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Source channel @githubtrending · Post #15212 · Oct 10

#typescript#agent#agent_platform#ai_plugins#chatbot#chatbot_framework#coze#coze_platform#generative_ai#go#kouzi#low_code_ai#multimodel_ai#no_code#rag#studio#typescript#workflow Coze Studio is an easy-to-use, all-in-one platform for building AI agents and apps without needing much coding. It offers visual tools to design, debug, and deploy AI projects quickly using drag-and-drop workflows, plugins, and large language models like GPT-4. You can create smart assistants, chatbots, or custom AI apps with ready templates and manage models, knowledge bases, and plugins in one place. It supports no-code and low-code development, making AI accessible to both beginners and professionals, saving you time and effort in building powerful AI solutions tailored to your needs. It also supports multi-model integration and easy deployment. https://github.com/coze-dev/coze-studio

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

#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