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Source channel @githubtrending · Post #14975 · Jul 19

#typescript bknd is a lightweight backend system that makes app development easier by providing ready-to-use features like database management, user authentication, media handling, and workflow automation, all in one place. It works with many JavaScript runtimes and frameworks, so you can deploy it almost anywhere and even bundle backend and frontend together. It offers a full REST API, a React SDK, and UI components to speed up development without needing deep backend knowledge. This saves you time, reduces complexity, and helps you build secure, scalable apps faster with less effort. You can start quickly with a simple command and customize as needed. https://github.com/bknd-io/bknd

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Посольство России в Индии

@RusEmbIndia_Ru · Post #14913 · 04/14/2026, 08:01 AM

Дорогие друзья! 📚 Русский дом в Нью-Дели приглашает вас принять участие в международной исторической акции «Диктант Победы». 📆 Ждем Вас 24 апреля в 12:00. 🔗 Язык диктанта - русский и английский. 🏢 Место проведения: Русский дом в Нью-Дели. 📍Адрес: 24, Фироз Шах Роуд, г. Нью-Дели. ✅ Вход для посетителей мероприятия - свободный. 🔗При себе необходимо обязательно иметь ID-карту (на бумажном носителе). 💎 Не упустите возможность стать частью важного события! Ждем Вас! #РусскийДом#Диктант#Индия Dear friends! 📚 The Russian House in New Delhi invites you to participate in the international historical campaign "Victory Dictation." 📆 We look forward to seeing you on April 24 at 12:00 p.m. 🔗 The language of the dictation is Russian and English. 🏢 Venue: Russian House in New Delhi. 📍Address: 24, Firoz Shah Road, New Delhi. ✅ Entrance for visitors to the dictation is free. 💎 Don't miss the opportunity to become part of an important event! We are waiting for you! #RussianHouse#Dictation#India

Libreware

@libreware · Post #1477 · 08/07/2025, 03:49 AM

WhisperTux Simple #voice#dictation application for #Linux. Uses whisper.cpp for offline speech-to-text transcription. No fancy GPUs are required although whisper.cpp is capable of using them if available. Once your speech is transcribed, it is sent to a ydotool daemon that will write the text into the focused application. Features Local speech-to-text processing via whisper.cpp (no cloud dependencies) No expensive hardware required (works well on a plain x86 laptop with AVX instructions) Global keyboard shortcuts for system-wide operation Automatic text injection into focused applications Configurable whisper models and shortcuts https://github.com/cjams/whispertux #assistant#speech#stt