mofa-org / mofa

MoFA Agent Framework English | 简体中文 Website | Quick Start | GitHub | Hackathon | Community 📋 Table of Contents • Overview • Why MoFA? • Core Architecture • Core Features • Quick Start • Roadmap • Ecosystem & Related Repos • Documentation • Security • Contributing • Community • License Overview MoFA (Modular Framework for Agents) is not just another entry in the crowded agent framework landscape. It is the first production-grade framework to achieve **"write once, run everywhere"** across languages, built for **extreme performance, boundless extensibility, and runtime programmability**. Through its revolutionary microkernel architecture and innovative **dual-layer plugin system** (compile-time + runtime), MoFA strikes the elusive balance between raw performance and dynamic flexibility. What Sets MoFA Apart: ✅ **Rust Core + UniFFI**: Blazing performance with native multi-language interoperability ✅ **Dual-Layer Plugins**: Zero-cost compile-time extensions meet hot-swappable runtime scripts ✅ **Microkernel Architecture**: Clean separation of concerns, effortless to extend ✅ **Cloud-Native by Design**: First-class support for distributed and edge deployments Why MoFA? **Performance** • Zero-cost abstractions in Rust • Memory safety without garbage collection • Orders of magnitude faster than Python-based frameworks **Polyglot by Design** • Auto-generated bindings for Python, Java, Go, Kotlin, Swift via UniFFI • Call Rust core logic natively from any supported language • Near-zero overhead compared to traditional FFI **Runtime Programmability** • Embedded Rhai scripting engine • Hot-reload business logic without recompilation • Runtime configuration and rule adjustments • User-defined extensions on the fly **Dual-Layer Plugin Architecture** • **Compile-time plugins**: Extreme performance, native integration • **Runtime plugins**: Dynamic loading, instant effect • Support plugin hot loading and version management **Distributed by Nature** • Built on Dora-rs for distributed dataflow • Seamless cross-process, cross-machine agent communication • Edge computing ready **Actor-Model Concurrency** • Isolated agent processes via Ractor • Message-passing architecture • Battle-tested for high-concurrency workloads Core Architecture Microkernel + Dual-Layer Plugin System MoFA adopts a **layered microkernel architecture**, achieving extreme extensibility through a **dual-layer plugin system**: Advantages of Dual-Layer Plugin System **Compile-time Plugins (Rust/WASM)** • Extreme performance, zero runtime overhead • Type safety, compile-time error checking • Support complex system calls and native integration • WASM sandbox provides secure isolation **Runtime Plugins (Rhai Scripts)** • No recompilation needed, instant effect • Business logic hot updates • User-defined extensions • Secure sandbox execution with configurable resource limits **Combined Power** • Use Rust plugins for performance-critical paths (e.g., LLM inference, data processing) • Use Rhai scripts for business logic (e.g., rule engines, workflow orchestration) • Seamless interoperability between both, covering 99% of extension scenarios Core Features • Microkernel Architecture MoFA adopts a **layered microkernel architecture** with at its core. All other features (including plugin system, LLM capabilities, multi-agent collaboration, etc.) are built as modular components on top of the microkernel. Core Design Principles • **Core Simplicity**: The microkernel contains only the most basic functions: agent lifecycle management, metadata system, and dynamic management • **High Extensibility**: All advanced features are extended through modular components and plugins, keeping the kernel stable • **Loose Coupling**: Components communicate through standardized interfaces, easy to replace and upgrade Integration with Plugin System • The plugin system is developed based on the interface of the microkernel. All plugins (including LLM plugins, tool plugins, etc.) are integrated through the standard interface • The microkernel provides plugin registration center and lifecycle management, supporting plugin hot loading and version control • LLM capabilities are implemented through , encapsulating LLM providers as plugins compliant with microkernel specifications Integration with LLM • LLM exists as a plugin component of the microkernel, providing standard LLM access capabilities through the interface • All agent collaboration patterns (chain, parallel, debate, etc.) are built on the microkernel's workflow engine and interact with LLMs through standardized LLM plugin interfaces • Secretary mode is also implemented based on the microkernel's A2A communication protocol and task scheduling system • Dual-Layer Plugins • **Compile-time plugins**: Extreme performance, native integration • **Runtime plugins**: Dynamic loading, instant effect • Seamless collaboration between both, covering all scenarios • Agent Coordination • **Priority Scheduling**: Task scheduling system based on priority levels • **Communication Bus**: Built-in inter-agent communication bus • **Workflow Engine**: Visual workflow builder and executor • LLM and AI Capabilities • **LLM Abstraction Layer**: Standardized LLM integration interface • **OpenAI Support**: Built-in OpenAI API integration • **ReAct Pattern**: Agent framework based on reasoning and action • **Multi-Agent Collaboration**: LLM-driven agent coordination, supporting multiple collaboration modes: • **Request-Response**: One-to-one deterministic tasks with synchronous replies • **Publish-Subscribe**: One-to-many broadcast tasks with multiple receivers • **Consensus**: Multi-round negotiation and voting for decision-making • **Debate**: Agents alternate speaking to iteratively refine results • **Parallel**: Simultaneous execution with automatic result aggregation • **Sequential**: Pipeline execution where output flows to the next agent • **Custom**: User-defined modes interpreted by the LLM • **Sec…