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Source channel @githubtrending · Post #15261 · Nov 2

#javascript#123pan#139_cloud#189_cloud#ali_netdisk#aliyun_drive#aria2#baidu#baidu_netdisk#baidunetdisk#baiduyun#motrix#quark_netdisk#tampermonkey#tampermonkey_script#tampermonkey_userscript#tianyi_netdisk#uc_netdisk#userscript#xunlei_netdisk#yidong_netdisk LinkSwift is a browser script that helps you quickly get direct download links for files stored on popular Chinese cloud services like Baidu, Alibaba, 123, and others—saving you time and making downloads easier without needing to visit each service’s website separately. It also improves the look of these cloud storage pages and adds extra features, such as support for different download tools and customizable themes. The main benefit is convenience: you can manage and download your cloud files faster, with a nicer interface, all from your browser. Just install the script using a tool like Tampermonkey, and it works on Chrome, Edge, and other major browsers. https://github.com/hmjz100/LinkSwift

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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