Localize subtitles for a confidential video project without sending text to a third party API
Translate SRT subtitle files into Telugu, Hindi, Tamil, Malayalam, or Kannada with model assisted suggestions
Run a self hosted subtitle editor inside a private network for NDA covered content
| saitejamummadi/subagent | 0xkinno/astraea | 0xkinno/halcyon | |
|---|---|---|---|
| Stars | 0 | 0 | 0 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | hard | hard | hard |
| Complexity | 4/5 | 4/5 | 4/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Needs Windows, Docker with GPU passthrough, and an NVIDIA GPU for live suggestions.
SubAgent is a subtitle localization tool meant to run entirely inside a private network, with no data ever sent to an outside company. You import a subtitle file in SRT or RTF format, optionally attach the matching video, and then go through each subtitle line, called a cue, translating it into Telugu, Hindi, Tamil, Malayalam, or Kannada. As you work, a language model running on your own graphics card suggests translations you can accept or edit, and the finished subtitles can then be exported. The project exists because most subtitle translation tools send your dialogue to a third party API, which is a problem if the content is under a non disclosure agreement or if you simply do not want an outside vendor involved. SubAgent keeps the editor, the translation model, and the conversion between romanized and native script text all inside infrastructure you control, with no calls to any hosted AI service anywhere in the code. The editor shows the video on one side and the list of cues on the other, with each cue expandable to show the original text, an editable translation, and suggestion chips with confidence scores from the model. Behind the scenes, a React frontend talks to a FastAPI backend backed by SQLite, which in turn talks to a translation model served through vLLM and a transliteration service, both reachable only over private or local network addresses so that pointing the system at a public server on purpose still fails. Running it requires Windows, Python 3.12, Node 20 or newer, Docker Desktop with GPU support, and an NVIDIA graphics card for live translation suggestions, though the editing and export features work without a GPU using a stand in translation worker. The project includes a one command startup script as well as instructions for starting each piece by hand. It is licensed under MIT.
An on prem subtitle translation studio for Telugu, Hindi, Tamil, Malayalam, and Kannada, using a local GPU model so no subtitle text leaves the network.
Mainly TypeScript. The stack also includes Python, FastAPI, React.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Don't trust strangers blindly. Verify against the repo.