OpenManus: The Open Source Alternative to Manus AI

OpenManus is a fully open-source alternative to Manus AI, designed to democratize access to autonomous AI agents. While Manus AI requires an invitation code, OpenManus breaks down barriers by providing a powerful framework that's freely available to everyone. Developed by the MetaGPT research team, OpenManus allows users to create AI agents capable of executing complex tasks with minimal human input, from automated workflows to website development and market analysis.

In this tutorial, we'll explore everything you need to know about OpenManus, including installation, configuration, features, and practical applications. We'll also touch on OpenManus-RL, an extension focusing on reinforcement learning techniques for enhancing AI agents.

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What is OpenManus Project?

OpenManus is a cutting-edge AI framework that enables autonomous agent capabilities without the restrictions of invitation-only platforms like Manus AI. Built on state-of-the-art Large Language Models (LLMs) such as GPT-4o, OpenManus allows your AI agent to:

• Generate and execute workflows for automation
• Perform in-depth research and summarize information
• Autonomously develop and maintain websites
• Analyze data and provide meaningful insights
• Plan and optimize tasks with minimal human intervention

Unlike many AI systems that require constant human supervision, OpenManus is designed to self-learn, improve its decision-making processes, and operate with greater autonomy over time.

Key Features of OpenManus Project, Explained:

Modular and Extensible Architecture

OpenManus features a modular architecture that allows users to customize and extend functionality based on specific needs. This flexibility enables developers to adapt the framework for various use cases without being constrained by rigid structures.

No Invite Code Required

Unlike Manus AI, OpenManus is freely available to everyone. There's no waitlist, no invitation process, and no enterprise-only features. This democratization of access ensures that cutting-edge AI technology is available to individual developers, researchers, and organizations of all sizes.

Advanced Autonomous Capabilities

OpenManus agents can:

• Make informed decisions based on available data
• Interact meaningfully with users through natural language
• Execute complex tasks independently
• Learn from past interactions to improve performance

Open-Source Community

Being open-source, OpenManus benefits from community contributions, ensuring continuous improvement and adaptation to emerging needs and technologies.

How to Install OpenManus (Step by Step Guide)

OpenManus provides two installation methods. The second method using uv is recommended for faster installation and better dependency management.

Method 1: Using Conda

1. Create a new conda environment:

conda create -n open_manus python=3.12
conda activate open_manus

1. Clone the repository:

git clone <https://github.com/mannaandpoem/OpenManus.git>
cd OpenManus

1. Install dependencies:

pip install -r requirements.txt

Method 2: Using UV (Recommended)

1. Install UV (A fast Python package installer and resolver):

curl -LsSf <https://astral.sh/uv/install.sh> | sh

1. Clone the repository:

git clone <https://github.com/mannaandpoem/OpenManus.git>
cd OpenManus

1. Create a new virtual environment and activate it:

# On Unix/macOS:
uv venv --python 3.12
source .venv/bin/activate

# On Windows:
# uv venv --python 3.12
# .venv\\Scripts\\activate

1. Install dependencies:

uv pip install -r requirements.txt

Optional: Browser Automation Tool

If you want to use the browser automation features:

playwright install

How to Configure OpenManus Project

OpenManus requires configuration for the LLM APIs it uses. Follow these steps to set up your configuration:

1. Create a config file:

cp config/config.example.toml config/config.toml

1. Edit the configuration file:

Open config/config.toml in your preferred text editor and add your API keys:

[Global]
# llm model
llm = "gpt-4o"
base_url = "<https://api.openai.com/v1>"
api_key = "sk-..." # Replace with your actual API key
# max_tokens = 4096
temperature = 0.0

[Global.vision]
# llm vision model
llm = "gpt-4o"
base_url = "<https://api.openai.com/v1>"
api_key = "sk-..." # Replace with your actual API key

Make sure to replace the placeholder API keys with your actual OpenAI API keys. You can obtain these by signing up on the OpenAI platform.

Getting Started with OpenManus {#getting-started-with-openmanus}

Once you've installed and configured OpenManus, you can start using it with a single command:

python main.py

After running this command, you can interact with OpenManus via the terminal. Simply input your idea or task, and OpenManus will work to accomplish it.

Example inputs:

• "Create a simple portfolio website for a photographer"
• "Research the impact of AI on healthcare and provide a summary"
• "Analyze the stock market trends for technology companies in the last quarter"

The system will process your request, break it down into manageable tasks, and work through them autonomously.

How to Run Different Modes for OpenManus

OpenManus offers different modes for various use cases:

Standard Mode

python main.py

This is the default mode that provides the full OpenManus experience.

MCP Tool Version

python run_mcp.py

The MCP (Master Control Program) tool version provides a more controlled environment for running specific tasks with predefined tools.

Multi-Agent Version (Experimental)

python run_flow.py

This unstable but promising version enables multiple AI agents to collaborate on complex tasks, distributing the workload and specializing in different aspects of the problem.

OpenManus-RL: Reinforcement Learning for AI Agents {#openmanus-rl}

OpenManus-RL is an extension of the core framework focused on enhancing AI agents using reinforcement learning techniques. Developed collaboratively by researchers from UIUC and the OpenManus team, it implements methods like GRPO (Generalized Reinforcement Policy Optimization) to improve agent performance.

Key aspects of OpenManus-RL include:

• Enhanced Decision Making: Using reinforcement learning to optimize agent decisions based on outcomes and feedback
• Multi-Environment Support: Training agents across various environments to improve adaptability
• Performance Tuning: Fine-tuning LLM-based agents for specific tasks through systematic reinforcement

To experiment with OpenManus-RL, you can check out the dedicated examples in the repository's examples directory:

# Navigate to examples
cd examples/reinforcement_learning

# Run a basic RL example
python simple_rl_example.py

How to Use Open Manus in Real World

OpenManus can be applied to numerous real-world scenarios:

Web Development and Maintenance

Create websites, generate content, and maintain online presence with minimal human intervention.

python main.py
# Input: "Create a personal blog website with five placeholder articles about artificial intelligence"

Research Assistant

Conduct in-depth research on specific topics, summarize findings, and identify key insights.

python main.py
# Input: "Research recent advancements in renewable energy and prepare a comprehensive report"

Business Analytics

Analyze market trends, customer data, and performance metrics to provide actionable business insights.

python run_mcp.py
# Input: "Analyze customer feedback from our e-commerce store and identify recurring themes"

Personal Productivity

Plan schedules, organize tasks, and optimize workflows for better personal productivity.

python main.py
# Input: "Create a weekly meal plan with grocery list based on Mediterranean diet preferences"

Resources for OpenManus Project

The OpenManus team welcomes contributions from the community. Here's how you can contribute:

1. Report Issues: If you encounter bugs or have feature suggestions, create an issue on GitHub.
2. Submit Pull Requests: Contribute code improvements, documentation updates, or new features.
3. Share Examples: Create and share examples of OpenManus applications to inspire others.

Before submitting a pull request, use the pre-commit tool to check your changes:

pre-commit run --all-files

You can also reach out to the OpenManus team directly via email at [email protected].

Join the OpenManus community to share experiences, ask questions, and collaborate with other developers:

• GitHub Repository: https://github.com/mannaandpoem/OpenManus
• Community Group: Join the networking group on Feishu (link available in the GitHub repository)
• Contributions: As of early 2025, OpenManus has garnered over 40,000 stars and 6,800 forks on GitHub, with 46+ contributors actively improving the project

Conclusion

OpenManus represents a significant step toward democratizing access to autonomous AI agents. By providing an open-source alternative to invitation-only platforms like Manus AI, it empowers developers, researchers, and organizations to harness the power of AI without barriers.

Whether you're looking to automate routine tasks, develop intelligent applications, or explore the frontiers of AI research, OpenManus offers a flexible, powerful framework that grows with community contributions.

Start your journey with OpenManus today, and join the revolution in open-source autonomous AI agents!

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This tutorial is designed to help you get started with OpenManus. As the project evolves, some details may change. Always refer to the official GitHub repository for the most up-to-date information.