About

Imported from bobmatnyc/claude-mpm-skills (toolchains/ai/ops/local-llm-ops/SKILL.md) via skills.sh. Install upstream with npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops. Copyright stays with the author (MIT).

Local LLM Ops (Ollama)

Name: local-llm-ops
Author: bobmatnyc

Overview

Your localLLM repo provides a full local LLM toolchain on Apple Silicon: setup scripts, a rich CLI chat launcher, benchmarks, and diagnostics. The operational path is: install Ollama, ensure the service is running, initialize the venv, pull models, then launch chat or benchmarks.

Quick Start

./setup_chatbot.sh
./chatllm

If no models are present:

ollama pull mistral

Setup Checklist

Install Ollama: brew install ollama
Start the service: brew services start ollama
Run setup: ./setup_chatbot.sh
Verify service: curl http://localhost:11434/api/version

Chat Launchers

./chatllm (primary launcher)
./chat or ./chat.py (alternate launchers)
Aliases: ./install_aliases.sh then llm, llm-code, llm-fast

Task modes:

./chat -t coding -m codellama:70b
./chat -t creative -m llama3.1:70b
./chat -t analytical

Benchmark Workflow

Benchmarks are scripted in scripts/run_benchmarks.sh:

./scripts/run_benchmarks.sh

This runs bench_ollama.py with:

benchmarks/prompts.yaml
benchmarks/models.yaml
Multiple runs and max token limits

Diagnostics

Run the built-in diagnostic script when setup fails:

./diagnose.sh

Common fixes:

Re-run ./setup_chatbot.sh
Ensure ollama is in PATH
Pull at least one model: ollama pull mistral

Operational Notes

Virtualenv lives in .venv
Chat configs and sessions live under ~/.localllm/
Ollama API runs at http://localhost:11434

Related Skills

toolchains/universal/infrastructure/docker

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/bobmatnyc-claude-mpm-skills-local-llm-ops/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

bobmatnyc-claude-mpm-skills-local-llm-ops.ocm.jsonjson

{
  "ocm": "1",
  "id": "bobmatnyc-claude-mpm-skills-local-llm-ops",
  "kind": "skill",
  "name": "local-llm-ops",
  "description": "Local LLM operations with Ollama on Apple Silicon, including setup, model pulls, chat launchers, benchmarks, and diagnostics.",
  "publisher": "bobmatnyc",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "llm",
      "ollama",
      "local",
      "benchmark",
      "chat",
      "ops",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Local LLM operations with Ollama on Apple Silicon, including setup, model pulls, chat launchers, benchmarks, and diagnostics."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/bobmatnyc/claude-mpm-skills",
      "path": "toolchains/ai/ops/local-llm-ops/SKILL.md",
      "ref": "HEAD",
      "url": "https://www.skills.sh/bobmatnyc/claude-mpm-skills/local-llm-ops",
      "key": "bobmatnyc/claude-mpm-skills/toolchains/ai/ops/local-llm-ops/SKILL.md"
    },
    "license": "MIT"
  },
  "instructions": "# Local LLM Ops (Ollama)\n\n## Overview\n\nYour `localLLM` repo provides a full local LLM toolchain on Apple Silicon: setup scripts, a rich CLI chat launcher, benchmarks, and diagnostics. The operational path is: install Ollama, ensure the service is running, initialize the venv, pull models, then launch chat or benchmarks.\n\n## Quick Start\n\n```bash\n./setup_chatbot.sh\n./chatllm\n```\n\nIf no models are present:\n\n```bash\nollama pull mistral\n```\n\n## Setup Checklist\n\n1. Install Ollama: `brew install ollama`\n2. Start the service: `brew services start ollama`\n3. Run setup: `./setup_chatbot.sh`\n4. Verify se",
  "cost": {
    "context_tokens": 406
  }
}

Fetch it by URL: GET /api/v1/registry/bobmatnyc-claude-mpm-skills-local-llm-ops/manifest?version=1.0.0

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