to contribute to this project, take a look at [the contribution
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guide](./docs/CONTRIBUTING.md), which contains information about some basic

docs/CONTRIBUTING.md

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coverage report are also in the CI configuration, but it might still help to run
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them locally before you open the PR.
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You may also find it helpful to
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[enable logging](https://github.com/Davidyz/VectorCode/blob/main/docs/cli.md#debugging-and-diagnosing)
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for the CLI when developing new features or working on fixes.
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# Neovim Plugin
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At the moment, there isn't much to cover on here. As long as the code is
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formatted (stylua) and appropriately type-annotated, you're good. I do have
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plans to write some tests, but before that happens, formatting and type
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annotations are the only things that you need to take special care of.
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You may find it useful to
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[enable logging](https://github.com/Davidyz/VectorCode/blob/main/docs/cli.md#debugging-and-diagnosing)
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when you're poking around the codebase.

images/codecompanion_chat.png

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