docx-translator 0.1.10

🌍📄✨ Immersive translation of Word docx files

English · Français · Deutsch · 简体中文 · 繁體中文 · 한국어 · Português

Looking for someone to translate this README.

Pure, unadulterated vibe coding powers this entire beast of a project.

DocxTranslator is a tool to translate Word documents (.docx) using OpenAI's API. It preserves the original document formatting and adds translations below each paragraph.

⤷ If these images breaks, you can view them on Github

✨ Features

• 🔄 Translate Word documents (.docx) using OpenAI GPT models
• 🎨 Preserve document formatting and structure
• 🌐 Add translations directly below the original text
• 💻 Command-line interface for easy integration into scripts
• 🌍 Web interface powered by Streamlit
• 💾 Translation caching to avoid redundant API calls
• ⚡ Parallel processing for faster translation
• 🔧 Support for custom OpenAI API endpoints

📦 Installation

Via Pip

pip install docx-translator

Via Docker

You can use the prebuilt Docker image to get started immediately:

# Pull the prebuilt image
docker pull johndope/docx-translator:latest

# Run with your API key
docker run -p 8501:8501 -e OPENAI_API_KEY=your-api-key johndope/docx-translator

🖥️ Command Line Usage

After installation, you can use the dt command to translate documents:

# Basic usage
dt translate document.docx Spanish

# Specify output file
dt translate document.docx French --output translated_document.docx

# Translate specific paragraph styles
dt translate document.docx German --styles "Normal,Heading 1,List Paragraph"

# Use a different model
dt translate document.docx Japanese --model gpt-4o

# Disable caching
dt translate document.docx Chinese --no-cache

# Clear cache for a language before translation
dt translate document.docx Italian --clear-cache

# Process sequentially (instead of in parallel)
dt translate document.docx Russian --sequential

# Show verbose logging
dt translate document.docx Portuguese --verbose

🧹 Clear Translation Caches

dt clear-caches

🚀 Launch Web Interface

dt serve

🐳 Docker Usage

You can run DocxTranslator using Docker:

Option 1: Using prebuilt image (recommended)

# Pull the prebuilt image
docker pull johndope/docx-translator:latest

# Run with your API key
docker run -p 8501:8501 -e OPENAI_API_KEY=your-api-key johndope/docx-translator

Option 2: Using docker-compose

# Create a .env file with your OpenAI API key and other settings
echo "OPENAI_API_KEY=your-api-key" > .env

# Build and start the Docker container
docker-compose up -d

# Access the web interface at http://localhost:8501

The Docker setup:

• 📂 Uses the installed package directly via the dt command
• 💽 Mounts a cache directory for persistent translations
• 📁 Mounts a data directory for sharing documents with the container

🔑 Environment Variables

You can set the following environment variables (or use a .env file):

• OPENAI_API_KEY: Your OpenAI API key
• OPENAI_BASE_URL: Custom base URL for OpenAI API (optional)
• OPENAI_MODEL: The model to use (default: gpt-4-turbo)
• OPENAI_MAX_CONCURRENT: Maximum concurrent requests (default: 5)
• TARGET_LANGUAGE: Default target language (default: Spanish)
• DOCX_TRANSLATOR_CACHE_DIR: Custom cache directory

🐍 Python API

You can also use DocxTranslator programmatically:

from pathlib import Path
from docx_translator.translator import setup_openai_client, process_document

# Set up OpenAI client
client = setup_openai_client(api_key="your-api-key")

# Translate document
process_document(
   input_file=Path("document.docx"),
   output_file=Path("translated_document.docx"),
   target_language="Spanish",
   target_styles=["Normal", "Heading 1"],
   openai_client=client,
   use_cache=True,
   parallel=True,
   max_concurrent=5
)

🌐 Web Interface

DocxTranslator includes a web interface powered by Streamlit. To start it:

dt serve

This will launch a local web server where you can:

• 📤 Upload Word documents
• 🎯 Select which paragraph styles to translate
• ⚙️ Configure OpenAI API settings
• 🚀 Start translations with progress tracking
• 📥 Download the translated document

📜 License

MIT