ollama
FeaturedDeploy and serve local models with Ollama — pull and run them, then expose the OpenAI-compatible endpoint to apps and agents.
AI & Automation 208 stars
24 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
Integrates with
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