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ollama-memory-setup

Sets up local semantic memory search for OpenClaw using Ollama + nomic-embed-text. Use when: (1) memory_search returns 'node-llama-cpp is missing' or 'Local embeddings unavailable' error, (2) user wants local/private embeddings without external API keys (OpenAI, Gemini, Voyage), (3) setting up memory search for the first time on macOS or Linux, (4) node-llama-cpp fails to install or build. Fixes the common node-llama-cpp installation failure by routing through Ollama's OpenAI-compatible embedding API instead of a local binary.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/brasco05/ollama-memory-setup
Or

Ollama Memory Setup

Enables semantic memory search in OpenClaw using Ollama locally — no API keys, no cloud, fully private.

Wann verwenden?

Nutze diesen Skill wenn memory_search folgende Fehler wirft:

  • node-llama-cpp is missing (or failed to install)
  • Local embeddings unavailable
  • Cannot find package 'node-llama-cpp'
  • optional dependency node-llama-cpp is missing

Oder wenn du Embeddings lokal halten willst ohne externe APIs (OpenAI, Gemini, Voyage).

Verwendung

Automatisch (empfohlen)

# Setup-Script ausführen
bash ~/.openclaw/workspace/skills/ollama-memory-setup/scripts/setup.sh

# OpenClaw neu starten
openclaw gateway restart

Manuell (Schritt für Schritt)

# 1. Ollama installieren
brew install ollama                    # macOS
curl -fsSL https://ollama.com/install.sh | sh  # Linux

# 2. Ollama starten (macOS: als Service, startet automatisch)
brew services start ollama

# 3. Embedding-Modell laden (~270MB, einmalig)
ollama pull nomic-embed-text

# 4. OpenClaw konfigurieren
openclaw config set agents.defaults.memorySearch.provider ollama
openclaw config set agents.defaults.memorySearch.model nomic-embed-text
openclaw config set agents.defaults.memorySearch.remote.baseUrl http://localhost:11434
openclaw config set agents.defaults.memorySearch.enabled true

# 5. Neu starten
openclaw gateway restart

Aufstellen

Keine API-Keys nötig. Voraussetzungen:

  • macOS: Homebrew installiert (brew --version)
  • Linux: curl installiert, systemd empfohlen
  • Ollama Version: >= 0.18.0
  • Speicher: ~300MB für das nomic-embed-text Modell

Verifizieren

Nach dem Neustart in einer frischen Session testen:

memory_search("test")

Erwartete Antwort enthält "provider": "ollama" — nicht disabled: true.

Warum nomic-embed-text?

nomic-embed-text ist ein spezialisiertes Embedding-Modell (nicht für Chat):

  • Klein (~270MB vs. mehrere GB für Chat-Modelle)
  • Schnell (~50ms pro Anfrage auf moderner Hardware)
  • Hohe Qualität für semantische Suche
  • Kostenlos, Open Source (Apache 2.0)

Alternativer Modellname für ältere Ollama-Versionen: nomic-embed-text:latest

Fehlersuche

Siehe references/troubleshooting.md für häufige Probleme wie:

  • Ollama startet nicht
  • memory_search bleibt deaktiviert nach Setup
  • macOS: Ollama stoppt nach Neustart
  • Linux: Systemd-Service einrichten
Read Full Documentation on GitHub

Metadata

Author@brasco05
Stars4190
Views1
Updated2026-04-18
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-brasco05-ollama-memory-setup": {
      "enabled": true,
      "auto_update": true
    }
  }
}
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