Eclipse LMOS Creation Review

Type
Creation
State
Ongoing
End Date of the Review Period

Reviews run for a minimum of one week. The outcome of the review is decided on this date. This is the last day to make comments or ask questions about this review.

Proposal

Eclipse LMOS

Thursday, October 31, 2024 - 10:14 by Kai Kreuzer
This proposal is in the Project Proposal Phase (as defined in the Eclipse Development Process) and is written to declare its intent and scope. We solicit additional participation and input from the community. Please login and add your feedback in the comments section.
Parent Project
Proposal State
Community Review
Background

The LMOS project arose from the need for a more adaptable and scalable solution for building AI agents. While single-agent systems were common, there was a lack of established frameworks for multi-agent systems.

Scope

Eclipse LMOS provides a comprehensive platform for developing, deploying, and managing complex multi-agent systems, extending beyond the creation of individual AI agents. Eclipse LMOS is designed to be open and interoperable, leveraging established open standards to foster collaboration and innovation in the field of Multi-Agent Systems.

Description

The Eclipse LMOS project (Language Model Operating System) is essentially a platform for building and running AI systems that can handle complex tasks. Imagine it like an operating system for your computer, but instead of managing applications, it manages AI agents. These agents are like smaller, specialized AI programs that each handle a specific part of a larger problem.

The key idea behind Eclipse LMOS is to break down complex tasks into smaller parts that can be handled by different AI agents. For instance, if you're building a customer service chatbot, one agent might handle basic greetings, another might answer questions about billing, and another might deal with technical support issues. This way, each agent can be really good at its specific job, leading to better overall performance.

Eclipse LMOS helps these agents work together by providing a common platform where they can communicate and share information. It's like a central hub that keeps everything organized and running smoothly. This platform also makes it easier to manage and scale the system as needed. If you need to add more agents or handle more traffic, LMOS can handle it without breaking a sweat.

Eclipse LMOS was designed to be very flexible and user-friendly. You don't need to be an AI expert to use it. The platform provides tools and features that make it easy to build, deploy, and manage AI agents.

Why Here?

The Eclipse Foundation focuses on supporting projects that address real-world enterprise challenges. Eclipse LMOS is designed to solve AI needs of enterprises in an open and transparent manner.

Additionally, we are seeking for collaboration with other enterprises especially in Europe, which is a stronghold of the Eclipse Foundation.

Future Work

Besides further improving the existing code, we plan to add more features (e.g. other routing and inter-agent communication options) and tools to more easily manage installations. Also, integrations to other services are planned such as common Web APIs as functions or simple "bring-your-own-agent" (BYOA) mechanisms for integrating existing agents that can be build with any other framework.

Project Scheduling

We plan the project creation to be done by end of November 2024 with possibly a first release under the Eclipse name by the end of the year.

Initial Contribution

The initial contribution consists out of a couple of repositories that currently exist under https://github.com/lmos-ai.
These contain "ARC", a framework for easily building AI agents plus tooling like Spring Boot templates, a UI etc.

Additionally, there are different components of LMOS, such as the router, the runtime and the operator, all of which together comprise the agent management plane for Kubernetes.

Furthermore, there are repos for demos, samples and documentation.

So far, all contributors to these repos are employees of Deutsche Telekom.

All code is licensed under the Apache 2.0 license. Only some non-code parts are provided under CC-BY or CC0 licenses.

 

Source Repository Type

The Eclipse LMOS project (Language Model Operating System) is essentially a platform for building and running AI systems that can handle complex tasks. Imagine it like an operating system for your computer, but instead of managing applications, it manages AI agents. These agents are like smaller, specialized AI programs that each handle a specific part of a larger problem.

The key idea behind Eclipse LMOS is to break down complex tasks into smaller parts that can be handled by different AI agents. For instance, if you're building a customer service chatbot, one agent might handle basic greetings, another might answer questions about billing, and another might deal with technical support issues. This way, each agent can be really good at its specific job, leading to better overall performance.

Eclipse LMOS helps these agents work together by providing a common platform where they can communicate and share information. It's like a central hub that keeps everything organized and running smoothly. This platform also makes it easier to manage and scale the system as needed. If you need to add more agents or handle more traffic, LMOS can handle it without breaking a sweat.

Eclipse LMOS was designed to be very flexible and user-friendly. You don't need to be an AI expert to use it. The platform provides tools and features that make it easy to build, deploy, and manage AI agents.