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Source channel @githubtrending · Post #14668 · May 3

#svelte#component#component_library#components#css#css_components#css_framework#daisyui#design_pattern#design_system#design_systems#postcss#svelte#tailwind#tailwind_css#tailwindcss#ui_design#ui_framework#ui_kit#ui_library#ui_pattern daisyUI is a popular, free, and open-source component library for Tailwind CSS. It helps you build faster by providing useful class names for common UI elements like cards and calendars. This means you write less code and can focus on designing your interface more efficiently. daisyUI is also very customizable and works well with Next.js, adding no extra JavaScript to your projects, which keeps them fast and efficient. Overall, using daisyUI simplifies your development process and makes your projects more maintainable. https://github.com/saadeghi/daisyui

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@githubtrending · Post #14693 · 05/10/2025, 12:00 PM

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#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4]. https://github.com/panaversity/learn-agentic-ai