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Source channel @githubtrending · Post #15203 · Oct 7

#python#agents#ai#framework#llm#openai#python The OpenAI Agents SDK is a Python framework that lets you easily build and connect AI agents—smart programs that can talk, use tools, and work together to solve tasks[2][3]. You can turn any Python function into a tool an agent can use, set up safety checks to control what agents do, and automatically pass tasks between different agents when needed[2][4]. The SDK manages conversation history for you, so agents remember past interactions, and it includes tools to track and debug how agents make decisions[2]. This makes it simple to create reliable, customizable AI helpers for things like customer support, research, or automation, with clear oversight and fast development. https://github.com/openai/openai-agents-python

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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