gpt-po-translator 2.0.4

A CLI tool for translating .po files using GPT models.

GPT-PO Translator

Translate gettext (.po) files using AI models. Supports OpenAI, Azure OpenAI, Anthropic/Claude, and DeepSeek with automatic AI translation tagging and context-aware translations.

🚀 Quick Start

# Install
pip install gpt-po-translator

# Set API key
export OPENAI_API_KEY='your_api_key_here'

# Auto-detect and translate all languages
gpt-po-translator --folder ./locales --bulk

✨ Key Features

• Multiple AI providers - OpenAI, Azure OpenAI, Anthropic/Claude, DeepSeek, Ollama
• Context-aware translations - Automatically uses msgctxt for better accuracy with ambiguous terms
• AI translation tracking - Auto-tags AI-generated translations with #. AI-generated comments
• Bulk processing - Efficient batch translation for large files
• Smart language detection - Auto-detects target languages from folder structure
• Fuzzy entry handling - Translates and fixes fuzzy entries properly
• Docker ready - Available as container for easy deployment

📦 Installation

PyPI (Recommended)

pip install gpt-po-translator

Docker

docker pull ghcr.io/pescheckit/python-gpt-po:latest

Manual

git clone https://github.com/pescheckit/python-gpt-po.git
cd python-gpt-po
pip install -e .

🔧 Setup

API Keys (Cloud Providers)

Choose your AI provider and set the corresponding API key:

# OpenAI
export OPENAI_API_KEY='your_key'

# Anthropic/Claude
export ANTHROPIC_API_KEY='your_key'

# DeepSeek
export DEEPSEEK_API_KEY='your_key'

# Azure OpenAI
export AZURE_OPENAI_API_KEY='your_key'
export AZURE_OPENAI_ENDPOINT='https://your-resource.openai.azure.com/'
export AZURE_OPENAI_API_VERSION='2024-02-01'

💡 Usage Examples

Basic Translation

# Auto-detect languages from PO files (recommended)
gpt-po-translator --folder ./locales --bulk -v

# Or specify languages explicitly
gpt-po-translator --folder ./locales --lang de,fr,es --bulk -v

# Single language with progress information
gpt-po-translator --folder ./locales --lang de -v

Different AI Providers

# Use Claude (Anthropic) - auto-detect languages
gpt-po-translator --provider anthropic --folder ./locales --bulk

# Use DeepSeek with specific languages
gpt-po-translator --provider deepseek --folder ./locales --lang de

# Use Azure OpenAI with auto-detection
gpt-po-translator --provider azure_openai --folder ./locales --bulk

# Use Ollama (local, see docs/usage.md for setup)
gpt-po-translator --provider ollama --folder ./locales

Docker Usage

# Basic usage with OpenAI
docker run -v $(pwd):/data \
  -e OPENAI_API_KEY="your_key" \
  ghcr.io/pescheckit/python-gpt-po:latest \
  --folder /data --bulk

# With Ollama (see docs/usage.md for full setup guide)
docker run --rm \
  -v $(pwd):/data \
  --network host \
  ghcr.io/pescheckit/python-gpt-po:latest \
  --provider ollama \
  --folder /data

# With Azure OpenAI
docker run -v $(pwd):/data \
  -e AZURE_OPENAI_API_KEY="your_key" \
  -e AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" \
  -e AZURE_OPENAI_API_VERSION="2024-02-01" \
  ghcr.io/pescheckit/python-gpt-po:latest \
  --provider azure_openai --folder /data --lang de

🎯 Context-Aware Translations

Automatically uses msgctxt for better accuracy:

msgctxt "button"
msgid "Save"
msgstr ""  → "Speichern" (button action)

msgctxt "money"
msgid "Save"
msgstr ""  → "Sparen" (save money)

The tool extracts context from your PO files and passes it to the AI for more accurate translations of ambiguous terms.

Tip: Use detailed context for best results: msgctxt "status label (not verb)" works better than just msgctxt "status".

Default Context

Provide a default context for entries without msgctxt:

# Via command-line
gpt-po-translator --folder ./locales --default-context "web application" --bulk

# Via environment variable
export GPT_TRANSLATOR_CONTEXT="mobile app for iOS"
gpt-po-translator --folder ./locales --bulk

# Via pyproject.toml
# Add to your pyproject.toml:
[tool.gpt-po-translator]
default_context = "e-commerce checkout flow"

Priority: CLI argument > Environment variable > Config file

The default context is applied to entries without explicit msgctxt, while entries with msgctxt always take precedence.

🏷️ AI Translation Tracking

All AI translations are automatically tagged for transparency and compliance:

#. AI-generated
msgid "Hello"
msgstr "Hallo"

This helps you:

• Track which translations are AI vs human-generated
• Comply with AI content disclosure requirements
• Manage incremental translation workflows

Note: Django's makemessages removes these comments but preserves translations. Re-run the translator after makemessages to restore tags.

📚 Command Reference

Option	Description
--folder	Path to .po files
--lang	Target languages (e.g., de,fr,es, fr_CA, pt_BR)
--provider	AI provider: openai, azure_openai, anthropic, deepseek, ollama
--bulk	Enable batch translation (recommended for large files)
--bulksize	Entries per batch (default: 50)
--model	Specific model to use
--list-models	Show available models
--fix-fuzzy	Translate fuzzy entries
--folder-language	Auto-detect languages from folders
--default-context	Default translation context for entries without msgctxt
--no-ai-comment	Disable AI tagging
--ollama-base-url	Ollama server URL (default: http://localhost:11434)
--ollama-timeout	Ollama timeout in seconds (default: 120)
-v, --verbose	Show progress information (use -vv for debug)
-q, --quiet	Only show errors
--version	Show version and exit

🛠️ Development

Build Docker Locally

git clone https://github.com/pescheckit/python-gpt-po.git
cd python-gpt-po
docker build -t python-gpt-po .

Run Tests

# Local
python -m pytest

# Docker
docker run --rm -v $(pwd):/app -w /app --entrypoint python python-gpt-po -m pytest -v

📋 Requirements

• Python 3.9+
• Dependencies: polib, openai, anthropic, requests, tenacity

📖 Documentation

• Advanced Usage Guide - Comprehensive options and mechanics
• Development Guide - Contributing guidelines
• GitHub Issues - Bug reports and feature requests

📄 License

MIT License - See LICENSE for details.