Co-op Translator: Effortless Multilingual Translation Solution for Project Documentation

Easily automate multilingual translations for your projects with co-op-translator, powered by advanced LLM technology and Azure AI Services.

Table of contents

• Overview
• Why choose Co-op Translator for Markdown translations?
• Key Features
• How it works
• Getting started with Co-op Translator
  • Prerequisites
  • Quick install
  • How to use Co-op Translator
• Case Studies: Applying Co-op Translator in real projects
• 🌐Multi-language support setup
• Supported languages
• Adding a new language
• Repository Structure
• Contributing
• Code of Conduct
• Responsible AI
• Trademarks

Overview

Co-op Translator is a Python package designed to automate multilingual translations for your projects using advanced Large Language Model (LLM) technology and Azure AI Services. This project aims to simplify the process of translating content into multiple languages, making it accessible and efficient for developers.

By integrating Co-op Translator into your workflow, you can automatically generate organized translation folders for different languages, and translate both Markdown files and images effortlessly.

Here is an example of how Co-op Translator structures the translations and translates both Markdown files and text within images in your project:

Why choose Co-op Translator for Markdown translations?

Have you struggled with traditional translation tools when working with Markdown files? Many translation engines fail to preserve Markdown syntax, forcing you to manually fix formatting issues after translation. Even advanced tools like ChatGPT can misinterpret code blocks, making it hard to copy and paste the translated content while maintaining the original structure.

Co-op Translator is specifically designed to solve these problems. With a single command, you can translate all Markdown files and images in your project into any desired language while preserving the correct Markdown syntax.

Translate your project's Markdown files effortlessly with Co-op Translator!

Key features

• Automated translations: Easily translate text in your project files into multiple languages.
• Comprehensive coverage: Translate all Markdown files and text within images in your project directories.
• Advanced LLM technology: Utilize cutting-edge language models for high-quality translations.
• Simplify localization: Streamline the process of localizing your project for international markets.
• Easy integration: Seamlessly integrate with your existing project setup.

How it works

The process begins with Markdown and image files from your project folder, which are processed by Azure AI Services:

• Azure OpenAI: Translates text from Markdown files.
• Azure Computer Vision: Extracts text from images, which are then translated by Azure OpenAI.

The final translated Markdown and image files are saved in the designated translation folder, ready to be used in multiple languages.

Getting started with Co-op Translator

Prerequisites

• Azure Computer vision resource
• Azure OpenAI resource
• Python 3.10 or higher

Quick install

Install Co-op Translator via pip

pip install co-op-translator

Install Co-op Translator via poetry

poetry add co-op-translator

How to use Co-op Translator

1. Set up Azure resources before starting
2. Create an '.env' file in the root directory
3. Install the Co-op translator package
4. Translate your project using Co-op Translator

Case Studies: Applying Co-op Translator in real projects

These case studies show how Co-op Translator was applied to translate a real-world project. It highlights the translation process, the challenges encountered, and the results achieved, providing a useful reference for applying the tool to similar projects.

1. Phi-3 Cookbook translation: A case study

🌐 Multi-language support setup

Before starting the translation process, you can add a table in the README that links to the translated versions of your document. Co-op Translator will automatically adjust these links during the translation process, allowing users to seamlessly switch between different language versions.

For example, if a user navigates to the Korean README, they can easily switch to other translations like Spanish or Japanese without leaving the translated page.

Here is an example of how the table should look before running the translation:

Example

## 🌐 Multi-Language Support

> **Note:**
> These translations were automatically generated using the open-source [co-op-translator](https://github.com/Azure/co-op-translator) and may contain errors or inaccuracies. For critical information, it is recommended to refer to the original or consult a professional human translation. If you'd like to add or update a translation, please refer to the [co-op-translator](https://github.com/Azure/co-op-translator) repository, where you can easily contribute using simple commands.

| Language             | Code | Link to Translated README                               | Last Updated |
|----------------------|------|---------------------------------------------------------|--------------|
| Chinese (Simplified) | zh   | [Chinese Translation](./translations/zh/README.md)      | 2024-10-04   |
| Chinese (Traditional)| tw   | [Chinese Translation](./translations/tw/README.md)      | 2024-10-04   |
| French               | fr   | [French Translation](./translations/fr/README.md)       | 2024-10-04   |
| Japanese             | ja   | [Japanese Translation](./translations/ja/README.md)     | 2024-10-04   |
| Korean               | ko   | [Korean Translation](./translations/ko/README.md)       | 2024-10-04   |
| Spanish              | es   | [Spanish Translation](./translations/es/README.md)      | 2024-10-04   |

Simplified example

## 🌐 Multi-Language Support

| [English](./translations/en/README.md) | [French](./translations/fr/README.md) | [Spanish](./translations/es/README.md) | [German](./translations/de/README.md) | [Russian](./translations/ru/README.md) | [Arabic](./translations/ar/README.md) | [Persian (Farsi)](./translations/fa/README.md) | [Urdu](./translations/ur/README.md) | [Chinese (Simplified)](./translations/zh/README.md) | [Chinese (Traditional, Macau)](./translations/mo/README.md) | [Chinese (Traditional, Hong Kong)](./translations/hk/README.md) | [Chinese (Traditional, Taiwan)](./translations/tw/README.md) | [Japanese](./translations/ja/README.md) | [Korean](./translations/ko/README.md) | [Hindi](./translations/hi/README.md) | [Bengali](./translations/bn/README.md) | [Marathi](./translations/mr/README.md) | [Nepali](./translations/ne/README.md) | [Punjabi (Gurmukhi)](./translations/pa/README.md) | [Portuguese](./translations/pt/README.md) | [Italian](./translations/it/README.md) | [Polish](./translations/pl/README.md) | [Turkish](./translations/tr/README.md) | [Greek](./translations/el/README.md) | [Thai](./translations/th/README.md) | [Swedish](./translations/sv/README.md) | [Danish](./translations/da/README.md) | [Norwegian](./translations/no/README.md) | [Finnish](./translations/fi/README.md) | [Dutch](./translations/nl/README.md) | [Hebrew](./translations/he/README.md) | [Vietnamese](./translations/vi/README.md) | [Indonesian](./translations/id/README.md) | [Malay](./translations/ms/README.md) | [Tagalog (Filipino)](./translations/tl/README.md) | [Swahili](./translations/sw/README.md) | [Hungarian](./translations/hu/README.md) | [Czech](./translations/cs/README.md) | [Slovak](./translations/sk/README.md) | [Romanian](./translations/ro/README.md) | [Bulgarian](./translations/bg/README.md) | [Serbian (Cyrillic)](./translations/sr/README.md) | [Croatian](./translations/hr/README.md) | [Slovenian](./translations/sl/README.md) |

> **Note:**
> These translations were automatically generated using the open-source [co-op-translator](https://github.com/Azure/co-op-translator) and may contain errors or inaccuracies. For critical information, it is recommended to refer to the original or consult a professional human translation. If you'd like to add or update a translation, please refer to the [co-op-translator](https://github.com/Azure/co-op-translator) repository, where you can easily contribute using simple commands.

Supported languages

The table below lists the languages currently supported by Co-op Translator. It includes language codes, language names, and any known issues associated with each language. If you would like to add support for a new language, please add the corresponding language code, name, and appropriate font in the font_language_mappings.yml file located at src/co_op_translator/fonts/ and submit a pull request after testing.

Adding a new language

To add support for a new language:

1. Go to src/co_op_translator/fonts/font_language_mappings.yml.
2. Add the language code, name, and appropriate font file name. Make sure to include the rtl attribute if the language is right-to-left.
3. If you need to use a new font, ensure that the font is free to use in open-source projects by checking its licensing and copyright terms. After verifying, add the font file to the src/co_op_translator/fonts/ directory.
4. Test your changes locally to ensure that the new language is properly supported.
5. Submit a Pull Request with your changes and indicate the addition of the new language in the PR description.

Example:

new_lang:
  name: "New Language"
  font: "NotoSans-Medium.ttf"
  rtl: false

Repository Structure

• src/co_op_translator/: Source code for the translator.
• getting_started/: Guides and tutorials to get started.
• imgs/: Images used in documentation.
• tests/: Test cases for the project.
• data/: Contains data files.

Contributing

This project welcomes contributions and suggestions. Interested in contributing to Azure Co-op Translator? Please see our CONTRIBUTING.md for guidelines on how you can help make Co-op Translator more accessible.

Contributors

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Responsible AI

Microsoft is committed to helping our customers use our AI products responsibly, sharing our learnings, and building trust-based partnerships through tools like Transparency Notes and Impact Assessments. Many of these resources can be found at https://aka.ms/RAI. Microsoft’s approach to responsible AI is grounded in our AI principles of fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.

Large-scale natural language, image, and speech models - like the ones used in this sample - can potentially behave in ways that are unfair, unreliable, or offensive, in turn causing harms. Please consult the Azure OpenAI service Transparency note to be informed about risks and limitations.

The recommended approach to mitigating these risks is to include a safety system in your architecture that can detect and prevent harmful behavior. Azure AI Content Safety provides an independent layer of protection, able to detect harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes text and image APIs that allow you to detect material that is harmful. We also have an interactive Content Safety Studio that allows you to view, explore and try out sample code for detecting harmful content across different modalities. The following quickstart documentation guides you through making requests to the service.

Another aspect to take into account is the overall application performance. With multi-modal and multi-models applications, we consider performance to mean that the system performs as you and your users expect, including not generating harmful outputs. It's important to assess the performance of your overall application using generation quality and risk and safety metrics.

You can evaluate your AI application in your development environment using the prompt flow SDK. Given either a test dataset or a target, your generative AI application generations are quantitatively measured with built-in evaluators or custom evaluators of your choice. To get started with the prompt flow sdk to evaluate your system, you can follow the quickstart guide. Once you execute an evaluation run, you can visualize the results in Azure AI Studio.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.