Lingtrain Studio is a powerful, open-source application designed for aligning texts in different languages. It leverages machine learning models to create high-quality parallel corpora, which can be used for a variety of purposes, including training translation models, creating bilingual books, and for language learning.

The application provides a user-friendly interface for aligning texts, as well as a tool for translators to edit and refine the alignments. It also supports a variety of models, allowing users to choose the best one for their specific needs.

• Accurate Text Alignment: Utilizes state-of-the-art sentence embedding models to accurately align texts in different languages.
• Parallel Corpus Creation: Extracts parallel corpora from two texts, which can be used for a variety of downstream tasks.
• Bilingual Book Formatter: Creates formatted parallel books with sentence highlighting, making them ideal for language learners.
• Model Flexibility: Supports a variety of sentence embedding models, including distiluse-base-multilingual-cased-v2, LaBSE, and SONAR.
• User-Friendly Interface: Provides a simple and intuitive interface for aligning texts and editing alignments.
• Dockerized Deployment: Can be easily deployed on a local machine or a server using Docker.

%%{ init: {
     "theme": "base",
     "themeVariables": {
       "fontFamily": "Inter, Roboto, Helvetica, Arial, sans-serif",
       "primaryColor":    "#3F51B5",
       "primaryBorderColor":"#303F9F",
       "primaryTextColor":"#FFFFFF",
       "clusterBkg":      "#E8EAF6",
       "clusterBorder":   "#3F51B5",
       "lineColor":       "#303F9F"
     }
   }
}%%

flowchart TD
    %% ─── Nodes ────────────────────────────────────────────────
    A["<fa:fa-user>  User"]:::user

    subgraph "Frontend"
        direction TB
        B["<fa:fa-window-maximize>  SPA (Vue)"]:::frontend
    end

    subgraph "Backend"
        direction TB
        C["<fa:fa-server>  API Service<br/>(Flask)"]:::backend
        D["<fa:fa-cogs>  lingtrain_aligner"]:::core
        E["<fa:fa-brain>  Embedding Models<br/>(LaBSE, SONAR…)"]:::model
        F["<fa:fa-database>  Data Storage"]:::storage
    end

    %% ─── Connections ──────────────────────────────────────────
    A -- "HTTP"      --> B
    B -- "REST API"  --> C
    C --> D
    D -- "Vectorise" --> E
    C -- "CRUD"      --> F

    %% ─── Styles ───────────────────────────────────────────────
    classDef user     fill:#4FC3F7,stroke:#0288D1,stroke-width:2px,color:#fff,font-weight:bold;
    classDef frontend fill:#AED581,stroke:#7CB342,stroke-width:2px;
    classDef backend  fill:#FFB74D,stroke:#F57C00,stroke-width:2px;
    classDef core     fill:#E57373,stroke:#D32F2F,stroke-width:3px,font-weight:bold;
    classDef storage  fill:#8D6E63,stroke:#5D4037,stroke-width:2px,color:#fff;
    classDef model    fill:#9575CD,stroke:#512DA8,stroke-width:2px,color:#fff;

• Docker
• Docker Compose

1. Clone the repository:

   git clone https://github.com/lingtrain/a-studio.git

2. Navigate to the project directory:

   cd a-studio

3. Build and run the application using Docker Compose:

   docker-compose build
   docker-compose up

The application will be available at http://localhost:80.

The backend is a Flask/uwsgi REST API service that contains all the alignment logic.

1. Navigate to the backend directory:

   cd backend

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the backend application:

   python main.py

The frontend is a Vue.js single-page application that provides the user interface for the application.

1. Navigate to the frontend directory:

   cd frontend

2. Install the required dependencies:

   npm install

3. Run the frontend application:

   npm run serve

The frontend application will be available at http://localhost:8080.

Contributions are welcome! Please feel free to submit a pull request or open an issue if you find a bug or have a feature request.

This project is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 International license. See the LICENSE file for more details.

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