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Source channel @githubtrending · Post #14850 · Jun 21

#blade#erp#food#groceries#grocy#home#meal_planner#ownyourdata#php#self_hosted Grocy is a free, web-based tool you can host yourself to manage your groceries and household easily. It helps you track your food stock, plan meals, create shopping lists, manage chores, and keep info about your household devices all in one place. You can scan barcodes to add products quickly and get notifications about expired or low-stock items, reducing waste and saving money. It works on any device with a browser and offers a mobile app-like experience. You can customize it, use its API, and even run it via Docker. This makes managing your home organized, efficient, and less stressful. https://github.com/grocy/grocy

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GitHub Trends

@githubtrending · Post #15265 · 11/03/2025, 12:00 PM

#python#ai#llm#rag#reasoning#retrieval PageIndex is an advanced AI tool that helps you find the most relevant information in long professional documents by thinking and reasoning like a human expert, rather than just matching keywords. It organizes documents into a clear tree structure, similar to a table of contents, and searches through this structure to give precise, trustworthy answers with exact page references. This method avoids the common problems of traditional vector-based search, making it ideal for complex reports, legal texts, or financial filings. You can use it easily via cloud services or run it locally, improving your ability to analyze and understand large documents quickly and accurately. https://github.com/VectifyAI/PageIndex

Machinelearning

@ai_machinelearning_big_data · Post #8801 · 10/17/2025, 10:13 AM

⚡️ Omni-Embed-Nemotron - новая единая модель от NVIDIA для поиска по тексту, изображениям, аудио и видео Модель обучена на разнообразных мультимодальных данных и может объединять разные типы входных сигналов в общее векторное представление. - Поддержка всех типов данных: текст, изображение, аудио, видео. - Основана на архитектуре Qwen Omni (Thinker-модуль, без генерации текста). - Контекст - до 32 768 токенов, размер embedding — 2048. - Оптимизирована под GPU, поддерживает FlashAttention 2. Это делает её идеальной для: - кросс-модального поиска (поиск текста по видео или изображению); - улучшения RAG-проектов; - систем мультимодального понимания контента. Просто, быстро и эффективно - всё в одном открытом решении. 🌐 Открытая модель: https://huggingface.co/nvidia/omni-embed-nemotron-3b @ai_machinelearning_big_data #crossmodal#retrieval#openAI#NVIDIA#OmniEmbed#multimodal#AIModels#OpenSource#Search#UnifiedEmbedding