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Source channel @githubtrending · Post #14965 · Jul 16

#rust#agent#ai#amazon_q#cli#linux#llm#macos#mcp#open_source#productivity#rust#shell#terminal#typescript Amazon Q CLI is a powerful tool that lets you interact with AWS and your development environment using natural language right from your terminal. It helps you write code, run commands, and manage AWS resources faster by understanding your context and providing smart suggestions, autocompletion, and even translating plain English into shell commands. It supports multi-turn conversations, so you can ask follow-up questions and get real-time help without leaving the command line. This boosts your productivity by simplifying complex tasks, reducing errors, and speeding up development workflows, making it easier to manage projects and infrastructure efficiently[1][2][3]. https://github.com/aws/amazon-q-developer-cli

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​​Совсем лайтовая статья для новичков "10 главных конструкций языка R". Содержание: - Комментарии - Переменные и векторы - Внешние модули - Ввод и вывод - Присваивание и сравнение - Условный оператор if - Цикл for - Функции - Классы, методы и объекты #статьи #easy

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@githubtrending · Post #15433 · 01/23/2026, 02:30 PM

#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG