Skill: twinsgeeks/ubuntu-ollama (version 1.0.0)

--- name: ubuntu-ollama description: Ubuntu Ollama — run Ollama on Ubuntu with fleet routing across multiple Ubuntu machines. Ubuntu Ollama setup with apt, systemd, and NVIDIA CUDA. Route Ollama inference across Ubuntu servers and desktops. Ubuntu Ollama load balancing, auto-discovery, and health monitoring. Ubuntu Ollama本地推理。Ubuntu Ollama enrutador IA. version: 1.0.0 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 Ollama — Fleet Routing for Ollama on Ubuntu Run Ollama on Ubuntu with multi-machine load balancing. Ubuntu Ollama Herd turns your Ubuntu servers and desktops into one smart Ollama endpoint. Install with apt + pip, manage with systemd, monitor with the web dashboard. ## Ubuntu Ollama setup ### Step 1: Install Ollama on Ubuntu ```bash # Install Ollama on Ubuntu curl -fsSL https://ollama.ai/install.sh | sh # Verify Ollama is running on Ubuntu ollama --version systemctl status ollama ``` ### Step 2: Install Ubuntu Ollama Herd ```bash # Ubuntu prerequisites sudo apt update && sudo apt install python3-pip curl -y # Install Ubuntu Ollama fleet router pip install ollama-herd ``` ### Step 3: Start Ubuntu Ollama router On one Ubuntu machine (the router): ```bash herd # start Ubuntu Ollama router on port 11435 herd-node # register this Ubuntu Ollama node ``` On every other Ubuntu machine: ```bash herd-node # auto-discovers the Ubuntu Ollama router via mDNS ``` > No mDNS? Connect Ubuntu Ollama nodes directly: `herd-node --router-url http://router-ip:11435` ### Step 4: Verify Ubuntu Ollama fleet ```bash curl -s http://localhost:11435/fleet/status | python3 -m json.tool ``` ## Ubuntu Ollama systemd services Run Ubuntu Ollama as systemd services for automatic startup: ```bash # Ubuntu Ollama router service sudo tee /etc/systemd/system/herd-router.service << 'EOF' [Unit] Description=Ubuntu Ollama Router After=network.target ollama.service [Service] Type=simple ExecStart=/usr/local/bin/herd Restart=always RestartSec=5 [Install] WantedBy=multi-user.target EOF # Ubuntu Ollama node service sudo tee /etc/systemd/system/herd-node.service << 'EOF' [Unit] Description=Ubuntu Ollama 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-router sudo systemctl enable --now herd-node ``` ## Use Ubuntu Ollama ### OpenAI SDK ```python from openai import OpenAI # Your Ubuntu Ollama fleet client = OpenAI(base_url="http://localhost:11435/v1", [REDACTED_SECRET]") response = client.chat.completions.create( model="llama3.3:70b", messages=[{"role": "user", "content": "Write an Ubuntu cron job for log rotation"}], stream=True, ) for chunk in response: print(chunk.choices[0].delta.content or "", end="") ``` ### curl (Ollama format) ```bash # Ubuntu Ollama inference curl http://localhost:11435/api/chat -d '{ "model": "qwen3.5:32b", "messages": [{"role": "user", "content": "Explain Ubuntu apt package management"}], "stream": false }' ``` ### curl (OpenAI format) ```bash curl http://localhost:11435/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{"model": "phi4", "messages": [{"role": "user", "content": "Hello from Ubuntu Ollama"}]}' ``` ## Ubuntu Ollama NVIDIA CUDA setup ```bash # Install NVIDIA drivers on Ubuntu for Ollama CUDA sudo apt install nvidia-driver-550 -y sudo reboot # Verify Ubuntu NVIDIA CUDA nvidia-smi # Ubuntu Ollama automatically uses CUDA when NVIDIA drivers are installed ollama ps # should show GPU acceleration ``` ## Ubuntu Ollama environment ```bash # Optimize Ollama on Ubuntu via systemd sudo systemctl edit ollama # Add under [Service]: # Environment="OLLAMA_KEEP_ALIVE=-1" # Environment="OLLAMA_MAX_LOADED_MODELS=-1" # Environment="OLLAMA_NUM_PARALLEL=2" sudo systemctl restart ollama # Verify Ubuntu Ollama settings systemctl show ollama | grep Environment ``` ## Ubuntu Ollama model recommendations | Ubuntu Machine | GPU | Best Ubuntu Ollama models | |---------------|-----|--------------------------| | Ubuntu desktop (RTX 4090) | 24GB | `llama3.3:70b`, `qwen3.5:32b`, `deepseek-r1:32b` | | 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` | | Ubuntu on Raspberry Pi 5 | CPU | `gemma3:1b`, `phi4-mini` | ## Ubuntu Ollama firewall ```bash # Ubuntu UFW sudo ufw allow 11435/tcp sudo ufw reload ``` ## Monitor Ubuntu Ollama ```bash # Ubuntu Ollama fleet status curl -s http://localhost:11435/fleet/status | python3 -m json.tool # Ubuntu Ollama health — 15 automated checks curl -s http://localhost:11435/dashboard/api/health | python3 -m json.tool # Ubuntu Ollama models loaded curl -s http://localhost:11435/api/ps | python3 -m json.tool # Ubuntu Ollama logs journalctl -u herd-router -f tail -f ~/.fleet-manager/logs/herd.jsonl.$(date +%Y-%m-%d) ``` Dashboard at `http://localhost:11435/dashboard` — live Ubuntu Ollama monitoring. ## Also available on Ubuntu Ollama ### Image generation ```bash curl http://localhost:11435/api/generate-image \ -d '{"model": "z-image-turbo", "prompt": "Ubuntu penguin in space", "width": 1024, "height": 1024}' ``` ### Embeddings ```bash curl http://localhost:11435/api/embed \ -d '{"model": "nomic-embed-text", "input": "Ubuntu Ollama local inference routing"}' ``` ## Full documentation - [Agent Setup Guide](https://github.com/geeks-accelerator/ollama-herd/blob/main/docs/guides/agent-setup-guide.md) - [API Reference](https://github.com/geeks-accelerator/ollama-herd/blob/main/docs/api-reference.md) ## Contribute Ollama Herd is open source (MIT). Ubuntu Ollama users welcome: - [Star on GitHub](https://github.com/geeks-accelerator/ollama-herd) - [Open an issue](https://github.com/geeks-accelerator/ollama-herd/issues) ## Guardrails - **Ubuntu Ollama model downloads require explicit user confirmation.** - **Ubuntu Ollama 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.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)