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Fast Unified Memory

Provides a high-performance unified memory combining file-based OpenClaw storage with semantic vector search using local Ollama embeddings for fast, private...
提供高性能统一内存,融合基于文件的OpenClaw存储与语义向量搜索,使用本地Ollama嵌入实现快速、私密的...
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数据分析 clawhub v1.0.1 1 版本 99870.1 Key: 无需
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#fast#latest#memory#ollama

概述

Skill: Fast Unified Memory

A high-performance unified memory system that integrates OpenClaw memory with semantic memory storage using Ollama's nomic-embed-text model for ultra-fast embeddings.

Overview

This skill provides a unified memory layer that combines:

  • OpenClaw Memory: Standard file-based memory storage
  • Semantic Memory: Vector-based memory using Ollama embeddings

Features

  • Ultra-fast: ~130ms for combined search (embedding ~40ms + search ~90ms)
  • 🔒 Private: All processing done locally via Ollama
  • 💰 Free: No API costs - uses local Ollama instance
  • 🧠 Semantic: Uses nomic-embed-text for intelligent similarity matching

Requirements

  • Ollama installed and running
  • nomic-embed-text model pulled: ollama pull nomic-embed-text

Installation

# Install Ollama first
curl -fsSL https://ollama.ai/install.sh | sh

# Pull the embedding model
ollama pull nomic-embed-text

# Start Ollama
ollama serve

Usage

Commands

# Search both memory systems
node fast-unified-memory.js search "your query"

# Add a memory
node fast-unified-memory.js add "User prefers concise responses"

# List all memories
node fast-unified-memory.js list

# Show system stats
node fast-unified-memory.js stats

Architecture

┌─────────────────────────────────────────────┐
│           FAST UNIFIED MEMORY                │
│                                             │
│  ┌─────────────┐    ┌─────────────┐        │
│  │   OpenClaw  │    │   Semantic  │        │
│  │   Memory    │    │   Memory    │        │
│  │ (files)     │    │  (vectors) │        │
│  └─────────────┘    └─────────────┘        │
│           ↓                  ↓              │
│    [Keyword Match]   [Cosine Similarity]   │
│                                             │
│        Unified Results (ranked)             │
└─────────────────────────────────────────────┘

Performance

MetricValue
---------------
Embedding generation~40ms
Vector search~50ms
File search~40ms
Total search~130ms

Configuration

The skill uses these defaults:

  • Ollama URL: http://localhost:11434
  • Embedding model: nomic-embed-text
  • Memory storage: ~/.mem0/fast-store.json
  • OpenClaw memory: ~/.openclaw/workspace/memory/

Files

  • fast-unified-memory.js - Main CLI tool
  • SKILL.md - This documentation

Troubleshooting

Ollama not running:

ollama serve

Model not found:

ollama pull nomic-embed-text

Port conflict:

The skill assumes Ollama is on port 11434. Update the OLLAMA_URL constant if using a different port.

License

MIT

版本历史

共 1 个版本

  • v1.0.1 当前
    2026-03-30 06:33 安全 安全

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安全,无风险
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腾讯云安全 (Sanbu)

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