Local Llm Ops

Name: Local Llm Ops
Author: bobmatnyc

bobmatnyc/claude-mpm-skills

304 installs
63 repo stars
Updated July 18, 2026
bobmatnyc/claude-mpm-skills

Run, tune, and maintain local LLM stacks for private inference, offline agents, and cost-controlled model serving.

About

Teaches operating local LLM infrastructure: model download, quantization, GPU/runtime setup, serving endpoints, caching, upgrades, and monitoring for private agent, CLI, and API inference workloads.

Local model serving
GPU and runtime setup
Quantization choices
Private inference workflows
Ops monitoring for LLMs

Local Llm Ops by the numbers

304 all-time installs (skills.sh)
Ranked #2,279 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
Data as of Aug 1, 2026 (Skillselion catalog sync)

npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill local-llm-ops

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Installs	304
repo stars	★ 63
Last updated	July 18, 2026
Repository	bobmatnyc/claude-mpm-skills ↗

What it does

Run, tune, and maintain local LLM stacks for private inference, offline agents, and cost-controlled model serving.

Files

SKILL.mdMarkdownGitHub ↗

Local LLM Ops (Ollama)

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

1. Install Ollama: brew install ollama 2. Start the service: brew services start ollama 3. Run setup: ./setup_chatbot.sh 4. 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

{
  "name": "local-llm-ops",
  "version": "1.0.0",
  "category": "toolchain",
  "toolchain": "ai",
  "framework": "local-llm-ops",
  "tags": [
    "llm",
    "ollama",
    "local",
    "benchmark",
    "chat",
    "ops"
  ],
  "entry_point_tokens": 125,
  "full_tokens": 659,
  "related_skills": [],
  "author": "Claude MPM Team",
  "license": "MIT",
  "updated": "2025-12-31",
  "source_path": "toolchains/ai/ops/local-llm-ops/SKILL.md",
  "repository": "https://github.com/bobmatnyc/claude-mpm-skills"
}