Kagent is a Kubernetes-native framework for building, deploying, and managing AI agents. It targets developers and researchers seeking to leverage the orchestration power of Kubernetes for complex AI agent workflows, offering a declarative and extensible approach.

How It Works

Kagent leverages Kubernetes Custom Resource Definitions (CRDs) to define agents, tools, and models as declarative YAML configurations. A central controller watches these CRDs and orchestrates the necessary Kubernetes resources to run the agents. The core agent execution is powered by a Python engine built on Microsoft's Autogen library, enabling multi-agent conversations and tool integration. This Kubernetes-native approach provides inherent scalability, observability, and manageability for AI agent deployments.

Quick Start & Requirements

• Install: Follow instructions in the Quick Start guide.
• Prerequisites: Kubernetes cluster, kubectl.
• Dependencies: Python, Autogen.
• Setup: Local development instructions are in DEVELOPMENT.md.

Highlighted Details

• Kubernetes-native design for declarative management of AI agents.
• Built on Autogen for multi-agent conversation capabilities.
• Extensible architecture allowing custom agents and tools defined as CRDs.
• Includes a UI for agent and tool management.

Maintenance & Community

• Actively developed with a roadmap including enhanced observability, feedback mechanisms, and runtime improvements.
• Community support available via Discord.

Licensing & Compatibility

• License details are not explicitly stated in the README.
• Compatibility for commercial or closed-source use is not specified.

Limitations & Caveats

The project is in active development, with features like true graph execution and advanced debugging tools still on the roadmap. Licensing and commercial use compatibility require further clarification.