#148 · Primary category： Knowledge Base & RAG
NetCoreKevin
🤖 Enterprise-level AI knowledge base agent open-source architecture built on .NET: AISkills skill management, AI voice phone mode, agent memory, AI-Qdrant knowledge base, knowledge base reranking model, AI web search, multi-agent collaboration, chat history compression strategy, agent permission control, AgentFramework, RAG retrieval augmentation, local Ollama AI model invocation, controllable agent skill loading, domain events, multi-tenancy with one database, Log4, JWT, CAP, SignalR, MCP, Hangfire, RabbitMQ, frontend (Vue + Ant Design).
Project last updated：08/28/26
GitHub Stars
505
Forks
117
Contributors
5
License
Other
Why we included this project
NetCoreKevin suits .NET teams that want a head start on a company knowledge service with AI agents, since it is a full-stack architecture instead of a single demo. The stack pairs a .NET 9 backend with a Vue 3 and Ant Design admin console, and the pipeline runs from document upload through Qdrant vector retrieval to generated answers. Around that core sit skill tool management, multi-agent orchestration with conversation-history compression, AI web search, reranking, and local Ollama models, with multi-tenant isolation handling data separation. The RBAC permissions, Hangfire scheduled jobs, and modular DDD-style layout push it toward a reference base for a production-shaped product. Treat it as an architecture to adapt and build on rather than something plug-and-play.
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