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Plearn-agentic-ai
Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.
Ddapr
Portable runtime combining event-driven architecture and workflow orchestration for distributed cloud and edge applications.
Popularity
Repository stars4,39426,174Highest
7-day net stars——
Fork1,0062,172Highest
30-day trendInsufficient historyInsufficient history
Maintenance
Last push2025-10-262026-11-02
Maintenance notesNot verifiedUnknown
Repository created2024-06-122019-06-19
License & use
LicenseMIT · PermissiveApache-2.0 · Permissive
PricingPricing not verifiedPricing not verified
Basics
Browse by purposeKubernetes operationsContainers · Kubernetes operations
TypeFrameworks & SDKsFrameworks & SDKs
SubcategoryAgent frameworksApplication frameworks
PlatformNot verifiedNot verified
Cost detailsCheck current official software, hosting, model and infrastructure pricing.Verify software, hosting, model and infrastructure costs against the current official documentation.
Pricing source——
First collected2026-11-032026-11-02
MetricRepository stars, not unique users or individual-skill installsRepository Stars, not unique users
LanguageJupyter NotebookGo
About this projectLearn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.Portable runtime combining event-driven architecture and workflow orchestration for distributed cloud and edge applications.
Measured at2026-11-03 09:37 UTC2026-11-02 19:26 UTC
License tiers are derived from metadata. Check obligations for your use; unknown does not mean prohibited. Ranked by repository stars, one position per repository. Stars and forks are not user counts.