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Loqi is a local-first, hackable, scriptable translation tool for desktop and developer workflows. Translate text, files, docs and structured content using local LLMs

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Loqi, a "local-first" translation tool using Ollama/llama.cpp

by danterolle·Jun 22, 2026·2 points·0 comments

AI Analysis

MidCozyNiche Gem

Local LLM translation when Argos Translate and Ollama wrappers already exist.

Strengths
  • Three backend options: Ollama, llama.cpp, or argos-translate.
  • Bubble Tea TUI with CLI and batch modes for different workflows.
  • Processes files, Markdown, and JSON entirely offline.
Weaknesses
  • Author admits results are drafts to review, not guaranteed translations.
  • Local LLM translation is becoming a known pattern with many alternatives.
Category
Target Audience

Privacy-conscious developers and writers

Similar To

Argos Translate · Ollama · DeepL

Post Description

I got tired of sending every text I translate to Google/DeepL. Even with all the opt-out options and privacy policies, it never felt right especially for some work documents, personal writing, or anything sensitive. So I decided to build this tool, which lets me use LLMs for context translations and also a standard translation engine like Argos. It works with Ollama, llama.cpp or argos-translate, and you can configure the model you want to use.

loqi translate --model phi4-mini --from it --to en "Ciao mondo"

Obviously, the quality of the translation depends entirely on the model used, but I've noticed that you can get good, if not excellent, results even with a small model (such as Gemma 4 E2B or Phi4-min).

So there you have it: Loqi is open source, cross-platform (MacOS, GNU/Linux, Windows), written in Go with Bubble Tea for the TUI. It allows the model to translate individual sentences or process entire files (whether plain text, Markdown or JSON).

I used LLMs to help write parts of the code, including self-hostable ones (those that run on AMD GPU with 16 GB of VRAM), but I've tried to set up the project as much as possible, and there's probably a lot more work to be done and some ideas to implement.

I'd be more than happy to accept contributions.

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