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Project Overview
SparkCore Network Studio
📌 Fuxi (Fuxi-OM)
A Large Language Model for Server Operations & Automation Script Development
📖 Project Overview
Fuxi (Fuxi-OM) is a large language model launched by SparkCore Network Studio, specifically designed for server operations and automation script development.
The model has been trained on a vast corpus of operations documentation, Shell/Python/Ansible scripts, cloud platform API manuals, and real-world production troubleshooting cases, enabling it to:
- Generate secure, executable operations scripts directly from natural language requirements
- Analyze existing configurations and logs, and provide optimization recommendations
- Simulate troubleshooting processes to assist in rapidly pinpointing online issues
- Support interactive command generation, seamlessly embedding into daily operations workflows
This project provides the open-source weights, inference code, and supporting tools for Fuxi-OM, aiming to lower the barrier to automated operations and promote the democratization of AIOps (AI for IT Operations) technology.
✨ Features
- Purpose-Built for Ops: Built upon a base language model with extensive continual pre-training and instruction fine-tuning in the operations domain, with deep understanding of core concepts such as
crontab,systemd,iptables,docker, andk8s - Multi-Language Script Generation: Supports a wide range of operations scripting languages
- High-Security Alerts: Every generated script includes risk warnings and permission notes to prevent misoperation
For example, high-risk commands like
rm -rf will trigger explicit warnings
- Interactive Dialogue: Supports multi-turn conversations, allowing you to refine requirements step by step — for instance, "First write a monitoring script, then add DingTalk alerting"
- Lightweight Options: Offers 4‑bit quantized and GGUF versions, capable of running on standard servers or even a Raspberry Pi
- Local & Offline: All inference is performed locally, with no need to upload sensitive operations data to third parties
Screenshots