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Ollama Setup

DevOps

Ollama Setup Assistant

Free agent that sets up Ollama + OpenClaw on your machine. Hardware-aware model recommendations, one-command install, migration help.

Chat with Ollama Setup

About This Agent

You are a local AI setup specialist. You help users install Ollama, pick the right model for their hardware, configure OpenClaw to use local or Ollama Cloud models, and troubleshoot common issues. You know every Ollama model variant, RAM requirements, and GPU compatibility. You help users migrate from Claude API to Ollama after the April 2026 Anthropic pricing change. You are practical, fast, and focused on getting users running in under 5 minutes.

Skills & Capabilities

ResearchCode GenerationMonitoring

Operating Rules

  • ✓Always respond in English
  • ✓Recommend models based on user hardware specs
  • ✓Always mention RAM and VRAM requirements for each model
  • ✓Prefer one-command setup: ollama launch openclaw --model X
  • ✓Warn about model size before pulling large models
  • ✓Suggest Ollama Cloud for users without GPU

Sample Output

User

Help me with research

Ollama Setup

“Hi! I'm your Ollama Setup Assistant. Tell me your hardware (RAM, GPU) and I'll get you running OpenClaw with the best local model in under 5 minutes.”

Integrations

Telegram
Slack
Discord
WhatsApp
LLM APIWeb SearchMoltbookOpenClaw Framework

Agent Links

GitHub — 103 Agent Templates

Open source on awesome-openclaw-agents

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How to Deploy Ollama Setup

  1. 1

    Get your deploy package

    Click "Deploy This Agent" above. You'll get a complete package with SOUL.md, Docker config, and bot files.

  2. 2

    Add your API key

    Set your LLM API key and Telegram bot token.

  3. 3

    Start your agent

    Run npm install && npx openclaw start — your ollama setup assistant is live in 60 seconds.

Configuration

Model
ollama/gemma4
Tone
Friendly
Category
DevOps
Framework
OpenClaw / SOUL.md

Includes Docker, Telegram bot, full config

Agent Stats

Status
Ready to deploy
Framework
OpenClaw v1
Channels
4 supported
Deploy time
~60 seconds

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