# Eclipse LMOS

> Open-source platform for building, deploying, and managing AI agents at scale with enterprise-grade capabilities.

Eclipse LMOS is an open-source platform designed for building, deploying, and managing AI agents at enterprise scale. It provides a comprehensive framework that enables organizations to create intelligent agents capable of handling complex tasks while maintaining production-grade reliability and scalability. The platform is built on Kotlin and leverages modern cloud-native technologies to deliver a robust foundation for AI agent development.

**Key Features:**

- **Agent Development Framework** - Provides a structured approach to building AI agents with support for multiple LLM providers, enabling developers to create sophisticated conversational and task-oriented agents with minimal boilerplate code.

- **Multi-Agent Orchestration** - Supports coordination between multiple agents, allowing complex workflows where specialized agents collaborate to solve problems that require diverse capabilities.

- **Channel Integration** - Offers built-in support for various communication channels, making it easy to deploy agents across different platforms and interfaces.

- **Kubernetes-Native Deployment** - Designed for cloud-native environments with first-class Kubernetes support, enabling seamless scaling and management of agent deployments.

- **Observability and Monitoring** - Includes comprehensive logging, tracing, and metrics capabilities to monitor agent performance and behavior in production environments.

- **Extensible Architecture** - Features a modular design that allows developers to extend functionality through custom components, tools, and integrations.

- **Enterprise Security** - Implements security best practices with support for authentication, authorization, and secure communication between components.

**Getting Started:**

To begin using Eclipse LMOS, clone the repository from GitHub and follow the quickstart guide in the documentation. The platform requires Kotlin and a Kubernetes environment for full functionality. Developers can start by creating a simple agent using the provided templates and gradually add more sophisticated capabilities as needed. The documentation includes examples for common use cases and integration patterns.

## Features
- AI agent development framework
- Multi-agent orchestration
- LLM provider integration
- Kubernetes-native deployment
- Channel integration support
- Observability and monitoring
- Extensible plugin architecture
- Enterprise security features
- Kotlin-based SDK
- Cloud-native scalability

## Integrations
Kubernetes, OpenAI, Azure OpenAI, Multiple LLM providers

## Platforms
LINUX, MACOS, WINDOWS, API, DEVELOPER_SDK

## Pricing
Open Source

## Links
- Website: https://eclipse.dev/lmos/
- Documentation: https://eclipse.dev/lmos/docs/
- Repository: https://github.com/eclipse-lmos/lmos
- EveryDev.ai: https://www.everydev.ai/tools/eclipse-lmos