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Google Vertex AI Memory Bank

该 Skill 用于在 OpenClaw 中安装并配置 Vertex AI Memory Bank 插件,实现持久化、跨会话和跨代理记忆。它提供自动召回、自动记录、工作区文件同步及记忆管理 CLI,并说明 GCP、Node.js 环境和 openclaw.json 配置步骤。

shubhamsaboo
shubhamsaboo
热度 83.91
最近更新 2026-05-17 14:51:20
分类:知识依赖:代码执行 / 读写文件 / 第三方 API应用场景:笔记整理 / 工作流 / API 集成

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add vertexai-memory-bank
Metadata
name
vertexai-memorybank
description
Install and configure the OpenClaw Vertex AI Memory Bank plugin for persistent, cross-agent memory. Use when the user wants long-term memory, cross-session recall, or shared memory across agents. Handles GCP setup, plugin installation, and openclaw.json configuration.
license
Apache-2.0
compatibility
Requires Node.js, npm, Google Cloud SDK (gcloud), and a GCP project with Vertex AI enabled.
metadata
{"author":"Shubhamsaboo","version":"1.0.0","repository":"https://github.com/Shubhamsaboo/openclaw-vertexai-memorybank"}

Vertex AI Memory Bank Plugin

Give your OpenClaw agent persistent, cross-agent memory powered by Google's Vertex AI Memory Bank.

What This Does

After setup, your agent will:

  • Auto-recall: Before each turn, relevant memories are retrieved and injected into context
  • Auto-capture: After each turn, facts are extracted and stored automatically
  • File sync: Workspace files (MEMORY.md, USER.md, SOUL.md) sync to Memory Bank with hash tracking
  • Cross-agent: Tell one agent something, all agents remember it

Prerequisites

Before running the setup script, ensure:

  1. Google Cloud SDK installed and authenticated (gcloud auth application-default login)
  2. A GCP project with billing enabled
  3. Vertex AI API enabled on the project
  4. Node.js 18+ and npm installed

If the user doesn't have these, help them set up each one.

Installation

Run the setup script:

bash scripts/setup.sh

This script will:

  1. Check for required tools (gcloud, npm, node)
  2. Prompt for GCP project ID and region
  3. Create a Vertex AI Agent Engine reasoning engine (Memory Bank instance)
  4. Install the npm plugin package
  5. Add the plugin configuration to openclaw.json
  6. Restart the gateway to load the plugin

Manual Installation

If the script doesn't work for your environment, follow these steps:

Step 1: Create a Memory Bank Instance

# Set your project
gcloud config set project YOUR_PROJECT_ID

# Create a reasoning engine for Memory Bank
curl -X POST \
  "https://REGION-aiplatform.googleapis.com/v1beta1/projects/YOUR_PROJECT_ID/locations/REGION/reasoningEngines" \
  -H "Authorization: Bearer $(gcloud auth print-access-token)" \
  -H "Content-Type: application/json" \
  -d '{"display_name": "openclaw-memory-bank"}'

Note the reasoning engine ID from the response.

Step 2: Install the Plugin

cd /path/to/openclaw-vertex-memorybank
npm install
npm run build

Step 3: Configure openclaw.json

Add to your openclaw.json under plugins:

{
  "plugins": {
    "openclaw-vertex-memorybank": {
      "enabled": true,
      "path": "/path/to/openclaw-vertex-memorybank",
      "config": {
        "projectId": "YOUR_PROJECT_ID",
        "location": "us-central1",
        "reasoningEngineId": "YOUR_REASONING_ENGINE_ID"
      }
    }
  }
}

Step 4: Restart

openclaw gateway restart

Configuration Options

Option Default Description
projectId required GCP project ID or number
location required GCP region (e.g. us-central1)
reasoningEngineId required Agent Engine reasoning engine ID
autoRecall true Retrieve memories before each turn
autoCapture true Store memories after each turn
autoSyncFiles true Sync workspace .md files to Memory Bank
autoSyncTopics true Auto-configure memory topics at startup
topK 10 Max memories to retrieve per query
perspective "third" Memory perspective (first or third person)
backgroundGenerate true Fire-and-forget memory generation
ttlSeconds none Auto-expire memories after N seconds

Verifying It Works

After installation, check the gateway log:

tail -f ~/.openclaw/logs/gateway.log | grep memory

You should see:

  • [memory-vertex] synced N topics on startup
  • [memory-vertex] recall: N memories on each turn
  • [memory-vertex] capture fired (bg) after each turn

CLI Commands

The plugin adds these commands:

  • memorybank-search <query> - Search your memories
  • memorybank-remember <fact> - Store a specific fact
  • memorybank-forget <memory_id> - Delete a memory
  • memorybank-sync - Force sync workspace files
  • memorybank-status - Check plugin status
  • memorybank-list - List all stored memories

Troubleshooting

  • "401 Unauthorized": Run gcloud auth application-default login
  • "Memory Bank not found": Check reasoningEngineId matches your instance
  • No memories recalled: Check topK and maxDistance settings. Try memorybank-search to verify memories exist
  • High token usage: Reduce topK or set introspection: "off" to remove similarity scores

Source

Full source code and documentation: https://github.com/Shubhamsaboo/openclaw-vertexai-memorybank