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Source channel @githubtrending · Post #14828 · Jun 16

#python#python#redis#redis_client#redis_cluster#redis_py Redis-py lets you connect your Python programs to Redis, a fast in-memory database, making it easy to store and retrieve data quickly. You can install it with a simple command, and it works with the latest Redis versions. It supports advanced features like connection pools, pipelines for faster operations, and pub/sub for real-time messaging. Using Redis with Python helps your applications run faster, handle more users, and process data in real time, all while reducing the load on your main database[1][3][5]. https://github.com/redis/redis-py

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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