by Datayoo · Agent Tool · ★ 316
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中文 | English HuggingFists ================ HuggingFists is a low-code data flow tool that enables convenient use of LLM and HuggingFace models. Some of its functions can be considered as a low-code version of Langchain. Currently, it does not support model training scenarios, but this will be developed and supplemented in the future. Installation Instructions ============================= System Requirements Linux:Linux system 3.10.0-957.21.3.el7.x8664 At least 4 cores and 8GB of RAM; the system uses Containerd containers, and containers and images will be stored in the /data directory. Windows:Windows 11 is recommended. Installation Steps Linux Clone the project files from git using: git clone https://github.com/Datayoo/HuggingFists.git, or download directly as a zip file. Note that when cloning the project on a Windows operating system, the '\n' in Linux script files will be replaced with '\r\n'. When copying the project to a Linux system, the scripts will not execute due to the difference in '\n'. Developers using IDEA can refer to configuring Git to handle line endings to resolve this issue.
| Stars | 316 |
| Forks | 43 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 48.3181744262112/100 |
| Open Issues | 11 |
| Last Updated | 2025-10-28 |
| Created | 2023-10-24 |
| Platforms | python |
| Est. Tokens | ~277130k |
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HuggingFists is A low-code data flow tool that allows for convenient use of LLM and HuggingFace models, with some features considered as a low-code version of Langchain.. It is categorized as a Agent Tool with 316 GitHub stars.
HuggingFists is primarily written in Python.
You can find installation instructions and usage details in the HuggingFists GitHub repository at github.com/Datayoo/HuggingFists. The project has 316 stars and 43 forks, indicating an active community.
The top alternatives to HuggingFists on Agent Skills Hub include claude-forge, excalidraw-diagram-skill, agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.