What is Leviathan (Lev)?

Leviathan is a universal agent runtime that enables developers to build AI agent workflows once and deploy them across 38+ platforms (IDEs, gateways, APIs) without code changes.

How does Leviathan achieve multi-platform deployment without code rewrites?

It utilizes a hex (ports-and-adapters) architecture and a declarative YAML compiler called FlowMind. This allows your agent workflows to be defined once and then adapted to various execution environments.

What kind of platforms can I deploy AI agents to with Leviathan?

Leviathan supports a wide range of over 38 platforms, including popular IDEs (e.g., Claude Code, Cursor), chat gateways (e.g., WhatsApp, Discord), and AI APIs (e.g., Claude, OpenAI, Gemini).

What other core capabilities does Leviathan offer?

Beyond deployment, Leviathan features polyglot search across codebases, built-in production readiness with XState v5 state machines and CloudEvents, and flexible fractal configuration management.

Leviathan

Name: Leviathan
Author: lev-os

bylev-os

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开发者工具

数据科学与机器学习

生产力与工作流

Provides a universal agent runtime for building and deploying AI agent workflows across diverse platforms without code changes.

Leviathan (Lev) is a research project and a universal agent runtime designed to eliminate the significant overhead of platform-specific rewrites for AI agent workflows. It enables developers to define agent workflows once using declarative YAML (FlowMind) and seamlessly deploy them across 38 different targets, including various IDEs, chat gateways, and major AI APIs. By abstracting away platform-specific complexities and offering core capabilities like polyglot search and production lifecycle management, Lev addresses the substantial time and effort lost in migrating AI agents between different environments, thereby facilitating rapid iteration and multi-platform deployment of intelligent systems.

主要功能

010 GitHub stars

02Deploy AI agent workflows to 38 platforms (IDEs, gateways, APIs) without code changes via platform adapters.

03Declare complex agent workflows using FlowMind, a YAML-based compiler that targets various execution environments.

04Execute polyglot search across any codebase in under a second using semantic, AST-aware, and fast text search engines.

05Ensure production readiness with built-in XState v5 state machines and CloudEvents audit trails for lifecycle management.

06Manage configurations hierarchically with fractal config, supporting system-wide, project-specific, and local overrides.

使用案例

01Develop and deploy AI agent workflows once and run them across multiple platforms like IDEs, chat applications, and custom APIs.

02Eliminate the need to rewrite AI agent code when migrating between different ecosystems (e.g., Claude Code to Cursor, LangChain to an API).

03Orchestrate complex AI agent pipelines for research, analysis, and reporting with declarative YAML workflows.