Skill: twinsgeeks/linux-ollama (version 1.0.0)

--- name: linux-ollama description: Linux Ollama — run Ollama on Linux with fleet routing across multiple Linux machines. Linux Ollama setup for Llama, Qwen, DeepSeek, Phi, Mistral. Route Ollama inference across Linux servers, desktops, and edge devices. Linux Ollama load balancing with systemd integration. Linux Ollama本地推理。Linux 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"]},"configPaths":["~/.fleet-manager/latency.db","~/.fleet-manager/logs/herd.jsonl"],"os":["linux"]}} --- # Linux Ollama — Fleet Routing for Ollama on Linux Run Ollama on Linux with multi-machine load balancing. Linux Ollama Herd turns multiple Linux machines into one smart Ollama endpoint. Your server rack, your desktop, your edge device — all serving AI through one Linux Ollama URL. ## Linux Ollama setup ### Step 1: Install Ollama on Linux ```bash curl -fsSL https://ollama.ai/install.sh | sh ``` ### Step 2: Install Linux Ollama Herd ```bash pip install ollama-herd ``` ### Step 3: Start the Linux Ollama router On one Linux machine (your router): ```bash herd # starts Linux Ollama router on port 11435 herd-node # registers this Linux machine ``` On every other Linux machine: ```bash herd-node # auto-discovers the Linux Ollama router via mDNS ``` > No mDNS? Connect Linux nodes directly: `herd-node --router-url http://router-ip:11435` ## Linux Ollama systemd integration Run Linux Ollama Herd as a systemd service for automatic startup: ```bash # /etc/systemd/system/ollama-herd.service [Unit] Description=Linux Ollama Herd Router After=network.target ollama.service [Service] Type=simple ExecStart=/usr/local/bin/herd Restart=always RestartSec=5 [Install] WantedBy=multi-user.target ``` ```bash sudo systemctl enable ollama-herd sudo systemctl start ollama-herd ``` Node agent as a Linux systemd service: ```bash # /etc/systemd/system/ollama-herd-node.service [Unit] Description=Linux Ollama Herd Node Agent After=network.target ollama.service [Service] Type=simple ExecStart=/usr/local/bin/herd-node Restart=always RestartSec=5 [Install] WantedBy=multi-user.target ``` ## Use Linux Ollama ### OpenAI SDK ```python from openai import OpenAI # Your Linux 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 a systemd service file for a Python API"}], stream=True, ) for chunk in response: print(chunk.choices[0].delta.content or "", end="") ``` ### curl (Ollama format) ```bash # Linux Ollama inference curl http://localhost:11435/api/chat -d '{ "model": "qwen3.5:32b", "messages": [{"role": "user", "content": "Explain Linux process scheduling"}], "stream": false }' ``` ## Linux Ollama environment setup ```bash # Optimize Linux Ollama performance 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 ``` Or via shell profile: ```bash echo 'export OLLAMA_KEEP_ALIVE=-1' >> ~/.bashrc echo 'export OLLAMA_MAX_LOADED_MODELS=-1' >> ~/.bashrc source ~/.bashrc ``` ## Linux Ollama GPU support | Linux GPU | vRAM | Best Linux Ollama models | |-----------|------|-------------------------| | NVIDIA RTX 4090 | 24GB | `llama3.3:70b`, `qwen3.5:32b` | | NVIDIA A100 | 40/80GB | `deepseek-v3`, `qwen3.5:72b` | | NVIDIA L40S | 48GB | `llama3.3:70b` (full precision) | | AMD ROCm (experimental) | varies | Ollama ROCm support on Linux | | CPU only | system RAM | `phi4-mini`, `gemma3:1b` — slower but works | > Linux Ollama supports NVIDIA CUDA, experimental AMD ROCm, and CPU-only inference. ## Linux Ollama firewall ```bash # UFW (Ubuntu/Debian) sudo ufw allow 11435/tcp # firewalld (RHEL/Fedora) sudo firewall-cmd --add-port=11435/tcp --permanent sudo firewall-cmd --reload # iptables sudo iptables -A INPUT -p tcp --dport 11435 -j ACCEPT ``` ## Monitor Linux Ollama ```bash # Linux Ollama fleet status curl -s http://localhost:11435/fleet/status | python3 -m json.tool # Linux Ollama health — 15 automated checks curl -s http://localhost:11435/dashboard/api/health | python3 -m json.tool # Models on Linux Ollama nodes curl -s http://localhost:11435/api/ps | python3 -m json.tool ``` Dashboard at `http://localhost:11435/dashboard` — live Linux Ollama monitoring. ## Linux Ollama logs ```bash # JSONL structured logs tail -f ~/.fleet-manager/logs/herd.jsonl.$(date +%Y-%m-%d) | python3 -m json.tool # Check for Linux Ollama errors grep '"level":"ERROR"' ~/.fleet-manager/logs/herd.jsonl.$(date +%Y-%m-%d) ``` ## Also available on Linux Ollama ### Image generation ```bash curl http://localhost:11435/api/generate-image \ -d '{"model": "z-image-turbo", "prompt": "Linux penguin in cyberspace", "width": 1024, "height": 1024}' ``` ### Embeddings ```bash curl http://localhost:11435/api/embed \ -d '{"model": "nomic-embed-text", "input": "Linux Ollama local inference"}' ``` ## 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). Linux 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 - **Linux Ollama model downloads require explicit user confirmation.** - **Linux 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:  | SkillSpector: suspicious (HIGH)