DataFlow-WebUI is a full-stack open-source web application that provides a graphical interface for the DataFlow framework. This guide walks you through setting up both the frontend and backend so you can quickly get up and running.
Before you begin, make sure you have:
- Python 3.10+
- pip
- Git
- A Unix-like shell (Linux/macOS) or PowerShell / CMD (Windows)
First, clone the DataFlow-WebUI repository and enter the project directory:
git clone https://github.com/OpenDCAI/DataFlow-WebUI.git
cd DataFlow-WebUIThe frontend is built with Node.js. We recommend using NVM (Node Version Manager) to manage your Node.js version.
# Download from GitHub
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
# Mirror download (recommended if you are in China)
curl -so- https://gitee.com/mirrors/nvm/raw/v0.39.7/install.sh | bashAfter installing NVM, restart your terminal or run one of the following commands:
# For bash
source ~/.bashrc
# For zsh
source ~/.zshrcnvm install 20
nvm use 20
nvm alias default 20Ensure that Node.js is version v20.x.x:
node -v
npm -vThe backend is powered by DataFlow and FastAPI.
You can install DataFlow in one of two ways:
git clone https://github.com/OpenDCAI/DataFlow
cd DataFlow
pip install -e .pip install open-dataflowFrom the project root directory, run:
pip install -r backend/requirements.txtcd frontend/
npm install
npm run buildThis will generate the production-ready frontend assets.
cd backend/- On Linux / macOS:
make dev- On Windows:
uvicorn app.main:app --reload --port 8000 --reload-dir app --host 0.0.0.0Once the backend is running, open your browser and visit:
http://localhost:8000/
💡 If you changed the backend port, replace
8000with your custom port.
You should now have the full DataFlow-WebUI stack running locally. If you encounter issues, double-check your Node.js and Python versions, and feel free to open an issue on GitHub.
Happy hacking! 🚀
If you use DataFlow in your research, feel free to give us a cite.
@article{liang2025dataflow,
title={DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI},
author={Liang, Hao and Ma, Xiaochen and Liu, Zhou and Wong, Zhen Hao and Zhao, Zhengyang and Meng, Zimo and He, Runming and Shen, Chengyu and Cai, Qifeng and Han, Zhaoyang and others},
journal={arXiv preprint arXiv:2512.16676},
year={2025}
}