Instantly translate any selected text on your screen without switching apps, using a keyboard shortcut.
Extract text from a screenshot or on-screen image using OCR, then translate or copy it.
Use your preferred translation service, DeepL, OpenAI, Google, or a local Ollama model, rather than being locked to one provider.
Export translated words to an Anki deck for language learning.
Some translation services require API keys from third-party providers such as DeepL or OpenAI before they can be used.
Pot is a cross-platform desktop app for translating text and reading text out of images (OCR, optical character recognition, the process of turning a picture of words into editable text). You install it on your computer and use keyboard shortcuts to translate whatever you have selected, whatever is on your clipboard, or whatever you draw a box around on the screen. It works on Windows, macOS, and Linux, including Linux setups using Wayland (a modern display system used by KDE, Gnome, and Hyprland). Rather than locking you to one translation provider, Pot lets you plug in a long list of online services like OpenAI, Gemini Pro, DeepL, Google, Bing, Yandex, and a range of Chinese services such as Baidu, Tencent, Youdao, and Volcano. It can also run offline against a locally installed Ollama instance for translation, and against system OCR on each platform (Windows Media OCR, Apple's Vision framework, and Tesseract on Linux) plus Tesseract.js. A plugin system using files with a .potext extension lets the community add new translation services, OCR engines, text-to-speech backends, and vocabulary-book exporters such as Anki. You would reach for Pot if you read or write in multiple languages on a daily basis, for example, working across English and Chinese documentation, captioning screenshots, or copying text out of images. It is also useful when you want to pick your own translation provider rather than be tied to one company's cloud. The app is built with Tauri (a framework for building lightweight desktop apps with web technologies), with a JavaScript user interface and a Rust core. The full README is longer than what was provided.
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