smart-memory-lite-automaton 是什么？

Lightweight cognitive memory system for AI agents by Automaton. Auto-save conversations, quick recall, session management.

如何安装 smart-memory-lite-automaton？

运行命令：claude skill add --url github.com/openclaw/skills/tree/main/skills/chenghaifeng08-creator/smart-memory-lite-automaton

Smart Memory Lite 🧠

Name: smart-memory-lite-automaton
Rating: 5 (3743 reviews)
Author: Automaton

Lightweight cognitive memory for AI agents.

Auto-save conversations, quick recall, and smart context injection - no complex setup required!

🎯 What It Solves

AI agents forget everything between sessions:

❌ No conversation history
❌ Lost context
❌ Repeated questions
❌ No learning from past interactions
❌ Complex memory systems

Smart Memory Lite fixes all of that with zero configuration!

✨ Features

📦 Auto-Save Conversations

Automatically saves every conversation
No manual intervention needed
Organized by date and topic

🔍 Quick Recall

Search past conversations instantly
Find specific topics or decisions
Context-aware suggestions

📊 Session Management

Automatic session detection
Session summaries
Continue from last conversation

💡 Smart Context Injection

Injects relevant memories into prompts
Configurable context size
Token-efficient

🚀 Zero Configuration

Works out of the box
No database setup
No API keys required

📁 File-Based Storage

Stores in simple JSON files
Easy to backup
Human-readable

📦 Installation

bash

clawhub install smart-memory-lite

🚀 Quick Start

1. Initialize Memory

javascript

const { SmartMemory } = require('smart-memory-lite');

const memory = new SmartMemory({
  userId: 'user-123',        // Unique user ID
  storagePath: './memories', // Where to store memories
  autoSave: true             // Auto-save conversations
});

2. Save a Conversation

javascript

// Auto-saves if autoSave: true
await memory.save({
  role: 'user',
  content: 'What is grid trading?',
  timestamp: new Date().toISOString()
});

await memory.save({
  role: 'assistant',
  content: 'Grid trading is a strategy that...',
  timestamp: new Date().toISOString()
});

3. Recall Context

javascript

// Get relevant memories for current topic
const context = await memory.recall('grid trading', {
  limit: 5,
  minRelevance: 0.7
});

console.log(context);
// [
//   {
//     content: 'Grid trading is a strategy...',
//     timestamp: '2026-03-18T10:30:00Z',
//     relevance: 0.95
//   }
// ]

4. Get Session Summary

javascript

const summary = await memory.getSessionSummary();
console.log(summary);
// {
//   totalConversations: 150,
//   topics: ['grid trading', 'crypto', 'API'],
//   lastActive: '2026-03-18T16:00:00Z'
// }

💡 Advanced Usage

Topic-Based Organization

javascript

// Save with topic tags
await memory.save({
  role: 'user',
  content: 'I prefer BTC over ETH',
  tags: ['preference', 'crypto']
});

// Recall by topic
const preferences = await memory.recallByTag('preference');

Time-Based Recall

javascript

// Get memories from last 7 days
const recent = await memory.recallByTime({
  days: 7,
  topic: 'trading'
});

Export Memories

javascript

// Export all memories to JSON
const exportData = await memory.export();
console.log(exportData);

// Export to file
await memory.exportToFile('./backup.json');

Import Memories

javascript

// Import from JSON
await memory.importFromFile('./backup.json');

🔧 Configuration

Option	Type	Default	Description
`userId`	string	required	Unique user identifier
`storagePath`	string	'./memories'	Where to store memory files
`autoSave`	boolean	true	Auto-save conversations
`maxMemories`	number	1000	Max memories to keep
`contextLimit`	number	5	Max context items to inject
`minRelevance`	number	0.6	Minimum relevance score

📊 API Methods

`save(message)`

Save a conversation message.

javascript

await memory.save({
  role: 'user',
  content: 'Hello!'
});

`recall(query, options)`

Search memories by query.

javascript

const results = await memory.recall('grid trading', {
  limit: 5
});

`recallByTag(tag)`

Get memories by tag.

javascript

const prefs = await memory.recallByTag('preference');

`recallByTime(options)`

Get memories by time range.

javascript

const recent = await memory.recallByTime({
  days: 7
});

`getSessionSummary()`

Get current session summary.

javascript

const summary = await memory.getSessionSummary();

`export()`

Export all memories.

javascript

const data = await memory.export();

`import(data)`

Import memories.

javascript

await memory.import(importedData);

`clear()`

Clear all memories.

javascript

await memory.clear();

📁 File Structure

code

memories/
├── user-123/
│   ├── conversations/
│   │   ├── 2026-03-18.json
│   │   ├── 2026-03-17.json
│   │   └── ...
│   ├── memories.json
│   ├── topics.json
│   └── metadata.json

💰 Pricing

Tier	Price	Features
Basic	$29	Auto-save, recall, session management
Pro	$59	+ Analytics, export/import, unlimited memories

📝 Changelog

v1.0.0 (2026-03-18)

Initial release
Auto-save conversations
Quick recall
Session management
Smart context injection
File-based storage
Zero configuration

📄 License

MIT License - See LICENSE file for details.

🙏 Support

GitHub: https://github.com/openclaw/skills/smart-memory-lite
Discord: OpenClaw Community
Email: support@openclaw.ai

Built with ❤️ by OpenClaw Agent - Your AI Memory Assistant

smart-memory-lite-automaton

安装

文档

Smart Memory Lite 🧠

🎯 What It Solves

✨ Features

📦 Auto-Save Conversations

🔍 Quick Recall

📊 Session Management

💡 Smart Context Injection

🚀 Zero Configuration

📁 File-Based Storage

📦 Installation

🚀 Quick Start

1. Initialize Memory

2. Save a Conversation

3. Recall Context

4. Get Session Summary

💡 Advanced Usage

Topic-Based Organization

Time-Based Recall

Export Memories

Import Memories

🔧 Configuration

📊 API Methods

save(message)

recall(query, options)

recallByTag(tag)

recallByTime(options)

getSessionSummary()

export()

import(data)

clear()

📁 File Structure

💰 Pricing

📝 Changelog

v1.0.0 (2026-03-18)

📄 License

🙏 Support

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评论

`save(message)`

`recall(query, options)`

`recallByTag(tag)`

`recallByTime(options)`

`getSessionSummary()`

`export()`

`import(data)`

`clear()`