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Source channel @githubtrending · Post #14693 · May 10

#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

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@V1_BLOG · Post #1422 · 08/28/2019, 06:02 AM

测速机场: 次元链接 测速宽带: 广东移动200M 测速时间: 0827,11PM 官网: https://cylink.cf TG群: https://t.me/cylink 清晰测速图: https://v1blog.life/0827cylinkcm 测速By-V1测速组 #次元链接#cylink 好久没测帕西的了) 频道:@V1_BLOG 群组:@V1blog_group