ollama

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Deploy and serve local models with Ollama — pull and run them, then expose the OpenAI-compatible endpoint to apps and agents.

AI & Automation 199 stars 23 forks Updated today Apache-2.0

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Skill Content

# Ollama Serving Ollama runs open-weight models locally with automatic GPU detection and an OpenAI-compatible API on `http://localhost:11434`. ## Before you start If the user's message only invokes this skill (e.g. "use ollama skill") without a concrete request, ask the user what they want. Do not run any command until the goal is clear. Ask the user which model to run; if they have no preference, recommend the small default [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) (`ollama pull qwen3.5:0.8b`). The model must fit the machine's RAM/VRAM. Ollama runs everywhere — macOS, Linux and Windows, on CPUs as well as NVIDIA/AMD GPUs — so engine choice follows the user's preference: Ollama is the simple default, while vLLM targets high-throughput GPU serving. Check the current state first: ```bash ollama --version # is Ollama installed? ollama ps # is the service already serving models? ``` If port 11434 is already serving, reuse that instance — never kill an existing Ollama process. ## Suggested workflow 1. Ask the user which model to run; with no preference, recommend [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) (`qwen3.5:0.8b`). 2. Pick the engine the user prefers: Ollama is the default; vLLM covers high-throughput GPU serving. 3. Install Ollama if missing, then `ollama pull qwen3.5:0.8b`. 4. Verify with `curl http://localhost:11434/v1/models`. 5. Register the endpoint: `penguin config model add ... --client-type openai --base-u...

Details

Author
Prism-Shadow
Repository
Prism-Shadow/penguin-harness
Created
1 weeks ago
Last Updated
today
Language
TypeScript
License
Apache-2.0

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