360 Secure SkillHub
360 安全技能中心

Ubuntu Ai

Ubuntu AI是专为Ubuntu/Debian打造的本地AI平台,支持x86、ARM异构硬件集群,兼容NVIDIA CUDA等加速方案。核心功能涵盖LLM推理、图像生成、嵌入服务,兼容OpenAI SDK,自带监控面板。可部署在桌面、服务器、树莓派等设备,无需云API及订阅,全程免费。通过命令行快速部署,可通过curl或代码调用API获取结果。

twinsgeeks
twinsgeeks
热度 46.82
最近更新 2026-05-11 17:39:59
分类:开发依赖:纯提示词应用场景:DevOps / API 集成 / 代码生成

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add ubuntu-ai
Metadata
name
ubuntu-ai
description
Ubuntu AI — build a local AI platform on Ubuntu and Debian. Ubuntu AI across x86 desktops, ARM edge devices, Raspberry Pi, Jetson Orin, and cloud VMs. Heterogeneous Ubuntu AI cluster with NVIDIA CUDA, AMD ROCm, and CPU inference. LLM, image generation, and embeddings on Ubuntu. Debian AI with the same stack. Ubuntu AI本地推理平台。Ubuntu IA plataforma local.
version
1.0.1
homepage
https://github.com/geeks-accelerator/ollama-herd
metadata
{"openclaw":{"emoji":"penguin","requires":{"anyBins":["curl","wget"],"optionalBins":["python3","pip","nvidia-smi","systemctl","apt"]},"configPaths":["~/.fleet-manager/latency.db","~/.fleet-manager/logs/herd.jsonl"],"os":["linux"]}}

Ubuntu AI — Build a Local AI Platform on Ubuntu

Build a complete local AI platform on Ubuntu. LLM inference, image generation, and embeddings across desktops, servers, Raspberry Pis, and Jetson boards. Ubuntu AI supports x86-64 and ARM in the same cluster — heterogeneous hardware, one endpoint. No cloud APIs, no subscriptions.

Why Ubuntu AI

  • Largest Linux ecosystem — Ubuntu is the #1 Linux distribution for AI/ML workloads
  • apt-get native — install dependencies with the Ubuntu package manager you know
  • systemd integration — Ubuntu AI starts on boot, restarts on failure
  • NVIDIA CUDA on Ubuntu — best GPU driver support on any Linux distribution
  • ARM + x86 — Ubuntu AI runs on x86-64 servers and ARM devices (Raspberry Pi, Jetson)
  • Free forever — Ubuntu is free, Ollama is free, Ollama Herd is free

Ubuntu AI quick start

# Ubuntu prerequisites
sudo apt update
sudo apt install python3-pip curl

# Install Ollama on Ubuntu
curl -fsSL https://ollama.ai/install.sh | sh

# Install Ubuntu AI router
pip install ollama-herd

# Start Ubuntu AI
herd          # Ubuntu AI router on port 11435
herd-node     # register this Ubuntu machine

On other Ubuntu/Debian machines:

pip install ollama-herd
herd-node     # auto-discovers the Ubuntu AI router

Ubuntu AI with NVIDIA CUDA

# Install NVIDIA drivers on Ubuntu
sudo apt install nvidia-driver-550
sudo reboot

# Verify Ubuntu NVIDIA CUDA
nvidia-smi

# Ollama on Ubuntu automatically detects NVIDIA CUDA
ollama ps    # should show GPU acceleration

Ubuntu AI systemd services

# Ubuntu AI router service
sudo tee /etc/systemd/system/herd-router.service << 'EOF'
[Unit]
Description=Ubuntu AI Router
After=network.target ollama.service

[Service]
Type=simple
ExecStart=/usr/local/bin/herd
Restart=always
RestartSec=5

[Install]
WantedBy=multi-user.target
EOF

sudo systemctl enable --now herd-router
# Ubuntu AI node service
sudo tee /etc/systemd/system/herd-node.service << 'EOF'
[Unit]
Description=Ubuntu AI Node
After=network.target ollama.service

[Service]
Type=simple
ExecStart=/usr/local/bin/herd-node
Restart=always
RestartSec=5

[Install]
WantedBy=multi-user.target
EOF

sudo systemctl enable --now herd-node

Use Ubuntu AI

OpenAI SDK

from openai import OpenAI

# Your Ubuntu AI endpoint
client = OpenAI(base_url="http://localhost:11435/v1", api_key="not-needed")

response = client.chat.completions.create(
    model="qwen3.5:32b",
    messages=[{"role": "user", "content": "Write an Ubuntu systemd timer for daily backups"}],
    stream=True,
)
for chunk in response:
    print(chunk.choices[0].delta.content or "", end="")

curl

# Ubuntu AI inference
curl http://localhost:11435/api/chat -d '{
  "model": "llama3.3:70b",
  "messages": [{"role": "user", "content": "Explain Ubuntu package management"}],
  "stream": false
}'

Ubuntu AI hardware guide

Ubuntu Device GPU Best Ubuntu AI models
Ubuntu desktop (RTX 4090) 24GB llama3.3:70b, qwen3.5:32b
Ubuntu desktop (RTX 4080) 16GB phi4, codestral, qwen3.5:14b
Ubuntu Server (A100) 80GB deepseek-v3, qwen3.5:72b
Ubuntu Server (no GPU) CPU phi4-mini, gemma3:4b
Raspberry Pi 5 (Ubuntu) CPU gemma3:1b, phi4-mini — edge Ubuntu AI
Jetson Orin Nano (Ubuntu) 8GB shared phi4, llama3.2:3b — ARM Ubuntu AI

Ubuntu AI supports x86-64 and ARM architectures. Heterogeneous Ubuntu AI clusters work automatically.

Ubuntu AI environment

# Optimize Ollama on Ubuntu
sudo systemctl edit ollama
# Add under [Service]:
#   Environment="OLLAMA_KEEP_ALIVE=-1"
#   Environment="OLLAMA_MAX_LOADED_MODELS=-1"
sudo systemctl restart ollama

Ubuntu AI firewall

# Ubuntu UFW
sudo ufw allow 11435/tcp
sudo ufw reload

Monitor Ubuntu AI

# Ubuntu AI fleet status
curl -s http://localhost:11435/fleet/status | python3 -m json.tool

# Ubuntu AI health — 15 automated checks
curl -s http://localhost:11435/dashboard/api/health | python3 -m json.tool

# Ubuntu AI logs
journalctl -u herd-router -f

Dashboard at http://localhost:11435/dashboard — live Ubuntu AI monitoring.

Also available on Ubuntu AI

Image generation

curl http://localhost:11435/api/generate-image \
  -d '{"model": "z-image-turbo", "prompt": "Ubuntu penguin mascot", "width": 1024, "height": 1024}'

Embeddings

curl http://localhost:11435/api/embed \
  -d '{"model": "nomic-embed-text", "input": "Ubuntu AI local inference Debian"}'

Full documentation

Contribute

Ollama Herd is open source (MIT). Ubuntu AI users welcome:

Guardrails

  • Ubuntu AI model downloads require explicit user confirmation.
  • Ubuntu AI model deletion requires explicit user confirmation.
  • Never delete or modify files in ~/.fleet-manager/.
  • No models are downloaded automatically — all pulls are user-initiated or require opt-in.