Koog, a Kotlin-based framework to build and run Al agents in idiomatic Kotlin

Summary

Koog Overview Koog is a Kotlin-based framework designed to build and run AI agents entirely in idiomatic Kotlin. It lets you create agents that can interact with tools, handle complex workflows, and communicate with users. Key features Key features of Koog include: Pure Kotlin implementation : Build AI agents entirely in natural and idiomatic Kotlin. : Build AI agents entirely in natural and idiomatic Kotlin. MCP integration : Connect to Model Control Protocol for enhanced model management. : Connect to Model Control Protocol for enhanced model management. Embedding capabilities : Use vector embeddings for semantic search and knowledge retrieval. : Use vector embeddings for semantic search and knowledge retrieval. Custom tool creation : Extend your agents with tools that access external systems and APIs. : Extend your agents with tools that access external systems and APIs. Ready-to-use components : Speed up development with pre-built solutions for common AI engineering challenges. : Speed up development with pre-built solutions for common AI engineering challenges. Intelligent history compression : Optimize token usage while maintaining conversation context using various pre-built strategies. : Optimize token usage while maintaining conversation context using various pre-built strategies. Powerful Streaming API : Process responses in real-time with streaming support and parallel tool calls. : Process responses in real-time with streaming support and parallel tool calls. Persistent agent memory : Enable knowledge retention across sessions and even different agents. : Enable knowledge retention across sessions and even different agents. Comprehensive tracing : Debug and monitor agent execution with detailed and configurable tracing. : Debug and monitor agent execution with detailed and configurable tracing. Flexible graph workflows : Design complex agent behaviors using intuitive graph-based workflows. : Design complex agent behaviors using intuitive graph-based work...