Panlingo

Overview

Welcome to the Panlingo repository! 🚀

This project presents a comprehensive collection of language identification libraries for .NET. Its primary purpose is to bring popular language identification models to the .NET ecosystem, allowing developers to seamlessly integrate language detection functionality into their applications.

Libraries

| Library | NuGet Package | | :------ | :------------ | | Panlingo.LanguageIdentification.CLD2 | | | Panlingo.LanguageIdentification.CLD3 | | | Panlingo.LanguageIdentification.FastText | | | Panlingo.LanguageIdentification.Whatlang | | | Panlingo.LanguageIdentification.MediaPipe | | | Panlingo.LanguageIdentification.Lingua | | | Panlingo.LanguageCode | |

Contents

1. Models
2. Features
3. Platform Support
4. Key Concerns
5. Contributing
6. License

Models

| Model | Authors | License | Original source code | Wrapper docs | | :------------ | :------------------- | :--------- | :------------------- | :------------------- | | CLD2 | Google, Inc. | Apache-2.0 | @CLD2Owners/cld2 | link | | CLD3 | Google, Inc. | Apache-2.0 | @google/cld3 | link | | FastText | Meta Platforms, Inc. | MIT | @facebookresearch/fastText | link | | Whatlang | Serhii Potapov | MIT | @greyblake/whatlang-rs | link | | MediaPipe | Google, Inc. | Apache-2.0 | @google-ai-edge/mediapipe | link | | Lingua | Peter M. Stahl | Apache-2.0 | @pemistahl/lingua-rs | link |

Key concerns

• Zero-dependency development.
• The original code of libraries (CLD2, CLD3, FastText, MediaPipe) is used as submodules without additional significant modifications or improvements (except for a small monkey-patching 😂). Third-party code is not included into this repository.
• Preserve the original library behavior without breaking changes.

Features

| Feature | CLD2 | CLD3 | FastText* | Whatlang | MediaPipe** | Lingua | | :----------------------------- | :-------: | :------------: | :----------------: | :------: | :------------: | :------: | | Single language prediction | Yes | Yes | Yes | Yes | Yes | Yes | | Multi language prediction | Yes | Yes | Yes | No | Yes | Yes | | Supported languages | 83 | 107 | 176 or 217 | 69 | 110 | 75 | | Unknown language detection | Yes | Yes | No | No | Yes | No | | Algorithm | quadgrams | neural network | neural network | trigrams | neural network | trigrams | | Script detection | No | No | Yes (only lid218e) | Yes | No | No | | Written in | C++ | C++ | C++ | Rust | C++ | Rust |

* When using these models: lid176, lid218e

** When using MediaPipe Language Detector

Platform support

| Model | Linux (x86_64) | Linux (arm64) | Windows (x86_64) | Windows (arm64) | macOS (x86_64) | macOS (arm64) | | :------------ | :----------------: | :----------------: | :----------------: | :----------------: | :----------------: | :----------------: | | CLD2 | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | | CLD3 | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | | FastText | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | | Whatlang | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | | MediaPipe | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: | :white_check_mark: | | Lingua | :white_check_mark: | :x: | :white_check_mark: | :x: | :x: | :white_check_mark: |

:white_check_mark: — Full support | :x: — No support | :construction: — Under research

Contributing

We welcome contributions from developers of all skill levels. Whether you're fixing a bug, adding a new feature, or improving documentation, we appreciate your help in making this project better.

Getting Started

To get started with contributing, follow these simple steps:

1. Clone the Repository

   First, clone the repository to your local machine with the following command:

   git clone --recurse-submodules --remote-submodules https://github.com/gluschenko/panlingo.git
   

2. Create a Branch

   Before you start making changes, create a new branch to keep your work organized. Use a descriptive name for your branch to make it easy to understand its purpose:

   git checkout -b feature/your-feature-name
   

3. Make Changes

   Now, you can make changes to the codebase. Please ensure your code follows our project's coding standards and includes relevant tests if applicable.

4. Commit Your Changes

   Once you've made your changes, commit them with a clear and informative commit message:

   git add .
   git commit -m "Add description of your changes"
   

5. Push Your Changes

   Push your branch to the remote repository:

   git push origin feature/your-feature-name
   

6. Build

   Each library project in the solution has four configurations: ReleaseLinuxOnly, DebugLinuxOnly, Release, and Debug.

   • The ReleaseLinuxOnly and DebugLinuxOnly configurations are for building on a local Linux or Windows machine (WSL is supported as well). It produces native binaries only for Linux.
   • The Release and Debug configurations are intended for cross-platform builds, which are only supported in CI/CD environments like GitHub Actions.

   Here's how you can build the projects on a local Linux machine.

   Requirements:

   • Windows 10 or higher.
   • WSL2 set up for simulating a Linux environment.
   • Docker Desktop for container management.
   • 45GB+ of free disk space for storing Docker images.
   • Modern CPU with AVX support for optimal performance.

   To build the entire solution:

   cd src
   dotnet build -c ReleaseLinuxOnly
   

   To build a specific library:

   cd src/LanguageIdentification.FastText.Native
   dotnet build -c ReleaseLinuxOnly
   
   cd src/LanguageIdentification.FastText
   dotnet build -c ReleaseLinuxOnly
   

7. Test

   To execute the test project on Linux or Windows, follow these instructions:

   • Linux:

     For Linux systems, access the test project's directory and execute:

     cd src/LanguageIdentification.Tests
     dotnet test -c ReleaseLinuxOnly
     

   • Windows:

     On Windows, you can utilize WSL to run the test project. Do so by:

     cd src/LanguageIdentification.Tests
     wsl -d Ubuntu -e bash -c "dotnet test -c ReleaseLinuxOnly"
     

   • Docker:

     Also you can run test project inside Docker-container on every supported platform (see run-tests.ps1 and run-tests.sh):

     cd src
     docker build --file test.Dockerfile -t panlingo-test-image .
     docker container create --name panlingo-test-runner -v "${PWD}:/src" -i panlingo-test-image