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Source channel @olddriverGDstudy · Post #13 · Mar 17

#秀哥语录 2020.12.27【撩妹模板】#撩妹#语录 告诉你们一个小秘密 没事多去逛逛有年轻漂亮老板娘的美甲店 不要问我为什么 小姐姐 我买几瓶指甲油送给喜欢的人 买好付完钱送给老板娘 你就是我喜欢的人 你可以直白的告诉老板娘 其实我已经关注你好久了 第一次见到你 就有种心跳的感觉 我已经好多次想进来了 就是不知道怎么和你搭讪 可是 你的身影实在挥之不去 我今天忍不住了 豁出去了 就想告诉你 我真的好喜欢你 能不能加个好友

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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