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local-ai-stack本地 AI 堆栈

Agent Skill

local-ai-stack 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,999

周安装

85

GitHub Stars

公开资料未说明

下载量

561
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:local-ai-stack(本地 AI 堆栈)
来源仓库:https://github.com/jaysclawd-cloud/local-ai-stack
安装命令:
openclaw skills install local-ai-stack
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install local-ai-stack

简介

使用 Ollama 和 OpenCode 将您的 Mac 转变为离线 AI 工作站,运行精选的本地模型进行编码和推理,无需互联网或 API 成本。

SKILL.md

SKILL.md — Local AI Stack

Purpose

Transform any Mac into a powerful offline AI workstation. Installs Ollama (local model runner) + OpenCode (terminal coding agent) with the best pre-selected models. Fully offline — no API costs, no internet required.

What You Get

  • Ollama — Local model runner (14GB models, ~$0 to run)
  • OpenCode — Terminal coding agent with free built-in models
  • 4 curated models — qwen2.5-coder, mistral, gemma3, llama3.2
  • Bi-weekly auto-updates — New models pulled automatically
  • OpenClaw integration — Works with your existing agent

Requirements

  • macOS (Apple Silicon recommended)
  • 24GB+ RAM (for larger models)
  • 50GB+ free disk space
  • Homebrew installed

Installation

Step 1: Install Ollama

curl -fsSL https://ollama.com/install.sh | sh

Or download from: https://ollama.com/download

Step 2: Pull Models

ollama pull qwen2.5-coder    # Best for coding
ollama pull mistral          # Fast tasks
ollama pull gemma3          # Reasoning
ollama pull llama3.2        # General purpose

Step 3: Install OpenCode

brew install opencode

Step 4: Configure OpenCode

# Test free built-in model
opencode run "Hello" --model opencode/big-pickle

Usage

Ollama Commands

# Run a local model
ollama run qwen2.5-coder "Write a Python function..."

# List installed models
ollama list

# Pull latest model version
ollama pull qwen2.5-coder

# Remove a model
ollama rm mistral

OpenCode Commands

# Interactive coding session
opencode

# Single command
opencode run "Write a React component" --model opencode/big-pickle

# List available models
opencode models

# Help
opencode --help

Model Selection Guide

ModelSizeBest For
qwen2.5-coder4.7GBCoding (primary)
mistral4.4GBFast responses
gemma33.3GBReasoning
llama3.22.0GBGeneral purpose

When to Use Local vs Cloud

Use Local When:

  • Offline (no internet)
  • Privacy-sensitive work
  • Quick coding tasks
  • Cost-sensitive (zero API fees)
  • Simple to medium complexity tasks

Use Cloud When:

  • Complex multi-step reasoning
  • Web search required
  • Long creative writing
  • Image generation
  • Advanced AI capabilities

Bi-Weekly Auto-Update

Add to cron for automatic model updates:

# Edit crontab
crontab -e

# Add this line (1st and 15th of each month at 9 AM)
0 9 1,15 * * /path/to/update-models.sh

Troubleshooting

Ollama won't start

# Check if running
ps aux | grep ollama

# Start manually
ollama serve

# Check logs
cat ~/.ollama/ollama.log

Model runs out of memory

  • Close other apps
  • Use smaller model (llama3.2 instead of qwen2.5-coder)
  • Check available RAM: top | head -20

OpenCode not found

# Find installation
which opencode

# Reinstall if needed
brew reinstall opencode

Files

  • Models stored: ~/.ollama/models/
  • Config: ~/.ollama/config.json
  • Logs: ~/.ollama/ollama.log

License

Ollama: MIT OpenCode: MIT

Author

Built with ❤️ for the OpenClaw community

Notes

  • Models load into RAM when used, unload when idle
  • Only one model runs at a time by default
  • For best performance, use Apple Silicon Mac with 24GB+ RAM

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

75.36%
按下载量换算423

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install local-ai-stack 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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