https://github.com/henryalps/OpenManus
OpenManus is an open-source initiative to replicate the capabilities of the Manus AI agent, a state-of-the-art general-purpose AI developed by Monica, which excels in autonomously executing complex tasks.
https://github.com/henryalps/OpenManus
Last synced: 3 months ago
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OpenManus is an open-source initiative to replicate the capabilities of the Manus AI agent, a state-of-the-art general-purpose AI developed by Monica, which excels in autonomously executing complex tasks.
- Host: GitHub
- URL: https://github.com/henryalps/OpenManus
- Owner: henryalps
- License: unlicense
- Created: 2025-03-06T10:42:34.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-06-07T04:45:05.000Z (4 months ago)
- Last Synced: 2025-06-16T03:32:35.487Z (4 months ago)
- Language: Python
- Size: 65.4 KB
- Stars: 646
- Watchers: 29
- Forks: 170
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- Awesome-MCoT - **OpenManus: An open-source framework for building general AI agents**
README
# OpenManus
## Overview
OpenManus is an open-source project aimed at replicating the capabilities of the Manus AI agent, a groundbreaking general-purpose AI developed by Monica. Manus is known for its ability to autonomously execute complex tasks—ranging from personalized travel planning to stock analysis—surpassing models like GPT-4 on the GAIA benchmark. OpenManus seeks to bring these capabilities to the open-source community using a modular, containerized framework built with Docker, Python, and JavaScript.
This repository provides a starting point for developers and researchers to build, deploy, and experiment with a multi-agent AI system. Our goal is to create a flexible and extensible platform that mirrors Manus's autonomous task execution while fostering community contributions.
## Features
- **Multi-Agent System**: Collaborative AI agents working together to solve complex tasks.
- **Dockerized Environment**: Easy setup and deployment with containerization.
- **Task Execution**: Supports tasks like travel planning, data analysis, and content generation.
- **Tool Integration**: Web browsing, code execution, and data retrieval capabilities.
- **Modular Design**: Easily extendable with new agents, tools, or features.
- **Community-Driven**: Open to contributions and enhancements.
## Prerequisites
Before you begin, ensure you have the following installed:
- [Docker](https://docs.docker.com/get-docker/) (version 20.10 or higher)
- [Docker Compose](https://docs.docker.com/compose/install/) (version 1.29 or higher)
- [Node.js](https://nodejs.org/) (version 20.18 or higher, for local development)
- [Python](https://python.org/) (version 3.9 or higher, for local development)
- Git (for cloning and contributing)
## Getting Started
### 1. Clone the Repository
```bash
git clone https://github.com/henryalps/OpenManus.git
cd OpenManus
```
### 2. Build and Run with Docker
```bash
# Build and start all containers
docker-compose up --build
```
This will launch:
- Backend container with the multi-agent system and integrated tools
- Frontend container serving the Next.js web interface
- FastAPI server for task delegation and execution
### 3. Test the System
Once running, you can interact with OpenManus via:
- CLI: Use the provided Python client (`python client.py`)
- API: Send requests to http://localhost:8000 (see API docs below)
- Web UI: Access http://localhost:3000
Example CLI command:
```bash
python client.py --task "Plan a 3-day trip to Tokyo"
```
### Project Structure
```
OpenManus/
├── docker/ # Docker configurations
│ ├── frontend/ # Next.js frontend container
│ │ └── Dockerfile # Frontend container configuration
│ └── unified/ # Backend container configuration
│ ├── Dockerfile # Backend container configuration
│ └── start.sh # Container startup script
├── src/ # Source code
│ ├── agents/ # Multi-agent logic (Python)
│ │ ├── nodes/ # Agent node implementations
│ │ ├── browser_agent.py
│ │ ├── coder_agent.py
│ │ ├── coordinator.py
│ │ ├── reporter_agent.py
│ │ └── research_agent.py
│ ├── components/ # React components
│ ├── config/ # Configuration files
│ ├── graph/ # Graph-based workflow
│ ├── llms/ # LLM integrations
│ ├── pages/ # Next.js pages
│ ├── prompts/ # Agent prompts
│ ├── service/ # Backend services
│ ├── tools/ # Tool implementations
│ ├── utils/ # Utility functions
│ ├── workflow/ # Workflow management
│ ├── client.py # CLI client for testing
│ └── server.py # FastAPI server
├── docs/ # Documentation and API specs
├── package.json # Next.js frontend dependencies
├── next.config.js # Next.js configuration
├── docker-compose.yml # Docker Compose configuration
└── README.md # This file
```
### Configuration
Edit the `docker-compose.yml` file to customize:
```yaml
services:
backend:
build:
context: .
dockerfile: docker/unified/Dockerfile
ports:
- "8000:8000" # FastAPI port
environment:
- WEB_BROWSER_API_KEY=your_key_here
volumes:
- ./src:/app/src
- ./data:/app/data
frontend:
build:
context: .
dockerfile: docker/frontend/Dockerfile
ports:
- "3000:3000" # Web UI port
depends_on:
- backend
```
### API Documentation
The agent server exposes a REST API at http://localhost:8000. Key endpoints:
**POST /task**: Submit a task for execution.
```json
Body: { "task": "Analyze Tesla stock trends" }
Response: { "status": "success", "result": "..." }
```
**GET /status**: Check system health.
```json
Response: { "status": "running" }
```
Full API docs are available in `docs/api.md`.
### Contributing
We welcome contributions! To get started:
1. Fork the repository.
2. Create a feature branch (`git checkout -b feature/your-feature`).
3. Commit your changes (`git commit -m "Add your feature"`).
4. Push to your branch (`git push origin feature/your-feature`).
5. Open a Pull Request.
Please read `CONTRIBUTING.md` for guidelines.
### Roadmap
- Implement core multi-agent coordination.
- Add support for GAIA benchmark tasks.
- Integrate advanced NLP models (e.g., LLaMA, Grok).
- Enhance toolset with real-time web scraping and visualization.
- Release v1.0 with stable task execution.
### Inspiration
OpenManus is inspired by:
- The langmanus project (GitHub).
- The official Manus project (manus.im).
- The open-Manus community effort (GitHub).
- GAIA benchmark for general AI assistants (arXiv).
### License
This project is licensed under the UNLICENSE. See `LICENSE` for details.
### Contact
For questions or collaboration, reach out via GitHub Issues or email [henryalps@gmail.com](mailto:henryalps@gmail.com).
Happy coding! Let's build the future of AI agents together!
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