GalTransl is an automated translation solution for visual novels, designed to create embedded translation patches. It targets visual novel enthusiasts and modders seeking to improve the quality of machine translations by leveraging advanced prompt engineering techniques and offering a comprehensive workflow from text extraction to patch injection.

How It Works

GalTransl combines innovative prompt engineering with multiple large language models (LLMs) like GPT-4, Claude, and Deepseek to enhance translation quality. Its core features include a "GPT Dictionary" for character-specific context and vocabulary, a flexible dictionary system (pre-translation, post-translation, conditional), real-time caching, and breakpoint resuming. It also integrates with other tools for a complete patch creation process, lowering the barrier to entry for users.

Quick Start & Requirements

• Installation: Download the release zip and extract. A "no environment" version with an .exe is available. Python 3.11.9 is recommended if building from source. Install dependencies via install_dependencies.bat.
• Prerequisites: Access to LLM APIs (OpenAI, Claude, etc.) or a local LLM setup (e.g., GalTransl-7B-v2 requires 6GB+ VRAM). Proxy setup is often required for API access.
• Setup: Basic setup involves downloading, extracting, and configuring config.yaml. Full patch creation requires additional tools like GARbro and VNTextPatch.
• Resources: Official documentation and tutorials are available on the project's GitHub Wiki.

Highlighted Details

• Supports multiple LLMs including GPT-4, Claude, Deepseek, and Sakura.
• Features a novel "GPT Dictionary" to improve character consistency and accuracy.
• Includes flexible pre- and post-translation dictionaries with conditional logic.
• Offers a specialized local model, GalTransl-7B-v2, optimized for visual novels.

Maintenance & Community

The project has seen regular updates, with significant refactors in v2 and v3, and the introduction of a plugin system in v4. Community support and further development information can be found via links to Discord/Slack and other community resources on the project's GitHub page.

Licensing & Compatibility

The project's licensing is not explicitly stated in the provided README excerpt. Compatibility for commercial use or closed-source linking would depend on the specific license chosen by the developers.

Limitations & Caveats

The README notes that releasing translations without full proofreading should be clearly marked as "GPT Translation/AI Translation Patch." Some features, like simulated web operations for ChatGPT, may be outdated. Certain engine/encoding combinations might require advanced reverse-engineering knowledge for proper display of translated text.