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* Move CONTRIBUTING.md + Ad Test for Adding New Models * Update CONTRIBUTING.md Co-authored-by: Kumar Shivendu <kshivendu1@gmail.com> --------- Co-authored-by: Kumar Shivendu <kshivendu1@gmail.com>
78 lines
4.6 KiB
Markdown
78 lines
4.6 KiB
Markdown
# Contributing to FastEmbed!
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:+1::tada: First off, thanks for taking the time to contribute! :tada::+1:
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The following is a set of guidelines for contributing to FastEmbed. These are mostly guidelines, not rules. Use your best judgment, and feel free to propose changes to this document in a pull request.
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## Table Of Contents
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[I don't want to read this whole thing, I just have a question!!!](#i-dont-want-to-read-this-whole-thing-i-just-have-a-question)
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[How Can I Contribute?](#how-can-i-contribute)
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* [Your First Code Contribution](#your-first-code-contribution)
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* [Adding New Models](#adding-new-models)
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[Styleguides](#styleguides)
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* [Code Lint](#code-lint)
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* [Pre-Commit Hooks](#pre-commit-hooks)
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## I don't want to read this whole thing I just have a question!!!
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> **Note:** Please don't file an issue to ask a question. You'll get faster results by using the resources below:
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* [FastEmbed Docs](https://qdrant.github.io/fastembed/)
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* [Qdrant Discord](https://discord.gg/Qy6HCJK9Dc)
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## How Can I Contribute?
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## How Do I Submit A (Good) Bug Report?
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Bugs are tracked as [GitHub issues](https://guides.github.com/features/issues/).
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Explain the problem and include additional details to help maintainers reproduce the problem:
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* **Use a clear and descriptive title** for the issue to identify the problem.
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* **Describe the exact steps which reproduce the problem** in as many details as possible. For example, start by explaining how you are using FastEmbed, e.g. with Langchain, Qdrant Client, Llama Index and which command exactly you used. When listing steps, **don't just say what you did, but explain how you did it**.
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* **Provide specific examples to demonstrate the steps**. Include links to files or GitHub projects, or copy/pasteable snippets, which you use in those examples. If you're providing snippets in the issue, use [Markdown code blocks](https://help.github.com/articles/markdown-basics/#multiple-lines).
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* **Describe the behavior you observed after following the steps** and point out what exactly is the problem with that behavior.
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* **Explain which behavior you expected to see instead and why.**
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* **If the problem is related to performance or memory**, include a [call stack profile capture](https://github.com/joerick/pyinstrument) and your observations.
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Include details about your configuration and environment:
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* **Which version of FastEmbed are you using?** You can get the exact version by running `python -c "import fastembed; print(fastembed.__version__)"`.
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* **What's the name and version of the OS you're using**?
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* **Which packages do you have installed?** You can get that list by running `pip freeze`
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### Your First Code Contribution
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Unsure where to begin contributing to FastEmbed? You can start by looking through these `good-first-issue`issues:
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* [Good First Issue](https://github.com/qdrant/fastembed/labels/good%20first%20issue) - issues which should only require a few lines of code, and a test or two. These are a great way to get started with FastEmbed. This includes adding new models which are already tested and ready on Huggingface Hub.
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## Pull Requests
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The best way to learn about the mechanics of FastEmbed is to start working on it.
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### Your First Code Contribution
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Your first code contribution can be small bug fixes:
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1. This PR adds a small bug fix for a single input: https://github.com/qdrant/fastembed/pull/148
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2. This PR adds a check for the right file location and extension, specific to an OS: https://github.com/qdrant/fastembed/pull/128
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Even documentation improvements and tests are most welcome:
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1. This PR fixes a README link: https://github.com/qdrant/fastembed/pull/143
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### Adding New Models
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1. Open Requests for New Models are [here](https://github.com/qdrant/fastembed/labels/model%20request).
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2. There are quite a few pull requests that were merged for this purpose and you can use them as a reference. Here is an example: https://github.com/qdrant/fastembed/pull/129
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3. Make sure to add tests for the new model
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- The CANONICAL_VECTOR values must come from a reference implementation usually from Huggingface Transformers or Sentence Transformers
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- Here is a reference [Colab Notebook](https://colab.research.google.com/drive/1tNdV3DsiwsJzu2AXnUnoeF5av1Hp8HF1?usp=sharing) for how we will evaluate whether your VECTOR values in the test are correct or not.
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## Styleguides
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### Code Lint
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We use ruff for code linting. It should be installed with poetry since it's a dev dependency.
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### Pre-Commit Hooks
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We use pre-commit hooks to ensure that the code is linted before it's committed. You can install pre-commit hooks by running `pre-commit install` in the root directory of the project. |