English | [中文](README_zh.md) [](https://github.com/gregpr07/browser-use/stargazers) [](https://twitter.com/openmanus) [](https://opensource.org/licenses/MIT) # 👋 OpenManus Manus is incredible, but OpenManus can achieve any idea without an *Invite Code* 🛫! Our team members [@mannaandpoem](https://github.com/mannaandpoem) [@XiangJinyu](https://github.com/XiangJinyu) [@MoshiQAQ](https://github.com/MoshiQAQ) [@didiforgithub](https://github.com/didiforgithub) [@stellaHSR](https://github.com/stellaHSR) and [@Xinyu Zhang](https://x.com/xinyzng), we are from [@MetaGPT](https://github.com/geekan/MetaGPT) etc. The prototype is launched within 3 hours and we are keeping building! It's a simple implementation, so we welcome any suggestions, contributions, and feedback! Enjoy your own agent with OpenManus! We're also excited to introduce [OpenManus-RL](https://github.com/OpenManus/OpenManus-RL), an open-source project dedicated to reinforcement learning (RL)- based (such as GRPO) tuning methods for LLM agents, developed collaboratively by researchers from UIUC and OpenManus. ## Project Demo ## Installation We provide two installation methods. Method 2 (using uv) is recommended for faster installation and better dependency management. ### Method 1: Using conda 1. Create a new conda environment: ```bash conda create -n open_manus python=3.12 conda activate open_manus ``` 2. Clone the repository: ```bash git clone https://github.com/mannaandpoem/OpenManus.git cd OpenManus ``` 3. Install dependencies: ```bash pip install -r requirements.txt ``` ### Method 2: Using uv (Recommended) 1. Install uv (A fast Python package installer and resolver): ```bash curl -LsSf https://astral.sh/uv/install.sh | sh ``` 2. Clone the repository: ```bash git clone https://github.com/mannaandpoem/OpenManus.git cd OpenManus ``` 3. Create a new virtual environment and activate it: ```bash uv venv source .venv/bin/activate # On Unix/macOS # Or on Windows: # .venv\Scripts\activate ``` 4. Install dependencies: ```bash uv pip install -r requirements.txt ``` ## Configuration OpenManus requires configuration for the LLM APIs it uses. Follow these steps to set up your configuration: 1. Create a `config.toml` file in the `config` directory (you can copy from the example): ```bash cp config/config.example.toml config/config.toml ``` 2. Edit `config/config.toml` to add your API keys and customize settings: ```toml # Global LLM configuration [llm] model = "gpt-4o" base_url = "https://api.openai.com/v1" api_key = "sk-..." # Replace with your actual API key max_tokens = 4096 temperature = 0.0 # Optional configuration for specific LLM models [llm.vision] model = "gpt-4o" base_url = "https://api.openai.com/v1" api_key = "sk-..." # Replace with your actual API key ``` ## Quick Start One line for run OpenManus: ```bash python main.py ``` Then input your idea via terminal! For unstable version, you also can run: ```bash python run_flow.py ``` ## How to contribute We welcome any friendly suggestions and helpful contributions! Just create issues or submit pull requests. Or contact @mannaandpoem via 📧email: mannaandpoem@gmail.com ## Roadmap After comprehensively gathering feedback from community members, we have decided to adopt a 3-4 day iteration cycle to gradually implement the highly anticipated features. - [ ] Enhance Planning capabilities, optimize task breakdown and execution logic - [ ] Introduce standardized evaluation metrics (based on GAIA and TAU-Bench) for continuous performance assessment and optimization - [ ] Expand model adaptation and optimize low-cost application scenarios - [ ] Implement containerized deployment to simplify installation and usage workflows - [ ] Enrich example libraries with more practical cases, including analysis of both successful and failed examples - [ ] Frontend/backend development to improve user experience ## Community Group Join our discord group [](https://discord.gg/jkT5udP9bw) Join our networking group on Feishu and share your experience with other developers!