README.md

metadata

title: HHH - Complete AI Platform
emoji: 🚀
colorFrom: red
colorTo: yellow
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: true
license: apache-2.0
suggested_hardware: l4x1
suggested_storage: large
tags:
  - AI
  - Authentication
  - Multi-Modal
  - HuggingFace
  - OpenManus
  - Qwen
  - DeepSeek
  - TTS
  - STT
  - Face-Swap
  - Avatar
  - Arabic
  - English
  - Cloudflare
short_description: Complete AI platform with 200+ models and mobile auth

English | 中文 | 한국어 | 日本語

   

👋 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:

# 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 and @Jinyu Xiang (core authors), along with @Zhaoyang Yu, @Jiayi Zhang, and @Sirui Hong, we are from @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, 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:

conda create -n open_manus python=3.12
conda activate open_manus

2. Clone the repository:

git clone https://github.com/FoundationAgents/OpenManus.git
cd OpenManus

3. 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

2. Clone the repository:

git clone https://github.com/FoundationAgents/OpenManus.git
cd OpenManus

3. Create a new virtual environment and activate it:

uv venv --python 3.12
source .venv/bin/activate  # On Unix/macOS
# Or on Windows:
# .venv\Scripts\activate

4. Install dependencies:

uv pip install -r requirements.txt

Browser Automation Tool (Optional)

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):

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

2. Edit config/config.toml to add your API keys and customize settings:

# 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:

python main.py

Then input your idea via terminal!

For MCP tool version, you can run:

python run_mcp.py

For unstable multi-agent version, you also can run:

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.

# 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

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!

Star History

Sponsors

Thanks to PPIO for computing source support.

PPIO: The most affordable and easily-integrated MaaS and GPU cloud solution.

Acknowledgement

Thanks to anthropic-computer-use, browser-use and crawl4ai for providing basic support for this project!

Additionally, we are grateful to AAAJ, MetaGPT, OpenHands and 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

@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},
}