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Source channel @githubtrending · Post #15607 · Apr 7

#python#ai_agents#ai_tutor#clawdbot#cli_tool#deepresearch#interactive_learning#large_language_models#multi_agent_systems#rag DeepTutor v1.0.0 is an open-source AI tutoring tool with personalized TutorBots, unified chat modes for solving problems, quizzes, research, and math animations, plus knowledge bases from your PDFs, persistent memory of your learning style, AI co-writing, and guided plans—all via easy web, Docker, or CLI setup. You benefit by getting a smart, evolving study companion that adapts to you, boosts understanding with interactive tools, and saves time on tough topics without starting over. https://github.com/HKUDS/DeepTutor

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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