--- title: ORYNXML Complete AI Platform emoji: 🤖 colorFrom: blue colorTo: indigo sdk: docker app_port: 7860 pinned: true license: apache-2.0 short_description: Complete AI Platform with 211 models across 8 categories suggested_hardware: a10g-large suggested_storage: large tags: - AI - Authentication - Multi-Modal - HuggingFace - OpenManus - Qwen - DeepSeek - TTS - STT - Face-Swap - Avatar - Arabic - English - Cloudflare ---

English | [中文](README_zh.md) | [한국어](README_ko.md) | [日本語](README_ja.md) [![GitHub stars](https://img.shields.io/github/stars/FoundationAgents/OpenManus?style=social)](https://github.com/FoundationAgents/OpenManus/stargazers)   [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)   [![Discord Follow](https://dcbadge.vercel.app/api/server/DYn29wFk9z?style=flat)](https://discord.gg/DYn29wFk9z) [![Demo](https://img.shields.io/badge/Demo-Hugging%20Face-yellow)](https://huggingface.co/spaces/lyh-917/OpenManusDemo) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15186407.svg)](https://doi.org/10.5281/zenodo.15186407) # 👋 OpenManus - Complete AI Platform 🤖 **200+ AI Models + Mobile Authentication + Cloudflare Services** Manus is incredible, but OpenManus can achieve any idea without an *Invite Code* 🛫! ## 🌟 Environment Variables Set these in your HuggingFace Space settings for full functionality: ```bash # Required for full Cloudflare integration CLOUDFLARE_API_TOKEN=your_cloudflare_token CLOUDFLARE_ACCOUNT_ID=your_account_id CLOUDFLARE_D1_DATABASE_ID=your_d1_database_id CLOUDFLARE_R2_BUCKET_NAME=your_r2_bucket CLOUDFLARE_KV_NAMESPACE_ID=your_kv_namespace # Enhanced AI model access HF_TOKEN=your_huggingface_token OPENAI_API_KEY=your_openai_key ANTHROPIC_API_KEY=your_anthropic_key # Application configuration ENVIRONMENT=production LOG_LEVEL=INFO SECRET_KEY=your_secret_key ``` Our team members [@Xinbin Liang](https://github.com/mannaandpoem) and [@Jinyu Xiang](https://github.com/XiangJinyu) (core authors), along with [@Zhaoyang Yu](https://github.com/MoshiQAQ), [@Jiayi Zhang](https://github.com/didiforgithub), and [@Sirui Hong](https://github.com/stellaHSR), we are from [@MetaGPT](https://github.com/geekan/MetaGPT). 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/FoundationAgents/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/FoundationAgents/OpenManus.git cd OpenManus ``` 3. Create a new virtual environment and activate it: ```bash uv venv --python 3.12 source .venv/bin/activate # On Unix/macOS # Or on Windows: # .venv\Scripts\activate ``` 4. Install dependencies: ```bash uv pip install -r requirements.txt ``` ### Browser Automation Tool (Optional) ```bash playwright install ``` ## 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 MCP tool version, you can run: ```bash python run_mcp.py ``` For unstable multi-agent version, you also can run: ```bash python run_flow.py ``` ### Custom Adding Multiple Agents Currently, besides the general OpenManus Agent, we have also integrated the DataAnalysis Agent, which is suitable for data analysis and data visualization tasks. You can add this agent to `run_flow` in `config.toml`. ```toml # Optional configuration for run-flow [runflow] use_data_analysis_agent = true # Disabled by default, change to true to activate ``` In addition, you need to install the relevant dependencies to ensure the agent runs properly: [Detailed Installation Guide](app/tool/chart_visualization/README.md##Installation) ## 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 **Note**: Before submitting a pull request, please use the pre-commit tool to check your changes. Run `pre-commit run --all-files` to execute the checks. ## Community Group Join our networking group on Feishu and share your experience with other developers!
OpenManus 交流群
## Star History [![Star History Chart](https://api.star-history.com/svg?repos=FoundationAgents/OpenManus&type=Date)](https://star-history.com/#FoundationAgents/OpenManus&Date) ## Sponsors Thanks to [PPIO](https://ppinfra.com/user/register?invited_by=OCPKCN&utm_source=github_openmanus&utm_medium=github_readme&utm_campaign=link) for computing source support. > PPIO: The most affordable and easily-integrated MaaS and GPU cloud solution. ## Acknowledgement Thanks to [anthropic-computer-use](https://github.com/anthropics/anthropic-quickstarts/tree/main/computer-use-demo), [browser-use](https://github.com/browser-use/browser-use) and [crawl4ai](https://github.com/unclecode/crawl4ai) for providing basic support for this project! Additionally, we are grateful to [AAAJ](https://github.com/metauto-ai/agent-as-a-judge), [MetaGPT](https://github.com/geekan/MetaGPT), [OpenHands](https://github.com/All-Hands-AI/OpenHands) and [SWE-agent](https://github.com/SWE-agent/SWE-agent). We also thank stepfun(阶跃星辰) for supporting our Hugging Face demo space. OpenManus is built by contributors from MetaGPT. Huge thanks to this agent community! ## Cite ```bibtex @misc{openmanus2025, author = {Xinbin Liang and Jinyu Xiang and Zhaoyang Yu and Jiayi Zhang and Sirui Hong and Sheng Fan and Xiao Tang}, title = {OpenManus: An open-source framework for building general AI agents}, year = {2025}, publisher = {Zenodo}, doi = {10.5281/zenodo.15186407}, url = {https://doi.org/10.5281/zenodo.15186407}, } ```