dokumori/rag-llm-translator

rag-llm-translator is a prototype-level tool addressing the common problem of terminology drift in software localization. While the use of RAG to enforce a glossary/style guide in translations is a valid architectural pattern, the project lacks any significant moat. With only 2 stars and no forks after nearly three months, it shows no community traction. Defensibility is low because the core logic—feeding a vector store with previously translated strings or glossaries and prompting an LLM with relevant context—is now a standard RAG recipe. Established Translation Management Systems (TMS) like Crowdin, Lokalise, and Tolgee have already integrated similar AI-assisted translation features directly into their platforms. Furthermore, frontier models are increasingly capable of handling long-context windows, which may eventually render the RAG component for small-to-medium PO files obsolete as the entire glossary can fit within the prompt. This project serves more as a reference implementation or personal utility than a defensible infrastructure component.