OpenManus - AI Agent Frameworks Tool

Overview

OpenManus is an open-source project that replicates the capabilities of the Manus AI agent by offering a modular, containerized multi-agent framework. According to the GitHub repository, it is implemented with Docker, Python, and JavaScript and is designed to let developers assemble, run, and iterate multi-agent workflows inside isolated containers. The framework focuses on autonomous execution of complex, multi-step tasks — examples listed by the project include travel planning, data analysis, and content generation. OpenManus is geared toward experimentation and prototyping: users can compose agents that specialize in particular sub-tasks and orchestrate their interactions to solve higher-level goals. Because the codebase is containerized, deployments and environment reproducibility are simplified for local development and for controlled testing across machines. The repository provides the building blocks for agent communication, task orchestration, and modular extension, making it suitable for researchers and engineers exploring multi-agent approaches or recreating Manus-like capabilities in an open-source stack.

Installation

Install via docker:

git clone https://github.com/henryalps/OpenManus.git

cd OpenManus

docker compose up --build

Key Features

• Modular agent architecture: compose independent agents for distinct sub-tasks and responsibilities.
• Containerized deployment: each component runs in Docker containers for reproducible environments.
• Multi-agent orchestration: coordinate multiple agents to achieve complex, multi-step objectives.
• Polyglot implementation: agents and services implemented using Python and JavaScript runtimes.
• Use-case examples: templates for travel planning, data analysis, and content generation workflows.

Community

Community activity is centered on the project's GitHub repository where users can open issues, submit pull requests, and review source code. The repository is the primary place for contribution instructions, bug reports, and discussion of design decisions. Contributors should be familiar with Docker and with Python or JavaScript to run and extend the codebase; engagement typically follows standard open-source workflows (issues, PRs, code reviews) on GitHub.

Key Information

• Category: Agent Frameworks
• Type: AI Agent Frameworks Tool